The tourism economy plays an essential role in supporting and driving tourism development. Therefore, studying its resilience is crucial for promoting sustainable and high-quality tourism development. Based on the core essentials of economic toughness, this paper constructs the tourism economic toughness evaluation index system, uses the entropy weight TOPSIS method to measure the tourism economic toughness of 10 counties and cities in the Yili River Valley in 2010-2019, analyzes its spatio-temporal evolution characteristics through the standard deviation ellipse, the traditional Markov chain, and the spatial Markov chain, and uses the grey correlation analysis method to analyze the driving factors of the tourism economic toughness. The results show that: (1) the economic resilience of tourism in the Yili River Valley shows a "W"-shaped time-series dynamic development trend with an average index of 0.28394, in which it experienced a decline from 0.28 to 0.27 during 2012-2013 and 2015-2016; (2) Spatial Pattern: The Yili River Valley tourism economic resilience is characterized by a clear uneven spatial distribution. The city of Yining, representing the northwestern region, exhibits a high level of resilience, while the southwestern region, endowed with rich tourism resources, demonstrates a medium level of resilience. Conversely, the central to southeastern counties and cities, such as ChabuchaerXibo Autonomous County and other counties and cities, are characterized by a lack of developed tourism facilities, which has resulted in a lower level of resilience and a weak development situation; (3) In terms of spatial and temporal evolution, the standard deviation ellipse is stabilized year by year pointing to "northwest-southeast", the clustering tendency is gradually enhanced, and five tourism economic resilience convergence clubs are identified, whose internal transition probability is significantly affected by spatial location, and which show obvious stability and neighborhood effects; (4) Regarding the driving factors, the impact of each driving factor on the resilience of the tourism economy reaches the statistical significance threshold of 0.77 or above. Among them, the number of employees in the tertiary industry, especially the input of high-quality talents in the tourism industry, plays a key role in improving the quality of tourism services and strengthening the industry's ability to withstand risks and development potential.

Several studies report an impact of the neurotransmitter dopamine (DA) on human immune cells, with effects dependent on immune cell type addressed and their activation status. Another contributing factor appears to be sex, as sex-specific differences in the dopaminergic pathway are described in the neurological context as well as in autoimmune diseases. However, a deeper understanding of these differences in peripheral immune cells remains limited. In this study, we investigated the effects of dopaminergic stimulation on activation and cytokine secretion of peripheral blood mononuclear cells from women and men using flow cytometry, ELISA and multiplex assay. We found a B cell-driven downregulation in cytokine secretion of monocytes exclusively from women under physiological conditions. Moreover, B cells from men showed higher dopamine receptor (DR) expression, which was shown to be further increased by sex hormones only in men. In monocytes from women, an acute inflammatory stimulus via CpG combined with dopaminergic stimulation caused a switch to a proinflammatory phenotype, which was less pronounced in men. These novel findings in sex-specific responses to dopaminergic stimulation are crucial for understanding DA’s function in the healthy and activated immune system and provide evidence to treat DA-related pathologies in a sex-specific manner.

Globalization, knowledge economy, information technology advancements, and the rise of learning societies contribute to the concept of a learning city. The study examines the economic indicators of Yazd city, Iran, in the context of learning city development. A descriptive-analytical approach with a survey method and cluster sampling was employed. Data analysis involved Kolmogorov-Smirnov normality test, single-sample T-test, simple linear regression, and Kendall's W test. The normality test confirmed data normality. The T-test indicated that experts perceived the current state of most variables in Yazd as undesirable. Regression analysis revealed a significant positive association between the economic index and independent variables. Kendall's W test prioritized areas based on economic indicators, with the top 7 and bottom 5 areas identified for focused interventions. The study emphasizes the need to prioritize areas within Yazd based on their economic indicators. This prioritization informs strategies for enhancing social and legal aspects of Yazd's transformation into a learning city. Further research should explore effective methods to cultivate a full-fledged learning environment in the city.

A previous research showed the 1755 tsunami would inundate the Marginal Avenue, the railway and the low ground area of Caxias, Oeiras municipality, Portugal. Thus, in this study several proposals for coastal protection are presented. A new Lidar data of local topography allowed the construction of a more accurate DEM, including the representation of the streets of Caxias downtown, to be used in the tsunami numerical model. The results were combined with field survey on Caxias and other coastal areas of Portugal and Japan. The new calculations show the low ground areas up to 6 m in height area inundated by the tsunami. However, with the new proposal DEM the tsunami inundation is restricted to the beaches. The proposal includes the construction of a new sea wall with 7 m in height at Caxias beach, the increase in height of the Barcarena Stream levees and the elevation of the sidewalk at São Bruno beach, with a gentle slope up to 7 m in height. It is also proposed the construction of a third bridge over the Barcarena Stream for pedestrian ranging from 5 to 7 m in height that will serve as a gate for the incoming tsunami waves.

The growing concerns about floods have highlighted the need for accurate and detailed precipitation data as extreme precipitation occurrences can lead to catastrophic floods, resulting in significant economic losses and casualties. Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM-IMERG) is a commonly used high-resolution gridded precipitation dataset and is recognized as trustworthy alternative sources of precipitation data. The aim of this study is to comprehensively evaluate the performance of GPM IMERG Early (IMERG-E), Late (IMERG-L), and Run Final (IMERG-F) in precipitation estimation and their capability in detecting extreme rainfall indices over southwestern Iran during 2001-2020. The Asfezari gridded precipitation data which are developed using a dense of ground-based observation were utilized as the reference dataset. The findings indicate that the IMERG-F performs reasonably well in capturing many extreme precipitation events (defined by various indices). All the three products showed a better performance in capturing fixed and non-threshold precipitation indices across the study region. The findings also revealed that both IMERG-E and IMERG-L have problems in rainfall estimation over elevated areas showing values of overestimations. Examining the effect of land cover type on the accuracy of the precipitation products suggest that both IMERG-E and IMERG-L show large and highly unrealistic overestimations over inland water bodies and permanent wetlands. The results of the current study highlight the potential of IMERG-F as a valuable source of data for precipitation monitoring in the region.

In the context of rapid urbanization, the spatiotemporal patterns of socio-economic exposed to high seismic hazard in large cities lacks quantitative assessment, thus, it is difficult to understand the evolution of earthquake catastrophe risk there. In this paper, exposure change rate, and absolute and relatively exposure indices were proposed to quantitatively study the changes of spatiotemporal exposure to high seismic hazard in urban areas of large cities (i.e., permanent residents in urban areas more than 1 million) in Chinese mainland, using a set of multi-temporal population, GDP, and built-up datasets and a seismic hazard zoning map. The results show that, 64 out of 78 large cities are entirely or partially located in high seismically hazardous zones. Although the urban areas of large cities in high seismically hazardous zones (HSHUAs) cover only 1.73% (167177 km²) of mainland China, their share of population, GDP, and built-up land amounted to 18.14%, 30.24% and 24.55%, respectively, in 2015. Unprecedented urbanization has led to a dramatic exposure growth in HSHUAs between 1990 and 2015. The population, GDP, and built-up land in HSHUAs increased by 110 million people (with an average annual growth rate of 2.37%), 273.71 trillion USD(average annual growth rate of 11.15%), and 10593 km2 (average annual growth rate of 2.02%), respectively. HSHUAs experienced much faster population and GDP growth than the whole country, while relatively slower growth in built-up land. Exposure growth in HSHUAs also was varied for different types of large cities. Megacities had a higher proportion of increased GDP and population in HSHUAs, induced by industry and population agglomeration. Whereas, Type II large cities had a higher proportion of increased built-up land in HSHUAs, driven mainly by urban sprawl. Our analysis indicates that, for large cities under rapid urbanization, it is an urgent need to strengthen resilient urban planning, renewal and construction.

REDD+ (Reducing Emissions from Deforestation and Forest Degradation) aims to achieve its purpose by working across multiple sectors and involving multi-level actors in reducing deforestation and forest degradation in tropical countries. By contrast, the European Union (EU) Action Plan on Forest Law Enforcement, Governance and Trade (FLEGT) and its Voluntary Partnership Agreements (VPAs) focus on forestry and functions at bilateral state level. The FLEGT Action Plan specifically aims to tackle illegal logging, legalise timber production and trade improve forest governance in countries exporting tropical timber to the EU. Since illegal logging is just one driver of deforestation and forest degeneration, and legalisation of logging does not necessarily reduce deforestation and forest degradation, the two instruments differ in scale and scope. However, by addressing the causes of deforestation and forest degradation and their underlying governance issues, the EU FLEGT and REDD+ share many functional linkages at higher levels of forest policy and forest governance. The contribution and participation of civil society organisations (CSOs) and other actors is imperative to both processes. Our study is based on a survey of key actors (national and international) in REDD+ and FLEGT VPA processes in the Lao People’s Democratic Republic. Our analysis was guided by the theoretical perspectives of the policy arrangement approach and examination of two specific dimensions of this approach, namely resources and rules of the game. This paper argues that participation of CSOs in both processes is crucial as it facilitates and nurtures the very much needed cooperation between other national and international actors. The paper also argues that participation of CSOs feeds valuable information and knowledge into REDD+ and FLEGT VPA processes, thus contributing to increased legitimacy, justice and transparency.

To characterize the fecal microbiota of lactating Bactrian camels, this study employed a random selection of camels, assigning them to three groups: the first parity group, the third parity group, and the fifth parity group. The fecal microbial community of lactating camels was assessed using 16S rRNA amplicon sequencing, and the resulting library was sequenced on an Illumina NovaSeq platform. The first parity group was characterized by Verrucomicrobiaceae as a distinctive bi-omarker, whereas Clostridiaceae exhibited a similar role to the third parity group. In terms of functional analysis, the relative abundance of the Steroid biosynthesis pathway was highest in the first parity group, whereas the fifth parity group demonstrated a higher relative abundance of the Tuberculosis pathway compared to the other groups. The first parity group exhibited the greatest presence of seven types of enzymes, whereas the fifth parity group displayed the highest levels of two specific enzymes. Additionally, a positive association was observed between the relative abundance of the Steroid biosynthesis pathway and Verrucomicrobiaceae. Furthermore, the relative abundance of the Tuberculosis pathway displayed positive correlations with 14 enzymes. In conclusion, this study revealed that different parity was associated with distinct fecal microbial ecologies in lactating Bactrian camels.

Wetland ecosystems in the Qinghai-Tibet Plateau are pivotal for global ecology and regional sustainability, contributing significantly to terrestrial ecosystems by regulating runoff, mitigating floods, and enhancing water quality. This study investigates the dynamic changes in wetland ecosystems within the Chaidamu Basin and their response to drought, aiming to foster sustainable wetland utilization in the Qinghai-Tibet Plateau. Using Landsat TM/ETM/OLI data on the Google Earth Engine platform, we employed a random forest method for annual long-term land cover classification. Meteorological drought conditions were assessed using SPEI3, SPEI6, SPEI9, and SPEI12, derived from monthly precipitation and evapotranspiration data. Pearson correlation analysis examined the relationship between wetland changes and various SPEI scales. The BFASAT method evaluated the impact of SPEI12 trends on wetlands, while cross-wavelet analysis explored teleconnections between SPEI12 and atmospheric circulation factors. Our findings revealed that the land cover dataset of the Chaidamu Basin (1990-2020) exhibited diverse categories with high classification accuracy (OA: 90.27%, Kappa: 88.34%). Wetlands, including lake, glacier, and marsh types, exhibited a noticeable increasing trend. Wetland expansion occurred during specific periods (1990-1997, 1998-2007, 2008-2020), featuring extensive conversions between wetland and other types, notably from other types to wetlands. Spatially, lake and marsh wetlands predominated in the low-latitude basin, while glacier wetlands were situated at higher altitudes. The study identified significant negative correlations between SPEI at various scales and total wetland area and types, with SPEI12 exhibiting the most substantial effect between September and December (r <-0.75) on wetlands. SPEI12 displayed a decreasing trend with non-stationarity and distinct breakpoints in 1996, 2002, and 2011, indicating heightened drought severity. Atmospheric circulation indices (ENSO, NAO, PDO, AO, WP) exhibited varying resonance with SPEI12, with NAO, PDO, AO, and WP demonstrating longer resonance times and pronounced responses.The continuous growth of wetlands amidst increasing aridification emphasizes the need for thoughtful wetland development to establish a sustainable "forest-lake-grass-field-river" ecological community. These findings underscore the significance of comprehending wetland changes and drought dynamics for effective ecological management in the Chaidamu Basin of the Qinghai-Tibet Plateau.

Areas covered with vegetation play a key role for life on Earth and should be inventoried in a clear and complete manner in order to improve the process of its protection and development. Data showing the amount of greenery in areas most deformed by humans, i.e. urbanized areas, are particularly important. Local governments need to know how to invest theirs limited sources in the quality of life of residents by supplementing the urban fabric with additional vegetation. The article presents a proposal for how to calculate the degree of greenness of cities based on remote sensing data. Additionally, a novel method was proposed to help in planning the development of areas covered with vegetation, taking into account the spatial distribution of the local population. The result was a comprehensive method presenting the actual natural situation in a specific city.

Aim: To analysis the relationship between healthy adults right ventricular diameter (RVD) and geographical factors. Location: China’s 22 provinces, municipalities and autonomous regions. Methods: Using correlation analysis the relationship between RVD and nine geographic factors, build predictive models by factor analysis. Results: There is significant correlation between RVD and geographical factors, and the annual average temperature is most relevant geographical factors, a predictive model was built by factor analysis: Ŷ = 19.46 + 0.0007072X1 + 0.001034X2 -0.05412X3 -0.001405X4 -0.0006351X5 + 0.02903X6 + 0.01243X7 -0.01033X8 + 0.03816X9 ± 0.63. Then using Kriging interpolation interpolate the geographical distribution of Chinese healthy adult right ventricular diameter reference value in ArcGIS software. Main Conclusion: If geographic factors can be derived in anywhere of China, RVD can be calculated by the model, you can also get RVD from geographical distribution.

Uzbekistan, as an emerging national economy, aims to attract foreign direct investment (FDI) to foster the development of its free economic zones (FEZs). While recent policy reforms have enhanced the country's appeal to investors and facilitated the inflow of international capital, challenges persist in attracting investment. This study employs an economic geographical approach to analyze and propose solutions to these obstacles. By examining the spatial patterns of FEZs and FDI through a comprehensive geographical lens, this research utilizes document analysis as an alternative to empirical analysis, considering the broader context rather than focusing on a specific FEZ. The findings reveal that the insufficiency of an innovation-driven environment, logistical systems, energy resource-related issues, among others, negatively impact the inflow of FDI into FEZs. Moreover, the study underscores the significance of economic geography in understanding these factors. Finally, relevant insights and recommendations are provided from an economic geographical perspective.

The COVID-19 pandemic has significantly impacted human health and daily life. Meteorological factors play a crucial role in virus transmission. Understanding these factors is critical for pandemic control, yet debates continue due to variations in research methods and data. This study uses a global dataset and focuses on administrative units smaller than 10,000 km². The relationship between daily COVID-19 incidence rates and meteorological factors—including temperature, relative humidity (RH), ultraviolet radiation (UVR), and diurnal temperature range (DTR)—was analyzed across 173 units in 62 countries. The results revealed significant nonlinear responses and lag effects between incidence rates and the meteorological factors. Key inflection points were observed at 0°C and 24°C for temperature, 63% for RH, 102 KJ/m² for UVR, and 15°C for DTR. Below 0°C, infection risk increased with rising temperatures; from 0°C to 24°C, risk decreased; and above 24°C, risk escalated rapidly. RH below 63% correlated inversely with infection risk, while above 63%, the correlation was positive. Infection risk decreased with UVR below 102 KJ/m² but increased beyond this threshold. These nonlinear responses are primarily driven by the differential effects of these factors on virus survival, transmission, and human immunity. Conditions around 24°C, 63% RH, 102 KJ/m² UVR, and DTR below 15°C appear optimal for human immunity, correlating with lower infection risk. High temperature and low UVR prompted immediate infection responses, while low temperatures, high UVR, and larger DTR showed delayed effects. These findings provide new, more reliable evidence for understanding the mechanisms driving COVID-19 pandemic dynamics and for preventing the future normalization of the epidemic.

In Mexico there is a deficit in the production of pine resin, because it depends on natural forests. Therefore, it is necessary to select provenances and phenotypes of potential species such as P. oocarpa. The objective was to determine the difference between provenances and the variation of resin components and quality, as well as the effect of geographic and climatic factors. Resin from five provenances was collected from southern Mexico. The percentage of rosin, turpentine and water was obtained, as well as the acidity and saponification index. P. oocarpa resin had 80.94 % rosin, 7.7 % turpentine and 11.49 % water. The saponification and acidity index was 125.47 and 117.49 mg KOH.g_1, respectively. All variables showed differences (p≤ 0.0001) between provenances. The provenance contributed between 6.44 and 11.71 % to the total variance, the error contributed between 88.29 and 93.56 %. Geographic and climatic variables only had an effect on the percentage of turpentine; the correlation was negative with altitude and longitude, but positive with temperature and precipitation. The results allow defining seed collection sites for resin plantations and orienting the selection for a P. oocarpa improvement program.

This study analyses regional development in one of the poorest provinces in China, Guizhou Province, between 2000 and 2012 using a multiscale and multi-mechanism framework. In general, regional inequality has been declining since 2000. In addition, economic development in Guizhou Province presented spatial agglomeration and club convergence, which shows how the development pattern of one core area, two-wing areas and a contiguous area at the edge of the province have been developed between 2006 and 2012. Multilevel regression analysis revealed that industrialization and investment level were the primary driving forces of regional economic disparity in Guizhou Province. The influences of marketization and decentralization on regional economic disparity were relatively weak. Investment level reinforced regional economic disparity and the development of core-periphery structure in the province. However, investment level actually weakened the regional economic disparity in Guizhou Province when the variable of time was considered. In addition, both the topography and urban–rural differentiation were the two main reasons for forming a core-periphery structure in Guizhou Province.

The objective of this paper was to verify the applicability of statistical learning (SL) compared to human reasoning with respect to the Universal Thermal Climate Index (UTCI), a complex tool for the assessment of outdoor thermal stress. UTCI is an equivalent temperature index based on the 48-dimensional output of an advanced model of human thermoregulation formed by 12 variables at four consecutive 30-minute intervals, which were calculated for 105642 thermal conditions from extreme cold to extreme heat. Comparing the performance of SL algorithms to the results accomplished by an international endeavor involving more than 40 experts from 23 countries, we found that random forests and k-nearest neighbors closely predicted UTCI values, but that clustering applied after dimension reduction algorithms (principal component analysis and t-distributed stochastic neighbor embedding) were inadequate for risk assessment in relation to the UTCI stress categories. This indicates a potential supportive role for SL, as it will not (yet) fully replace the bio-meteorological expert knowledge.

The objective of the present study is to analyze COVID-19 transmission in specific dampest regions with excess rainfall and recurring fogs. The working hypothesis is that widespread transmission of SARS CoV 2 (leading to COVID-19) and similar viral agents can be explained by specific climate factors having high air humidity. The main case study of the Turkish Black Sea region is investigated. Results reveal that the provinces in region under study have some climate factors and geographical features that foster the accelerated transmission of viral agents, such as SARS-CoV-2, and consequential negative impact on society. In particular, Spearman's Correlation Coefficient shows a statistically significant positive association between the average atmospheric pressure and the spread of the COVID-19 confirmed cases in Samsun province (Spearman’s correlation coefficient rs =0.86, p-value 0.05). A statistically significant positive association between the average precipitation and the spread of COVID-19 confirmed cases in Sinop province (Spearman’s correlation coefficient rs =0.79, p-value 0.05), and finally, a statistically significant negative association between the average sun hour and the spread of the COVID-19 confirmed cases in Samsun province (Spearman’s correlation coefficient rs = 0.89, p-value 0.01). These findings suggest that regions' geographical characteristics, demographic structure, climate and environmental parameters must be considered in the national scale epidemic management plans to design effective anti-pandemic health policies to cope with future waves of the COVID-19 and new airborne diseases and to reduce negative effects on health, social and economic systems.

This study is dedicated to the economic valuation of human capital in the regions where the Indigenous peoples of Kamchatka reside. The entire Kamchatksky Krai is considered an Indigenous people's ancestral territory. However, in this study, only municipalities whose population is more than one-third Indigenous were chosen for the assessment. This includes six municipal districts and one urban district (Aleytsky, Bystrinsky, Karaginsky, Olyutorsky, Penzhinsky, Tigilsky municipal districts and Palana urban district). The study employs statistical analysis and integrated, situational approaches: the investment approach was deemed the most appropriate tool for the economic assessment of human capital in Indigenous territories. The document analysis was based on a content analysis of open-access government documents and included legal acts, resolutions, orders, and other documents issued by federal, regional, and local authorities and pertaining to the economic activities of Kamchatka Indigenous peoples. Based on proposed calculation algorithm the assessed combined monetized value of human capital for the Kamchatka territories with large Indigenous populations at 38.8 billion rubles (approximately 520 million U.S. dollars) in 2021. It was observed that the growth of human capital in the Indigenous areas of Kamchatka between the years 2017 and 2021. The mean regional value of human capital per capita increased by more than twofold over this period. The accurate and precise assessment of human capital in the Kamchatka Indigenous homelands is provides baseline information necessary for the decision-making about economic development and sustainable development policies, and the approach proposed in this paper can be utilized by the Indigenous communities worldwide.

Sick leave is influenced by various modifiable lifestyle factors and sex differences. This study examines the impact of body mass index, fruit and vegetable consumption, physical activity, smoking, and alcohol consumption on sick leave among Serbia's working population, focusing on sex differences. Data from the 2019 National Health Survey of Serbia were analyzed, focusing on a representative sample of 4,652 individuals aged 18-65. Chi-square tests and logistic regression models assessed the relationships between lifestyle factors and sick leave, adjusting for sociodemographic, work-related, and health-related variables. Among respondents, 15.8% reported sick leave in the past 12 months, with higher rates among women in both, short-term (13.9% vs. 10.6%) and long-term sick leave (3.4% vs. 2.2%). For men, obesity (OR = 2.6), poor dietary habits (fruit OR = 2.1; vegetables OR = 2.8), smoking (OR = 1.9), and risky alcohol consumption (OR = 4.1) significantly increase the likelihood of sick leave. In women, smoking (OR = 1.8) and risky alcohol consumption (OR = 3.1) are major predictors, while BMI and physical activity show less impact. Fruit and vegetable consumption and physical activity have inconsistent effects on sick leave, indicating the need for further research. This study identifies obesity, poor dietary habits, smoking, and alcohol consumption as key predictors of sick leave in men. In women, smoking and risky alcohol consumption are major predictors. Smoking is a risk factor for both sexes, while risky alcohol consumption emerges as a prominent predictor and is a significant predictor overall. These findings highlight the need for targeted public health interventions to address these lifestyle factors and reduce sick leave rates. Further research is needed to clarify the roles of dietary habits and physical activity in influencing sick leave.

The development and utilization of wind energy is of great significance to the sustainable development of China's economy and the realization of the goal of "dual carbon". Under the typhoon system, the randomness and volatility of wind speed become an important basis for affecting the energy efficiency utilization and design of wind turbines. Therefore, based on wind speed and wind direction data at 10m, 30m, 50m and 70m heights of a wind power tower in Yancheng, Jiangsu Province, this paper analyzes the change characteristics of wind speed and wind direction by using BFAST method and Hurst index. Based on typhoon body data, topographic data and mesoscale system wind direction data, the causes of the occurrence and development of wind speed and wind direction of wind tower are further analyzed, and a conclusion is drawn: (1) In BEAST method, there are 5, 5, 6 and 6 change points at the height of 10m, 30m, 50m and 70m respectively. Among them, the change points at the height of 10m, 30m and 50m all change before and after node 325, and the change time point at the height of 70m is inconsistent with other heights. Hurst index results show that the inconsistency at 70m altitude is stronger than that at other altitudes. (2) The wind direction sequence at 10m, 30m, 50m and 70m altitude is fitted by stages, and the direction of wind direction is SE-E-SE-SW-W-NW, where, At the height of 70m, the deviation of the fitting trend line from other altitudes is larger in the wind speed strengthening stage and weakening stage. (3) The wind speed at the height of 10m and 70m has different response degrees to the typhoon body. The correlation between the wind speed and the distance between the wind measurement tower and the typhoon near the center is stronger at the height of 10m than at the height of 70m. The surface type and the wind direction of the mesoscale system also have certain effects on the wind speed and direction. In this paper, the change characteristics and influencing factors of wind speed and direction of wind tower are studied, which provides methods and theoretical support for the study of short-term wind speed when typhoon passes through, and provides reliable support for the selection of wind power forecast indicators and the selection and design of wind turbines under extreme gale weather systems.

Green spaces take part a vital role in reducing the harmful effects occurred through the process of rapid urbanization. This study focuses on evaluating the change of green space and per capita green space in Colombo District, Sri Lanka in between 2008 and 2015 using Landsat images. The NDVI differencing method and classification method were used to detect the change of land cover. According to the results, a gradual decline of green space from 629.1km2 to 591.16km2 with a rate of 6.03% can be depicted. The change is considerable in Kaduwela, Moratuwa and Maharagama DSDs and quite better in the areas such as Avissawella, Homagama and Padukka. The per capita green space has been decreased from 272.361 m2 to 248.811 m2. Though these rates are very well higher than the UN, EU and WHO standards for the district, Colombo DSD do not comply with UN and EU standards. The case would turn into worst in 2025, as the predictions with current rates. Therefore, the study recommends taking immediate actions to make a greener city. Further, a tax system is proposed to get the attraction of the general public.

This study addresses the gap in methodological guidelines for Neuroergonomic attention assessment in safety-critical tasks, focusing on validating EEG indices including the Engagement Index (EI) and Beta/Alpha ratio alongside subjective ratings. A novel task-embedded reaction time paradigm was developed to evaluate the sensitivity of these metrics to dynamic attentional demands in a more naturalistic multitasking context. By manipulating attention levels through varying secondary tasks in the NASA MATB-II task while maintaining a consistent primary reaction-time task, the study successfully demonstrated the effectiveness of the paradigm. Results indicate that both Beta/Alpha ratio and EI are sensitive to changes in attentional demands, with Beta/Alpha being more responsive to dynamic variations in attention, and EI reflecting more the overall effort required to sustain performance, especially in conditions where maintaining attention is challenging. The potential for predicting the attention lapses through integration of performance metrics, EEG measures, and subjective assessments was demonstrated, providing a more nuanced understanding of dynamic fluctuations of attention in multitasking scenarios, mimicking those in real-world safety-critical tasks. These findings provide a foundation for advancing methods to accurately monitor attention fluctuations and mitigate risks in critical scenarios, such as train-driving or automated vehicle operation, where maintaining high attention level is crucial.

In view of intensified disasters and fatalities caused by natural phenomena and geographical expansion, there is a pressing need for a more effective environment logging for a better management and urban planning. This paper proposes a novel utility computing model (UCM) for structural health monitoring (SHM) that would enable dynamic planning of monitoring systems in an efficient and cost-effective manner. The proposed UCM consists of network-attached data drive that stores data from SHM logger, population count system and Geographic Information System (GIS) enhanced with a Cloud IoT data backup, display, and analysis server. The UCM using this data and data from building information systems applies a simple machine learning algorithm to generate real-time structure health and suggests re-planning of SHM units. The health of structure varies dynamically with disturbances created by higher occupancy and structure density per zone. The proposed SHM-UCM is unique in terms of its capability to manage heterogeneous SHM resources. This was tested in a case study on Qatar University (QU) in Doha Qatar, where it looked at where SHM nodes are distributed along with occupancy density in each building. This information was taken from QU simulated occupation and zone calculation models and then compared to ideal SHM system data. Results show the effectiveness of the proposed model in logging and dynamically planning SHM.

Cynomorium songaricum is an important endangered plant with significant medicinal and edible values. However, the lack of resources and quality variation have limited the comprehensive developments and sustainable utilization of C. songaricum. Here, we evaluated chemical and genetic traits of C. songaricum from the highly suitable habitat regions simulated with species distribution models. The PCA and NJ tree analyses displayed intraspecific variation in C. songaricum, that could be divided into two ecotypes: ecotype I and ecotype II. Furthermore, the LC-MS/MS-based metabolomic was used to identify and analyze the metabolites of two ecotypes. The results indicated that a total of 589 compounds were detected, 236 of which were significantly different between the two ecotypes. Specifically, the relative content and the kind of flavonoids were more abundant in ecotype I, which were closely associated with the medicinal activities. In contrast, amino acids and organic acids were more enriched in ecotype II, which may provide better nutritional quality and unique flavor. In summary, our findings demonstrate the ecotype division and chemical diversity of C. songaricum in China from different geographical regions and provide a reference for the development of germplasm and directed plant breeding of endangered medicinal plants.

The Covid-19 has hit Italy in February 2020 after its outbreak in China at the beginning of January. But why Italy first among Western countries? What are the conditions that made Italy more vulnerable and the first target of such disease? What characteristics and what diffusion patterns could be highlighted and hypothesized, from the outbreak to the end of March 2020, after containment measures - including a national lock down – were introduced? In this paper we try to provide some answers to these questions, analyzing the issue from the medical, geographical and planning points of view. In particular, we started from a hypothesis of very similar economic, geographical, climatic and environmental conditions of the areas of Wuhan – in Hubei Province in China, the outbreak of the epidemics – and the Po Valley area – in Italy – where most cases and deaths were registered. Adopting an ecological approach, we compared the spatial distribution and pattern of Covid-19-related mortality in Italy with several geographical, environmental and socio-economic variables at Provincial level, analyzing them by means of spatial analytical techniques as LISA – Local Indicators of Spatial Association. Possible evidence relating Covid-19 cases and Nitrogen-related pollutants and land take arise, particularly in the Po Valley area.

The purpose of this study is to identify, and examine the potential characteristics of Siompu Tangerines to be given legal protection for Geographical Indications and examine the efforts of local governments in encouraging legal protection of Siompu Tangerines Geographical Indications, this research uses a type of empirical legal research. The conclusion of this study explains that characteristics of Siompu Tangerines have the potential to be given legal protection for Geographical Indications because they have a distinctive sweet, slightly sour taste and strong aroma with a sugar content scale of 9-10º Brix, the orange has been named the sweetest orange in the National Citrus fruit contest and several times served at official ceremonies at the State palace, the reputation of Siompu Tangerines makes it a National Flagship Orange through the Decree of the Minister of Agriculture number 742 / Kpts / TP. 240/7/1997. Geographical environmental factors from natural conditions and human factors make Siompu Tangerines can only grow well in the Siompu island area. The Regional Government of South Buton Regency has made efforts in terms of the development of Siompu Tangerines but has not been optimal in carrying out legal protection of Geographical Indications, due to a lack of community understanding, and the Regional Government regarding the potential of Siompu Tangerines which can be given protection by registering as a Geographical Indication product, the importance of obtaining legal certainty and obtaining exclusive rights is very useful in improving the community's economy and Farmer Tangerines Siompu.

Recently, the intensities of natural disasters have increased significantly owing to climate change and various other environmental factors, causing unprecedented damage. Measures must be established to reduce damage from large-scale natural disasters caused by the rapidly changing environment. The Japanese government published a hazard map manual in 2015 and obligates the creation of a hazard map as a measure to reduce high-scale storm surges. This manual presents a typhoon model based on a parametric model that is used to create a hazard map. The Myers model assuming concentric circles, which is primarily used in East Asia, is disadvantageous as it cannot consider geographic characteristics. Therefore, a new parametric model is necessary to calculate wind and pressure fields, which change according to geographic characteristics. To improve this limitation of the Myers model, we calculated the wind and pressure fields considering geographical effects by combining the Holland model, which can consider the size of a developing typhoon, and the Mascon model, which changes by geographic characteristics. To determine the gradient coefficient of the Holland model, the coefficient that changes every moment was calculated using grid point value data. The result indicated excellent reproducibility of storm surge height according to the geographic characteristics.

Bulgaria and North Macedonia have a long history of production and use of honey, however, there is an obvious lack of systematic and in-depth research on honey from both countries. Of particular interest is the oak honeydew honey, highly valued by consumers because of its health benefits. Aim of this study was to characterize honeydew and floral honeys from Bulgaria and North Macedonia based on their NMR profiles. 1D and 2D 1H and 13C NMR spectra were measured of 16 North Macedonian and 22 Bulgarian honey samples. 25 individual substances were identified, including quinovose, which was found for the first time in honey. Chemometric methods (PCA - principal component analysis, PLS-DA - partial least squares discriminant analysis, ANOVA) were used to detect similarities and differences between samples, as well as to determine their botanical and geographical origin. Semiquantitative data on individual sugars and some other constituents were obtained; which allowed reliable classification of honey samples by botanical and geographical origin, based on chemometric approaches. The results enabled to distinguish oak honeydew honey from other honey types, and to determine the country of origin. NMR was a rapid and convenient method, avoiding the need for other more time-consuming analytical techniques.

Crowdsourced Data (CSD) generated by citizens is becoming more popular as its potential utilisation in many applications is increasing due to its currency and availability. However, the quality of CSD, including its relevance, is often questioned as the data is not generated by professionals nor follows standard data collection procedures. The quality of CSD can be assessed according to a range of attributes including its relevance. Information relevance has been explored through using in Geographic Information Retrieval (GIR) techniques to identify relevant information. This research tested a relevance assessment approach for CSD by adapting relevance assessment techniques available in the GIR domain. The thematic and geographic relevance were assessed using the Term Frequency-Inverse Document Frequency (TF-IDF), Vector Space Model (VSM) and Natural Language Processing (NLP) techniques. The thematic and geographic specificities of the queries were calculated as 0.44 and 0.67 respectively, which indicates the queries used were more geographically specific than thematically specific. The Spearman's rho value of 0.62 indicated that the final ranked relevance lists showed reasonable agreement with a manually classified list and confirmed the potential of the approach for CSD relevance assessment for other possible crowdsourced data analysis.

Food waste is a common issue arising from grinding of food by experimental animals, leading to excessive food scraps falling into cages. In the wild, animals grind food by gnawing vegetation and seeds, potentially damaging the ecological environment. However, limited ecology studies have focused on food grinding behavior since the last century, with even fewer on rodent food grinding, particularly recently. Although food grinding function is partially understood, biological purposes remain under-investigated and driving factors unclear. This review aims to explain potential causes of animal food grinding, identify influencing factors, and discuss contexts and limitations. Specifically, we emphasize recent progress on gut microbiota significance for food grinding. Moreover, we show abnormal food grinding is determined by degree of excess normal behavior, emphasizing food grinding is not meaningless. Findings from this review promote comprehensive research on the myriad factors, multifaceted roles, and intricate evolution underlying food grinding behavior, benefiting laboratory animal husbandry and ecological environment protection, and identifying potential physiological benefits yet undiscovered.

Surgical site infections (SSIs) are a major concern in public healthcare, leading to increased morbidity, pro-longed hospital stays length, and significant economic costs. Understanding the epidemiology and risk fac-tors of SSIs is crucial for developing effective prevention and management strategies. In the last century, CDC ‘s HICPAC improved a bundle for prevention of HAIs based on the use of aseptic procedures, disin-fection of the skin and correct use of antibiotics for SSIs. In our country, Gelli-Bianco law introduced the national health guidelines system that include the prophylaxis antibiotic therapy pre- and post-surgery. The aim of our study is to evaluate adherence and appropriateness of the use of antibiotic-preoperative prophylaxis in a province of southern Italy and to identify risk factors that may influence the development of an SSI. The study found many statistically significant associations among the factors examined, i.e. the timing of administration adherent to guidelines, with 47% of the analyzed files administering antibiotics within 60 min before the intervention and 62.7% using intravenous administration.

A three-year survey was conducted to estimate the incidence of grapevine trunk diseases (GTDs) in Greece and identify fungi associated with the disease complex. In total, 310 vineyards in different geographical regions in northern, central, and southern Greece were surveyed, and 533 fungal strains were isolated from diseased vines. Morphological, physiological and molecular (5.8S rRNA gene-ITS sequencing) analyses revealed that isolates belonged to 35 distinct fungal genera, including well-known (e.g. Botryosphaeria sp, Diaporthe spp., Eutypa sp., Diplodia sp., Fomitiporia sp., Phaeoacremonium spp., Phaeomoniella sp.) and lesser-known (e.g. Neosetophoma sp., Seimatosporium sp., Didymosphaeria sp., Kalmusia sp.) grapevine wood inhabitants. GTDs-inducing population structure differed significantly among the discrete geographical zones. Phaeomoniella chlamydospora (26.62%, n=70), Diaporthe spp. (18.25%, n=48) and F. mediterranea (10.27%, n=27) were the most prevalent in Heraklion, whereas D. seriata, Alternaria spp., P. chlamydospora and Fusarium spp. were predominant in Nemea (central Greece). In Amyntaio and Kavala (northern Greece), D. seriata was the most frequently isolated species (&gt;50% frequency). Multi-genes (rDNA-ITS, LSU, tef1-α, tub2, act) sequencing of selected isolates, followed by pathogenicity tests revealed that Neosetophoma italica, Seimatosporium vitis, Didymosphaeria variabile and Kalmusia variispora caused wood infection with the former being the most virulent. To the best of our knowledge, this is the first report of N. italica associated with GTDs worldwide. This is also the first record of K. variispora, S. vitis and D. variabile associated with wood infection of grapevine in Greece. The potential associations of disease indices with vine age, cultivar, GTD-associated population structure and the prevailed meteorological conditions in different viticultural zones in Greece are presented and discussed.

Abstract: Transcription factors are crucial pre-transcriptional regulatory mechanisms that can modulate the expression of downstream genes by binding to their promoter regions. DOF (DNA binding with One Finger) proteins are a unique class of transcription factors with extensive roles in plant growth and development. Our previous research indicated a decrease in iron content in chlorotic bamboo leaves. However, to our knowledge, genes related to iron metabolism pathways in bamboo species have not yet been studied. Therefore, in the current study, we identified iron metabolism-related (IMR) genes in bamboo and determined the transcription factors that significantly influence them. Among these, DOFs were found to have widespread effects and potentially significant impacts on their expression. We identified specific DOF members in Dendrocalamus latiflorus with binding abilities through homology with Arabidopsis DOF proteins, and established connections between some of these members and IMR genes using RNA-seq data. Additionally, molecular docking confirmed the binding interactions between these DlDOFs and the DOF binding sites in the promoter regions of IMR genes. The co-expression relationship between the two gene sets was further validated using q-PCR experiments. This study paves the way for research into iron metabolism pathways in bamboo and lays the foundation for understanding the role of DOF transcription factors in D. latiflorus.

Several methods have been tried to estimate air temperature using satellite imagery. In this paper, the results of two machine learning algorithms, Support Vector Machine and Random Forest, are compared with Multivariate Linear Regression, TVX and Ordinary kriging. Several geographic, remote sensing and time variables are used as predictors. The validation is carried out using four different statistics on a daily basis allowing the use of ANOVA to compare the results. The main conclusion is that Random Forest with residual kriging produces the best results (R$^2$=0.612 $\pm$ 0.019, NSE=0.578 $\pm$ 0.025, RMSE=1.068 $\pm$ 0.027, PBIAS=-0.172 $\pm$ 0.046), whereas TVX produces the least accurate results. The environmental conditions in the study area are not really suited to TVX, moreover this method only takes into account satellite data. On the other hand, regression methods (Support Vector Machine, Random Forest and Multivariate Linear Regression) use several parameters that are easily calculated from a Digital Elevation Model, adding very little difficulty to the use of satellite data alone. The most important variables in the Random Forest Model were satellite temperature, potential irradiation and cdayt, a cosine transformation of the julian day.

This study uses machine learning to identify key factors influencing the cost-effectiveness of over-the-counter (OTC) medications. By developing a novel cost-effectiveness rating (CER) from user ratings and prices, we analyzed data from Amazon. The findings indicate that FSA/HSA eligibility, symptom treatment range, safety warnings, special effects, active ingredients, and packaging size significantly impact cost-effectiveness across cold, allergy, digestion, and pain relief medications. Medications eligible for FSA or HSA funds, treating a broader range of symptoms, and having smaller packaging are perceived as more cost-effective. Cold medicines with safety warnings were found to be cost-effective due to their lower average price and effective ingredients like phenylephrine and acetaminophen. Allergy medications with kid-friendly features showed higher cost-effectiveness, and ingredients like calcium, famotidine, and magnesium boosted the cost-effectiveness of digestion medicines. These insights help consumers make informed purchasing decisions and assist manufacturers and retailers in enhancing product competitiveness. Overall, this research supports better decision-making in the pharmaceutical industry by highlighting factors that drive cost-effective medication purchases.

Groundwater is an important role of the environment in natural resources. The major sources of groundwater contamination in this study were open discharges of domestic sewage, inadequate sewerage system, open defecation, septic tanks, soak pits, contaminated water pools, unorganized solid waste dumping and use of fertilizers, pesticides for agriculture deteriorated the condition. In this present study revealed that the physical and chemical characteristics of ground water in different areas of Kannur district in Kerala have been determined different seasons with respect to its suitability for drinking and agricultural purposes. For this study the groundwater samples were collected during pre-monsoon and post-monsoon seasons from 70 wells representing the entire the study area. The groundwater samples were analyzed for Physico-chemical characteristics using standard techniques in laboratory and compared with standards. The samples were analyzed with reference to the WHO and BIS standards. The groundwater quality information of the entire study area have been prepared using statistical and GIS technique for all the parameters. This paper proved in GIS will be helpful for measuring, monitoring and managing the groundwater pollution in the study area and suggested to protect groundwater resources in the environment.

Cervical cancer is one of the ailments that endangers the health of women all over the world and causes infertility. Fortunately, this disease can be avoided. Both the results and participation rates of the current preventative strategy remain poor. Hence, preventative or early detection methods remain challenging and open. In gynecology and computer science fields, few studies on identifying cervical cancer are based on behavior risk factor and machine learning. Moreover, various social and behavioral aspects might often make it more difficult to detect cervical cancer especially in low‑ and middle‑income countries (LMICs). Accordingly, focus on predicting the presence of cervical cancer through behavioral risk factors is the basic structure of this research. We proposed an approach to classify cervical cancer from a social-behavioral perspective using logistic regression to predict cervical cancer. We got significantly improved outcomes than the existing methods. Moreover, we used feature engineering to formulate less dimensionality as a pre-processing step and optimized parameters to be prepared for classification phase. The results proved that using the logistic regression with regularization type L1 had a promising performance. The accuracy of Logistic Regression (LR) L1 was 97.2%. Such results support the proposed work as a reliable classification predictive tool.

As a precious natural resource, forests are being destroyed. In previous studies, there is a lack of interactive assessment of its distribution that comprehensively considers multiple external disturbances. This paper takes the Barcelona Metropolitan Region as an example. Based on remote sensing, it analyzes the development process of the forest from 2006 to 2018 through multiple landscape indicators, and OLS models were established to analyze variables that have direct and indirect effects on forest distribution. In addition, the ecological structure of the forest was analyzed based on NDVI. It was found that the forest area is the largest but has been decreasing, becoming more complex in distribution structure. Much of the forest was converted to agricultural land and grassland. The green quality of forests was increasing, and the broad-leaved forest, the second largest area, contributes the most. NDVI is the most important positively correlated variable, and daytime surface temperature is an important inverse factor related to NDVI. In addition, NDBI is also a negative condition that inhibits forest development. In conclusion: The BMR forest area is decreasing and becoming more fragmented. NDVI and daytime LST are the two most significant factors. Climate warming may lead to worse forest development.

Background: Telemonitoring systems in cardiology have shown potential in improving chronic cardiovascular disease (CVD) management. This study aims to evaluate the impact of telemonitoring, mainly through mobile applications, on patient outcomes such as self-care, blood pressure control, quality of life, and hospitalization. Methods: We systematically reviewed studies assessing telemonitoring methods for patients with chronic CVD. The analysis included studies from various geographic regions and healthcare settings, focusing on qualitative outcomes without performing a meta-analysis. Results: Telemonitoring was found to aid in maintaining blood pressure and significantly enhance self-care abilities. Improvements in quality of life were observed in some studies, though results varied. Most studies indicated telemonitoring could effectively manage blood pressure and reduce hypertension-related complications. However, the heterogeneity of interventions and outcomes measured across trials posed challenges for a comprehensive meta-analysis. Conclusions: Integrating telemonitoring systems into routine care can significantly improve disease management and patient outcomes for chronic CVD patients. Future research should standardize telemonitoring interventions and outcome measures, conduct long-term studies, and evaluate the cost-effectiveness of these systems. Greater blindness in future randomized controlled trials and more studies on atrial fibrillation are also necessary. Significant potential exists for telemonitoring to improve patient outcomes and assist in managing chronic illnesses.

Severe early childhood caries remains the most common chronic disease affecting children. Its multifactorial etiology has established a controversy about which risk factors were more significant to its development. Therefore our study aimed through meticulous statistical analysis to arrange the “well agreed upon” common risk factors in order of significance, to aid the clinician in tailoring an adequate preventive program for this affected age group. The study reshuffled the risk factors contributing to severe early childhood caries and placed them in the order of their significance as follows: snacking of sugary food several times a day, increased number of siblings to 3 or more, night feeding, child self-employed brushing, mother caries experience, 2 siblings, on demand feeding, once/day sugary food, sharing utensils, 1 Sibling, male gender, father’s education, late first child dental visit, brushing time, mother’s education, no dental visit, decreased brushing frequency & no night brushing.

Microsporidia are intracellular parasites infecting a wide range of vertebrates and invertebrates. In bees, they cause a diarrheal disease called nosematosis, which represents a growing problem contributing to the decline of bee colonies. This parasitic disease infects the gastrointestinal tract of bees, disrupts their immune system, weakens them, and shortens their lifespan. There are two known species of this microsporidial parasite with a global distribution: Vairimorpha apis and Vairimorpha ceranae, with current research indicating that the species V. ceranae is gradually replacing V. apis. In this study, we focused on the detection and occurrence of Vairimorpha spp. in bee colonies kept in different environments, as well as on comparing the impact of hive location on its occurrence. The methods used included sampling from winter bee carcasses, microscopic examination of bee gut contents, and subsequent molecular duplex PCR analysis. Altogether, we examined 82 hives located at 4 different sites and focused on the impact of transportation as an abiotic factor disturbing bees leading to the development of Vairimorpha spp. disease. The results indicate an increased occurrence of this parasite in hives located in urban sites and hives situated in intravillage locations, which may be attributed to transportation and associated vibrations as an abiotic stress factor. Detection revealed that all samples were positive for Vairimorpha ceranae.

Multiple sclerosis (MS) is an immune-mediated disease characterized by inflammation, demyelination, and neurodegeneration within the central nervous system. Brain plasticity, the brain's ability to adapt its structure and function, plays a crucial role in mitigating MS's impact. This paper explores the potential benefits of lifestyle changes and nutraceuticals on brain plasticity in MS population. Lifestyle modifications, including physical activity and dietary adjustments, can enhance brain plasticity by upregulating neurotrophic factors, promoting synaptogenesis, and reducing oxidative stress. Nutraceuticals, such as vitamin D, omega-3 fatty acids, and antioxidants like alpha-lipoic acid, have shown promise in supporting brain health through anti-inflammatory and neuroprotective mechanisms. Regular physical activity has been linked to increased levels of brain-derived neurotrophic factor and improved cognitive function. Dietary interventions, including caloric restriction and the intake of polyphenols, can also positively influence brain plasticity. Integrating these lifestyle changes and nutraceuticals into the management of MS could provide a complementary approach to traditional therapies, potentially improving neurological outcomes and enhancing the quality of life for MS population.

When analyzing user geospatial information through deep learning methods, it is typically necessary to annotate existing geospatial data. Currently, manual annotation methods are commonly employed, suffering from issues related to low efficiency and accuracy. This design is based on the TensorFlow deep learning framework and first realizes the BiLSTM+CRF+AGG deep learning model. Among the models, AGG is the aggregation layer, which is introduced to solve the problem of solid particle size equilibrium. Secondly, based on the characteristics of original data and professional data, an automatic labeling algorithm is proposed. The algorithm first preprocesses the acquired original data set and professional data set, The most valuable unlabeled data set which can make the training model converge quickly is selected from the original data set as the target data set. Sort the target data set based on preset rules and set annotation parameters for the sorted target data set. Based on the set annotation parameters, the corpus is synthesized and used as the annotation result. Thirdly, based on the active learning strategy, a manual annotation auxiliary scheme is proposed, and an Excel generation module that is convenient for manual annotation correction is designed and developed to further improve the efficiency and quality of annotation through iterative processing. The combination of the BiLSTM+CRF+AGG deep learning model and high-quality annotation can accurately identify non-standard, incomplete, or even incorrect geographical information entities. This annotation method has found successful practical application within the context of the research project and has been granted an invention patent.

In the dynamic interplay between people and their physical environments, the Global South stands as a mosaic undergoing a multitude of transformative influences in architecture and urbanism where examining social sustainability becomes imperative. While prevailing attention remains on environmental and economic sustainability, this study addresses a persistent gap in the urban literature by focusing on the dynamic and manifold nature of social sustainability. Positioning itself within the context of sustainable development, the study links the pursuit of social aspects of sustainability with selected unique urban contexts from the Global South. Five cases that include Alexandria (Egypt), Tripoli (Libya), Basra (Iraq), Lilongwe (Malawi), and Accra (Ghana) are discussed through multi-layered investigations that involve attitude surveys, interviews, focus groups, participatory systematic observations, and behavioral mapping, engaging directly with inhabitants and stakeholders. Uncovering people-place narratives in the identified contexts, the cases are developed into five knowledge typologies that serve as practical tools for planning and design decision-making, policy formulation, and academic discourse. Discussions are conceived to demonstrate the transformative role people-place narratives play in fostering a more sustainable and equitable urban future. Conclusions are drawn to offer practical insights for stakeholders involved in various capacities in shaping the urban landscape of the Global South.

VarroMed® is a soft acaricide registered for honey bees on the European Union market since 2017 for Varroa control. Researchers involved were partners of different countries of the Varroa control task force of COLOSS Association. Our goal was to evaluate performances (acaricide efficacy and toxic effects on honey bees) of VarroMed® in different climatic conditions. Our results in the tested apiaries showed an efficacy ranging from 71.2 to 89.3 % in summer/autumn, and from 71.8 % to 95.6 % in winter. No toxic effects on bees were observed, except in one apiary, where severe cold climatic conditions played a crucial role. The treatment could be efficiently applied in brood right as well as in broodless colonies. Integrated pest management (IPM) recommendations for bee-keepers are provided in order to apply the best Varroa control protocol.

Background: Rabies, a zoonotic disease caused by the lyssavirus genus, is widely distributed and a significant cause of human death in Africa and Asia. This study aimed to investigate human rabies exposure and associated risk factors in Northwest Ethiopia. Methods: The study encompassed four zones, seven districts, and four kebeles from each district. The research team developed a questionnaire for data collection. Results: A total of 642 households were interviewed. The current study rabies exposure was revealed 10.47%. Over 98% of respondents displayed a strong understanding of rabies, with 99.69% correctly identifying rabies as a zoonotic disease. However, 80% of the interviewees were trusted traditional medicine could treat rabies. Only 21.93% of victims were took post exposure prophylaxis. Dogs were the primary affected animals (87.73%), of this 48.70% was bites by own dogs. Metema district had higher risk (p < 0.001) compared to others six districts. Dog ownership (p<0.05) and a higher number of households (p<0.01) were also identified as risk factors for rabies exposure. Conclusion: Residence, low education levels, high household density, free-roaming dogs, and dog ownership as key risk factors for rabies exposure. Public health awareness campaigns are crucial to emphasise the risks associated with animal bites.

Background This study aimed to identify the prominent risk factors that may trigger danger signals of early onset of vascular deregulation in T1D. The risk factors we have identified may serve as dual-purpose biomarkers of rapid diagnosis that offer prospective tailor-made resolution therapeutics. Methods The healthy control (HC) was compared with individuals diagnosed with T1D for the risk factors of vascular deregulation in published research studies from year 2013 to 2023. The PubMed, Web of Science and Google Scholar databases were searched from 1/1/2013 to 1/9/2023. The risk of bias was assessed with the Cochrane (ROBINS-I ) tool, which is relevant to clinical subjects. A random effect model for continuous data was followed and analysed by RevMan 5.4 and GraphPad Prism software. Results 80 relevant case-control studies having 5293 HC and 7492 T1D patients were included. The age and sex-matched HC consisted of persons free of disease and not under any medication while clinical subjects of all age groups were included. 28 risk factors were grouped into six primary outcome models, all of which favoured the T1D synonymous with a high risk of CVD. Conclusions Our findings have strong implications for improving the quality of life and health economics related to vascular disease in T1D. HbA1c% is the most effective biomarker, followed by FBG, LDL-C, and AI% which the clinicians could evaluate using a simple blood test or non-invasive techniques. (Protocol registered at https://www.crd.york.ac.uk/prospero/ CRD42022384636).

We propose a geographical time-space model extending time-space relief cartography introduced by Mathis and L’Hostis [,,,]. The novelty of the model resides in the use of cones to describe the terrestrial surface instead of graph faces, and in the use of curves instead of broken segments for edges. The approach lies a the intersection of two domains involving graphic representation: cartography, and three dimensional computer graphics. We implement the model on the Chinese space. The Chinese geographical time-space of the reference year 2006 is produced by the combination and the confrontation of the fast air transport system and of the 7.5 times slower road transport system. Slower, short range flights are represented as curved lines above the earth surface with longer length than the geodesic, in order to account for a slower speed. The very steep slope of cones expresses the relative difficulty of crossing terrestrial time-space, as well as the comparably extreme efficiency of long-range flights for moving between cities. Finally, the whole image proposes a coherent representation of the geographical time-space where fast city to city transport is combined with slow terrestrial systems that allow to reach any location.

Glaciation and mountain orogeny have generated new ecologic opportunities for plants, favoring an increase in the speciation rate. Moreover, they also act as corridors or barriers for plant lineages and populations. High genetic diversity ensures that species are able to survive and adapt. Gene flow is one of the most important determinants of the genetic diversity and structure of out-crossed species, and it is easily affected by biotic and abiotic factors. The aim of this study was to characterize the genetic diversity and structure of an alpine species, Festuca ovina L., in Xingjiang, China. A total of 100 individuals from 10 populations were analyzed using six amplified fragment length polymorphism (AFLP) primer pairs. A total of 583 clear bands were generated, of which 392 were polymorphic; thus, the percentage of polymorphic bands (PPB) was 67.24%. The total and average genetic diversities were 0.2722 and 0.2006 (0.1686-0.2225), respectively. The unweighted group method with arithmetic mean (UPGMA) tree, principal coordinates analysis (PCoA) and STRUCTURE analyses revealed that these populations or individuals could be clustered into two groups. The analysis of molecular variance analysis (AMOVA) suggested that most of the genetic variance existed within a population, and the genetic differentiation (Fst) among populations was 20.71%. The Shannon differentiation coefficient (G’st) among populations was 0.2350. Limited gene flow (Nm = 0.9571) was detected across all sampling sites. The Fst and Nm presented at different levels under the genetic barriers due to fragmentation. The population genetic diversity was significant relative to environmental factors such as temperature, altitude and precipitation.

Obesity has increasingly become a worldwide epidemic, as demonstrated by epidemiological and clinical studies. Obesity may lead to development of a broad spectrum of cardiovascular diseases (CVDs), such as coronary heart disease (CHD), hypertension, heart failure (HF), cerebrovascular disease, atrial fibrillation (AF), ventricular arrhythmias, and sudden cardiac death (SCD). In addition to hypertension, there are other cardiometabolic risk factors (CRFs) such as visceral adiposity, dyslipidemia, insulin resistance, diabetes, elevated levels of fibrinogen, and C-reactive protein and others, all of which increase the risk of CVD events. Mechanisms involved between obesity and CVD mainly include insulin resistance, oxidative stress, inflammation, and adipokines dysregulation, which cause maladaptive structural and functional alterations of the heart, particularly left ventricular (LV) remodeling and diastolic dysfunction. Natural products of plants, provide a diversity of nutrients and different bioactive compounds, including phenolics, flavonoids, terpenoids, carotenoids, anthocyanins, vitamins, minerals, fibers, and others, which possess a wide range of biological activities including antihypertensive, antilipidemic, antidiabetic, and other activities, thus conferring cardiometabolic benefits. In this review, we discussed the main therapeutic interventions using extracts from herbs and plants in preclinical and clinical trials with protective properties targeting CRFs. Molecular mechanisms and therapeutic targets of herbs and plants extracts for the prevention and treatment of CRFs are also reviewed.

The African continent has the highest prevalence of hypertension globally, with South Africa reporting the highest prevalence in Southern Africa. While the influence of genetic variability in the pathogenesis of hypertension is well described internationally, limited reports are available for African populations. This study aimed to assess the association of genetic variants and essential hypertension in a cohort of two ethnic South African population groups. Two hundred and seventy-seven hypertensive and one hundred and seventy-six normotensive individuals were genotyped for 79 variants. Genotyping was performed using the Illumina GoldenGate Assay and allele-specific polymerase chain reaction. The association of variants was assessed using the Fisher Exact test under the additive and allelic genetic models, while multivariate logistic regression was used to predict the development of hypertension. Five variants (CYP11B2 rs179998, AGT rs5051 and rs699, AGTR1 rs5186 and ACE rs4646994) were significantly associated with essential hypertension in the cohort under study. Furthermore, AGTR1 rs5186 and AGT rs699 were identified as risk factors for the development of hypertension in both ethnic groups. In two ethnic South African populations an association was observed between Renin-Angiotensin-Aldosterone System (RAAS) related genes and the development of hypertension.

By repeated unloading and loading of the excavation dynamic and static loads, repeated train dynamic and static loads of multi-factors, the underpass tunnel, cross tunnel engineering influence area rock layer, the existing tunnel structure of the three constitutes a multifaceted structure, multi-factor interaction system. Existing tunnels into the prediction theory model of the new tunnel excavation process of dynamic and static loads, dynamic and static loads of existing tunnels are mostly analyzed individually, the results of synergistic analysis needs to be improved. Based on the theory of the current layer method, the paper comprehensively considers the stiffness of the existing tunnel, the stiffness of the new tunnel, the excavation method load and the existing tunnel load, coupled with Peck's empirical formula, the theoretical model of deformation prediction for excavation of a two-lane highway tunnel under the tunnel through the existing railroad is proposed, and verified and optimized by numerical calculations and monitoring data, which proves the applicability and reliability of the theoretical model in the similar strata and the project promotion.

Graphene hybrid-filler polymer composites have emerged as prominent materials that revolutionize heavy industries. This study encapsulates the in-depth analysis of different influential factors such as filler/graphene type, aspect ratios, dispersion methods, filler-matrix compatibility, fiber orientation, synergistic effects, different processing techniques, and post-curing conditions that affect the processing, properties and determine the resultant applications of graphene hybrid polymer composites. Additionally, it discusses the substantial role of graphene collaboration with other fillers such as carbon nanotubes, silica, nano-clays and metal oxides to produce functionalized hybrid polymer composites with synergistically enhanced tailored properties to offer solutions for heavy industries like aerospace, automotive, electronics, and energy harvesting. The review concludes with some suggestions and outlook on the future of these composite materials by emphasizing the need for continued research to fully optimize their potential.

Partial Differential Equations (PDEs) constitute a fundamental framework for modeling various physical phenomena across diverse fields such as physics, engineering, and finance. Solving PDEs accurately and efficiently remains a significant challenge, particularly when dealing with complex systems or high-dimensional data. In this paper, we present a novel approach based on deep learning techniques to investigate the effective factors in solving PDEs. Our methodology leverages the expressive power of deep neural networks to learn and represent the underlying relationships between input parameters and the solutions of PDEs. By incorporating domain knowledge into the network architecture and training process, our approach aims to provide insights into the key factors influencing the solution of PDEs. We demonstrate the effectiveness of our method through numerical experiments on various PDEs, showcasing its capability to identify important features and improve predictive accuracy. Our findings suggest that deep learning techniques offer a promising avenue for understanding and analyzing the complex dynamics inherent in PDEs, paving the way for enhanced computational methods in scientific and engineering applications.

(1) Background: Food waste (FW) in Romania is 70 Kg/capita/year, while 70% of food waste comes from public catering, retail services, and households (over 50% – 47 million tons). (2) Methods: A cross-sectional observational study was conducted using an online questionnaire via the Google Forms platform from 15 April 2023 to 15 May 2023. The questionnaire was designed to assess various aspects, such as some socio-demographic information (age, sex, occupation, area of residence, study level, household members number, children &lt; 18 years of age); the personal involvement and frequency of food purchases and homemade food cooking; the main sources that generate food waste; the motivation and frequency with which food waste occurs; the level of awareness regarding the impact of food waste; the respondents' intentions regarding sustainable behaviors and practices food management; the level of information and familiarity of the respondents with the notions of validity and how these may influence their food consumption decisions. (3) The results show that FW incidence is occasionally (42%), very rarely (43.33%), frequently (15%), and no food waste was reported by 2.66% of respondents. The [35-44] age category records the highest FW frequency, followed by [18-24]. The most wasted are homemade food (29.67%), bread and bakery products (27.00%), and fruits and vegetables (14.33%). High involvement in purchasing and buying food following a previously established list reduces FW frequency. The same is valid for high daily involvement in food and homemade cooking. High interest in the FW problem and its perception as a waste of money leads to diminishing it, while guilty feelings increase the FW level (37.50% to 73.33%). (4) Conclusions: The present study shows that household food waste management is a multifactorial process that involves numerous socio-demographic, behavioral, and emotional aspects. Extensive data analysis supports our results, revealing deep self-reported information details and confirming its complex approach.

Gastrointestinal bleeding (GIB) after heart transplantation (HT) remains a significant clinical issue. The study aimed to explore its incidence, trends, outcomes and clinical predictors of GIB in HT patients. Adult patients who underwent HT between 2015 and 2021 at Union Hospital were recruited and divided into two groups based on the presence or absence of postoperative GIB. Primary outcomes were evaluated by follow-up. Independent predictors of GIB after HT were identified by logistic regression analysis. A nomogram prediction model was constructed according to these independent variables, and the accuracy of the model was assessed using the receiver operating characteristic (ROC) curve and the calibration curve. Among 461 patients, 40 (8.7%) developed GIB post-HT. HT patients with postoperative GIB exhibited higher in-hospital, 30-day, 90-day and 1-year mortality (all P < 0.05). Multivariate analysis identified age, preoperative warfarin, postoperative continuous renal replacement therapy and postoperative nasogastric tube as independent risk factors for GIB following HT. The nomogram prediction model was performed using the 4 variables. The area under the curve (AUC) of this model was 0.852(95% CI: 0.787-0.917, P < 0.001) and the calibration curve was close to the ideal diagonal line. GIB following HT is associated with a poor clinical prognosis. The constructed nomogram, incorporating its independent risk factors, demonstrated a favorable predictive value for GIB.

Ovarian cancer (OC) represents a significant challenge in the realm of gynecological cancers, characterized by poor survival rates and complex etiology. In this review, we delve into the se-lected genetic, environmental, and hormonal factors underpinning OC development. We have reviewed scientific databases searching for ovarian cancer genetic and epigenetic factors. We have included studies based on their relevancy. As a result of exploring ovarian carcinogen-esis, this systematic review contains data collected from 126 various works. The role of prominent genetic players such as BRCA mutations, DNA repair mechanisms, un-derscores the intricate landscape of OC susceptibility. We explore Li-Fraumeni and Lynch syn-drome, which impart a heightened predisposition to OC development. Hormonal factors such as estrogen, progesterone, and androgens are also discussed. Environmental alterations, ranging from lifestyle influences on OC to microbiome dysbiosis and lifestyle factors such as obesity, al-cohol consumption, and physical activity intersect with genetic and epigenetic pathways, shaping the risk landscape for OC. Through a meticulous examination of current literature, this review provides a nuanced under-standing of the multifactorial nature of OC, emphasizing the need for holistic approaches to prevention, diagnosis, and treatment.

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.

Background and Objectives: The aim of this study was to determine the job-related and individual features that influence BS and depression levels among dentists working in faculties, oral and dental health centres (ODHC) and private clinics. Materials and Methods: This prospective, cross sectional study was carried out on dentists working in different regions of Turkey. Data were collected using an on-line questionnaire created using Google Forms. The questionnaire consisted of demographic data, Maslach BS Inventory (MBI) and Beck Depression Inventory (BDI) sections. Demographics were age, height, weight, marital status, blood type, gender, monthly income, income satisfaction and having enough free time. The dentists were divided into 3 groups as faculty, private clinic and ODHC according to the institutions in which they worked. Results: Of the total 290 dentists enrolled in the study, there were 172 males and 118 females with a mean age of 36.98±5.6 years. 128 of the dentists worked in faculties, 72 in private clinics and 90 in ODHCs. It was observed that women's EE scores were higher than men's (P&lt;0.05). No statistically significant difference was found between the groups when comparing BS and depression scores according to marital status and blood group (P&gt;0.05). There was no significant relationship between emotional exhaustion (EE), depersonalisation (DP), personal accomplishment (PA) and depression scores according to age, BMI and work experience, age, work experience and BMI (P&lt;0.05). It was found that the EE scores of the dentists working in the faculty and private clinic were lower than those of the dentists working in the ODHC (P&lt;0.05). Monthly income was associated with depression (r = -0.35). Conclusions: This study showed that dentists working in ODHCs had more EE. These findings suggest that there is a need for improvement in the working conditions of dentists, particularly in ODHCs.

Dogs and cats have become the most influential and successful pets through long-term domestication. People keep them for various reasons, such as their functional roles or for physical or psychological support. However, why humans are so attached to dogs and cats remains unclear. A comprehensive understanding of the current state of human preferences for dogs and cats and the potential influential factors behind it is required. Here, we investigate this question using two independent online datasets and anonymous questionnaires. We find that current human preferences for dogs and cats are relatively higher than for most other interests, such as games and music. Genetic variations, gender, age, and economic development levels notably influence these preferences for dogs and cats. Specifically, dog and cat ownership is significantly heritable (h2 = 0.43, 95%CI: 0.35 -0.51) and further analysis found that women, young people, and those with higher incomes are more likely to keep dogs and cats, and the primary reason is to gain emotional support. Our study provides insights into why humans get so attached to dogs and cats and establishes a foundation for developing co-evolutionary models.

Mosquitoes are widespread arthropods that serve as vectors for a broad spectrum of viruses, many of which pose a substantial threat to humans. Conversely, some viruses may seemingly present with beneficial implications for the health of man whilst impinging on other domains of life, such as the fungi-infecting mycoviruses. This study is only the second one so far to describe the exceptionally scarcely identified Xanthi chryso-like virus (XCLV), member of the mycopathogenic Chrysoviridae family, in a new geographical area and a novel potential arthropod vector, the Culex pipiens mosquito. Interestingly, the XCLV was initially fortuitously detected by West Nile virus-specific primers directed at a conserved part of the NS5 gene, possibly indicative of a genetic resemblance and shared ancestry reflected in the NS5 evolutionary heritage. Detection and characterization of the virus and insect alike was done via PCR and Sanger sequencing. This investigation draws attention to our knowledge of viral pervasiveness – be it topographical or vectorial – and how humble it truly is. Additionally, we would propose that more attention be given to arthropod-borne viral pathogens that might prove advantageous to human health.

Measuring the impact of land use regulation on the land market involves identifying and classifying relevant impact factors related to the land market. The objective of this study was to identify land market impact factors in the context of the introduction of land use regulation in Nepal. A desktop review was carried out to identify preliminary set of impact factors, which were reclassified through intuitive analysis based on the degree of thematic closeness. Perspective-based impact factors were identified through the qualitative analysis of primary data collected through semi-structured interviews with the Nepalese land market stakeholders. These independently derived impact factors were compared with the desktop literature review impact factors resulting in fourteen land market impact factors across four dimensions, including transaction cost, valuation, mortgage availability, taxation, and compensation across the economic dimension; lot size, subdivision restrictions, and coordination across the institutional dimension; awareness, expectation and proximity across the social dimension; and risk reduction, quality of residential land, and suitability of zoning classification across the environmental dimension. There was significant overlap and commonality across factors identified from both the literature review and semi-structured interviews. The land market impact factors determined in the study may be adapted and generalized across other countries and could be utilized to better understand the impacts of land policy decisions on urban planning and development. Further research is recommended on the process to operationalize the use of these factors to quantify the impact of land use regulation on different land markets.

The aim of the article is to verify differences in the perception of selected factors of sustainability among small and medium-sized enterprises (SMEs) in Central Europe. The subjects of analysis are factors such as corporate social responsibility (CSR), business risk sources (market, financial, personnel, and operational), reputation and social media, national support, social changes, and crisis events in business. The questionnaire was completed by 1,090 SMEs from the business environments of Visegrad Group countries. Statistical hypotheses were verified using Z-scores for two population properties. The most negatively perceived factors among owners and managers in the SME segment are national support and legislative changes. The most positively perceived factor is reputation and social media. The country of doing business is a significant factor. The perception of crisis events in business is most negative among Czech SMEs. More than 80% of Hungarian SMEs perceive their companies as sustainable. In comparison with Slovak and Polish SMEs, Hungarian perceptions are more positive in the context of sustainability. The country of doing business is the strongest factor in evaluating CSR indicators. The positive perception of CSR in Czech SMEs (43.9%) is lower than in other countries.

This paper is aimed at studying the temporal evolution of the surface displacements occurred over the past few years in the ocean-reclaimed platforms of the Shanghai megacity (China), which are mainly ascribable to consolidation processes of large dredger fills and alluvial deposits. With respect to previous analyses carried out over the same area, this work provides a joint multi-platform differential interferometry synthetic aperture radar (DInSAR) analysis, based on the application of the advanced Small BAseline Subset (SBAS) algorithm. This led us to retrieve long-term deformation time-series that are helpful for a better understanding of the on-going deformation phenomena. To this aim, we have exploited two sequences of SAR data collected by the ASAR/ENVISAT and by the COSMO-SkyMed (CSK) sensors, respectively, spanning the whole time period from 2007 to 2016. Unfortunately, the large time gap (of about three years) existing between the available ASAR/ENVISAT and CSK datasets gave rise to additional difficulties for their combination. Nevertheless, this problem has been faced by benefiting from the knowledge of a time-dependent model describing the temporal evolution of the expected deformations affecting the Shanghai ocean-reclaimed platforms.

Following the transfer of hospital services to provincial government oversight, it is essential to understand how such changes impact service quality and efficiency. This study aims to identify the factors affecting hospital service quality post-transfer and evaluate the role of professional nurses in maintaining service standards under new governance.We conducted the study at sub-district health-promoting hospitals using a mixed-methods design based on the Global Fund-HSS framework (2012), which categorizes factors into accessibility, processes, productivity, and outcomes. We collected data from 340 nurses and 400 patients using structured questionnaires. We divided the questionnaires into seven sections, which captured a range of metrics such as the personal data of nurses, hospital service activities, and leadership qualities. We employed a Likert scale to gauge perceptions and expectations of service quality. We used paired t-tests to compare performance metrics before and after the administrative transfer, one-way ANOVA to assess variability among different service units, and binary logistic regression to identify key determinants of service quality in our statistical analysis. The analysis revealed a significant correlation between the attitudes and competencies of healthcare teams and the levels of service quality. Notably, service units transferred less than 50% exhibited minimal changes, indicating that the degree of transfer significantly impacts service outcomes. Despite these variations, the fundamental mission of promoting health remained consistent. The study emphasizes the critical role of nurses and recommends further research to identify additional factors that could improve service quality in transferred healthcare facilities. This could contribute to improved healthcare delivery across restructured health systems.

The ECM is composed of a considerable number of biochemically and structurally diverse constituents. ECM is a highly dynamic system that constantly receives and sends biological, chemical and mechanical signals. Several studies suggest that mechanical signals derived from the extracellular microenvironment regulate skin regeneration and wound healing. We evaluated effects of a mixture of biomolecules extracted and purified from bovine colostrum on restoring the mechanical properties of ECM. Test measuring collagen contraction showed a significant difference in contraction activation in samples treated with the 2% colostrum derivative mixture compared to the control. The analysis of the supernatant showed an inhibition of metalloproteinase-2 expression and an increase in collagen secretion by fibroblasts in treatment samples. Our hypothesis is that the molecules extracted and purified from bovine colostrum restore the ECM environment qualitative and quantitative characteristics, thus guaranteeing through a mechanical action the restoration of the wound due to the transduction of the signal activated by the integrins.

This study aimed to assess the variations in the nutritional attributes of thirteen Moringa oleifera cultivars. Leaves from six-month-old plants were harvested and tested for various nutritional attributes. There were significant (p ≤ 0.05) differences in the carbohydrates, energy, some of the sugars and fibre amongst the cultivars. The levels of moisture in the cultivars ranged from 7.10% to 8.20%. Additionally, there were significant (p ≤ 0.05) differences across the cultivars in microelements studied except for zinc (Zn). These data revealed that plants from different geographical provenances differed in their adapting to varied environments. In general, under the same cultivation, management and environmental conditions, the main reasons for these differences occurred in cultivars could be associated with the genetic background of each M. oleifera germplasm. However, the study cautions on the differences of nutritional properties, as some of the cultivars have been reported not to be pharmacological potent.

Background: Colorectal cancer (CRC) patients experienced multiple chemotoxicity affecting treatment compliance, survival, and quality of life (QOL). Prior research shows clinician-reported chemotoxicity (i.e., grading scales or diagnostic codes) predicts rehospitalization and cancer survival. However, a comprehensive synthesis of clinician-reported chemotoxicity is still lacking. Objectives: We conducted a systematic review and meta-analysis to determine the chemotoxicity's prevalence and risk factors in CRC. Methods: A systematic search from 2009 to 2024 yielded 30 studies for review, with 25 included in the meta-analysis. Results: Pooled prevalences of overall, non-hematological, and hematological moderate-to-severe toxicities were 45.7%, 39.2%, and 25.3%, respectively. The most common clinician-reported chemotoxicities were gastrointestinal (GI) toxicity (22.9%) and neuropathy or neutropenia (17.9%). Significant risk factors at baseline were malnutritional status, frailty, impaired immune or hepato-renal functions, short telomere lengths, low gut lactobacillus levels, age, female sex, aggressive chemotherapy, and low QOL. Age was associated with neutropenia (β: -1.44) and GI toxicity (β:1.85) (Ps 65 y.o.) had higher prevalences of overall (OR: 1.14) and GI (OR: 1.65) toxicities, but a lower prevalence of neutropenia (OR: 0.65) than younger adults (Ps

Following the transfer of hospital services to provincial government oversight, it is essential to understand how such changes impact service quality and efficiency. This study, conducted from 1 March 2023 to 31 March 2024 at sub-district health-promoting hospitals in Thailand, aims to identify the factors affecting hospital service quality post-transfer and evaluate the role of profes-sional nurses in maintaining service standards under new governance. Utilizing a mixed-methods design based on the Global Fund-HSS framework (2012), which categorizes factors into accessibility, processes, productivity, and outcomes, we collected data from 340 nurses and 400 patients through structured questionnaires. These questionnaires were divided into seven sec-tions, capturing metrics such as the personal data of nurses, hospital service activities, and lead-ership qualities. We employed a Likert scale to gauge perceptions and expectations of service quality and conducted paired t-tests to compare performance metrics before and after the admin-istrative transfer. One-way ANOVA was used to assess variability among different service units, and binary logistic regression helped identify key determinants of service quality. The analysis revealed a significant correlation between the attitudes and competencies of healthcare teams and the levels of service quality. Notably, service units transferred less than 50% exhibited mini-mal changes, indicating that the degree of transfer significantly impacts service outcomes. Despite these variations, the fundamental mission of promoting health remained consistent. The study emphasizes the critical role of nurses and recommends further research to identify additional factors that could improve service quality in transferred healthcare facilities, potentially contributing to enhanced healthcare delivery across restructured health systems.

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

In the context of sustainable development, integrating the work aspect into health promotion systems is essential, ensuring that employees maintain a healthy balance between their professional and personal lives, which respects and amplifies the potential of every individual. Lately, there has been a noticeable shift of medical professionals from the public to the private sector. This trend paints a bleak picture, highlighting the vulnerabilities of a system teetering on the brink of failure, with significant impacts on patient care. Among the myriad reasons behind this shift, burnout stands out prominently. Medical professionals face increasing pressures due to understaffing, limited organizational support, and insufficient resources, leading to feelings of cynicism, exhaustion, and detachment from their roles. Utilizing the Maslach et al. questionnaire, we assessed the risk of burnout among physicians in public hospitals to identify and underscore preventive measures and improvements, correlating our findings with key aspects of organizational empowerment. Our research indicates that enhancing interpersonal relationships and resources—both within teams and between the organization and its physicians—is crucial for the revival of the healthcare system. This approach aims at improving the delivery of healthcare services and offering appropriate recognition to healthcare professionals, aligning with the principles of sustainable employment.

Purpose: This integrated review aims to identify and analyze the multifactorial contributors to the longevity of direct restorations, focusing on tooth-, patient-, and dentist-related factors. Materials and Methods: A literature search was performed using an electronic database, PubMed/Medline, Web of Science, and Scopus, between 1980 and 2024. Titles and abstracts of papers that evaluated aspects categorized into tooth-related, patient-related, and dentist-related factors influencing restoration failure were selected and screened. Full-text assessments were conducted, and the extracted data were compiled, summarized, and synthesized. The reference lists of the collected papers were also screened, and relevant citations were included in this review. Data were gathered from clinical and laboratorial studies, systematic reviews, and meta-analyses to provide a comprehensive understanding of restoration longevity. Results: Among the tooth-related factors, multiple-surface restorations, deep margins, tooth location, and tooth vitality significantly impact restoration survival. Patient-related factors such as medical conditions, risk predictors of caries, age, sex, parafunctional habits, smoking, periodontal health, number of restorations, and socioeconomic status all play crucial roles. Regarding dentist-related factors, the decision-making process, age, experience, and dentist manual dexterity are vital aspects. Furthermore, the technique used, including isolation methods for moisture control, as well as the type of dental practice (large group vs. small practice), notably influenced the restoration survival. Conclusions: The longevity of dental restorations is influenced by a complex interplay of tooth-related, patient-related, and dentist-related factors. Strategies to improve restoration outcomes should consider all these multifactorial contributors. Continuing professional education, diligent patient guidance on the factors that influence restoration survival, careful material selection and restorative technique, and tailored individual treatment are crucial factors to reduce failure rates and improve the lifespan of restorations.

Questions：SAP in mountainous cities of China serve as crucial carriers for species and wild food, constituting potential green infrastructure. These patches should be recognized as locally specific resources. This study investigates the transformation characteristics of the landscape patterns of SAP, along with their elements, across urban-rural gradients, providing foundational support for the planning of conservation and utilization strategies. Location: Yongchuan area of Chongqing in southwest China. Methods: The study investigated urban-rural gradient-based transformation of SAP. A four-direction transect space was selected and divided into uniform sample squares. Fragstats 4.3 calculated the landscape index of SAP, and Spearman correlation coefficients in SPSS were used to evaluate the influence of landform and artificial factors on agroforestry patch transformation. Results: 1) Patch area (PA), Plaque density (PD), and CLUMPY of SAP systematically transform, showing increased SAP areas and higher connectivity with greater distance from the city, resulting in reduced patch fragmentation. However, Edge density (ED) and Largest plaque index (LPI) exhibit irregular transformation patterns. 2) With increased distance from the city, woodland patch area and connectivity increase, leading to decreased fragmentation, dispersal, and lower fractal dimensions. Conversely, Cultivated land follows the opposite trend. garden land patch area, fractal dimension, fragmentation, and dispersal all increase, while connectivity decreases. 3) Landscape pattern transformations of SPA are significantly influenced by artificial factors. Woodland patches are influenced similarly by landform and artificial factors. In contrast, cultivated land and garden land patches are more significantly impacted by artificial factors. Conclusions: SAP exhibit differentiated conservation and utilization measures across urban-rural gradients. Small patches located far from urban centers may benefit from systematic conservation measures to prevent further fragmentation and erosion in peri-urban areas.

Abstract. Background: COVID-19's first victim was announced by Chinese health authorities on the 11th of January 2020. On January 13, the first official case was reported outside China, in Thailand. On January 25, the same occurred in São Paulo and on March 8, the first case was recorded in Minas Gerais. From that point onwards until the 3rd of October 2020, a total of 370,911 cases and 9,204 deaths were recorded in the state. This study aims to investigate spatiotemporal patterns of COVID-19 with incidence from March 22 to October 3 of 2020. Methods: The database itself was obtained from Health Division of Minas Gerais state. The vulnerability index was calculated using a principal component analysis. Moran's I autocorrelation was tested, z-score and P-value < 0.05. Results: From March 22 to October 3 of 2020 the incidence level varied from 45.680/100,000 to 312.130/100,000. The most influential variables were: illiteracy, gross domestic product and breath apparel per municipality. The clusters were concentrated in the metropolitan area of Belo Horizonte, Zona da Mata and Triangulo Mineiro. Conclusion: The spatial distribution of COVID-19 from week 13 until week 40 showed that different levels of endemicity and mesoregional vulnerabilities were represented in these maps.

Polycystic ovary syndrome (PCOS) is a common condition in reproductive-age women. Women with PCOS are at higher risk of pregnancy complications including gestational diabetes (GDM). The prevalence of PCOS and GDM varies according to the diagnostic criteria used. The mechanism for the occurrence of GDM in women with PCOS is still unclear. Materials &amp; Methods- A systematic search of the electronic database was done using keywords like PCOS, and GDM to include studies between April 2008 and March 2023 where uniform diagnostic criteria were used. Studies were excluded with high-risk of bias after the assessment of bias, and meta-analysis was done with relative risks and confidence intervals. Results &amp; Discussion-Out of 1896 search results, 95 were selected for full-text. The quality of the studies was scrutinized and a total of 28 studies were included as they fulfilled the inclusion criteria. The incidence of GDM in women with PCOS was found to be 10.55 % (2.9- 54.9%) from pooled data involving 1,280,245. The prevalence of PCOS in women diagnosed with GDM was found from pooled data of 36,351 women in retrospective studies to be 2.47% (1.5- 50.1%). Selection predominantly included cohort studies, most commonly from China. The meta-analysis reported the risk of GDM is higher in women with PCOS than in those without PCOS (HR: 1.59, 95% CI: 1.27–1.91, p &lt; 0.001). Family history of diabetes, ethnicity, pre-pregnancy BMI, insulin resistance, gestational weight gain, use of assisted reproductive techniques, and multifetal gestation were the risk factors for GDM in women with PCOS. Conclusion- The prevalence of GDM in patients with PCOS is high, but the causality is complex. The newer predictive models are promising in clarifying the causative relationships, yet use various parameters at different cut-offs. There is a need for the development of universally acceptable parameters for the early prediction of GDM in women with PCOS.

The supply chain has incorporated products by putting them into hair scarfs. This study introduces the use of mini chips in health and beauty products and can reduce fatigue through enhanced sleep patterns. The mini chip could be placed in the scarf and used as a prototype. RFID technology provides the supply chain with specific information that is used to identify products and make communication easier. (Muhammad, et. al. 2013) This paper presents a new tool herein referred to as a scarf prototype which is developed to analyse EMG (electromyogram), ECG (electrocardiography), EEG (electroencephalogram), and EOG (electro-oculogram) signals that focuses in the area of sleep disorders. The mini chips used can be used to determine a solution for sleep disruption by using automated analytics. This could lead to improvement in our understanding of sleep disruption and overall sleep physiology. Automated technology allows repeated measurements, evaluation of sleep patterns, and provide suggestions to improve a person’s quality of sleep. This analysis compares the use of polysomnography and the scarf prototype. The analytics provide models and shows correlation between variables, such as EMG, ECG, EEG, and EOG. This study shows that the results from the scarf prototype is just as reliable as the original method, polysomnography.

Driving factors of smart city construction are exploratively studied by grounded theory method based on text sources from journal papers in SCI and CSSCI databases. Initial scale of driving factors about smart city construction is obtained on the basis of above analyses. This paper modifies measuring items of the initial scale with a small sample pretest and reliability test, then forms final items by exploratory factor analysis. According to the above scale, questionnaires are designed to obtain empirical data, and confirmatory factor analysis is used to verify further validity and reliability of the scale. The results show that driving factors of smart city construction include three main dimensions: problem-oriented factors, business- or technology-driven factors and endogenous development requirements.

Laportea bulbifera (Sieb. et Zucc.) Wedd. (L. bulbifera) is a significant plant belonging to the Laportea genus. It has been traditionally used in ethnomedicine to treat various conditions such as rheumatic arthralgia, fractures, falling injuries, nephritis dropsy, limb numbness, pruritus, fatigue-induced internal imbalances, and irregular menstruation. Modern pharmacological studies have confirmed its therapeutic potential, as it exhibits anti-inflammatory, immunosuppressive, analgesic, and anti-rheumatoid arthritis properties. In order to gather in-depth information on L. bulbifera, a comprehensive literature search was conducted using databases such as Web of Science, PubMed, ProQuest, and CNKI. This review aims to provide a comprehensive understanding of L. bulbifera by covering various aspects, including ethnomedicinal uses, geographical distribution, botanical description, phytochemistry, pharmacology, and quality control. By doing so, this review intends to lay a strong foundation and propose new research avenues for the exploration and development of potential applications of L. bulbifera. Thus far, a total of 189 compounds have been isolated and identified from L. bulbifera. These compounds include flavonoids, phenolics, nitrogen compounds, steroids, terpenoids, coumarins, phenylpropanoids, fatty acids and their derivatives, and other compounds. Notably, flavonoids and fatty acids in L. bulbifera have demonstrated remarkable antioxidant and anti-inflammatory properties. Furthermore, these compounds show promising potential in activities such as analgesia, hypoglycemia, and hypolipidemia, as well as toxicity. Despite the extensive fundamental studies conducted on L. bulbifera, further research is still needed to enhance our understanding of its credible mechanism of action and improve its quality control. This necessitates more comprehensive investigations to explore the specific material basis, uncover new mechanisms of action, and refine the quality control methods related to L. bulbifera. By doing so, we could contribute to the further development and utilization of this plant.

There is an observed general low performance of Ethiopian Sport Governing Bodies (SGBs) in service delivery. Evidence shows that the trend can be corrected with proper understanding and insight into the process of organisational and management factors of these SGBs. This study aimed to investigate the contribution of organisational and management factors on effective sport service delivery in SGBs. For this study, a cross-sectional research design was employed. Purposive sampling was used to choose 350 samples. Pearson Product Moment Correlation Coefficient and multiple regression were used to analyse the data at the 0.05 significant level. The findings confirmed that organisational and management factor variables had a significant positive relationship with sport service delivery (organisational structure (r=0.515), organisational capabilities (r=0.701), communication (r=0.549), management practice (r=0.571), materials &amp; resources (r=0.527) and stakeholders satisfaction (r=0.742). In addition, Management factors were found to be significant contributors for predicting effective sport service delivery (F(3, 329)= 165.868, R2= 0.612). Furthermore, organisational factors had a joint significant contribution to effective sport service delivery (F(3, 329) = 148.743, R2= 0.576). In addition, organisational and management factor variables jointly best predicted effective sport service delivery in Ethiopian SGBs (F(6, 326) =130.81, R2= 0.707). Therefore, this study suggests organisational and management factor variables can be used to predict effective sport service delivery.

Business-to-business (B2B) manufacturing companies are increasingly confronted with transformative trends such as sustainability, digitalization, and servitization. These trends are changing how product portfolios are developed, and value contributions are assessed, and therefore have disruptive potential. Dealing with these disruptive factors in Product Portfolio Management (PPM) is a largely unexplored topic. This study presents an empirical-qualitative exploration that contributes significantly to the field. The aim is to clarify the extent to which disruptive factors influence the evaluation and shaping of the product portfolio in B2B manufacturing companies. The Gioia method was used to evaluate 21 semi-structured interviews with experts from leading B2B manufacturing companies. Eight overarching challenges in PPM resulting from the disruptive factors were identified. Based on the eight overarching challenges and their associated causal relationships, two aggregated dimensions of action were derived: (1) increasing speed and flexibility by using generative artificial intelligence (AI) in a defined PPM process and (2) adjusting the product portfolio evaluation to consider various strategic drivers. These two dimensions of action call for future research to overcome the disruptive factors in PPM.

Occupational incidents in construction workplaces present a persistent challenge, with severe consequences for both workers and project outcomes. This study aims to examine the specific causal factors contributing to these incidents, focusing on the interaction between worker-related, environmental, and procedural factors. The objective is to identify key contributors to workplace accidents and develop a unified predictive model to mitigate future risks. To achieve this, we employed a machine learning approach on a comprehensive accidentology dataset collected from contractors across multiple construction sites. The dataset includes variables such as worker ex-perience, environmental conditions, adherence to safety protocols, and more. By analyzing direct, indirect, and root causes, the methodology uncovers hidden patterns and interdependencies that traditional analysis might overlook. The study’s findings indicate that worker experience and environmental factors are the most significant contributors to incident occurrence, with a clear interaction effect between these variables. The results not only confirm previous research but also offer enhanced predictive capabilities for future safety measures. This research demonstrates the value of machine learning in generating data-driven insights, ultimately aiding in the develop-ment of targeted interventions to improve safety standards in the construction industry.

Background: Condoms have proven to be an effective contraceptive barrier method of family planning and have played a vital role in preventing sexually transmitted diseases including HIV. However, existing evidence shows that utilization of condoms still remains low, especially among youth and adolescents. We aimed to determine the prevalence of condom use and associated factors among the students of Gulu university in Uganda. Methods: A cross-sectional study was conducted among undergraduate students of Gulu University between June and December 2023. The students were accessed from their respective faculties and chosen using a simple random sampling method. Data were collected using a pretested self-administered structured questionnaire. Condom use was defined as use of either male or female condom in the last sexual encounter in the previous six months. Results: A total of 404 participants, with a median age of 23 years (interquartile range (21.5-24) years) were enrolled in the study, 54.2%(n=219) of whom were male. Overall, 81.4%(n=329) of the participants were in senior classes (year 2,3,4, and 5) and 18.6%(n=75) were in their first year of study. The prevalence of condom use was 53.7%(n=217). Prevalence of condom use was 50.2%(n=109) among male and 49.8%(n=108) among female students. Year of study (senior class)(aPR = 1.4, 95% CI = 1.59, 3.54), having a sexual partner (aPR = 2.4, 95% CI = 1.89, 2.94), having a sexual partner within campus (aPR = 2.0, 95% CI = 1.69, 2.45), experience of condom bursting (aPR = 1.3, 95% CI = 1.08, 1.61), having sex in absence of condoms (aPR = 0.6, 95% CI = 0.44, 0.70), alcohol use (aPR = 1.2, 95% CI = 1.01, 1.45) were independently associated with condom use. Conclusion: Just over half of undergraduate students of Gulu university used condoms during sexual encounters. There should be heighten campaigns on condom use to prevent unintended pregnancies and sexually transmitted infections.

Spatial modeling in Geographic Information Systems (GIS) always involves choices. The existence of constraints, either of a financial nature or related to the specifics of the software itself, to the algorithms, the uncertainty and even the reliability of the data, the purposes and the applications of the studies, make this a kind of guiding compass for GIS analysts. Building on a previous exercise of data acquisition (check-ins) based on two Digital Social Networks (DSN — Facebook and Foursquare) and on the awareness of the use of Volunteered Geographic Information (VGI) generated by tourists sharing their topophilic ties through DSN, the present analysis aims to evaluate the contribution of modern techniques of spatial analysis applied to tourism in the “Alta and University of Coimbra” area. Concepts and procedural tasks related to density determination, cluster analysis and identification of patterns associated with regionalized variables have thus been implemented with the purpose of evaluating and comparing the results obtained through the application of two techniques of spatial analysis, Kernel Density Estimation (KDE) and Optimized Hot-Spot Analysis (OHSA) & Inverse Distance Weighting (IDW) Interpolation.

Abnormalities in male fertility constitute about 50% of all infertility causes. According to some data, the quality of human semen has deteriorated by 50-60 % over the last 40 years. A high-fat diet and obesity, the development of which is encouraged by the western lifestyle, affects the structure of spermatozoa, but also the development of the offspring and their health in later stages of life. In obese individuals, disorders on the hypothalamic-pituitary-gonadal axis are observed, as well as elevated oestrogen levels with simultaneous decrease of testosterone, LH and FSH hormone levels. Healthy dietary models clearly correlate with better sperm quality and a smaller risk of abnormalities in parameters, such as sperm count, sperm concentration and motility, as well as lower sperm DNA fragmentation. Apart from mineral components such as zinc and selenium, the role of omega-3 fatty acids and antioxidant vitamins should be emphasized, since their action will be based primarily on the minimization of oxidative stress and inflammation process. Additionally, the incorporation of carnitine supplements and coenzyme Q10 in therapeutic intervention seems also promising. Therefore, it is advisable to have a varied and balanced diet based on vegetables and fruit, fish and seafood, nuts, seeds, whole-grain products, poultry and low-fat dairy products.

The most prevalent musculoskeletal disorder of childhood with unclear aetiology is Growing Pains (GPs). Anatomic deformities and factors that change bone turnover are implicated in GPs pathophysiology. Perinatal risk factors alter the bone metabolism affecting the bone mineral density and content. The aim of our study was to analyze the relationship between GPs, knock knees and perinatal factors. The examined population consisted of 276 children aged 3-7 years. Among them 10 pairs of dizygotic twins were evaluated. The data were collected by using a combination of semi-structured questionnaires, clinical examinations and medical charts of the children and the obstetric history of the mothers. 78 children presented GPs meeting Peterson’s criteria. Genu valgum severity was a significant factor for GPs manifestation and for their increased frequency and intensity. Subsequently, perinatal factors regarding gestational age, Apgar score, head circumference (lower than 33cm) and birth length or weight (smaller than 50 cm and 3000gr, respectively) made a remarkable contribution to the development of GPs. Conversely, antenatal corticosteroid treatment, increased maternal age and maternal smoking during pregnancy were not predictive for the disorder. Our data are potentially supportive for the “bone strength” theory and for the contribution of anatomical disturbances in GPs appearance.

The role of natural factors mainly solar eleven-year cycle variability, and volcanic eruptions on two major modes of climate variability the North Atlantic Oscillation (NAO) and El Niño Southern Oscillation (ENSO) are studied for around last 150 years period. The NAO is the primary factor to regulate Central England Temperature (CET) during winter throughout the period, though NAO is impacted differently by other factors in various time periods. Solar variability indicates a strong positive influence on NAO during 1978-1997, though suggests opposite in earlier period. Solar NAO lag relationship is also shown sensitive to the chosen times of reference and thus points towards the previously proposed mechanism/ relationship related to the sun and NAO. The ENSO is influenced strongly by solar variability and volcanic eruptions in certain periods. This study observes a strong negative association between the sun and ENSO before the 1950s, which is even opposite during the second half of 20th century. The period 1978-1997, when two strong eruptions coincided with active years of strong solar cycles, the ENSO, and volcano suggested a stronger association, and we discussed the important role played by ENSO. That period showed warming in central tropical Pacific while cooling in the North Atlantic with reference to the later period (1999-2017) and also from chosen earlier period. Here we show that the mean atmospheric state is important for understanding the connection between solar variability, the NAO and ENSO and associated mechanism. It presents a critical analysis to improve knowledge about major modes of variability and their role in climate. We also discussed the importance of detecting the robust signal of natural variability, mainly the sun.

(1) Background: Sleep disordered breathing represent a growing public health concern, especially among children and adolescents. Full-night polysomnography is considered the gold standard for diagnosing obstructive sleep apnea. Our goals are to identify personal and environmental risk factors for the onset and persistence of sleep respiratory disorders. We also want to investigate the differences in neuropsychological profiles; (2) Methods: This is an observational, retrospective cohort study. We collected information on adenoidectomy or adenotonsillectomy. We reviewed the clinical history and preoperative visits and collected data through a telephone questionnaire. Pediatric Sleep Questionnaire (PSQ) and the Pediatric Quality of Life Inventory (PedsQL) are questionnaires used for screening sleep respiratory disorders in children. The data were statistically analyzed it using SPSS version 22.0 for Windows (SPSS Inc., Chicago, IL); (3) Results: The study involved 138 patients, but only 100 parents participated. A higher percentage of patients with sleep disordered breathing were observed to have mothers who smoked during pregnancy. A smaller proportion of patients with sleep disordered breathing had a habit of using a pacifier. A rise in physical results is associated with a reduction in the PSQ at follow-up (p=0.051). An increase of overall academic achievement is associated with an average decrease in the PSQ at follow-up (p&lt;0.0001). A more significant proportion of patients undergoing adenotonsillectomy were observed to have a history of prematurity and cesarean birth (4) Conclusions: These results provide essential information on the effectiveness and effects of adenotonsillectomy intervention compared to adenoidectomy intervention and the factors associated with SDB in children undergoing these interventions.

Abstract: Field studies with large-stemmed plants Artemisia dubia (wormwood) have been carried out at Vėžaičiai Branch LAMMC since 2018. According to three years of experimental results, annual dry matter (DM) yield varied from 7.94 to 10.14 t ha-1. Growing conditions, nitrogen ap-plication level and harvesting time had significant impacts on Artemisia dubia productivity. This article presents the results of research on preparation and use of Artemisia dubia biomass for en-ergy conversion and evaluation of technological-technical and environmental parameters of these plants utilization for solid biofuel. For experiments were used 6 variants of Artemisia dubia samples, which were grown in 2021: plants were cut three times and two fertilization options were used: (1) no fertilization and (2) fertilization with 180 kg ha-1 of nitrogen fertilizer. These harvested plants were chopped, milled and were pressed into the pellets. The physi-cal-mechanical characteristics (mоisture content, density and strength) of Artemisia dubia pellets were investigated. During this study, it was found that the density in dry mass (DM) of pellets ranged from 1119.86 to 1192.44 kg m-3. The pellet moisture content ranged from 8.80 to 10.49%. After testing of pellet strength, it was found that the pellets which were made from plant bio-mass PK-1-1, were the most resistant to compression, they withstood 560.36 N of pressure. Dry fuel lower heating value (LHV) of pellets was sufficiently high and was very close to pine saw-dust pellets, it varied from 17.46±0.25 MJ kg-1 to 18.14±0.28 MJ kg-1. The ash content of burned pellets ranged from 3.62±0.02% to 6.47±0.09%. Emissions of harmful pollutants – CO2, CO, NOx and unburnt hydrocarbons (CxHy) did not exceed the maximum permissible levels. Summariz-ing the results of investigated properties, cоmbustion and emissiоns of Artemisia dubia pellets, it can be concluded that this biofuel can be used for production of pressed biofuel and it is charac-terized by sufficient high quality, efficient combustion and permissible emissions to the envi-ronment.

The rise in precocious puberty cases can be attributed to a combination of genetic and environmental factors. Genetic factors play a significant role, with studies identifying genetic abnormalities in genes such as KISS1, KISS1R, MKRN3, DLK1, GABRA1, LIN28B, NPYR, TAC3, and TACR3, which are associated with central precocious puberty (CPP). Epigenetic factors like DNA methylation and histone modifications may mediate the relationship between genetic and environmental influences on CPP development. Environmental factors such as exposure to secondhand smoke, cesarean section, and BMI have also been linked to precocious puberty, particularly in girls, highlighting the multifactorial nature of this phenomenon. Understanding the interplay between these genetic and environmental factors is crucial in addressing the increasing prevalence of precocious puberty in children. The published literature in the past five years was systematically reviewed and summarized highlighting the interplay of genetic and environmental factors for the rise in the precocious puberty.

Cryptococcus neoformans is a facultative intracellular fungal pathogen. Ten-generation-old (10GEN) C. neoformans cells are more resistant to phagocytosis and killing by macrophages than younger daughter cells. However, mechanisms that mediate this resistance and intracellular parasitism are poorly understood. Here, we identified factors important for the intracellular survival of 10GEN C. neoformans, such as urease activity, capsule synthesis, and DNA content using flow cytometry and fluorescent microscopy techniques. Real-time visualization of time-lapse imaging was applied to determine the phagosomal acidity, membrane permeability, and vomocytosis (non-lytic exocytosis) rate in J774 macrophages that phagocytosed C. neoformans of different generational ages. Our results showed that old C. neoformans exhibited higher urease activity, and enhanced capsule formation, which was supported by an increased Golgi complex. In addition, old C. neoformans were more likely to be arrested in the G2 phase, resulting in the occasional formation of aberrant trimera-like cells. To finish, the advanced generational age of the yeast cells slightly reduced vomocytosis events within host cells, which might be associated with increased phagolysosomal pH and membrane permeability. Altogether our results contribute to a better understanding of the strategies used by old C. neoformans to resist phagosomal killing and suggest that old generation C. neoformans intracellular behavior may be driving cryptococcosis pathogenesis.

Trichiurus japonicus is the most productive fish caught in our country. In order to understand the seasonal distribution of Trichiurus japonicus in the central and southern parts of the East China Sea and Yellow Sea, three species distribution models were adopted, namely Random Forest Model, K-nearest neighbor algorithm and gradient ascending decision Tree model, based on the data of trawling surveys in the central and southern parts of the East China Sea and Yellow Sea from 2008 to 2009. Combined with variance inflation factor and cross-check, the distribution model of Trichiurus japonicus was screened and constructed to analyze the influence of environmental factors on the distribution of Trichiurus japonicus in the central and southern parts of the East China Sea and the Yellow Sea. The results showed that the random forest model had the advantages of fitting effect and prediction ability among the three models. The analysis of this model showed that the water depth, bottom water temperature and surface salinity had a great influence on the habitat distribution of Trichiurus japonicus. The relative resources of Trichiurus japonicus increased with the increase of bottom water temperature and reached the maximum at 23.8℃, and first increased and then decreased with the increase of water depth and surface salinity, reaching the maximum at 72 m and 31.2‰, respectively. The random forest model was used to predict the spatial distribution of Trichiurus japonicus in the East China Sea and the central and southern Yellow Sea during 2008-2009, and the results showed that the predicted results were close to the actual situation. The research results can provide reference for the exploitation and protection of Trichiurus japonicus resources in the East China Sea and the central and southern Yellow Sea.

(1) Background: Mouse-mammary tumor virus (MMTV) might play a role in the etiology of some breast cancers in humans. The purpose of our study was to identify MMTV DNA sequences in breast tissue samples from breast cancer patients operated in our regional center from Romania. (2) Methods: We have selected 75 patients with non-metastatic breast cancer treated with curative intent and searched with PCR the MMTV-like DNA sequence in the breast cancer tissue and normal breast tissue obtained from the same patients. (3) Results: None of the examined samples was positive for MMTV-like target sequences on PCR. (4) Conclusions: We could not prove that MMTV plays a role in the etiology of breast cancer in our patient group. This finding is similar to findings of other geographically related research groups and might be due to the fact that only the Mus musculus domesticus mouse species was proven to carry infectious MMTV, but not the Mus musculus musculus species, which is specific to South-Eastern Europe and some parts of Asia.

Breast cancer, although the most frequently diagnosed malignant tumour in humans, has a less clear aetiology compared to other frequent cancer types. Mouse-mammary tumour virus (MMTV) is involved in breast cancer in mice and dogs and might play a role in the aetiology of some breast cancers in humans, since it has been identified in 20-40% of breast cancer samples in Western Europe, USA, Australia and some other parts of the world population. The purpose of our study was to identify MMTV DNA sequences in breast tissue samples from breast cancer patients operated in our regional centre from Romania. We have selected 75 patients with non-metastatic breast cancer treated with curative intent and searched with PCR the MMTV-like DNA sequence in the breast cancer tissue and normal breast tissue obtained from the same patients. Since none of the examined samples was positive for MMTV-like target sequences on PCR we could not prove that MMTV plays a role in the aetiology of breast cancer in our patient group. This finding is similar to publications of other geographically related research groups and might be due to the fact that only the Mus musculus domesticus mouse species was proven to carry infectious MMTV, but not the Mus musculus musculus species, which is specific to South-Eastern Europe (including Romania) and some parts of Asia.

This retrospective study aimed to assess coronary artery calcium (CAC) progression in serial computed tomography measurements according to risk factor changes. In 448 asymptomatic adults who underwent CAC measurements with more than one-year intervals, CAC progression was assessed according to age, sex, variable traditional risk factors (diabetes mellitus, hypertension, hyperlipidemia, and smoking), and initial CAC score (0, 0.1–100, and &gt;100). Univariate and multivariate logistic regression analyses were assessed for independent predictors of rapid CAC progression (△CAC/year&gt;20). During the 3.5-year follow-up, coronary artery calcifications occurred in 43 (12.8%) of 336 individuals with an initial CAC score of zero. Of 112 individuals with initial CAC presence, 60 (53.6%) had △CAC/year&gt;20. Age, male sex, body mass index, and all risk factors were significantly associated with △CAC/year&gt;20, but recently diagnosed hypertension (odds ratio [OR], 11.3) and initial CAC score (OR, 1.05) were significant independent predictors in multivariate regression analyses. CAC progression was affected by demographic and traditional risk factors, but adjusting for these factors, recently diagnosed hypertension and initial CAC score were the most influential factors for rapid CAC progression. These findings suggest that patients with higher initial CAC scores may benefit from more frequent follow-up scans and checks regarding risk factor changes.

Hyperspectral imaging, a rapidly evolving technique, furnishes exhaustive information on Earth's surface reflectance over an extensive spectrum of wavelengths. We have developed a more precise method for analyzing spectral data by meticulously selecting plant leaf pixels and employing a relative reference approach. This enhanced technique correlates camera pixel values with light intensity, bypassing the need for complex equations and thereby providing clearer insights into vegetation vitality. The findings of this study not only enhance the precision of hyperspectral imaging but also bolster our capability for ecological monitoring and understanding environmental health. A novel algorithm based on the red-edge slope was established to classify images, exploiting the spectral reflectance data gleaned from the hyperspectral Liquid Crystal Tunable Filter (LCTF) camera. Compared with conventional SVM and K-means algorithms, our novel algorithm demonstrated commendable performance, achieving an overall accuracy of 90% with a Kappa Coefficient of 0.86. This comparison highlights the novel algorithm's relative strength and potential for large-scale satellite and drone imagery analysis applications. The advancements facilitated by this research are instrumental in ecological assessments, conservation efforts, and resource management strategies, signaling a leap forward in the era of environmental monitoring and analysis.

Solid waste management in Accra is a major challenge to the Metropolitan Authorities and inhabitants. The rapidly increasing population coupled with poor capacity of the municipal and private waste management companies to management waste effectively has created issues of environmental concern. Due to poor waste managements systems, most household dispose waste indiscriminately leading to floods and health issues. The study showed that about 60% of household waste is organic materials which has the potential to be converted to compost for agriculture purpose. Meanwhile plastics and rubbers which litters the environment as well as blocking major storm drains and gutters hence creating huge environmental hazard is made of 11% of the total component of most household waste generated daily. The study also revealed that among the methods of disposing waste, dumping waste in skip containers located at authorized places was the preferred means of disposing waste by household though others also dispose waste by other means such as burying and burning. Inadequate skip containers per population of household in an area coupled with irregularity of tracks picking these containers makes skip containers dumping site ugly scene, hence creating health issues. Among the constraints that impact negatively on sustainable waste management in Accra Metropolis, economic constraints was perceived as the main challenge which affect efficient waste management. Currently the country is going through serious economic challenges so government does not release money timely to fund projects which waste management is key. Most donor partners that use to support the government with funds have either reduced or redrawn their services as they have no confidence in the state of Ghana economy. Aside the constrains, the study also indicated that factors such as poor public attitude towards waste management, poor enforcement of sanitation by-laws, inadequate and untimely release of government funds were also seen as the main factors affecting waste management.

The intestinal microbial community of aquatic animals is closely related to the environment and thus affects the health of aquatic animals. Here we investigated annual variation of intestinal bacteria community structures of Ruditapes philippinarum cultured using two different methods, bottom sown and raft hanging. Bacterial diversity of seawater and sediment in different seasons was examined as well. Correlation between R. philippinarum intestinal bacteria community structures and environmental factors was analyzed. The results showed that in the two aquculture areas where R. philippinarum was differentially cultured, bacteria community structure of seawater and sediment both altered with seasons. However, neither seasonal changes nor difference in culture methods could significantly affect the intestinal bacteria community structures of R. philippinarum. Additionally, in terms of the alpha diversity of intestinal bacteria communities, there was no significant difference in R. philippinarum cultured using the two methods. For benthic cultured clams, alpha diversity of the intestinal bacterial communities was often higher than that of the environmental bacterial communities. For raft hanging cultured calms, Alpha diversity of the intestinal bacterial communities was normally comparable with that of the environmental counterparts. Beta diversity analysis showed that the intestinal bacterial community structure of R. philippinarum was mainly determined by both deterministic and stochastic processes. Correlation analysis showed that the intestinal bacterial community structures of R. philippinarum were determined by a variety of environmental factors. For clams collected from the benthic culture area, the intestinal bacterial structure was more correlated with the physicochemical properties of sediment in comparing with those of seawater. For clams collected from the raft-culture area, the intestinal bacterial structure was mainly determined by the phsicochemical characteristics of seawater. This study helps us to better understand the bacterial community structure in complex aquaculture ecosystems, providing a reference for healthy shellfish aquaculture and ecosystem protection in aquaculture area.

Urban air pollution is a critical global environmental issue, necessitating an understanding of the spatiotemporal characteristics and driving factors for effective environmental protection and urban planning. This study introduced an advanced air quality assessment system that integrates environmental, socio-economic, and urban layout factors, addressing gaps in traditional models that often overlook the impact of urban spatial structures. Analyzing air quality data from Beijing's main urban area (2016-2020) alongside multi-source geographic data, the research develops a comprehensive evaluation system, incorporating 14 key driving factors. Employing Geographically Weighted Regression (GWR) and Multi-scale Geographically Weighted Regression (MGWR), the study quantitatively assessed the influence and spatial heterogeneity of these factors. Findings revealed an annual improvement in air quality, with a U-shaped seasonal pattern and significant spatial clustering (Global Moran’s I = 0.922). The MGWR model, in particular, provided a superior fit over GWR, effectively capturing the spatial variability of factors. Variables such as NDVI), economic output (GDP), and humidity space adjustment capability (HSAC) showed significant positive spatial impacts on air quality, while population density (POP), temperature (TEMP), and road density (RD) exhibited negative effects. These insights enhance the understanding of air pollution dynamics and aid in refining urban planning strategies.

Background: The effect of velamentous cord insertion (VCI) on perinatal outcomes in twin pregnancies is unclear due to conflicting findings. This retrospective study aimed to examine VCI prevalence and related risk factors in twin pregnancies and its association with adverse perinatal outcomes. Methods: Women with twin pregnancies who delivered between January 2012 and December 2021 in a single tertiary hospital were included. The participants were divided into dichorionic (DC) and monochorionic diamniotic (MCDA) groups, and their maternal and fetal characteristics and VCI rates were compared. Logistic regression models were used to identify risk factors for VCI and VCI-related perinatal outcomes. Results: Among the 694 twin pregnancies included in this study, the VCI rate was significantly higher in MCDA than in DC twins. Body mass index and MCDA twins were significant risk factors for VCI, whereas assisted reproductive technology pregnancy was a significant protective factor against VCI. In DC twins, VCI did not affect perinatal outcomes. Conclusion: In MCDA twins, VCI was a significant risk factor for fetal growth restriction, twin-to-twin transfusion syndrome, and preterm birth at

Indigenous trees have great economic potential and ecological benefits for enhancing environmental prosperity, mostly in forestry and the forest products sector in the developing countries of Sub-Sahara Africa. The baobab (Adansonia Digitata L.) is known as the African green jewel in both fruit production and medicinal benefits also remarkable for so many forest products exported across the world. Research conducted in the different Sub-Saharan African sub-regions has shown this iconic tree with a majestic outlook has a priority tree species for local and foreign use and conservation. However, data on the benefits and conservation of baobab trees in Africa, especially the Sub-Saharan countries is limited. This study aimed to assess the predominant geo-graphical distribution of the tree, the indigenous (cultural, socio-economic, ecological, and medical/health) benefits, and the conservation strategies of the baobab resources in Sub-Saharan Africa. The baobab tree's succulent roots, bulbs, branches, fruit, pods, foliage, and petals are all nourishing. Baobab parts have been used for diverse reasons in Africa, some countries of Asia, and Europe for the past two centuries due to their medicinal well-being properties. In addition, the medicinal applications of the plant parts are discussed. Many authors have highlighted the baobab tree as one of the most important trees to be saved and localized in Africa because of its high indigenous usage and commercial worth. Anthropogenic global warming may induce a drop in baobab species, which could inflict negative impacts on African economies. As a result, it's critical to research the species' likely future distribution and develop conservation policies. Literature was consulted for records and availability of this tree in the Western, Central, Eastern, and Southern African species records and it was also analyzed what percentage of the current environment would be appropriate in the future. Recent studies suggested that farmers and the locals be provided free seeds and seedlings to encourage biological rejuvenation to maximize the plant's potential, people should be informed about the additional uses of baobab that have been discovered. Individuals must also be educated on simple sustainable agroforestry activities that can be performed in plant and forest management.