In this paper the dynamics of spatially extended infected phytoplankton with the Holling type II functional response and logistically growing susceptible phytoplankton system is studied. The proposed model is an extension of temporal model available [6], in spatiotemporal domain. The reaction diffusion system exhibits spatiotemporal chaos in phytoplankton dynamics. This is particularly important for the spatially extended systems that are studied in this paper as they display a wide spectrum of ecologically relevant behavior, including chaos. In this system stability of the system is studied with respect to disease contact rate and the growth fraction of infected phytoplankton indirectly rejoin the susceptible phytoplankton population. The results of numerical experiments in one dimension and two dimensions in space as well as time series in temporal models are presented using MATLAB simulation. Moreover, the stability of the corresponding temporal model is studied analytically. Finally, the comparison of the three types of numerical experimentations are discussed in conclusion.

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.

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.

With the rapid development of network science, Turing pattern on complex networks has attracted extensive attention from researchers. In this paper, we focus on spatial patterns in multiplex ER (Erdös-Rényi) random networks, taking the predator-prey model with Allee effect and hyperbolic mortality as an example. In theory, the threshold condition for generating Turing pattern is given using the Turing instability theory of multiplex networks. Numerically, we design relevant experiments to explore the impact of network topology on Turing pattern. The factors considered include model parameters, diffusion rate, average degree of the network, and differences in the average degree of different layers. The results indicate that the importance of diffusion rate and network average degree for Turing pattern is affirmed on the single-layer network. For multiplex networks, the differentiation of average degrees in different layers controls the generation of Turing pattern, which is not affected by the diffusion rates of the two populations. More interestingly, we observe the switching of Turing pattern and spatiotemporal pattern. We believe that these findings contribute to a better understanding of self-organization on complex networks.

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.

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.

Motivated by the fact that the restrictive conditions for a Turing instability are relaxed in sub- diffusive regime, we investigate the effects of subdiffu- sion in the predator−prey model with toxins under the homogeneous Neumann boundary condition. First, the stability analysis of the corresponding ordinary differ- ential equation is carried out. From this analysis, it fol- lows that stability is closely related to the coefficient of toxicity. In addition, the temporal fractional derivative does not systematically widen the range of parameters to maintain a point in the stability domain. Further- more, we derive the condition which links the Turing instability to the coefficient of toxicity in the subdif- fusive regime. System parameters are varied in order to test our mathematical predictions while comparing them to ecological literature. It turns out that the mem- ory effects, linked to the transport process can, depend- ing on the parameters, either stabilize an ecosystem or make a completely different configuration.

Pretreatment of cells with proteolysis inhibitors diminished intensity and changed shape of DNICs specific EPR signal in a treatment time-dependent manner. The level of DNIC formation was significantly influenced by the presence of protein degradation products. Interestingly, formation of HMWDNICs depended on the availability of LMWDNICs. The extent of glutathione involvement in the in vivo formation of DNICs is minor yet noticeable, aligning with our prior research findings.

Semisolid casting can provide excellent castings, but the nature of the pore-forming mechanisms has not been properly clarified. In the current communication, it was suggested that hydrogen precipitated during slurry making might have a decisive role in the formation of both gas and shrinkage porosity. Intensive stirring at the end of the slurry making process may act as a degassing step. Without the intense stirring, structures of primary slurry particles form around the hydrogen pores, strongly affecting pore formation and feeding during the intensification stage.

Background: RSV, or respiratory syncytial virus, is a deadly condition that is present all over the world today. The infection is initially contained in the lower respiratory tract without systemic transmission. The objective of the study: Bioinformatics was used in Egypt to create an mRNA vaccine against the Respiratory syncytial virus (RSV). Methodology: In the present screening experimental study, a lipid nanoparticles vaccine of mRNA of the surface fusion protein of Respiratory syncytial virus was manufactured. The present vaccine delivery system was lipid nanoparticles with a particle size of approximately 90 nanometres, manufactured by the hot micro-emulsion method. In stages 1 and 2 of clinical trials, the immunogenicity of the current mRNA RSV vaccine was evaluated. Results: The current vaccine demonstrated 81% immunogenicity in animal testing, but only 69% in stages 1 and 2 of clinical trials. Its side effects were manageable. The results persisted for a while. In the current trial, the vaccination proved effective as a preventative measure against RSV infection. The current vaccination lacked antibody-dependent enhancement, which causes non-protective antibodies to develop. These non-neutralizing antibodies exacerbate infection by activating cytokines and complement cascade through the formation of immune complexes or enhancement of the virus entry and replication in the host cells. On the other hand, the current RSV mRNA vaccine of the surface fusion protein consequent on the production of powerful neutralizing antibodies with prolonged immunity especially to infants and elderly candidates who received the optimal dosage regimen.

Some peptide-based drugs including oxytocin, vasopressin, ziconotide, pramlintide, nesiritide, and octreotide, contain one intramolecular disulfide bonds. A novel and reusable monodispersed silica nanosphere-supported Pt(IV) complex (SiO2@TPEA@Pt(IV)) was synthesized via a four-step procedure and used for formation of intramolecular disulfide bonds in peptides. TEM and chemical mapping results for the Pt(II) intermediates and for SiO2@TPEA@Pt(IV) show that the silica nanospheres possess a monodisperse spherical structure and contain uniformly distributed Si, O, C, N, Cl, and Pt. The valence state of Pt on the silica nanospheres was characterized by XPS. The Pt(IV) loaded on SiO2@TPEA@Pt(IV) was 0.15 mmol/g, as determined by UV-vis spectrometry. Formation of intramolecular disulfides in six dithiol-containing peptides of variable lengths by use of SiO2@TPEA@Pt(IV) was investigated and the relative oxidation yields were determined by HPLC. In addition, peptide 1 (Ac-CPFC-NH2) was utilized to study the reusability of SiO2@TPEA@Pt(IV). No significant decrease in the relative oxidation yield was observed after ten reaction cycles. Moreover, the structure of SiO2@TPEA@Pt(IV) after being used ten cycles was determined to be similar to its initial one, demonstrating the cycling stability of the complex.

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 rapid increase in metabolic diseases occurred in the last three decades in both industrialized and developing countries has been related to the rise in sugar-added foods and sweetened beverages consumption. An emerging topic in the pathogenesis of metabolic diseases related to modern nutrition is the role of Advanced Glycation Endproducts (AGEs). AGEs can be ingested with high temperature processed foods, but also endogenously formed as consequence of a high dietary sugars intake. Animal models of high sugars consumption, in particular fructose, have reported AGEs accumulation in different tissues in association with peripheral insulin resistance and lipid metabolism alterations. The in vitro observation that fructose is one of the most rapid and effective glycating agent when compared to other sugars has prompted the investigation of the in vivo fructose-induced glycation. In particular, the widespread employment of fructose as sweetener has been ascribed by many experimental and observational studies for the enhancement of lipogenesis and intracellular lipid deposition. Indeed, diet-derived AGEs have been demonstrated to interfere with many cell functions such as lipid synthesis, inflammation, antioxidant defences, and mitochondrial metabolism. Moreover, emerging evidences also in humans suggest that this impact of dietary AGEs on different signalling pathways can contribute to the onset of organ damage in liver, skeletal and cardiac muscle, and brain, affecting not only metabolic control, but global health. Indeed, the here reviewed most recent reports on the effects of high sugars consumption and diet-derived AGEs on human health suggest the need to limit the dietary sources of AGEs, including added sugars, to prevent the development of metabolic diseases and related comorbidities.

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.

Hybrid materials are a recent addition in the field of Restorative Dentistry for computer-assisted design/ computer-assisted manufacturing (CAD/CAM) indirect restorations. The long–term clinical success of modern dental restorative materials follows a multifactorial pattern. Among the characteristics, affecting the longevity of a restoration, mechanical properties and physicο – chemical interactions are of utmost importance. While numerous researchers constantly evaluate the mechanical properties, the biological background of resin–based CAD/CAM biomaterials is scarcely investigated and, therefore, less described in the literature. This review aims to analyze the biofilm formation on the surfaces of novel hybrid, resin–based CAD/CAM materials and evaluate the methodological protocols followed to assess microbial growth. It is demonstrated that the surface structure, the composition and the finishing and polishing procedures on the surface of a dental restorative material influence the initial bacterial adhesion; however most studies focus on in vitro protocols, whereas in vivo and/or in situ research of microbiomics in CAD/CAM restorative materials is lacking, obstructing in that manner the accurate understanding of the bioadhesion phenomenon in the oral cavity.

Spinocerebellar ataxia type 3 is a neurodegenerative disease caused by an abnormal expansion of CAG repeats in the disease gene ATXN3, leading to prolonged polyglutamine (polyQ) tracts in the respective protein ataxin-3. The polyQ-expanded protein forms polyQ-containing aggregates in several brain regions which leads to neuronal cell loss. Autophagy is thought to play a significant role in clearing these polyQ-containing protein aggregates. Therefore, the autophagy mechanism was investigated in SCA3 with focus on the autophagic protein p62/sequestosome-1. Human and mouse RNA sequencing data were analyzed to determine RNA expression level of autophagic genes. Additionally, autophagy was studied in the SCA3 304Q knock-in mouse model and through several cell culture experiments using HEK-293T cells transfected with ATXN3 of differ-ent polyQ lengths. For cell culture experiments, autophagy was induced with rapamycin treat-ment, proteasomal degradation was blocked with MG132 and degradation of autophagic pro-teins was investigated using cycloheximide treatment. Here, we report an increased autophagy impairment with SCA3 disease progression seen in HEK-293T cells transfected with ATXN3 plasmid with expanded polyQ tracts, higher aged 304Q-knock-in mice, or human post-mortem brain material. Furthermore, co-localized aggregation of the autophagic protein p62 and the dis-ease protein ATXN3 was observed in the course of SCA3 disease. Therefore, we suggest a signifi-cant role for p62 in aggregate formation seen in the neurodegenerative disease SCA3.

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.

Arboviruses are infections caused by arboviruses that may be either symptomatic or asymptomatic, according to individuals' resistance and immune response, which dietary patterns can influence. Thus, this study aimed to investigate the possible association between the occurrence of clinical manifestations of arboviruses and the dietary pattern of the population studied. The study was conducted in a rural population in the metropolitan area of Belém, Pará State, Brazil. The sampling consisted of 95 individuals during a febrile outbreak. Two investigations were conducted: clinical-epidemiological-dietary and laboratory investigation based on blood samples taken for arbovirus analysis. Out of the 95 individuals studied, more than half (57.89%) showed clinical manifestations. Following the laboratory serology (HI and IgM ELISA) analyses, viral isolation in C6/36 cells, and viral genome detection (RT-qPCR), the final diagnosis of the cases was 47.37% Oropouche Fever, 2.11% Oropouche Fever and Chikungunya Fever, and 1.05% Mayaro Fever. Regarding dietary pattern, as for the comparison analyses, statistical significance was observed between dietary pattern and classification regarding the presence of symptoms (p<0.05); after the correspondence analysis, symptomatic cases were more associated with a bad dietary pattern, while asymptomatic cases were more associated with a good dietary pattern.

Induction heating is a fast, reproducible, and efficient heating method used in various manufacturing processes. However, there is no established additive manufacturing (AM) process based on induction heating using wire as feedstock. This study investigates a novel approach to AM based on inductive heating, where a steel wire is melted and droplets are detached periodically using a two-winding induction coil. The process parameters and energy input into the droplets are characterized. The induction generator exhibits sluggish response to the excitation voltage, resulting in a lag in the coil current. The process is captured using a high-speed camera, revealing regular droplet formation and uniform size and shape when operated within an appropriate process window. Larger drops and increased spatter formation occur outside this window. The proposed method allows for the production of droplets with almost spherical shapes. Further analysis and characterization of droplet formation and energy input provide insights into process optimization and overall efficiency.

Our results demonstrated that SWT stimulates osteoblastogenesis and increase the cell number of osteoblasts, suggesting positive regulatory effects on osteoblast differentiation. However, the effect of SWT on bone formation need further examination, since the expression of alp gene is downregulated. On the other hand, SWT appears to negatively regulate osteoclast differentiation and bone resorption, as number of osteoclasts and the expression of critical bone resorptive genes are all downregulated. Collectively, SWT might change the equilibrium of bone remodeling and increase the bone mass. Our data provided supportive evidences that this medicine formulation can be applied to treat osteoporosis or bone destructive diseases.

Waste glycerol can be subjected to various processing operations, including purification and re-fining, to obtain glycerol of appropriate purity. In addition, alternative methods of utilising waste glycerol are also being sought, e.g. by converting it into other valuable chemical products or biofuels. Therefore, various technologies are being developed to utilise this type of waste effectively and sustainably. The production of value-added products from waste glycerol is an important issue that determines the improvement of the economic viability of biofuel production and corresponds to the model of a waste-free and emission-free circular economy. This paper characterised the mechanisms and evaluated the efficiency of existing methods of microbiological utilisation of waste glycerol into liquid biofuels, including biodiesel, bioethanol and biobutanol, and identified further directions for the production of value-added products. In addition, a bibliographical analysis of publications re-lated to the production of liquid fuels and economically valuable products from glycerol was carried out, the progress of research and application work was assessed and directions for future research were identified.

Children are inherently curious about everything they encounter, making the early years a perfect time for STEAM (science, technology, engineering, arts, and math) investigations. An outdoor learning environment can influence STEAM concept formation of preschoolers with intentional design that offer STEAM learning affordances. Despite the rising interest in early STEAM education, there is still limited literature on how the outdoor environment may influence STEAM learning behaviors of preschoolers (3-5 years old). This scoping review intends to evaluate the existing knowledge regarding the physical factors that contribute to STEAM learning affordances in an outdoor environment for children aged 3 to 5. The review included studies from the last twenty years. This scoping review was conducted in accordance with the criteria outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). For this scoping review, 843 citations were discovered across four databases (JSTOR, Scopus, EBSCOhost, and Web of Science), ProQuest, and Google Scholar, and 31 articles were considered eligible for inclusion. Through the synthesis of information from those 31 studies, a list of STEAM learning behaviors of children and STEAM activity-supportive settings were identified that may positively influence preschoolers' STEAM concept development.

Consumption of refined foods and beverages high in sugar make the teeth susceptible to the formation of biofilm, and lead to dental caries and diseases of the oral cavity such as periodontitis and periodontal disease. The aim of the present study was to determine the ability of selected probiotics to inhibit growth and biofilm formation by the cariogenic bacterium Streptococcus mutans in vitro. We screened strains of latic acid bacteria (LAB) (n=120) from the Bioresources Collection and Research Center (BCRC), saliva of healthy adults and infant stool. The antimicrobial activity of LAB in vitro was evaluated by agar spot culture and co-culture of the S. mutans strains. We determined the effect of heating and dilution factors (2- and 4-fold) on the antagonistic activity of LAB. Antagonistic substances in the spent culture suspensions (SCS) of LAB were precipitated by extraction with ammonium sulphate and chloroform to characterise the protein and lipophilic fractions. Results of co-culturing show that the SCS of the three LAB strains (Lactobacillus pentosus 13-1, 13-4 and Lactobacillus crispatus BCRC 14618) subjected to heat treatment showed significantly high antimicrobial activity. We found that substances produced by L. pentosus 13-4 which have the potential to exhibit antimicrobial properties might be lipophilic proteins. Additionally, we infer that the mechanism of reducing biofilm formation by Lactobacillus strains is associated with sucrose-dependent cell–cell adhesion and the gtfC level of glucosyltransferases (Gtfs) in the biofilm. Native LAB strains screened in our study may be used in chewing gums and other processed foods for preventing tooth decay.

A hallmark of Alzheimer’s disease (AD) are the proteinaceous aggregates formed by the amyloid-beta peptide (Aβ) that is deposited inside the brain as amyloid plaques. The accumulation of aggregated Aβ may initiate or enhance pathologic processes in AD. According to the amyloid hypothesis any agent that has the capability to inhibit Aβ aggregation and/or destroy amyloid plaques represents a potential disease modifying drug. In 2023, a humanized IgG1 monoclonal antibody (lecanemab) against the Aβ soluble protofibrils was approved by US FDA for AD therapy thus providing compelling support to the amyloid hypothesis. To acquire a deeper insight on the in vivo Aβ aggregation, various animal models, including aged herbivores and carnivores, non-human primates, transgenic rodents, fish and worms are widely exploited. This review is based on the recent data obtained using transgenic animal AD models and presents experimental verification of the critical role in Aβ aggregation seeding of the interactions between zinc ions, Aβ with the isomerized Asp7 (isoD7- Aβ) and the α4β2 nicotinic acetylcholine receptor.

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.

Background/objectives: The health benefits of resistant starch are well known, but there have not been many studies available documenting the effect of basmati rice products containg resistant starch upon blood glucose level and lipid profile in vivo efficacy. Methods: Common cooking methods were used to prepare basmati rice products including two boiling methods viz. boiling 1 (boiling by absorption), boiling 2 (boiling in extra amount of water), frying and pressure cooking. The cooked rice were held at various temperatures and times: it was made fresh (T1), kept at room temperature (20–22°C) for 24 h (T2), kept at 4°C for 24 h (T3), and then reheated after being kept at 4°C for 24 h(T4). Next, the products' proximate composition, total dietary fibre (soluble and insoluble), resistant starch (RS), and In vitro starch digestion rate (rapidly and slowly digested starch) were examined. The effect of RS on blood glucose and lipid profile were measured in humans and rats. Histopathological study of liver and pancreas in rats were also observed. Results: The basmati rice prepared by boiling 1 and stored with T3 was found more effective to control blood glucose and lipid profile. Similarly in rats, the blood glucose level, cholesterol, triglycerides and LDL were reduced about 29.7, 37.9, 31.3 and 30.5% respectively, after consumption of basmsti rice prepared by boiling 1 and stored at T3. Conclusion: Rice products stored at 4⁰C have a high amount of resistant starh, insoluble dietary fibre, slowly digestible starch and low glycemic index. Thus helps to inhibit glycogen and lipid synthesis.

The static formation temperature (SFT) is required to determine the thermophysical properties and production parameters in geothermal and oil reservoirs. However, the SFT is not easy to be obtained by both experimental and physical methods. In this paper, a mathematical approach to predicting SFT based on a new model describing the relationship between bottom hole temperature (BHT) and shut-in time was proposed. The unknown coefficients of the model were derived from least squares fit by Particle Swarm Optimization (PSO) algorithm. Besides, the ability to predict SFT based on a few BHT data (such as first 3, 4, or 5 ones of a data set) was evaluated. The accuracy of the proposed method to predict SFT was testified with a deviation percentage less than ±4% and high values of regression coefficient R² (>0.98). The proposed method could be used as a practical tool to predict SFT in both geothermal and oil wells.

Dietary patterns were recently applied to examine the relationship between eating habits and prostate cancer (PC) risk. While the associations between PC risk with glycemic index and Mediterranean score have been reviewed, no meta-analysis is currently available on dietary patterns defined by “a posteriori” methods. Search was carried out (PubMed, Web of Science) to identify studies reporting the relationship between dietary patterns and PC risk. Relevant dietary patterns were selected and the risk estimated were calculated by a random-effect model. Multivariable-adjusted odds ratios (ORs) for a 1st-percentile increase in dietary pattern score were combined by a dose response meta-analysis. 12 observational studies were included in the meta-analysis which identified “Healthy pattern” and “Western pattern”. The Healthy pattern was not related to PC risk (OR=0.96; 95% CI: 0.88-1.04) while the Western pattern significantly increased it (OR=1.34; 95% CI: 1.08-1.65). In addition, a “Carbohydrate pattern”, identified in four articles, was positively associated with a higher PC risk (OR=1.64; 95% CI: 1.35-2.00). A significant linear trend between the Western (p=0.011) and the Carbohydrate (p=0.005) pattern and the increment of PC risk was observed. The small numbers of studies included suggest that further investigations are necessary to support these findings.

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.

The treatment of the bulky Rind-based dibromosilanes, (Rind)2SiBr2 (2) [Rind = 1,1,7,7-tetra-R1-3,3,5,5-tetra-R2-s-hydrindacen-4-yl: EMind (a: R1 = Et, R2 = Me) and Eind (b: R1 = R2 = Et)], with two equivalents of tBuLi in Et2O at low temperatures resulted in the formation of blue solutions derived from the diarylsilylenes, (Rind)2Si: (3). Upon warming the solutions above −20 °C, the blue color gradually faded, accompanying the decomposition of 3 and yielding the cyclic hydrosilanes (4) via intramolecular C−H bond insertion at the Si(II) center. The molecular structures of the bulky Eind-based 3b and 4b were confirmed by X-ray crystallography. Thus, at −20 °C, blue crystals were formed (Crystal-A), which were identified as mixed crystals of 3b and 4b. Additionally, colorless crystals of 4b as a singular component were isolated (Crystal-B), whose structure was also determined by an X-ray diffraction analysis. Although the isolation of 3 was difficult due to their thermally-labile nature, their structural characteristics and electronic properties were discussed based on the experimental findings complemented by computational results. We also examined the hydrolysis of 3b to afford the silanol, (Eind)2SiH(OH) (5b).

We first explore negative-ion formation in fullerenes C44, C60, C70, C98, C112, C120, C132 and C136 through low-energy electron elastic scattering total cross sections calculations using our Regge-pole methodology. Water oxidation to peroxide and water synthesis from H₂ and O₂ are then investigated using the anionic catalysts C44ˉ to C136ˉ. The fundamental mechanism underlying negative-ion catalysis involves hydrogen bond strength-weakening in the transition state. DFT transition state calculations found C60ˉ numerically stable for both water and peroxide synthesis, C100ˉ increases the energy barrier the most and C136ˉ the most effective catalyst in both water synthesis and oxidation to H2O2.

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.

This study focuses on enhancing controllable fibrin-based hydrogels for tissue engineering, addressing existing weaknesses. By integrating a novel copolymer, we improve the foundation for cell-based angiogenesis with adaptable structural features. Tissue engineering often faces challenges like waste disposal and nutrient supply beyond the 200 µm diffusion limit. Angiogenesis breaks through this limitation, allowing the construction of larger constructs. Our innovative scaffold combination significantly boosts angiogenesis, resulting in longer branches and more capillary network junctions. The copolymer attached to fibrin fibers enables precise adjustment of hydrogel mechanical-dynamic properties for specific applications. Our material proves effective for angiogenesis, even under suppression factors like suramin. In our study, we prepared fibrin-based hydrogels with and without the copolymer PVP12400-co-GMA10mol%. Using a co-culture system of human umbilical vein endothelial cells (HUVEC) and mesenchymal stem cells (MSC), we analyzed angiogenetic behavior on and within the modified hydrogels. Capillary-like structures were reproducibly formed on different surfaces, demonstrating the general feasibility of three-dimensional endothelial cell networks in fibrin-based hydrogels. This highlights the biomaterial's suitability for in vitro pre-vascularization of biohybrid implants.

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.

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.

Throughout the eukaryotic tree of life, amoeboid organisms have evolved that aggregate upon starvation and form multicellular fruiting bodies, consisting of a ball of spores atop a stalk. This chapter discusses the remarkable convergent evolution of a stalked fruiting body in these different taxa. It then discusses a well-studied group of aggregative fruiters, the cellular slime molds, in more detail. These organisms exhibit substantial variation in their stalk formation and composition, which allows a better understanding of the evolution, maintenance and possible functions of stalked fruiting bodies, but also points to potential costs and benefits of different types of stalks.

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.

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.

The main objective of this study is to conduct a bibliometric analysis of scholarly publications of Authorship Pattern. The present study covers 1723 research papers published in the area of authorship pattern and indexed in Scopus database from the year 2013 to 2022. These research publications considered for the present study have been analysed based on their year wise growth, pattern of authorship, times citations, type of publication, most productive publication source as well as countries and institutions. The study shows the positive growth of the literatures with collaborative authorship pattern and good citation status. This original research paper will be helpful to the researchers of library and information science, especially who are working in the area of bibliometrics studies.

The oral mucosa represents a defense between the external environment and the rest of the body and encompasses several antimicrobial and antiviral mechanisms. Oral mucosal cells are constantly bathed in hypotonic saliva (normally one-third tonicity compared to plasma) and are repeatedly exposed to environmental stresses of tonicity, temperature and pH by the drinks we imbibe (e.g. hypotonic: water, tea, coffee; hypertonic: assorted fruit juices, red wines), as well as of diverse microbial and viral flora. In the mouth, the broad-spectrum antiviral mediator MxA (a dynamin-family large GTPase) is constitutively expressed in healthy periodontal tissues, and also induced by Type III interferons (e.g. IFN-λ1). Endogenously induced human MxA and exogenously expressed human GFP-MxA formed membraneless biomolecular condensates in the cytoplasm of oral carcinoma cells (OECM1 cell line). These condensates likely represent storage granules in equilibrium with antivirally active dispersed MxA. Remarkably, cytoplasmic MxA condensates were exquisitely sensitive sensors of hypotonicity – the condensates in oral epithelium disassembled within 1-2 min of exposure of cells to saliva-like one-third hypotonicity, and spontaneously reassembled in the next 4-7 min. OECM1 cells preloaded with calcein-AM (a reporter of cytosolic “macromolecular crowding”) confirmed unquenching and then requenching of calcein fluorescence during this process. Hypertonicity had little effect on MxA condensates. The spontaneous reassembly of GFP-MxA condensates in oral epithelial cells even under continuous saliva-like hypotonicity was slowed by the protein phosphatase inhibitor cyclosporin A (CsA) and by the K-channel blocker tetraethylammonium chloride (TEA) suggestive of the involvement of the volume-sensitive WNK kinase-protein phosphatase (PTP)-K-Cl cotransporter (KCC) pathway in the regulated volume decrease (RVD) during condensate reassembly in oral cells. Thus, physiologically, hypotonic drinks (water, tea, coffee) trigger a rapid deployment of antiviral MxA throughout the cytoplasm of oral epithelial cells, with subsequent salvage of MxA back into storage granules/condensates.

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.

This study introduces an efficient strategy for synthesizing polyhydroxyurethane-based multicomponent hydrogels with enhanced rheological properties. In a single-step process, 3D materials composed of Polymer 1 (PHU) and Polymer 2 (PVA or gelatin) were produced. Polymer 1, a crosslinked polyhydroxyurethane (PHU) grew within a colloidal suspension of Polymer 2, forming an interconnected network. The synthesis of Polymer 1 utilized a Non-Isocyanate Polyurethane (NIPU) methodology based on the aminolysis of bis(cyclic carbonate) (bisCC) monomers derived from 1-thioglycerol and 1,2-dithioglycerol (monomers MA and ME, respectively). This method, applied for the first time in Semi Interpenetrating Network (SIPN) formation, demonstrated exceptional orthogonality, since the functional groups in Polymer 2 do not interfere with Polymer 1 formation. Optimizing PHU formation involved a twenty-trial methodology, identifying influential variables such as polymer concentration, temperature, solvent (an aprotic and a protic solvent), and the organo-catalyst used [a thiourea derivative (TU) and 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU)]. The highest molecular weights were achieved under near-bulk polymerization conditions using TU-protic and DBU-aprotic as catalyst-solvent combinations. ME-based PHU exhibited higher (M_w ) ̅ than MA-based PHU (34,100 Da and 16,400 Da, respectively). Applying the enhanced methodology to prepare ten multicomponent hydrogels using PVA or gelatin as the polymer scaffold revealed superior rheological properties in PVA-based hydrogels, exhibiting solid-like gel behavior. Incorporating ME enhanced mechanical properties and elasticity (with loss tangent values of 0.09 and 0.14). SEM images unveiled distinct microstructures, including a sponge-like pattern in certain PVA-based hydrogels when MA was chosen, indicating the formation of highly superporous interpenetrated materials. In summary, this innovative approach presents a versatile methodology for obtaining advanced hydrogel-based systems with potential applications in various biomedical fields.

Elevation has been a cornerstone of biodiversity research, and changes in the environmental factors behind it influence biodiversity and community patterns. Exploring the potential reasons behind liverwort community patterns has been a matter of multiplied interest for ecologists. In the present study, we assessed the liverwort plants of the Sygera Mountain from 3100 m to 4500 m decaying wood, tree, soil, and rock using complex field surveys in 2017 and 2019, and investigated the effects of altitude and various climatic factors on the diversity and community composition of the Sygera Mountain. Also, we used including ANOVA, mixed effects modeling, NMDS, ANOSIM, and CCA, which helped to critically assess the liverwort diversity with respect to environmental variables. The results of the study showed a bimodal variation in the richness of liverwort communities with altitude, with peaks occurring at 3500 m and 4100 m. The variation with altitude was significant, with communities at 4100 m and 4300 m being associated with arid environments, and those at 3100 m and 3300 m favoring areas of higher mean annual temperatures and precipitation. Among the climatic factors, the variation in mean diurnal rang, precipitation, and annual temperature was found to be the determinant of liverwort communities. The results suggest that elevation and daily temperature fluctuations play a crucial role in the distribution and community structure formation of mountain liverwort plants. This study deepens our understanding of liverwort ecology and emphasizes the importance of climatic variables in determining plant community composition.

In the investment casting process, the pattern made of wax is obtained in a die for further formation of shell mold. This work investigates commercial pattern waxes fluidity with a newly developed injection fluidity test. A good correlation between wax fluidity and its viscosity is observed, which is different from metallic alloys, where the solidification behavior is more critical. The difference in investigated filled waxes fluidity can be associated with the type and amount of filler.

MRI shows in-vivo the three archetypal patterns of CNS volume loss underlying progressive ataxias, namely spinal atrophy (SA), cortical cerebellar atrophy (CCA) and olivopontocerebellar atrophy (OPCA). The MRI-based CNS atrophy pattern was reviewed in 128 progressive ataxias. A CNS atrophy pattern was identified in 91 conditions: SA in Freidreich’s ataxia, CCA in 5 acquired and 72 (24 dominant, 47 recessive,1 X-linked) inherited ataxias, OPCA in Multi-System Atrophy and 12 (9 dominant, 2 recessive,1 X-linked) inherited ataxias. The MRI-based CNS atrophy pattern may be useful for genetic assessment, identification of shared cellular targets, and repurposing therapies or enlargement of drugs indications in progressive ataxias.

The state of knowledge of properties of the Andromeda Galaxy (also known as M31) is reviewed. The spatial structure of the Andromeda Galaxy, its main source populations and the properties of its gas and dust are discussed. To understand the formation history of the Andromeda Galaxy, the critical issues of its star formation history and the gas streams and dwarf galaxies in its surrounding environment are reviewed. Emphasis is on recent studies with important earlier work described in the references provided here. It is important to understand the Andromeda Galaxy because it is the nearest large external galaxy and is close enough for high resolution studies. This allows the Andromeda Galaxy to be used as a template to understand more distant and less resolved galaxies in the universe.

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.

This article introduces a novel approach, termed the Asymmetric Probabilistic Tsetlin (APT) Machine, which incorporates the Stochastic Point Location (SPL) algorithm with the Asymmetric Steps technique into the Tsetlin Machine (TM). APT introduces stochasticity into the state transitions of Tsetlin Automata (TA) by leveraging the SPL algorithm, thereby enhancing pattern recognition capabilities. To enhance random search processes, we introduced a decaying normal distribution into the procedure. Meanwhile, the Asymmetric Steps approach biases state transition probabilities towards specific input patterns, further elevating operational efficiency. The efficacy of the proposed approach is assessed across diverse benchmark datasets for classification tasks. The performance of APT is compared with traditional machine learning algorithms and other Tsetlin Machine models, including the Asymmetric Tsetlin (AT) Machine, characterized by deterministic rules for Asymmetric transitions, and the Classical Tsetlin (CT) Machine, employing deterministic rules for symmetric transitions. Strikingly, the introduced APT methodology demonstrates highly competitive outcomes compared to established machine learning methods. Notably, both APT and AT exhibit state-of-the-art performance, surpassing the Classical Tsetlin Machine, emphasizing the efficacy of asymmetric models for achieving superior outcomes. Remarkably, APT exhibits even better performance than AT, particularly in handling complex datasets.

Security patterns encompass security-related issues in secure software system development and operations that often appear in certain contexts. Since the late 1990s about 500 security patterns have been proposed. Although the technical components are well investigated, the direction, overall picture, and barriers to implementation are not. Here, a systematic literature review of 240 papers is used to devise a taxonomy for security pattern research. Our taxonomy and the survey results should improve communications among practitioners and researchers, standardize the terminology, and increase the effectiveness of security patterns.

Ovarian tissue cryopreservation (OTC) or testicular tissue cryopreservation (TTC) are effective and often the only options for fertility preservation in female or male patients due to oncological, medical, or social aspects. While TTC and resumption of spermatogenesis, either in vivo or in vitro, has still be considered an experimental approach in humans, OTC and autotransplantation has been applied increasingly to preserve fertility with more than 200 live births worldwide. However, the cryopreservation of reproductive cells followed by the resumption of gametogenesis, either in vivo or in vitro, may interfere with sensitive and highly regulated cellular processes. In particular, the epigenetic profile, which includes not just reversible modifications of the DNA itself but also post-translational histone modifications, small non-coding RNAs, gene expression and availability, and storage of related proteins or transcripts, have to be considered in this context. Due to complex reprogramming and maintenance mechanisms of the epigenome in germ cells, growing embryos, and offspring, OTC and TTC are carried out at very critical moments early in the life cycle. Given this background, the safety of OTC and TTC taking into account the epigenetic profile has to be clarified. Cryopreservation of mature germ cells (including Metaphase II oocytes and mature spermatozoa collected via ejaculation or more invasively after testicular biopsy) or embryos has been used successfully for many years in Medically Assisted Reproduction (MAR). However, tissue freezing followed by in vitro or in vivo gametogenesis has become more attractive in the past, while few human studies have analysed the epigenetic effects, with most data deriving from animal studies. In this review, we highlight the potential influence of the cryopreservation of immature germ cells and subsequent in vivo or in vitro growth and differentiation on the epigenetic profile in humans and animals.

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.

Footprints are powerful indicators for evaluating the impact of the bioeconomy of a country on environmental goods, domestically and abroad. In this study, we apply a hybrid approach combining a Multi-Regional Input-Output model and land use modelling to compute the agricultural land footprint (aLF). Furthermore, we added information on land-use change to the analysis and allocated land conversion to specific commodities. The German case study shows that the aLF abroad is larger by a factor of 2.5 to 3 than the aLF in Germany. In 2005 and 2010, conversion of natural and semi-natural land-cover types abroad allocated to Germany due to import increases was 2.5 times higher than the global average. Import increases to Germany slowed down in 2015 and 2020, reducing land conversion attributed to the German bioeconomy to the global average. The case study shows that the applied land footprint provides clear and meaningful information for policymakers and other stakeholders. The presented methodological approach can be applied to other countries and regions covered in the underlying database EXIOBASE. It can be adapted, also for an assessment of other ecosystem functions, such as water or soil fertility.

The effective management of Fusarium wilt of bananas (FW) depends on the knowledge of the disease dynamics in time and space. The objectives of this work were: To estimate disease intensity and impact, and to investigate the spatial and temporal dynamic of FW. Fields planted with Silk (n = 10), Pome (n = 17) or Cavendish (n = 3) banana subgroups were surveyed in Brazil, totaling 95 ha. In each field, all plants were visually assessed and diseased plants were georeferenced. The incidence of FW and the impact of the disease on yield on a regional scale were estimated. Spatial patterns were analyzed using quadrat- and distance-based methods. FW incidence ranged from 0.09 to 41.42%, being higher in Silk fields (median = 14.26%). Impacts of epidemics on yield ranged from 18.4 to 8,192.5 kg.ha-1.year-1, with a median of 935.2 kg.ha-1.year-1. The higher economic impact of the disease was observed on Silk cultivar with a median loss of US$ 910.5 ha-1.year-1. Overall, estimated losses increased on average by US$ 109.8 ha-1.year-1 at each 1% of incidence. Aggregation of FW was detected by all analytical methods in 13 fields (1 of Cavendish, 11 of Pome and 1 of Silk). In the other 17 fields, at least one analytical method did not reject the null hypothesis of randomness. One field (5 ha), composed of six plots, was selected for spatial and temporal studies during two years with bi-monthly assessments. A sigmoidal curve represented the FW progress and the Gompertz model best fitted disease progress. The level of aggregation varied over time, and evidence of secondary infection to neighboring and distant plants were detected. FW is a widespread problem in Brazil and yield losses can be of high magnitude. Epidemiology-based management strategies can now be better established.

The expression microarray technique was performed to investigate the differences in gene expression between Czech Large White pigs and wild boars in the longissimus lumborum et thoracis and biceps femoris muscle tissues. The NREP gene (neuronal regeneration related protein homolog) was selected for detailed study as an expressional and functional candidate gene. NREP plays a role in the transformation of neural, muscle and fibroblast cells and in smooth muscle myogenesis. Quantitative real-time PCR results confirmed that the porcine NREP gene was expressed in both skeletal muscles and significantly overexpressed in Czech Large White pigs compared to wild boars (P &lt; 0.05). We identified 9 polymorphic sites in genomic DNA of NREP gene. Six of these polymorphisms were in complete linkage disequilibrium and therefore only 4 polymorphisms were informative. Associations of these 4 polymorphisms (HF571253:g.103G&gt;A, HF571253:g.134G&gt;A, HF571253:g.179T&gt;C and HF571253:g.402_409delT) with meat performance traits were assessed in Czech Large White pigs. New polymorphisms in NREP gene were significantly associated with parameters of daily weight gain, lean meat and backfat thickness in Czech Large White pigs. Our primary study suggested that porcine NREP may play an important role in skeletal muscle growth, fat metabolism and meat performance traits.

Agriculture and farming worldwide are responsible for numerous environmental threats, including degradation of land and water resources depletion. Underlining the dynamic interaction between bio-physical and socio-economic drivers is the key towards a more sustainable land and water management. With regard to a highly developed agricultural area in southern Italy, multi-regression models were developed to interpret the observed inter-annual variability of cropped land. Main drivers related to Common Agricultural Policy support, product market prices, crop yield and irrigation water availability were investigated. The adopted models revealed the different weighs of each driver. The findings reported the role that direct payments played in supporting the extension of irrigated crops, such as processing tomato. Likewise, the models pointed to decoupled payment scheme as the most important driver of change in the crop pattern over the last years.

Rotavirus (RV) replicates within viroplasms, membrane-less electron-dense globular cytosolic inclusions with liquid-liquid phase properties. In these structures occur the virus transcription, replication, and packaging of the virus genome in newly assembled double-layered particles. The viroplasms are composed of virus proteins (NSP2, NSP5, NSP4, VP1, VP2, VP3, and VP6), single and double-stranded virus RNAs, and host components such as microtubules, perilipin-1 and chaperonins. The formation, coalescence, maintenance, and perinuclear localization of viroplasms rely on their association with the cytoskeleton. A stabilized microtubule network involving microtubules and kinesin Eg5 and dynein molecular motors is associated with NSP5, NSP2, and VP2, facilitating dynamic processes such as viroplasm coalescence and perinuclear localization. Key post-translation modifications, particularly phosphorylation events of RV proteins NSP5 and NSP2, play pivotal roles in orchestrating these interactions. Actin filaments also contribute, triggering the formation of the viroplasms through the association of soluble cytosolic VP4 with actin and the molecular motor myosin. This review explores the evolving understanding of RV replication, emphasizing the host requirements essential for viroplasm formation and highlighting their dynamic interplay within the host cell.

In this study, the literature on varnish contamination is investigated among the various con-taminations of lubricant. As the period of use of lubricant increases, the lubricant deteriorates and becomes contaminated. The varnish causes filter plugging, sticking of hydraulic valves and fuel injection pumps, obstruction of flow, reduction of clearance, poor heater and cooler perfor-mance, and increase of friction and wear in various lubrication systems. These problems also cause mechanical system failure, performance degradation, and increased maintenance and re-pair cost. To improve the problems causes by the varnish, an adequate understanding of varnish is required. Therefore, in this literature review, definitions and characteristics, generating ma-chinery, generating mechanisms, causes, measurement methods, and prevention or removal methods are summarized. Most of the data are reports of companies related to lubricant and machine maintenance, and are included in some papers. We hope that this summary of varnish will be helpful to those who are engaged in reducing or preventing varnish problems.

As bakery products contribute considerably to the daily intake of the carcinogen acting substance acrylamide (AA), the aim of this study was to evaluate the impact of the cropping system (conventional vs. organic farming) on AA precursor levels of free asparagine (Asn) across different cultivars of the cereal species, namely winter wheat (Triticum aestivum), winter spelt (Triticum aestivum ssp. spelta) and winter rye (Secale cereale) with simultaneous consideration of gained grain yields and flour qualities. For this purpose, orthogonal field trials were established at two sites in Southwest Germany over two growing seasons (2006-2007 and 2007-2008). The results indicated a significant impact of the cropping system on free Asn contents. Across all species, free Asn contents in the flour were 26 % lower under organic compared to conventional farming. The impact of the cropping system on individual cultivars was obvious with a maximum reduction in free Asn contents of 50 % (e.g. for cultivars Ludwig, Privileg, Capo) if organically produced. For spelt, a significant impact of the cropping system was only found in 2008 with a reduction in free Asn of up to 25 % if organically produced. Across both cropping systems, cultivar Franckenkorn reached the lowest levels of free Asn. For rye, a significant impact of the cropping system was observed only in 2007 with 33 % higher Asn amounts in the conventional cropping system. Independent of the cropping system, rye reached the highest levels of free Asn followed by wheat and spelt. Across both cropping systems, species and cultivars, the amount of free Asn correlated with the AA content in heated flour with R2=0.63***. Furthermore, the results indicated that lower AA contents in bakery products can be achieved by proper selection of species (e.g. 66 % lower if rye is replaced by wheat) and cultivars. With an appropriate choice of the cultivar, a reduction of up to 65 % was possible within wheat, along with a reduction of 44 % within spelt and 12.5 % within rye. In summary, the results indicated that organically produced wheat especially offers the opportunity to significantly lower the AA potential of bread and bread rolls by the choice of raw materials low in free Asn.

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 prediction of hydrological flows (rainfall-depth or rainfall-discharge) is becoming increasingly important in the management of hydrological risks such as floods. In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of lake Nokoue in Benin. This paper aims to provide an effective and reliable method enable of reproducing the future daily water level of Lake Nokoue, which is influenced by a combination of two phenomena: rainfall and river flow (runoff from the Ouémé River, the Sô River, the Porto-Novo lagoon, and the Atlantic Ocean). Performance analysis based on the forecasting horizon indicates that LSTM can predict the water level of Nokoué Lake up to a forecast horizon of t+10 days. Performance metrics such as Root Mean Square Error (RMSE), coefficient of correlation (R²), Nash-Sutcliffe Efficiency (NSE), and Mean Absolute Error (MAE) agree on a forecast horizon of up to t+3 days. The values of these metrics remain stable for forecast horizons of t+1 days, t+2 days, and t+3 days. The values of R² and NSE are greater than 0.97 during the training and testing phases in the Nokoué Lake basin. Based on the evaluation indices used to assess the model's performance for the appropriate forecast horizon of water level in the Nokoué lake basin, the forecast horizon of t+3 days is chosen for predicting future daily water levels.

Generally, when cognitive radio users are in Underlay mode, through the analysis of the electromagnetic spectrum in time, frequency, space, and field of multiple dimensional data accounts for judging the inherent correlation of the radio spectrum used/idle state, this is the realization of cognitive radio users (secondary users, SUs) efficient access to the foundation of the limited spectrum resources. Therefore, how to efficiently use of spectrum status of each SU implementation of reception multidimensional combination forecasting is the core of this paper addressing the problem. In this paper, we propose a deep-learning hybrid model called TensorGCN-LSTM based on the tensor data structure. The model treats SUs deployed at different spatial locations under the same frequency and the spectrum status of SUs themselves under different frequencies in the task area as nodes and constructs two types of graph structures. Graph convolutional operations are used to sequentially extract corresponding spatial-domain and frequency-domain features from the two types of graph structures. Then, the long short-term memory (LSTM) model is used to fuse the spatial, frequency, and temporal features of the cognitive radio environment data. Finally, the prediction task of the spectrum distribution situation is accomplished through fully connected layers. Specifically, the model constructs a tensor graph based on the spatial similarity of SUs' locations and the frequency correlation between different frequency signals received by SUs, which describes the electromagnetic wave's dependency relationship in spatial and frequency domains. LSTM is used to capture the electromagnetic wave's dependency relationship in the temporal domain. To evaluate the effectiveness of the model, we conducted ablation experiments on LSTM, GCN, GC-LSTM, and TensorGCN-LSTM models using simulated data. The experimental results show that our model achieved better prediction performance in RMSE, and the correlation coefficient R2 of 0.8753 also confirmed the feasibility of the model.

Music acoustics is an interdisciplinary field and mathematics is the basis in the music art form. Music and mathematics correlation exist since the inception of music. Various philosophers, scientists, mathematicians and musicians have expressed their views about this relationship. This paper attempts to explore this association with focus on melodic pattern identification. Mathematics in Indian Classical music with raga as the basis and just intonation tuning system is discussed. Indian vocal music clips are used for different pitch estimation algorithms in the experimentation. Harmonic product spectrum and auto-correlation algorithms are tested for accurate pitch estimation. Enhanced auto-correlation function using audio segmentation is compared with other approaches for effective pitch extraction. Results indicate pitch extraction with enhanced auto-correlation function provides accurate results as compared with other approaches tested.

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.

Understanding how and why cells cooperate to form multicellular organisms is a central aim of evolutionary biology. Multicellular groups can form through clonal development (where daughter cells stick to mother cells after division) or by aggregation (where cells aggregate to form groups). These different ways of forming groups directly affect relatedness between individual cells, which in turn influences the degree of cooperation and conflict within the multicellular group. It is hard to study the factors that favoured multicellularity by focusing only on obligately multicellular organisms, like complex animals and plants, because the factors that favour multicellular cooperation cannot be disentangled, as cells cannot survive and reproduce independently. We propose bakers yeast, Saccharomyces cerevisiae, as an ideal model for studying the very first stages of the evolution of multicellularity. This is because it can form multicellular groups both clonally and through aggregation and uses a family of proteins called ‘flocculins’ that determine the way in which groups form, making it particularly amenable to lab experiments. We briefly review current knowledge about multicellularity in S. cerevisiae and then propose a framework for making predictions about the evolution of multicellular phenotypes in yeast based on social evolution theory. We finish by suggesting outstanding questions and potentially fruitful avenues for future research.

Despite increased protection globally, climate change and other anthropogenic factors have caused a significant decline in seagrass cover. Identifying the specific causes of this decline is paramount if they are to be addressed. Therefore, we identified the causes of long-term change in seagrass/submerged aquatic vegetation (SAV) percentage cover and extent in the Bluefields Bay Special Fish Conservation Area (BBSFCA), a marine protected area on Jamaica’s southern coast. We used two random forest regression (RFr) models that included 2013 hydroacoustic survey SAV percentage cover data (dependent variable), and auxiliary data, reflectance data from level 2 processed 2013 Landsat 7 and 8 images and image band texture statistics maps (mean and variance) as predictors to generate 24 SAV percentage cover maps for the period 1984 – 2021 (37 years) using data from Landsat 4-5, 7 and 8 images., from which benthic features maps (SAV present, absent and coral reef) were created. Rainfall and map data were used to determine if SAV extent/area (km2) and average percentage cover and annual rainfall changed significantly over time and to evaluate the influence of rainfall. Rainfall impact on the overall spatial patterns of SAV loss, gain, and percentage cover change was assessed using a pixel-based regression. Finally, the most important spatial pattern predictors (two rainfall proxies (distance and direction from river mouth), benthic topography, depth, and hurricane exposure (a measure of hurricane disturbance)) of SAV loss, gain, and percentage cover change during 23 successive 1-to-4-year periods were identified using spatial Bayesian INLA generalized linear mixed models. SAV area/extent was largely stable with &gt; 70% mean percentage cover for multiple years. However, Hurricane Ivan (in 2004) caused a significant decline in SAV area/extent (by 1.62 km2, or a 13%) during 2002 – 2006 and a second hurricane (Dean) in 2007 delayed recovery until 2015. Additionally, rainfall declined significantly by &gt;1000 mm since 1901, and mean monthly rainfall positively influenced SAV percentage cover change. The pixel-based regression highlighted areas where mean monthly rainfall had a positive overall effect on SAV cover percentage change (across the entire bay) and gain (closer to the mouth of a river). The most frequently selected important spatial pattern predictors were the two rainfall proxies (areas closer to the river mouth were more likely to experience SAV loss and gain) and depth, with shallow areas generally having a higher probability of SAV loss and gain. Three hurricanes had significant but different impacts depending on their distance from the southern coastline. Hurricane Gilbert, which made landfall in 1988, resulted in higher SAV percentage cover loss in 1987 - 1988. Benthic locations with a northwestern/northern facing aspect (the predominant direction of Ivan’s leading edge wind bands) experienced higher SAV losses during 2002 – 2006. Although some locations impacted by Ivan and not by Dean recovered during 2006 – 2008, exposure to Ivan explained percentage cover loss during 2006 – 2008 and average exposure to (the cumulative impact of) Ivan and Dean (both with tracks close to the southern coastline) explained SAV loss during 2013 – 2015. Therefore, despite historic lows in annual rainfall, overall, higher rainfall was beneficial, multiple hurricanes impacted the site, and despite two hurricanes in three years SAV recovered within a decade. Hurricanes and a further reduction in rainfall may pose a serious threat to SAV persistence in the future.

Cells that experience high levels of oxidative stress respond with the induction of antioxidant proteins through the activation of the transcription factor Nrf2. Nrf2 is negatively regulated by Keap1 which binds to Nrf2 to facilitate its ubiquitination and ensuing proteasomal degradation under basal conditions. Here, we study protein folding and misfolding in Nrf2 and Keap1 in yeast, mammalian cells, and purified proteins under oxidative stress conditions. Both Nrf2 and Keap1 are susceptible to protein misfolding and inclusion formation upon oxidative stress. We propose that the intrinsically disordered regions within Nrf2 and the high cysteine content of Keap1 contribute to their oxidation and the ensuing misfolding. Our work reveals previously unexplored aspects of Nrf2 and Keap1 regulation and dysregulation by oxidation-induced protein misfolding.

In offshore drilling, accidents such as gas invasion, overflow, and kicks are inevitable, and they can escalate into blowouts and other catastrophic events that result in casualties and substantial economic losses. Therefore, maintaining drilling safety requires accurate monitoring of gas invasion and overflow. The majority of overflow monitoring methods currently utilized at drilling sites are threshold-based. However, monitoring parameters acquired during actual drilling operations frequently contain noise signals, making it difficult for threshold-based methods to strike a balance between improving accuracy and minimizing false positives. In this paper, Pattern Recognition-based Kick Detection (PRKD) is proposed as a novel method for diagnosing overflow in offshore drilling. This method utilizes the overflow evolution process by integrating multi-phase flow calculations, data filtering theory, pattern recognition theory, the Bayesian framework, and other theoretical models. The PRKD effectively detects and monitors gas intrusion and overflow based on single parameters by analyzing the shape and wave characteristics of the curves. The case analysis demonstrates that the proposed method for monitoring drilling overflow achieves high precision while maintaining a low false positive rate. By combining advanced computational techniques with pattern recognition algorithms, the PRKD improves the accuracy and reliability of kick detection, enabling proactive responses to potential risks, protecting the environment and human lives, and optimizing drilling operations.

Ground penetrating radar (georadar, GPR), widely used in geology, archeology and road construction, is an efficient tool for searching and studying subsurface objects and structures. When planning GPR missions, it is necessary to predict the resolution of the device and the achievable probing depth. The article discusses the methods and results of assessing these characteristics of the Loza-V and Loza-N radars obtained in the course of archaeological and geographical expedition works.

For personalized recommender systems,matrix factorization and its variants have become mainstream in collaborative filtering.However,the dot product in matrix factorization does not satisfy the triangle inequality and therefore fails to capture fine-grained information. Metric learning-based models have been shown to be better at capturing fine-grained information than matrix factorization. Nevertheless,most of these models only focus on rating data and social information, which are not sufficient for dealing with the challenges of data sparsity. In this paper,we propose a metric learning-based social recommendation model called SRMC.SRMC exploits users' co-occurrence pattern to discover their potentially similar or dissimilar users with symmetric relationships and change their relative positions to achieve better recommendations.Experiments on three public datasets show that our model is more effective than the compared models.

Existing implementations of game design patterns have largely been confined to theoretical or research settings. Weaknesses in these implementations have prevented game design patterns from being properly evaluated as an educational and practical development tool. This paper examines these weaknesses, describes a method of developing and applying patterns that overcome the weaknesses, and evaluates use of the method for game design education and practice. Weaknesses in existing pattern implementations are: omission of design problems, presumption of functional completeness at the level of pattern languages, narrow topical focus, and lack of a concise, repeatable method for pattern production. Several features of the proposed method were specifically built to address these weaknesses, namely the pattern template, the process for connecting patterns into a language and assessing the language’s scope, a rubric for assessing pattern confidence and interconnectivity confidence, and pattern-building exercises. This method was applied in a classroom setting. Results, as assessed by the evaluation of student work, suggest that creating patterns/pattern languages is an effective pedagogical approach. De-signs produced using designer-created patterns closely align with existing design theory and are clearly understood by students. The above results may indicate that the path to gaining wider acceptance of pattern theory as a design framework within game design is not to produce a universal pattern language but to facilitate the creation of case-specific languages, by students and professional designers, that use a shared ontology and thus can be combined easily to solve the diverse sets of problems faced by these groups.

The study aimed to evaluate the association between the changes in ventilatory variables (tidal volume (Vt), respiratory rate (RR), and lung ventilation (VE)) and deoxygenation of m.intescostales (∆SmO2-m.intercostales) during a maximal incremental exercise in nineteen male competitive marathon runners. The ventilatory variables and oxygen-consumption (VO2) were recorded breath-by-breath by exhaled gas analysis. A near-infrared spectroscopy device (MOXY) located in the right-hemithorax allowed recording SmO2-m.intercostales. To explore changes in oxygen levels in muscles with high demand during exercise, a second MOXY records SmO2-m.vastus laterallis. The triphasic model of exercise intensity was used for evaluating changes in SmO2 in both muscle groups. We found that ∆SmO2-m.intercostales correlated with VO2-peak (r=0.65; p=0.002) and the increase of VE (r=0.78; p=0.001), RR (r=0.54; p=0.001), but not Vt (p=0.210). The interaction of factors (muscles X exercise-phases) in SmO2 expressed as an arbitrary unit (a.u) was significant (p=0.005). At VT1 were no difference (p=0.177), but SmO2-m.intercostales was higher at VT1 (p&lt;0.001) and VO2-peak (p&lt;0.001). In competitive marathon runners, the m.intercostales deoxygenation during incremental exercise is directly associated with the aerobic capacity and increased lung ventilation and respiratory rate, but not tidal volume. Besides, it shows less deoxygenation than m.vastus laterallis at intensities above the aerobic ventilatory threshold.

Recent advancements in web-based geospatial software and smartphone technology have popularized the process of voluntary production and sharing of geospatial data by individual citizens. Through such Volunteered Geographic Information (VGI) activities, people across the world participate in online mapping projects (such as OpenStreetMap) to insert their spatial information. The quality of data generated by such VGI activities has profound impacts on online mapping projects and their spatial database. In this study, we examine the VGI contribution pattern in OpenStreetMap through three case study neighborhoods located in three major cities: Tehran, London, and Los Angeles, and investigate how it might affect the process of quality assessment of VGI.

Although the presence of dark energy is well established from various observations, its true nature is still not well understood. The cosmological constant term seems to be the preferred candidate. In earlier work we had a constant cosmological constant term to limit the sizes of large-scale structures at lower redshifts. In this work, we extend this to large scale structures at higher redshifts. Here we invoke a time varying cosmological constant to set constraints on sizes of galaxies at high redshifts and see that they are consistent with their observed sizes. The time-varying cosmological constant also provides a possible solution to the puzzle of structure formation of large disk galaxies (like the Wolfe disk) observed at very early stages of the Universe. Future observations of galaxies at even higher redshifts could support our approach.

Membrane remodeling and phospholipid biosynthesis are normally tightly regulated to maintain the shape and function of cells. Indeed, different physiological mechanisms ensure a precise coordination between de novo phospholipid biosynthesis and modulation of membrane morphology. Interestingly, the overproduction of certain membrane proteins hijack these regulation networks, leading to the formation of impressive intracellular membrane structures in both prokaryotic and eukaryotic cells. The proteins triggering an abnormal accumulation of membrane structures inside the cells (or membrane proliferation) share two major common features: 1) they promote the formation of highly curved membrane domains and 2) they lead to an enrichment in anionic, cone-shaped phospholipids (cardiolipin or phosphatidic acid) in the newly formed membranes. Taking into account the available examples of membrane proliferation upon protein overproduction, together with the latest biochemical, biophysical and structural data, we explore the relationship between protein synthesis and membrane biogenesis. We propose a mechanism for the formation of these non-physiological intracellular membranes that shares similarities with natural inner membrane structures found in α-proteobacteria, mitochondria and some viruses-infected cells, pointing towards a conserved feature through evolution. We hope that the information discussed in this review will give a better grasp of the biophysical mechanisms behind physiological and induced intracellular membrane proliferation, and inspire new applications, either for academia (high-yield membrane protein production and nanovesicle production) or industry (biofuel production and vaccine preparation).

A 9,10-phenanthrenequinone (PQ) was electrochemically polymerized on a graphite rod electrode using potential cycling. The electrode modified by poly-9,10-phenanthrenequinone (poly-PQ) was studied by means of cyclic voltammetry, electrochemical impedance spectroscopy, atomic force microscopy and scanning electron microscopy. The poly-PQ shows variations in growth pattern depending on the number of potential cycles for the initiation of polymerization. Formed poly-PQ layer demonstrates good electric conductivity, great electrochemical capacitance and unique oxidation/reduction properties, which are suitable for broad technological applications, including applicability in biosensors, supercapacitors, and in some other electrochemical systems.

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

Background: Poisoning is a challenging medical condition facing health care providers, as it usually results in serious outcomes in terms of morbidities or mortalities. Poisoning is a challenging medical condition facing health care providers, as it usually results in serious outcomes in terms of morbidities or mortalities. The lack of or inadequate information about the circumstances, substances and populations at risk are considered barriers to the actual prevention of poisoning and effective intervention strategies in Saudi Arabia. The aim of the current study was to describe the pattern and determinants of chemical and drug overdose poisoning in Makkah.Subjects and methods: All reports of chemical and drug overdose poisoning delivered to the Environmental Health and Occupational Safety Department in Makkah over two years (2018-2019) were reviewed.Results: The total number of cases reported in 2018 was 209 cases, while it reached 42 cases in 2019. The overwhelming majority of the cases were Saudi (91.6%), with a slight predominance of males (57.4%) over females (42.6%). Generally, almost two-thirds of the cases occurred in children below 13 years (61.4%), most of the poisoning cases resulted from drug overdose (63.3%), while 34.7% were chemical poisoning. The most common drug poisoning was attributed to analgesics followed by antiepileptics, antihypertensive drugs, antipsychotics and antimicrobials, while cleaning and detergent agents were the most commonly poisoned chemicals. The majority of these agents were taken by the oral route. Children's chemical poisoning was significantly higher than that in older age groups (p<0.05). All intentional poisoning occurred in adults; the great majority of them (88.9%) used drug overdosing rather than chemical substances.Conclusion and recommendations: The current study results are consistent with most of the previous studies carried out in different regions of Saudi Arabia. Further in-depth studies are needed to elaborate other social and demographic factors associated with chemical and drug overdose poisoning. Public health plans, policies and legislations should be implemented to reduce these factors. Intensive supervision of children is needed. Suicidal poisoning patients should seek psychiatric help to limit the possibility of attempting suicide again in the future. Furthermore, efforts are needed to plan and implement health education programs about the factors proven in the current study to be significantly related to chemical and drug overdose poisoning.

Pressure drop and flow pattern of oil-water flows were investigated in a 19 mm ID clear polyvinyl chloride pipe consisting of U-bend with radius of curvature of 100 mm. The range for oil and water superficial velocities tested were and respectively. Measurements were carried out under different flow conditions in a test section that consisted of four different parts: upstream of the bend, at the bend and at two redeveloping flow locations after the bend. The result indicated that the bend had limited influence on downstream flow patterns. However, the shear forces imposed by the bend caused some shift flow pattern transition and bubble characteristics in the redeveloping flow section after the bend relative to develop flow before the bend. Generally, pressure gradient at all the test sections increased with both oil fraction and water superficial velocity and there was a sharp change of pressure gradient profile during phase inversion. The transition point where phase inversion occurred was always within the range of . Pressure losses differed at the various test sections and the difference was strongly linked to the superficial velocity of the phases and the flow pattern. At high mixture velocity, pressure losses at the redeveloping section after the bend were higher than that at the bend and that for fully developed flows. At low mixture velocity, pressure losses at the bend are higher than in the straight sections. Pressure drop generally decreased with level of flow development downstream of the bend.

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.

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.

Pregestational and gestational diabetes mellitus are relevant complications of pregnancy and antidiabetic drugs are prescribed to obtain glycemic control and improve perinatal outcomes. The objective of this study was to highlight the prescription pattern of antidiabetics before, during and after pregnancy in Italy and to evaluate its appropriateness. A multi-database cross sectional population study using a Common Data Model was performed. In a cohort of about 450,000 women, the prescribing profile of antidiabetics seemed to be in line with the Italian standards for the treatment of GDM which currently do not recommend the use of oral antidiabetics and non-insulin injection, even if a small share of new users (up to 3.8% in the third trimester) used oral antidiabetics. A substantial variability in the prescription pattern was observed among the Italian regions considered: the highest increase was registered in Tuscany (4.2%), Umbria (3.5%) and Emilia-Romagna (2.6%) while the lowest in Lombardy (1.5%), Veneto (1.7%) and Apulia (1.7%). Analysing the prevalence of use of antidiabetics between foreign women we observed that the consumption during pregnancy was higher than Italians (second trimester: 1,8% vs 0,9%, third trimester: 3,6% vs 1,8%).

Traditionally, neutron scattering is an essential method for the analysis of spin structures and spin excitations in bulk materials. Over the last 30 years, polarized neutron scattering in terms of reflectometry has also contributed largely to the analysis of magnetic thin films and magnetic multilayers. More recently it has been shown that polarized neutron reflectivity is, in addition, a suitable tool for the study of thin films laterally patterned with magnetic stripes or islands. We provide a brief overview of the fundamental properties of polarized neutron reflectivity, considering different domain states, domain fluctuations, and different domain sizes with respect to the neutron coherence volume. The discussion is exemplified by a set of simulated reflectivities assuming either complete polarization and polarization analysis, or a reduced form of polarized neutron reflectivity without polarization analysis. Furthermore, we emphasize the importance of the neutron coherence volume for the interpretation of specular and off-specular intensity maps, in particular when studying laterally non-homogeneous magnetic films. Finally, experimental results, fits, and simulations are shown for specular and off-specular scattering from a magnetic film that has been lithographically patterned into a periodic stripe array. These experiments demonstrate the different and mutually complementary information that can be gained when orienting the stripe array parallel or perpendicular to the scattering plane.

The human proteome is composed from diverse and heterogeneous gene products/proteoforms. Previously, we have been discussing the main technical aspects in developing for inventory of human proteoforms that would be visually attractive, clear, and easy to search (Naryzhny S. J. Proteomics 2018, S1874-3919(18) 30220-3). Here, we present our first draft of the database of proteoforms that is based on this discussion. The database principles and structure are described. The database is called “2DE-pattern” as it contains multiple isoform-centric patterns of proteoforms separated according to 2DE principles.

This paper presents a study and implementation of a convolutional neural network to identify and recognize humpback whale specimens from the unique patterns of their tails. Starting from a dataset composed of images of whale tails, all the phases of the process of creation and training of a neural network are detailed – from the analysis and pre-processing of images to the elaboration of predictions, using TensorFlow and Keras frameworks. Other possible alternatives are also explained when it comes to tackling this problem and the complications that have arisen during the process of developing this paper.