China's cotton production has shown a concentration to the advantageous regions in recent years. Based on the relevant data of cotton production in China, the study measures the cotton production agglomeration levels of 16 major cotton-producing provinces from 1978 to 2020, summarizes the spatiotemporal evolution characteristics of cotton production agglomeration, and analyzes the factors influencing cotton production agglomeration using spatial econometric models. The results indicate that: Firstly, since the opening-up and reform, China's cotton production agglomeration levels have shown an overall upward trend, exhibiting periodic dynamic changes over time, and the spatial pattern reveals a dynamic regional gradient. Secondly, there is spatial correlation among the production scales of cotton in different provinces, with a trend resembling a "U" shape, and the agglomeration form shows a low-level convergence. Thirdly, technological level, policies, substitute industrial products and foreign trade are identified as important factors. The cotton production in each province is spatially correlated through these factors, and there is also a presence of spillover effects. In conclusion, the government should prioritize considerations of various influencing factors to formulate tailored support policies, promote large-scale production to enhance technological levels, and focus on policies aimed at improving the quality of cotton.

Global positioning systems (GPS) have recently been shown to reliably quantify the spatiotemporal characteristics of Polo, with the physiological demands of Polo play at low and high goal levels also investigated. This study aimed to describe the spatiotemporal demands of Polo across 0 – 24 goal levels. A player worn GPS unit was used to quantify distance, speed and high intensity activities performed. Data was divided into chukkas and five equine-based speed zones, grouped per cumulative player handicap and assessed using standardised mean differences. Average distance and speed per chukka increased in accordance with cumulative player handicap, with the magnitude of differences being Trivial – Large and Trivial – Very Large, respectively. Differences between time spent in speed zones 4 and 5 show a linear increase in magnitude, when comparing 0 goal Polo to all other levels of play (Small – Very Large; 6 – 24 goals, respectively). High intensity activities predominantly shared this trend, displaying Trivial – Large differences between levels. These findings highlight the increasingly demanding cardiovascular, anaerobic and speed-based needs of Polo ponies as playing level increases. Strategies such as high intensity interval training, maximal speed work and aerobic conditioning may be warranted to facilitate this development and improve pony welfare and performance.

In addition to their importance in statistical thermodynamics, probabilistic entropy measurements are crucial for understanding and analyzing complex systems, with diverse applications in time series and one-dimensional profiles. However, extending these methods to two- and three-dimensional data still requires further development. In this study, we present a new method to classify spatiotemporal processes based on entropy measurements. To test and validate the method, we selected four classes of similar processes related to the evolution of random patterns: dynamic colored noises ((i)~white and (ii)~red); (iii)~weak turbulence from reaction-diffusion; (iv)~hydrodynamic fully developed turbulence, and (v)~plasma turbulence from MHD. Considering seven possible ways to measure entropy from a matrix, we present the method as a parameter space composed of the two best separating measures of the five selected classes. The results highlight better combined performance of Shannon Permutation Entropy ($S^p_H$) and a new approach based on Tsallis Spectral Permutation Entropy ($S^s_q$). Notably, our observations reveal the segregation of reaction terms in this $S^p_H \times S^s_q$ space, a result that identifies specific sectors for each class of dynamic process, and can be used to train machine learning models for automatic classification of complex spatiotemporal patterns.

This study aims to assess the spatiotemporal characteristics of meteorological droughts in Bangladesh during 1981–2015 using the Effective Drought Index (EDI). Monthly precipitation data for 36 years (1980-2015) obtained from 27 metrological stations, were used in this study. The EDI performance was evaluated for four sub-regions over the country through comparisons with historical drought records identified at the regional scale. Analysis at a regional level showed that EDI could reasonably detect the drought years/events during the study period. The study also revealed that the overall drought severity had increased during the past 35 y; the most significant increasing trend was observed in the central region. The characteristics (severity and duration) of drought were also analysed in terms of spatiotemporal evolution of the frequency of drought events. It was found that the western and central regions of the country are comparatively more vulnerable to drought. Moreover, the southwestern region is more prone to extreme drought, whereas the central region is more prone to severe droughts. In addition, the central region was more prone to extra-long-term droughts, while the coastal areas in the southwestern as well as in the central and north-western region were more prone to long-term droughts. The frequency of droughts in all categories significantly increased during the last quinquennial period (2011 to 2015). The seasonal analysis showed that the north-western areas were prone to extreme droughts during the Kharif (wet) and Rabi (dry) seasons. The central and northern regions were affected by recurring severe droughts in all cropping seasons. Further, the most significant increasing trend of the drought-affected area was observed within the central region, especially during the pre-monsoon (March-May) season. The results of this study can aid policymakers in the development of drought mitigation strategies in the future.

Habitat quality has great significance for regional ecological conservation and human welfare. In this study, we evaluated the spatial and temporal characteristics of land use and habitat quality in the temperate desert sub-region of Ordos Plateau using patch-generating land use simulation (PLUS) and integrated valuation of ecosystem services and trade-offs (InVEST) models. From 2000 to 2020, the areas of grassland, cropland, and unused land in the study area increased significantly; the areas of water bodies and woodland increased slightly; and the area of wasteland decreased significantly. Moreover, the habitat quality in the temperate desert subzone of the Ordos Plateau showed a trend of increasing and then decreasing from 2000 to 2020. The areas of lower and low habitat quality first decreased and then increased, and the overall area decreased over time. Conversely, the areas of high and higher habitat quality initially increased and then decreased, and the overall area increased over time. The area of medium habitat quality first decreased and then increased, although the overall change was minimal. Based on the PLUS model, the habitat quality of the study area in 2025 predicted under the natural development scenario was compared with that predicted under the ecological conservation scenario, showing higher habitat quality and lower habitat degradation under the ecological conservation development scenario. These results can be used to provide a scientific basis and decision reference for the sustainable use of land resources and high-quality socio-economic development in the temperate desert sub-region of the Ordos Plateau.

Drought severity still remains a serious concern across sub-Saharan Africa (SSA) due to the destructive impact on multiple sectors of our society The interannual variability and trends in the changes of self-calibrated Palmer Drought Severity Index based on Penman–Monteith (scPDSIPM) and Thornthwaite (scPDSITH) methods for potential evapotranspiration (PET), precipitation (P) and normalized difference vegetation index (NDVI) anomalies, and sea surface temperature (SST) anomaly were investigated through statistical analysis of modelled and remote sensing data. It is shown that scPDSIPM and scPDSITH differed in the representation of drought characteristics over SSA. The scPDSI and remotely-sensed-based anomalies of P and NDVI showed wetting and drying trends over the period 1980-2012. The trend analysis showed increased drought events in the semi-arid and arid regions of SSA over the same period. A correlation analysis reveals a strong relationship between scPDSI variability and P, and NDVI anomalies for monsoon and pre-monsoon seasons. The correlation analysis of scPDSI variability with SST anomalies indicates significant positive and negative relationships, respectively. This study has demonstrated the applicability of multiple data sources for drought assessment and provides useful information for regional drought predictability and mitigation strategies.

Climate change is challenging the agricultural sector worldwide. The pressure exerted by the altered thermal conditions drives the zonal shift for various cultivations. This study presents the multiyear analysis of the Growing Degree Days (GDD) index over the Northern Mediterranean Basin (NMB), focused on the high-value vine cultivation derived from the E-OBS dataset. To handle this extensive environmental dataset, R-language scripts and packages were applied, along with the capabilities of the GIS software. The investigated time period spans from 1969 to 2018, and the performed analysis indicates a broad shift/expansion in areas of GDD exceeding 2000 heat units. The extracted results specify the viticultural areas where the GDD index surpasses the suitable values for vine cultivation, owing to the increase of the thermal stress risk. In addition to mapping areas with GDD ≥ 2000, spatial calculations of the surface of areas meeting this criterion per country in the study area were made. In the northern parts of the NMB, the rise of the GDD index values indicates the establishment of vine plantations in the future.

Background: The bacterium Capnocytophaga spp. is a part of the oral microbiome of dogs, which has zoonotic potential. This study aimed to assess factors that influence the prevalence of Capnocytophaga cynodegmi and Capnocytophaga canimorsus in Wrocaw’s dog population. Methods: Molecular detection (PCR) involved 105 swabs, examining parameters such as oral cavity condition, underlying health issues, recent antibiotics, age, medications, material collection, and dog chews. Results: The study highlighted significant associations between the presence of Capnocytophaga cynodegmi and oral cavity condition, material collection method, and use of dog’s chews. Conclusions: Correlations obtained in this study between the oral health of Wroclaw's dog population and the presence of Capnocytophaga cynodegmi suggest its significance in the oral microbiome of dogs. Limitations, including the small sample size, highlight the need for more research to comprehensively understand additional factors that affect the prevalence of Capnocytophaga spp. in dogs

Historic expeditions are events that are flavored by exploratory, scientific, military or geographic characteristics. Such events are often documented in literature, journey notes or personal diaries. A typical historic expedition involves multiple site visits and their descriptions contain spatiotemporal and attributive contexts. Expeditions involve movements in space that can be represented by triplet features (location, time and description). However, such features are implicit and innate parts of textual documents. Extracting the geospatial information from these documents requires understanding the contextualized entities in the text. To this end, we developed a semi-automated framework that has multiple Information Retrieval and Natural Language Processing components to extract the spatiotemporal information from a two-volumes historic expedition gazetteer. Our framework has three basic components, namely, the Text Preprocessor, the Gazetteer Processing Machine and the JAPE (Java Annotation Pattern Engine) Transducer. We used the Brazilian Ornithological Gazetteer as an experimental dataset and extracted the spatial and temporal entities from entries that refer to three expeditioners’ site visits and mapped the trajectory of each expedition using the extracted information. Finally, one of the mapped trajectories was manually compared with a historical reference map of that expedition to assess the reliability of our framework. The reference map was manually prepared in previous research work by others.

Quantifying the landscape pattern change can effectively demonstrate the ecological progresses and the consequences of urbanization. Based on remotely sensed land cover data in 1994, 2000, 2006 and a gradient analysis with landscape metrics at landscape- and class- level, we attempted to characterize the individual and entire landscape patterns of Shanghai metropolitan during the rapid urbanization. We highlighted that a roadscape transect approach that combined the buffer zone method and the transect-based approach was introduced to describe the urban-rural patterns of agricultural, residential, green, industrial, and public facilities land along the railway route. Our results of landscape metrics showed significant spatiotemporal patterns and gradient variations along the transect. The urban growth pattern in two time spans conform to the hypothesis for diffusion–coalescence processes, implying that the railway is adaptive as a gradient element to analyze the landscape patterns with urbanization. As the natural landscape was replaced by urban landscape gradually, the urban fringe expanded radically. The results also showed that the desakota region expanded its extent widely. Satellite towns witnessed the continual transformation from the predominantly rural landscape to peri-urban landscape. Furthermore, the gap between urban and rural areas remained large especially in public service. More reasonable urban plans and land use policies should push to make more of an effort to transition from the urban-rural separation to coordinated urban-rural development. This study is a meaningful trial in demonstrating a new form of urban–rural transects to study the landscape change of large cities from a strategic viewpoint. By combining gradient analysis with landscape metrics, we addressed the process of urbanization both spatially and temporally, and provided a more quantitative approach to urban studies.

The purpose of the study is to establish compliance of the design of the modernized car with the requirements for safe operation. An option has been proposed for upgrading a passenger wagon to a Mobile Diagnostic Complex for transporting a combined vehicle equipped with appropriate flaw detection equipment intended for rail diagnostics. The authors have established the most optimal option for locating the diagnostic vehicle on board the Mobile Diagnostic Complex (MDC) wagon, taking into account the additional load from the vehicle. To achieve this goal, the article developed a three-dimensional model of the supporting structure of the wagon body, proposed a methodology and presented the results of a study of the stress-strain state of the wagon body, taking into account the additional weight of the wagon. The article develops a methodology for studying the natural frequencies of vibrations of the wagon body and develops a three-dimensional model of the wagon for calculating dynamic indicators in the Universal Mechanism software package. Taking into account the previously carried out strength calculations, as well as in order to maintain the factory life cycle indicators of the supporting structure of the wagon body, it is recommended to use the model in the first version.

Spectral characteristics of CDOM in water column are a key parameter for bio-optical modeling. Knowledge of CDOM optical properties and spatial discrepancy based on the relationship between water quality and spectral parameters in Yinma River watershed with in situ data collected highly-polluted waters are exhibited in this study. Seasonal field data sets collected over a period of 2 months in 2015 in Yinma River Watershed. Based on the comprehensive index method, the riverine waters showed serious contamination, especially the COD, Fe, Mn, Hg and DO were out of range contamination warning. Dissolved organic carbon (DOC) and total suspended matter (TSM) with prominent non-homogenizing were significantly high in the riverine waters, but chlorophyll-a (Chl-a) was opposite. Ternary phase diagram showed that non-algal paritcles absorption played an important role in total non-water light absorption (>50%) in most sampling locations, and mean contribution of CDOM were 13% and 22% in summer and autumn respectively. Analysis of ratio of absorption at 250-365 nm (E_250:365) and spectral slope (S_275-295) indicated that CDOM had higher aromaticity and molecular weight in autumn than in summer, is consistent with the results of water quality and relative contribution. Redundancy analysis (RDA) indicated that the environmental variables OSM had a strong correlation with CDOM absorption, followed by heavy metal, e.g., Mn, Hg and Cr⁶⁺. However, for the specific UV absorbance (SUVA₂₅₄), the seasonal values showed opposite results compared with the reported literature. The potential reasons were the more UDOM (uncolored Dissolved Organic Matter) from human source (wastewater effluent) existed in waters. Terrigenous inputs simultaneously are in relation to the a_CDOM(440)-DOC relationship with the correlation coefficient was 0.90 in summer (2-tailed, p<0.01), and 0.58 in autumn (2-tailed, p<0.05). Spatial distribution of CDOM parameters exhibited that the downstream regions focused on dry land have high CDOM molecular weight and aromatic hydrocarbon. Partial sampling locations around the cities or countries generally showed abnormal values due to terrigenous inputs. As a bio-optical model parameter, spectral characteristic of CDOM is helpful in adjusting the derived algorithms in highly-polluted environments. The study on organic carbon and pollutants in highly-polluted waters had an important contribution to global carbon balance estimation and water environment protection.

Soil organic matter (SOM) is important for the global carbon cycle, and hyperspectral remote sensing has proven a promising method for fast SOM content estimation. However, soil physical properties significantly affect the sensitivity of satellite hyperspectral imaging to SOM, leading to poor generalization ability of the estimation model. This study aims to improve the spatiotemporal transferability of the SOM prediction model by alleviating the coupling effect of soil physical properties on the spectra. Based on satellite hyperspectral images and soil physical variables, including soil moisture (SM), soil surface roughness (root mean squared height, RMSH), and soil bulk weight (SBW), a soil spectral correction strategy was established based on the information unmixing method. Two important grain-producing areas in Northeast China were selected as study areas to verify the performance and transferability of the spectral correction model and SOM content prediction model. The results showed that soil spectral corrections based on fourth-order polynomials and the XG-Boost algorithm had excellent accuracy and generalization ability, with residual predictive deviations (RPD) exceeding 1.4 in almost all bands. In addition, when the soil spectral correction strategy was adopted, the accuracy of the SOM prediction model and the generalization ability after model migration were significantly improved. The SOM prediction accuracy based on the XG-Boost corrected spectrum was the highest, with a coefficient of determination (R2) of 0.76, root mean square error (RMSE) of 5.74 g/kg, and RPD of 1.68. The prediction accuracy, R2, RMSE, and RPD of the model after migration were 0.72, 6.71 g/kg, and 1.53, respectively. Compared with the direct migration prediction of the model, adopting the soil spectral correction strategy based on fourth-order polynomials and XG-Boost reduced the RMSE of the SOM prediction results by 57.90% and 60.27%, respectively. The performance comparison highlighted the advantages of considering soil physical properties in regional-scale SOM prediction.

Safe water is a global public health concern amid increasing scarcity and pollution. Bottled water production and consumption contribute to these problems. This study examines tap water consumption in Italy, assessing associated sociodemographic factors and related health outcomes such as obesity and self-perceived health status. Data from the Italian National Statistics Institute's "Aspects of daily life" survey (N=45,597) were analyzed. Covariates included education, age, gender, economic status, region, concerns about waste and climate change, consumption of carbonated drinks excluding water, alcohol consumption, consumption of vegetables, consumption of snacks, body mass index, and self-perceived health status. Bivariate analyses and mixed-effect logistic regression models explored the associations. People who drink tap water were 19,674 with a higher prevalence in people aged 45 to 59 old, people with a graduate/post-graduate degree diploma, with optimal economic resources, and concerned about waste production and climate change, coming from the North-East regions of Italy. Underweight people showed a higher prevalence of TW assumption as well as those who drink less than occasionally carbonated drinks, drink alcohol, consume vegetables more than once a day, and snacks less than once a week with a satisfying level perceived health status. Regressions showed that all age classes are less likely to drink tap water than people younger than 20 years old. The category with “inadequate” economic resources is more likely to consume tap water. Low educational classes show a low likelihood of consuming tap water as well as Islands. A concern about waste production and climate change is associated with an increased likelihood of assuming tap water. Tap water consumption was negatively associate with obesity but not with a satisfactory Self-perceived health status. Insights from this study can inform public health strategies.

As a new plant slope protection technology, living stumps can effectively improve slope stability. The current study attemptes to investigate the mechanical characteristics of the root system of living stumps and their reinforcement mechanism on slopes by carrying out a three-dimensional living stump slope modeling test. Using ABS materials, a 3D model of a living elm stump was created by 3D printing and a slope model test was carried out. The reinforcement mechanism of the living stump was studied through a combination of model testing and numerical simulation. The results indicate that, due to the presence of living stumps in the lower and middle parts of the slope, the maximum shear stress area of the soil moved to a deeper direction. The stress state of the soil around the living stump was effectively improved due to the existence of the lateral root system.Living stumps in the lower part of the slope cross the potential sliding surface and transferred the soil shear stress gradually to the root system through root-soil interaction. Moreover, the tap roots and lateral roots of living stumps form a robust spatial structure that bears the shear stress of soil together, thus increasing the stability of the slope.

Recently, volatile organic compounds (VOCs) have been shown to act as precursors of secondary organic particles that react with ultraviolet rays in the atmosphere and contribute to photochemical smog, global warming, odor, and human health risks, highlighting the importance of VOC management. In this study, we measured VOC concentrations in various contexts including industrial and residential areas of Bucheon, Korea, through mobile laboratory and proton-transfer-reaction time-of-flight mass spectrometry methods to determine winter VOC concentrations, visualized the data based on spatial information, and used the results to develop an air quality management plan. For this purpose, global information system (GIS)-based air quality data and various environmental variables were comprehensively reviewed to assess spatial and temporal concentrations in three dimensions rather than in tables and graphs. Among VOCs, the levels of toluene, methanol, and n+i-butene were relatively high, with average concentrations of 48.3 ± 67.2, 34.4 ± 102.7, and 32.6 ± 57.7 ppb, respectively, at the end of the working day. The highest concentrations occurred near the Ojeong Industrial Complex. Mobile pollution sources are also a major driver of VOCs, highlighting the necessity of comprehensively reviewing traffic variables such as road level, estimated traffic volume, and average speed when identifying hotspots of air pollution. GIS-based visualization analysis techniques will improve the efficiency of air quality management.

Water quality assessment in pastoral of Tibetan Plateau, which is water sources for about 40% of world's population and the runoff-yield area of Yellow rivers, is very important. In this paper, Xiahe county which belongs to Tibetan Plateau pastoral was investigated. Six parameters(via, chloride, COD, ammonia nitrogen, nitrate, fluoride, sulfate) were selected to assess the water quality and health degree by using fuzzy comprehensive evaluation methods. The hydrochemical type in surface water was of HCO3--Mg2+-Ca2+ type. The cations and anions in surface water were mainly from weathering and dissolution of carbonate rock. Results showed that the water quality in all 69 sampling sites was all of class Ⅰ. The integrated health degree reached more than 0.85 and the health rate were 100%. Although ammonia nitrogen was regarded as the main contamination factor, but it had a little effect on the entire body of water. Overall, the surface water qualities of most samples in Xiahe County was good condition.

More than 20 years after the discovery of the first anelloviruses (AVs), they still remain a mysterious group of viruses. To date, there is no clear understanding of their impact on the host organism, although information is emerging about their participation in various pathologies. However, it is well known that AVs are an important component of the human virome. In the current study we assessed the abundance of AVs in viromes from four nasal and pharyngeal samples from children with respiratory symptoms using a metagenomic approach. It is worth noting that three patients had known respiratory viruses and one did not have any. Regarding AVs, they were detected in all samples, namely Torque teno mini virus (TTMV). The greatest abundance and diversity of AVs (Torque teno virus (TTV), TTMV and Torque teno midi virus (TTMDV)) were shown in a diseased patient with an absence of respiratory viruses, which may indicate the potential involvement of AVs in the maintenance of respiratory symptoms. An activated immune system to combat the main pathogens, against the background of which the number of AVs decreases, is discussed as a possible reason for the reduced diversity of anellome in other patients. We also compared the results of the metagenomic approach and qPCR for major respiratory viruses, which were in agreement. In addition, metagenomic sequencing made it possible to obtain additional data on viral genomes in order to establish their taxonomic identification and characterize individual viral profiles in patients from the Siberian part of Russia.

Background: Diabetes mellitus (DM) and osteoporosis are two of the most widespread metabolic disease in the world. The aim of this study is to investigate the prevalence of DM among patients affected by osteoporosis and fragility fractures, and to search differences in clinical features. Methods: 713 patients belonging to CTO Bone Unit because of osteoporosis and fragility fractures were divided into two groups, according to the diagnosis of DM. The clinical and bone characteristics of patients were compared. Results: Prevalence of DM was 10.8%. When compared to patients without DM, the median age at the time of first fracture was similar (72 years ± 14 IQR vs 71 years ± 12 IQR); prevalence of combination of vertebral and hip fractures was higher (p=0.039), as well as prevalence of males, although not significantly (p=0.051). Bone mineral density (BMD) at all sites was higher in DM group; Trabecular Bone Score (TBS), instead, was significantly lower (p&lt;0.001). Conclusions: Patients with fragility fractures and DM more frequently show combination of major fractures with higher BMD levels. In these patients, TBS could be a better indicator of bone health than BMD and therefore should be used as a diagnostic tool in clinical practice.

The objective of this study was to investigate the concentration and spatial distribution patterns of six potentially toxic heavy metal elements (Mn, Zn, Cr, Pb, Cu and Ni) in bus station dusts in the Xifeng district of Gansu province, NW China. The contents were analyzed for Mn, Zn, Cr, Pb, Cu and Ni by using S8 TIGER Brochures wavelength dispersive X-ray fluorescence spectrometry. Geoaccumulation index (Igeo ), enrichment factor (EF), pollution index (PI) and integrated pollution index(IPI) were calculated to evaluate the heavy metal contamination level of bus station dusts. The results indicate that, in comparison with the background values of local soil, bus station dusts in Xifeng have elevated metal concentrations as a whole. The concentrations of heavy metals investigated in this paper are compared with the reported data of other cities. The results show that the arithmetic means of Mn, Zn, Cr, Pb, Cu and Ni are 440.8, 137.9, 60.0, 42.8, 33.5 and 19.8mg kg−1 respectively. The mean values of Igeo reveal the order of Ni<Mn<Cr<Cu<Zn<Pb. The high Igeo and EF for Cu, Zn and Pb in bus station dusts indicate that there is a considerable Cu, Zn and Pb pollution, which mainly originate from traffic and industry activities. The Igeo and EF of Ni, Mn and Cr are low and the assessment results indicate an absence of distinct Ni, Mn and Cr pollution in bus station dusts. The assessment results of PI also support Cu, Zn and Pb in bus station dusts presented middle pollution, and IPI indicates heavy metals of bus station dusts polluted seriously.

Introduction: Cleft lip with or without cleft palate (CL/P) is the most common congenital face anomaly in the world of multifactorial etiology. Objective: To determine the prevalence and characteristics of cleft palate. To identify associated risk factors to guide prevention and/or prenatal detection for early intervention and better health outcomes. To assess the rehabilitation protocols after operations in cleft palate. Design: Retrospective descriptive and clinical study. Patients: One hundred and three children with cleft palate treated in the Department of Head and Neck Surgery Clinic for Children and Young Adults, Department of Clinical Pediatrics, University of Warmia and Mazury, were included in the study. Methods: Records evaluation was conducted regarding sex, cleft type, mother occupation, parents education, histories of cleft in any of parents. The data were analyzed using R (R core team 2021) and the ordinal logistic regression analyses. Results: Children of stressed mothers during pregnancy had 9.4 times higher odds of having bilateral cleft. While there was no evidence that children sex, order of birth, and body mass as well as risk of maternal toxicity at work or reporting infections or drugs toxicity had a significant effect on the dependent variable. Conclusions: Children of parents with cleft history and having low educated mothers had higher probability of bilateral cleft palate. Children of stressed mothers during pregnancy had higher odds of having bilateral cleft. In literature, there is a lack of reports about rehabilitation in different operations methods in children with cleft palates.

The degree of ore rock fragmentation of mine blasting is an important index for evaluating the effect of engineering blasting. In order to study the effect of millisecond delayed blasting on the internal fragmentation of the ore rock, LS-DYNA numerical simulation software was used to obtain the damage characteristics of the ore rock in the blasting area using the RHT model. The Mohr-Coulomb strength damage criterion was applied to analyze the internal stress state of the ore rock, and the effects of 25ms, 50ms and 75ms delay time conditions on ore rock fragmentation were studied. The results show that, within a certain range of delay time, the degree of rock fragmentation increases with the increase of delay time. The stress state in the ore rock due to blasting is strengthened with the increase of delay time in the direction of the blast hole, which shows that the stress concentration is strengthened from the excavation face to the interior of the ore rock. The damage and the degree of fragmentation show a characteristic relationship of 25ms＜50ms＜75ms, which is verified by carrying out blasting experiments on site.

ABSTRACT Background: To date, the COVID-19 pandemic has been the foremost health concern for humankind in the new millennia. This paper aims to describe the related hospitalizations in Italy during the first two years of the health emergency. Design and methods: This is a retrospective, population-based study of Italian hospitalizations for patients diagnosed with COVID-19 during the 2020-2021 period, extracted from the National Hospital Discharge Registry. The outcome variables considered include hospital admissions, costs, and length of stay, among other hospitalization-level variables. Costs were estimated through the charges associated with the Diagnosis-Related Group and Major Diagnostic Categories coding system, plus an additional cost attributed to COVID-19 admissions. To these charges was added an extra cost defined by the ministry of health. Results: In Italy, there were 357,354 hospitalizations for COVID-19 attributed to 298,856 patients in 2020 and 399,043 hospitalizations for COVID-19 attributed to 333,447 patients in 2021. COVID-19 patients faced a transfer rate thrice that of other patients. Hospitalizations were concentrated predominantly in the northern regions, particularly in the first year. Hospitalization rates varied by age in a sine wave pattern, peaking in the youngest and oldest age groups, with mortality rates escalating with age— tending to remain below 3% for those under 44 but surging to 40% in individuals over 75. The financial impact of COVID-19 hospitalizations was substantial, with total costs reaching €3.97 billion in 2020 and €4.99 billion in 2021. Costs per admission and per day also rose, from €11,112 and €807 in 2020 to €12,503 and €844 in 2021, respectively. Excluding the added financial burden of COVID-19, costs would have been notably lower. Hospitalizations involving continuous invasive mechanical ventilation were particularly costly (about 24.000 euros x admission), reflecting the significant resources required for these treatments. Conclusion: Implementing a protective pad around the entire health system that leverages networks of family doctors and nurses, connected in real time to the entire health system, can be crucial. Such a network, tasked with monitoring the local epidemiological situation, protecting vulnerable individuals also through telehealth visits, and establishing a triage system for infections in the initial phase, may effectively help in managing virus spread and protecting hospitals from unpredictable waves of admission demand. Strengthening primary health care could be a decisive factor for the future and enhance the system's resilience in facing new challenges.

The partial discharge (PD) event in high voltage insulation releases energy, exerts mechanical pressure, and generates elastic waves. Detecting and locating these PD events through short-duration acoustic pulses is well-established, particularly in gas-insulated systems and oil-insulated transformers. However, its full potential remains untapped in solid insulation systems, where the propagation capability of acoustic pulse and the acoustic reflections pose fundamental challenges to the Acoustic Emission (AE) detection technique. This study investigates the influence of reflections and multiple paths on the propagating acoustic pulse in polymeric insulating materials using a finite element method (FEM) in COMSOL. It was observed that the reflections from the boundary influence the propagating pulse's shape, peak magnitude, and arrival time. An analytical MATLAB model further quantifies the impact of multiple propagation paths on the shape, magnitude, and arrival time of the pulse travelling in a cylinder. Additionally, a Perfect Matched Layer (PML) was implemented in the COMSOL model to eliminate reflections from the boundary, and it revealed that the acoustic pulse magnitude decreases with distance following the inverse square law. In essence, the models aid in measuring how reflections contribute to the observed signals, facilitating the precise identification of the source of the PD event in the tested system.

We developed a novel approach in the field of spatiotemporal modelling, based on the spatialisation of time: the Timescape algorithm. It is especially aimed at sparsely distributed datasets in ecological research, whose spatial and temporal variability is strongly entangled. The algorithm is based on the definition of a spatiotemporal distance that incorporates a causality constraint and that is capable of accommodating the seasonal behaviour of the modelled variable as well. The actual modelling is conducted exploiting any established spatial interpolation technique, substituting the ordinary spatial distance with our Timescape distance, thus sorting, from the same input set of observations, those causally related to each estimated value at a given site and time. The notion of causality is expressed topologically and it has to be tuned for each particular case. The Timescape algorithm originates from the field of stable isotopes spatial modelling (isoscapes), but in principle it can be used to model any real scalar random field distribution.

The River Habitat Survey (RHS) is a method for assessing the conditions of a river channel and valley, taking into account hydromorphological factors, and assessing the degree of naturalness or the degree of anthropogenic alteration within the channel and valley based on physical and landscape data. The hypothesis tested in this study was that the quality of river habitats demonstrated using the RHS should translate into the composition of their fauna. We investigated aquatic bugs (Heteroptera Aquatica), which are a group with considerable dispersal abilities and, at the same time, composed of stenotopic species associated with a particular environment as well as of eurytopic elements inhabiting a wide range of environments (REF). The research was carried out in a small lowland river, the River Krąpiel (north-western Poland) at 6 sites with 43 sub-sites included. Our analyses suggest the RHS method can predict the composition and quality of the aquatic bug fauna inhabiting a given river. Indicators of river habitat quality (HQA and RHQ) will be associated with different habitat types depending on the geographic location and type of river, once indicating habitats associated with the mainstream river and mineral substrate (mountain and small lowland rivers) and at other times habitats covered by vegetation with relatively slow water flow (large and medium lowland rivers). Therefore, RHS may be a good method for estimating the water bug fauna, linking it to the size and character of the river.

Expansion tube is ideal energy absorber which dissipates kinetic energy through plastic deformation and friction. There is an urgent need to understand the influence of key parameter, e.g. semi angle, tube material, and friction coefficient, on the mechanical response and energy absorption characteristics of expansion tube. In the present work, the material properties of the tubes were tested under quasi-static loading condition, and the numerical simulations were carried out by using commercial software ABAQUS. Based on the validated finite element simulation, all the semi angle, tube material, and friction have significant effects on the energy absorption capacity of expansion tube. The expansion tube with high tensile stress of parent material have high energy absorption capacity, while the specific energy absorption is linear with the tensile stress/density of tube material. This work would give a guidance to the structural design and parent materials selection for expansion tubes.

The research on the excavation mechanical properties of underpass tunnels has already had certain results, but fewer of them consider the effects of dynamic and static loads on the excavation mechanical properties of underground tunnels at the same time, especially the lack of research cases of double-line highway tunnels with angled underpasses of existing railway tunnels. In this paper, based on the tunnel project of the new double-line Shiqian Highway Tunnel passing under the Hurong Railway at an oblique angle, the mechanical parameters of the rock body in the cross-tunneling area under the influence of static and dynamic load coupling are obtained by using the disturbance quantification coefficients and the Hoek-Brown criterion based on the method of over-advanced geological prediction and the investigation of the surrounding rock on the palisade face, and the engineering-scale finite element model is constructed and the mechanical characteristics of the excavation in the tunnel of the double-lane highway tunnel passing under the existing railroad under the influence of the static and dynamic loads are analyzed. The results show that: the new tunnel rock movement law for the top of the arch sinking, bottom plate bulging, side wall to move outward, the height and width of the arch and bottom plate arch with the tunnel excavation and increase, the side wall rock displacement effect is smaller; left and right lines of the tunnel disturbed area of the rule of change is similar; the existing tunnel bottom plate displacement is more than the top plate and the left and right side walls by the excavation of the time step influence is larger. Typical profile displacement is mainly determined by the distance from the excavation surface; the new tunnel in the four types of calculation conditions of the rock disturbance angle is the same; the existing tunnel roof and side wall Von Mises stress extreme occurs in the tunnel structure, the bottom plate there are pressure relief and pressure-bearing areas; based on the displacement control criteria, the recommended upper and lower step blasting method.

The Giant Babax, an endemic bird in China and a nationally protected wildlife species of Class Ⅱ, is primarily distributed in southern and southeastern Tibet. To investigate the factors influencing nesting site selection, this study conducted research on nest characteristics and nesting site preferences at four sample sites around Lhasa from March to October 2023y, using systematic search methods, tracking methods, and sampling methods. The research findings are as follows: (1) The average nest depth was (7.70±1.47)cm, nest height was (19.58±2.97)cm, inner diameter was (10.64±1.73)cm, outer diameter was (24.65±4.8)cm, average weight was (162.3±13.5)g, and average nest spacing within the plot was 396.93m. (2) The nests of Giant Babax were predominantly found on vegetation such as Salix longistamina (38%), Hippophae gyantsensis (20%), Rosa sericea Lindl. (14%), and Populus szechuanica Schneid(11%). They showed a preference for artificial secondary forests as nesting sites. (3) Giant Babax exhibited a preference for habitats with robust trees that had high canopies while being distant from houses and roads, but close to water sources; moreover, the canopy of the nesting tree played a crucial role in their choice of nesting sites. (4) The reproductive success rate reached 76%, with key factors affecting it being the canopy coverage of the nesting tree and the number of helpers. These research results provide fundamental data support for population conservation efforts and ecological resource management strategies concerning the Giant Babax.

Populational aging is marked by chronic non-communicable diseases, such as metabolic syndrome (MetS). IL-10 and IL-1β are pleiotropic cytokines with multiple biological effects linked to metabolic disorders. This cross-sectional study assessed 193 participants' IL-10 and IL-1β serum levels regarding their role in developing MetS, clinical characteristics, and their IL1B rs1143627 and IL10 rs1800890 variants' genotype frequencies in a population over 60. IL-10 levels correlated weakly with HDL levels and fat mass and inversely with triglycerides, glucose, glycated hemoglobin, and estimated average blood glucose levels. IL-10 levels were also indirectly influenced by the patient's T2DM duration, lean mass amount, and bone mineral content. Participants with altered HDL, elevated serum glucose, raised HbA1c levels, or those over 80 had reduced serum IL-10 levels compared to those with normal levels or other age groups, respectively. Women also had higher serum IL-10 levels than men. Dissimilarity, IL-1β levels correlated directly only with the number of total leukocytes and segmented neutrophils, showing only significant variations with self-reported alcohol consumption. Our study also found that those with the IL10 AA genotype (lower IL-10 levels) had a significantly higher risk of developing MetS. These findings may help direct future research and more targeted therapeutic approaches in older adults.

Emulsifiers like egg yolk (EY) are necessary for the formation of mayonnaise, which is an oil-in-water type colloid. This study aimed to assess the potential of defatted soybean powder treated with supercritical carbon dioxide (DSF-SC) in enhancing the quality of plant-based may-onnaise as plant-based alternatives gain popularity. This study involved producing DSF-SC and comparing its quality attributes to those of mayonnaise made with varying amounts of control soy flour (CSF), DSF-SC, and EY. It was found that mayonnaise made with DSF-SC, with increased emulsifier quantity, showed better emulsion stability, viscosity, and smaller, more uniform particle size compared with CSF mayonnaise. Additionally, DSF-SC mayonnaise was overall rated higher in sensory evaluation. The addition of approximately 2% DSF-SC positively influenced the emul-sion and sensory properties of the vegan mayonnaise, making DSF-SC a promising plant-based alternative emulsifier for replacing animal ingredients.

Composite fiber materials are superior materials due to their high strength and light weight. Composites reflect the properties of their constituents, which is proportional to the volume fraction of each phase. There are different fiber reinforcement types and each affects it’s flexural, tensile and compression strength. When selecting a composite for a specific application, the forces excreted on the composite must be known in order to determine the reinforcement type. Unidirectional fiber reinforcement will allow very strong load resistance but only in one direction where as a random orientated fiber reinforcement can resist less load but can maintain this quota in all directions. These materials are said to be anisotropic. Certain composite fibers, taking into consideration there weights, are physically stronger than conventional metals. This research deals with the analysis of three composite materials with different reinforcement types, volume fraction and phase content. It was found that material A (glass epoxy) was the strongest in the longitudinal direction with a flexural strength of 534 MPa in the longitudinal and 420 MPa in the transverse direction. The flexural stresses of material B (glass silicone) and material C (glass polyester) where both found in the 120 to 135 MPa range. Differences were due to their differences in matrix composition and reinforcement type.

Eye movements support memory encoding by binding distinct elements of the visual world into coherent representations. However, the role of eye movements in memory retrieval is less clear. We propose that eye movements play a functional role in retrieval by reinstating the encoding context. By overtly shifting attention in a manner that broadly recapitulates the spatial locations and temporal order of encoded content, eye movements facilitate access to, and reactivation of, associated details. Such mnemonic gaze reinstatement may be obligatorily recruited when task demands exceed cognitive resources, as is often observed in older adults. We review research linking gaze reinstatement to retrieval, describe the neural integration between the oculomotor and memory systems, and discuss implications for models of oculomotor control, memory, and aging.

Abstract: A. baumannii exhibits resilience in harsh environments and progressively develops resistance to diverse antibacterial agents over time. This adaptability poses a significant challenge in treating an infection caused by this bacterium within healthcare settings. The presence of peptidoglycan, a crucial precursor for cell wall synthesis, contributes to this challenge. Peptidoglycan serves not only as a structural support in bacterial cells but also provides protection against adverse environmental conditions. The synthesis of the peptidoglycan layer involves a group of substrates such as N-acetylglucosamine (GlcNAc) and N-acetylmuramic acid (MurNAc), within a three-partitioned process occurring in the membrane, periplasmic space, and cytoplasm of each bacterium. Initiated in the cytoplasm and extending to the inner cell membrane, this synthesis starts with the production of nucleotide precursors. The first step involves the synthesis of UDP-GlcNAc, orchestrated by Glm (GlmS, GlmM, and GlmU) enzymes using fructose-6-phosphate. Subsequently, enzymes from the Mur family, namely MurB, MurA, MurD, MurC, MurI, MurF, and MurE, synthesize UDP-N-acetylmuramyl-pentapeptide (UDP-Mpp) from UDP-GlcNAc. Concurrently, on the cytosolic side, the production of membrane-surrounded undecaprenyl phosphate occurs, involving membrane-side proteins MraY and MurG in the biosynthesis of peptidoglycan. This review emphasizes updated information on Mur family proteins, encompassing physicochemical properties, nature of binding site, number and type of binding site residues, functional domain details, three-dimensional structural aspects, and their functions within bacterial cells. Special attention is directed towards their enzymatic role in peptidoglycan biosynthesis due to the limited availability of precursors in the market. Additionally, the review provides a comprehensive summary of existing inhibitors and ongoing efforts in identifying new targeted inhibitors, recognizing these enzymes as potential candidates for antibacterial drug design and discovery.

Intense climate change and rapid urbanization have increased the risk of urban flooding, seriously affecting urban economic and social stability. Enhancing the urban flood resilience (UFR) has required a new solution to cope with urban flood disasters. In this study, taking Yingtan city as an example, a system of indicators for evaluating UFR was constructed, with 17 representative indicators, comprising three subsystems: socio-economic, ecological and infrastructural. A hybrid (FAHP-EWM)-TOPSIS model was applied, to develop an index-based measurement to compare and evaluate UFR, and Gray Relational Analysis (GRA) was used to discover the main factors affecting UFR. In addition, the natural discontinuous method was innovatively used to divide the UFR grade interval into levels, and the grade change was evaluated based on the TOPSIS method. The results showed that (1) from 2010 to 2022, the UFR in Yingtan City increased by 80.69%, and the factors affecting UFR are highly correlated with urban infrastructure development. However, the ecological resilience in the subsystem showed a fluctuating downward trend, because of the influence of the surface area of lakes and rivers. (2) The grades of UFR for Yingtan City increased from Level III (2010 and 2016) to Level IV (2022), with local financial expenditures and the age structure of the population being the main factors currently limiting the development of UFR. The study provides a theoretical basis for the construction of an indicator system for assessing the UFR of Yingtan and proposes practical improvement directions for UFR.

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. We develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1˚ over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.00 μg/m^3 and R2 = 0.72) and outperforms either AOD-retrieved PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-retrieved PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides all-spacetime-covered predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.75 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81, across China during 2014. Fused estimates will be publicly available for future health-related studies.

China's economic development has shifted from high speed to high quality. This study constructs an evaluation index for China’s high-quality development utilizing a new development concept. The entropy method and cluster analysis were used to assess the level of high-quality development in China between 2015 and 2021. Kernel density estimation method was employed to explore spatiotemporal dynamics. The results reveal significant differences in the level of economic development among provinces in China; the eastern region is significantly better than the central, northeastern, and western regions. From the perspective of the sub-item evaluation, challenges with uneven, uncoordinated, and insufficient economic development exist in various Chinese provinces.

The Eastern Kunlun Fault Zone (EKFZ) is located in a seismic blank area. This study investigates the hydrogeochemical characteristics of varied-temperature springs in the EKFZ to understand the relationship between fractures, fluids and earthquakes. It aids in establishing their induction mechanisms and assists in monitoring the earthquake precursors of the EKFZ. In this study, the main elements, trace elements, hydrogen and oxygen isotopes and strontium isotopes of 23 varied-temperature springs in the EKFZ were analyzed. The results reveal the source of groundwater recharge, hydrochemical types, mineral saturation, and for a select few springs indicative of geothermal activity, collected geothermal reservoir temperatures. The study also explores the relationship between earthquakes and springs, identifying sensitive chemical indicators. Based on continuous monitoring at Maqu Station, we found that before the occurrence of the Maerkang Ms 6.0 earthquake, the concentration of Cl− rose by 2.9 times, and 46 days before the Gande earthquake (Ms = 4.7), the concentrations of Na+ and SO42− significantly increased. Finally, a conceptual model of the hydrogeochemistry of springs is presented to describe the groundwater circulation in the study area. This research is of great significance for the analysis of fluid geochemistry in this area and for assessing the seismic hazards of the EKFZ.

.With the increasing use of carbon fiber reinforced plastics in various area, carbon fiber composites based on prepregs have attracted attention in industries and academia research. However, prepreg manufacturing processes are costly, and the strength of structures varies depending on the orientation and defects (pores and delamination). For non-contact evaluation of internal defects, we proposed lock-in infrared thermography to investigate orientation angles after a compression test. We also conducted a drop-weight impact test to study the behaviour of the composites after impact according the fibers orientation for composite fabricated using unidirectional carbon fiber prepregs. Using CAI tests, we determined the residual compressive strength and confirmed the damage modes using a thermal camera. The results of the drop weight impact tests show that the specimen laminated at 0° suffered the largest damage because of susceptibility of the resin to impact. In contrast, the specimens oriented in of 0°/90° and +45°/–45° directions transferred more than 90% of the impact energy back to the impactor because of the lamination of fibers in the orthogonal directions. Furthermore, the specimens that underwent complete damage in the impact tests were subjected to the lock-in method and showed internal delamination and cut fibers. With the finite elements analysis, the damage of each ply could be observed. Moreover, the temperature differences in the residual compression tests were not significant.

Background and Objectives: In recent years Electronic scooters (E-Scooters) have gained popularity, whether for private use or as a publicly available transportation method. With introduction of these vehicles, reports of E-Scooter related accidents have surged, sparking a public debate and concern. Aim of this study was to analyse epidemiological data, characteristics and severity of traumatic brain injury (TBI) related to E-Scooter accidents. Materials and Methods: This retrospective case series evaluated 28 patients who were admitted to three largest neurosurgery clinics in Riga, Latvia between time period from April to October in two separate years – 2022 and 2023 after an E-Scooter related accident. Data were collected on patient demographics, time of the accident, alcohol consumption, helmet use, type of TBI, other related injuries, treatment and assessment at discharge. Results: A total of 28 patients were admitted with TBI related to E-Scooter use, with median age 30 years (Q1-Q3, 20.25-37.25), four individuals under age of 18, majority (64%) were male. In 23 cases the injury mechanism was fall, in 5 cases collision. None were wearing a helmet at time of injury. Alcohol intoxication was evident in over half of the patients (51.5%), with severe intoxication (&gt;1.2ppm) in 75% cases among them. Neurological symptoms upon admission were noted in 50% of cases. All patients had intracranial trauma - 50% brain contusions, 43% traumatic subdural hematoma, almost 30% - epidural hematoma. Craniofacial fractures were evident in 71% of cases, fractures in other parts of body in 3 patients. 6 patients required emergency neurosurgical intervention. Neurological complications were noted in 2 patients, 1 patient died. Conclusions: E-Scooter related accidents result in a significant number of brain and other associated injuries, with notable frequency linked to alcohol influence and lack of helmet use. Prevention campaigns to raise awareness of potential risks and implementation of more strict regulations should be done.

We evaluated the potential of using fish species and functional traits as indicators of land use impacts to fish assemblages. We used environmental data collected at multiple spatial scales (local, reach, and upstream catchment) for 19 tributary and main stem sites in the Nolichucky River watershed in Tennessee. Canonical correspondence analyses showed that temperature, elevation, specific conductivity, sediment yield, impervious surfaces, and row crop cover at the catchment scale were strongly associated with fish assemblage structure, as well as forest cover from all three spatial scales. Blocked indicator species analysis, with stream size as the block, showed that significantly strong indicators of the least-impacted riparian land use condition (≥60% forest cover) were Saffron Shiner (Notropis rubricroceus), Rainbow Trout (Oncorhyncus mykiss), Longnose Dace (Rhynichthys cataractae), Creek Chub (Semotilus atromaculatus), and Mottled Sculpin (Cottus bairdi). Traits indicative of the least-impacted sites were the herbivorous trophic guild, mean female age-at-maturity, longevity, rock-gravel spawners, montane geology and pelagic swimmers. Specific conductivity was strongly related to multiple catchment-scale land use variables, and was a strong local-scale influence on fish assemblage structure. Our results show promise for using a relatively common but endemic southern Appalachian fish species, the Saffron Shiner, as an indicator for land-use related impacts to these streams.

The study combines two critical aspects of climate research in Nigeria. The first segment focuses on improving predictive performance of global circulation models (GCMs) employing ensemble techniques. ANN ensemble displayed significant improvement in the accuracy of climate projections, particularly in high-altitude geographic areas where traditional models exhibit limitations. Performance evaluation metrics such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Nash–Sutcliffe Efficiency (NSE) demonstrate the effectiveness of the ANN multimodal ensemble. Building on the improved climate modelling, the second segment delves into a spatial and temporal analysis of rainfall and mean temperature patterns under climate change in Nigeria. By considering two Representative Concentration Pathways (RCPs), namely RCP4.5 and RCP8.5, the study utilizes dynamically downscaled GCMs obtained from the Coupled Model Intercomparison Project phase 5 (CMIP5). The Mann-Kendall test reveals significant spatiotemporal variations in climate trends across the country. The warming trend is particularly pronounced in the northern regions, with RCP8.5 showing more severe impacts compared to RCP4.5. This integrated approach not only highlights the importance of multimodal ensembles in climate modelling but also provides valuable insights into the spatial and temporal patterns of climate change to inform effective adaptation and mitigation strategies for Nigeria.

Increasing groundwater levels (GWL) may become one of the most serious issues for Odessa City, Ukraine. This study investigated the spatial distribution characteristics and multifractal scaling behaviour of groundwater level/depth fluctuation for a Quaternary aquifer in Odessa City using a geostatistical approach and a Multifractal Detrended Fluctuation Analysis (MF-DFA). These two methods were applied to monthly GWL fluctuation time series from 1970 to 2020 to monitor 72 hydrogeological wells situated in different parts of Odessa City. The spatial distribution of GWL revealed an overall trend of decline and recovery from 1970 to 2020 in the study area, except for most of the southern region, where a persistent recovery of groundwater depth was observed. The MF-DFA results suggest that the dynamics of GWL fluctuations have multifractal characteristics in the Odessa City area. In addition, both long-range correlation and fat-tail probability distribution contribute to multifractality. However, long-range correlations among fluctuations made a major contribution to the observed multifractality of the GWL fluctuations time series. The generalized Hurst exponent shows a wide range of change (0.20 &lt; h(q) &lt; 2.85), indicating the sensitivity of GWL fluctuations to changes in small scale factors and large-scale factors. Regarding the long range correlations of GWL depth, the Hurst exponents (q = 2) demonstrated the positive persistence of groundwater depth recovery in the southern region and the persistence of groundwater depth variation in the other regions of the study area. The dynamic changes in GWL depth in the Odessa City area may be affected by both natural structural and anthropogenic factors.

Due to the long-term deformation settlement of foundations, issues such as damage and functional failure of buildings and structures have long been of concern in the engineering field. The creep of soil is one of the primary causes leading to long-term deformation of foundations. In this paper, the consolidation deformation, creep characteristics, and creep model of reconstituted saturated silty clay were studied by isotropic compression test and triaxial shear creep test. The results show that for the isotropic compression test, although the applied load adopts different stages of loading, as long as the final applied confining pressure is the same, the number of stages applied by the confining pressure has little effect on the final isotropic consolidation deformation of the sample and the triaxial undrained shear strength after creep. However, for the triaxial shear creep test, it is found that under the same final deviatoric stress, the final deviatoric strain of the sample is closely related to the number of loading stages of deviatoric stress. It shows that the more loading stages of the sample loaded with the same deviatoric stress, the smaller the final deviatoric strain, and the triaxial undrained shear strength of the sample after creep will increase. In addition, it is reasonable to determine the pore pressure dissipation of the sample to 95%((u0-u0)/u0=95%) as the main consolidation end time (tEOP) of the sample. The isotropic consolidation creep curves and the triaxial shear creep curves show certain nonlinearity. Then the logarithmic model and the hyperbolic model were used to fit the creep curves of the samples. It is found that the hyperbolic model has a better fitting effect than the logarithmic model, but for the triaxial shear creep test, the creep parameters of the sample change greatly. Therefore, studying the creep characteristics of soil under different pre-loading steps is of significant engineering importance for evaluating the long-term deformation of underground structures.

Aluminum wire is a common material for wire bonding due to its resistance to oxidation and low price. It does not melt when becoming a free air ball (FAB) during the electronic flame-off (EFO) process with wettability, and is applied by wedge bonding. This study used 20μm Zn-Coated Al-0.5wt.%Si (ZAS) wires to improve the FAB shape after the EFO process, while maintaining stability of the mechanical properties, including the interface bonding strength and hardness. In order to test circuit stability after ball bonding, the current-tensile test was performed. During the experiment, it was found that 80nm ZAS with wire bonding has lower resistance and higher fusing current. For the bias tensile test, the thicker Zn film diffused into the Al-Si matrix easily, after which the strength was reduced. The ball-bond interfaces had no change in their condition before and after the bias. Accordingly, ZAS could be a promising candidate for ball bonding in the future.

Micro-expression (ME) is one of the key psychological stress reactions. It is a modest, spontaneous facial mechanism. ME has significant applicability in a variety of psychologically-related sectors because to its precision and unpredictability with regard to psychological manifestations. Nevertheless, the current Micro-expression recognition (MER) algorithms have poor accuracy and a limited quantity of ME data, and this study issue has not been thoroughly investigated. Therefore, we present an approach for deep learning based on a Spatio-temporal capsule network (STCP-Net). STCP-Net has four components: a jitter reduction module, a differential feature extraction module, an STCP module, and a fully linked layer. The first two modules are aimed to extract diversifying differential features more precisely and to limit the influence of head jitter. The STCP module is used to extract Spatio-temporal features layer by layer, taking the temporal and geographical connection between features into account. This research runs sufficient trials using the Leave One Subject Out (LOSO) methodology for cross-validation using the CASMEII dataset. The conclusion and analysis demonstrate that the algorithm is innovative and efficient.

Lyme disease is a growing public health problem in Québec. Its emergence over the last decade is caused by environmental and anthropological factors that favour the survival of Ixodes scapularis, the vector of Lyme disease transmission. The objective of this study was to estimate the speed and direction of Lyme disease emergence in Québec and to identify spatiotemporal risk patterns. A surface trend analysis was conducted to estimate the speed and direction of its emergence based upon the first detected case of Lyme disease in each municipality in Québec since 2004. A cluster analysis was also conducted to identify at-risk regions across space and time. These analyses were reproduced for the date of disease onset and date of notification for each case of Lyme disease. It was estimated that Lyme disease is spreading northward in Québec at a speed varying between 18 and 32 km/year according to the date of notification and the date of disease onset, respectively. A high rate of disease risk was found in seven clusters identified in the south-west of Québec in the sociosanitary regions of Montérégie and Estrie. The results obtained in this study improve our understanding of the spatiotemporal patterns of Lyme disease in Québec, which can be used for proactive, targeted interventions by public and clinical health authorities.

Comprehensive understanding of tree characteristics and conditions holds paramount importance for the precise management of hazelnut orchards. It facilitates the determination of tree vigor, pruning requirements, phytosanitary interventions, and plant water consumption. The primary objective of this study was to explore, for the first time on a fruit tree with a bushy structure and across trees of four Italian distinct hazelnut cultivars, the efficacy of multispectral and thermal UAV (Unmanned Aerial Vehicle) technologies in assessing canopy attributes, vegetative growth, and predicting abiotic stresses. These technologies serve as tools for precision agriculture, enabling the computation of various indices such as the Normalized Difference Vegetation Index (NDVI) and crop water stress index (CWSI). The study of water content is of particular importance at this time, especially considering the increasing water stress levels in Europe as well as globally. While Red Green Blue (RGB) and thermal imagery collectively demonstrated superior performance in model reconstruction, the multispectral UAV remained more adept at characterizing size traits of hazelnut plants. Thermal images alone proved inadequate for accurately reconstructing hazelnut biometric characteristics. Furthermore, all indices were found to be cultivar-specific, underscoring the importance of conducting studies across different cultivars. The utilization of two UAVs, namely multispectral and thermal, facilitated the examination of the relationship between NDVI and CWSI across tree species.

Although migraine belongs to the main causes of disability worldwide the mechanisms of its pathogenesis are poorly known, which is among the reasons that this disease is underdiagnosed and undertreated. As migraine diagnosis is based on the subjective assessment of symptoms, there is a need to establish objective markers of its occurrence and severity. Tryptophan (TRP) metabolism has been associated with the pathogenesis of neurological and psychiatric disorders. In the present work, we investigated an association between migraine and the urine concentration of TRP and its metabolites 5-hydroxyindoleacetic acid (5-HIAA), kynurenine (KYN), kynurenic acid (KYNA) and quinolinic acid (QA) in 21 low-frequency episodic migraine patients and 32 controls. Migraine patients displayed lower urinary levels of 5-HIAA and KYNA, but KYN and QA were enhanced as compared with the controls. Consequently, the patients were characterized by different values of the 5-HIAA/TRP, KYN/TRP, KYNA/KYN, and KYNA/QA ratios. Furthermore, urinary concentration of 5-HIAA was negatively correlated with Migraine Disability Assessment score, monthly migraine, and monthly headache days. A negative correlation between Patient Health Questionnaire 9 scores assessing depression. In conclusion, the urinary 5-HIAA level may be an easy-to-determine marker of migraine occurrence and severity and may contribute to the identification of migraine patients with depression.

The surface velocity of the Amery Ice Shelf (AIS) is vital to assessing its stability and mass balance. Previous studies have shown that the AIS basin has a stable multi-year average surface velocity. However, spatiotemporal variations in the surface velocity of the AIS and the underlying physical mechanism remain poorly understood. This study combined offset tracking and DInSAR methods to extract the monthly average surface velocity of the AIS and obtained the inter-annual surface velocity from the ITS_LIVE product. An uneven spatial distribution in inter-annual variation of the surface velocity was observed between 2000–2022, although the magnitude of variation was small at less than 20.5 m/yr. The increase and decrease in surface velocity on the eastern and western-central sides of the AIS, respectively, could be attributed to the change in the thickness of the AIS. There was clear seasonal variation in monthly average surface velocity at the eastern side of the AIS between 2017–2021, which could be attributed to variations in the area and thickness of fast-ice and also to variations in ocean temperature. This study suggested that changes in fast-ice and ocean temperature are the main factors driving spatiotemporal variation in the surface velocity of the AIS.

Domestic cats (Felis catus) are widespread worldwide as the most popular pets. This medium-sized carnivore have well-known negative effects on biodiversity, but there is still need to better understand the proximate causes of its predation. Based on a citizen science project, we assessed the role of spatiotemporal (i.e., latitude, longitude and seasons), climatic (i.e., rainfall), anthropogenic (i.e., human footprint, HFI) and individual (i.e., sex and age) variables on the number of preys returned home by cats in metropolitan France. Over the 5 048 cats monitored between 2015 and 2022, prey from 12 different classes (n= 36 568) were returned, being 68% mammals, 21% birds and 8% squamates. Shrews brought home by cats peaked during summer, while rodents were recorded during summer-autumn. Birds brought home by cats peaked in spring-summer and in autumn, and lizards in spring and in late summer. Lower HFI was associated with more voles and mice brought home and the opposite trend was observed for lizards and birds. Younger cats were more prone to bring home shrews, birds and reptiles. Although environmental factors play a minor role in prey brought home by cats, some geographical characteristics of prey species distribution partly explains the hunting behaviour of cats.

Fake news detection has become a significant topic based on the fast-spreading and detrimental effects of such news. Many methods based on deep neural networks learn clues from claim content and message propagation structure or temporal information, which have been widely recognized. However, such models (i) ignore the fact that information quality is uneven in propagation, which makes semantic representations unreliable. (ii) Most models do not fully leverage spatial and temporal structure in combination. (iii) Finally, internal decision-making processes and results are non-transparent and unexplained. In this study, we develop a trust-aware evidence reasoning and spatiotemporal feature aggregation model for more interpretable and accurate fake news detection. Specifically, we first design a trust-aware evidence reasoning module to calculate the credibility of posts based on a random walk model to discover high-quality evidence. Next, from the perspective of spatiotemporal structure, we design an evidence-representation module to capture the semantic interactions granularly and enhance the reliable representation of evidence. Finally, a two-layer capsule network is designed to aggregate the implicit bias in evidence while capturing the false portions of source information in a transparent and interpretable manner. Extensive experiments on two benchmark datasets indicate that the proposed model can provide explanations for fake news detection results, as well as can achieve better performance, boosting 3.5% in F1-score on average.

Polo is an equestrian team sport, consisting of Open and Women’s only handicapping systems. As cumulative player handicap increases in Open Polo, distance covered, average speeds and high intensity work performed per chukka also increase. These activities may differ in terms of distribution of, and their affect upon, match outcome in Women’s Polo, and thus have implications for equine preparation and management. This study aimed to quantify spatiotemporal differences between Open and Women’s Polo when matched for handicap and assess their affect upon chukka and match outcome using a prospective cohort design. Distance, speed and high intensity activity data were collected via player worn global positioning system (GPS) units during 16-goal Open and Women’s Polo tournaments. Notational analysis quantified chukka duration and chukka and game outcomes. Between group differences were assessed by independent samples t-tests, and two factor mixed effects ANOVA for within group analyses. Between group differences were analysed using an independent samples t-test with alpha defined a priori as p<0.05. Open and Women’s Polo differed by a small to large extent (ES: 0.54 – 1.81) for all spatiotemporal metrics. In Open Polo, players covered moderately more distance (429.0m; 238.9m to 619.0m), with small to large increases in high intensity activities performed in games won. Whereas in Women’s Polo, moderately higher maximum speeds were attained in games won (17.13 km/h; 11.86 km/h to 22.40 km/h) and a small increase in accelerations performed (5.1; 0.2 to 10.0). Open and Women’s Polo, when matched for handicap, present with small to large spatiotemporal differences that are likely of practical significance, and influence game outcome differently between codes. These differences do not necessarily mean that Polo ponies need to be trained differently for each code.

The aim of this study is to analyze the characteristics of drought such as intensity, cumulative curves and trends, based on SPEI (Standardized Precipitation Evapotranspiration Index) at 8 stations in Korea from 1981 to 2010. The traditional SPEI is based on Thornthwaite equation for estimating evapotranspiration; SPEI_th. However, a standard of agricultural water management in Korea suggests FAO Penman-Monteith equation; SPEI_pm. In this study, we analyzed the intensity and trends of drought using SPEI_th and SPEI_pm, respectively, and analyzed the relationship between them. Both of central and southern region, the SPEIs were below -1.0 (moderated drought) for the periods May-August in the representative drought year such as 1988, 2001, and 2008-09. The frequency of drought was higher in southern region than central region. In addition, SPEI_pm showed slightly more intensive drought rather than SPEI_th except for Chuncheon and Gwangju. In 5 stations except for Cheoncheon, Gwangju and Jinju, the cumulative probability that SPEI_pm is below -1.5 was significantly increased from 1981-1995 to 1996-2010. As the results of drought trends, the increasing trend of SPEIs was shown on fall season, and the cumulative probability that SPEI_pm is below -1.5 was also significantly increased.

Human action recognition (HAR) based on skeleton data is a challenging yet important technique because of its wide range of applications in many fields, including patient monitoring, security surveillance, and observing human-machine interactions. Many algorithms that attempt to distinguish between many types of activities have been proposed. However, most practical applications require highly accurate detection of specific types of activities. In this study, a novel and highly accurate spatiotemporal graph autoencoder network for HAR based on skeleton data is proposed. Furthermore, an extensive study was conducted using different modalities. For this purpose, a spatiotemporal graph autoencoder that automatically learns spatial as well as temporal patterns from human skeleton datasets was built. The powerful graph convolutional network named GA-GCN, developed in this study, notably outperforms most of the existing state-of-the-art methods based on two common datasets, namely NTU RGB+D and NTU RGB+D 120 . On the first dataset, we achieved an accuracy of 92.3% and 96.7% based on the cross-subject and cross-view evaluations, respectively. On the other more challenging dataset (i.e. NTU RGB+D 120), GA-GCN achieved 88.8% and 90.4% based on the cross-subject and cross-set evaluation, respectively.

Advances in technology have introduced remarkable capabilities, particularly in the realm of gathering and accessing vast amounts of data, which has led to the emergence of the "Big Data" era, presenting exciting opportunities to harness the wealth of the generated information. Traffic management centers comprise a stakeholder that can exploit such data towards improving road network operation. This research, explores the utilization of real traffic data, collected by distinct sources on an interurban motorway: static location based aggregate traffic data and probe vehicle data. The first is collected by traffic detectors, while the second involves patrol vehicles’ GNSS data. The traffic quantity analysed is vehicle speed, while specific emphasis has been given on the ap-plication of heatmaps to represent daily traffic patterns and the utilization of k-means clustering. The performed analysis demonstrates the importance of considering spatiotemporal variables as a unified entity when analysing speed in transportation networks. The limitations of using patrol vehicles as estimators of ambient speed, especially in low and heavy traffic conditions, are deline-ated, while the dual purpose of data gathered from these vehicles towards enhancing driving performance and enabling detector maintenance is emphasized. Valuable traffic insights are offered through comprehensive spatiotemporal speed behavior analysis and data combination. The inte-gration of these techniques enhances decision-making for a streamlined and secure transportation system

The processes of soliton generation and interference focus on the complex nonlinear soliton dynamics resembling matter particles. In order to further understand the dynamic process of solitons from a multidimensional perspective, here we report the vectorial solitons nature under two-sets pulse splitting in a single cavity induced by dual-core fiber assisted ultrafast fiber lasers. Owing to the weakly coupled cores in symmetrical dual core fiber (SDCF), two pulse groups interaction are formed in a cavity. By using the dispersive Fourier transformation technique (DFT), it was found that the four-component polarized rotation vector solitons (PRVS) generate. Moreover, gradually increasing the power can obtain the locked soliton bound state in two core space, and the corresponding evolution is similar to that of non-degenerate bright solitons in Bose Einstein condensates (BEC). In addition, by properly controlling the soliton phase offset in SDCF, the soliton rain state of multi pulse evolution can be obtained. The related experimental results would be fruitful to the communities interested in soliton dynamics and frequency comb lasers.

Abstract: Research Highlights: This study is among the first to investigate ozone levels in urban forests in China. It establishes that urban forest air quality in Yuanshan Forest Park, Shenzhen, is suitable for recreational activities and identifies spatial, seasonal, and diurnal O3 patterns and relationships with micrometeorological parameters, suggesting the possibility of manipulating relevant forest characteristics to reduce O3 levels. Background and Objectives: An understanding of O3 levels of urban forest environments is needed to assess potential effects on human health and recreational activities. Such studies in China are scarce. This study investigated urban forest O3 levels to improve understanding and support residents engaging in forest recreational activities. Materials and Methods: We monitored O3 levels in 2015–2016 for three urban forests representing common habitats (foothill, valley, and ridge) in Yuanshan Forest Park, Shenzhen, and for an adjacent square. Results: The overall mean daily and daily maximum 8-h mean (MDA8) O3 concentrations were highest for the ridge forest and lowest for the valley forest. Each forest’s O3 concentrations were highest in summer. Diurnally, forest O3 concentrations peaked between 13:00 and 17:00 and reached a minimum between 03:00 and 09:00. The correlation between forest O3 concentrations and air temperature (AT) was strongly positive in summer and autumn but negative in spring. In each season, O3 concentration was negatively correlated with relative humidity (RH). No MDA8 or hourly O3 concentrations in the forests exceeded National Ambient Air Quality Standard Grade I thresholds (100 and 160 μg m−3, respectively). Conclusions: O3 accumulation is present in ridge urban forest in all seasons. Foothill and valley urban forests have better air quality than ridge forestation. Urban forest air quality is better in spring and autumn than in summer and is better from night-time to early morning than from noon to afternoon.

Intratumoral heterogeneity associates with more aggressive disease progression and worse patient outcomes. Understanding the reasons enabling the emergence of such heterogeneity remains incomplete, which restricts our ability to manage it from a therapeutic perspective. Technological advancements such as high-throughput molecular imaging, single-cell omics and spatial transcriptomics now allow recording the patterns of spatiotemporal heterogeneity in a longitudinal manner, thus offering insights into the multi-scale dynamics of its evolution. Here, we review latest technological trends and biological insights from molecular diagnostics as well as spatial transcriptomics, both of which have witnessed a burgeoning growth in recent past in terms of mapping heterogeneity within tumor cell types as well as stromal constitution. We also discuss ongoing challenges, indicating possible ways to integrate insights across these methods to have a systems-level spatiotemporal map of heterogeneity in each tumor, and a more systematic investigation of implications of heterogeneity for the patient outcomes.

Successful fertilization treatments targeted to improve stand productivity while reducing operational complexities and cost depend on a clear understanding of soil nutrient availability under varying environmental conditions. Soil nutrient data collected from 154 forest sites throughout the Inland Northwest, USA were analyzed to examine soil nutrient characteristics on different geologic soil parent materials and to rank soil fertility. Results show that soil parent material explains significant differences in soil nutrient availability. Soils developed from volcanic rocks have the highest CEC and are relatively high in P, K, S, Mg, Cu, Ca, and B, but generally poor in N. Forest soils developed from plutonic rocks exhibit the lowest CEC and are low in N, S, K, Mg, Cu, and Ca, but higher in P. Some soils located on mixed glacial till are low only in K, Cu, Mg, and Ca, but many glacial soils are relatively rich in other nutrients, albeit the second lowest CEC. Soils developed from metasedimentary and sedimentary rocks are among those with lowest soil nutrient availability for P and B. Sulfur was found to have the highest concentrations in metasedimentary influenced soils and the least in sedimentary derived soils. Our results should be useful in designing site-specific fertilizer and nutrient management prescriptions for forest stands growing on soils developed from these major geologies within the Inland Northwest region of the United States.

The geographical location of Yunnan province is at the upstream area of water vapor transportation from the Bay of Bengal and the South China Sea to inland China. Understanding the spatiotemporal variations of water vapor over this region holds significant importance. We utilized the GNSS data collected from 12 stations situated in Yunnan, which are part of Crustal Movement Observation Network of China, to retrieve hourly precipitable water vapor (PWV) from 2011 to 2022. The retrieved PWV at Station KMIN were evaluated by the nearby radiosonde data, and the result shows that the mean bias and RMS of the differences between the two datasets are 0.08 and 1.78 mm respectively. Average PWV values at these stations are in the range of 11.77 to 33.53 mm, which decrease from the southwest to the north of Yunnan and are negatively correlated with the station heights and latitudes. Differences between average PWV in wet season and dry season range from 12 to 27 mm. These differences tend to increase as the average PWV increases. The yearly rates of PWV variations, averaging 0.18 mm/year, are all positive for the stations, indicating a year-by-year increase in water vapor. Amplitudes of the PWV annual cycles are 9.75-20.94 mm. The spatial variation of these amplitudes is similar to that of average PWV over the region. Generally, monthly average PWV values increase from January to July and decrease from July to December, and the growth rate is less than the decline rate. Average diurnal PWV variations show unimodal PWV distributions over the course of the day at the stations except Station YNRL, where bimodal PWV distribution was observed.

Since the 1970s, land subsidence has been developing rapidly in the Beijing Plain, the systematic study of its evolution mechanism is of great significance to the sustainable development of the regional economy. First, based on ENVISAT ASAT and RADARSAT2 data, the land subsidence data in Beijing Plain were obtained using permanent interferometer technology. Second, based on the GIS platform and using fishing net tools, vector data of ground settlement with different resolutions were obtained. Through a series of tests, a scale of 960 metres was selected as the research unit, and the subsidence rate of the grid was obtained from 2004 to 2015. Finally, based on the Mann-Kendall mutation test method, a trend analysis of land subsidence changes in various grids was carried out. The results showed that single-year mutation mainly distributed in the middle and lower parts of the Yongding River alluvial fan and the Chaobai River alluvial fan, mainly occurring in 2015, 2005 and 2013, respectively. The upper and middle alluvial fan of the Chaobai River, the vicinity of the emergency water source and the edge velocity of the groundwater funnel have undergone several sudden changes. Combined with hydrogeology, basic geological conditions and the impact of the South-to-North Water transfer project, we analysed the causes of the mutations in the grid. The research results can provide a basis for the study and prevention of land subsidence in this area and help to further explore the trend characteristics of land subsidence in this area.

The Yellow River Basin (YRB) is a crucial ecological zone and an environmentally vulnerable re-gion in China. Understanding the temporal and spatial trends of terraced-field areas (TRAs) and the factors underlying them in the YRB is essential for improving land use, conserving water re-sources, promoting biodiversity, and preserving cultural heritage. In this study, we employed ma-chine learning on the Google Earth Engine (GEE) platform to obtain spatial distribution images of TRAs from 1990 to 2020 using Landsat 5 (1990－2010) and Landsat 8 (2015－2020) remote sens-ing data. The GeoDa software platform was used for spatial autocorrelation analysis, revealing distinct spatial clustering patterns. Mixed linear and random forest models were constructed to identify the driving force factors behind TRA changes. The research findings reveal that TRAs were primarily concentrated in the upper and middle reaches of the YRB, encompassing provinc-es such as Shaanxi, Shanxi, Qinghai, and Gansu, with areas exceeding 40,000 km2, whereas other provinces had TRAs of less than 30,000 km2 in total. The TRAs exhibited a relatively stable trend, with provinces such as Gansu, Qinghai, and Shaanxi showing an overall upward trajectory. Conversely, Shanxi and Inner Mongolia demonstrated an overall declining trend. When com-pared with other provinces, the variations in TRAs in Ningxia, Shandong, Sichuan, and Henan appeared to be more stable. The linear mixed model (LMM) revealed that farmland, shrubs, and grassland had significant positive effects on the TRA, explaining 41.6% of the variance. The ran-dom forest model also indicated positive effects for these factors, with high R² values of 0.983 and 0.86 for the training and testing sets, respectively, thus outperforming the LMM. The findings of this study can contribute to the restoration of the YRB's ecosystem and support sustainable devel-opment. The insights gained will be valuable for policymaking and decision support in soil and water conservation, agricultural planning, and environmental protection in the region.

With the rapid development in Beijing, there is a critical need to explore the circumstance and reveal the mechanisms of precious urban natural resources. In this context, urban blue space has attracted more and more attention by driving microcirculation, cooling heat islands, and relaxing residential. We extracted the UBS at Beijing using remote sensing, explored the spatial and temporal development in the last two decades via USDA methods, uncovered the full spectrum of landscape patterns from an ecological perspective, and simulated the mechanisms of the UBS area and the landscape quantitatively. We found that: (1) The UBS area in Beijing increased with fluctuation from 2000 to 2020. (2) The spatial clustering has distributed stable with some subtle changes. (3)The ecological circumstance has improved in the last 21 years in Beijing, with the increasing habitat diversity and richness, while the inferior landscape fragmentation has indicated some severe challenges. (4) Natural factors impact urban blue space areas more than social ones, while both similarly influence the UBS landscape. (5) Vegetation circumstances and precipitation are the most important natural factors on both area and landscape of UBS, and population and artificial surface are the most important social factors.

In this study, based on frost formation data provided by Harbin Meteorological Bureau, combined with geographical factors, temperature and population density, linear fitting, Mann-Kendall mutation test, pettitt method and sliding T test were used to analyze the spatio-temporal variation characteristics of frost date in Harbin Municipality and the effects of geographical factors, temperature and population density on frost regularity. The results showed that (1) The earliest year of FSD appeared was 1966 and 1967, on the 255th, i.e., August 18th, and the latest was 283 days, i.e., October 10th, 2006. The earliest year in which the FED appeared was April 24th of 2015, the 114th day of that year, and the latest was April 21st of 1974, the 141st day of that year. The year with the most frost was 2012, with 161 days, and the year with the shortest was 1966, with 123 days. (2) Throughout the study period, FSD increased by 7.8 days at a rate of -1.27d/10a, FED increased by 10.9 days at a rate of 1.77d/10a, and FFS increased by 18.9 days at a rate of 3.05d/10a. The tendency rate of FSD and FFS at each site in Harbin showed an increasing trend. For FED, the tendency rate of some sites showed an increasing trend. In general, FSD showed a delayed trend, FED showed an advanced trend, and FFS showed a prolonged trend. Using the method of unary linear regression, FSD of each site showed an increasing trend, FFS showed an increasing trend, and FED showed a decreasing trend in general. (3) Throughout the study period, FSD was mutated in 2000, and the arrival time of it in the study area averaged the 265th, i.e., September 22nd, and after that, the arrival time of it changed to the 272nd, i.e., September 29th of that year. FED was mutated in 2006, and the arrival time of it in the study area averaged 128th, i.e., April 8th. After the mutation, the arrival time of FED changed to 121st, i.e., April 1st of that year. FFS was mutated in 2004. Before the mutation, with an average arrival time of 137days in the study area .But after that, the time changed to 150 days.(4) FSD and FFS in Harbin Municipality were negatively correlated with latitude and positively correlated with temperature, while FED was positively correlated with latitude and negatively correlated with temperature. The FSD, FED and FFS in the central part of Harbin Municipality were the earliest, the latest and the longest, respectively, so the Pearson correlation coefficient method and the influence of longitude could not be reflected in the multiple regression. Several factors were judged by grey correlation analysis method. The longitude is significantly related to FSD, FED and FFS.

Background: to analyze the impact of COVID-19 pandemic on characteristics and management of uveal melanoma (UM) in National Referral Center in Poland. Materials and Methods: the retrospective analysis of 1336 patients who were newly diagnosed with UM at Department of Ophthalmology and Ophthalmic Oncology, Jagiellonian University Collegium Medicum Krakow, Poland between January 1, 2018 and December 31, 2021. The demographic and clinical data were compiled including localization, size and treatment methods of tumors. Results: In total, 728 patients with UM were included before COVID-19 pandemic in years 2018-2019 and 608 were included during COVID-19 pandemic in years 2020-2021. Fixed-base dynamics indicators for the incidence of uveal melanoma (base year 2018) in the national referral center in Poland were 80.22% and 86.81% in year 2020 and 2021, respectively. UMs were statistically significantly larger and more frequently localized anterior to the equator of the eye globe in year 2021 than in year 2018 (Chi^2 Pearson test p= 0.0001 and p= 0.0077, respectively). The rate of patients treated with enucleation increased from 15.94% in year 2018 to 26.90% in year 2021 (Chi^2 Pearson test p=0.0005). Conclusions: statistically significant differences were found in the management of uveal melanoma in National Referral Center in Poland during COVID-19 pandemic with tumors being larger, more frequently localized anterior to the equator of the eye globe and more often enucleated.

Immune-cell reprogramming driven by mitochondria-derived reactive electrophilic immunometabolites (mt-REMs—e.g., fumarate, itaconate) is an emerging phenomenon of major biomedical importance. Despite their localized production, mt-REMs elicit significantly-large local and global footprints within and across cells, through mechanisms involving electrophile signaling. Burgeoning efforts are being put into profiling mt-REMs’ potential protein-targets and phenotypic mapping of their multifaceted inflammatory behaviors. Yet, precision indexing of mt-REMs’ first-responders with spatiotemporal intelligence and locale-specific function assignments remains elusive. Highlighting the latest advances and overarching challenges, this perspective aims to stimulate thoughts and spur interdisciplinary innovations to address these unmet chemical-biotechnological needs at therapeutic immuno-signaling frontiers.

Tuberculosis (TB) is a major public health concern in low and middle-income countries including Ethiopia. This study aimed to assess the spatiotemporal distribution and identify TB risk factors in Ethiopia's Oromia region. Descriptive and spatiotemporal analyses were conducted. Bayesian spatiotemporal modeling was employed to identify covariates that accounted for variability and spatiotemporal distribution of TB. A total of 206,278 new pulmonary TB cases were reported in the Oromia region between 2018 and 2022, with the lowest annual TB case notification (96.93 per 100,000 population) reported in 2020 (i.e., during the COVID-19 pandemic) and the highest TB case notification (106.19 per 100,000 population) reported in 2019. Substantial spatiotemporal variations in the distribution of notified TB case notifications were observed at zonal and district levels with most of the hotspot areas detected in the northern and southern parts of the region. The spatiotemporal distribution of notified TB incidence was positively associated with different ecological variables. The findings of this study indicated that preventive measures considering socio-demographic and health system factors can be targeted to high-risk areas for effective control of TB in the Oromia region. Further studies are needed to develop effective strategies for reducing the burden of TB in hotspot areas.

Impervious surface area (ISA) is a crucial indicator for quantitative urban studies. It is also important for land use land cover classification, groundwater recharge, sustainable development, urban heat island effects, and more. Spectral ISA mapping suffers from mixed pixel problems, especially with bare soil. This study aims to develop an ISA index for spatiotemporal urban mapping from common multispectral bands by reducing soil signature better than in previous studies. This study proposed a global impervious surface area index (GISAI) enhancing ISA mapping accuracy using a temporal parameter of the remote sensing (RS) dataset. Bare soil spectral reflectance shows more fluctuation than urban ISA. Therefore, the study uses minimum composites of earlier urban indices to compile minimum soil signature. It is later improved by removing water, increasing the contrast between bare soil and urban ISA and reducing bright bare soil area. This study maps the ISA of all 12 megacities using the annual RS image collection from 2021. GISAI reduced the bare soil signature and achieved an overall accuracy of 87.29%, F1-score of 0.84, and Kappa coefficient of 0.75. However, it has some limitations with grey bare soil and barren hilly areas. By limiting bare soil signature, GISAI broadens the scope of inter-urban studies globally and lengthens potential urban time-series analysis using common multispectral bands.

To investigate the dynamics of land surface temperature (LST) in Afghanistan in the period 2000-2021 and to assess the impact of such factors as soil moisture, precipitation, and vegetation coverage on it, remotely sensed soil moisture data from Land Data Assimilation System (FLDAS), precipitation data from Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), and NDVI and LST from Moderate Resolution Imaging Spectroradiometer (MODIS) were downloaded and correlations between them were analyzed using the regression method. The result shows that the LST in Afghanistan has a slightly decreasing, but insignificant trend during the study period (R=0.2, p-value=0.25), while vegetation coverage, precipitation, and soil moisture had an increasing trend. It was revealed that soil moisture has the highest impact on LST (R=0.7, p-value=0.0007), and the soil moisture, precipitation, and vegetation coverage explain almost 80% of spring (R2=0.73) and summer (R2=0.76) LST variability in Afghanistan. The LST variability analysis done separately for Afghanistan’s rivers subbasins shows that the LST of the Amu Darya subbasin had an upward trend in the study period, while for the Kabul subbasin the trend was downward.

Abstract: Green walls and green dams are increasingly being considered as part of many nation-al and international desertification initiatives. This paper studies the spatiotemporal evolution of the green dam in the Moudjbara region (Djelfa Province, Algeria) from 1972 to 2019 by using Landsat imagery, Land Change Modeler and Open Land package. The future evolution of pine plantations for the year 2029 was also forecasted, based on an anthropogenic scenario (i.e., an-thropogenic pressure is the main driver of the green dam destruction). Our findings revealed that the green dam project was successful for a few years, but after that, pine plantations deteri-orated significantly due to forest harvesting, livestock overgrazing, and the proliferation of the pine caterpillar processionary, which destroyed most of the reforestation. Land Change Modeler predicted a huge degradation of pine plantations for the year 2029, and if the deforestation con-tinues at the same rate, the green dam will disappear in the Moudjbara region during the next few decades. Aware of this threat, the Algerian authorities are now planning to reforest more than 1.2 million ha under the latest rural renewal policy by introducing new principles related to sustainable development, fighting desertification, and climate change adaptation

Dolichandrone spathacea is a rare and endangered semi-mangrove plant species with an extremely small population, naturally distributed only in Zhanjiang City and the east coast of Hainan Island, China. Regrettably, the present situation of the D. spathacea population in China has not yet been carefully investigated. In this study, we aim to evaluate the current resource status and population dynamic characteristics of D. spathacea on Hainan Island, China, in order to propose sustainable conservation and management strategies for future ecological restoration of its natural population. Our results show that D. spathacea on Hainan Island can be divided into four populations. All the D. spathacea populations present a state of overall dispersion, local concentration, and occasionally sporadic existence, and they exist in geographical isolation. The young, middle, and old D. spathacea plants account for 20.42%, 66.20%, and 13.38%, respectively, indicating that the overall age class of the D. spathacea population on Hainan Island belongs to a declining type. Furthermore, instead of temporal structure, we chose diameter at breast height (DBH) to establish a static life table, draw a population survival curve, and quantify the future development trend through population dynamic analysis and time-series prediction. These results directly point out that the D. spathacea population on Hainan Island is sensitive to external disturbances and possesses two main increases in mortality rate—namely, in its juvenile and mature stages—due to weak vitality, competition, and anthropogenic interferences, which are the most important reasons for its endangered status. Depending on the current conditions of the D. spathacea population, we should conserve and expand mature trees in situ, preserve their germplasm resources, rehabilitate their habitats to promote provenance restoration, and conduct artificial cultivation and spreading planting in order to realize the sustainable conservation and management of D. spathacea.

Background: Infective endocarditis (IE) continues to be a disease with high mortality despite medical advances. Objective: To investigate the characteristics and prognosis of IE according to the affected valves. Material and methods: The study is retrospective, single-center, cross-sectional and includes 270 patients with diagnosis IE, for the period 2005 – 2021, who received treatment at the University Hospital "St. Georgi" in Plovdiv, Bulgaria. Results: Single-valve IE (SIE) was found in 82.6% (n-222), multivalvular IE (MIE) in 16.66% (n=45) and device IE (CDRIE) in 0.74% (n=2) patients. The most commonly affected valve was the aortic 44.8% (n=121). The predominant multivalvular involvement was aortic-mitral valves (AV-MV) – 13.7% (n=37). The patients with tricuspid valve (TV) IE were significantly younger – 39 (30) years and were more frequently male (80.8%). Mortality was higher in MIE than SIE (31.1% vs 23.8%) and highest in multivalve aortic-tricuspid (AV-TV) IE (75%). Early surgery was done most in AV-MV IE 29.7% (n=11). Charlson comorbidity index was significantly higher in MV 4 (4) and AV 3 (3) than TV IE 1 (5) (p=0.048 and p=0.011, respectively). Septic shock occurred most frequently in AV-TV involvement (75%; p=0.0001). The most common causative agent was Staphylococcus group. Staphylococcus aureus affected more often TV alone 46.2% (n=124) vs. AV 9.9% (n=14); p=0.0001 and vs. MV 22.6% (n=17), p=0.022; Staphylococcus coagulase-negative (CNG) was the prevalent cause of MV IE 22.7% (n=17) vs AV-MV 2.7% (n=1); p=0.007. Streptococci were represented in a low percentage and only in left-sided IE, and more frequently in AV-MV 18.9% (n=7); vs. AV 6.6% (n=8); (p=0.025). Conclusion: Aortic valve is the most frequently affected valve, as single valve IE or multivalve AV-MV, with the predominant causative agents Staphylococcus group. The AV-TV IE has the worst prognosis, with the most common complication of septic shock and the highest in-hospital mortality.

Recharge is a crucial section of water balance for both surface and subsurface models in water resource assessment. However, quantifying its spatiotemporal distribution at a regional scale poses a significant challenge. Empirical and numerical modeling are the most commonly used methods at the watershed scales. However, integrated model inherently contain a vast number of unknowns and uncertainties, which can limit their accuracy and reliability. In this work, we have proposed integrated SWAT-MODFLOW and Transient Water Table Fluctuation Method (TWTFM) to evaluate the spatiotemporal distribution of groundwater recharge in Anyang wa-tershed, South Korea. Since TWTFM also uses SWAT model percolation output data, calibration was performed for individual models and coupled model. The coupled model was calibrated using daily streamflow and hydraulic head. SWAT-MODFLOW model performed well during the simulation of streamflow compared SWAT model. The study output showed that the study watershed had significant groundwater recharge variations during the simulated period. A sig-nificant amount of recharge happens in the wet season. It contributes about 34% of the average annual precipitation of the region. The direct flow components (surface and lateral) showed sig-nificant contributions when the water balance components were evaluated in the region. TWTFM showed a glimpse to estimate recharge, which requires representative monitoring wells in the study region. Comprehensively, the SWAT-MODFLOW model estimated groundwater recharge with reasonable accuracy in the region.

Studies on the gait's parameters have been identified on the patients population. Most researchers confirm that the patients walk differently than normal people and they may have a risk for falls. Consistent finding and description of gender, age, and body mass index differences in gait studies is rare in healthy subjects. A cross-sectional study with forty-five young adult (F = 20, M = 25) was conducted. Stadiometer and Physilog 4 inertial sensors were used for data collection. A gait analyser 5.2 software (GaitUp, S.A. Lausanne, Switzerland) was used to determine spatiotemporal parameters. No statistically significant differences were found in any bilateral foot gait parameters with respect to gender, age, and body mass index. Females are found with higher total double support and cadence than males. Cadence also increases with age. Obese people showed lower gait speed, cadence, and total double support. These findings may be beneficial to those who have abnormal gait pattern due to age, body mass index differences, decreased muscle strength, spasticity, and joint mobility. This important informations should be considered to rehabilitate patients with abnormal gait patterns to controlling dynamic balance and riks to falling.

Direct Energy Deposition (DED) is a versatile and efficient method in metal additive manufacturing. However, humping, caused by abnormal dynamics in the melt pool (MP), poses a significant threat to the geometric integrity of manufactured products. Current state-of-the-art (SOTA) methods primarily detect humping by analyzing late-stage spatial abnormalities, such as MP detachment. This approach is fundamentally reactive, leading to a tendency to miss early humping spatiotemporal dynamics, like cyclic elongation of the MP. This study introduces a novel, proactive indicator named VIMPS (Variability of Instantaneous MP Solidification-Front Speed), a physics-based tool designed to quantify early abnormal fluctuations in MP solidification speed. The experiments demonstrate VIMPS correlation with humping-induced geometric inaccuracies. By capturing early spatiotemporal dynamics of the MP, VIMPS reduces detection latency by 30 seconds compared to existing SOTAs that focus solely on spatial abnormalities. This significant improvement transforms detection from reactive to proactive, providing the time needed for corrective actions to enhance the overall productivity and quality of the DED process.

The study investigated the application of Wastewater-Based Epidemiology (WBE) as a tool for monitoring SARS-CoV-2 prevalence in a city in Northern Italy from October 2021 to May 2023. Starting from a widely applied deterministic model, this study proposed a variation to take into account population characteristics and virus biodegradation in the sewer network. The model calculated virus loads and corresponding COVID-19 cases over time in different areas of the city and was validated with healthcare data while considering viral mutations, vaccinations, and testing variability. The correlation between the predicted and reported cases was high across the three waves that occurred in the considered period, demonstrating the model’s capacity to predict relevant fluctuations in the number of cases. Population characteristics did not substantially influence the predicted and reported infection rates. Conversely, biodegradation significantly reduced the virus load reaching the wastewater treatment plant, resulting in a 30% reduction in the total virus load produced in the study area. This approach can be applied for comparing virus load values across cities with varying population demographics and sewer network structures, enhancing the comparability of WBE data for effective surveillance and intervention strategies.

Soil moisture modeling is necessary for many hydrometeorological and agricultural applications. One of the ways in which modeling of soil moisture (SM) can be improved is by assimilating SM observations to update the model states. Remotely sensed SM observations are prone to being riddled with data discontinuities, namely in the horizontal and vertical spatial, and temporal dimensions. A set of synthetic experiments were designed in this study to assess how much impact each of these individual components of spatiotemporal gaps can have on the modeling performance of SM as well as streamflow. Results show that not having root-zone SM estimates from satellite derived observations is most impactful in terms of modeling performance. Having temporal gaps and horizontal spatial gaps in the satellite SM data also impacts modeling performance, but to a lesser degree. Real-data experiments with the remotely sensed Soil Moisture Active Passive (SMAP) product generally brought improvements to the SM modeling performance in the upper soil layers, but not so much in the bottom soil layer. The updating of model SM states with observations also resulted in some improvements in the streamflow modeling performance during the synthetic experiments, but not during the real-data experiments.

There exists a compelling need to better understand the temporal dynamics of public sentiment towards COVID-19 vaccines in the US on a national and state-wise level for facilitating appropriate public policy applications. Our analysis of social media data from early February of 2021 and late March of 2021 shows that in spite of overall strength of positive sentiment, and increasing numbers of Americans being fully vaccinated, negative sentiment about COVID-19 vaccines still persists among sections of people who are hesitant towards the vaccine. In this study, we performed sentiment analytics on vaccine tweets, studied changes in public sentiment over time, conducted vaccination sentiment validation using actual vaccination data from the US CDC and Household Pulse Survey (HPS), explored influence of maturity of Twitter user-accounts and generated geographic mapping of sentiments by location of Twitter users. Furthermore, we leverage the emotion polarity based Public Sentiment Scenarios (PSS) framework which was developed for COVID-19 sentiment analytics, to systematically analyze directions for public policy processes to potentially improve the administration of vaccines. Application of the PSS framework provides important time sensitive insights for state and federal government agencies and associated organizations to better implement public policy processes for healthcare management, communication, transparency, motivation and societal operational policies such as social distancing. These insights are expected to contribute to processes that can expedite the vaccination program and move closer to the cherished herd immunity goal.

Microbial contamination is now more common than chemical contamination in Tibet, and water-borne microbes can cause a number of diseases that threaten public health. Thus, in order to clarify the spatiotemporal distribution of bacteria in small watersheds for which there is no data in Tibet, we set up four sampling points along an upstream-downstream transect of the Xincang River Basin. We collected 239 water samples in 2014 and 2015, and evaluated their total constituent numbers of bacteria (TB) and coliforms (TC). The results of this study show that the microbial contamination of the Xincang River Basin is mild-to-moderate in terms of TB and TC contents, and that these concentrations vary significantly in different seasons. Results show that in summer TB and TC concentrations in the downstream section of this river were highest and that microbial contamination was most serious. Data also demonstrate that precipitation is the most important factor underlying increases in TB and TC concentrations during the summer months; both these variables are significantly correlated with precipitation, while animal husbandry and domestic sewage are the main sources of microbial contamination overall. The results of this study are likely to reflect the basic characteristics of small watersheds for which there is no data to some extent, and are thus of significant practical importance for protecting their ecological environments and promoting sustainable development.

The commercialization of historic streets constitutes a pivotal aspect of urban cultural heritage, and the comprehension of their visual perception serves as a valuable asset to urban planning and cultural conservation efforts. However, current research concerning the disparities in visual perception among diverse demographics within historic streets, as well as their spatiotemporal dynamics, remains insufficient. This study aims to utilize mobile eye-tracking technology to delve deeply into the visual perception characteristics of diverse demographics within commercialized historic streets, while also analyzing their spatiotemporal dynamics. We explore the disparities in visual perception of historic streets among groups with varying degrees of architectural knowledge and professional literacy. Through meticulous observation using mobile eye-tracking technology, we elucidate the visual perception patterns of different demographic characteristics through statistical analysis and spatiotemporal modeling. The findings reveal significant discrepancies in visual attention and perception among various groups. Participants with a higher understanding of architecture tend to focus more on architectural details and structures within the streetscape compared to those with a lower understanding, who exhibit greater interest in elements such as shops and signage. Moreover, during the process of perceiving the streetscape, participants’ eye movements transition from surrounding landscapes and historical edifices upon initial entry to the district, gradually shifting towards the commercial activities and distinctive architecture within the district. This study delves deeply into the visual perception characteristics and spatiotemporal dynamics of commercialized historic streets, providing invaluable insights for urban planning and cultural preservation endeavors. By revealing the impact of different demographic characteristics on the visual perception of historic streets, it offers new insights for urban planning and cultural heritage conservation.

Vegetation Net Primary Productivity (NPP) plays a crucial role in terrestrial carbon sinks and the global carbon cycle. Investigating the spatiotemporal evolution and influencing factors in the Yangtze River Delta (YRD) region can furnish a solid scientific foundation for green, low-carbon, and sustainable development in China, as well as a reference for other rapidly urbanizing regions. This study focuses on the YRD region as an illustration and utilizes the Carnegie-Ames-Stanford Approach (CASA model) to quantify NPP in this region from 2000 to 2018. Investigation into the spatiotemporal evolution and influencing factors was conducted using Theil–Sen Median Trend Analysis and Scenario Analysis. The results indicate that (1) the NPP in the YRD region from 2000 to 2018 exhibited pronounced spatial differentiation characteristics, typically exhibiting a spatial distribution pattern of being high in the south and low in the north, high in the west and low in the east. Additionally, the expansion of built-up areas and the reduction of cultivated land have the potential to reduce NPP in the YRD region. Moreover, the influence of LUCC is anticipated to be relatively limited compared to that of climate change. Furthermore, changes in precipitation were found to be positively correlated with changes in NPP, with the effect being relatively more pronounced. The correlation between temperature and NPP demonstrated spatial differentiation, with a mainly positive correlation in the central and southern parts of the YRD and a mainly negative correlation in the northern part. Changes in solar radiation had a negative correlation with changes in NPP. Based on these results, it is recommended that local governments strictly enforce urban development boundaries and manage the disorderly expansion of built-up areas, enhance the regional irrigation infrastructure, and address air pollution, so as to ensure the necessary conditions for the growth of vegetation, reduce greenhouse gas emissions, and control regional temperature rise.

This research seeks to advance the understanding of ecological management in the Huaihe River Basin, China. The spatiotemporal variability of the Normalized Difference Vegetation Index (NDVI) and its underlying driving forces are examined utilizing SPOT-NDVI data covering the period 2000-2019. Linear regression analysis is employed to quantify trends and assess the statistical significance of NDVI variations. A differencing approach is subsequently applied to discern the variability in NDVI. The distribution of its spatial pattern stability over 20 years is explored through the coefficient of variation. Lastly, the Geodetector method is utilized to elucidate the driving factors influencing NDVI dynamics. The results indicate that the overall NDVI is generally high, with an overall growth rate of 0.00148/year, and 2010 is identified as a significant inflection point in the trend. NDVI values are notably lower in urban areas, corresponding to urban expansion, except for regions near rivers and lakes. Land use type emerges as the strongest explanatory factor for NDVI among single factors, with climate factors exhibiting a relatively weaker degree of explanatory force. These findings suggest that the overall NDVI in the Huaihe River Basin is high, indicative of a vegetation condition that continues to improve.

Dengue virus is becoming a major public health threat worldwide principally in Africa. From 2016 to 2020, 23 outbreaks were reported in Africa principally in West Africa. In Senegal outbreak are reported yearly since 2017 ; data about the circulating serotypes and their spatial and temporal distribution are limited to 2017 – 2018 period. Herein we describes up to date molecular surveillance of circulating DENV serotypes in Senegal between 2019 to 2023 and their temporal and spatial distribution around the country. For this purpose collected suspected DENV infections samples were subjected to dengue detection and serotyping using RT-qPCR methods. Positive samples subjected to temporal and spatial mapping. Subset of DENV+ samples were then sequenced and subjected to phylogenetic analysis. Results show a co-circulation of three DENV serotypes with a overall predominance of DENV-3 followed by DENV-1 with scarce cases of DENV-2 from 02_2019 to 02_2022. Interestingly data shows extinct of both serotype 1 and serotype 2 and the only circulation of DENV-3 from March 2022 to July 2023. At the genotype level analysis shows that sequenced strains belong to same genotype as previously described DENV-1 belong to genotype V, DENV-2 to cosmopolitan genotype and DENV-3 to Genotype III. Interestingly newly obtained DENV 1-3 sequences cluster in different clades within genotypes. This co-circulation of strains belonging to different clades could have effect on virus epidemiology and transmission dynamic. Overall our results highlight DENV serotypes replacement by DENV-3 accompanied by wider geographic distribution in Senegalese regions. All unmentioned results highlight the importance of virus genomic surveillance and call for further fitness studies using both in vitro and in vivo model as well as in depth phylogeographic study to uncover the virus dispersal patterns across the country.

The irregular timing and spatial variation in zoonotic arbovirus spillover from vertebrate hosts to humans and livestock present challenges to predicting their occurrence from year to year and within their broader geographic range, compromising effective prevention and control strategies. The objective of this study was to quantify effects of landscape composition and configuration and dynamic temperature and precipitation values on the 2018 spatiotemporal distribution of eastern equine encephalitis virus (EEEV) (Togaviridae, Alphavirus) and West Nile virus (WNV) (Flaviviridae, Flavivirus) sentinel chicken seroconversion in northeastern Florida using Earth Observation (EO) data and a modeling framework that incorporated joint spatial and temporal effects. We investigated environmental effects using Bernoulli generalized linear mixed effects models (GLMMs) including a site level random effect, and then added spatial random effects and spatiotemporal random effects in subsequent runs. Models were executed using integrated nested Laplace approximation (INLA) and a stochastic partial differential equation (SPDE) approach in R-INLA. GLMMs that included a spatiotemporal random effect performed better relative to models that included only spatial random effects and better than non-spatial models. Results indicated strong spatiotemporal structure in seroconversion for both viruses, but EEEV exhibited more punctuated and compact structure at the beginning of the sampling season, while WNV exhibited more gradual and diffuse structure across the study area toward the end of the sampling season. Percentage of cypress/tupelo wetland land cover within 3500 m of coop sites and edge density of forest land cover within 500 m had a strong positive effect on EEEV seroconversion, while the best fitting model for WNV was the intercept only model with spatiotemporal random effects. Lagged temperature and precipitation variables included in our study did not have a strong effect on seroconversion for either virus when accounting for temporal autocorrelation, demonstrating the utility of capturing this structure to avoid Type I errors. Predictive accuracy on out-of-sample data for EEEV seroconversion demonstrates the potential to develop a temporally dynamic framework to predict arbovirus transmission.

Coastal urbanisation is a widespread phenomenon throughout the world and is often linked to increased erosion. Small Pacific islands are not spared from this issue, which is of great importance in the context of climate change. The French Polynesian island of Bora Bora was used as a case study to investigate the historical evolution of its coastline classification and position from 1955 to 2019. A time series of very-high-resolution aerial imagery was processed to highlight the changes of the island’s coastline. The overall length of natural shores, including beaches, decreased by 46% from 1955 to 2019 while man-made shores such as seawalls increased by 476%, and as of 2019 represented 61% of the coastline. This evolution alters sedimentary processes: the time series of aerial images highlights increased erosion in the vicinity of seawalls and embankments, leading to the incremental need to construct additional walls. In addition, the gradual removal of natural shoreline types modifies landscapes and may negatively impact marine biodiversity. Through documenting coastal changes on Bora Bora through time, this study highlights the impacts of man-made structures on erosional processes and underscores the need for sustainable coastal management plans in French Polynesia.

The endocannabinoid system (eCB) began to be studied from the identification of the molecular structures present in the cannabis sativa plant. The ECS is constituted of cannabinoid receptors, endogenous ligands and all the associated enzymatic apparatus responsible for maintaining homeostasis. Several physiological effects of cannabinoids are exerted through interaction with various receptors such as CB1 and CB2 receptors, vanilloid receptors, and the recently discovered [GPCRs (GPR55, GPR3, GPR6, GPR12 and GPR19). Endogenous ligands such anandamide and 2-arachidonoylglycerol might modulate these receptors. eCB has proved to play a critical role in some human diseases and has been extensively studied due to its wide therapeutic potential and because it is a promising target for the development of new drugs. Phytocannabinoids and synthetic cannabinoids have shown varied affinities to eCB, which are relevant to the treatment of various diseases. They may also have potential as lead compounds in the development of cannabinoid-based pharmaceuticals for a variety of diseases. Furthermore, Integrative and Complementary Health Practices (ICHP) appear to influence the endocannabinoid system through modulation. This review will show a description of ECS components and discuss how phytocannabinoids, other exogenous compounds, and PICS may operate the eCB balance.

Weather surveillance radars routinely detect smoke of various origin. Of particular significance to the meteorological community are wildfires in forests and/or prairies. For example, one responsibility of the National Weather Service in the USA is to forecast fire outlooks as well as to monitor wild fire evolution. Polarimetric variables have enabled relatively easy recognitions of smoke plumes in data fields of weather radars. Presented here are the fields of these variables from smoke plumes caused by grass fire, brush fire, and forest fire. Histograms of polarimetric data from plumes contrast these three cases. Most of the data are from the polarimetric Weather Surveillance Radar 1988 Doppler (WSR-88D aka Nexrad, 10 cm wavelength) hence the wavelength does not influence these comparisons. Nevertheless, in one case simultaneous observations of a plume by the operational Terminal Doppler Weather Radar (TDWR, 5 cm wavelength) and a WSR-88D is used to infer backscattering characteristic and hence sizes of dominant contributors to the returns. In addition, comparisons with observations by other investigators of plumes from urban area but at a 5 cm wavelength are made. To interpret some measurements Computational Electromagnetics (CEM) tools are applied.

Social customer relationship management (SCRM) is a new philosophy influencing the relationship between customer and organization, where the customer gets opportunity to control relationship through social media. The paper aims on (a) identification of current level of SCRM and also on (b) influence of basic organizational characteristics on SCRM level. The data were gathered through the questionnaire distributed in 362 organization headquartered in the Czech Republic. The questionnaire comprised 54 questions focusing on the significance of marketing and CRM practices, establishing a relationship with the customer, online communities, the use of social media in marketing, and acquiring and managing information. The majority of questions were scalable and used typical five-level Likert scale. Results showed that larger firms more often set up their own online communities and manage them strategically, moreover they are able to manage information better. Contrariwise, small sized organizations use social networks as a way to establish communication with the customer more than large sized entities. Use of social media for marketing purposes is significantly higher in organizations oriented on consumer markets than on business markets.

"Suero costeño" a type of sour cream, is a traditional dairy product made mainly in the Colombian Caribbean region and has a variety of uses. The objective was to characterize the physicochemical and rheological properties of “suero costeño” produced in department of Córdoba-Colombia. Samples of " suero costeño " were obtained from local producers, characterized physicochemically (protein, fat, crude fiber, moisture, ash, carbohydrates, chlorides, pH and acidity), and rheologically (stationary tests), adjusting their behavior to the power-law model. The results show great variability in the physicochemical characteristics of the “suero costeño” made by the different artisanal producers, classifying it as a full-fat sour cream or light sour cream, and values of protein, pH and acidity similar to similar traditional dairy products from other countries, such as Reindeer sour cream and Curd or cottage cheese. “Suero costeño” can be classified as a pseudoplastic fluid and depending on the raw materials used and the production process, some present thixotropy, which may be the product of interactions between proteins and fats, which cause changes in the internal structure. Due to this great variability in its physicochemical and rheological characteristics, it is necessary to standardize the process of producing to improve the marketing of this Colombian culinary product.

Environmental degradation leads to a totally unsustainable food system. In addition to this is-sue, the consumption of foods that improve people's health and well-being is recommend-ed. These guidelines create new challenges and the demand for alternatives to meet these needs in the short term. One of the alternatives is undoubtedly the use of by-products of winemaking, namely in the form of grape pomace flour (GPF), which is obtained in a totally sustainable way, requires no further water consumption or agricultural land, and is an ingredient that boasts all the characteristics that meet the circular economy and has colossal potential in promoting nutrition and healthy eating. To verify the benefits of using the Touriga Nacional and Arinto (Vitis vinifera L.) flour varieties, analytical determinations were made to identify and quantify different components, such as nitrogen and extractable phosphorus, ash, moisture, proteins, fats, dietary fibers, total sugars, and phenolic content. GPF could become a valuable ingredient due to its nutritional quality and high content in various polyphenols namely flavonoids and pyranoanthocyanins.

This study aimed to simulate dynamic irrigation management zones (MZs) in two maize fields for a variable rate hose-reel fertigation machine (VRFM) with a 4-section boom control. Soil moisture content was measured from nine and four soil moisture sensors in Field 1 (8.2 ha) and Field 2 (2.5 ha), respectively in different dates during the 2022 crop season. Three- and five-MZs scenarios were simulated per irrigation and the theoretical maps were processed for implementation. The application maps fitted to the VRFM showed significant spatiotemporal variations in irrigation requirements. For instance, in Field 1, 3-MZs modelling showed that the areas requiring High (H), Medium (M), and Low (L) level irrigation on July 21 were 1.60, 4.84, and 1.85 ha, respectively, whereas the farmer applied uniform rate over the whole field. H level sub-areas ranged between 1.22 ha (July 25) and 3.25 ha (July 7), showing a coefficient of variation (CV) of 43.32% for the 3-MZs, whereas H level sub-areas for 5-MZs varied from 0.41 ha (July 2) to 1.49 ha (July 7) with a CV value of 48.84%. High levels of within-field variability can be addressed using precise and dynamic irrigation MZs fitted to the irrigation technology used.

Traffic congestion and frequent traffic accidents have become main problems affecting urban traffic. Effective location prediction of vehicle trajectory can help alleviate traffic congestion, reduce the occurrence of traffic accidents, and optimize the urban traffic system. Vehicle trajectory is closely related to the surrounding Points of Interest (POI). POI can be considered as the spatial feature and can be fused with trajectory points to improve prediction accuracy. A Local Dynamic Graph Spatiotemporal- Long Short-Term Memory (LDGST-LSTM) is proposed in this paper to extract and fuse the POI knowledge and realize next location prediction. POI semantic information is learned by constructing the traffic knowledge graph, and spatial and temporal features are extracted by combining Graph Attention Network (GAT) and temporal attention mechanism. Moreover, the weights of POI that influence location prediction are visualized to improve the interpretability of the proposed model. The effectiveness of LDGST-LSTM is verified on two datasets, including Chengdu taxi trajectory data in October 2018 and August 2014. The accuracy and robustness of the proposed model are significantly improved compared with the benchmark models.

Humans can recombine thousands of different facial expressions. This variability is due to the ability to voluntarily or involuntarily modulate emotional expressions, which, in turn, depends on the existence of two anatomically separate pathways. The Voluntary (VP) and Involuntary (IP) pathways mediate the production of posed and spontaneous facial expressions, respectively, and might also affect the left and right sides of the face differently. This is a neglected aspect in the emotion literature, where posed expressions instead of genuine expressions are often used as stimuli. Two experiments with different induction methods were specifically designed to inves-tigate the unfolding of spontaneous and posed facial expressions of happiness along the facial vertical axis (left, right) with a high-definition 3D optoelectronic system. The results showed that spontaneous expressions were distinguished from posed facial movements as revealed by relia-ble spatial and speed key kinematic patterns in both experiments. Moreover, VP activation pro-duced a lateralization effect: compared with the felt smile, the posed smile involved an initial acceleration of the left corner of the mouth, while an early deceleration of the right corner oc-curred in the second phase of the movement, after the velocity peak.

The ability to handle spatiotemporal information makes contribution for improving the prediction performance of machine RUL. However, most existing models for spatiotemporal information processing are not only complex in structure but also lack adaptive feature extraction capabilities. Therefore, a lightweight operator with adaptive spatiotemporal information extraction ability named Involution GRU (Inv-GRU) is proposed for aero-engine RUL prediction. Involution, the adaptive feature extraction operator, is replaced by the information connection in the gated recurrent unit for obtaining the adaptively spatiotemporal information extraction ability and reducing the parameters. Thus, Inv-GRU can well extract the degradation information the of aero-engine. Then for RUL prediction task, the Inv-GRU based deep learning (DL) framework is firstly constructed, where features extracted by Inv-GRU and several human-made features are separately processed to generate the health indicators (HIs) from multi-raw data of aero-engines. Finally, fully connection layers are adopted are adopted to reduce dimension and regress RUL based on the generated HIs. By applying the Inv-GRU based DL framework to the Commercial Modular Aero Propulsion System Simulation (C-MAPSS) datasets, successful predictions of aero-engines RUL have been achieved. Comparative analysis reveals that the proposed model exhibits superior overall prediction performance compared to recent public methods.

Spatiotemporal dynamics of the atmospheric kinetic energy and its components caused by the ordered and turbulent motions of air masses are estimated from minisodar measurements of three velocity vector components and their variances within the lowest 5–200 m layer of the atmosphere, with a particular emphasis on the turbulent kinetic energy. The layered structure of the total atmospheric kinetic energy has been established. From the diurnal hourly dynamics of the altitude profiles of the turbulent kinetic energy (TKE) retrieved from minisodar data, four layers are established by the character of the altitude TKE dependence, namely, the near-ground layer, the surface layer, the layer with a linear TKE increase, and the transitive layer above. In the first layer, the most significant changes of the ТКЕ were observed in the evening hours. In the second layer, no significant changes in the TKE values were observed. A linear increase in the TKE values with altitude was observed in the third layer. In the fourth layer, the TKE slightly increased with altitude and exhibited variations during the entire observation period. The altitudes of the upper boundaries of these layers depended on the time of day. The MKE values were much less than the corresponding TKE values, they did not exceed 50 m²/s². From two to four MKE layers were distinguished based on the character of its altitude dependence. The two-layer structures were observed in the evening and at night (under conditions of the stable atmospheric boundary layer). In the morning and daytime, the four-layer MKE structures with intermediate layers of linear increase and subsequent decrease in the MKE values were observed. Our estimates demonstrated that the ТКЕ contribution to the total atmospheric kinetic energy considerably (by a factor of 2.5–3) exceeded the corresponding МКЕ contribution.

With the advancement of urbanization in China, effective control of pollutant emissions and air quality have become important goals in current environmental management. Nitrogen dioxide (NO2), as a precursor of tropospheric ozone and fine particulate matter, plays a significant role in atmospheric chemistry research and air pollution control. However, the uneven ground monitoring stations and low temporal resolution of polar-orbiting satellites set challenges for accurately assessing near-surface NO2. To address this issue, a spatiotemporal refined NO2 retrieval model was established for China using the geostationary satellite Himawari-8. The spatiotemporal characteristics of NO2 were analyzed and its contribution factors were explored. Firstly, seven Himawari-8 channels sensitive to NO2 were selected by using the forward feature selection based on information entropy. Subsequently, a 2DCNN-LSTM network model was constructed, incorporating the selected channels and meteorological variables as retrieval factors to estimate hourly NO2 in China from March 2018 to February 2020 (with a resolution of 0.05°, per hour). The performance evaluation demonstrated that the full-channel 2DCNN-LSTM model had good fitting capability and robustness (R2=0.74, RMSE=10.93), and further improvements were achieved after channel selection (R2=0.87, RMSE=6.84). The 10-fold cross-validation results indicated that the R2 between retrieval and measured values was above 0.85, the MAE was within 5.60, and the RMSE was within 7.90. R2 varied between 0.85 and 0.90, showing better validation at mid-day (R2=0.89) and in spring and fall transition seasons (R2 =0.88 and R2 =0.90). To investigate the cooperative effect of meteorological factors and other air pollutants on NO2, statistical methods (Beta coefficients) were used to test the factor interpretability. Meteorological factors as well as other pollutants were analyzed. From a statistical perspective, PM2.5, Boundary Layer Height, and O3 were found to have the largest impacts on near-surface NO2, with each standard deviation change in these factors leading to 0.28, 0.24, and 0.23 in standard deviations of near-surface NO2, respectively. Findings of the study contribute to a comprehensive understanding of the spatiotemporal distribution of NO2 and provide a scientific basis for formulating targeted air pollution policies.

Baía de Todos os Santos is the second largest bay in Brazil and is home to important ecosystems, including estuarine systems and mangroves. However, studies on the seasonal variability of its soil properties and composition are still scarce. For this study, soil and leaf samples were seasonally collected from mangrove forests at four sites (Cacha Prego, Ponta Grossa, Ilha de Maré, and Pitinga), which are representative of different environmental conditions within the BTS. Soil physicochemical properties, soil composition and partition of Fe forms were determined, and analysis of minerals by Scanning Electron Microscope, was performed on soil samples. Isotopic ratios (δ13C, δ15N) were also determined on soil and leaf samples. Soils showed significant spatial and temporal changes affecting both their properties (pH, Eh) and their composition (TOC, pyrite and Fe oxyhydroxide contents). Clear spatial changes were observed in redox potential, significantly affecting the concentrations of the different geochemical forms of Fe, particularly the concentrations of crystalline oxyhydroxydes and pyrite in one of the studied sites. In three of the study sites, pyrite crystals showed clear evidence of degradation associated with sandy soils. Finally, δ13C and N/C ratios in soils seem to suggest a mixed origin of organic matter.

Since the early 1990s, the European (ESA) and Italian (ASI) space agencies have managed and distributed a huge amount of satellite-recorded SAR data to the research community and private industries. Moreover, the availability of advanced cloud computing services implementing different multi-temporal SAR interferometry techniques allows the generation of deformation time series from massive SAR images. We exploit the information provided by a large PS dataset to determine the temporal trend of ground deformation and the relative deformation rate with millimetric accuracy to analyse the spatial and temporal distribution of land subsidence induced by water pumping from a deep confined aquifer in the Northern Valle Umbra Basin (Central Italy), exploiting 24 years of Permanent Scatterers – Interferometric SAR data archives. The SAR images were acquired between 1992 and 2016 by satellite ERS1/2, ENVISAT and Sentinel 1 ESA missions, and the COSMO-SkyMed ASI mission). We observe ground velocities and deformation geometries between 1992 and 2016, with displacements of more than 70 cm and velocities of up to 55 mm/yr and the results suggest that the shape and position of the surface ground displacement are controlled by the fault activity hidden under the valley deposits.

Differences in fish assemblages’ structure and their relation with environmental variables (due to the variations in sampled seasons, habitats, and zones), were analyzed in two adjacent estuaries on the north Pacific coast of Mexico. Environmental variables and fish catches were registered monthly between August 2018 and October 2020. Multivariate analyses were conducted to define habitats and zones based on their environmental characteristics, and the effect of this variability on fish assemblages’ composition, biomass, and diversity (α and β) was evaluated. A total of 12,008 fish individuals of 143 species were collected using different fishing nets. Multivariate analyses indicated that fish assemblages’ structure was different between zones due to the presence, height, and coverage of distinct mangrove species. Additionally, factors such as depth and salinity showed effects on fish assemblages’ diversity (α and β-nestedness), which presented higher values in the ocean and remained similar in the rest of the analyzed zones and habitats. These results and the differences in species replacement (β-turnover) indicate the singularity of fish assemblages at estuaries (even in areas very close to the ocean), and the necessity to establish local management strategies for these ecosystems.