In France, the regional airport’s demand for services is facing challenges due to the continuous expansion of the high-speed train, high-speed line, and highway networks. This study focuses on the viability of regional airports in France through technical efficiency using data envelopment, principle component analysis, Malmquist productivity index, and regression analysis using bootstrapping. To face the current competitive environment, the regional airports in France adopted strategies, such as the construction of low-cost carrier (LCC) dedicated terminals (LCCTs) with lower expenses to attract more LCCs, increasing non-aeronautical revenue, and hosting regional hubs of LCCs. This is the first study that analyzes all of the French regional airports. The findings indicate that the existence of LCCTs positively affects technical efficiency on the airport’s performance, and share of LCCs at a regional airport leads to neither the efficiency nor the profit level.

As Li-ion batteries use is spreading, incidents in large energy storage systems (stationary storage containers, …) or in large-scale cell and battery storages (warehouse, recyclers, …), often leading to fire, are occurring on regular basis. Water remains one of the most efficient fire extinguishing agents for tackling those battery incidents and large quantities are usually necessary. Since bat-teries contains various potentially harmful components (metals and their oxides or salts, sol-vents…) and that thermal runway induced battery incidents are accompanied with complex and potentially multistage fume emissions (containing both gas and particles) the potential impact of fire run-off water on the environment should be considered and assessed carefully. The tests presented in this paper focus on the analysis of the composition of run-off waters used to spray NMC Li-ion modules under thermal runaway. It highlights that waters used for fire-fighting are susceptible to contain many metals, including Ni, Mn, Co, Li and Al mixed with other carbonaceous species (soot, tarballs) and sometimes undecomposed solvents used in the elec-trolyte. Extra-polation of pollutant concentrations compared with PNEC values showed that, for large scale incidents, run-off water could be potentially hazardous to the environment.

This study extends the CGAN-based MODIS cloud vertical-profile (64×64-scene, about 70km width×15km height) retrieval technique developed by Leinonen et al. (2019) [1] to construct seamless 3D cloud fields for the MODIS granules [2]. Firstly, the accuracy and spatial continuity of the Leinonen et al. [1] retrievals are statistically evaluated. Then, according to the characteristics of the retrieval error, a spatially overlapping-scene ensemble generation method and a bi-directional Ensemble Binning Probability Fusion (CGAN-BEBPF) technique are developed, which improves the CGAN retrieval accuracy and support to construct seamless 3D clouds. The CGAN-BEBPF technique involves three steps: cloud masking, intensity scaling, and optimal value selection. It ensures adequate coverage of the low reflectivity areas while preserving the high reflectivity cloud cores. The technique is applied to retrieve the 3D cloud fields of Typhoon Chaba and a multi-cell convective system. The cloud structures of the CGAN-BEBPF results are highly consistent with the ground-based radar observations. It can retrieve weak clouds at the top levels of convective storms and hurricanes that were missed by ground-based radars and fill the gaps of the ground-based radar lower-level PPI scan. Overall, CGAN-BEBPF can be automated to retrieve the rich informative 3D structures of typhoons and severe convective systems over the oceans along the MODIS swath, which certainly presents great value for improving maritime and near-shore typhoons and convection prediction and other cloud-sensitive applications.

SOC stock (SOCS) changes caused by land use changes are still unclear, and understanding this response is essential for many environmental policies and land management practices. In this study, we investigated the temporal-spatial and vertical distribution characteristics of SOCS on the Western Sichuan Plateau (WSP) using the sparrow search algorithm-random forest regression (SSA-RFR) models with excellent model applicability and accuracy. The temporal-spatial varia-tions in the SOCS were modeled using 1080 soil samples and a set of nine environmental covariates. We analyzed the effect of land use changes on the SOCS on the WSP. The total SOCS increased by 18.03 Tg C from 1990 to 2020. The results of this study confirmed that the SOCS in the study area has increased significantly since 2010, with an increase of 27.88 Tg C compared to the total SOCS in 2010. We found that the spatial distribution of the SOCS increased from southeast to northwest, and the vertical distribution of the SOCS in the study area decreased with increasing soil depth. Forest and grassland are the main sources of SOCS, the total SOCS in the forest and grassland accounted for 37.53 and 59.39% of the total SOC pool in 2020, respectively. Expansion of the wetlands, forest, and grassland areas could increase SOCS in the study area.

Today's city needs more than ever methodological devices that ensure a specific urbanism, in keeping with the complexity of relationships that occur in the urban space. Networks or systems of diverse nature must be activated to achieve a certain success of the city, even more so in its fragile central fabrics. The study is focused on the historic neighborhoods of the city of Jaén (Spain), which have a high vulnerability index. The aim is to establish a strategy to revitalize their urban and social capital and improve their articulation with the rest of the urban and territorial structure. A methodological proposal for the analysis of vulnerability factors and an urban and cartographic analysis of the public space is addressed through an interweaving of a triple network: environmental, social, and urban. For this purpose, the configuration of this overlapping network of analysis and formulation of criteria is presented, which considers the urban multiplicity and promotes new dynamics for the integrated urban regeneration of the area and for the activation of public and collective urban spaces.

Introduction: maxillary hypoplasia and mandibular asymmetry may be corrected with orthognathic surgery at the completion of growth. Many patients require segmental Le Fort I osteotomies to obtain the most stable results. Unfortunately, if Invisalign is chosen for pre-surgical preparation, ClinCheck © software does not allow for prediction when these complex surgeries are planned. The objective of this paper was to show the potential of aligners beyond its software in most complex cases like multiple-piece maxillary osteotomies in cleft and non-cleft patients. Method: Thirteen patients who underwent pre-surgical treatment with clear aligners-Invisalign (study group) were matched in terms of diagnosis, surgical procedure, and orthodontic complexity with thirteen patients treated using fixed appliances (control group). A technique based on simple superimposition was devised to enhance the software for creating a suitable occlusion for segmental pre-surgical treatments. Virtual curves following the lower arch were employed to guide the correct pre-surgical positions of the upper teeth. The amount of impressions required in both groups to achieve satisfactory pre-surgical alignment of the segmented arches was compared. Results: one or no refinement phase were needed in the Invisalign group to reach an acceptable pre-surgical occlusion while the amount of pre-surgical impressions taken in order to reach adequate coordination with fixed appliance treatment was slightly higher. The average overall treatment duration did not show a statistically significant variation between the groups. Conclusions: it appears that clear aligner could serve as an effective treatment for individuals with skeletal discrepancies, including cleft and craniofacial anomalies, necessitating segmental Le Fort I osteotomies when aided by the suggested superimposition approach during digital pre-surgical movement simulations. More sophisticated softwares will certainly be implemented in the future.

Deep Learning (DL) oriented document processing is widely used in different fields for extraction, recognition, and classification processes from raw corpora of data. The article examines the application of deep learning approaches, based on different neural network methods, including Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), and Convolutional Neural Networks (CNN). The compared models were combined with two different word embedding techniques, namely: Bidirectional Encoder Representations from Transformers BERT and Gensim Word2Vec. The models are designed to evaluate the performance of architectures based on neural network techniques for the classification of CVs of Moroccan engineering students at ENSAK(National School of Applied Sciences of Kenitra, Ibn Tofail University). The used dataset included resumes collected from engineering students at ENSAK in 2023 for a project on the employability of Moroccan engineers in which new approaches were applied, especially machine learning, deep learning, and big data. Accordingly, 867 resumes were collected from five specialties of study (Electrical Engineering, Networks and Systems Telecommunications, Computer Engineering, Automotive Mechatronics Engineering, Industrial Engineering). The results revealed good performance of the proposed models based on the BERT embedding approach compared to models based on the Gensim Word2Vec embedding approach. Accordingly, the CNN-GRU/Bert model achieved slightly better accuracy with 0.9251 compared to other hybrid models.

Finding a good MIMO system model also major issue in Wireless Communication system. It is facing with so many problem, one of the major problem is finding good system model in terms of capacity and transmitting antenna system. In this paper, we analyze the channel capacity of various MIMO system model with some constant SNR level and outage probability. We establish a novel idea for MIMO system models as consider as 2^N- MIMO system model and find-out change in channel capacity when different transmitting antennas with constant SNR and outage probability. The channel capacity ratio CC_R is presented here on the basis of 2^N- MIMO channel capacity model. Number of transmitted antenna presented in MIMO system is increases is well-known however paper shows change in capacity in simple form.

Increasingly, architects are looking towards nature to design more sustainable, efficient cities to reduce the environmental impact of urban life. At the moment, plants are incorporated into urban design for conservation or aesthetic reasons. Here, I argue plants can be rationally designed into synthetic systems based on chemical and other functional traits to increase the stability of urban infrastructure, protect native biodiversity, and promote human health while meeting key UN Sustainable Development Goals.

Advances in genetic engineering have placed synthetic biology at a prime position to develop new products, materials, and services that could contribute to the 2030 UN Sustainable Development goals. These include novel materials for water purification, new bio-based products to replace toxic industrial chemicals, and engineered organisms for bioremediation. Supporting the development of synthetic biology initiatives in developing countries is needed to ensure these benefits are open to all.

In this study, the microbial strain was isolated from the humus soil to ferment Sophora flavescens and Eleutherococcus sessiliflorus extracts. The isolated microbial was identified as Bacillus genus by 16S rRNA sequence analysis. The fermented plant extracts exhibited the antifungal effects against four types of the plant pathogens such as P. carotorum, B. cinerea, C. fructicola Sau-3, and C. gloeosporioides according to incubation time. Especially, the fermented plant extracts showed the most active activities for Colletotrichum genus to inhibit mycelium growth. Metabolite changes in fermented S. flavescens and E. sessiliflorus extracts were confirmed through LC-Q-TOF/MS. Flavonoid and peptide derivatives were improved in fermented S. flavescens and E. sessiliflorus extracts compared to their unfermented one, respectively. This study suggested that the isolated Bacillus microbial fermentation could be a valuable tool in improving the bioactivity of S. flavescens and E. sessiliflorus extracts to have potential with more environmentally-friendly antifungal agents.

China's vast geographical and climatic diversity presents distinct challenges to its aviation industry, especially in understanding Density Altitude (DA). The study reveals a concentration of airports in the eastern and central regions due to socio-economic factors, while the west, shaped by the Tibetan Plateau, faces infrastructural constraints owing to geographical barriers and limited economic activity. Notable DA variations, particularly negative values in the northeast and discrepancies between DA and elevation in the south, underscore operational complexities. The prominent influence of humidity on DA, especially in the southern coast, prompts a reevaluation of conventional aviation practices. To address these challenges, there's a pressing need for specialized training, region-centric flight planning, comprehensive risk assessment, and increased awareness about humidity's impact on DA. As China's aviation sector expands, harnessing these insights is crucial for sustained operational excellence.

Evaluating the economic impact of airports is crucial for understanding the benefits they bring to a region. However, when an area has more than one airport, it becomes essential to analyze each airport's contribution to the local economy to make informed investment and policy decisions. Thus, studying economic models that can distinguish each airport's impact on the region's economy becomes essential. In this context, this paper aims to compare three different approaches to determine the economic contribution of airports in a given region and identify their social and economic benefits. The International Civil Aviation Organization recommends using Input-Output analysis in this context. The study considered three weight factors for the Input-Output basic model: circular buffer, displacement time, and Huff's gravitational model. The analysis was performed using the three largest airports in São Paulo's state, Brazil, due to their proximity and influence on the surrounding area. The models were compared based on their efficiency and accuracy in reflecting the reality of the case study context. The study identified the most suitable model for establishing correlations between investments made in airport infrastructure and the generation of gross domestic product, employment, and added value. This study fills a gap in the existing literature by proposing improvements to the methods for evaluating airports' economic and social benefits. In recent times, airport investors, both in the government and private sectors, have become increasingly demanding in their need for accurate analyses before making investments. Therefore, the results of this paper will provide valuable insights into the benefits of investing in airport infrastructure and help policymakers and investors make informed decisions.

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e. professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies. This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.

A simple approach was developed to predict corn yields using the MoDerate Resolution Imaging Spectroradiometer (MODIS) data product from two geographically separate major corn crop production regions: Illinois, USA and Heilongjiang, China. The MOD09A1 data product, which are 8-day interval surface reflectance data, were obtained from day of the year (DOY) 89 to 337 to calculate the leaf area index (LAI). The sum of the LAI from early in the season to a given date in the season [end of DOY (EOD)] was well fitted to a logistic function and represented seasonal changes in leaf area duration (LAD). A simple phenology model was derived to estimate the dates of emergence and maturity using the logistic function parameters b1 and b2, which represented the rate of increase in LAI and the date of maximum LAI, respectively. The phenology model predicted emergence and maturity dates fairly well, with root mean square error (RMSE) values of 6.3 and 4.9 days for the validation dataset, respectively. Two simple linear regression models (YP and YF) were established using LAD as the variable to predict corn yield; the yield model (YP) used LAD from predicted emergence to maturity, and the yield model (YF) used LAD for a predetermined period from DOY 89 to a particular EOD. When state/province corn yields for the validation dataset were predicted at DOY 321, near completion of the corn harvest, the YP model performed much better than the YF model, with RMSE values of 0.68 t/ha and 0.66 t/ha for Illinois and Heilongjiang, respectively. The YP model showed a similar or better performance, even for the much earlier yield prediction at DOY 257, compared to that of the YF model. In conclusion, the phenology and yield models were developed based only on logistic changes in remote sensing-derived LAD, and predicted phenological dates and corn yields with considerable accuracy and precision for the two regions selected for this study. However, these models must be examined for spatial portability in more diverse agro-climatic regions.

This article analyzes the Franco-Spanish invasion of Vietnam from 1858 to 1860. Research is based on documents such as correspondence, reports, archives and diplomatic treaties as well as monographs from the time France intended to invade Vietnam through missionary activities until the end of the Franco-Spanish invasion. The article focuses on three basic issues that are the causes of the alliance, the evolution of the French and Spanish coalition invasion in Vietnam and its impact on stakeholders. The research results on the Franco-Spanish invasion of Vietnam indicated that the invasion carried out by this alliance was more special than that of the other French coalitions before. The invasion was based on an alliance without any commitment to the interests and responsibilities of the parties. The goals of France and Spain in this invasion were different. That led to conflict between France and Spain during the invasion and the fall of the alliance. France achieved its goal through an invasion that turned Vietnam into a colony, while Spain had barely achieved its desire to have commercial and missionary interests in the area.

French Guiana, located in the Guiana Shield, is a natural reservoir for many zoonotic pathogens that are of considerable medical or veterinary importance. Until now, there are few data available on the description of parasites circulating in this area, especially on protozoan belonging to the phy-lum Apicomplexa; conversely, the neighbouring countries describe a high parasitic prevalence in animals and humans. Epidemiological surveillance is necessary, as new potentially virulent strains may emerge from these forest ecosystems, such as Amazonian toxoplasmosis. However, there is no standard tool for detecting protozoa in wildlife. In this study, we developed Meat-Borne-Parasite, a high-throughput meta-barcoding workflow for detecting Apicomplexa based on Oxford Nanopore Technologies sequencing platform using the 18S gene of fourteen Apicomplexa-positive samples collected in French Guiana. Sequencing reads were then analysed with MetONTIIME pipeline. Thanks to a scoring rule, we were able to classify as Apicom-plexa-positive 10 samples out of 14 and reveal the presence of co-carriages. The same samples were also sequenced with Illumina platform, for validation purposes. On samples identified as Apicomplexa-positive by both platforms, a strong positive correlation at up to genus level was reported. Overall, the presented workflow represents a reliable method for Apicomplexa detec-tion, which may pave the way for more comprehensive biomonitoring of zoonotic pathogens.

The Aviation industry in Malaysia is categorized as highly regulated and dominated by Government Linked Companies (GLCs) via monopolistic concessions due to its nature of strategic national importance and security. Connectivity is an essential component of economic activity and a catalyst for business growth. Since the invention of aircraft, air connectivity has expanded businesses and markets, facilitating trade, encouraging Foreign Direct Investment (FDI) and enabling tourism. This case study aims to provide a holistic analysis of the Malaysia Airport Holdings Berhad (MAHB) strategic planning framework and discuss its effectiveness towards its strategy formulation to address its market dynamics, both domestically and abroad. From military superiority to economic connectivity, aviation, one of humanity's greatest inventions, has advanced human civilization over the past 150 years. With the emergence of low-cost carriers, air travel patterns have shifted dramatically, with the increase of travel and trade, due to its time efficiency. With the trend of globalization and the liberation of airspace in recent decades, aviation enables the movement of people and goods that foster a borderless marketplace at an exponential growth rate. With technological innovation, pressure over climate change and the shift in travelers' behavior and patterns, strategic planning becomes more crucial and complex for aerodrome operators to create a sustainable competitive advantage among their regional rivals. However, strategic planning is dependent on several critical success factors. The role of management leadership and an inclusive strategy to adapt to the changes in market dynamics are essential for survival in business competition.

With the integrated development of the Internet, wireless sensor technology, cloud computing, and mobile Internet, there has been a lot of attention given to research about and applications of the Internet of Things. A Wireless Sensor Network (WSN) is one of the important information technologies in the Internet of Things; it integrates multi-technology to detect and gather information in a network environment by mutual cooperation, using a variety of methods to process and analyze data, implement awareness, and perform tests. This paper mainly researches the localization algorithm of sensor nodes in a wireless sensor network. Firstly, a multi-granularity region partition is proposed to divide the location region. In the range-based method, the RSSI (Received Signal Strength indicator, RSSI) is used to estimate distance. The optimal RSSI value is computed by the Gaussian fitting method. Furthermore, a Voronoi diagram is characterized by the use of dividing region. Rach anchor node is regarded as the center of each region; the whole position region is divided into several regions and the sub-region of neighboring nodes is combined into triangles while the unknown node is locked in the ultimate area. Secondly, the multi-granularity regional division and Lagrange multiplier method are used to calculate the final coordinates. Because nodes are influenced by many factors in the practical application, two kinds of positioning methods are designed: the unknown node is in the positioning unit or not. When the unknown node is on the side of the positioning unit, we use the method of vector similarity. Moreover, we use the centroid algorithm to calculate the ultimate coordinates of unknown node. When the unknown node is not on the side of the positioning unit, we establish a Lagrange equation containing the constraint condition to calculate the first coordinates. Furthermore, we use the Taylor expansion formula to correct the coordinates of the unknown node. In addition, this localization method has been validated by establishing the real environment.

HIV early detection (CD4 counts ≥350 cells/μL) is correlated with higher life expectancy among people living with HIV (PLHIV). Several factors including physical, cultural, structural, and financial barriers have contributed to HIV late detection. This is the first-of-its-kind study on the regional differences in early detection of HIV within Tajikistan and any country in the Central Asia region. Utilizing Tajikistan Ministry of Health's national HIV data (N=10,700) spanning 2010 to 2023, we developed median regression models with median CD4 cell count as the outcome and as predictors: time (years), region, age, gender, and area (urban/rural status). Individuals younger than 19 years old are more likely to be detected early for HIV, whereas those older than 39 years are more prone to late detection. Given their active engagement in age-related and sexual activities, those older than 39 years face a higher risk of HIV transmission to others if diagnosed late. Therefore, they require further attention and targeted interventions. Females are detected earlier compared to their male counterparts, regardless of region of residence. Rural populations are detected earlier in most years compared to their urban counterparts. The COVID-19 pandemic accelerated HIV early detection in 2021 but most regions have returned to near pre-pandemic levels of detection in 2022 and 2023. These fluctuations in early detection may signify a shift in attention and resource allocation, potentially affecting efforts to address access gaps during the initial year of the COVID-19 pandemic. There are significant health inequities among different demographic and geographic groups which warrant further attention.

As Artificial Intelligence (AI) technology, particularly Machine Learning algorithms, becomes increasingly ubiquitous, our abilities to understand and interpret AI and machine learning algorithms are becoming increasingly desirable. Visualization has been used as a common tool to view and understand complex machine learning processes. In this paper, we will focus on developing a general framework for the visualization of machine learning models as a scalar valued multi-dimensional function to help users understand how the models behave over different viewing spaces. We first give a formal definition of the visualization problem. Interpolation-based morphing and subspace sampling techniques are applied to generate various renderings through projections and cross-sections of the model space as 3D surfaces or heatmap images. This method will be applied to two real-world datasets and applications: the diagnosis of Alzheimer's Disease (AD) using a human brain networks dataset and a real-world benchmark dataset for predicting home credit default risks. The visualizations show that different machine learning algorithms can behave quite differently under different conditions.

Human induced pluripotent stem cell (iPSC)-based model systems can be used to produce blood cells for the study of both hematologic and non-hematologic disorders. This commentary discusses recent advances that have utilized iPSC-derived red blood cells, megakaryocytes, myeloid cells, and lymphoid cells to model hematopoietic disorders. In addition, we review recent studies that have defined how microglial cells differentiated from iPSC-derived monocytes impact neurodegenerative disease. Related translational insights highlight the utility of iPSC models for studying pathologic anemia, bleeding, thrombosis, autoimmunity, immunodeficiency, blood cancers, and neurodegenerative disease such as Alzheimer’s.

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.

Our aim was to determine the secondary antibody deficiency profiles of patients in a mesoregion of São Paulo state, Brazil, focusing on infectious diseases. Demographic characteristics, clinical and laboratory data were obtained from electronic files; infections were classified as organ-specific and graded as mild, moderate, life-threatening, and fatal. Non-Hodgkin lymphoma (NHL) accounted for 30% of patients, nephrotic syndrome (NS) 25%; chronic lymphocyte leukemia 20%, and multiple myeloma 15%. Patients with NS were younger than those in other groups, and hypo-γ-globulinemia was detected in 94.1%, IgG <400 mg/dL in 60.0%, IgA <40 mg/dL in 55.0%, and CD19 <20 cells/mm³ in 30.0%. One hundred and one infections were found; 82.1% were classified as mild or moderate, 7.9% as life-threatening, and 1.9% as fatal. Respiratory tract infections were more prevalent (41.5%), and pneumonia accounted for 19.8%. Lower levels of infections were found in patients with NS compared with NHL (P=0.0001). Most patients progressed to hypo-γ-globulinemia and secondary antibody deficiency after treatment with immunosuppressants, and mild and moderate infections were predominant. These therapies are increasing in patients with different diseases, therefore monitoring hypo-γ-globulinemia and infections may help to identify patients at high risk for severe complications, antibiotic prophylaxis or treatment, and immunoglobulin replacement

Nowadays, the identification and characterization of grapevine cultivars resilient to climate and water stress while preserving quality traits is crucial for the wine industry. Therefore, the objective of this work was to characterize according to their aromatic potential 9 white and 6 red minority cultivars recently recovered from Castilla-La Mancha region (Spain), subjected at two different water deficit regimes: rainfed, with subsistence irrigation, and irrigated. For this, the varietal aromatic potential index (IPAv) and the detailed aromatic composition were analyzed by HS-SBSE-GC/MS, in extracts of two different ph. For IPAv values, red varieties did not show a clear trend with respect to irrigation. However, in white minority varieties, higher values were obtained under irrigation conditions. Thus, a clear differentiation of the minority varieties in comparison to the references was observed, primarily attributed to the content of esters and acids, in both white and red varieties. A notable contrast was observed at different pH, indicating a greater extractability of certain compounds like linalool, under more acidic conditions. This suggests that some recovered minority cultivars could be promising for cultivation in semi-arid regions with limited water, contributing to the wine sector sustainability in the future.

Violence against paramedics is increasingly recognized as an important occupational health problem, but pervasive and institutionalized underreporting hinders efforts at risk mitigation. Earlier research has shown that the organizational culture within paramedicine may contribute to underreporting and researchers have recommended involving paramedics in the development of violence prevention policies, including reporting systems. Eighteen months after the launch of a new comprehensive violence reporting system in Peel Region, Ontario, Canada, we surveyed paramedics about their willingness to report violent encounters. A total of 204 (33% of eligible) paramedics chose to participate, of whom 67% (N=137) had experienced violence since the launch of the new reporting process, with 83% (N=114) reporting the incidents at least some of the time. In choosing to report, participants cited the accessibility of the new reporting process and the desire to promote accountability among perpetrators while contributing to a safer workplace as motivating factors. Their decisions to file a report, however, could be influenced by the perceived ‘volitionality’ and severity of the violent encounters, particularly in the context of (un)supportive co-workers and supervisors. Ultimately, the participants’ belief that the report would lead to meaningful change within the service was a key driver of reporting behavior.

This study examines the projected impact of climate change on the Density Altitude (DA) at Chinese airports during the summer by the end of the 21st century. Findings indicate that climate change is expected to significantly increase the DA at all Chinese airports, with an estimated rise between 300 and 800 feet. The analysis suggests temperature increases will universally contribute to a rise in DA. Pressure changes, however, are more variable. Most airports are predicted to see an increase in pressure, which could offset some temperature effects on the DA. Airports in eastern China are expected to see a decrease in pressure, amplifying the effects on DA and creating operational challenges.

Aim: The aim of this study was to investigate if tests used to assess core stability could be used to determine success in physiological tests applied to assess dynamic balance and agility for a young active population. Methods: Pearson's r correlation coefficient was used to assess the relationship between the core stability tests and the dynamic balance and agility tests. Evaluation of the tests was established using Cronbach's coefficient of variance as part of intra-rater reliability tests. An analysis of 18 active college aged students was conducted (males: n= 13, females: n= 5). The mean ± SD age for males was 19.2 years ± 3.22 years and for females was 19.4 years ± 1.14 years. Conclusion: The results indicate that there is no significant relationship between tests that assess core stability and tests conducted to assess dynamic balance in active young adults. With the exception of the abdominal flexion test, no significant relationship exists between the remaining core stability tests and agility T-Test. Core stability is not a determinant of balance and agility.

Long term Precipitation and temperature variations are one of the main determinants of climate variability of one’s area. The aim of this study is to determine trends variation in climatic elements of temperature and precipitation in the southern zone of Tigray regional state, Ethiopia. The station is assumed for the study of climatic records over southern zone of the region in detection for probable trends. The daily, monthly and annual precipitation totals and temperature observed at korem meteorological station were used for the period of 1981-2010 for Precipitation and 1985 – 2010 for minimum and maximum temperature. Summary of descriptive statistics and Mann Kendall test methods were employed for the observed data analysis to demonstrate any existence of possible trends. The main findings of the study indicated that the mean and maximum temperature had a general increasing trend; however, minimum temperature showed decreasing trend. In general annual temperature from 1985 – 2010 of the area showed a warming trend. Moreover analysis of the 30 years (1981-2010) annual precipitation showed a coefficient of variation ranging from 33.77 – 233 %. It indicated that the precipitation dissemination is not normal with large year to year variances.

Cameroon introduced the malaria vaccine in its routine immunization programme on 22 January 2024, in the 42 districts out of 200, among the most at risk of malaria. A cross-sectional analysis of data on vaccine key events in the introduction roadmap and vaccine uptake during the first 30 days was conducted. In addition to available gray literature related to the introduction of the malaria vaccine, data on malaria vaccine uptake by vaccination session, collected through a digital platform, were analyzed. A total of 1,893 reports were received from 22 January 2024 to 21 February 2024 from 766 health facilities (85% of overall completeness). Two regions out of 10 recorded less than 80% of completeness. As of 21 February 2024, 13,811 children have received the first dose of the malaria vaccine, including 7,124 girls (51.6%) and 6,687 boys (48.4%). Thirty six percent of children were vaccinated through outreach sessions versus 61.5% through sessions in fixed posts. The overall monthly immunization coverage with the first dose was 37%. Early results have shown positive attitudes towards and acceptance of malaria vaccines. Suboptimal completeness of data reporting and low coverage highlight persistent gaps and challenges in vaccine rollout.

Annotating training data is a time consuming and labor intensive process in deep learning, especially for images with many objects present. In this paper, we propose a method to allow deep networks to be trained on data with reduced numbers of annotations (per image) in heatmap regression tasks (e.g. object detection and counting), by applying an asymmetric loss function. In a real scenario, this reduction of annotations can be imposed by the researchers (e.g. ask the annotators to label only 50% of what they see in each image), or can potentially counteract unintentionally missing labels from the annotators. To demonstrate the effectiveness of our method, we conduct experiments in two domains, crowd counting and wheat spikelet detection, using different deep network architecture. We drop various percentages of instance annotations per image in training. Results show that an asymmetric loss function is effective across different models and datasets, even in very extreme cases with limited annotations provided (e.g. 90% of the original annotations reduced). Whilst tuning of the key parameters are required, we find that setting conservative parameter values can help more realistic situations, where only small amounts of data have been missed by annotators.

The interconnection between the objectives of territorial development and the agro-ecological transition highlights the value of past knowledge in the sustainable management of resources and agro-ecological systems. However, retrospection in rural areas presents difficulties due to a lack of data. This paper contributes to the search for such knowledge from the past by developing an interactive methodology capable of combining heterogeneous sources of information and the activation of local collective memory. Its effectiveness is based on ensuring the interoperability of information and communication in an environment simultaneously shaped by geoinformatics and 3D geo-visualizations. This virtual environment fosters participation and interactivity, supported by representations of the paleo-landscape. Furthermore, synergies were achieved between information sources and their integration into local spatial systems. The application example involved identifying a rice field that existed from the 15th to the 19th century in Thessaly, Greece. It is an interesting case because the location and organization of cultivation in combination with its spatio-temporal coordination ensures the sustainable use of natural resources. It appears that the interplay between information and communication facilitates community participation and the activation of its collective memory as a source of information that enriches the search and local intelligence.

Paramedics are increasingly being subjected to violence, creating the potential for significant physical and psychological harm. Where a patient has a history of violent behavior, hazard flags - applied either to the individual, their residential address, or phone number - can alert paramedics to the possibility of violence, potentially reducing the risk of injury. Leveraging a novel violence reporting process embedded in the electronic patient care record, we reviewed violence reports filed over a thirteen-month period since its inception in February 2021to assess the effectiveness of hazard flagging as a potential risk mitigation strategy. Upon reviewing a report, paramedic-supervisors can generate a hazard flag if recurrent violent behavior from the patient is anticipated. In all, 502 violence reports were filed, for which paramedic-supervisors generated hazard flags in 20% of cases (n=99). In general, cases were not flagged either because the incident occurred at a location not amenable to flagging, or because the supervisors felt that a hazard flag was not warranted based on the details in the report. Hazard flagging was associated with an increased risk of violence during subsequent paramedic attendance (Odds Ratio [OR] 6.21, p

The identification of fetal cells in the blood and tissues of healthy mothers raised questions about the potential alloreactive origins of various diseases, such as autoimmunity, diabetes, arteriosclerosis, and cancer. However, the extent to which alloreactivity contributes to these diseases remains unverified. This study presents a basic mathematical disease model based on the genes’ origin and immunological interactions. This model, grounded in set theory, classifies these immunological interactions based on their intrinsic, extrinsic, and allogeneic nature. Therefore, this model offers an unexpected common theoretical foundation for understanding alloreactivity, genetic diseases, and infections. Furthermore, this model provides a valuable framework for scrutinizing the role of alloreactivity in health and disease.

The Circular Bioeconomy (CBE) combines the concepts of bioeconomy and circular economy. As an alternative concept to the current fossil-based, linear economy, it de-scribes an economy based on the efficient valorization of biomass. It is regional in nature and aims to improve sustainability. An analysis of the transition process, by identifying its success criteria and assessing its impacts through the modelling of technology-specific scenarios is necessary to ensure that CBE concepts are sustainable. However, a compre-hensive consideration of regional influences on both is lacking. Based on extensive literature research and an expert survey, we (i) present a compre-hensive catalog of CBE success criteria and discuss their region-specific character and (ii) develop a methodology based on evaluation matrices that enable to match CBE technolo-gies with regions. The matrices support the evaluation of technological and regional characteristics influencing the successful CBE implementation. The results show that the success criteria "biomass resources", "technological", and "social" are perceived as highly important, and that most of the success criteria are both region- and technology-specific, highlighting the relevance of developing matrices to match them. We describe such matrices indicatively for the two broadest and most im-portant success criteria clusters “social acceptance” and “biomass supply chain”. With this, we substantiate the regional nature of CBE and raise the awareness on the importance of considering regional conditions in CBE transition processes. Furthermore, we provide practical guidance on how regional conditions can be reflected in the selection of technologies, e.g. in regional CBE technology scenarios.

: Seaweeds are among the most important biomass feedstocks for the production of third generation biofuels. They are also efficient in carbon sequestration during growth, and produce a variety of high value chemicals. Given these characteristics together with the relatively high carbohydrate content, seaweeds have been discussed as an ideal means for CO2 capture and biofuel production. Though third generation biofuels have emerged as some of the best alternatives to fossil fuels, there is currently no large-scale production or mainstream use of such liquid fuels due to the many technical challenges and high production costs. The present study describes the concept of coastal marine biorefineries as the most cost-effective and sustainable approach for biofuel production from sea-weeds as well as atmospheric carbon capture and storage (CCS). The suggested refinery system makes use of marine resources, namely seawater, seaweed, and marine microorganisms. Firstly, extensive screening of the current literature was performed to determine which technologies would enable the emergence of such a novel biorefinery system and its merits over conventional refineries. Secondly, the study investigates various scenarios assessing the potential of seaweeds as a means of carbon sequestration. We demonstrate that the removal of 100 Gigatons of excess CO2 using seaweed farms can be achieved in around 4 months to less than 12 years depending on the area under cultivation and the seaweed species. The total bioethanol that could be generated from the harvested biomass is around 8 trillion litres. In addition, high-value chemicals (HVC) that could potentially be recovered from the process represent a considerable op-portunity with multi-billion-dollar commercial value. Overall, coastal marine biorefineries have strong potential for a sustainable green economy and rep-resent a rapid approach for climate change mitigation.

Abstract: Background: Irreversible electroporation (IRE) is a form of non-thermal ablation that delivers pulses of high voltage electrical current between electrodes. The role of IRE in the treatment of colorectal hepatic metastases is unestablished. This study is an international ques-tionnaire survey of the use of IRE for colorectal hepatic metastases. Methods: A questionnaire addressing views on the use of IRE for colorectal liver metastases was circulated to clinicians with an interest and/or expertise in this technique. Results: 64 clinicians from 17 different countries replied to the questionnaire. Thirty-six (56%) had experience of treating patients with colorectal liver metastases with IRE. The preferred mode of delivery of IRE was percutaneous treatment under CT guidance. Thirty-three (70% respondents) used IRE exclusively for lesions in proximity to inflow or outflow structures. Twenty (43% respondents) used IRE as their sole ablative treat-ment whilst 19 (40% respondents) used IRE in combination with thermal ablation. The maximum number of lesions that could be treated by IRE was two and preferred size of lesion was

The study of precipitation amount at different time scales constitutes an important issue in climate research and risk assessment. When dealing with daily totals, a frequent but sometimes underestimated problem is at what time the observation day begins. The choice of different starting times may lead to incompatibility between stations and incorrect identification of extreme events. In this work, the problem of temporal misalignment between precipitation datasets characterized by different starting time of the observation day is analyzed. The most widely used adjustment methods (1day and uniform shift) and two methods based on reanalysis (NOAA and ERA5) are evaluated in terms of temporal alignment, precipitation statistics and percentile distributions. As test series, the precipitation amount collected from 9 a.m. local time (09 LT) on the previous day to 09 LT on the target day (9-9 datasets) of the Padua and nearby stations in the period 1993-2022 have been selected. Results show that the reanalysis-based methods, in particular ERA5, outperform the others in temporal alignment, regardless the station. But, for the periods in which reanalysis data are not available, “1day” method, which shifts the daily amount back one calendar day, and “unif” method, which distributes uniformly the daily total from a 2-day moving window surrounding the target date, can be considered valid alternatives. On the other side, concerning the precipitation statistics, the reanalysis-based methods are not the best option, as they increase the precipitation frequency and reduce the mean value over wet days, NOAA much more than ERA5. Nevertheless, the uniform method provides a larger deviation from the original daily series. The use of the series of a station nearby the target one, which is mandatory in case of missing data, gives similar or better results than applying any adjustment method to the 9-9 series. General conclusions can hardly be drawn as they depend on the method and station. For the Padua dataset, the analysis was repeated at monthly and seasonal resolution. In general, the adjustment series show the most relevant changes in the precipitation statistics in summer and less temporal alignment with the original series in summer and autumn, the two seasons mainly affected by heavy rains in Padua. Finally, the percentiles distribution, analyzed for all the methods and stations, indicates that any adjustment method underestimates the percentile values, except ERA5. Only Legnaro, the station most correlated with Padua, gives results like ERA5.

Climate change is a major development challenge to Ethiopia. Unless adaptation measures are widely implemented, climate change can set back development efforts and achievements by years. Recognizing this, the Government of Ethiopia (GoE) and civil society organizations have since recently been making considerable efforts to tackle the climate change problem. This paper documents the experience of CARE International in Ethiopia in facilitating bottom-up approaches to promote community-led disaster risk management and climate change adaptation planning through a participator scenario planning (PSP) methodology. PSP is a coordinated approach which leverages a variety of stakeholders' skills and mandates to explore potential climate change risks and their impacts, and then develop locally relevant and shared adaptation action plans that support livelihoods, social capital and ecosystem resilience. The approach has facilitated timely access to and communication of seasonal climate advisories which in turn is empowering communities to take advantage of opportunities that climate presents, which is a key part of adapting to climate change. The institutionalization of the approach by district and regional disaster prevention and food security coordination offices in the southern pastoral regions of Ethiopia encouraged integration of PSP into community livelihood adaptation and local government development planning, hence continuity of the process. Sustainability is expected to be fully achieved when local government planning processes recognize the importance of and provides resources for the participation of meteorological services and community forecasting experts to help refine plans on a seasonal basis, and for systems for dissemination of advisories. Key words: Climate Change, Disaster Risk Reduction, Adaptation, Pastoralism, Ethiopia,

In the present work the problem of the attenuation of longitudinal sound oscillations in a conducting medium are considered. The proposed approach is based on the dynamic interaction of electron gas with the lattice vibrations. This interaction is manifested in the modification of kinetic equation for electrons. The process is accompanied by generation of an electric field.

This paper explores the impact of international university rankings on French universities. A multiple case study of three French universities examined the nature of these impacts at national, organisational, and individual level. A thematic analysis of interviews using NVivo software showed that the changes, either imposed by new policies or initiated by the university managers, have profoundly altered the traditional values of academia. The novel findings reveal the degree of influence of rankings and the perception of academics regarding the changes experienced. After describing the current state of affairs in the French higher education system, the paper predicts that universities will engage more actively in the quest for a better position in the future, and will consequently accept the rules and norms of rankings. In contributing to the discussion on the effects of quantification of higher education processes and outcomes to the academia, by analysing the perception of academics on the experienced evolutions. This paper addresses policymakers, university managers and researchers interested in understanding how evaluation instruments, such as international rankings affect organizations and individuals in the higher education sector.

In this paper, we introduce a model for the automatic generation of literary sentences in French. It is based on algorithms that we have previously used to generate sentences in Spanish and Portuguese, and on a new corpus consisting of literary texts in French that we have constructed, called [FR]. Our automatic text generation algorithm combines language models, shallow parsing and deep learning, artificial neural networks. We have also proposed and implemented a manual evaluation protocol to assess the quality of the artificial sentences generated by our algorithm, by testing if they fulfill four simple criteria. We have obtained encouraging results from the evaluators for most of the desired features of our artificially generated sentences.

This study explores optimizing Synthetic Aperture Radar (SAR) satellite constellation scheduling for multi-imaging missions in densely targeted areas using an in-house developed Modified Dynamic Programming (MDP) algorithm. By employing Mixed-Integer Linear Programming (MILP) to define the mission planning problem, the research aims to maximize observation of high-value targets within restricted planning horizons. Numerical simulations, covering a wide range of target numbers and satellite configurations, reveal the MDP algorithm’s superior mission allocation efficiency, enhanced success rates, and reduced revisit times, compared to the Greedy algorithm. The findings underscore the MDP algorithm’s improved operational efficiency and planning robustness for complex imaging tasks, demonstrating significant advancements over traditional approaches.

The acquisition of adverbs in French as L2 (FSL) by learners with different L1s, at various levels of proficiency, has been extensively studied within various SLA projects (ESF, Interfra etc.). In the generativist tradition, it has been noted that “high category adverbs” such as those related to Mood-evaluative, Mood-epistemic and Tense are present early in FSL data. In the functionalist school, the early presence of time adverbs and scope particles in learner varieties has been analysed in relation with the informational and syntactic structures observed in these varieties and in terms of their contribution to temporal reference and other semantic domains in discourse.

The EASY-NET network program (NET-2016-02364191 - Effectiveness of Audit and Feedback (A&F) strategies to improve health practice and equity in various clinical and organizational set-tings), piloted a new and more structured A&F strategy. This study compared the effectiveness of the new strategy versus the periodic publication of indicators alone in improving the appropri-ateness and timeliness of emergency health interventions in patients with Acute Miocardial In-farction (AMI) and ischemic stroke in the Lazio Region. Efficacy was evaluated according to a prospective quasi-experimental design of pre-post (2021-2022) intervention type with control group. The exposed are hospitals in the Lazio Region where professional teams voluntarily par-ticipated in the intervention. The control group is involved only in the usual reporting activities. Effectiveness analysis was conducted at the patient level. Regional health information systems were used to calculate process and outcome indicators. The effectiveness of the intervention was assessed with Difference In Difference models, comparing pre-post intervention periods between exposures and controls. Estimates were calculated in terms of the difference in percentage points (pp) between absolute risks. Sixteen facilities for the IMA pathway and 13 for the stroke pathway joined the intervention. The intervention reduced the proportion of 30-days readmissions after a hospitalization for ischemic stroke by 0.54 pp in the exposed patients with a significant difference of -3.80 pp (IC95% -6.57; -1.03; 5453 patients, 63.7% cases) in the exposed compared to controls. There were no statistically significant differences attributable to the implemented A&F interven-tion in the other indicators considered. The results show, for the first time in Italy, the impact of A&F interventions in an emergency setting using aggregated data from hospitals involved in the Lazio Region emergency network.

This work compared the performance of three methods for constructing a regional ensemble prediction system (EPS) for wind speed forecasts: dynamical downscaling, breeding of growth modes (BGM), and blending method. The Weather Research and Forecasting (WRF) model was used to downscale the European Centre for Medium-range Weather Forecast (ECMWF) EPS. In addition, as the BGM method needs observation data for generating scaling factors, an alternative method for generating scaling factors was proposed to eliminate dependence on observation data. One-month tests between October 1st and October 30th, 2020, were implemented to evaluate the performance of three methods in the Gansu province of China. The results demonstrate that the blending method outperforms the other two methods. Furthermore, the difference in performance is evident mainly in early forecast lead time and becomes negligible as forecast time increases.

In 1990 the Malaysian Government launched Vision 2020 with the goal of Malaysia becoming a ‘fully developed country’ by the year 2020. In this drive for development the country has been examining many of its key natural assets, exploring how to both preserve them whilst ensuring that they make the maximum possible contribution to national development goals. Endau Rompin is one of these assets, being the second largest National Park in Peninsula Malaysia. The rich tropical rainforest flora and fauna of the Park and its hinterland, however, are threatened by various anthropogenic forces, most notably deforestation and poaching; both of which have taken the Park’s flagship species - the Tiger Panthera tigris jacksoni – towards the brink of local extinction. Malaysia’s statutory East Coast Economic Region Development Council commissioned a study to consider ways of increasing tourism revenues from the Park while at the same time reversing these threats. The key conclusion drawn is that a more holistic, landscape-scale approach should be adopted, with Endau Rompin forming part of a wider strategic economic zone based around sustainable tourism and land management. The proposed expanded zone extends eastwards beyond the confines of the Park, across the coastal plain to the South China Sea, and onwards to the neighbouring Mersing Islands. This expanded zone is referred to as Malaysia’s new ‘Rainforest to Reef Region’.

This study aimed to evaluate the effectiveness of an intensive care unit (ICU) round checklist, FAST HUGS BID (Feeding, Analgesia, Sedation, Thromboembolic prophylaxis, Head-of-bed elevation, Ulcer prophylaxis, Glycemic control, Spontaneous breathing trial, Bowel regimen, Indwelling catheter removal, and De-escalation of antibiotics) in improving clinical outcomes for patients with severe trauma. Patients admitted to our trauma ICU between 2016 and 2020 were retrospectively analyzed. We divided the participants into two groups: before (before-FD, 2016-2017) and after (after-FD, 2019-2020) the checklist's implementation. We compared patient characteristics and clinical outcomes, including ICU and hospital length of stay (LOS) and in-hospital mortality. Survival analysis was performed using Kaplan–Meier curves and multivariable logistic regression models, and multiple linear regression analysis was used to identify independent factors associated with ICU and hospital LOS. Compared with the before-FD group, the after-FD group had significantly lower in-hospital mortality and complication rates, shorter ICU and hospital LOS, and reduced duration of mechanical ventilation. revealed that the checklist's implementation was a significant independent factor in reducing ICU and hospital LOS and in-hospital mortality. In this before/after study, we observed that the FAST HUGS BID checklist implementation was associated with decreased ICU and hospital LOS and in-hospital mortality.

The lipid fraction of margarines and fast-food French-fries, two types of foods traditionally high in trans fatty acids (TFA), is assessed. TFA data reported worldwide during the last 20 years have been gathered, and show that some countries still report high TFA amounts in these products. The content of TFA was analysed in margarines (2 store and 4 premium brands) and French-fries from fast-food restaurants (5 chains). Margarines showed mean values of 0.68% and 0.43% (gTFA/100g fat) for store and premium brands, respectively. French-fries values ranged from 0.49% to 0.89%. All samples were lower than the 2% set by some European countries as the maximum legal content of TFA in fats, and contained less than 0.5g/serving, so they could also be considered “trans free products”. This work confirmed that the presence of TFA is not significant in the two analysed products and contributes to update food composition tables, key tools for epidemiological and nutrition studies.

Bioethanol has many environmental and practical benefits as a transportation fuel. It is one of the best alternatives to replace fossil fuels due to its liquid nature which is similar to petrol and diesel fuels traditionally used in transportation. In addition, bioethanol production technology has the capacity for negative carbon emissions which is vital for solving the current global warming dilemma. However, conventional bioethanol production takes place based on an inland site and relies on freshwater and edible crops (or land suitable for edible crop production) for production, which has led to the food vs fuel debate. Establishing a coastal marine biorefinery (CMB) system for bioethanol production that is based on coastal sites and relies on marine resources (seawater, marine biomass and marine yeast) could be the ultimate solution. In this paper, we aim to evaluate the environmental impact of using seawater for bioethanol production at coastal locations as a step towards the evaluation of a CMB system. Hence, a life cycle assessment for bioethanol production was conducted using the proposed scenario named Coastal-Seawater and compared to the conventional scenario, named Inland-Freshwater (IF). The impact of each scenario in relation to climate change, water depletion, land use and fossil depletion was studied for comparison. The coastal-seawater scenario demonstrated an improvement upon the conventional scenario in all the selected impact categories. In particular, the use of seawater in the process had a significant effect on water depletion showing an impact reduction of 31.2%. Furthermore, reductions are demonstrated in natural land transformation, climate change and fossil depletion of 5.5%, 3.5% and 4.2% respectively. This indicates the positive impact of using seawater and coastal locations for bioethanol production and encourages research to investigate the CMB system.

The mineralogical indices, e.g., Quartz Index (QI), Carbonate Index (CI), Mafic Index (MI) for ASTER multispectral thermal infrared (TIR) data have been applied to various geological materials. The indices are proved to be robust in extracting geological information at the local scale. Considering the relatively narrow spatial coverage of each ASTER scene compared to LANDSAT, many scenes are needed when mosaicking the images to be mapped at regional scales. We develop a system to search ASTER data for a target area given the vast and expanding ASTER data archive. The data is then conditioned, prioritized, and the indices are calculated before finally mosaicking the imagery. The maps of the indices covering the very wide region of the central Tibetan Plateau are produced with this system. The characteristic features of the indices relating to their geology in the study area are analyzed and discussed. Many interesting lithological and structural information that are not currently well understood in the central Tibetan Plateau, the highest and most extensive plateau in the world, with an average elevation of over 4,500 meters above sea level, for example, distributions of the mafic-ultramafic rocks along the suture zones, the quarzitic and marine sedimentology accreted to the Eurasian continent and sulfate layers related to the Tethys and neo-Tethys geological setting can be retrieved from the processed ASTER images.

Reservoirs created by damming rivers significantly modify the environment and problems may arise: the storage of nutrients and organic matter in reservoirs often leads to decreased water quality due to eutrophication. Reservoirs built on lowland rivers are exposed to significant nutrient loads, often leading to eutrophication. In this article, the Sulejów Reservoir, in Central Poland, was the subject of the research, which focused on the use of Sentinel-2 remote sensing data to detect phytoplankton blooms, and on understanding the pattern of wind-driven surface currents using the CCHE2D model (a depth-averaged hydrodynamic model). The calculation of the total phosphorus load has shown that the reservoir mainly acts as nutrient storage. Still, during the low flow and intensive phytoplankton bloom, it can be a source of nutrients. The distribution of phytoplankton bloom on the Sulejów Reservoir was documented using eight Sentinel-2 satellite images from the vegetation season of 2020 and the Normalized Difference Chlorophyll Index (NDCl). Coupling remote sensing data and numerical modelling helps to interpret the hydrodynamic model results and understand nutrients and sediment dynamics within the reservoir. Hydrodynamic modelling combined with remote sensing data can be a valuable tool for selecting appropriate locations for water quality measurements at monitoring stations.

In the United States (US), tianeptine is sold as a dietary supplement under the trade name Tianaa™. Tianeptine is a synthetic drug prescribed by physicians as an antidepressant in parts of Europe, Asia and South America. The drug is not permitted for use by physicians in the US, be-cause it is a μ-opioid receptor agonist with a propensity for severe addiction. As incidence of Tianaa™ related opioid addiction across the southern US escalate, the current study aimed to quantify tianeptine in over the counter Tianaa™ White, Red, and Green products. The results of this investigation measured tianeptine levels between 3.1 to 10.9 mg per 531 mg capsules. Tianaa™ White capsules consistently contained the least tianeptine, while Green had the most. Close inspection of Tianaa™ products showed that capsule mass varied by as much as 16% from label claim, and the amount of tianeptine per capsule varied by as much as 35 % from the aver-age measured amount for each product. Tianaa™ Red contains kava leaf extract, which led to the identification of four kavapyrone components by mass spectrometry. The data presented pro-vide insight into tianeptine quantity and capsule mass variation for Tianaa™ supplements sold to customers naive to the risk of addiction.

There is a need to develop tools for mastitis management in goats and to measure the effects of milking machines on teats. Infrared thermography (IRT), as shown in cows, was a good candidate for early detection of mastitis and focusing on milking equipment and settings implicated in potential problems. The aim of this study was to test IRT to detect udder inflammation and the effects of mechanical milking on teats in relation to inflammation status, udder balance and teat shape in Alpine goats. IRT spectra were compared before and after milking in 551 goats from three commercial herds compared to their individual SCC (somatic cell count). We found no regression or trend between logSCC and IRT measurement or response to milking, even in highly inflamed goat udders. The effect of milking was significant (P

The purposes of this study were to identify clinician’s characteristics associated with higher prescription rates of long-acting injectable (LAI) antipsychotics, as well as the information sources influencing medical decision-making about treatment of schizophrenia. We surveyed 202 psychiatrists during 6 regional French conferences (Bordeaux, Lyon, Marseille, Nice, Paris, Strasbourg). Data on the characteristics of practice, prescription rates of antipsychotic and information sources about their clinical decisions were collected. Most of psychiatrists used second-generation antipsychotic (SGA), and preferentially an oral formulation, in the treatment of schizophrenia. SGA LAI was prescribed to 30.4% of schizophrenic patients. The duration and the type of practice did not influence the class or formulation of antipsychotics used. The clinicians following the higher percentage of schizophrenic patients were associated with the higher use of LAI antipsychotics and the lower use of oral SGA. Personal experience, government regulatory approval and guidelines for the treatment of schizophrenia were the 3 main contributing factors guiding the clinical decision-making of clinicians about treatment of schizophrenia. The more clinicians follow schizophrenic patients, the more they use LAI antipsychotic. The development of specialised programmes with top specialists should lead to better use of LAI in the treatment of schizophrenia.

Ticks transmit a wide variety of pathogens including bacteria, parasites and viruses. Over the last decade, numerous novel viruses have been described in arthropods, including ticks, and their characterization has provided new insights into RNA virus diversity and evolution. However, little is known about their ability to infect vertebrates. As very few studies have described the diversity of viruses present in ticks from the Caribbean, we implemented an RNA-sequencing approach on Amblyomma variegatum and Rhipicephalus microplus ticks collected from cattle in Guadeloupe and Martinique. Among the viral communities infecting Caribbean ticks, we selected four viruses belonging to the Chuviridae, Phenuiviridae and Flaviviridae families for further characterization and designing antibody screening tests. While viral prevalence in individual tick samples revealed high infection rates, suggesting a high level of exposure of Caribbean cattle to these viruses, no seropositive animals were detected. These results suggest that the Chuviridae- and Phenuiviridae-related viruses identified in the present study are more likely tick endosymbionts, raising the question of the epidemiological significance of their occurrence in ticks, especially regarding their possible impact on tick biology and vector capacity. The characterization of these viruses might open the door to new ways of preventing and controlling tick-borne diseases.

In French Polynesia, Wuhan, Delta and Omicron SARS-CoV-2 variants-of-concern (VOCs) caused epidemics with variable severities. We assessed the prevalence and titers of anti-SARS-CoV-2 antibodies related to natural infection and/or vaccination, from a representative sample (N=673) of the adult population of Tahiti recruited during November-December 2021 (after the Delta outbreak and just before the Omicron epidemic). Of the 673 participants tested, 644 (95.7%) had detectable antibodies against SARS-CoV-2-S and/or -N proteins resulting from natural infection and/or vaccination, and 388 (57.7%) were positive only for the detection of anti-N antibodies indicating natural infection. SARS-CoV-2 seroprevalence extrapolated to the adult population of Tahiti was estimated at 95.9%. Concentrations of anti-SARS-CoV-2-S antibodies significantly increased with age, number of self-reported SARS-CoV-2 infections (0 or ≥1), and number of COVID-19 vaccine doses (0, 1, 2, or 3) received by the participants. Elderly people, who are at higher risk of severe outcomes, had received more vaccine doses than younger individuals both in our sample and in the general population. The high level of antibody responses related to past infections and vaccination, especially booster doses, has likely contributed to reducing the severity of the Omicron outbreak in French Polynesia.

This paper investigates the use of deep learning techniques to perform energy demand forecasting. Specifically, the authors have adapted a deep neural network originally thought for image classification and composed of a convolutional neural network (CNN) followed by a multilayered fully connected artificial neural network (ANN). The convolutional part of the network was fed with a grid of temperature forecasting data distributed in the area of interest in order to extract a featured temperature. The subsequent ANN is then fed with this calculated temperature along with other data related to the timing of the forecast. The proposed structure was first trained and then used in a real setting aimed to provide the French energy demand forecast using ARPEGE forecasting weather data. The results show that the performance of this approach is in the line of the performance provided by the reference RTE subscription-based service, which opens the possibility to obtain high accuracy forecasting using widely accessible deep learning techniques through open-source machine learning platforms.

This paper investigates how blocks of buildings could fit into load shedding strategies. It focuses in particular on what could be the effects on peak shaving, occupants’ thermal comfort or CO2 emissions reduction and how to quickly quantify them. To achieve this goal, we focused on a new residential district, thermally fed by heat pumps. Four modeling approaches were confronted in order to estimate buildings' responses to load shedding orders. On the one hand, a quick estimation of the peak shaving impact can rely on experimental results if the buildings' envelope and uses of the experimentation match those of the study case. On the other hand, thermal simulation models allow us to assess thermal comfort while considering the building physical response. Finally, a hybrid modeling approach can provide a good compromise between modeling rapidity and accuracy of the impacts estimation. At district scale, it may be necessary to mix modeling approaches, from experimental results to detailed thermal models. Accuracy is not guaranteed for all approaches so that the choice should be made carefully in regards to study needs. However, results are sufficient to compare the effects of load shedding strategies on peak shaving, thermal comfort, and CO2 emissions reductions.

In the rapidly evolving landscape of the AI era, the measurement of Computational Thinking ability among Computer Science (CS) University students is of paramount importance. This study introduces UniCTCheck, a novel method designed to assess the main components of Computational Thinking in CS students. Utilizing two key instruments, namely the web application CTScore and the psychometric scale CTProg, this research aims to precisely evaluate seven core components of Computational Thinking and six programming concepts skills essential for CS students. The study, conducted at Rey Juan Carlos University and Atlantic Technological University Galway, involved a diverse sample of students from different year levels and program specializations. Through a rigorous research design, including sampling strategies and data collection tools, this study seeks to address critical research questions related to measurement of variations in students' Computational Thinking and programming skills by gender, university level, and location. By shedding light on the significance of Computational Thinking and programming in the educational realm, this research contributes to the existing literature and underscores the essential role of computational skills in the modern era.

Students in their first year of computer science (CS1) at universities typically struggle to grasp programming concepts. This paper covers research using a Java programming language-guided visual execution environment (VEE) to teach CS1 students about programming concepts. The topics covered include input and output, conditionals, loops, functions, arrays, recursion, and files, all of which are covered in an introductory programming course. The VEE walks beginner programmers through the fundamentals of programming, utilizing visual metaphors to explain and direct interactive Java tasks. The primary goal of this study is to determine whether a cohort of 105 CS1 students from four different groups who are enrolled in two universities—one in Madrid, Spain, and the other in Galway, Ireland—can advance their programming abilities under the guidance of the VEE. Second, does the improvement vary depending on the programming concept? The findings demonstrate that students' programming knowledge has greatly increased. This improvement is significant for all programming concepts, while it is more pronounced for some topics than others, such as operators, conditionals, and loops. Additionally, it demonstrates that students had little prior understanding of files and recursion. The most well-known concept to them was the sequence concept.

We investigate the human sustainability of ICT and management changes using a French linked employer-employee survey on organizational changes and computerization (COI). We approach the human sustainability of changes through the evolutions of work intensity, skill utilization and the subjective relationship to work. We compare in the private sector and the State civil service the impacts of ICT and management changes on the evolution of these three dimensions of work experience. We find that when ICT and management changes are intense, they are positively associated in the public sector with work intensification and new knowledge. In the private sector ICT and management changes increase the use of skills, but at a rate decreasing with their intensity and without favoring the accumulation of new knowledge. However, their impacts on the subjective relationship to work are much stronger, with public sector employees expressing discouragement as well as the feeling of an increased effort-reward imbalance when private sector employees become more committed. We tested that the self-selection of employees, the specific sources and paths of changes and the implementation of performance pay did not explain this divergence. We identify two partial explanations: one is related with employee turnover in the private sector, the other one with the role of trade unions. These results suggest that the human sustainability of ICT and management changes depends on their intensity and on how their implementation takes into account the institutional context of the organization.

Dirofilariosis is an infectious disease caused by species of the Dirofilaria genus. It is manifested by the appearance of a subcutaneous swelling, especially in the eye region. We present the case of a 29-year-old patient that accused facial asymmetry in the right genian region. Following clinical and paraclinical evaluations, the diagnosis of parasitic cyst was established in the context of dirofilariosis with Dirofilaria repens (D. repens). Treatment consisted of surgical excision of the formation associated with prophylactic antibiotic medication. Macroscopic analysis of the excision piece revealed a structure that contains a cystic cavity and a filamentous form with a length of approximately 10 mM and a diameter of 1 mM. This is the first case of dirofilariosis located in the genian region reported in Romania. The overview of this pathology is important to raise awareness among physicians about its presence and its clinical variations.

In a global context, the story of the Jesuit compound in Shanghai, since its establishment by French Jesuits in 1847, reflected not only conflicts between rival powers in Europe but also the fight for their interests in the Eastern world. The Pope, who was stuck without legal status in the Vatican after 1861, was also seeking the chance to save the authority of the Church in the face of questions regarding the extent of his temporal power and the status of Rome in the context of Italian unification. As in the Reformation, a break-through in the east seemed to offer a solution for losses in Europe. However, the Jesuits to the East in the late 19th century were not only troops working and fighting on behalf of the Pope; their identities under the French Protectorate added complexity to an already complicated story involving not just the Church, but the course of world history.The female Catholic orders at the east bank of Zi-ka-wei compound became a unique window to approach the complexity.

Text summarization remains a challenging task in the Natural Language Processing field despite the plethora of applications in enterprises and daily life. One of the common use cases is the summarization of web pages which has the potential to provide an overview of web pages to devices with limited features. In fact, despite the increasing penetration rate of mobile devices in rural areas, the bulk of those devices offer limited features in addition to the fact that these areas are covered with limited connectivity such as the GSM network. Summarizing web pages into SMS becomes, therefore, an important task to provide information to limited devices. This work introduces WATS-SMS, a T5-based French Wikipedia Abstractive Text Summarizer for SMS. It is built through a transfer learning approach. The T5 English pre-trained model is used to generate a French text summarization model by retraining the model on 25,000 Wikipedia pages then compared with different approaches in the literature. The objective is twofold: (1) to check the assumption made in the literature that abstractive models provide better results compared to extractive ones; and (2) to evaluate the performance of our model compared to other existing abstractive models. A score based on ROUGE metrics gave us a value of 52% for articles with length up to 500 characters against 34.2% for transformer-ED and 12.7% for seq-2seq-attention; and a value of 77% for articles with larger size against 37% for transformers-DMCA. Moreover, an architecture including a software SMS-gateway has been developed to allow owners of mobile devices with limited features to send requests and to receive summaries through the GSM network.

This article examines evolution of trans-regional Ethio-Djibouti railway corridor and its impact on urbanization. Exploratory and descriptive research methods were employed to examine the impact of this railway corridor. Case study also applied to examine eight selected intermediate cities. The article points out that, the Ethio-Djibouti railway corridor conceived different kinds of linear urban centers ranging from small towns to intermediate cities around stations. Those urban centers have been attracting industries along their fringes that leads to rural urban continuum ribbon urbanization. As the old railway line deteriorated, these linear urban centers on the railway corridor had also been declining from time to time. In 2011 new project was started to construct the Ethi-Djibouti standard gauge railway parallel to the old railway line. This new standard gauge railway infrastructure adopts ‘peripheral station’ development approach, which provides a room for width expansion for station based urban centers. It also attracts industries in a form of special economic zones, which causes for labour migration from rural and nearby small urban centers that caused rural-urban continuum of ribbon settlement; strengthen trade gate way for the landlocked Ethiopia that caused trans-regional integration.

The digital transformation of healthcare is advancing, leading to an increasing availability of clinical data for research. Perioperative big data initiatives were established to monitor treatment quality and benchmark outcomes. However, big data analyzes have long exceeded the status of pure quality surveillance instruments. Large retrospective studies nowadays often represent the first approach to new questions in clinical research and pave the way for more expensive and resource intensive prospective trials. As a consequence, utilization of big data in acute pain and regional anesthesia research considerably increased over the last decade. Multicentric clinical registries and administrative databases (e.g., healthcare claims databases) have collected millions of cases until today, on which basis several important research questions were approached. In acute pain research, big data was used to assess postoperative pain outcomes, opioid utilization, and the efficiency of multimodal pain management strategies. In regional anesthesia, adverse events and potential benefits of regional anesthesia on postoperative morbidity and mortality were evaluated. This article provides a narrative review on the growing importance of big data for research in acute postoperative pain and regional anesthesia.

Ammonium sulfate has been utilized in agriculture; however, there is a dearth of research on its application in maize cultivation subsequent to the implementation of nitrification inhibitors or coating. This study aims to analyze the impacts of various combinations of ammonium sulfate fertilizers on soil nutrients, plant nutrient uptake, yield, and fertilizer utilization efficiency in maize cultivation to ascertain the optimal and stabilized disposal method for ammonium sulfate. A completely randomized design was employed with five treatments (AU, the control using urea; AS, treatment using ammonium sulfate; ASN, treatment using ammonium sulfate with a nitrification inhibitor; ASG, treatment using oil-coated ammonium sulfate; ASD, treatment using oil-humic acid-coated ammonium sulfate). Results showed that: (1) Compared with AU and AS, ASN, ASG and ASD decreased the leaching rates of TN, NH4+-N and NO3-N to the 10-20 cm soil layer, and more residual N was obtained in 0-10 cm soil layer. The first-order kinetic equation Nt=N0(1-e-kt) can better fit the process of nitrogen accumulation and release, and the N release rate constant is AU>CK>AS>ASH>ASN>ASD; (2) Compared with AU and AS treatments, the plant dry weight, grain dry weight, spike width, spike length, and yields of maize increased by 8.85-11.08%, 12.98-14.15%, 2.95-3.52%, 5.50-5.65%, and 43.21-51.10% under ASG treatment respectively. The impact of effective spike number on maize yield was found to be significant, as demonstrated by the path analysis conducted in this study. Furthermore, the accumulation levels of nitrogen, phosphorus, and potassium within above-ground plants significantly increased under the ASG treatment compared to the AU and AS treatments. The partial productivity of nitrogen, phosphorus, and potassium increased by 1.43-1.51-fold under ASG treatment, while grain nitrogen balance, grain phosphorus balance, and grain potassium balance increased by 1.41-1.58-fold, 1.51-1.95-fold, and 1.15-l.96-fold respectively. The oil-coated ammonium sulfate, therefore, exhibited the optimal slow-release effect of nutrients, thereby achieving superior performance in enhancing maize production and efficiency.

Synanthropic flora (weeds, spontaneously developed plants) are plants that accompany humans, appearing as a result of anthropopressure as well as after its cessation. The potential of synanthropic flora in shaping green areas usually brings many measurable benefits that depend on land management in cities. The study aimed to determine the preferences and attitudes of adults towards synanthropic flora in settlement units. The article presents survey results from 447 city residents. The obtained results were statistically analyzed using the k-means clustering method to identify segments of respondents with similar attitudes and preferences toward synanthropic flora. Mann-Whitney U tests were employed to determine statistical differences in the demographic variables among the analyzed clusters of respondents. Additionally, multiple regression analysis was performed to identify the opinions and attitudes towards synanthropic flora, that may influence their greater acceptance in the vicinity of residential areas. The results obtained in multiple regression allow for the statement that the respondent’s evaluation of the level of support for the introduction of more synanthropic vegetation into urban greenery (Yw) grows with the increase of acceptance of synanthropic plants occurrence in surroundings. Respondents’ opinions on the subject of the presence of synanthropic plants were studied using such variables concerning: synanthropic vegetation found in turfgrasses has a positive impact on the visual attractiveness of a site (X1), synanthropic plant communities present themselves better than others (X2), presence of synanthropic vegetation in an estate improves the quality of life in that location (X3), introduction of synanthropic flora into estate arrangements is a positive (X4), support for the use of synanthropic flora for educational purposes - as elements of playgrounds or in the form of environmental workshops (X5). Residents’ acceptance of synanthropic flora in green areas is at a relatively high level.

The world is in the grips of the COVID-19 pandemic. Public health measures that can reduce the risk of infection and death in addition to quarantines are desperately needed. This article reviews the roles of vitamin D in reducing risk of respiratory tract infections, knowledge about the epidemiology of influenza and COVID-19, and how vitamin D supplementation might be a useful measure to reduce risk. Through several mechanisms, vitamin D can reduce risk of infections. Those mechanisms include inducing cathelicidins and defensins that can lower viral replication rates and reducing concentrations of pro-inflammatory cytokines that produce the inflammation that injures the lining of the lungs, leading to pneumonia, as well as increase concentrations of anti-inflammatory cytokines. Several observational studies and clinical trials reported that vitamin D supplementation reduced risk of influenza, whereas others did not. Evidence supporting the role of vitamin D in reducing risk of COVID-19 includes that the outbreak occurred in winter, a time when 25-hydroxyvitamin D [25(OH)D] concentrations are lowest; that the number of cases in the Southern Hemisphere near the end of summer are low; that vitamin D deficiency has been found to contribute to acute respiratory distress syndrome, and that case-fatality rates increase with age and with chronic disease comorbidity, both of which are associated with lower 25(OH)D concentration. To reduce risk of infection, it is recommended that people at risk of influenza and/or COVID-19 consider taking 10,000 IU/d of vitamin D₃ for a few weeks to rapidly raise 25(OH)D concentrations, followed by 5000 IU/d. The goal should be to raise 25(OH)D concentrations above 40–60 ng/ml (100–150 nmol/l). For treatment of people who become infected with COVID-19, higher vitamin D₃ doses might be useful. Randomized controlled trials and large population studies should be conducted to evaluate these recommendations.

Residual sugars (RS) in wine are the sugars that remain in a wine after fermentation is complete. In some wine styles, such as semi-dry wines, the accurate measurement of the RS concentration is critical for both qualitative and legislative reasons. Brix, measured by a simple refractometer, can give a good estimation of the RS concentration in the must, but during fermentation, the presence of alcohol leads to inaccurate sugar measurements. In order to measure the RS accurately, other more precise techniques are used, most of which are expensive or require professional skills. Therefore, novel approaches for rapid, easy, and practical measurements for estimating the sugar content were suggested over the years. However, most of these methods do not supply an actual measurement of RS but rather give brix values, and those that measure RS involve special equipment, which is less relevant for small wineries. This study suggests a novel model for predicting and controlling the wine's residual sugar. The data the model uses is the initial brix of the must before fermentation and its density during fermentation. The model was created by measuring actual residual sugars during the fermentation of natural and synthetic musts, with various degrees of initial brix levels, while simultaneously measuring their densities and correlating the two measurements. Linear regression between the residual sugar of the wine and its density was obtained for all treatments and repetitions (i.e., different values of must initial brix) with R² values above 0.97. Using the model, one can calculate (before commencing the fermentation) the density values at which the fermentation will reach a particular desired residual sugar value for a specific initial brix level; the model is applicable for the fermentation conditions used in this work, i.e., brix levels of 18-27˚Bx, Saccharomyces cerevisiae strains (fx-33 and fx-10) in common conditions of fermentation regarding temperature and aeration.

A review of quantitative risk assessment (QRA) models of L. monocytogenes in produce was carried out, with the objective of appraising and contrasting the effectiveness of the control strategies placed along the food chains. Despite nine of the thirteen QRA models recovered focused on fresh or RTE leafy greens, none of them represented important factors or sources of contamination in the primary production, such as type of cultivation, water, fertilisers or irrigation method/practices. Cross-contamination at processing and during consumer’s handling was modelled using transfer rates, which were shown to moderately drive the final risk of listeriosis; highlighting therefore the importance of accurately representing the transfer coefficient parameters. Many QRA models coincided in the fact that temperature fluctuations at retail or temperature abuse at home were key factors contributing to increasing the risk of listeriosis. In addition to a primary module that could help assess current on-farm practices and potential control measures, future QRA models for minimally-processed produce should also contain a refined sanitisation module able to estimate the effectiveness of various sanitisers as a function of type, concentration and exposure time. Finally, L. monocytogenes growth in the products down the supply chain should be estimated by using realistic time-temperature trajectories, and validated microbial kinetic parameters, both of them currently available in the literature.

Background: In France, no previous studies had addressed the acquisition of multidrug resistant (MDR) bacteria and colistin resistance genes by medical students when undertaking internships abroad. Methods: Nasopharyngeal, rectal, and vaginal swabs samples were collected from 382 French medical students before and after travel to investigate the acquisition of MDR bacteria. The bacterial diversity in the samples was assessed by culture on selective media. We also genetically characterised the isolates of MDR bacteria including Extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-E), methicillin-resistant Staphylococcus aureus (MRSA), and Carbapenemase-producing Enterobacteriacae (CPE) using the real-time polymerase chain reaction method. The samples were collected from 293 students and were investigated for mcr colistin-resistance genes using RT-PCR directly on the samples, followed by conventional PCR and sequencing. Results: A proportion of 29.3% of the participants had acquired ESBL-E and 2.6% had acquired CPE. The most common species and ESBL-E encoding gene were Escherichia coli (98.4%) and bla_CTX-M-A (95.3%), respectively. A proportion of 6.8% of the participants had acquired mcr-1 genes, followed by mcr-3 (0.3%) and mcr-8 (0.3%). We found that taking part in humanitarian missions to orphanages, being in contact with children during travel, the primary destination of travel being Vietnam and north India, using antibiotics during travel, and studying in 2017 were associated with the acquisition of ESBL-E. When the primary destination of travel was Vietnam and the year of study was 2018, this was associated with acquisition of colistin resistance genes. Conclusion: Medical students are at a potential risk of acquiring ESBL-E, CPE and colistin resistance genes. A number of risk factors have been identified, which may be used to develop targeted preventive measures.

This study introduces a specialized Automatic Speech Recognition (ASR) system, leveraging the Whisper Large-v2 model, specifically adapted for radiological applications in French language. Our methodology focused on adapting the model to accurately transcribe medical terminology and diverse accents within the French language context, achieving a notable Word Error Rate (WER) of 17.121%. The research involved extensive data collection and preprocessing, utilizing a wide range of French medical audio content. The results demonstrate the system's effectiveness in transcribing complex radiological data, underscoring its potential to enhance medical documentation efficiency in French-speaking clinical settings. The discussion extends to the broader implications of this technology in healthcare, including its potential integration with Electronic Health Records (EHRs) and its utility in medical education. The study also explores future research directions, such as tailoring ASR systems to specific medical specialties and languages. Overall, this research contributes significantly to the field of medical ASR systems, presenting a robust tool for radiological transcription in the French language and paving the way for advanced technology-enhanced healthcare solutions.

We assessed the use of Evidence-Based Practice (EBP) among pharmacists working in community pharmacies in France, and the factors linked to this practice. During 3 months in 2018 an online survey was sent to over 7,000 active pharmacists, and posted on pharmacist social media sites. The 40-item questionnaire described four clinical cases reflecting typical situations (conventional med-icine and Complementary and Alternative Medicine) encountered daily by community pharma-cists. Multiple-choice responses were proposed and scored according to whether they reflected EBP. A high total score indicated behavior in line with EBP. Univariate and multivariate analyses were used to evaluate factors that might explain adherence to EPB (pharmacy’s characteristics, the pharmacist’s status, mode of continuing education and sources of information). 595 pharmacists completed the questionnaire. The majority relied on pharmaceutical industry and other biased and/or non-evidence-based sources, particularly concerning information on homeopathic products. The consultation of independent reviews, health agency recommendations, and peer-reviewed scientific journals, was associated with evidence-based decisions. In contrast, reliance on phar-maceutical industry documents, personal experience and informal handbooks was linked to lower EBP scores. The level of EBP use by French community pharmacists needs to be improved to ensure that good quality scientifically-based advice is given to customers.

Policy is a lever for initiating the structural and environmental changes that foster health-enhancing physical activity (HEPA) promotion. However, little is known about the evidence in support of local governments regarding their HEPA-promoting policies. This study collected comprehensive information on municipal HEPA policies on the French Riviera to gain an overview of HEPA policy development in this territory. Mid-sized cities from the two counties constituting the French Riviera were targeted (n = 17). In each city, a local tool for HEPA policy analysis, CAPLA-Santé, was used to gain information from key informants heading the departments of sports, health services and social services. Data were collected through semi-structured interviews and document analysis. Ten mid-sized cities volunteered to participate. Key informants from the sports (n = 10), health services (n = 5) and social services (n = 6) departments were interviewed. Written HEPA policy documents were formalized in six cities. These documents (n = 14) were mainly from the sports (n = 8) and health services (n = 4) sectors. The key informants reported that support from that national policy, the commitment of elected officials, and large local stakeholder networks facilitated HEPA promotion, whereas the lack of intersectoral collaboration and limited resources were limitations. The results provide insight into the development of municipal HEPA policies, highlighting some of the barriers, facilitators and perspectives. These findings could be valuable to scale up HEPA promotion at the local level.

The aim of our study was to describe our experience using a Spectra Optia® automated apheresis system in children with sickle cell disease (SCD). We used automated red blood cell exchange (RCE) to treat acute and chronic complications in 75 children with SCD who had a median age of 10 years [7-13]. We analysed 649 exchange sessions. Peripheral venous access was limited in a number of the children, thus requiring a femoral central double‐lumen venous catheter (CVC). We recommend the use of heparin locking, with 500 units in each lumen of a CVC. This method was well tolerated, with few complications during the procedures. For preoperative prevention, all of the patients had achieved a post-RCE HbS level of <30% since this is a mandatory condition imposed by the anaesthesiologist. With a post-RCE Hb level of approximately 10-11 g/dL, a blood exchange volume of ≥32 mL/kg, and an interval between each RCE procedure of ≤30 days, it was able to maintain the residual HbS level below 30%. Despite a target pre‐exchange HbS level of 47%, we did not encounter a single stroke recurrence. Erythrocytapheresis is useful and safe for children with SCD.

Intertidal seagrass plays a vital role in estimating the overall health and dynamics of coastal environments due to its interaction with tidal changes. However, most seagrass habitats around the globe have been in steady decline due to human impacts, disturbing the already delicate balance in environmental conditions that sustain seagrass. Miniaturization of multi-spectral sensors has facilitated very high resolution mapping of seagrass meadows, which significantly improve the potential for ecologists to monitor changes. In this study, two analytical approaches used for classifying intertidal seagrass habitats are compared: Object-based Image Analysis (OBIA) and Fully Convolutional Neural Networks (FCNNs). Both methods produce pixel-wise classifications in order to create segmented maps, however FCNNs are an emerging set of algorithms within Deep Learning with sparse application towards seagrass mapping. Conversely, OBIA has been a prominent solution within this field, with many studies leveraging in-situ data and multiscale segmentation to create habitat maps. This work demonstrates the utility of FCNNs in a semi-supervised setting to map seagrass and other coastal features from an optical drone survey conducted at Budle Bay, Northumberland, England. Semi-supervision is also an emerging field within Deep Learning that has practical benefits of achieving state of the art results using only subsets of labelled data. This is especially beneficial for remote sensing applications where in-situ data is an expensive commodity. For our results, we show that FCNNs have comparable performance with standard OBIA method used by ecologists, while also noting an increase in performance for mapping ecological features that are sparsely labelled across the study site.

Zero-emission trucks for regional and long haul missions are an option for fossil-free freight. The viability of such powertrains and system solutions was studied conceptually in project ESCALATE for trucks with GVW of 40 tonnes and beyond through various prime mover combinations. The study covers battery and fuel cell power sources with different degrees of battery electric as well as H2 and fuel cell operation. As a design basis, two different missions with a single-charge/H2 refill were analysed. The first mission was the VECTO long haul profile repeated up to 750 km, whereas the second was a real 520 km on-road mission in Finland. Based on the simulated energy consumption on the driving cycle, on-board energy demand was estimated, and the initial single-charge operational scenarios were analysed with five different power source topologies. The traction motors of the tractor were dimensioned so that a secondary mission of GVW up to 76 tons on a shorter route can be operated. Based on the powertrain and vehicle model, various infrastructure options for charging and H2 refuelling strategy as well as various operative scenarios with indicative total cost of ownership (TCO) were analysed.

The objectives of the study were to determine the spatial rate of CO₂ flux (Net Ecosystem Exchange) and soil moisture in a wetland ecosystem applying Sentinel-1 IW (Interferometric Wide) data of VH (Vertical Transmit/Horizontal Receive—cross polarization) and VV (Vertical Transmit/Vertical Receive—like polarization) polarization. In-situ measurements of carbon flux, soil moisture, and LAI (Leaf Area Index) were carried out over the Biebrza Wetland in north-eastern Poland. The impact of soil moisture and LAI on backscattering coefficient (σ°) calculated from Sentinel-1 data showed that LAI dominates the influence on σ° when soil moisture is low. The models for soil moisture have been derived for wetland vegetation habitat types applying VH polarization (R² = 0.70 to 0.76). The vegetation habitats: reeds, sedge-moss, sedges, grass-herbs, and grass were classified using combined one Landsat 8 OLI (Operational Land Imager) and three TerraSAR-X (TSX) ScanSAR VV data. The model for the assessment of Net Ecosystem Exchange (NEE) has been developed based on the assumption that soil moisture and biomass represented by LAI have an influence on it. The σ° VH and σ° VV describe soil moisture and LAI, and have been the input to the NEE model. The model, created for classified habitats, is as follows: NEE = f (σ° Sentinel-1 VH, σ° Sentinel-1 VV). Reasonably good predictions of NEE have been achieved for classified habitats (R² = 0.51 to 0.58). The developed model has been used for mapping spatial and temporal distribution of NEE over Biebrza wetland habitat types. Eventually, emissions of CO₂ to the atmosphere (NEE positive) has been noted when soil moisture (SM) and biomass were low. This study demonstrates the importance of the capability of Sentinel-1 microwave data to calculate soil moisture and estimate NEE with all-weather acquisition conditions, offering an important advantage for frequent wetlands monitoring.

Extant research pays little attention to migrant workers’ skill accumulation/upgrading from the perspective of the labor supply. This paper takes China as an example to explore the factors influencing skill accumulation of rural-urban migrant workers (RUMWs), with a purpose to discover how to sustain or reshape regional competitive advantage through improving RUMWs’ skill accumulation. Structured questionnaire surveys were adopted for data collection in Suzhou City, Jiangsu Province and Taizhou City, Zhejiang Province located in the Yangtze River Delta in the east of China. 900 questionnaires were issued and 491 effective questionnaires were recovered totally. This paper takes a perspective of global production networks, and gets a broad viewpoint containing intra-firm coordination, inter-firm partnership and extra-firm bargaining with non-firm actors, beyond what the extant literature on laborers’ human capital focuses on. The finding indicates that firms’ skill-oriented preference, which concerns about employees’ skills and innovation ability and stimulates them to learn initiatively, have a significant influence on RUMWs’ skill accumulation. In terms of collective efficiency based on co-competitive relationship between local firms, the more intensive interactions are, the more opportunities of skill accumulation RUMWs get. The accessibility of local institutions and favorable policies benefit RUMWs’ skill accumulation. Besides, the place itself, as a synthesized space of labor-management relations inside a firm and inter-organization relations, exerts an influence on and cause the regional differences in RUMWs’ skill accumulation.

Veratrum californicum is a rich source of steroidal alkaloids such as cyclopamine, a known inhibitor of the Hedgehog (Hh) signaling pathway. Here we provide a detailed analysis of the alkaloid composition of V. californicum by plant part through quantitative analysis of cyclopamine, veratramine, muldamine and isorubijervine in the leaf, stem and root/rhizome of the plant. To determine if additional alkaloids in the extracts contribute to Hh signaling inhibition, we replicated the concentrations of these alkaloids observed in extracts using commercially available standards and compared the inhibitory potential of the extracts to alkaloid standard mixtures using Shh-Light II cells. Alkaloid combinations enhanced Hh signaling pathway antagonism compared to cyclopamine alone, and significant differences were observed in the Hh pathway inhibition between the stem and root/rhizome extracts and their corresponding alkaloid standard mixtures, indicating that additional alkaloids present in these extracts contribute to Hh signaling inhibition.

The number of new financing options has increased quickly, including alumni crowdfunding and strategic investments. The antecedents and consequence of these funding mechanisms have not been thoroughly studied in research yet. In this study, the efficacy of leveraging alumni crowdfunding and strategic investments to overcome the perennial funding challenges in French language education was rigorously examined. The study examined the funding challenges plaguing French language education, casting a spotlight on the urgency of creative financial solutions and the strategic provisions of alumni engagements. The study further covered the various roles of strategic investments, synergy of alumni crowdfunding and investments. The analysis proffers a balanced perspective, delving into challenges and concerns that can potentially hinder the smooth operation of these innovative funding channels. Practical recommendations for successful alumni crowdfunding and effective strategic investments were provided. A synthesis of the key findings reveals profound implications for the future of French language education. It was concluded that effective fundraising for French language education relies on well-structured policy and institutional guidance. With these policies in place, educational institutions can navigate the complexities of funding French language programs and secure their future.

The rehabilitation of abandoned mining sites is an increasingly pressing issue in the context of sustainable development. Recent research has emphasized the need for a holistic approach to the abandoned mining sites and their environmental rehabilitation. Based on field analysis, environmental assessments, satellite imagery processing and geographic information operations, this paper pushes forward the existing knowledge by doing a comprehensive assessment of abandoned mining sites in the Romanian Carpathians and by proposing innovative and sustainable rehabilitation solutions. Our findings highlight that abandoned mining sites and their surrounding territories in the Romanian mountains have significant ecological imbalances and complex socio-economic issues. The findings also suggest that by adopting innovative, integrated, and sustainability-oriented approaches, territories affected by mining can be transformed into valuable and sustainable spaces to meet human needs. We conclude by presenting the importance of innovation in ecological reconstruction and spatial-functional reintegration of mining sites in mountain areas as a useful tool in making fair decisions, both in the context of implementing appropriate development policies as well as for resilience and environmental sustainability of mining-affected mountain areas.

.Maize cultivation in Thailand faces challenges owing to climate change and soil organic carbon (SOC) loss. This highlights the importance of comparing maize soil with paddy soil in terms of the role of dissolved organic carbon (DOC) and nutrient availability, as they influence SOC content. Soil samples from Chiang Mai province, primarily Fluvisol, were collected for the cultivation of paddy rice and maize, analysed for carbon fractions and chemical properties, and categorised into layers. Comparative analysis revealed that maize soils had lower levels of labile carbon components and organic carbon than paddy soils (P

Accurate detection and state analysis of traffic flows are essential for effectively reconstructing traffic flows and reducing the risk of severe injury and fatality. For this reason, several studies on resolving traffic problems have proposed the use of crowdsourcing, in which drivers provide real-time traffic information using mobile devices, to monitor traffic conditions. Using data collected via crowdsourcing for traffic event detection has advantages in terms of improved accuracy and reduced time cost in collecting relevant data. In this paper, we propose a technique that employs crowdsourcing to collect traffic-related data and uses these data to detect events that influence traffic. The proposed technique uses various machine-learning methods to more accurately identify events and find accurate location information. Therefore, it is able to resolve problems typically encountered with conventionally provided location information, such as broadly defined locations or inaccurate location information. The proposed technique has advantages in terms of reducing time and cost while increasing accuracy. Its validity and effectiveness were also demonstrated through various performance evaluations.

This study was conducted to investigate the status of regional linkage in tourism development in in the Midlands and Northern Mountains of Vietnam. The data was collected from a survey of 755 people, including officials from State management bodies in charge of tourism, officials and staffs at tourism resorts, tourism firms, tourism scientists and tourists. In addition, we conducted 10 group discussions, interviewed 30 State tourism agency officials and tourism firms in the Midland and Mountainous provinces of Vietnam. The results show that tourism development in Vietnam in general and the Northwest region in particular is extremely fragmented, not yet forming a regional linkage; Regional and national tourism development programs are just formalistic. The main cause of the situation is the limited regional integration policy in Vietnam, the lack of appropriate regional governance mechanisms and inactive participation of the private sector in regional integration. Based on the findings, we propose a tourism sector linkage model; besides, policy implications are given for fulfilling the linkage policy in the Midlands and Northern Mountains area.

Cyanobacterial harmful algal blooms (CyanoHABs) are increasing in prevalence and severity globally and locally in the Great Lakes region. CyanoHABs have the potential to produce serious adverse human health effects due to the production of cyanotoxins from cyanobacteria. Common routes of exposure include recreational exposure (swimming, skiing, and boating), ingestion, and aerosolization of contaminated water sources. Cyanotoxins have been shown to adversely affect several major organ systems contributing to hepatotoxicity, gastrointestinal distress, and pulmonary inflammation. We present three pediatric case-reports that coincided with CyanoHABs exposure with a focus on presentation of illness, diagnostic work-up, and treatment of CyanoHAB-related illnesses. Potential cyanotoxin exposure occurred while swimming in the Maumee River and Maumee State Park in Northwest OH during the Summer months which coincide with peak CyanoHAB activity. Primary symptoms included generalized macular rash, fever, vomiting, diarrhea, and severe respiratory distress. Significant labs included leukocytosis and elevated C-reactive protein. All patients ultimately recovered with supportive care. Symptoms following potential cyanotoxin exposure coincide with multiple disease states representing an urgent need to develop specific diagnostic tests of exposure.

A remote sensing-based evapotranspiration (ET) study was conducted over the Central Arizona Irrigation and Drainage District (CAIDD), an Arizona agricultural region. ET was assessed means for 137 wheat plots, 183 cotton plots, and 225 alfalfa plots. The remote sensing ET models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. The models produced similar daily ET for wheat, with 6–8 mm/d mid-season. For cotton and alfalfa daily ET showed greater differences, where TSEB produced largest daily ET, METRIC the least, and VISW in the midrange. Modeled cotton ET at mid-season ranged from 9.5 mm/d (TSEB), to 8 mm/d (VISW), and 6 mm/d (METRIC). For alfalfa ET, values at peak cover ranged from 8 mm/d (TSEB), 6 mm/d (VISW), and 5 mm/d (METRIC). Model bias ranged −10% to +18%. Relative to potential ET, FAO-56 ET, and USDA-SW gravimetric-ET, model variability ranged from negligible to 35% of annual crop water use. Model averaging was found a useful way to consider and reconcile all ET estimates.

Resistance against amitraz in varroa mite populations has become a subject of interest in recent years due to increasing reports of reduced field efficacy of amitraz treatments, especially from some beekeepers in France and the United States. The loss of amitraz as a reliable tool to effectively reduce varroa mite infestation in the field could severely worsen the position of beekeepers in the fight to keep varroa infestation rates in their colonies at low levels. In this publication, we present data from French apiaries, collected in the years 2020 and 2021. These data include field efficacy of an authorized amitraz-based varroa treatment (Apivar®) and results of laboratory sensitivity assays of varroa mites exposed towards the reference LC90 concentration of amitraz. In addition, a total of 240 varroa mites from Eastern, Central, and Southern regions in France that were previously classified as either “sensitive” or “resistant” towards amitraz in a laboratory sensitivity assay were genotyped. The genetic analyses of mite samples are focused on the β−adrenergic-like octopamine receptor, which is considered as the main target site for amitraz in varroa mites. Special attention was given to a single nucleotide polymorphism (SNP) at position 260 of the ORβ-2R-L gene that had previously been described by Hernández Rodríguez et al. (2021) as associated to the resistance to amitraz in French varroa mites. Our findings confirm that amitraz resistance occurs in patches or “islands of resistance” with a less severe reduction in treatment efficacy compared to pyrethroid resistance or coumaphos resistance in varroa mites. The results of our genetic analyses of varroa mites call into question the hypothesis of the SNP at position 260 of the ORβ-2R-L gene being directly responsible for amitraz resistance development.

Ciguatera fish poisoning (CFP) is one of the most common causes worldwide of marine poisoning associated with fish consumption from tropical areas. Its incidence is underreported. CFP cases seem to increase with grouped cases reported during summer. Exposure to ciguatoxin, the toxin responsible for CFP with sodium-channel agonistic, cholinergic, and adrenergic activities, may result in a large spectrum of manifestations. We aimed to describe the clinical characteristics, management, and outcome of CFP in Martinique, French West Indies. We conducted an observational retrospective single-center study for six years (October 2012 to September 2018) including all CFP patients managed by the prehospital medical services, admitted to the university hospital emergency department, or declared to the regional health agency. One hundred and forty-nine CFP patients (81females/63males; median age, 46 years [interquartile range, 34-61]) were included. Acute features consisted of general (91%; mainly, myalgia pruritus, and asthenia), gastrointestinal (90%; mainly diarrhea, abdominal pain, and nausea), neurological (72%; mainly, paresthesia, dysgeusia, and impairment of hot/cold feeling), and cardiovascular manifestations (22%; bradycardia, hypotension, and heart conduction disorders). Management was supportive. No patient died but symptoms persisted in 40% of the 77 patients with follow-up on day 15. CFP was mainly attributed to the ingestion of trevallies (59%), snappers (13%), and king mackerels (8%) with collective contaminations (71%). Unusual fish (tuna, salmon, and spider conchs) were suspected in rare cases. Ingestion of trevallies was associated with significantly higher persistent symptoms (odds ratio, 3.00; 95% confidence interval, [1.20-8.00]; p=0.03). CFP incidence was 0.67 cases per 10,000 patient-years in Martinique over the study period. To conclude, CFP represents an increasing public health issue in Martinique like in other Caribbean islands. Patients present usual but possibly life-threatening features. The outcome is excellent despite frequently prolonged manifestations.

In this study, data analysis methods from ecology were applied to litter surveys to evaluate patterns among urban litter items found in two types of streets in England (High Streets and Central Business Districts). Results indicate that sites characterised as a High Street (predominantly leisure activities such as shopping and dining) contained lower densities, less variety, yet featured items with higher potential for environmental contamination than sites categorised as Central Business District (identified by high numbers of professional workers and transport links). Although litter were significantly different between sites, the litter community structure was not. Our results suggest that litter typologies and associated activities can lead to specific knowledge of key influential items in a site and inform future evidence based and sustainable mitigation systems.

Air pollution knows no boundaries, which means for a city or a region to attain clean air standards, must not only look at the emission sources within its own administrative boundary, but also at sources in the immediate vicinity and those originating from long-range transport. And there is a limit to how much area can be explored to evaluate, govern, and manage as designated airsheds for cities and larger regions. This paper discusses the need from an official airshed framework for India’s air quality management, urban airsheds designated for India’s 131 non-attainment cities under the national clean air programme, and proposes climatically and geographically appropriate regional airsheds to support long-term planning. Between 28 states, eight union territories, 36 meteorological sub-regional divisions, and six regional meteorological departments, establishing the proposed 15 regional airsheds for integrated and collaborative air quality management across India is a unique opportunity.

The goal of our study was to examine the effect of regional characteristics of living environment on individual a priori and a posteriori dietary patterns of the Russian population. For the analysis, we used cross-sectional data from the Epidemiology of Cardiovascular Diseases in the Regions of the Russian Federation study of 2013-2014. The sample included 18,054 men and women 25-64 years of age from 12 regions. Based on the frequency of consumption of basic foods, four a posteriori empirical dietary patterns (EDPs), along with an a priori cardioprotective dietary pattern (CPDP) were identified. To describe the regional living environment, 5 regional indices were used. The adherence to the meat-based EDP was directly associated with deterioration of social living conditions and the more northerly location of the region of residence. The probability of CPDP increased with deterioration of social living conditions, an aggravation of demographic crisis, higher industrial development of the region, as well as with a decline in the economic development of the region, income and economic inequality of the population. We detected some gender-dependent differences in associations. The revealed patterns reflect the national dietary preferences of Russians, and regional indices characterize the effect of living environment.

The detection of seismic events at regional and teleseismic distances is critical to Nuclear Treaty Monitoring. Traditionally, detecting regional and teleseismic events has required the use of an expensive multi-instrument seismic array; however in this work, we present DeepPick, a novel seismic detection algorithm capable of array-like performance from a single trace. We achieve this directly, by training our single-trace detector against labeled events from an array catalog, and by utilizing a deep temporal convolutional neural network. The training data consists of all arrivals in the International Seismological Centre Catalog for seven seismic arrays over a five year window from 1 Jan 2010 to 1 Jan 2015, yielding a total training set of 608,362 detections. The test set consists of the same seven arrays over a one year window from 1 Jan 2015 to 1 Jan 2016. We report our results by training the algorithm on six of the arrays and testing it on the seventh, so as to demonstrate the transportability and generalization of the technique to new stations. Detection performance against this test set is outstanding. Fixing a type-I error rate of 1%, the algorithm achieves an overall recall rate of 73% on the 141,095 array beam picks in the test set, yielding 102,394 correct detections. This is more than 4 times the 23,259 detections found in the analyst-reviewed single-trace catalogs over the same period, and represents an 8dB improvement in detector sensitivity over current methods. These results demonstrate the potential of our algorithm to significantly enhance the effectiveness of the global treaty monitoring network.

This study examines the performance of the Indian Monsoon Data Assimilation and Analy-sis (IMDAA) in predicting five extremely severe cyclonic storms (ESCS) over the Bay of Bengal. The Advanced Research version of the WRF (ARW) model is utilized for this analysis over the last two decades. The initial and lateral boundary conditions are derived from the IMDAA datasets with a horizontal resolution of 0.12° × 0.12°. Five ESCSs from the past two decades are considered: Sidr 2007, Phailin 2013, Hudhud 2014, Fani 2019, and Amphan 2020. The model is integrated up to 96 hours using double nested domains of 12 km and 4 km. Model performance is evaluated using the 4 km results, compared with available observational datasets, including the best-fit data from the India Meteorological Department (IMD), The Tropical Rainfall Measuring Mission (TRMM) satellite, and Doppler Weather Radar (DWR). The results indicate that IMDAA provides accurate forecasts for ESCSs Fani, Hudhud, and Sidr in terms of track, intensity, and mean sea level pressure, aligning well with IMD observational datasets. However, Sidr's track deviates more from the observations. The calculated mean absolute maximum sustained wind speed errors range from 8.4 m/s to 10.6 m/s from day-1 to day-4, while mean track errors range from 114 km to 496 km during the same period. Statistical analysis, including bias, mean error, and standard deviation, underscores the significance of ESCS prediction. The discussion also covers rainfall prediction, maximum reflectivity, and the associated structure of the storms.

There is a growing consensus that to effectively adapt to climate change, cities need user-friendly tools and reliable high-resolution biophysical and socio-economic data for analysis, mapping, modeling, and visualization. This study examines availability of various types of information used in climate adaptation plans of 40 municipalities with population less than 300,000 people in the United and in France, probing into the choice and usage of relevant information by small municipalities. We argue that non-climatic spatial data, such as population demographic and socio-economic patterns, urban infrastructure, and environmental data must be integrated with climate tools and datasets to inform effective vulnerability assessment and equitable climate adaptation planning goals. Climate adaptation plans frequently fail to address the existing structural inequalities and environmental injustices in urban infrastructure and land use. Adaptation methodological approaches should be reassessed in the context of much needed societal transformation. Lessons learned from our studies offer valuable insights for potential development of the national and state-level climate adaptation information services for cities.

Background: Post-acute sequelae of SARS-CoV-2 infection (PASC) is a complicated disease that affects millions of people all over the world. Previous studies have shown that PASC impacts 10% of SARS-CoV-2 infected patients of which 50-70% are hospitalized. It has also been shown that 10-12% of those vaccinated against COVID-19 were affected with PASC and its complications. The severity and the later development of PASC symptoms is positively associated with the early intensity of the infection. Results: The generated health complications caused by PASC involve a vast variety of organ systems. Patients affected by PASC have been diagnosed with neuropsychiatric and neurological symptoms. Cardiovascular system also has been involved and several diseases such as myocarditis, pericarditis, and coronary artery diseases were reported. Chronic hematological problems such as thrombotic endothelialitis and hypercoagulability were described as a condition that could increase the risk of clotting disorders and coagulopathy in PASC patients. Chest pain, breathlessness, and cough in PASC patients were associated with respiratory system in long COVID-19 causing respiratory distress syndrome. The observed immune complications were notable, involving several diseases. Renal system also was impacted and result in raising the risk of diseases such as thrombotic issues, fibrosis, and sepsis. Endocrine gland malfunction can lead to diabetes, thyroiditis, and male infertility. Symptoms such as diarrhea, nausea, loss of appetite and taste were also among reported observations due to several gastrointestinal disorders. Skin abnormalities might be an indication of infection and long-term implications such as persistent cutaneous complaints were linked to PASC. Conclusions: Long COVID is a multidimensional syndrome with considerable public health implications, affecting several physiological systems and demanding thorough medical therapy as well as more study to address its underlying causes and long-term effects.

The bioindicator potential of seagrass ecosystems in coastal trace metal monitoring is low for tropical island ecosystems. This study evaluated the bioindicator potential of six seagrass species exposed to anthropogenic trace metal pollution in the Andaman and Nicobar Islands (ANI) of India. Sediment and seagrass biomass, samples were analyzed for trace metals (Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb, Zn) from four locations of ANI exposed to anthropogenic contamination. Geo accumulation Index values indicated moderate trace metal contamination in seagrass sediment. Seagrass trace metal accumulation from sediment was both species-specific and location- specific for ANI. Small seagrass species such as H. ovalis, H. beccarii and H. uninervis accumulated the maximum concentration of six trace metals (Cr, Cu, Fe, Ni, Pb, Zn) in their tissues compared to big seagrass species like T. hemprichii and E. acoroides of ANI. This study indicates leaves of small seagrass and roots of big seagrass species can serve as short- and long-term bioindicators respectively, of coastal trace metal contamination in tropical islands of ANI.

Keywords: Amorphous-precipitate, Nitride, Morphological stability, Diffusion, Internal stresses, Modelling, Simulation