Introduction: Parameters used for neonatal mortality calculation vary among publications. Mortality in < 33 weeks gestational age at birth display global variations across different healthcare units. Objective: This study aims to explore trends in neonatal mortality among infants born preterm in the different units in Latin America and the Caribbean utilizing the EpicLatino Network Database in comparison to Canadian Neonatal Network (CNN) 2022. Materials and Methods: This study focused on an eight-year period, with a particular attention to mortality rates during the pre-pandemic (2015-2019) and pandemic/post pandemic (2020-2022) periods. Survival rates from CNN 2022 were included in the comparison analysis. Logistic regression analysis was confined to the 2020-2022 period. Adjustments were made for factors including gestational age, small for gestational age (SGA), Snape II score, inborn/outborn status, and center. As major malformations could account for mortality differences among units. The incidence of major congenital malformations, as defined by CNN, was compared among deceased patients. Results: A total of 15,454 records from 2015-2019 and 10,711 records from 2020-2022 were scrutinized. Overall, there were no significant differences in mortality rates between the two time periods (p=0.22). Moreover, the originating unit during the 2020-2022 period significantly influenced all statistical computations. Conclusions: Survival rates among infants < 26 weeks of gestation in Latin America and the Caribbean are on an upward trajectory, with the healthcare unit playing a pivotal role in this outcome within the EpicLatino database. Major malformations do not seem to be a significant contributing factor. These findings underscore the imperative of implementing quality improvement initiatives to elevate neonatal care standards in Latin America and the Caribbean.

Graph databases (GDBs) are becoming increasingly popular across scientific disciplines, being highly suitable to store and connect complex heterogeneous data. In systems biology, they are used as a backend solution for biological data repositories, ontologies, networks, pathways, and knowledge graph (KG) databases. In this review, we analyse all publications using or mentioning graph databases retrieved from PubMed and PubMed Central full-text search, focusing on the top 16 available GDB technologies. Relevant publications are then categorised according to their domain and application. We detail different approaches and highlight advantages of outstanding resources, such as UniProtKB, Disease Ontology, and Reactome, which provide graph-based solutions. We discuss ongoing efforts of the systems biology community to standardise and harmonise KG creation and the maintenance of integrated resources. Outlining prospects, including the use of GDBs as a way of communication between biological data repositories, we conclude that efficient design, querying, and maintenance of GDBs will be key for knowledge generation in systems biology and other research fields with heterogeneous data.

Artificial intelligence (AI) has emerged as a powerful tool for addressing the challenges posed by climate change and their impact on public health. By leveraging its capacity to analyze and predict climatic patterns, AI offers opportunities to enhance resource management and develop effective strategies for climate change mitigation. Moreover, AI can contribute to generating sustainable solutions that address the complex and interconnected nature of climate change. For example, AI can enable the optimization of energy consumption and facilitate the integration of renewable energy sources into existing systems. It can also support the development of climate models that provide timely and accurate predictions, enabling policymakers to implement proactive measures for disaster preparedness and response. Furthermore, AI-powered disease surveillance and mitigation techniques can improve public health outcomes by identifying patterns and trends in the spread of diseases in relation to climatic factors.However, the widespread adoption of AI-based solutions is not without challenges. Ethical concerns surrounding privacy and data ownership must be addressed, as the use of AI requires access to large datasets, raising potential privacy risks. Technical constraints, such as limited computational power and the need for sophisticated algorithms, also pose obstacles to the implementation of AI in climate change mitigation strategies. Furthermore, issues related to the accessibility and affordability of AI technologies must be resolved to ensure equitable distribution and maximize its potential impact on public health.To fully harness the power of AI in addressing climate change and improving public health outcomes, it is crucial to promote innovation, multidisciplinary collaboration, and open data science. Innovation can drive the development of new AI algorithms and technologies specifically tailored to address climate change challenges. Multidisciplinary approaches that bring together experts from diverse fields, including climate science, public health, and computer science, can foster a holistic understanding of complex systems and enable the design of comprehensive solutions. Finally, open data science practices, such as sharing data and algorithms, can facilitate collaboration and accelerate progress in mitigating climate change and its public health impacts.In conclusion, AI offers promising opportunities for effectively addressing climate change and its impact on public health. However, to fully realize its potential, it is essential to tackle ethical and privacy concerns, overcome technical constraints, and ensure accessibility and affordability. By promoting innovation, multidisciplinary collaboration, and open data science, we can unlock the transformative power of AI in mitigating climate change and improving public health outcomes.

Prostate cancer is the second most frequent malignancy (after lung cancer) in men worldwide. Prostate tissue biopsies are usually graded using scores according to the Gleason grading system. This Gleason score is the most popular prognostic marker that reveals the potential aggressiveness of the disease. However, inter-observer variability in rating by human assessors is a major limiting factor. Such variability could lead to missing a severe case or suggesting unnecessary treatments. This study explores the discriminative ability of artificial intelligence (deep learning models) for Gleason score assessment. The study was designed to use whole-slide images of digitized H&E-stained biopsies of prostate tissues to automate the grading process and provide a remotely accessible clinical decision support system. Custom convolutional neural network architectures were trained on 10,616 images of prostate tissues. Gaussian filters were applied to pre-process the images and improve model performance. Transfer learning was applied to train eight machine learning architectures namely: Xception, VGG16 & 19, ResNet101, MobileNet, DenseNet121, EfficientNetB5 & B7. Efficient NetB7 had the best performance 85.2% compared with ground-truth classification by experts. Performance improves as more data is available. The model was deployed and hosted as a web application API on Google cloud service to ensure remote access. Tissue biopsy images can be uploaded and the corresponding Gleason score recovered immediately. This system reduces diagnostics turnaround time, increase throughput, and compensate for limited skills, especially in low resource settings.

This paper shows the firsts results of a methodological approach in which Remote Sensing technologies (Satellite imagery and LiDAR) combined with Least Cost Path algorithm on GIS are being tested like tools to overcome locally-based interpretations about populational patterns and communication routes during Flavian municipality in the Comarca de El Condado region. The identification of fourteen hypothetical communication routes between already known archaeological sites thanks to a recent archaeological prospection, and the confirmation of three sections of them and a new archaeological site demonstrate that the combined use of the aforementioned technics has a very useful to delve more deeply, more widely and at a variety of different scales into the relation between the twelve known/selected Early Roman Empire sites and the surrounding landscape in the right bank of Guadalén River. It is expected that, in next phases, this methodological approach will allow us to go deeper in analysing and understanding spatial distribution, exploitation, and interrelation between different Early Roman Empire sites, helping us to fill the aforementioned gaps in our understanding of the archaeological continuum in the region reducing time and costs.

Rising demand and urbanization have led to the global increase and intensification of livestock production. Intensive production has harmful effects on the environment, public health (due to the emergence of zoonotic diseases), and animal welfare. In order to better understand how livestock production intensifies as countries develop and incomes rise, we examine the relationship between income per capita and intensification of poultry and cattle, using the states of India as a study region. We also replicate this analysis at the district level to test whether the relationship holds at different spatial scales. We identify outlying states and districts to see if there are policies that can keep agriculture production largely extensive, even as economic growth occurs. The results support the relationship of income being positively correlated with the proportion of livestock in intensive conditions. However, there are notable outlier states which have grown wealthy while still maintaining largely extensive production, indicating that there may be some cases where economic growth can occur without intensification.

The emerging industry of offshore wind turbines mounted on floating bases has garnered significant attention from both academia and industry. The desire to understand the complex physics of these floating structures has led to the development of numerical and physical modelling techniques. While physical testing has traditionally been employed, there is a growing focus on cost-effective and accurate high-fidelity numerical modelling as a potential alternative or supplement. However, commonly used numerical engineering tools in the offshore industry are considered mid- to low-fidelity and may lack the desired precision for floating offshore wind turbines (FOWTs). Given the complexity of these simulation codes, it is crucial to validate their accuracy. To address this, the International Energy Agency (IEA) Wind Technology Collaboration Programme initiated various research endeavors, including the Offshore Code Comparison Collaboration (OC3), Offshore Code Comparison Collaboration Continuation (OC4), Offshore Code Comparison Collaboration Continuation with Correlation (OC5), and the recent Offshore Code Comparison Collaboration Continued with Correlation and Uncertainty (OC6) projects. This study offers a comprehensive survey of the simulation tools available for FOWTs which were part of OC projects, focusing particularly on horizontal axis wind turbines (HAWTs) and highlighting their capabilities and fundamental theories.

Nanoindentation load-depth (P-h) plots is the basis for determination of mechanical properties of the samples and is especially vital for thin coatings deposited on substrates of various mechanical makeup from amorphous-brittle (borosilicate glass) to Silicon (having different crystallographic texture) to ductile substrates like stainless steel as well other aspects like indenter tip shape. The elastic-plastic response by simulated P-h plots as per modified empirical relations have been presented. The outcomes of this computational studies enlighten the database on the P-h plots for various coating/substrate systems and shall aid in the analysis of experimental P-h plots obtained,

We show succinctly a natural origin of the beautiful Gamma function in light of the WJ distribution, linking to quite distinct fields.

Modern research applies the Open Science approach that fosters the production and sharing of Open Data according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. In the geospatial context this is generally achieved through the setup of OGC Web services that implements open standards that satisfies the FAIR requirements. Nevertheless, the requirement of Findability is not fully satisfied by those services since there’s no use of persistent identifiers and no guarantee that the same dataset used for a study can be immutably accessed in a later period: a fact that hinders the replicability of research. This is particularly true in recent years where data-driven research and technological advances have boosted frequent updates of datasets. Here, we review needs and practices, supported by some real case examples, on frequent data or metadata updates in geo-datasets of different data types. Additionally we assess the currently available tools that support data versioning for databases, files and log-structured tables. Finally we discuss challenges and opportunities to enable geospatial web services that are fully FAIR: a fact that would provide, due to the massive use and increasing availability of geospatial data, a great push toward open science compliance with ultimately impacts on the science transparency and credibility.

Star copolymer films were studied for confirming the role of film morphology in antimicrobial activity previously reported. With this scope, films of a two-branches copolymer, namely m-PEG-(MMA-ran-DMAEMA)2, containing ≈ 40 % in mol of non-quaternized 2-(dimethylamino)ethyl methacrylate, were produced by using spin-coating, drop-casting and casting deposition techniques, thus obtaining ultra-thin, thin and thick films, respectively. The morphology is generally flat for thin and thick films, but it becomes substrate dependent for ultra-thin films where the film planarization effect is not efficient. Mechanical properties of such films were investigated by Force Volume Maps in both air and liquid. In air, ultra-thin films are in the substrate-dominated zone and thus the elastic modulus E is overestimated, while E reaches its bulk value for thin and thick films. In liquid (water), E follows an exponential decay for all films with a minimum soaked time t0 of 0.37 and 2.65 h for ultra-thin and thin and thick films, respectively. After this time, E saturates to a value in average 92 % smaller than that measured in air due to films swelling. Such results confirm the role of morphology envisaged in literature, suggesting also an additional role of mechanical properties in the antimicrobial activity.

Traditional methods of non-metallic materials joining for industrial uses are limited to lasers, or induction or conduction heating. The precision and efficiency for large-scale applications are difficult to be achieved at the same time. Here in this paper, we report a precise microwave welding method induced by localized surface plasmon of metallic macro-gaps under microwave excitation. The proposed method utilizes energy from well-developed commercial microwaver, and benefits from the precision of localized surface plasmon, an oscillating electron cloud excited by electromagnetic waves, which is currently under hot investigation only at micro- or nano-scales. The method is applied to the welding of polymers to solve the problems of complex processing equipment and high processing energy consumption in the traditional welding process, so as to cope with the growing energy and environmental crisis. Finite element numerical simulations are used to study the distribution characteristics of electric fields and temperature fields. The results show that the process is a high quality, efficient, low consumption and environmentally friendly green process compared to traditional polymer welding methods.

Coral reefs are one of the most productive yet vulnerable ecosystems on Earth. An important step in understanding the functioning of coral communities is studying the environmental impact on the state of reefs. The present study aimed to assess the impacts of the water temperature, precipitation, wave action and population density on the seasonal bleaching, partial and complete mortality of shallow-water branching corals of Pocillopora verrucosa species complex. The present study was conducted at the Dam Bay research station (Nha Trang Bay) from 26 April 2020 to 2 April 2021. Throughout the study the percentage of bleached coral colonies varied from 1 to 41.5% with two peaks, in autumn (October) and spring (April). Rates of the development of partial mortality varied from 0 to 10%, with a pronounced peak in December. At the end of the experiment, the percentage of coral colonies suffering from partial mortality reached 47%. Only 4,5% of experimental colonies died by the end of the study. Analysis revealed that water temperature and partial mortality are the drivers of bleaching, while wave action, temperature and bleaching are the factors with a significant impact on partial mortality. In the present study, the main cause of coral death was the development of algal fouling at the sites of colony lesions, which gradually spread over the entire surface of the colony. We showed also that the impact of individual stress on mortality prevailed over the impact of seasonal bleaching and partial mortality events.

The possibility of a shock wave recovery at a discrete closed interface with a heated gas has been investigated. A two-dimensional model applied to conditions of optical discharges featuring spherical, elliptical, and drop-like configurations demonstrated that non-symmetry in the shock refraction contributes to the specific mechanism of recovery other than simply its compensation. Even though the full restoration of the hypersonic flow state doesn’t occur in a strict sense of it, clear reverse changes toward the initial shape of the shock front eventually take place, thus creating an appearance of a full recovery seen in experiments. From analysis for different interfaces symmetries, the factors determining the recovery dynamics are identified. The results are directly applicable to the problem of energy deposition into a hypersonic flow, however it can be useful anywhere else where the flow modifications following the interaction are important. The dimensionless form of the equations allows applications on any scale other than that demonstrated for the optical discharges.

Focus Group Discussions (FGDs) are widely employed in qualitative research to delve into complex social issues, yet their application in conservation studies lacks standardised guidelines and thorough evaluation. This review assesses the utilisation of FGDs in biodiversity and conservation research from 2000 to April 2022, identifying 170 pertinent articles, primarily published between 2015 and 2022. FGDs, often integrated with other methodologies, predominantly sought to understand community perspectives, evaluate conservation practices, explore challenges, and document indigenous knowledge. Despite their extensive use, methodological intricacies were frequently underreported. This paper underscores the necessity for enhanced reporting standards and comprehensive guidelines to optimise the effectiveness and reliability of FGDs in conservation research. By means of critically investigating existing literature, this study contributes critical important insights into the strengths and limitations of FGDs, ultimately advocating for greater methodological rigour and transparency in their application within the realm of conservation science.

Fungi are ubiquitous and metabolically versatile. Their dispersion has important scientific, environmental, health, and economic implications. They can be dispersed through the air by the aerosolization of near surfaces or transported from distant sources. Here, we tested the contribution of local (scale of meters) versus regional (kilometers) sources by analyzing airborne fungal community by ITS sequencing around a copper mine in the North of Chile. The mine was the regional source, whereas soil and vegetal detritus were the local sources at each point. The airborne community was highly homogeneous in ca. 2,000 km2, impeding the detection of regional or local contributions. Ascomycota was the dominant phylum in the three communities. Soil and vegetal detritus communities had lower alpha-diversity, but some taxa had abundance patterns related to the distance to the mine and altitude. On the contrary, the air was compositionally even and unrelated to environmental or spatial factors, except for altitude. The presence of plant pathogens in the air suggests that other distant sources contribute to this region's airborne fungal community and reinforces the complexity of tracking the sources of air microbial communities in a real world where several natural and human activities coexist.

Antibiotic resistance currently considered as a global concern mostly impacting low- and middle-income nations and it can be accelerated by antibiotic abuse and other forms of excessive antibiotic use. There is little data on community practices and understanding in Somaliland on antibiotics and antibiotic resistance. To provide evidence-based communication intervention techniques for safer antibiotic use the qualitative study was done from November 1st to December 1st, 2023, and consisted of in-depth semi-structured interviews with adult heads of households in Hargeisa, Somaliland, using purposive and snowball sampling strategies. Participants were chosen from a variety of medical and educational backgrounds. Thematic analysis was used to investigate community knowledge and antibiotic use in the sampled population. To investigate the level of awareness on antibiotic use, 20 respondents (households) were questioned (Table 1). Of these, 17 (85%) became aware of the term antibiotic itself, with 7 (35%) being prescribed by a physician, 9 (45%) receiving laboratory diagnosis when using antibiotics, and 6 (30%) becoming aware of the potential risks associated with improper antibiotic use. This study highlighted the community's lack of understanding about antibiotic use. The majority of the study participants knew the phrase "antibiotic" but had no idea what it meant, the side effect of the antibiotics and other medical science related information regarding how to safely use antibiotics. According to the findings, initiatives for antibiotic stewardship should focus on community education to prevent antibiotic misuse or abuse.

BACKGROUND: Current research recorded hearing loss in 8.5million Nigerians. Hearing loss can be prevented and treated. Most individuals in the communities are unaware. Available hearing screening instruments are not readily accessible in communities. Regular screening is the key. Hence, the introduction of the HearWHO App in the communities, a mobile hearing screener. AIM: - To detect hearing loss and otological disorders - To validate the HearWHO App in the communities - To launch the HearWHO App in the communities MATERIALS AND METHODS: Commenced after obtaining due ethical clearance, informed consent and permissions. A 3 year duration study (March 2020 to March 2022). Study centres were 4 motor parks in Benin City Edo State (Muyi line, Faith motors, Iyare motors and Magorawa terminal) and 2 hospitals in Ondo City, Ondo state (General Hospital and Trauma Centre of the UNIMEDTH complexes). Ambient noise was recorded. Total population sampling technique was used. Health education was given. Using the HearWHO App in mobile smartphone connected to ear piece, each participant’s ears were tested. Each ear was regarded as a separate entity. Otoscopy was done. Findings of hearWHO App were compared with Otoscopic findings. Data realized were documented and analyzed with SPSS -23. P value < 0.05 was regarded statistically significant. RESULTS: 175 individuals participated, giving 350 ears examined. There were abnormal HearWHO findings in 77.4% ears compared to abnormal Otological findings in 65.0% ears. Predominant otological disorder was Eustachian Tube Dysfunction. Association of HearWHO finding with location was statistically significant (P=0.014). CONCLUSION AND RECOMMENDATION: Hearing loss and otological disorders were detected. There was agreement between HearWHO normal findings and normal otological findings. Based on challenges encountered, there is need to develop additional Apps or modify the HearWHO App to ensure Sustainable Developmental Goal -3 (SDG -3). Thus, creating a better future today making impact with mobile technology.

SIAKAD is a system developed to meet the needs of the academic community as a whole. Implementation of SIAKAD is based on three satisfaction indicators: access speed, ease of access and timeliness. Qualitative and quantitative methods on SERVQUAL analysis. Then analysed with statistical data as a comparison of satisfaction implementation in each academic community in IAKN and UIN universities. This study shows that the purpose of satisfaction affects the value of the academic community in providing an excellent and destructive impact on the value of work in higher education as well as the involvement of various elements in higher education to determine how the academic information system (SIAKAD) should be built to meet the expectations of its users and following SIAKAD standards in general in higher education.

The aim of this paper is to compare the taxonomic composition and species diversity of the macrozoobenthos in Maritsa River (Bulgaria) and Han River (South Korea). Samples were collected at 15 selected sites in each river, including some of their main tributaries in 2020 and 2021. The number of the taxa recorded in Maritsa River was more than twice as great as in Han River: 192 taxa belonging to 19 systematic groups compared to 88 taxa belonging to 18 groups respectively. The order Ephemeroptera had the highest species richness: 31 taxa in the Bulgarian rivers and 26 taxa in the South Korean ones. The macrozoobenthic communities responded and adapted to the various conditions and impacts in the water environment with changes in the species composition and structure. The analysis of the similarity in the taxonomic composition showed low resemblance between all study sites but displayed distinct separations between the rivers and the two years. In general, the species structure of the macrozoobenthic communities in Maritsa River and its studied tributaries was better than in Han River. In both years, high species diversity was recorded at the reference sites in the rivers, characterized by conditions closely resembling natural environments. The species richness and the evenness of macrozoobenthos were very low at sites downstream subjected to considerable anthropogenic pressure. Some of the communities in Han River were almost destroyed completely.

The relationship between religion and politics is a constant in the history of humanity. In the specific case of Western culture, it is possible to trace an archeology of the political as an effect of theological-political devices (essentially Christian-inspired). If we add to this the evolution of politics, in modern times, towards biopolitics, then the relationship focuses on very concrete topics. This is the case of the immunological process – from a personal, social, and philosophical perspective – thoroughly analyzed by Italian philosopher Roberto Esposito. In the context of his philosophical immunology, the place of religion is mainly archaeological and is interpreted critically. This article also aims to critically analyze his position, proposing a reading close to his thought but which is, at the same time, somewhat different.

The analysis of network structure is essential to many scientific areas, ranging from biology to sociology. As the computational task of clustering these networks into partitions, i.e., solving the community detection problem, is generally NP-hard, heuristic solutions are indispensable. The exploration of expedient heuristics has led to the development of particularly promising approaches in the emerging technology of quantum computing. Motivated by the substantial hardware demands for all established quantum community detection approaches, we introduce a novel QUBO based approach that only needs number-of-nodes many qubits and is represented by a QUBO-matrix as sparse as the input graph's adjacency matrix. The substantial improvement on the sparsity of the QUBO-matrix, which is typically very dense in related work, is achieved through the novel concept of separation-nodes. Instead of assigning every node to a community directly, this approach relies on the identification of a separation-node set, which - upon its removal from the graph - yields a set of connected components, representing the core components of the communities. Employing a greedy heuristic to assign the nodes from the separation-node sets to the identified community cores, subsequent experimental results yield a proof of concept. This work hence displays a promising approach to NISQ-ready quantum community detection, catalyzing the application of quantum computers for the network structure analysis of large scale, real world problem instances.}

Sustainability is essential for every business and organization, but how can it be achieved? This work is a study of sustainability based on the sufficiency economy philosophy, a valuable concept introduced by the Thai people. We apply it to the notion of sustainability in 400 agricultural community enterprise owners in Thailand, who participated in the study. An oblique rotation component analysis was performed, finding that the variables on the same side are related, and a confirmative component analysis with structural equation models was conducted. The results showed that the approach to applying the sufficiency economy philosophy among community enterprises consists of 11 components, as follows: 1) financial control, 2) planning, 3) member management, 4) morals, 5) prevention plan, 6) moderation, 7) knowledge and expertise, 8) market development, 9) care, 10) quality control and 11) value of investment. The confirmative component analysis with structural equation modeling was consistent with the empirical data. Agricultural community enterprises and entrepreneurs focus on the moral component, conduct business with honesty and avoid causing problems for others, value justice without taking advantage with diligence and adhere to moral principles in life, because all of the above will lead to sustainability in the future.

Indigenous knowledge is proven to be one of the foundations of sustainable land and marine management. While indigenous knowledge is acknowledged as of important factors on maintenance of biodiversity of the planet, it also ensures the sustenance of social and economic system of indigenous community. To facilitate the application of indigenous knowledge on management of customary forest in Indonesia, since 2012, the Government of Indonesia has been providing formal access for indigenous communities to their forests to maintain forest sustainability and to enhance the welfare of indigenous community. Nonetheless, the achievement of sustainable development goals in the scope of forest and conservation area management is threatened by various competing interests and power imbalance, which mostly leads to conversion of naturally vegetated area, as well as the inability of the community to integrate new economic opportunities to its institution. Moreover, the Government of Indonesia has not been regulating the involvement of indigenous community on the management of conservation area. Most importantly, such a program provides no reference on indigenous community, especially on the assessment of authenticity of indigenous community’s forest. Cultural space methodology may fill the aforementioned gaps. The methodology was developed based on the notion of cultural space and land administration, particularly the people-and-land/marine space relationship. Moreover, such a methodology was also constructed based on the experiences of agricultural and maritime communities in Indonesia on the administration of their territories. The methodology provides a procedure to convert information on the interrelation of indigenous community, its cultural space in forest and conservation area, and indigenous knowledge into geospatial information and data that represent the cultural space unit as a geographic feature. Therefore, such methodology may be utilised to assess the authenticity of a long-existing relationship between a community, especially an indigenous one, and its land, particularly that serves conservational function.

To get a better knowledge of the effects of residual chlorothalonil on soil characteristics and soil microbial communities, we evaluated the dissipation of chlorothalonil and the effects of different chlorothalonil concentrations on soil respiration, enzyme activities, and microbial community structure in yellow-brown loam soils. Bacterial and fungal soil communities were examined using traditional plate counting and polymerase chain reaction-denaturing gradient gel electrophoresis (PCR–DGGE) methods. Soil properties and the results of DGGE band analysis were both used to estimate the status of the soil microbial ecosystem. The results show that residual chlorothalonil has considerable effects on soil respiration, enzymatic activities, and microbial community structure. In particular, soil respiration and phosphatase activities were increased, while saccharase activity, microbial biomass, and microbial community diversity were decreased by increasing levels of chlorothalonil treatment. Correlation analyses revealed that the application of chlorothalonil was significantly correlated with the change of the soil respiration, urease activity, sucrase activity, soil culturable bacteria and culturable fungi biomass. We conclude that residual chlorothalonil is directly related to soil respiration, enzyme activities, and microbial community structure.

Three computer algorithms are presented. One reduces a network $\CALN$ to its interior, $\CALI$. Another counts all the triangles in the network, and the last randomly generates networks similar to $\CALN$ given just its interior $\CALI$. But these algorithms are not the usual numeric programs that manipulate a matrix representation of the network; they are set-based. Union and meet are essential binary operators; contained_in is the basic relational comparator. The interior $\CALI$ is shown to have desirable formal properties and to provide an effective way of revealing ``communities'' in social networks.

In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks in our ability to process information have reduced our capacity to fully exploit the growing volume and variety of data. Here, we take a critical look at the information infrastructure that connects modeling and measurement efforts, and propose a roadmap that accelerates production of new knowledge. We propose that community cyberinfrastructure tools can help mend the divisions between empirical research and modeling, and accelerate the pace of discovery. A new era of data-model integration requires investment in accessible, scalable, transparent tools that integrate the expertise of the whole community, not just a clique of ‘modelers’. This roadmap focuses on five key opportunities for community tools: the underlying backbone to community cyberinfrastructure; data ingest; calibration of models to data; model-data benchmarking; and data assimilation and ecological forecasting. This community-driven approach is key to meeting the pressing needs of science and society in the 21st century.

Information and communication technologies play an increasingly important role in the process of knowledge and management of places at different scales. ICTs allow a rapid diffusion of data not only through institutional channels but also through social networks where the smart community share experiences and perceptions. In this sense, ICTs become strategic tools to support the promotion of sustainable tourism development of territories, especially if the digital data are organised within a circular smart dashboard. This research focuses on the case study of the Santa Barbara Walk (SBW), an ancient mining route in the Sulcis Iglesiente region (Sardinia, Italy), where the authors have recognized a state of disorganization in slow tourism promotion activities. In fact, if the SBW represents a network - material infrastructure - which connects the main points of interest along the Walk, its digital network - intangible infrastructure - is fragmented in terms of policies and contents. The goal of this study is to provide a comprehensive set of data and to propose the architecture and design for a circular dashboard of the SBW, capable of organizing information concerning the main features of the walk, in order to facilitate a shared governance for an effective tourism promotion.

(1) Background: Travel medicine practice has not been a part of practice in the community pharmacies in Japan. However, it’s getting more common for pharmacists to run travel clinic in North America. With ongoing globalization, Japanese pharmacists might be practicing travel medicine in future. This descriptive study is to examine the current knowledge, attitudes, and practices among Japanese community pharmacists. (2) Methods: Invitation to the study was sent to all pharmacies or corporates listed on Nippon Pharmacist Association member list plus one another large size pharmacy chain that was not member of NPhA. Community pharmacists working under those companies received a weblink to the survey. The survey was conducted from June to July 2017 by online questionnaire. (3) Results: The self-declared knowledge level of infectious diseases as well as travel vaccinations was generally low. The frequency of correct answer of the antibiotic resistance in South East Asia was 48.5%. Knowledge level of qunine resistance to Plasmodium falciparum malaria in Ghana and Nicaragua was very low. (4) Conclusions: Japanese community pharmacists are not familiar with travel related infectious diseases and vaccines used in travel medicine. The knowledge on the antibiotic resistance in traveler’s diarrhea and malaria prophylaxis was all low that is consistent with low degree of exposure to travel health questions from patients in daily practice and low percentage of intention to earn travel health certificates.

Maternal-child care is one of the foundations of primary health care. Nurses’ competency skills they have been taught. Community awareness is an important part of preventive healthcare, and nurses must be aware of the factors that impact the health of the community. This study examines the effectiveness of lecture-based instructions in maternal and child care and its implications to students' social competency skills and community awareness in Nursing Colleges in Nueva Ecija, Philippines. The researcher uses survey questionnaire and employed the descriptive design where fifteen (15) nursing students and five (5) teachers were purposively selected. The findings revealed that the weighted mean for the effectiveness of lecture based instruction in maternal and child care is 3.91 with verbal description of “Effective”, the effects of lecture based instruction in maternal and childcare to students’ social competency skills and community awareness got the weighted mean of 3.87 and interpreted as “very satisfactory” and the effectiveness of actual community-based instruction is very effective with weighted mean of 4.25 and is higher compare to lecture based instruction. The results also revealed that students and teachers were challenged in lecture-based instruction in maternal and chi8ldcare during distance learning. Recommendations for the enhancement of lecture-based instruction in maternal and childcare in social competency skills and community awareness were also made.

With the trend of public infrastructure becoming more sustainable, large multi-purpose sports venues (LMPSVs) have become one of the world's most complex architectural projects and one of the landmark buildings of an international city. LMPSVs will lead the world in sustainable design, construction and operational innovations, and play a crucial role in raising awareness of sustainability around the world. System Thinking (ST), System Dynamics (SD) and Sustainable System Development (SSD) theories are three interrelated concepts that together form a methodological framework for solving complex system problems and driving strategies. The purpose of this study is to examine how LMPSVs can implement environmental, social, governance, and innovation (ESGI) enterprise transformation strategy (ETS) based on a sustainable systems development (SSD) framework. In view of the current global environmental challenges and social responsibility requirements, the motivation of this study is to provide an integrated transformation pathway for LMPSVs to achieve the goal of sustainable development and to contribute to the field of related disciplines. The methodology of this research adopts a combination of literature review and case study analysis, and the theoretical basis is mainly drawn from cutting-edge research in the fields of sustainable development, corporate social responsibility (CSR) and environmental management. Then, by analyzing successful transformation cases in China, we extract data and information to explore the application and effectiveness of these strategies in practice. The results of the study show that by implementing ESGI-based transformation strategy, LMPSVs can not only make significant progress in terms of environmental protection, social responsibility, and governance structure, but also drive long-term corporate growth and competitiveness through innovation. Specifically, these results are realized in terms of increased efficiency in energy use, improved waste management, community involvement and increased stakeholder satisfaction. The study concludes by emphasizing that the SSD-based ESGI Transformation Strategic framework provides a sustainable pathway for LMPSVs. In the future, the extension of this transformation strategy will help a wider range of industry sectors to achieve sustainable development goals, and has wide application potential and far-reaching social significance.

Using assembly theory, we investigate the assembly pathways of binary strings of length N formed by joining bits present in the assembly pool and the strings that entered the pool as a result of previous joining operations. We show that the string assembly index is bounded from below by the shortest addition chain for N, and we conjecture about the form of the upper bound. We define the degree of causation for the minimum assembly index and show that for certain N it features regularities that can be used to determine a shortest addition chain. We show that a string with the smallest assembly index for N can be assembled by a binary program of length equal to this index if the length of this string is expressible as a product of Fibonacci numbers. We conjecture that there is no binary program that has a length shorter than the length of the string having the largest assembly index for N that could assemble this string. The results confirm that four Planck areas provide a minimum information capacity that corresponds to a minimum thermodynamic (Bekenstein-Hawking) entropy. Knowing that the problem of determining the assembly index is at least NP-complete, we conjecture that this problem is NP-complete, while the problem of creating the string so that it would have a predetermined largest assembly index is NP-hard. The proof of this conjecture would imply P ≠ NP, since every computable problem and every computable solution can be encoded as a finite binary string.

CXC chemokine receptor 1 (CXCR1) is an important regulator for neutrophil granulocyte activation through binding to the ligand interleukin-8 (IL-8). Upon binding to IL-8, CXCR1 activates downstream signaling, critical for innate and adaptive immune responses. The IL-8-CXCR1 axis also plays an important role in tumor progression, especially in the tumor microenvironment. CXCR1 antagonists or anti-IL-8 monoclonal antibodies (mAbs) have been developed and evaluated in clinical trials for inflammatory diseases and tumors. In this study, we developed novel mAbs for mouse CXCR1 (mCXCR1) using the N-terminal peptide immunization. Among the established anti-mCXCR1 mAbs, Cx₁Mab-8 (rat IgG_2b, kappa) recognized mCXCR1-overexpressed Chinese hamster ovary-K1 (CHO/mCXCR1) and mCXCR1-overexpressed LN229 (LN229/mCXCR1) by flow cytometry. The dissociation constant (K_D) values of Cx₁Mab-8 for CHO/mCXCR1 and LN229/mCXCR1 were determined as 5.1 × 10⁻¹⁰ M and 1.3 × 10⁻⁹ M, respectively. These results indicated that Cx₁Mab-8 is useful for detecting mCXCR1 by flow cytometry with high affinity and can obtain the proof of concept in preclinical studies.

This study assessed the financial management practices and challenges of food cart businesses in Cabanatuan City, Nueva Ecija. The study used a descriptive research design and structured surveys and questionnaires to gather quantitative data from 20 food cart businesses. The data were analyzed using statistical tools such as weighted means, frequencies, and percentages to provide a comprehensive overview of these small enterprises' financial practices and challenges. Key findings highlight that while many businesses demonstrate basic financial literacy, significant gaps exist in financial record-keeping, budgeting, and revenue management. The study emphasizes the importance of improving these practices to ensure the sustainability and growth of food cart businesses. The research contributes to the broader discourse on small business management and economic development by identifying common challenges and offering targeted recommendations. The findings underscore the need for targeted interventions, such as financial training and policy support, to enhance the financial acumen of food cart owners. This study adds to the existing body of knowledge as it provides practical insights that can benefit business owners, policymakers, and community stakeholders in fostering a more resilient and economically vibrant local economy.

Artificial intelligence (AI) shows great potential in medical diagnosis and drug analysis. Through deep learning technology, AI can automatically extract features from large amounts of complex medical data, significantly improving diagnostic accuracy and drug development efficiency. Especially in drug target discovery and antiviral peptide classification, AI technology can accelerate data processing and prediction, helping researchers identify potential therapeutic molecules more quickly and optimize the drug development process. This study proposes and validates a Deep learn-based model, deep-Avpiden, to improve the classification and discovery efficiency of antiviral peptides (AVPs). By using sequential convolutional networks (TCNs), the model outperforms traditional recurrent neural networks (RNNs) and long short-term memory networks (LSTMs) in capturing long-term dependencies and parallel computing capabilities. In terms of dataset, we used AVPs and non-AVPS samples from multiple databases, totaling 5,414 cleaned and de-weighted peptide sequences for model training after data preprocessing and embedding. The Deep-AVPiden model has been shown to outperform existing advanced classifiers in experiments, and its effectiveness has been verified by accuracy, precision, recall rate, and area under the ROC curve (OC-ROC). In addition, to accommodate computing resource constraints, we propose an optimized version of Deep-AvPIDen (DS), which utilizes Deep separation convolution technology to significantly reduce computing resource consumption. Through the online application platform, researchers can efficiently classify antiviral proteins and discover new AVPs. Future research could further optimize the model's computational efficiency, handle larger data sets, and expand its potential for biomedical problems such as drug combination prediction and new drug discovery.

Digital transformation in government services is seen as a progression towards offering more efficient and convenient services. In the wake of the COVID-19 pandemic, many governments worldwide have expedited the digitisation of their services to facilitate social distancing. Digital transformation encompasses the shift from manual, face-to-face services to automated, online-based systems. This process occurs in three stages: digitisation, digitalisation, and digital transformation. However, the varying stages of digital government implementation across countries impact service outcomes differently. Little research has been devoted to focusing on the outcome metrics crucial for the success of digital services, particularly in Kuwait. Moreover, although the existing literature has explored some metrics, specific metrics have been neglected. This study aimed to investigate current trends and preferences in digital government services usage using empirical quantitative data gathered from users of digital services in Kuwait. Specifically, the aim is fourfold: (i) to identify crucial outcome metrics for the success of digital services, (ii) to assess how users evaluate these services according to these metrics, (iii) to examine significant differences between digital transformation and digitalisation services, and (iv) to develop and validate a model for evaluating the success of digital transformation services. To achieve the study's objectives, 378 users of digital government services were surveyed quantitatively. This study found that users primarily access services through smartphones and applications, underscoring the need for mobile optimisation. There was a marked preference for real-time, automated services, with dissatisfaction for those requiring lengthy approval processes. Six key metrics were identified and grouped into three domains: service-related (customer satisfaction and service quality), convenience-related (accessibility and ease of use), and security-related (perceived security and perceived trust). Digital transformation services outperformed digitalisation services in five key areas: customer satisfaction, service quality, accessibility, ease of use, and perceived security, except perceived trust, which remained consistent across both service types. Several recommendations were proposed to advance government digital transformation services, boost efficiency, and enhance the user experience.

Haug and Tatum [1, 2] have recently outlined a possible path to solving the Hubbletension within Rh = ct cosmology models using a trial-and-error algorithm for redshift scaling, 1 specifically z = (R_h/R_t) − 1 and z = (R_h/R_t)^{1/2}-1 . Their algorithm demonstrates that one canstart with the measured CMB temperature and a rough estimate of H_0. Based on this approach, they nearly perfectly match the entire distance ladder of observed supernovae by identifying a single value for H_0. However, their solution is based on a simple numerical search procedure, which, although it can be completed in a fraction of a second on a standard computer, is not a formal mathematical proof for resolving the Hubble tension.Here, we will demonstrate that the trial-and-error numerical method is not necessary and that the Hubble tension can be resolved using the same Haug and Tatum type R_h = ct model through a closed-form mathematical solution. Furthermore, we will prove that this solution is valid for a much more general case of any cosmological redshift scaling consistent with: z = (R)h/R)t)^x − 1. Haug and Tatum have only considered the most common assumptions of x = 1 and x = 1/2 .Our solution involves simply solving an equation to determine the correct value of H0. This is possible because an exact mathematical relation between H_0 and the CMB temperature has recently been established, in combination with the linearity in an R_h = ct model. We also demonstrate that a thermodynamic form of the Friedmann equation is consistent with a wide range of redshift scalings, namely: z = (R_h/R_t)^x − 1.

A sublingual vaccine comprising Poly(I:C) adjuvant and influenza HA antigen was evaluated for safety in both mice and macaque monkeys relative to its intranasal counterpart. Safety was assessed with harmful effects corresponding to upregulation of the inflammation-associated genes: Saa3, Tnf, IL6, IL1b, Ccl2, Timp1, C2, Ifi4, Aif1, Omp, Nos2, and/or Gzmb in mice and SAA2, TNF, IL6, IL1B, CCL2, TIMP, C2, AIF1, and GZMB in macaques. Quantitative gene expression analyses were performed using RT-qPCR with RNA samples from four tissues: olfactory bulb, pons, lung, tongue, and (submandibular) lymph node from both mice and macaques. In mice, the intranasally delivered vaccine markedly upregulated the inflammation-related genes in the olfactory bulb 1 day and 7 days after vaccination. The adverse effects of intranasal vaccination were also observed in macaques, however to a lesser extent than in mice. The intranasal vaccination also upregulated these genes in the pons of both mice and macaques. In contrast, the sublingual vaccine did not adversely affect the olfactory bulb or pons in either mice or macaques. The intranasally administered vaccine significantly upregulated these genes in the lungs only 1 day after vaccination, but not 7 days later, in both mice and macaques. We conclude that intranasal vaccination results in unfavorable side effects corresponding to upregulated inflammatory genes in the brain (olfactory bulb and pons). Sublingual vaccination, however, did not induce these side effects in either mice or macaque and was hence evaluated as safe.

In today’s business landscape, customer retention has become a critical factor for sustainable growth. Many companies continue to focus on acquisition, which leads to high costs and constant customer turnover. This article highlights the importance of retention, proposing a shift in focus toward loyalty as the key to maximizing customer lifetime value (LTV). Improving retention not only increases LTV but also reduces acquisition costs, enhances virality, and provides financial stability. This paper introduces a scientific approach that allows companies to identify the underlying causes of low retention through observation, hypothesis formulation, and controlled experimentation. Using tools such as data analysis and A/B testing, companies can iteratively optimize their retention strategy, adjusting interventions in real-time based on the results obtained. Continuous experimentation emerges as an indispensable tool for navigating market complexity, enabling organizations to learn and adapt quickly. This data-driven approach not only improves retention but also drives long-term growth by building strong relationships with customers. In an increasingly competitive environment, companies that prioritize retention and experimentation are better positioned to achieve resilient and profitable growth.

In this paper, we present an improved 100CMM regenerative thermal oxidizer (RTO) designed for low-emission combustion, capable of processing over 95% of volatile organic compound (VOC) gas emissions at generating sites. The existing RTO system features a cylindrical drum structure that cyclically introduces and discharges VOC gas into a rotating disk, achieving excellent energy efficiency with a heat recovery rate exceeding 95%. However, the driving force exerted on the rotating disk in the RTO combustion chamber causes increased wear around the rotating shaft, leading to untreated gas being released through the outlet due to the channeling phenomenon. Additionally, prolonged use can result in operational issues such as rotation stoppages or explosions caused by pollutant discharge, dust accumulation, and thermal expansion at high temperatures of up to 800°C. To address these challenges, we designed an enhanced rotating plate drive unit while ensuring the stable operation of the RTO combustion chamber. Considering that the combustion chamber can reach temperatures of up to 920°C when processing high-concentration VOC gas, the gas burner has been designed with a diameter of 125 mm, and the outlet dimensions are set to 650 mm x 650 mm to effectively discharge high-temperature waste heat. The heat storage material in the combustion chamber is configured with a ceramic block thickness, and the outer diameter and height of the combustion chamber are set at 250 mm, 2,530 mm, and 1,875 mm, respectively, to optimize the gas residence time and the insulation material thickness. Empirical experiments were conducted to analyze changes in VOC removal efficiency, nitrogen oxide emission concentration, and total hydrocarbon (THC) concentration, ultimately evaluating the economic performance of the 100CMM RTO.

Graph unlearning has emerged as a crucial technique in privacy-preserving applications, particularly in scenarios where sensitive data must be erased from graph-based systems. This paper explores the fundamental concepts, challenges, and methodologies associated with graph unlearning, including its application to domains such as social networks, financial transaction systems, and healthcare networks. By delving into various algorithms, including local and global unlearning methods, we analyze the trade-offs between accuracy, privacy, and computational efficiency. The paper further investigates the security risks associated with graph unlearning, including adversarial and inference attacks, and proposes mitigation strategies to safeguard unlearning processes. We also examine the unique challenges posed by federated learning systems, where unlearning requires coordination across decentralized clients. Finally, the paper evaluates graph unlearning techniques using performance metrics such as time complexity, accuracy, and privacy guarantees, supported by real-world examples from diverse applications. The findings emphasize the importance of developing robust, scalable, and secure unlearning mechanisms to ensure data privacy and compliance with regulations. Evaluation and metrics for Graph Unlearning will also be discussed in this paper.

Chitosan spherical scaffolds, derived from the deacetylation of chitin, are natural polymers with significant potential, though challenges remain in optimizing their properties. The use of chitosan as a carrier for the controlled release of iron chloride is not yet fully established, despite iron’s critical role in various essential biological processes, including as a component of metalloenzymes and in the maintenance of life. Methods: This study aimed to develop a novel protocol for synthesing chitosan scaffolds and to characterize their properties using analytical techniques. Additionally, the release profile of iron was modeled using two primary controlled-release mathematical models. Results: The results demonstrated successful synthesis and physicochemical characterization of the chitosan sphere scaffolds. These scaffolds exhibited appropriate topography for iron loading and cellular interaction, as confirmed by SEM analysis, and contained functional groups as identified by FTIR. The scaffolds were also semi-crystalline (XRD), showed controlled degradation, and were confirmed to be non-toxic biomaterials. Furthermore, the modeling of the controlled release of iron chloride adsorbed on the scaffold surface, as well as the modeling of iron chloride specimens using the MEDUZA software, was successfully conducted. A theoretical curve was generated from the experimental dose-response data collected over time, considering variations in pH and medium concentration. Conclusions: In conclusion, a novel protocol for chitosan-based carriers was successfully developed, enabling thorough physicochemical characterization and modeling of both absorption and controlled release.

The modern world is gradually moving towards a global civilisation that is automated and propelled by technology. Artificial intelligence (AI) is a highly advanced technology that has been acknowledged as a major innovation. The incorporation of this technology into the banking sector has enhanced operational procedures in relation to customer satisfaction, virtual assistance, and risk reduction. This machine is employed to streamline activities and improve how decisions are made in this sector. This study investigates the potential benefits and challenges of implementing artificial intelligence in the banking sector. The methodology ensures a comprehensive understanding of the implementation of artificial intelligence in banking by showcasing its effectiveness, precision, and efficiency, as well as the opportunities it presents. The study data were collected from secondary sources, such as recent publications that demonstrate applications of artificial intelligence from five different banks, as well as the examination of industry reports. The main findings of this study demonstrate the substantial improvement of administrative operations through AI-driven technology, which effectively automates activities that include inputting data and handling information. As a result, the frequency of mistakes caused by people has reduced, leading to a 30% decrease in operational expenditures for all evaluated institutions. However, the banking industry admits the challenges it encounters, such as issues with confidentiality and a scarcity of skilled employees. In the financial services industry, the integration of artificial intelligence into the banking sector is perceived as an advantageous chance instead of a harmful danger, with a greater potential for beneficial impact.

Often, in biology, we are faced with the problem of exploring relevant unknown biological hypotheses in the form of myriads of combinations of factors/genes/proteins that might be affecting the pathway under certain conditions. In colorectal cancer (CRC) cells treated with ETC-1922159, many genes were found up and down regu- lated, individually. A recently developed search engine ranked combinations of ATP- binding cassette (ABC) transporters-X (X, a particular gene/protein) at 2nd order level after drug administration. These rankings reveal which ABC-X combinations might be working synergistically in CRC. If found true, oncologists can further test the com- bination of interest in wet lab and determine the mechanism of functioning between the ABC and X. In this research work, we cover combinations of ABC with ubiquitin- conjugating enzymes (UBE2), Interleukin (IL), BCL and Caspase (CASP).

The amount of solar energy produced is directly proportional to the surface area of solar panels exposed to sun rays. To increase the productivity of solar panels, a number of techniques are proposed by curving the surface or protruding the panel surface to maximise the surface area, e.g. Protruding panel surfaces with shapes such as pyramidal, cone, spherical cap, sinusoidal wavy curve, etc. These techniques are analysed to determine whether the panel surface area increases. The geometrical design analysis showed that, depending on the chosen surface curving method, the panel can achieve a remarkable increase in surface area.The system advisor model was used to assess a sample of solar cells with standard measurements of 6 by 6 inches that were organised in a zigzag pattern with different angles of inclination (10°, 15°, 20°, 25°, 30°, and 35°). Overall, the maximum power pump and annual AC energy performance increase by 1.4%, 4.2%, 6.8%, 10.8%, 14.9%, and 21.6%, respectively, over a one-year period of productivity. However, by applying the concept of solar panel efficiency degradation due to tilting solar panels at an angle by Mamun et al. (2022), for each 5° increase in tilt angle beyond the ideal 10°, the efficiency decreases by approximately 0.76%. In conclusion, the overall efficiency is greater than that of standard flat solar panels, provided the tilt angle is within a reasonable range.

This paper presents an advanced software tool for precise laser beam propagation analysis, focusing on the calculation of the M2 value, a key measure of beam quality. Developed in Python, the software integrates libraries like NumPy, Matplotlib, and SciPy for robust data handling and accurate polynomial fitting. It features a user-friendly interface for easy data input, analysis, and visualization, making it accessible to both professionals and novices. The tool has been rigorously validated against theoretical models (M2=1) and experimental data (showing M2=1.2548 and 1.3166), ensuring high accuracy and reliability. It visualizes beam width data and fitted polynomial curves, aiding in assessing beam propagation characteristics and optimizing laser systems. Future enhancements include additional beam quality metrics, machine learning integration, and cloud-based functionality. This tool significantly advances laser beam analysis, benefiting research and industrial applications by improving performance and efficiency. The software is available at DOI: 10.5281/zenodo.13325911

This comprehensive analysis aims to offer valuable insights into the safety profiles of these glucocorticoids, facilitating the identification of compounds with potentially reduced adverse effects. This study investigates the toxicity profiles of various glucocorticoids, utilizing predictions from the pKCSM Server. Among the glucocorticoids examined, Dexamethasone, Triamcinolone, Hydrocortisone hemisuccinate, Paramethasone, Fluprednisolone, and Flumethasone emerge as potentially less toxic, displaying favorable scores across diverse parameters such as Max. Tolerated Dose (human, MRT), Oral Rat Acute Toxicity (LD50), and Oral Rat Chronic Toxicity (LOAEL). Notably, Hydrocortisone hemisuccinate and Triamcinolone stand out for their high tolerability capacity based on the Max. Tolerated Dose (human, MRT), suggesting enhanced safety profiles. These findings contribute insights into selecting glucocorticoids with optimal safety and tolerability for potential therapeutic applications.Further research and clinical investigations are warranted to validate and refine these findings, ensuring the responsible and effective use of glucocorticoids in medical practice.

This paper presents the Aether Physics Model (APM), a novel theoretical framework that offers a unified description of the fundamental forces and weak interaction. The APM proposes a quantum Aether composed of discrete units, recognizes two distinct charge manifestations, and treats all charges as distributed. Using dimensional analysis and simple equations, the APM derives force equations that unify gravity, electromagnetism, and the strong forces and the weak interaction. The model makes specific predictions about force strengths, maximum mass density, and fine structure constants for protons and neutrons. These predictions align with existing observations and offer new avenues for experimental testing. The APM addresses the limitations of the Standard Model while providing a more intuitive explanation for phenomena like the quantum Hall effect and Casimir effect. If validated, the APM could revolutionize our understanding of space, matter, and fundamental forces.

Maxwell's energy-momentum tensor cannot be used as is in Einstein's equation for general relativity in the presence of sources. In this case, its four-divergence is non-zero, whereas the tensors in the equation must have this characteristic. However, the sun emits streams of ionized particles, gases are present within galaxies, material transfers in the form of ionized plasma can occur in binary star systems, and so on. These charges cannot be neglected in the study of space-time in these regions. Here, we present a modified version of this tensor that eliminates this flaw, provided that the potentials satisfy the Lorenz gauge. The distribution of sources will also be analyzed in light of fluid mechanics, allowing us to account for its influence in terms of generated pressure.

The recent mountain pine beetle outbreaks have caused widespread mortality among lodgepole pine trees in western North America, resulting in a reduced population of surviving trees. While previous studies have focused on the cascading impacts of these outbreaks on the physiology and growth of the surviving trees, there remains a need for a comprehensive study into the interactions among various physiological traits and the growth in post-outbreak stands. Specifically, the relationship between chemical (primarily terpenes) and anatomical (mainly resin ducts) defences, as well as the allocation of non-structural carbohydrates (NSCs) to support these defence modalities, is poorly understood. To address these gaps, we conducted a field survey of surviving lodgepole pine trees in post-mountain pine beetle outbreak stands in western Canada. Our retrospective analysis targeted to determine correlations between the post-outbreak concentrations of monoterpenes, diterpenes, and NSCs in the phloem, and the historical resin duct characteristics and growth traits before and after the outbreak. We detected strong correlations between post-outbreak concentrations of monoterpenes and historical resin duct characteristics, suggesting a possible link between these two defence modalities. Additionally, we found a positive relationship between NSCs and the total concentrations of monoterpenes and diterpenes, suggesting that NSCs likely influence the production of these terpenes in lodgepole pine. Furthermore, historical tree growth patterns showed strong positive correlations with many individual monoterpenes and diterpenes. Interestingly, while surviving trees had enhanced anatomical defences after the outbreak, their growth patterns did not vary before and after the outbreak conditions. The complexity of these relationships emphasizes the dynamics of post-outbreak stand dynamics and resource allocation in lodgepole pine forests, highlighting the need for further research. These findings contribute to a broader understanding of conifer defenses and their coordinated responses to forest insect outbreaks, with implications for forest management and conservation strategies.

HIGHLIGHTS Mach's principle is linked with inertia and the mass around. Nowadays, physicists believe its effect is infinitesimal, so Mach's principle is simply ignored. This paper looks at the consequence of applying Mach's principle. It could replace dark matter. ABSTRACT After seeing the history of Mach's principle, we will work out a new model of galaxies inspired by Mach’s principle, which is more satisfactory than current dark matter models. This new model is just maths and needs an explanation. One possible explanation is obviously that Mach's principle is at work in a galaxy.

Substance use disorder (SUD) is a global health crisis that is becoming increasingly prevalent among younger generations and impacting the overall health of millions of people worldwide. Traditional treatment methods, including cognitive-behavioral therapies and medicinal-assisted treatments, often face limitations such as inconsistent efficacies and varying degrees of accessibility. Thus, there is a clear need for a new and innovative treatment strategy. Music therapy has recently gained attention through research as a promising non-pharmacological supplement to strengthen conventional SUD treatment methods. This review explores the potential benefits of music therapy in reducing substance cravings, alleviating depressive symptoms, and improving emotional expression among patients in the rehabilitation phase of SUD recovery. We review evidence from various studies and clinical trials to evaluate the efficacy of music therapy in improving standard treatment outcomes, with the results indicating that music therapy could be an effective complement to traditional treatment methods while noting that its efficacy could vary depending on the individual and type of intervention provided. The benefits of music therapy include accessibility of treatment for diverse patient groups and the potential for highly individualized care, although more research is needed to compare the efficacies of specific music treatment types for certain conditions and patient populations. Further research is also needed to validate the neurobiological mechanisms of music therapy, as well as increased communication between music therapists worldwide to enforce consistency in treatment methods and share learnings in this growing field.

This communication is to summarize our single center experience on applications of anti-IL-1 biologic response modifiers on autoimmune and autoinflammatory conditions in children. We present our rationale for off-label utilization of Anakinra and discuss evolving treatment paradigms that warrants further research and validation. Based on our observations and successful treatment outcomes, we advocate future multilateral efforts to liberate access to anti-IL-1 medications to control inordinate and detrimental inflammation in children.

This paper systematically discusses the application of reinforcement learning in automatic driving system. Reinforcement learning frameworks show significant advantages in optimizing decision making, predictive perception, path planning, and controller design, exceeding the limitations of traditional supervised learning methods. The paper highlights the critical role of components such as scene understanding, positioning, and map making in autonomous driving systems, which provide reliable environmental awareness through deep learning and sensor fusion technologies to support intelligent decision-making in complex urban environments. In addition, the paper discusses innovative approaches to safety reinforcement learning to reduce risk in autonomous driving and ensure that systems adhere strictly to safety constraints while maximizing expected rewards. These findings provide an important theoretical and practical basis for further improving algorithm robustness, managing multi-agent interactions, and integrating ethical considerations in the future.

The distribution of zakat, which is still carried out directly through mosques or zakat amil bodies, can hinder the payment process due to inaccurate calculations and difficulties in finding zakat amil institutions. In the digital era, information technology is very important in the management of zakat, alms, and infaq. Therefore, a zakat information management system was created. The e-Zakat program, developed using the waterfall method, plays an important role in five main aspects of zakat management: muzaki and mustahiq data collection, zakat collection, zakat distribution, mustahiq development, and reporting. The use of information technology in this program is expected to increase efficiency, accountability, transparency, as well as the reach of zakat and muzaki involvement.

The deaf-mute and individuals with hearing disabilities who communicate through sign language should not be overlooked or excluded. It is a social responsibility to strive for an inclusive world without inequality. Advances in technology offer various solutions to address the communication gap, one of which is the use of computer-based sign language recognition systems. This project proposes a Malaysian Sign Language recognition model utilizing MobileNetV1, a convolutional neural network-based algorithm, to interpret sign language in real-time settings through a website application using Streamlit. The outcome of the model test shows that it has achieved a recognition rate of 96 percent. Although the proposed model has demonstrated the ability to recognize sign language, it is suggested that further improvement can be achieved by enhancing the quality and diversity of the dataset. The implementation of a more comprehensive dataset would lead to improved performance and increased accuracy of the model. This project underscores the importance of considering and accommodating the needs of the deaf-mute and individuals with hearing disabilities and highlights the potential of technology to bridge communication barriers and achieve a more inclusive society.

In this study, we utilized the UniProt database to extract breast cancer genes Total 2658 genes in Homo sapiens are obtain. Then 166 genes are taken and after delating duplicates 158 genes were remains. These genes were then analyzed for their biological pathways using Gene Ontology enrichment analysis through the Genecodis platform, resulting in the identification of 12 unique genes involved in disease pathways. Protein-protein interaction (PPI) network analysis was conducted using the STRING database and Cytoscape software, identifying ANLN,TREM1,LZTFL1,OXSM,PLA2G3,TAS2R13,ABCB10,ECT2,TRPC,BCAS3,PLA2G3,ZDHHC7 and ERBB2 as potential gene targets for breast cancer.

We solve the problem of Apollonius by applying the Lorentz transformation within the frame- work of special relativity to go to a frame of simultaneity, where the solutions are the circum- center. We transform back to get the solutions in a general frame. We show that the solutions in a general frame are the foci of the ellipse going through the centers of the given 3 circles.

Objective To investigate nailfold capillary parameters in community-dwelling individuals aged over 60 years who have hypertension and do not exercise regularly. Furthermore, the study examined the correlations between capillary function and other health-related indicators. Design A single- center pilot trial Setting Faculty of Health, Tsukuba University of Technology, Japan Participants hypertensive community-dwelling elderly people Intervention Microcirculation was observed before and 1 min after arm-curl exercise by means microscopy of capillary with non-exercised limb. Additionally, we examined other health-related indicators. Outcome measures: Acute effects of reperfusion on nailfold density, flow, and diameters. Secondary outcomes included the correlations between microvascular parameters and other health-related indicators. We hypothesized that brief exercise could enhance microcirculation reperfusion and correlate with other health-related parameters.　 Results: There were 20 participants with a mean (SD) age of 67.1 (5.8) years. The capillary flow rate changed from 2.3±6.7 to 2.7±0.2 log µm/s (P

In genetic conflicts, driver and killer elements achieve biased survival, replication, or transmission over sensitive and targeted elements through a wide range of molecular mechanisms, including mimicry. Driving mechanisms manifest at all organismal levels, from the biased propagation of individual genes, as demonstrated by transposable elements, to the biased transmission of genomes, as illustrated by viruses, to the biased transmission of cell lineages, as in cancer. Targeted genomes are vulnerable to molecular mimicry through the conserved motifs they use for their own signaling and regulation. Mimicking these motifs enables a selfish element to control core target processes, and can occur at the sequence, structure, or functional level. Molecular mimicry was first appreciated as an important phenomenon more than twenty years ago. Modern genomics technologies, databases, and machine learning approaches offer tremendous potential to study the distribution of molecular mimicry across genetic conflicts in nature. Here, we explore the theoretical expectations for molecular mimicry between conflicting genomes, the trends in molecular mimicry mechanisms across known genetic conflicts, and outline how new examples can be gleaned from population genomic datasets. We discuss how mimics involving short sequence-based motifs or gene duplications can evolve convergently from new mutations. Whereas, processes that involve divergent domains or fully-folded structures occur among genomes by horizontal gene transfer. These trends are largely based on a small number of organisms and should be reevaluated in a general, phylogenetically independent framework. Currently, publicly available databases can be mined for genotypes driving non-mendelian inheritance patterns, epistatic interactions, and convergent protein structures. A subset of these conflicting elements may be molecular mimics. We propose approaches for detecting genetic conflict and molecular mimicry from these datasets.

Understanding clinical significance of variants of unknown significance (VUS) reported in next-generation sequencing (NGS) has become essential in cancer treatment. Our study examined six widely used in silico tools: PolyPhen-2, Align-GVGD, MutationTaster2, CADD, REVEL, and Chat-GPT. We utilized a dataset of gene variants known to potentially affect immune therapy. No single tool could comprehensively determine mutation variant pathogenicity. MutationTaster2021 showed the highest overall accuracy and MCC among the tools. Notably, REVEL and Chat-GPT exhibited 100% specificity, suggesting their proficiency in accurately identifying pathogenic variants and minimizing false positives. In contrast, CADD displayed optimal sensitivity, making it suitable for effectively ruling out benign variants.

Based on recent progress in cosmological thermodynamics, we present a new thermody- namic formulation of the Friedmann equations in the new Haug-Tatum cosmology model, as well as for other similar models put forward in the literature from different solutions to Einstein’s field equation. Since the CMB temperature has been measured much more accu- rately than the Hubble constant, we demonstrate that our thermodynamic formulation of the Friedmann equation dramatically narrows the acceptable range for the critical density of the universe. Furthermore, we show how our thermodynamic formulation leads to a more precise cosmological constant estimate.

In many countries, increasing concern for animal welfare is driving retailer commitments and government legislation that aim to improve the lives of farmed fish. One aspect of fish welfare involves stunning fish prior to slaughter. The feasibility of stunning depends on the species of fish and physical farm characteristics. In this article, we provide an overview of stunning before slaughter in European sea bass and sea bream aquaculture, one of the largest finfish farming industries in the developed world that does not yet stun most of its production. Sea bass and sea bream stunning necessitates the use of electrical stunning equipment aboard harvest vessels, often a significant distance from the shoreline; this presents an interesting engineering and policy challenge. Together, Türkiye, Greece, Spain, and Italy produced over 400,000 t of sea bass and sea bream in 2020. In Türkiye and Greece, farms are numerous and located very close to the shoreline. In Spain and Italy, farms are few and located far from the shoreline. The highest average production is found in farms from Türkiye (1,000 t) and Spain (1,300 t, and lower average production is found in Greece (300 t) and Italy (350 t). Producer progress towards the installation of electrical stunning appears comparatively well-developed for Türkiye, Spain, and Greece, though we emphasise that producers and other stakeholders require continued support to realise this opportunity. Producers in Italy appear slower to make progress on this aspect of animal welfare and may require additional support.

The Casimir effect can either work over very short distances or at very low temperatures. At the cosmic scale, we naturally deal with long distances, but at the same time, we encounter extraordinarily low temperatures, namely the CMB (Cosmic Microwave Background) tem- perature. Recently, there has been increased interest in the Casimir effect and its implications in cosmology. Here, we briefly demonstrate that the luminosity and radiation pressure of the CMB is mathematical identical to a theoretical Casimir effect within the Hubble sphere, or actually our solution seems to be valid for any Schwarzschild black hole. The Casimir effect forevery Schwarzschild black hole is identical. This also include the Hubble sphere if we treat it as a Schwarzschild black hole that is related to increased interest in black hole cosmology.

Caused by age or trauma, collapsed connective tissue can cause nerve entrapment and damage within the tarsal tunnel. Tarsal tunnel syndrome is relatively underdiagnosed. This study presents an intervention targeting damaged tissues surrounding the nerves and replacing the structural cushioning with a Wharton’s jelly tissue allograft. The eight selected patients from four clinical sites had tarsal tunnel-related defects. Patient outcomes were tracked on a 90-day calendar utilizing the Numeric Pain Rating Scale (NPRS) and the Western Ontario and McMaster University Arthritis Index (WOMAC). All patients had failed standard care practices for at least six weeks. Each patient received a Wharton’s jelly tissue allograft to sites around the affected tarsal tunnel. No patients experienced adverse reactions. Percent change calculated from the initial application to the 90-day follow-up showed an improvement of 59.43% in NPRS and a 37.58% improvement in WOMAC. This study provides evidence that WJ allograft applications are safe, minimally invasive, and efficacious for patients who have failed standard care treatments for tissue defects associated with Tarsal Tunnel syndrome. Limitations include the small cohort size and nonblinded nature. The results of this study warrant further research to confirm the efficacy, optimal dose, protocol, and durability of Wharton's jelly.

The hyperspectral vegetation index was defined based on the distinctive features of the spectral curve. In alignment with the growth and development characteristics of cotton, the spectral reflectivity of the cotton canopy was computed at different growth stages. The aim of this study was to clarify the association between cotton yield and canopy spectral indices and to develop yield estimation models utilizing hyperspectral imaging. The ASD Field Spec Pro VNIR 2500 spectrometer radiometer was employed to collect spectral reflectance data from cotton canopies at various growth stages. Using spectral analysis techniques, quantitative models were developed based on hyper-spectral vegetation indices, including Normalized Difference Vegetation Index (NDVI) (NDVI) and Radar Vegetation Index (RVI) to extract characteristic information from the cotton canopies. Following thorough testing and precise monitoring of the estimation models, the most optimal models representing cotton canopy structure parameters were identified. Results demonstrate that the power function model, relying on NDVI, provides the most accurate forecasting for Leaf Area Index (LAI)). Additionally, the exponential function model based on RVI proves to be the most effective for predicting cotton unit area above-ground fresh biomass, while another exponential function model based on RVI is identified as the best for predicting cotton unit area above-ground fresh biomass. Clearly, the application of hyper-spectral remote sensing technology enables the analysis, simulation, assessment, and providing scientific basis for precision cotton planting and cotton field management strategies.

The dermatological manifestations of Long Covid (LC) have languished in the shadows of chronic fatigue and brain fog. Yet they are all linked by gut dysbiosis and the cytokine triad of TNF-α, IL-1β, and IL-6. The gut microbiome common not only to LC, psoriasis, AA, and vitiligo but also to neurodegenerative disease has been recently described. This gut microbiome induces an altered tryptophan metabolism linked to autoimmune disease. SARS CoV2 invades enterochromaffin cells rich in ACE2 receptors and curtails absorption of the essential amino acid tryptophan and subsequent synthesis of serotonin and melatonin. This review suggests that an etiologic prebiotic (d-mannose)/probiotic (lactobacilli, bifidobacteria)/postbiotic (butyrate) approach to autoimmune skin disease that improves intestinal barrier integrity and that suppresses the triad of TNF-α, IL-6, and IL-1β may enhance or even eliminate the traditional immunotherapy of targeted monoclonal antibodies, Janus kinase inhibitors, and steroids. Health benefits of this approach extend well beyond suppression of autoimmune skin disease.

Upon the outbreak of the COVID-19, countries worldwide developed policies with the goal to introduce restrictive measures geared towards mitigating the spread of the virus. Although these health initiatives were put in place through top-down public directives, they relied heavily on the cooperation of citizens who had to be willing to carry them out. As a consequence, we could observe differences in compliance with governmental restrictions within and between countries. Increasing policy stringency was the method adopted overall to promote people’s compliance. This article used survey data from 10308 participants in Brazil to examine whether there was a positive correlation between policy stringency and compliance with restrictive measures to reduce the spread of COVID-19. The results revealed, however, that there was no direct influence of policy stringency on people’s health behaviors. Accordingly, I hypothesized that individual differences in personality traits were one of the drivers behind policy compliance, as they would support self-interests such as the duty to support authorities as well as the perceived health risks of certain behaviors and ultimately motivate compliance. The findings’ implications for both compliance research and for authorities wanting to nurture voluntary compliance with public health orders are discussed and suggestions are provided.

This work introduces a novel facial image capture system that utilizes computer vision technology and artificial intelligence for real-time detecting, tracking, and capturing of human faces. The objective of this study is to address the challenges posed by poor-quality facial images in biometric authentication, especially in passport photo acquisition and recognition. By combining face-aware capture technology with AES encryption for secure image storage, we present a completely open-source hardware solution that consists of a Jetson processor, a 16MP autofocus RGB camera, a custom enclosure, and a touch sensor LCD for user interaction. Pilot data collection demonstrates the system's ability to capture high-quality images, achieving a 98.98% accuracy in storing images of acceptable quality. The integration of AES encryption ensures data security, making the proposed system suitable for real-time applications in other domains beyond identity verification in passport applications, such as security systems, video conferencing, etc

Albert Einstein, shortly after publishing his General Relativity Theory (GRT) applied it to the entire universe in a paper of 1917. Einstein assumed that such a universe was static in time and possessed a uniform distribution of matter on the largest scales, obtaining a static and finite universe of spherical spatial curvature of radius R. Although this model was refuted by Edwin Hubble's discovery of the expansion of the universe, it is still often studied as a theoretical framework for some problems, such as the twin paradox. This paper will show that Einstein's static universe model leads to a privileged frame of reference, so that any observer moving at the speed v will be able to measure speeds of light other than c depending on the direction of beam transmission. The above will refute the validity of the application to this closed and static universe of the Special Relativity Theory (SRT) proposed by Einstein in 1905 in his article . In addition, a new synchronization convention and new coordinate transformations will be deduced, the "generic" transformations, which will replace those of Lorentz. Finally, the twin paradox in this universe will be solved by making use of them.

Exosomes, a subset of extracellular vesicles, have emerged as pivotal mediators of intercellular communication, revolutionizing our comprehension of cellular interactions. Their diverse cargo, comprising proteins, nucleic acids, and bioactive molecules, plays a crucial role in various physiological and pathological processes. In the intricate landscape of adult neurogenesis, exosomes wield significant influence, actively participating in the generation of new neurons within the adult mammalian brain. Originating predominantly from non-niche cells, these vesicles contribute substantially to the regulation of neuroinflammation, thereby impacting neurogenesis and offering therapeutic promise for neurological disorders. In the specific context of Parkinson's disease (PD), exosomes assume a multifaceted role, prominently implicated in the propagation of α-synuclein oligomers and the orchestration of neuroinflammation. Stem cell-derived exosomes present themselves as promising therapeutic agents, capable of reshaping the microenvironment, repairing neuronal damage, and mitigating apoptosis. The ongoing exploration of exosomes continues to unravel intricate biological processes, paving the way for innovative medical interventions and treatments, particularly within the challenging landscape of neurodegenerative diseases such as PD. The comprehensive understanding of exosomal functions holds the potential to advance our therapeutic approaches, offering new avenues for intervention and treatment strategies in the realm of neurodegenerative disorders.

Among the number of hurdles that the vaccines based in modRNA platforms have been facing, there is now another critical one: immune imprinting which decreases even more the effectiveness of the modRNA Covid vaccines.

The initiation of micro-cracks in concrete is primarily due to its brittleness, which causes severe impacts on the overall behavior of the concrete. However, incorporating fibers in concrete could significantly improve its mechanical properties. The current study demonstrates the influence of two types of fibers on the mechanical properties of concrete. Nylon Fiber Threads (NFT) and Nylon Fiber Strands (NFS) at a fiber content of 2.5 kg/m³ were incorporated in the concrete mix. Concrete with a compressive strength of 30 MPa and a water-cement ratio of 0.4 was produced to investigate the fresh and mechanical properties of conventional and nylon-fiber reinforced concrete (NFRC). The concrete prims and cylinders were tested for compressive, splitting, and flexural strength using ASTM standards (ASTM C-39, C-496, and D-790, respectively). It was found that NFT-reinforced samples achieved higher mechanical properties of concrete (13.05%) compared to NFS-reinforced samples. Test results showed that incorporation of nylon fibers (NF) in concrete decreased the compressive strength of cylindrical and cubical specimens by 0–10% and 5–15%, respectively. However, it increased the splitting tensile and flexural strengths by 0-15%, and 5-15% respectively. Furthermore, the incorporation of NF in concrete significantly improved the ductility and delayed the crack initiation in concrete.

The Power Theory of Exchange and Money (PTEM) refines the economic neoclassical two-equation model of exchange. PTEM replaces the statistical average condition of exchange, which represents the equality of supply and demand for all transactions in the market, with a more specific equation of the equality of the generalized power of the parties in relation to their objects of exchange. The purpose of the article is to show the application of PTEM for the study of various social phenomena. Along with a brief summary of the main statements of this theory, its integration into the existing corpus of theories and ideas in economics and sociology is considered. The conclusions of power theory are then applied to consider the following topics: the objective motivation of exchange by the desire to increase power, the power nature of market equilibrium, the power nature of money, the accumulation of power through profit, the creation of money as a power act, the role of the state in the creation of money, the measure of power as a possible tool for social and political research.

In the domain of financial trading, where accuracy and swift response to data discrep- ancies are paramount for maintaining clienttrust, our research paper delves into the development of a real-time alert system utilizing SpringBoot, a framework renowned for its robustness and adaptability in enterprise applications. We embark on a comprehensive journey, beginning with addressing thefoundational challenges inherent in monitoring trade inquiries - the necessity for real-time processing, unwavering data accuracy,and ensuring unwavering system reliability. The study then methodically transitions to the architectural design, where we explore howSpringBoot’s capabilities are optimally utilized to meet these challenges. Following this, we delve into the im- -plementationphase, detailing the strategic selection of compatible technologies and methods for effective data management and discrepancydetection. The paper culminates in a thorough evalu- ation of the system, where we assess performance across various operationalscenarios, scrutinize the accuracy of the discrepancy detection mechanisms, and integrate real-world feedback from users in thetrading sector. This holistic approach not only highlights the versatility and efficiency of SpringBoot in creating reliable alert systems in the high-stakes world of financial trading but also serves as a detailed guide for similar endeavors in this field

Community-Based Disaster Risk Reduction (CBDRR) plays a vital role in strengthening the resilience of local communities against both natural and human-made disasters. This paper seeks to examine the role of CBDRR in enhancing the resilience of local communities to both natural and man-made disasters. It underscores the critical importance of active community involvement across all stages of disaster management, from preparedness and mitigation to response and recovery. The paper also explores the key factors that contribute to the successful implementation of CBDRR, including institutional backing, capacity development, inclusive strategies, and the use of modern technologies. Additionally, it discusses the challenges and opportunities in building strong partnerships between local communities and external stakeholders, which are crucial for ensuring the sustainability of these efforts. Finally, the paper offers recommendations aimed at improving the effectiveness of CBDRR initiatives, drawing on insights gained from past disaster experiences. The findings of this study point to the importance of continuous monitoring and evaluation of CBDRR programs to maintain their relevance and ensure their effectiveness as risks evolve. Incorporating lessons learned from past disasters into future planning also plays a crucial role in helping communities enhance their resilience over time. Ultimately, by encouraging collaboration between communities, governments, and various organizations, CBDRR lays the foundation for a comprehensive disaster management framework that is equipped to meet future challenges and supports long-term sustainable development.

Access to urban green and blue spaces (UGBS) has been associated with positive effects on health and wellbeing; however, the past decades have seen a decline in quality and user satisfaction with UGBS. This reflects the mounting challenges that many UK cities face in providing appropriate public facilities alongside issues such as health inequalities, an ageing population, climate change, and loss of biodiversity. At present, little is known about the preferences of different population subgroups and, specifically, the UGBS they visit and the spaces they avoid. Using a public participatory geographic information system (PPGIS), the overall aim of the research presented here was to investigate the preferences of different population subgroups in urban areas, and the UGBS they visit, using Edinburgh, Scotland as a case study. We created a baseline visitor demographic profile for UGBS use, and highlighted how visitors perceive, physically access, use, and engage with UGBS. The results revealed considerable variation in UGBS preference: one person’s favourite UGBS may be one that someone else dislikes and avoids. It is clear that adapting UGBS to suit local communities should not be a ‘one-size-fits-all’ approach. The conflicting views and preferences of different groups of respondents point to the importance of developing policies and park management plans that can accommodate a variety of uses and experiential qualities within individual parks. PPGIS offers an ideal tool for achieving this

This review paper delves into the multifaceted aspects of pineapple cultivation, focusing on morphology studies, harvesting challenges, and mechanization efforts. Pineapple, renowned for its commercial value and unique flavor, holds a prominent position in global agriculture, with India alone producing 19.64 lakh tonnes annually. However, the hilly terrains of regions like northeastern India pose significant hurdles to traditional harvesting methods, necessitating innovative solutions. Understanding the morphology of pineapple plants is crucial for optimizing cultivation practices and designing efficient harvesting equipment. Insights from various studies shed light on leaf structure, fruit maturity, and growth patterns, providing valuable information for engineering tailored solutions. Mechanization endeavors, including semi-mechanized harvesting machines and semi-manual harvesters, demonstrate promising results in improving efficiency and reducing labor-intensive practices. Despite challenges such as increased crop losses and operational costs, continued research and development in mechanization hold the key to sustainable pineapple cultivation. This paper underscores the importance of integrating morphology studies and mechanization efforts to address the unique challenges faced by pineapple farmers, particularly in hilly terrains, and highlights the need for ongoing innovation to ensure the long-term sustainability of pineapple cultivation.

Multisensory spaces have been used across a number of health and social care contexts to promote well-being, engage the senses and promote inclusion by providing places where people can come together. Much of the existing research on such spaces focus on children or older adults with little investigation dedicated to spaces inclusive of both. Utilising multisensory spaces which bring together children and older adults can reduce costs and lead to opportunities for shared learning. We sought to identify empirical research which investigated the use of multisensory spaces for intergenerational participants. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines were used to guide this review. Five electronic databases (PsycINFO, CINAHL, Web of Science, Embase, Pubmed) were interrogated using search terms developed in collaboration with a specialist subject librarian around the concepts of ‘intergenerational’ and ‘multisensory’. Two authors independently applied the agreed upon eligibility criteria to the titles and abstracts of potential articles for inclusion. Once the final articles had been identified, the authors independently extracted data and assessed quality of the included studies. Data were subjected to narrative synthesis. Following review of 979 titles and abstracts, 3 articles were identified for inclusion. Quality appraisal rated these as between 3 to 6 out of a possible total of 7. Narrative synthesis identified three themes named as Independence, Connecting with others and Equitable multisensory space design. Multisensory spaces offer the potential to deliver care within health and social care contexts which caters to the needs of children and older adults. There is a need to co-create such spaces with service users and other stakeholders to ensure they adequately meet the needs of all.

Plant-microbe interactions are pivotal in a plant's growth and development. Mycor-rhizal fungi, in particular, play a crucial role in maintaining sustainable agroecosys-tems through symbiotic relationships with plant roots, improving soil health, facili-tating nutrient uptake, and enhancing plant stress resilience. Arbuscular mycorrhizal (AM) fungi enhance plant growth by increasing the absorption of essential nutrients, particularly phosphorus, nitrogen, potassium, zinc, and copper. The mutualistic rela-tionship between AM fungi and plants promotes a balanced microbial community and improves soil structure by forming stable soil aggregates. Additionally, mycorrhizal fungi increase plant tolerance to abiotic stresses, including drought, salinity, and heavy metal toxicity, by regulating osmotic balance, producing antioxidants, and altering exudatemorphology. It also negate harmful effects of high soil phosphorus levels and bolster plant resilience to environmental stresses. Beneficial microorganisms, such as potassium-solubilizing microbes and nitrogen-transforming bacteria, further enhance the functionality of mycorrhizal associations. Furthermore, mycorrhizal fungi con-tribute to plant health by reducing the incidence of root pathogens and soilborne dis-eases. However, the sustainability of mycorrhizal fungi is threatened by intensive agricultural practices, including heavy tillage, continuous monoculture, and excessive use of chemical fertilizers and pesticides. These practices disrupt hyphal networks and reduce microbial diversity, compromising mycorrhizal functionality. Alternatively, sustainable farming practices such as reduced tillage, crop rotation, and organic amendments are recommended to support healthy mycorrhizal populations. By adopting these practices, we can achieve long-term agricultural productivity while maintaining a healthy soil environment.

Kiwifruit Vine Decline Syndrome (KVDS) has recently become a concern in Italy, impacting plant health and production. This study aims to investigate the influence of KVDS on soil health indi-cators and the composition of soil microbial communities by comparing symptomatic and asymptomatic kiwifruit orchards located in two areas in Latium, Italy. Soil samples were collected in spring and autumn to evaluate the seasonal variations in soil physicochemical properties, enzyme activities, and microbial biomass. The results revealed that KVDS impacted soil properties such as pH, electrical conductivity, and water-soluble carbon and nitrogen contents, though these effects varied by orchard and season. Moreover, KVDS significantly affected soil enzyme activities and microbial biomass assessed through PLFAs analysis, particularly showing an increase in fungal biomass in symptomatic areas. In addition, metabarcoding revealed differences in the microbial communities between symptomatic and asymptomatic soils, with notable shifts in their diversity and relative abundance. Our findings highlight the complex interactions between plant-soil-microbiome in KVDS, suggesting that KVDS is multifactorial and is likely associated with an imbalance of soil microbial communities at the rhizosphere level, which can negatively affect soil health.

Health and social needs exist along a dynamic continuum. Recognizing that health status is inextricably impacted by social determinants of health, community paramedicine has opportunities and a responsibility to reduce inequities. The objective of this scoping review was to investigate peer-reviewed and grey literature to explore how community paramedicine supports community needs along a health and social continuum. We conducted a scoping review of English language literature using the JBI Scoping Review methodology. We searched CINAHL, EMBASE, MEDLINE, Google Scholar, and organisational websites. 30 peer-reviewed and 13 grey literature articles met inclusion criteria. The findings describe the ways community paramedicine models evolved from minimising system pressures on emergency health services to addressing health and social needs. A key recommendation across the literature was the need to meaningfully engage communities early in program development to understand how best to implement and co-design integrated service models addressing specific community needs, though there was a lack of evidence to guide this approach. There is a notable lack of evidence pertaining to optimising technologies in program design and implementation. Results highlight opportunities to determine best practices for conducting holistic community needs assessments that include equitable stakeholder engagement and enhancing education to prepare paramedics for expanded roles. Community paramedicine provides opportunities to better meet the needs of structurally marginalised communities. There is a social responsibility and opportunity to engage communities to co-design service delivery, advance paramedic education, and enhance interprofessional collaboration to better support community needs and generate upstream solutions for individuals and communities

Iron is a critical yet limited nutrient for microbial growth. To scavenge iron, most microbes produce siderophores—diverse small molecules with high iron affinities. Different siderophores are specifically recognized and uptaken by corresponding recognizers, enabling targeted interventions and intriguing cheater-producer dynamics. We propose constructing a comprehensive iron interaction network, or "iron-net," across the microbial world. Such a network offers the potential for precise manipulation of the microbiota, with conceivable applications in medicine, agriculture, and industry, as well as advancing microbial ecology and evolution theories. Previously, our successful construction of an iron-net in the Pseudomonas genus demonstrated the feasibility of co-evolution-inspired digital siderophore typing. Enhanced by machine learning techniques and expanding sequencing data, forging such an iron-net calls for multidisciplinary collaborations, and holds significant promise in addressing critical challenges in microbial communities.

Depression is one of the most prevalent mental disorders worldwide. This study examined the effect of a spiritual connectivity intervention on individuals with depression in a randomized waitlist control trial. Fifty-seven participants with mild or moderate depressive symptoms were randomly assigned to either the intervention group (n=28) or the waitlist control group (n=29). The intervention comprised eight weekly sessions focusing on divine connection, forgiveness and freedom, suffering and transcendence, hope, gratitude, and relapse prevention. The outcome measures included depressive symptoms, anxiety, hope, meaning in life, self-esteem, and social support. Participants completed self-administered questionnaires at baseline (week 0), post-intervention (week 8), and at a 3-month follow-up (week 20). Repeated-measures ANOVA and one-way ANCOVA were used to compare the within-group and between-group differences in the changes in outcome variables. Participants in the intervention group showed significant improvements in depression, anxiety, spiritual experience, hope, self-esteem, and perceived social support after the intervention. Effect size statistics showed small to large differences (Cohen’s d, 0.308 to -1.452). Moreover, 85.71% of participants in the intervention group also experienced clinically significant reductions in PHQ-9 scores from baseline to immediate post-intervention. This study highlights the effectiveness of a low-cost, accessible intervention suitable for community implementation by clergy and faith-based organizations.

Coronavirus disease-19 (COVID-19) has disproportionately affected certain demographics in England, exacerbating existing health disparities. Effective therapeutics are a critical line of defence against COVID-19, particularly for patients at elevated risk for severe disease. Surveillance systems were established to monitor usage of COVID-19 therapeutics in hospital and community settings and inform stewardship. Three antiviral therapies: nirmatrelvir plus ritonavir (Paxlovid®), remdesivir (Veklury®), and molnupiravir (Lagevrio®); and two neutralising monoclonal antibody therapies (nMAbs): sotrovimab (Xevudy®) and casirivimab with imdevimab (Ronapreve®); were in use in England between July 2020 to April 2023. This paper aims to illuminate trends in the utilisation of COVID-19 therapeutics treatment in both hospital and community settings, stratified by the Index of Multiple Deprivation (IMD) in England. Chapter 3 of the English Surveillance Programme for Antimicrobial Utilisation and Resistance (ESPAUR) report 2022 to 2023 also discusses the epidemiological surveillance of these five directly-acting antiviral COVID-19 therapeutics use in England between 2022 to 2023.

: Soil free living nematodes community composition was compared for five agro-management systems in a basaltic soil. The sites differed in their long-term management system and were designated as organic farming (OM), conventional (MI), natural pasture (NP), foliage farming (FF) and open field (OF). The effect of five diverse land use types in vineyard growth in basaltic soils on soil free living nematodes, density, diversity, and functionality in the plant rhizosphere was examined. We found 22 families, 42 genera of which only 14 genera were present in all soil samples, three bacteria feeders, 4 fungi feeders, 3 omnivores-predators and 4 plant parasites, in the soil collected from the five sampling sites. The organic and conventional managements were found to influence soil free living nematode community and its trophic composition. The higher abundance of bacteria feeders included the Cephalobidae and Panagrolaimidae families. The fungi feeders included the Anguinidae and Aphelenchidae families. Ominvores-predators included the Aprocelaimidae and Qudsianematidae, and the plant parasites included the Anguinidae (genus Anguina), Nothotylenchidae and Tylenchidae families. The changes in plant parasite nematodes were one of the main pests in the below-ground rhizosphere biome. Promoting the bacterial community could be a beneficial and promising way for a considerable increase in organic management.

(1) Background: As part of the Scottish Governments five-year recovery plan to address the backlog in NHS care following the COVID-19 pandemic, community pharmacies in Scotland are planned to provide a Hospital Discharge Medicines Supply and Medicines Reconciliation Service. We aimed to qualitatively explore patients’ experience of this new service; (2) Method: Adult patients (≥18yrs age) who consented to participate in the Community Pharmacy Hospital Dis-charge and Medicines Reconciliation Service were invited for interview within 21 days of dis-charge from hospital. Qualitative, one-to-one, semi-structured, patient interviews were conducted by telephone and audio-recorded using Microsoft Teams®. The interview audio recordings were transcribed verbatim and underwent thematic analysis; (3) Results: 12 patients were inter-viewed, evenly split by sex and with a median age of 62 years (range; 36 to 88 years). Analysis generated main five themes; Patient Engagement, Stakeholder Communication, Practical Factors, Human Factors, and Comparative Experiences. Many of these were interdependent; (4) Con-clusions: Patients appreciated that the service ensured a quicker discharge from hospital. Good stakeholder communication, practical factors (including choice, location, and the realities of ob-taining their medication from the community pharmacy), and a pre-existing and trusted rela-tionship in their usual community pharmacy were the key factors that regulated the patient ex-perience. In the main, patients were positive about the introduction of this new service. However, a lack of previous relationship or trust with a community pharmacy, and previous experiences with medication supply problems were factors which had the potential to negatively impact on patient experiences.

Background: Maternal mortality remains dire in Nigeria, claiming 40,000 lives yearly due to pregnancy complications. Factors like limited healthcare access, poverty, and early marriage worsen the crisis. Despite efforts to improve skilled birth attendance, Nigeria struggles to meet MDG targets, underscoring the urgent need for more effective interventions. Objectives: The objective of the study is to assess and understand the knowledge of community members regarding the risk factors influencing maternal mortality in the Ede South Local Government Area of Osun State, Nigeria. Methodology: A descriptive cross-sectional study was conducted. The study methodology involves employing the Leslie Kish formula to select 185 participants from the Ede South Local Government Area in Osun State, Nigeria. The selection process involved the use of a systematic sampling technique to ensure a representative sample based on population demographics and characteristics, ensuring a balanced and accurate selection process. Quantitative data was collected through a self-administered questionnaire and analysed using SPSS version 21. Results: The study encompassed 185 participants. 64.9% females with a mean age of 27.3 + 8.3 years. Among them, 60.5% were single, 46.6% being students, 55.7% held a BSc degree, 64.9% were Yoruba and 61.1% identified as Christian. 91.4% were aware about maternal mortality, 74.6% recognized maternal deaths in reproductive-aged women. Participants identified that maternal deaths mostly occur during labour (91.4%). Direct causes, such as bleeding (88.1%), unsafe abortion (88.6%), infection (49.2%), and hypertension (64.9%), were recognized. Results indicated substantial awareness concerning specific risk factors: lack of education (98.9%), poverty (91.6%), poor health care services in facilities (94.0%), alcohol consumption (87.6%) and poor transportation (78.4%). Conclusion: Findings revealed good awareness of maternal deaths and critical factors such as ANC impact and direct causes of maternal mortality like bleeding and unsafe abortion. However, gaps persisted in SDG awareness, suggesting the need for targeted interventions to enhance overall understanding and address identified knowledge gaps.

Public health is an important aspect of community activities, making research on health necessary because it is a crucial field in maintaining and improving the quality of life in society as a whole. Research in public health allows for a deeper understanding of the health problems faced by a population, including disease prevalence, risk factors and other determinants of health. This work aims to explore the potential of hospital patient data analysis as a valuable tool for understanding community implications and deriving insights for effective community health interventions. The study recognises the significance of harnessing the vast amount of data generated within hospital settings to inform population-level health strategies. The methodology employed in this study involves the collection and analysis of deidentified patient data from a representative sample of a hospital in Indonesia. Various data analysis techniques, such as statistical modelling, data mining and machine learning algorithms, are utilised to identify patterns, trends and associations within the data. A program written in Python is used to analyse patient data in a hospital for five years from 2018 to 2022. These findings are then interpreted within the context of public health implications, considering factors such as disease prevalence, socioeconomic determinants and healthcare utilisation patterns. The results of the data analysis provide valuable insights into the public health implications of hospital patient data. The research also covers prediction for the patient data to the hospital based on disease, age and geographical residence. The research prediction shows that in 2023, the number of patients was not considerably affected, but in in March to April 2024, the number significantly increased to 10,000 patients. These recommendations encompass targeted prevention strategies, improved healthcare delivery models and community engagement initiatives. The research emphasises the importance of collaboration between healthcare providers, policymakers and community stakeholders in implementing and evaluating these interventions.

Pluvial flooding (PF), triggered by intense short-duration rainfall events, poses a growing challenge in urban areas due to climate change and rapid urbanization. To mitigate the risk, it is imperative to identify flood-prone areas and implement mitigation strategies collaboratively with the public. This study aims to create a GIS-MCDA model of PF susceptibility zones based on topographical, environmental, and hydrological criteria and investigate the public perception of risk in Gospić. The survey included 5% of the city population (N=64), and data were obtained via face-to-face interviews. Five factors were examined: (F1) risk awareness, (F2) anthropogenic and (F3) natural causes of PF, (F4) potential consequences, and (F5) preparedness. All factors have moderate mean values, i.e., awareness, causes of PF, expectations of consequences, and preparedness is moderate. The reliability of questionnaire is very high (&gt; 0.71). The PF susceptibility zones were derived with an accuracy of 76%. The most susceptible zone covers 10% of the city, including agricultural land, forests, meadows, and residential properties. Of all respondents, 36% live in the most flood-prone area. In conclusion, mitigation measures for decision-makers were proposed. Results from this research can be a starting point for further research in Croatia and guidelines for decision-makers in implementing a risk mitigation strategy.

In this paper, the main physicochemical characteristics and evolutionary laws of microbial community structure during the fermentation of aged vinegar were discussed, and the correlation between Cuqu and microorganisms and physicochemical characteristics during fermentation was explored. The results showed that there are significant differences in genera at different stages of fermentation, the main dominant bacteria in R1 are Bacillus, Lactobacillus, Aspergillus and Issatchenkia. At R2 fermentation stage, Lactobacillus, Acetobacter and Saccharomyces showed an upward trend and finally became absolute advantage bacteria. The main genus of bacteria at the end of overall fermentation is Aspergillus. Correlation analysis shows that in Cuqu, the bacterial genera that are significantly positively and negatively correlated with reducing sugars and amino acid nitrogen are the same, while the bacterial genera that are significantly positively and negatively correlated with pH and saccharification power are the same. During the fermentation process, pH, reducing sugar and saccharification ability are mainly positively correlated with bacterial genera. And research has found that during the fermentation process, the overall correlation between fungal communities and physicochemical characteristics is weaker compared to bacteria.

Background: Community acquired Acinetobacter pneumonia (CAAP) typically presents with rapid progression to fulminant disease, and is complicated by high mortality. Australian epidemiological studies are few. Methods: We conducted a retrospective study on bacteraemic cases of CAAP over twenty years, (2000-2019) in North Queensland. Cases were selected on microbiologic, clinical, and radiographic parameters. Data on patient demographics were obtained, along with microbial, antibiotic, mortality, and climatic data. Results: 28 cases of CAAP were included. Nineteen (67.9%) were male, twenty-three (82.1%) were Indigenous Australians, and mean age was 45.9 years. Most presentations were of moderate to severe pneumonia, 25/28 (89.3%). 90% of cases had two or more risk factors. The strongest risk factors for CAAP were alcohol excess and tobacco use. No statistically significant difference in presenting severity, ICU admission or mortality was seen between dry and wet season disease. Dry season disease accounted for 35.7% of cases. Overall mortality was 28.6%. Early use of meropenem or gentamicin reduced mortality irrespective of presenting severity (mortality 17.6%) Non-targeted antibiotic therapy was associated with a non-significant difference in mortality of 44.4%. Conclusions: Early administration of targeted antibiotics can mitigate a high mortality rate. Choice of antibiotic therapy for community acquired pneumonia should be based upon severity, risk factors and clinical suspicion of CAAP rather than seasonality.

Agro-ecotourism is a tourism development activity in a location with ecological and agricultural advantages, leading to business utilization to generate economic value. Agro-ecotourism in West Java has a selling point in the form of natural potential, agriculture, arts, handicrafts, to the traditional culinary processing typical of the village. This research aims to analyze the sustainability level and the sensitive factors or attributes that affect the level of sustainability of community-based agro-ecotourism in West Java. The study used a survey method on 237 agritourist actors. Data were analyzed using Multi-Dimensional Scaling in the Rapid Appraisal-Tourism technique. The study results show that community-based agro-ecotourism in West Java is quite sustainable (57.07). This study analyzed sustainability through economic, social, cultural, institutional, ecological, and technological dimensions. The social dimension has the highest value because agriculture-based village tourism is carried out in the community. Meanwhile, the lowest value is the technology dimension. The availability of infrastructure influenced the value obtained and means of transportation as well as environmentally friendly farming techniques.

Exposure to air pollution have detrimental effects on the elderly, women, people with pre-existing medical conditions, people living in poverty and children. The aim of the study was to investigate the extent of community awareness and knowledge on the health risks associated with exposure to air pollution. A cross-sectional study design was used for the study, using self-administered questionnaires. A simple random sampling technique was used to select 376 respondents. Systematic sampling method was applied to select the households. SPSS version 26 was used to analyze data. Of 376 respondents, 221 were males and 154 females. 113 were aged between 23-47years and 353 were aware that if they don’t protect themselves against polluted air, they may get sick, with age and educational status associated with their awareness (p &lt; 0.05). About 361 knew what air pollution is and 188 think the air they breathe in Annadale is moderate. A total number of 278 said they feel sick/uncomfortable when the quality of air is bad. About 293 knew that people are exposed to air pollution by breathing contaminated air and 237 identified sewage smell as the main cause of air pollution. Respondents who identified internet and television as the main source of information were 199 and 177 respectively. Those who were not aware of actions implemented to reduce air pollution were 180. Based on the results of the study, respondents are aware of the dangers of exposure to polluted air, and it is necessary that air pollution risk communication strategies be implemented to empower residents.

This research aims to examine the level of readiness of the community to carry out sustainable tourism development, especially community-based tourism on small islands, such as Lombok Island, Indonesia. More specifically, the objectives of this study are as follows: (1) Knowing the level of community readiness in carrying out sustainable tourism development. (2) Knowing the various dimensions that influence sustainable tourism development. (3) Knowing the role of stakeholders in sustainable tourism development. The method applied in this research is mixed methods, a combination of quantitative and qualitative approaches. Quantitative methods are used to determine community readiness for sustainable tourism development. A qualitative approach is used to determine the various factors that influence the development of community-based tourism and to determine the role of stakeholders in the development of community-based tourism. The level of community readiness for sustainable tourism development is high in terms of economic, social, cultural, environmental, and symbolic capital aspects. Aspects that influence the development of sustainable tourism are economic, social, and cultural. Stakeholders who play a role in developing sustainable tourism in the research area are the government, the private sector, universities, non-governmental organizations, and the media.

Current epidemiological data reports that adults aged 65 years and older comprise the most vulnerable age group with the highest proportion of CAP-attributable hospitalizations. Pneumococcal vaccine efficacy (VE) has been shown to decrease over time, contributing to increasing incidence rates of CAP. A holistic evaluation of age, sex, seasonality, and VE are is conducted in this systematic review and meta-analysis of 12 prospective and retrospective cohort studies. The findings suggest that incidence and age are positively associated and that incidence in females is more often reported to be higher in females than in males. In studies that observed seasonality of CAP, high seasons and low seasons were reported to be in winter and summer months, respectively. Lastly, studies that reviewed the effect of vaccination on incidence consistently found decreased observance of CAP in elderly adults following reception of PCV13 or PPSV23. However, one study suggested that such vaccinations may have decreased effectiveness in elderly populations and that research examining potential explanations for this require further investigation. Furthermore, distinct diagnostic and case ascertainment standards, descriptive measures, and methods of prevention and treatment of CAP used across the US are outlined in this review. Public health guidance such as encouraging the reception of pneumococcal vaccinations and mask-wearing during high seasons of CAP, and communicating the risks of not adhering to the aforementioned preventative measures can facilitate an effort to reduce the incidence of CAP and its associated adverse outcomes in the US elderly population.

This study intends to study a distinct typology of vernacular architecture built by the Manipuri communities of Bangladesh. The Manipuris are one of the ethnic diasporic communities in Bangladesh commonly known for their diverse cultural practice, including their dance form. This research aims to reveal the cultural entity of Manipuri that has been transformed into their living environment and household architecture. Architectural elements adapted by the Manipuris are assessed here as a part of cultural symbols to have a rigorous view of the philosophy of living. This study is a documentation of Manipuri habitat culture through the intervention of their living environment, which will attract any future working on this issue. This research shows that despite a rapid socio-economic change of context, the Manipuri housing practice is deeply connected to their socio-cultural and religious values. As the authors used an observational and ethnographical approach to studying vernacular architecture for this research.

Knowledge and attitude towards mental illness play major role in the recognition, management, sociocultural factors and health seeking behavior among those with mental disorders. The study aim was to determine the knowledge and attitude among Nyamagana community members towards mental illness, Tanzania; A descriptive cross-sectional quantitative study involving 384 participants from sample population aged 18 years and above who were mentally health and semi-structured questionnaires was used to collect data. The results 110 (28.8%) respondents have good knowledge toward mental illness, about 292(76%) have negative attitude towards mentally ill people, 92(24%) respondents have positive attitude toward people who are mentally ill. More over about 318 (82.9%) respondents agreed that care and support of family and friends, could help people with mental illness to get rehabilitation while 66(17.1%) respondents disagreed on the care and support of the family and friends could help mentally ill people to get rehabilitation; The findings show most have poor knowledge and negative attitudes towards people with mental illness and may impair their social reintegration in the community. There’s need to develop strategies to enlighten the public regarding nature of mental illness so as to foster acceptance of people with mental illness by the community members.

Mancozeb is extensively used fungicide to prevent citrus melanose in most Asian countries, especially in China. So far, however, there have been no reports of thet effect of Mancozeb on the citrus rhizosphere bacterial community. Therefore, this comparative experiment defined the genomic and functional related to community and soil health of 2-years old Citrus unshiu Marc. rhizosphere through amplicon sequencing and chemical analysis. This study evaluated the effect of mancozeb on the chemical properties of citrus-cultivated soil and the richness and diversity of rhizosphere bacterial community. We also investigated the abundance response of rhizosphere bacterial groups to 0, 2, 4, 6 and 8 times application of 2 g mancozeb (active ingredient content, ai.) 600 times diluted with water. Our data revealed that the abundance of rhizosphere-associated bacterial species increased significantly after planting citrus. The relative abundance of Candidatus, Saccharibacteria, Parcubacteria, and Proteobacteria increased with the increase in mancozeb watering times. Meanwhile, the abundance of Nitrospirae decreased with the increase in mancozeb application times. The findings indicated that the chemical properties of the soil and the richness and diversity of rhizosphere bacterial community did not significantly differ across the mancozeb gradients in soil.

Background: Little is known about risk and prognostic factors in very old patients developing sepsis secondary to community-acquired pneumonia (CAP). Methods: We conducted a retrospective observational study of data prospectively collected at the Hospital Clinic of Barcelona over a 13-year period. Consecutive patients hospitalized with CAP were included if they were very old (≥80 years) and divided into those with and without sepsis for comparison. Sepsis was diagnosed based on the Sepsis-3 criteria. The main clinical outcome was 30-day mortality. Results: Among the 4,219 patients hospitalized with CAP during the study period, 1,238 (29%) were very old. The prevalence of sepsis in this aged group was 71%. Male sex, chronic renal disease, and diabetes mellitus were independent risk factors for sepsis, while antibiotic therapy before admission was independently associated with a lower risk of sepsis. Thirty-day and intensive care unit (ICU) mortality did not differ between patients with and without sepsis. In CAP-sepsis group, chronic renal disease and neurological disease were independent risk factors for 30-day mortality. Conclusion: In very old patients hospitalized with CAP, in-hospital and 1-year mortality rates were increased if they developed sepsis. Antibiotic therapy before hospital admission was associated with a lower risk of sepsis.