In this paper, a new approach to retrieve semantic images based on shape and geometric features of image in conjunction with multi-class support vector machine is proposed. Zernike moment as shape feature is to verify the invariance of objects for silhouette image. In addition, a set of geometrical features is to explore the objects shape using two features of rectangularity and circularity. Then the extracted features are normalized and employed for multi-class support vector machine either for learning or retrieving processes. The retrieving process relies on three main tasks which namely Query Engine, Matching Module and Ontology Manger, respectively. Query Engine is to build the input text or image query using SPARQL language. The matching module extracts the shape and geometric features of image’s objects and employ them to Ontology Manger which in turn inserts them in ontology knowledge base. Benchmark mammals have been conducted to empirically conclude the outcome of proposed approach. Our experiment on text and image retrieval yields efficient results to problematic phenomena than previously reported.

Malware complexity is rapidly increasing, causing catastrophic impacts on computer systems. Memory dump malware is gaining increased attention due to its ability to expose plaintext passwords or key encryption files. This paper presents an enhanced classification model based on One class SVM (OCSVM) classifier that can identify any deviation from the normal memory dump file patterns and detect it as malware. The proposed model integrates OCSVM and Principal Component Analysis (PCA) for increased model sensitivity and efficiency. An up-to-date dataset known as “MALMEMANALYSIS-2022” was utilized during the evaluation phase of this study. The accuracy achieved by the traditional one-class classification (TOCC) model was 55%, compared to 99.4% in the one-class classification with PCA (OCC-PCA) model. Such results have confirmed the increased performance achieved by the proposed model.

Deep learning has increasingly been employed to identify minerals. However, deep learning can only be used to identify minerals in the distribution of the training set, while any mineral outside the spectrum of the training set is inevitably categorized erroneously within a predetermined class from the training set. To solve this problem, the study introduces the approach that amalgamates One-Class Support Vector Machines (OCSVM) with the ResNet architecture for the out-of-distribution mineral detection. Initially, ResNet undergoes training using a training set comprising well-defined minerals. Subsequently, the earlier layers of the trained ResNet are employed to extract the discriminative features of the mineral under consideration. These extracted mineral features then become the input for OCSVM. When OCSVM discerns the mineral in the training set's distribution, it triggers the subsequent layers within the trained ResNet, facilitating the accurate classification of the mineral into one of the predefined categories encompassing the known minerals. In the event OCSVM identifies the mineral out of the training set's distribution, it is unequivocally categorized as an unclassified or 'unknown' mineral. Empirical results substantiate the method's capability to identify out-of-distribution minerals while concurrently maintaining a commendably high accuracy rate for the classification of the 36 in-distribution minerals.

Background: Insecticide resistance in Anopheles gambiae s.l. is a major challenge for malaria vector control in Nigeria. Both target-site insensitivity and metabolic resistance have been im-plicated in resistance process, with the latter receiving little attention in Nigeria. Therefore, we investigated metabolic enzyme activities in Anopheles gambiae s.l populations resistant to Del-tamethrin and Diethyldichlorotriethylethane (DDT) in South-West Nigeria. Methods: Anopheles larvae were collected from Ibadan, Oyo and Badagry, Lagos. Adults were exposed to Deltamethrin and DDT using WHO method. Cohorts of populations were further exposed to Pyperonil Butoxide (PBO) and Deltamethrin. Insecticide-exposed and unexposed co-horts were examined for metabolic enzyme activities. Results were compared between exposed and unexposed samples ANOVA (P<0.05). Results: Mosquitoes were identified as An. gambiae (89%, Ibadan; 0%, Badagry) and An. coluzzii (11%, Ibadan; 100%, Badagry). The populations showed varied level of resistance to Deltamethrin (26%, Ibadan; 71%, Badagry) and DDT (2%, Ibadan; 44%, Badagry). Mortality to Deltamethrin in-creased from 26% to 64% (Ibadan) and 71% to 84% (Badagry) when populations were pre-exposed to PBO. Biochemical analysis revealed significant high levels (P<0.05) of cytochrome P450 and GST in exposed samples. Conclusions: Cytochrome P450 and GST are involved in Deltamethrin and DDT resistance in Anopheles gambiae s.l populations in South-West Nigeria.

The holistic approach of One Health, which sees human, animal, plant, and environmental health as a unit, rather than discrete parts, requires not only interdisciplinary cooperation, but standardized methods for communicating and archiving data, enabling participants to easily share what they have learned and allow others to build upon their findings.Ongoing work by NCBI and the GenomeTrakr project illustrates how open data platforms can help meet the needs of federal and state regulators, public health laboratories, departments of agriculture, and universities. Here we describe how microbial pathogen surveillance can be transformed by having an open access database along with Best Practices for contributors to follow. First, we describe the open pathogen surveillance framework, hosted on the NCBI platform. We cover the current community standards for WGS quality, provide an SOP for assessing your own sequence quality and recommend QC thresholds for all submitters to follow. We then provide an overview of NCBI data submission along with step by step details. And finally, we provide curation guidance and an SOP for keeping your public data current within the database. These Best Practices can be models for other open data projects, thereby advancing the One Health goals of Findable, Accessible, Interoperable and Re-usable (FAIR) data.

This paper proposes a novel phase-resolved partial discharge (PRPD) sensor embedded in MV-class bushing for high-accuracy insulation analysis. The design, fabrication, and evaluation of a PRPD sensor embedded in MV-class bushing aimed to detect partial discharge (PD) pulses that are phase-synchronized with the applied primary HV signals. A prototype PRPD sensor was composed of a flexible printed circuit board (PCB) with dual-sensing electrodes, utilizing a capacitive voltage divider (CVD) principle for voltage measurement and D-dot principle for PD detection, and a signal transducer with passive elements. A PD simulator was prepared to emulate typical PD defects, i.e., a metal protrusion. The voltage measurement precision of the prototype PRPD sensor was satisfied with the accuracy class of 0.2 specified in IEC 61869-11, as the maximum corrected voltage error ratios and corrected phase errors in 80%, 100%, and 120% of the rated voltage (13.2 kV) were less than 0.2% and 10 minutes, respectively. In addition, the prototype PRPD sensor had good linearity and high sensitivity for PD detection compared with a conventional electrical detection method. According to performance evaluation tests, the prototype PRPD sensor embedded in the MV-class bushing can measure PRPD patterns phase-synchronized with the primary voltage without any additional synchronization equipment or system. Therefore, the prototype PRPD sensor holds potential as a substitute for conventional commercial PD sensors. Consequently, this advancement could lead to the enhancement of power system monitoring and maintenance, contributing to the digitalization and minimization of power apparatus.

This paper offers insights into the nexus of youth, masculinity and right-wing populism in Australia. Here we make reference to a wide body of international literature on the topic. There is some affinity between disenfranchised (white) working-class young men and the radical right. Survey data were collected for a project on masculinity and the far right in Australia. 203 young men worked primarily in “blue collar” sectors of the Australian labour force. Some survey responses locate them partly or potentially within the field of the populist right-wing, with many expressing anti-government sentiments and the discourse of white male victimhood. The majority were nostalgic for stereotypical masculinity. While right-wing populist movements across the world certainly differ, they often share a discourse promoting traditional gender roles.

Fraudulent transactions pose a significant threat to financial institutions and e-commerce platforms.Machine learning models, trained on historical labeled data (fraudulent vs. legitimate transactions), are often employed to identify and prevent fraud. However, real-world datasets frequently exhibit class imbalance, where fraudulent transactions (minority class) are significantly outnumbered by legitimate transactions (majority class). Machine learning models may perform poorly as a result of this imbalance, underestimating fraud and favouring the majority class. This paper proposes a novel approach to address class imbalance and improve fraud detection accuracy. We explore the implementation of FROST (Feature space RObust Synthetic saTuration) oversampling, a technique specifically designed to generate synthetic samples for the minority class. The FROST function leverages the k-nearest neighbors (KNN) algorithm and a user-defined amplification factor (m) to create synthetic data points that closely resemble existing minority class instances. We integrate the FROST-enhanced oversampling technique into the machine learning pipeline for fraud detection. The paper evaluates the effectiveness of this approach compared to traditional oversampling methods and analyzes its impact on classification accuracy metrics.

Facial expression recognition is crucial for understanding human emotions and nonverbal communication. With the growing prevalence of facial recognition technology and its various applications, accurate and efficient facial expression recognition has become a significant research area. However, most previous methods have focused on designing unique deep-learning architectures while overlooking the loss function. This study presents a new loss function that allows simultaneous consideration of inter- and intra-class variations to be applied to CNN architecture for facial expression recognition. More concretely, this loss function reduces the intra-class variations by minimizing the distances between the deep features and their corresponding class centers. It also increases the inter-class variations by maximizing the distances between deep features and their non-corresponding class centers, and the distances between different class centers. Numerical results from several benchmark facial expression databases, such as Cohn-Kanade Plus, Oulu-Casia, MMI, and FER2013, are provided to prove the capability of the proposed loss function compared with existing ones.

The present study explained factors influencing citizen satisfaction service in the Investment and One-Stop Service Agency of Tanah Bumbu Regency. In particular, this research analyses the level of citizen satisfaction and the extent to which Awareness, Rules, Organizational, Income, Skill-Ability, and Service Facility Factor influence Citizen Satisfaction. This study uses a mixed methodology with a sequential explanatory strategy. Using the incidental sampling with Slovin's Formula to calculate the number of samples is 93 respondents. The quantitative data were analyzed by the SmartPLS 3.0 program. The findings showed that the level of citizen satisfaction is included in the category "Satisfied". Furthermore, the variable of Citizen Satisfaction is influenced by variables of Awareness, Rules, Organizational, Income, Skill-Ability dan Service Facility Factor for 70,5%. Whereas Awareness, Rules, Organizational, and Skill-Ability Factor has a significant influence on Citizen Satisfaction. Besides, Income and Service Facility Factor do not have a significant influence on Citizen Satisfaction.

Background: Exclusive breastfeeding (EBF) for the first 6 months of life improves the growth, health and survival status of newborns. Breastfeeding has been accepted as the most vital intervention for reducing infant mortality and ensuring optimal growth and development of children. Objectives: The general objective was to identify the factors affecting exclusive breastfeeding among working class women in selected wards in Egbedore Local Government in Osun state, Nigeria. Methodology: This was descriptive cross-sectional study. Leslie Kish formula was used for sample size calculation and multistage sampling was used in selecting 316 working class women for the study. A structured, self-administered questionnaire was used for data collection. Data was analyzed using SPSS version 21.0 and level of significance was set at 5%. Results: 58% of the respondents were between the ages of 25-30. 72% demonstrated good understanding of exclusive breastfeeding based on the 6 months WHO recommendation for exclusive breast feeding, 25.9% had a fair knowledge and awareness of exclusive breastfeeding. 63.3% of the working class mother has a good practice of exclusive breast feeding, 19.6% of the women moderately practices exclusive breastfeeding while 17.1% poorly practices exclusive breastfeeding. Less than 3-months maternity leave for mothers, lack of crèche closer to place of work and lack of breastfeeding break were identified as barriers to exclusive breastfeeding practices among the working class women. The findings demonstrated a significant relationship between knowledge and practices of exclusively breastfeeding among working class women (P-value .009). Conclusion: This study demonstrated that working class women had good knowledge of exclusive breastfeeding and this influenced their breastfeeding practices. A good knowledge was associated with favorable attitudes to the practice of exclusive breast feeding. To derive long-term benefits from early childhood nutrition, interventions should focus on health education and community-based sensitization programs on the needs for mothers to engage in exclusive breast needing for global development.

From gene expression studies to identifying microbes quantitative polymerase chain reaction (qPCR) is widely used in research and medical diagnostics. In transmittable diseases like the Ebola outbreak in West Africa (2014-2016), or the present SARS-CoV2 pandemic qPCR plays a key role in the detection of infected patients. Although the technique itself is decades old with reliable approaches (eg. TaqMan essay) in the diagnosis of pathogens many people showed distrust in it during the SARS-CoV2 outbreak. This came mainly from not understanding or misunderstanding the principles of qPCR. This situation motivated us to design a simple laboratory practical class, in which students have opportunities to understand the underlying principles of qPCR and its advantages in microbiological diagnosis. Moreover, during the exercise, students can develop skills such as handling experimental assays, and the ability to solve problems, discuss their observations. Finally, this activity brings them closer to the clinical practice and they can see the impact of the science on real life. The class is addressed to undergraduate students of biological sciences.

Antimicrobial resistance (AMR) poses one of the significant challenges for the progress of modern medicine not only by its myriad manifestations on a microbiological plane but also due to its demand for a complex, multisectoral approach for its annulment. While some nations have been actively involved in the deployment of counter measures against AMR, the same have yet to be implemented in India. This can be attributed due to a combination of its epitomizing multivariate nature and the challenges encountered on a ground-level in policy implementation. This review surveys mechanisms and factors promoting incidence of AMR, potential Artificial Intelligence (AI) implementation alongside evaluating the efficacy of the One Health approach on national and state levels in curbing the rise of AMR.

A strategy to propose solutions to health-related problems recognizes that people, animals, and the environment are interconnected. Fusarium and Neocosmospora are an example of this interaction due to the capable of infecting plants, animals, and human. This review provides information on various aspects of these relations and proposes how to approach fusariosis with a One Health methodology. Here we give a framework to understand infection pathogenesis, through the epidemiological triad and explain how the broad utilization of fungicides in agriculture may play a role in the treatment of human fusariosis. We assess how plumbing systems and hospital environments might play a role as a reservoir for animal and human infections. We explain the role of antifungal resistance mechanism in both humans and agriculture. Our review emphasizes the importance of developing interdisciplinarity research studies where aquatic animals, plants, and human disease interactions can be explored through coordination and collaborative actions.

Usually, the two-bath dyeing process using disperse dyes and reactive dyes separately was employed for the dyeing of PC blends. The cost of the double bath, dyeing cycle, energy consumption and chemical consumption is quite higher than the one-step or single bath dyeing methods. In this study, the one-bath dyeing process using one kind of dye was investigated. Polyester cotton blends dyed in one-bath one-step dyeing methods with disperse dye after surface modifications of cotton by acetylation methods were studied. Surface modification of cotton was carried out using fibrous acetylation methods. The effect of acetic anhydride and time on percent acetyl content at room temperature was studied. Modified polyester/cotton was carried out in HTHP dyeing machine incorporates with different dye concentrations and dyeing temperature. Surface chemistry, thermal decomposition property and moisture regain of modified polyester/ cotton blend are evaluated. The color strength of the dyed fabrics and their fastness properties to washing, light, and rubbing as well as tear strength and abrasion resistance were evaluated. The effect of dye concentration and temperature color strength, tensile strength warp and weft direction was assessed. The optimum value for surface modification was obtained with a concentration of acetylation agent 16% and time of reaction 2.5 hours, gave percent acetylation of 34. An FTIR spectrum shows acetylation resonance. The experiment result of dyeing showed that the optimum value was obtained with dye concentration above 1% at a temperature of 120oC, warp tensile strength decreased by 12% and weft tensile strength was decreased by 9% from the control half-bleached fabric. Results of this study showed that a one-step one-bath dyed modified polyester/cotton blend with disperse dye fabric presents good fastness property compared with conventional two-bath dyed fabric as well as colour strength values.

Zoonoses are diseases transmitted from (vertebrate) animals to humans. Control and prevention of these diseases require an appropriate way to measure health for prudent and well-balanced decisions in public health. We propose a framework that aims to explore, understand and open up a conversation about the non-monetary value of animals through environmental and normative ethics. As an example of its application, participants can choose what they are willing to give in exchange for curing an animal in hypothetical scenarios selecting a human health condition to suffer, the amount of money, and lifetime as a tradeoff. We believe that considering animals beyond their monetary value in public health decisions will contribute to a more rigorous assessment of the burden of zoonotic diseases, among other health decisions. This method might help us complement the existing metrics in health, adding more comprehensive values for animal and human health for the “One Health” approach.

Since the advent of the OBORI, it was subjected to numerous studies. However, most previous studies investigated only the potential impact of the OBORI on the Chinese economy and geopolitics. Therefore, its real effect on Chinese international commerce in OBORI countries is not evaluated yet. Accordingly, this study intends to model the OBORI effect on Chinese product brand purchases across country members. The assessment is made on 18362 purchases of the International Online Consumers (IOCs) from a Chinese international online selling platform. The Data was obtained from a programming language and the octopus software. The OBORI policy's effect on Chinese brands' purchases was examined through a Different In Different Model (DIDM). Results show that the impact of OBORI is weak in the real market. However, it could be significant if OBORI includes more developed and economically strong countries. To Chinese brands and policymakers, we show how the inclusion in the OBORI project of developed countries could contribute more to Chinese product brands' purchases. Thus, the study enables decision-makers to understand the current impact of OBORI on the real market and its potential effect if more developed and economically strong countries are included.

The aim of this study was to analyze the profile of IgG subclasses in COVID-19 convalescent Puerto Rican subjects and compare this profile with those exhibited by no-infected immunocompetent or immunocompromised subjects that received the mRNA vaccine. The most notable find-ngs from this study are: 1) Convalescent subjects that were not hospitalized developed high and long-lasting antibody response. 2) Both, IgG1 and IgG3 are the subclasses more prevalent in the SARS-CoV-2 infected population whereas IgG1 is more prevalent after vaccination. 3) Individuals that first had the infection and further received two doses of mRNA vaccines exhibited more robust neutralizing capacity against Omicron than those that were never infected and received two doses of Pfizer-BioNTech vaccine. 4) A class switch toward the “anti-inflammatory” anti-body isotype IgG4 is induced a few weeks after the third dose, which peaked abruptly and remained at high levels for a long period. Moreover, the high levels of IgG4 are concurrent with high neutralizing percentages against various VOC including Omicron. 5) Subjects with IBD also develop IgG4 after the third dose, although these antibody levels have limited effect on the neutralizing capacity. Knowing that the mRNA vaccines do not prevent reinfections, all Omicron sub-variants that are dominant worldwide have shown to be less pathogenic, and the IgG4 levels have been associated to immunotolerance and causative of numerous negative effects, the recommendations of successive administration of booster vaccinations to people should be revised.

In the mid-layers of Deep Learning systems, clustered features tend to fit multiple classifications, which are filtered out during the final stages of object recognition. However, many misclassifications remain, regarded as errors of the system. This paper claims that tagging an entity incorrectly for reasons of similarity is evidence of spontaneous machine creativeness. According to the ratings of 40 design educators and researchers, AI-generated false-class inclusions produced creative design ideas, predicting the level of innovation value. These designers were not just anybody but came from a design school in Asia with a top position on the world ranking-lists. They entered an experiment in which 20 classification mistakes were framed as early-design ideas that were either human-made or intentionally suggested by creative AI. Many examples passed the Feigenbaum variant of the Turing test with a conceptual preference to creations supposedly done by human hand.

Automated software bots infiltrate online surveys and corrupt data integrity, not to mention waste researcher time and budgets. Although resources exist to help keep bots out and identify bots when they do evade survey barriers, bot attacks may be a persistent problem for online surveys for a long time to come. Bots are evolving -- even as survey designers try ever more sophisticated methods to fend them off and weed their answers out. Vigilance needs to be high and the bot generators should not be under-estimated. We recount here some bot features we encountered after our own survey was attacked that helped to identify them, and that have not been detailed elsewhere. We also discuss reasons why commonly recommended strategies for how to keep bots out may not be feasible for many scientific researchers.

This study has been taken during COVID-19. It describes the working scenario of all class of peoples and their mental anxieties are analysed based on their psychological behaviour patterns.

In Bangladesh, microcredit program has been in function for almost half a century. Though popularly termed as a tool for poverty alleviation and women empowerment, criticism about microcredit program’s actual effectiveness isn’t new. This study attempts to evaluate the impact of such programs by measuring borrowers’ social mobility. Using a multidimensional approach, indicators like household income, economic susceptibility, living conditions, consumption pattern, children’s education, healthcare facilities, women’s participation in decision-making were taken into account for measurement. Quantitative method was used. Based on a non-probability sampling, 107 microcredit borrowers were selected for conducting interview schedules who live in a rural, a semi-urban and an urban area. Statistical analysis of data reveals that those who have been taking loans for several number of years have all managed to increase their income level to a variety of extent, but only those have gained some sort of mobility who have been taking loans for more than 4-5 years and have taken 5 times or more. Few of them have actually moved from microcredit to become a microfinance client by taking bigger amount of loans and having savings. Positive responses about the indicators being used in the study were found among the handful of those who have mobilized significantly. In true sense, most of the borrowers are stuck at the bottom end of socio-economic ladder and are struggling to manage a better living standard.

This article is an anthropology study on how western-style coffee culture influences Indonesian coffee culture and eventually develops a new localized coffee culture. Immense development of such worldwide coffee franchise as Starbucks affects local community's coffee culture, particularly the middle class. This new wave is considered as an alternative lifestyle for those who are consumptive and seeking for leisure, dynamics, and identity. Broader than just the process of domestication or creolization, Indonesian new coffee culture has an element of “soft countering to” western coffee culture even though it still embraces some parts of the western styles. This phenomenon is referred to by the writer as the cultural encapsulation process or the process of substantial cultural resistance by drawing a line between the two coffee cultures with the intention of taking merely compatible elements.

Training researchers and stakeholders is crucial to mitigate the risks associated with toxins and venom. By sharing knowledge on the responsible use of toxins, venoms, chemicals, and data from biosecurity and cyberbiosecurity perspectives, we empower laboratorians to make informed choices. We need to remember that cultivating a culture of sustainable biosafety and biosecurity is vital for one health. This technical note highlights the essence of safeguarding biosecurity and cyberbiosecurity in toxin and venom research laboratories workshop designed and implemented to boost biosecurity.

According to data from the U.S FDA, the likelihood of a new drug progressing from Phase I clinical trials to market approval is only 8% (DiMasi et al., 2016). Furthermore, a significant attrition rate of 35% occurs during Phase II studies due to the failure to demonstrate clinical efficacy (Arrowsmith, 2011). These statistics underscore the urgent need to reassess the current research and development (R&D) paradigm. To address this challenge, a promising approach called reverse translational pharmacology (RTP) has emerged, aiming to enhance the predictive value of preclinical models used in biomedical research by leveraging animal models that spontaneously develop analogous diseases to humans (Schneider et al., 2018). The rationale behind RTP is that knowledge gained from clinical trials in canines can subsequently inform and guide human clinical trials, leading to improved outcomes for both species. Additionally, this approach capitalizes on the opportunity to stimulate veterinary drug development by leveraging pharmacokinetic (PK), efficacy, and safety data obtained from human clinical studies (Schneider et al., 2018). The application of reverse translational pharmacology holds immense potential for expediting drug development and advancing medical knowledge. By employing animal models that naturally develop diseases akin to those found in humans, researchers can enhance the predictive capacity of preclinical models, thereby mitigating the high attrition rates encountered in later stages of clinical trials. Moreover, the exchange of knowledge and data between human and veterinary medicine engenders a synergistic relationship, fostering progress in both domains (Schneider et al., 2018). As this innovative approach gains momentum, fostering collaborations between basic and clinician scientists, pharmaceutical companies, and veterinary professionals becomes increasingly imperative. By sharing resources, expertise, and findings, we can pave the way for groundbreaking discoveries and the development of safe and efficacious treatments for diverse diseases. Embracing reverse translational pharmacology offers an avenue to redefine the R&D paradigm, bringing us closer to a future where a higher proportion of drugs successfully traverse the arduous path from the laboratory to market approval, ultimately benefiting patients across species. In this brief commentary, we highlight four examples of diseases where reverse translational modeling has been used to support pharmaceutical research, including some applications developed in our research laboratory (SMART Pharmacology) at the Iowa State University College of Veterinary Medicine. In doing so, this report also seeks to provide a brief overview of the heuristic value of computational approaches in comparative research. To further illustrate the value of these in silico approaches, we deliberately chose to employ some features of ChatGPT to produce the present summary (OpenAI. (2023). GPT-3.5 [ChatGPT]. Retrieved from https://openai.com).

Urinary bladder cancer (UBC) is the most common malignancy of the urinary tract in humans, with an estimated global prevalence of 1.1 million cases over 5 years¹. Due to high rates of recurrence and resistance to chemotherapy, UBC is one of the most expensive cancers to treat, resulting in significant health care costs. There is, therefore, a critical need to develop innovative molecular and cellular tools to refine patient stratification and help predict response to treatment. Urine is an underused resource of biological components shed from bladder tumors, such as exfoliated cells and extracellular vesicles, that could serve as molecular fingerprints and provide valuable biological insights into tumor phenotype and mechanisms of resistance to chemotherapy. Additionally, characterization of urine-derived extracellular vesicles and cells could be used as reliable biomarkers for prediction of response to neoadjuvant therapy.

The microbioma is presently one of the hottest areas of scientific and medical research and exerts a marked influence on the host during homeostasis and disease. Fermented foods arise in the human relationship to the microbial environment. Further to the traditionally recognized effects of fermented foods and beverages on the digestive health and well-being there is now strong evidence on their general health benefits, namely the significance on the gut microbiota and brain functionality. We highlight the possibilities in this field, how little is still known, and call for a convergence of interdisciplinary research fields of One Health microbe-nutrition with fermented foods and gut-brain research. A consequence of civilisation, changes in present-day society in diets with more sugar, fat and salt, habits and lifestyle, contributes to the likelihood of an inflammatory microbiome, particularly the global epidemics of obesity and mental health. Although two recent papers claim that probiotics perturb rather than aid in microbiota recovery back to baseline after antibiotic administration in humans, consuming fermented foods has shown to reduce inflammation so improve gut health and the proper function of the body’s immune system.

Aiming at the problem of low charging efficiency caused by the scattered sensor nodes in traditional wireless rechargeable sensor networks (WRSNs), a UAV-assisted WRSN Online Charging Strategy Based on Dynamic Queue and Improved K-means (UOCS) is proposed. The scheme assumes that the energy consumption of nodes is unpredictable, and only generates charging requests when the energy is lower than a threshold, and performs on-demand responses to nodes that issue charging requests. The scheme combines the characteristics of one-to-one charging of UAVs, the selection and allocation timing of waiting queues and the number of UAVs, and the improved K-means partitioning based on space-time coordination(SPKM), which simplifies the problem of coordinated charging of multiple UAVs and maximizes energy. Using the efficiency and charging success rate, the optimal charging trajectory can be found under the constraint that the node will not starve to death due to power shortage. Finally, a simulation comparison experiment is carried out with the existing UAV charging scheduling strategy. UOCS achieves the optimal node survival rate with low algorithm complexity.

Due to the retrognathic mandible, an orthodontist frequently observes skeletal class II malocclusion in growing patients. The preferred technique for analyzing and monitoring the temporomandibular joint alterations caused by the functional device is magnetic resonance imaging [MRI]. The study aimed to assess and compare changes in the articular disc's dimension and location before and following the use of various class II correctors to correct the class II molar relation using MRI technology. Methods: 39 adolescent patients aged 15-23 years old [24 girls and 15 boys] who were diagnosed with skeletal Class II division 1 malocclusion based on clearly defined criteria underwent treatment with either the power scope II [PS], Sabbagh Advanced Repositioning Appliance [SARA] and or Dynaflex [DF] with fixed appliances. For fixed functional treatment, the average length of treatment was 5-7 months. The changes in the articular disc dimension and position and condylar position were assessed. The study was done at the Department of Orthodontics at the College of Dentistry, Hawler Medical University in Erbil City. Results: Group DF has a significant effect on the condylar position index and posterior joint space on the closed mouth and disc length on both open and close mouth techniques, and in the group SARA, disc position, and condylar position index on closed mouth technique have shown that significant differences were observed. Conclusion: Class II malocclusions can be effectively corrected by fixed functional appliances. The statistical significance forward movement of the condyle in the glenoid fossa and the posterior movement of the articular disc concerning the condylar head was observed. The mechanism of action of functional appliances appears to include the forward migration of the C-GF complex.

We propose Reduced Collatz Conjecture that is equivalent to Collatz Conjecture, which states that every positive integer can return to an integer less than it, instead of 1. Reduced Collatz Conjecture should be easier because some properties are presented in reduced dynamics, rather than in original dynamics (e.g., ratio and period). Reduced dynamics is a computation sequence from starting integer to the first integer less than it, and original dynamics is a computation sequence from starting integer to 1. Reduced dynamics is a component of original dynamics. We denote dynamics of x as a sequence of either computations in terms of ``I'' that represents (3*x+1)/2 and ``O'' that represents x/2. Here 3*x+1 and x/2 are combined together, because 3*x+1 is always even and followed by x/2. We formally prove that all positive integers are partitioned into two halves and either presents ``I'' or ``O'' in next ongoing computation. More specifically, (1) if any positive integer x that is i module $2^t$ (i is an odd integer) is given, then the first t computations (each one is either ``I'' or ``O'' corresponding to whether current integer is odd or even) will be identical with that of i. (2) If current integer after t computations (in terms of ``I'' or ``O'') is less than x, then reduced dynamics of x is available. Otherwise, the residue class of x (namely, i module $2^t$) can be partitioned into two halves (namely, i module $2^{t+1}$ and $i+2^t$ module $2^{t+1}$), and either half presents ``I'' or ``O'' in intermediately forthcoming (t+1)-th computation.

Objective. It is unknown whether the public accurately estimate socioeconomic health inequality and whether they wish to see it reduced or eliminated. Methods. Representative samples of the UK and US indicated the perceived and ideal lifespan of people working in “higher managerial/professional” and “routine” occupations. We present perceived and desired lifespan ratios for each sample and for key socio-demographic variables. Results. The UK public estimated the lifespan of professionals to be 5.9% longer than routine workers (true value of 5.8%), and 67.8% (UK) and 53.7% (US) participants correctly identified that professionals live longer than routine workers. In both populations, the median respondent expressed equal ideal lifespans for routine workers and professional workers. Conclusion. The UK public appear well-appraised on the average lifespan for professionals and routine workers. Across nationalities and most socio-demographic groups, the median respondent was aware of social class inequalities in lifespan and preferred that they be eliminated.

B lymphocyte development has two DNA recombination processes: V(D)J recombination of the immunoglobulin (Igh) gene variable region and class switching of the Igh constant regions from IgM to IgG, IgA, or IgE. V(D)J recombination is required for successful maturation of B cells from pro-B to pre-B to immature-B and then to mature B cells in the bone marrow. CSR occurs outside of the bone marrow when mature B cells migrate to peripheral lymphoid organs, such as spleen and lymph nodes. Both V(D)J recombination and CSR depend on an “open chromatin” state that makes DNA accessible to specific enzymes, recombination activating gene (RAG), and activation-induced cytidine deaminase (AID). Acetyltransferases GCN5 and PCAF possess redundant functions acetylating histone H3 lysine 9 (H3K9). Here, we generated a mouse model that lacks both GCN5 and PCAF in B cells. We found that double-deficient mice possess low levels of mature B cells in the bone marrow and peripheral organs, an accumulation of pro-B cells in bone marrow, and reduced CSR levels. We conclude that both GCN5 and PCAF are required for B cell development in vivo.

(1)Background: Fascioliasis is considered a neglected tropical disease affecting an estimated 17 million people in more than 70 countries worldwide. The highest prevalence of human fascioliasis is found in regions where livestock farming and consumption of raw or undercooked freshwater plants are common, such as parts of Africa, Asia, Europe, and Latin America. It is responsible for over 90,000 disability-adjusted years of life due to associated abdominal complications. We conducted a study to investigate the prevalence of human fascioliasis through a systematic review and meta-analysis of all available literature in Sun-Saharan Africa.(2). Methods: We screened a total of 126 publications using pubmed online search engine databases; Web of Science and CAB for articles published within a 20-year period between 2000 and 2022. We used a comprehensive search method using a combination of terms, parasite and disease names. The initial search resulted in a screening of articles by title, abstracts and full texts. The relevant information on the prevalence of human fascioliasis in Africa was extracted. Of the 126 publications, 33 articles were selected for meta-analysis. The essential information required was extracted from these documents and determined through statistical analysis in Microsoft Excel for calculating the prevalence of human fascioliasis in sub-Saharan Africa. The variance of each study was assessed using a bimodal distribution and heterogeneity assessment using a I2 index. Analysis was performed using random effects models.(3)Results: A total of 271 articles were searched through the database search and 33 articles were eligible studies that provided qualitative information on the prevalence of human fascioliasis in Africa. These make up 12.17% (n=33). The pooled prevalence estimates for human fascioliasis are 0.032% (IVhet PPE: 0.032% (95%CI 1.4-6.53). The highest prevalence rate was observed in Egypt with a prevalence of 100%. The prevalence of human fascioliasis is very high in some sub-Saharan countries, partly due to neglect of diagnostics, demonstrating the bias of available information for decision-making in human fascioliasis across Africa, given the spatial presence, scarcity and incompleteness are region.(4)Conclusions: The prevalence of Human fascioliasis is very high in some Sub-Saharan Countries partly due to neglect in diagnostics. This presents how highly focal with spatial occurrences, scarcity and patchy the available information for decision making is on Human fascioliasis across the Sub-Saharan African region.

Colistin [polymyxin E] is a veterinary exclusive antimicrobial and one of the oldest antibiotics that is currently recognised as one of the highest priority critically important antimicrobials for humans. It is extensively used for multiple medical and non-medical purposes particularly for growth promotion, prophylaxis/metaphylaxis and therapeutic in food animals. As a result, colistin resistance was widespread along the food-chain linking to multidrug resistant bacterial infections in humans reflected by greater use of colistin in healthcare settings resulted in different types of bans/restrictions in food-producing animals, around the world. This report debates the testimonies of 23 countries representing the bulk of global food producing animal production, providing robust evidence on the essential need for colistin in animal production.

Leishmaniosis is a zoonoses caused by Leishmania spp., an intracellular protozoan parasite. This parasite is transmitted by sandflies and the disease is endemic in Mediterranean basin. In the last years, the number of species which could be reservoir of parasite is increased. One of the most relevant is the horses, due to contact with humans and its ability to control the disease, being a possible silent reservoir. In this study, we have analyzed the prevalence and factors related to L. infantum infection in healthy horses in Mediterranean region. Epidemiological data and serum samples were obtained to 167 apparently healthy horses and presence of L. infantum was evaluated by ELISA method and qPCR. The results show 27,5% of prevalence and the main factors related to infection are equine breed, outdoor living, use and season. In conclusion, the prevalence of L. infantum infection in apparently horses from Eastern Spain (Mediterranean basin) is elevated. To control this zoonosis, it would be advisable to carry out more studies on this and other species that could be silent reservoirs of the parasite, as well as carry out measures such as the use of repellents on a regular basis.

Acid stress poses a common challenge for bacteria in diverse environments by the presence of inorganic (e.g., mammals’ stomach) or organic acids (e.g., feed additives; acid-based disinfectants). Limited knowledge exists regarding acid-tolerant strains of specific serotypes, clonal lineages, or sources in human/animal pathogens, namely non-typhoidal Salmonella enterica (NTS) and Enterococcus faecium (Efm). This study evaluated acidic pH and peracetic acid (PAA) susceptibility of Efm (n=72) and NTS (n=60) from diverse epidemiological/genetic backgrounds, and with multiple antibiotic resistance profiles. Efm minimum growth/survival-pH was 4,5-5/3-4 and for NTS 4,0-4,5/3,5-4,0. Among Efm, only those of clade-non-A1 (non-hospital associated) or food chain demonstrated greater tolerance to acidic pH compared to clade-A1 (hospital-associated clones) or clinical isolates (P<0.05). MDR (multidrug-resistant) NTS survived better to acidic pH (P<0.05). The MICPAA/MBCPAA was 70-120/80-150mg/L for Efm and 50-70/60-100mg/L for NTS. Efm-clade-A1 or MDR strains exhibited higher PAA tolerance than clade-non-A1 or non-MDR ones (P<0.05). Higher tolerance was found in non-MDR and clinical NTS than in food chain isolates (P<0.05), but not between different serogroups. This unique study identifies specific NTS or Efm populations more tolerant to acidic pH or PAA, emphasizing the need for further research to tailor control measures of public health and food safety within a One Health framework.

Brucellosis is an important infectious disease caused by bacteria of the genus Brucella. In the northeast region of Portugal, brucellosis is endemic in small ruminants, and there are also human cases. However, the epidemiological role of the wild boar in the dynamics of this disease in this region is unknown. For this reason, a total of 332 blood samples were collected from wild boar hunted in thirty-six hunting areas during the 2022/2023 hunting season. All were taken by the hunters for private consumption, with no evisceration and examination in the field. Serum sam-ples were tested by i-ELISA. It was observed that 88 wild boars were exposed to Brucella spp., pointing to a seroprevalence of 26.5% (95% CI: 21.8% – 31.3%). This high prevalence underlines the importance that wild boar may have in the dynamics of this disease in the region and its po-tential transmission to other animals and to human, for example, during the handling of carcasses. Increased awareness and knowledge of brucellosis in wild boar is essential for the implementation of effective practices and habits and, consequently, for the control and prevention of this important zoonosis.

Viral Encephalitis is a significant public health concern globally, especially west Africa. There are more than 500 known arboviruses with over 100 of them identified to cause encephalitic diseases in humans and animals, giving rise to a tremendous burden of the diseases, and socioeconomic strains in tropical and subtropical regions worldwide. Despite their importance, few effective preventive and control measures in form of vaccines and therapeutics are available and where they are, usage is limited. These limitations are largely hinged on the paucity of information about the molecular epidemiology and transmission patterns of VE in west Africa. Here, we reviewed the transmission dynamics, ecological drivers, and molecular epidemiology of VE in the region. Collectively, timely and accurate interventions are essential for encephalitic viral disease control. Moreover, the integrated health system approach, combining surveillance, vaccination, vector control, and community engagement could be effective in preventing viral encephalitis globally.

Natural products are an important source of antibacterial agents. Canthin-6-one alkaloids have displayed potential antibacterial activity based on our previous work. In order to improve the activity, twenty-two new 3-N-benzylated 10-methoxy canthin-6-ones were designed and synthesized through quaternization reaction. The in vitro antibacterial activity against three bacteria was evaluated by double dilution method. Four compounds (6f, 6i, 6p and 6t) displayed 2-fold superiority (minimum inhibitory concentration (MIC) = 3.91 µg/mL) against agricultural pathogenic bacteria R. solanacearum and P. syringae than agrochemical propineb. Moreover, the structure–activity relationships (SARs) were also carefully summarized in order to guide the development of antibacterial canthin-6-one agents.

Reducing the immunogenicity of animal-derived monoclonal antibodies (mAbs) for use in humans is critical to maximize therapeutic effectiveness and preclude potential adverse events. While traditional humanization methods have primarily focused on grafting antibody Complementarity-Determining Regions (CDRs) on homologous human antibody scaffolds, framework regions can also play essential roles in antigen binding. Here, we describe the humanization of the pan-HLA-DR mAb 44H10, a murine antibody displaying significant involvement of the framework region in antigen binding. Using a structure-guided approach, we identify and restore framework residues that directly interact with the antigen or indirectly modulate antigen binding by shaping the antibody paratope and engineer a humanized antibody with affinity, biophysical profile, and molecular binding basis comparable to that of the parental 44H10 mAb. As a humanized molecule, this antibody holds promise as a scaffold for the development of MHC class II-targeting therapeutics and vaccines.

In this article, rst we are going to review the concept of ordinary frames , in more general case in measure spaces, namely, gc-frames. We try to develop the use of measure space in describing frames. Then by means of the gc-frames, we shall introduce gn-operators, which we shall show that each trace class operator has a vector-valued integral representation and vice-versa.

Type 2 diabetes has been linked to the expression of Human Leukocyte Antigens, principally to the major Histocompatibility Complex Class II and only scarce reports to Major Histocompatibility Complex class I in specific populations. The objective of the present work was to explore the presence of polymorphisms in the MHC class I related to Type 2 diabetes in the Mexican population using the GWAS SIGMA database. This database contains information of 3,848 Mexican individuals with type 2 diabetes and 4,366 control individuals from the same population without clinical or hereditary history of the disease. The searching criteria considered a P value < 0.005 and odds ratio, OR > 1.0. Ten novel statistically significant nucleotide variants were identified: four polymorphisms associated with HLA-A (A*03:01:01:01), and six with HLA-C (C*01:02:01:01). These alleles have a high prevalence in Latin American populations and could potentially be associated with autoimmunity mechanisms related with the development of Type 2 diabetes complications.

Contagious pathogens have very high costs for dairy herds, and they may have zoonotic and reverse-zoonotic potentials, and may contribute in spreading antimicrobial resistance. One of the most important risk factors for spreading these infections is milking, when liner contamination may transfer the pathogens from infected to healthy cows. There is no effective protocol for avoiding the transmission of infection out of the segregation of infected cows. Recently, the availability of elastomers including patented antimicrobial components in their formulations has opened the way to explore alternative methods to decrease infection risk. Two different types of elastomers (rubber and silicon) and 9 different receipts were challenged by three major mastitis pathogens (S. aureus, S. agalactiae, and E. coli). The results showed interesting and unexpected results. Indeed, for the first time to our knowledge, we have shown that basic rubber materials have intrinsic antimicrobial activity. Silicon elastomers did not exhibit the same levels of killing activity, although they did exhibit some antibacterial capacity. Generally, a significant decrease in bacterial survival curves was observed with the tested formulations. The results observed for the various products are likely due to the specific activity of the chemical components, as well as the diverse chemical reactions that occur during their production. The availability of new tools able to reduce the risks for the spread of infections and generally decrease the bacterial load at milking, would be an important step forward to achieve a higher global sustainability of dairy production from a One Health perspective.

Metabolomics is an advanced technology, still under development, with multiple research applications, especially in the field of health. Individual metabolic profiles, the functionality of the body, as well as its interaction with the environment can be established using this technology. The body's response to various external factors, including the food consumed and the nutrients it contains, has increased researchers' interest in nutrimetabolomics. Establishing correlations between diet and the occurrence of various diseases or even the development of personalized nutrition plans, could contribute to advances in precision medicine. The interdependence between humans, animals and the environment are of particular importance today, with the dramatic emergence and spread of zoonotic diseases, food, water and soil contamination, and the degradation of resources and habitats. All these events have led to an increase of risk factors for functional diseases, burdening global health. Thus, this study aimed to highlight the importance of metabolomics, in particular of nutrimetabolomics, as a technical solution for a holistic, collaborative, and precise approach for the advancement of the One Health strategy.

Antimicrobial resistance (AMR), the capacity of microbial pathogens to survive in the presence of antimicrobials, is considered one of the greatest threats to human health worldwide and is growing rapidly in importance. AMR is thought to be driven in part by the use of antimicrobials (AMU) in livestock production. AMU reduction in agriculture is therefore important, but doing so may endanger farmers’ incomes and hamper broader food security. Understanding drivers for farmers' antibiotics use is essential to designing interventions which avoid harming agricultural output and safeguard farmers’ economic security. In this study, we analyse AMUSE survey data from poultry farmers in Senegal to explore the effects of vaccination, attitudes towards AMR, and biosecurity practices on: AMU, animal mortality, and farm productivity. We found that farmers with more “AMR-aware” attitudes may be less likely to use antibiotics in healthy birds. Stronger on-farm biosecurity was associated with less use of antibiotics in healthy birds, and in some specifications was linked to higher broiler productivity. Vaccination and AMU were both linked with higher disease prevalence, and both factors appeared conducive to higher broiler productivity. Overall, there is evidence that awareness-raising and biosecurity improvements could encourage prudent use of antibiotics, and that biosecurity and vaccination could to some extent replace antibiotic use as productivity-enhancing and disease-management tools in broiler farms. Finally, issues of farm antimicrobial stewardship must be considered at the structural level, with farm behaviours contingent on interaction with state and private stakeholders.

Antimicrobial resistance (AMR) is an increasingly pressing threat to human, animal, and environmental health. Reducing the use of antibiotics in agriculture has been identified as a key way to curb the spread of AMR. However, the effect of such policies on AMR prevalence, and their broader impacts on agricultural, health, and economic outcomes at the population level have proven very difficult to estimate and compare. This paper draws on and formalises ideas presented at the JPIAMR New Perspectives on Bacterial Drug Resistance workshop in June of 2022. With reference to emerging literature on the topic, it proposes a quantitative framework for estimating the relevant causal relationships needed to quantify the cross-sectoral impacts of AMR policies in agriculture, and for comparing these outcomes in like terms in a way which can feed directly into policy decision-making, notably without prohibitive data requirements. The ability of researchers to apply frameworks such as this will be increasingly necessary in order to holistically capture the impacts of AMR policies and to situate them in the broader policy context; especially where the mechanisms of transmission are opaque or complex, where data availability is limited; and where policymakers must allocate scarce resources among many competing objectives.

Graphene oxide was synthesized by a one-step environmentally friendly mechanochemistry process directly from graphite and characterized by Raman, FT-IR and UV/vis spectroscopies, Atomic Force Microscopy, X-ray Diffraction, Scanning Electron Microscopy, Energy-Dispersive X-ray Spectroscopy and Thermogravimetric Analysis. Spectroscopic analysis shows that the functional groups and oxygen content of the synthesized material are comparable with those of graphene oxide synthesized by other previously reported methods (Hummers). Thermogravimetric analysis reveals thermal stability up to 400 °C.

The advent of the genome editing era brings forth the promise of adoptive cell transfer using engineered chimeric antigen receptor (CAR) T-cells for targeted cancer therapy. CAR T-cell immunotherapy is probably one of the most encouraging developments for the treatment of hematological malignancies. In 2017, two CAR T-cell therapies were approved by the U. S Food and Drug Administration; one for the treatment of pediatric Acute Lymphoblastic Leukemia (ALL), the other for adult patients with advanced lymphomas. However, despite significant progress in the area, CAR T-cell therapy is still in its early days and faces significant challenges, including the complexity and costs associated with the technology. B-cell lymphoma is the most common hematopoietic cancer in dogs, with an incidence approaching 0.1% and a total of 20-100 cases per 100,000 individuals. It is a widely accepted naturally occurring model for human non-Hodgkin’s lymphoma. Current treatment is with combination chemotherapy protocols, which prolong life for less than a year in canines and are associated with severe dose-limiting side effects, such as gastrointestinal and bone marrow toxicity. To date, one canine study generated CAR T-cells by transfection of mRNA for CAR domain expression. While this was shown to provide a transient anti-tumor activity, results were modest, indicating that stable, genomic integration of CAR modules is required in order to achieve lasting therapeutic benefit. This Commentary summarizes the current state of knowledge on CAR T-cell immunotherapy in human medicine and its potential applications in animal health, while discussing the potential of the canine model as a translational system for immuno-oncology research.

The development of a method to produce coumarins unsubstituted on the pyranic nucleus catalyzed from Wells–Dawson heteropolyacid (H₆P₂W₁₈O₆₂), phenol derivatives and ethyl 3,3-diethoxypropionate using Pechmann condensation under solvent-free conditions is described. This catalytic method was also applied successfully to synthesize various substituted coumarins, including the corresponding phenols and ethyl 3,3-diethoxypropionate. This work provides a novel, cheaper and safer way to syhthesize coumarins unsubstituted on the pyranic nucleus.

Given a set of distinct non-negative integers X^n and a target certificate S in parametrized form: ∃X^k⊆X^n,∑_(x_i∈X^k)▒x_i =S (k=|X^k |,n=|X^n |). We present a polynomial solution of the subset sum problem with time complexity T≤O(kn)≤O(n^2) and space complexity S≤O(((n-1)n)/2)≤O(n^2 ), so that P = NP.

Migratory flows and international travel are triggering an increase in imported cases of schistosomiasis in non-endemic countries, with serology being the recommended method for screening migrants. The present study aims to evaluate, for the first time, the LAMP technique on patients’ urine samples for the diagnosis of imported schistosomiasis in a non-endemic area in comparison to a commercial immunochromatographic test and microscopic examination of feces and urine. A prospective observational study was conducted in sub-Saharan migrants attending at the Tropical Medicine Unit, Almería, Spain. For schistosomiasis diagnosis, serum samples were tested using an immunochromatographic test (Schistosoma ICT IgG-IgM). Stool and urine samples were examined by microcopy. Urine samples were evaluated by combining three LAMP assays for the specific detection of Schistosoma mansoni and S. haematobium, and an assay for the genus Schistosoma. To evaluate the diagnostic accuracy of Schistosoma-LAMP in comparison to microscopy and Schistosoma ICT IgG-IgM test, a Latent Class Analysis (LCA) was performed. A total of 115 patients were included; 21 patients (18.3%) were diagnosed with schistosomiasis confirmed by microscopy, with S. haematobium being the most frequent species identified (18/115; 15.7%). The Schistosoma ICT IgG-IgM test resulted 100% positive and Schistosoma-LAMP was 61.9% positive, reaching as high as 72.2% for S. haematobium. The sensitivity and specificity estimated by LCA, respectively, were: 92% and 76% for Schistosoma ICT IgG-IgM, 68% and 44% for Schistosoma-LAMP and, 46% and 97% for microscopy. The Schistosoma-LAMP technique presented a higher sensitivity than microscopy for the diagnosis of imported urinary schistosomiasis, which could improve the diagnosis both in referral centers and in centers with limited experience or scarce resources and infrastructure.

The implications of urban revitalization, gentrification, and residential migration have attracted widespread interest and ongoing debate among scholars across a range of disciplines. While a significant body of literature explores race and class interactions within urban gentrifying neighborhoods, few have examined the environments that await those displaced by this process. This study explores the social and political impact of urban gentrification and class stratification within the black community by examining responses of black middle class residents in Prince George’s County, MD to the growing in-migration of low-income and minority residents from Washington, DC. Drawing on data from the U.S. Census Bureau, a multi-neighborhood sample of ninety-five black middle class residents of Prince George’s County, and informal interviews with subject-area experts, this study explores how race and class shape residential decisions and their impact on residential mobility initiatives. Residents responded to a 26-item survey that covered demographic information, political and community engagement, and their attitudes and beliefs about the poor, changes in their community, and racial unity and responsibility. Findings from cross tabulations and binary logistic regression indicate that lower middle class residents are the most likely to resist in-migration by exiting their communities and/or voting against proposals to create affordable housing options. Core and upper middle class residents were the most likely to stay in their neighborhoods despite increases in low-income migration, to vote in support of policies to create affordable housing options and to believe their responsibility to poor blacks could include sharing residential space.

Air pollution is a situation that negatively affects the health of humans and all living things in nature and causes financial damage to the environment. In the case of air pollution, harmful and foreign substances in the air reach an amount and density above normal values. Air pollution also causes climate change, which affects global warming. Particulate matter is a harmful substance that harms the health of humans and other living things, causes air pollution, increases radiation, and negatively affects cloud formation. Particulate matter is extremely small solid particles and liquid droplets suspended in the air. PM10, which is less than 10 microns in diameter, is defined as small particles that can remain in the air for a long time and settle in the respiratory tract, damaging the lungs. Many criteria affect PM10 density and changes in density. The main criteria are vehicle traffic and fuel consumption, industrialization, coal, fuel oil and wood-burning heaters, greenhouse gas impact, and unregulated urbanization. It is important to identify the underlying causes of air pollution caused by PM10. In this context, these criteria need to be evaluated to minimize the negative effects of PM10. In the study, monthly average PM10 data between 2019 and 2023 obtained from the Air Monitoring Station in Kocaeli, Türkiye are used. After determining the criteria affecting PM10, the criteria are prioritized with the Intuitionistic Fuzzy AHP (IF-AHP) method by taking expert decision-maker opinions. The proposed decision-making model aims to guide obtaining the important causes of PM10 emission in terms of danger and focusing on these causes. Additionally, PM10 data is analyzed in the context of Covid-19 and a statistical analysis is made. One-way ANOVA is used to evaluate whether there is a significant difference in the average monthly data over the years. Games-Howell test, one of the post-hoc tests, is used for differences between groups (years). The study is important in that it provides a focus on the criteria affecting PM10 with an intuitive fuzzy perspective, along with statistical analysis.

Globally increasing antibiotic resistance has been connected to the use of antibiotics in medical, veterinary, and agricultural medicine, contributing to the burden of antibiotic resistance in Asia and Europe. The main objective of this study was to correlations of antimicrobial-resistant of various pathogens in three compartments: humans, animals and the environment in India and Germany. A systematic search was carried out in Medline via PubMed, Google Scholar, and science direct, including studies published in 2022. Out of 532 papers, 24 were considered for meta-analysis. This study reveals that in India, β-lactam is highly resistant in animals. Quinolone, on the other hand, was highly resistant in humans. Furthermore, in the environment and integrated studies, aminoglycosides and β-lactams is resistant. While in Germany, a high rate of AMR resistance in all three sectors was reported in β-lactam. However, E. coli was the most frequent pathogen in both countries and is highly resistant to β-lactam, followed by cephalosporin in all the compartments. Monitoring and evaluating antibiotic-sensitivity patterns and developing proper antibiotic regimens may lead to improved outcomes for inhibiting and controlling E. coli infections in various parts of the world.

Colorectal cancer (CRC) is the second cause of cancer-related death where the CpG-island methylation pathways (CIMP) is associated to KRAS/BRAF mutations, two oncogenes rewiring cell metabolism, worst prognosis and resistance to classical chemotherapies. Despite this, the question of a possible metabolic rewiring in CIMPs has never been asked. Here we asked if metabolic dysregulations were associated to the methylation status of tumours by evaluating the transcriptome of CRC tumours. CIMP-high patients were found to present a hyper-metabolism activating mainly carbohydrates, folates, sphingolipids and arachidonic acid metabolic pathways. A third of these genes had epigenetic targets of Myc in their proximal promoter, activating carboxylic acid, tetrahydrofolate interconversion, nucleobase, and oxoacid metabolisms. Amongst the Myc signature, the expression of GAPDH, TYMS, DHFR, TK1 was enough to predict methylation levels, microsatellite instability (MSI) and mutations in the mismatch repair (MMR) machinery, which are strong indicators of responsiveness to immunotherapies. Finally, we discovered that CIMP patients harboured an increase in genes involved in the one-carbon metabolism, a pathway critical to provide nucleotides for cancer growth and methyl donors for DNA methylation which was associated to worse prognosis. Transcriptomics could hence become a tool to help clinicians stratify their patients better.

Staphylococcus spp. are among the main pathogens responsible for important infections worldwide, both in humans and in domestic or wild animals. Chiropterans, popularly known as bats, inhabit natural environments and human constructions, and have been considered potential disseminators of several pathogens. Studies have shown the expression of the mecA gene in these animals, being a significant threat to One Health. The objective of this study was to determine antibiotic resistance and the presence of the mecA gene in Staphylococcus spp. isolates from bats from forest areas in the municipalities of Paraná, Brazil. A total of 87 frugivorous chiropterans belonging to the family Phyllostomidae were captured. Of these, 87 rectal and 87 oral swabs samples were collected, re-sulting in 32 Staphylococcus spp. isolates. Twenty-four isolates were characterized as coagu-lase-negative, and 8 coagulase-positive Staphylococcus spp. (STACP), which showed notable re-sistance to oxacillin (78.12%), penicillin G (65.62%) and to other antimicrobials as well. One STACP isolate was mecA-positive. Therefore, further studies are needed to elucidate the mechanisms of contamination and dissemination of these pathogens, emphasizing that anthropic actions in na-tural environments, especially those related to the use of antimicrobials, pesticides may be the main reasons for the presence of resistant bacteria in bats.

Wastewater surveillance, initially conceived in the early 20th century during typhoid fever outbreaks, has evolved into a powerful tool for monitoring public health-relevant analytes. Recent applications in tracking SARS-CoV-2 infection highlight its potential. Beyond humans, it can be extended to livestock populations due to the increasing demand for livestock products. Livestock intensification poses risks of zoonotic disease emergence. Wastewater surveillance offers non-invasive, cost-effective means to detect potential outbreaks. This approach aligns with the "One Health" paradigm, emphasizing the interconnectedness of human, animal, and ecosystem health. By monitoring viruses in livestock wastewater, early detection, prevention, and control strategies can be employed, safeguarding both animal and human health, economic stability, and international trade. This integrated One Health approach enhances collaboration and a comprehensive understanding of disease dynamics, supporting proactive measures in the Anthropocene era where animal and human diseases are on the rise.

Antimicrobial resistance (AMR) is a growing public health concern worldwide, and it poses a significant threat to human, animal, and environmental health. The overuse and misuse of antibiotics have contributed significantly to the emergence and spread of antimicrobial resistance, which may lead to significant economic consequences like reduced productivity and increased healthcare costs. Nanotechnology offers a promising platform for addressing this challenge. Nanoparticles have unique properties that make them highly effective in combating bacterial infections by inhibiting the growth and survival of multidrug-resistant bacteria in three areas of health: human, animal, and environmental. To conduct an economic evaluation of surveillance in this context, it is crucial to have a comprehension of the connections to be addressed by several nations by implementing national action policies based on the One Health strategy. This review provides an overview of the progress made thus far and presents potential future directions to optimize the impact of nanobiotics on AMR.

Antimicrobial resistance (AMR) is a global health problem threatening safe, effective healthcare delivery in all countries and settings. The ability of microorganisms to become resistant to the effects of antimicrobials is an inevitable evolutionary process. The misuse and overuse of antimicrobial agents has increased the importance of a global focus on antimicrobial stewardship (AMS). This review provides insight into the current AMS landscape and identifies contemporary actors and initiatives related to AMS projects in eight African countries (Ghana, Kenya, Malawi, Nigeria, Sierra Leone, Tanzania, Uganda, and Zambia), which form a network of countries participating in the Commonwealth Partnerships for Antimicrobial Stewardship (CwPAMS) programme. We focus on common themes across the eight countries, including the current status of AMR, infection prevention and control, AMR implementation strategies, AMS, antimicrobial surveillance, antimicrobial use, antimicrobial consumption surveillance, a one health approach, digital health, pre-service and in-service AMR & AMS training, access to and supply of medicines, and the impact of COVID-19. Recommendations suitable for adaptation are presented, including the development of a national AMS strategy and incorporation of AMS in pharmacists’ and other healthcare professionals' curricula for pre-service and in-service training.

Extremely low concentrations of ciprofloxacin may select for antimicrobial resistance. A recent global survey found that ciprofloxacin concentrations exceded safe levels at 64 sites. We assessed if national median ciprofloxacin concentrations in rivers were associated with fluoroquinolone resistance in Escherichia coli. Methods Spearman’s regression was used to assess the country-level association between the national prevalence of fluoroquinolone resistance in E. coli and the median ciprofloxacin concentration in the countries rivers. Results The prevalence of fluoroquinolone resistance in E. coli was positively correlated with the concentration of ciprofloxacin in rivers (ρ=0.36; P=0.011; N=48). Conclusions Steps to reducing the concentrations of fluoroquinolones in rivers may help prevent the emergence of resistance in E. coli and other bacterial species.

With rapid advances in gene editing and gene therapy technologies, the development of genetic, cell, or protein-based cures to disease are no longer the realm of science fiction but that of today’s practice. The impact of these technologies are rapidly bringing them to the veterinary market as both enhanced therapeutics and towards modeling their outcomes for translational application. Simply put, gene editing enables scientists to modify an organism’s DNA a priori through the use of site-specific DNA targeting tools like clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). Gene therapy is a broader definition that encompasses the addition of exogenous genetic materials into specific cells to correct a genetic defect. More precisely, the U.S Food and Drug Administration (FDA) defines gene therapy as “a technique that modifies a person’s genes to treat or cure disease” by either (i) replacing a disease-causing gene with a healthy copy of the gene; (ii) inactivating a disease-causing gene that was not functioning properly; or (iii) introducing a new or modified gene into the body to help treat a disease. In some instances, this can be accomplished through direct transfer of DNA or RNA into target cells of interest or more broadly through gene editing. While gene therapy is possible through the simple addition of genetic information into cells of interest, gene editing allows the genome to be reprogrammed intentionally through the deletion of diseased alleles, reconstitution of wild type sequence, or targeted integration of exogenous DNA to impart new function. Cells can be removed from the body, altered, and reinfused, or edited in vivo. Indeed, manufacturing and production efficiencies in gene editing and gene therapy in the 21^st century has brought the therapeutic potential of in vitro and in vivo reprogrammed cells, to the front lines of therapeutic intervention (Brooks et al., 2016). For example, CAR-T cell therapy is revolutionizing hematologic cancer care in humans and is being translated to canines by us and others, and gene therapy trials are ongoing for mitral valve disease in dogs.

An interesting anomaly of the diffusion process with an apparently negative diffusion coefficient defined through the mean-square displacement in a one-dimensional quantum molecular chain model is shown. Nevertheless, the system satisfies the H-theorem, so that the second law of thermodynamics is satisfied. The reason why the “diffusion constant” becomes negative is due to the effect of the phase mixing process, which is a characteristic result of the one-dimensionality of the system. We illustrate the situation where this negative “diffusion constant” appears.

This study addressed a Fluid-Structure Interaction of an open Water test for vp1304 propeller to predict pressure and stress distributions with a low cost and high precision method. The most striking aspect of such a method(one-way coupling) is to use one hydrodynamic solution for the number of different structural sets involved in other materials or different layup methods and combinations of layers. An open-access software(OpenFOAM) with an open-source code solver is used to simulate the fluid domain. Abaqus is used To evaluate and predict the deformation and strength of the blade with the Finite Element Method(FEM). The coupling approach is based on dry condition, which means the added mass effects due to propeller blades vibration is neglected. The pressures imposed on the blades are extracted from the fluid solver for each time step. Then, These pressures role as a load condition for the structure solver. This approach was verified in the last paper(wedge impact); a key factor for the present solution is the rotational rate interrelated between two solution domains, which is explained in this paper. Finally, the blades' stress and strain are calculated and compared in each advance coefficient.

In the past ten years several novel hantaviruses were discovered in shrews, moles and bats, suggesting the dispersal of hantaviruses in many animal taxa other than rodents during their evolution. Interestingly, the co-evolutionary analyses of most recent studies have raised the possibility of non-rodents may have served as the primordial mammalian host and harboured the ancestors of rodent-borne hantaviruses as well. The aim of our study was to investigate the presence of hantaviruses in bat lung tissue homogenates originally collected for taxonomic purposes in Malaysia, 2015. Hantavirus specific nested RT-PCR screening of 116 samples targeting the L segment of the virus have revealed the positivity of two lung tissue homogenates originating from Murina aenea bat species. Nanopore sequencing of hantavirus positive samples resulted in partial genomic data from S, M and L genome segments. The obtained results indicate the first molecular evidence for hantavirus in Murina aenae bat species and also the first discovery of a hantavirus in Murina bat species. Sequence analysis of the PCR amplicon and partial genome segments suggests the identified virus may represent a novel species in Mobatvirus genus within Hantaviridae family. Furthermore, our results provide additional genomic data to help extend our knowledge about the evolution of these viruses.

Ransomware attacks have risen alarmingly, with encryption techniques becoming more complex. This paper introduces a novel detection model tailored for ransomware's distinctive characteristics. The Intel PIN tool extracts Windows API invocation sequences related to file operations. These sequences are used to construct n-grams, forming feature vectors enhanced by a new Class Feature Weighting (CFW) metric to improve malware detection. Preliminary results demonstrate elevated accuracy and precision versus existing methods. The major contributions are: (1) Introducing an innovative deep learning model for few-shot ransomware classification using entropy features and transfer learning. (2) Achieving high weighted F1-score in classifying ransomware variants into families with limited training data. (3) Demonstrating the potential of entropy-based features to capture intricacies lost in image-based approaches, improving detection of new strains.

A new power receiving unit (PRU) is proposed in this paper for the resonant wireless power transfer (WPT), which is characterized by the capability of attracting high power from the power transmitting unit (PTU). The resonant WPT is designed for delivering the electrical power to the PRU attached on an electrical vehicle (EV) chassis 50cm away from a PTU installed on the ground. The proposed PRU uses only the passive elements such as inductors, diodes and the capacitors, which needs no initial power from the EV. It is then applicable for charging a battery to several hundred volts for even a first-time charging battery. At a switching frequency of the resonant WPT in the experiment being 4MHz, the proposed PRU behaves itself as a negative impedance converter (NIC) in the subharmonics of 4MHz. The NIC effect plus the subharmonic oscillation causes an instability current charging the battery connected to the PRU. In this paper, we simulated the PRU and performed the experiment. The experiment demonstrates a battery charging of 150W from 50cm away using three D-mode GaN HEMT transistors via the instability current ramp. The power transfer efficiency (PTE) improved as the power delivered to load (PDL) goes higher. The best power transfer efficiency (PTE) is 65% in the present findings. The simulation analysis shows that the circuit allows itself be used to much higher power transfer when it is implemented with more GaN HEMT transistors connected in parallel. The theoretical derivation of the PRU circuit is also used to support both the experimental and simulation results.

One method of estimating the evaporation rate (ER) is to use a variety of evaporation pans, such as the Class A standard evaporation pan (CASEP) and the Colorado Sanken standard evaporation pan (CSSEP). In this study, the rate of evaporation of CASEP and CSSEP have been investigated and compared with each other. This study was conducted in Semnan, Iran. CSSEP was used as a test pan, which was performed in an open space around the Faculty of Civil Engineering, Semnan University. Evaporation was recorded daily for 123 days. The evaporation of the CASEP pan was obtained from the synoptic station of Semnan, which is located at a distance of 2.39 km from the test site. Meteorological data were also obtained from the synoptic station of Semnan and compared with experimental evaporation data. The results of this study showed that the daily ER from CASEP and CSSEP in the tested time periods were not significantly different. Based on the Klomogorov-Sminrov method, the best statistical distributions for CASEP and CSSEP were calculated as Error and Gamma, respectively. The coefficient of determination (R 2 ) between the two pans was estimated to be about 93%. Also, by examining the ER with other meteorological data, it was observed that the ER has the highest correlation with the average daily air temperature.

The analogy between the theory of phase transitions in simple fluids and vehicular traffic flow has long been suspected, promising a new level of understanding of urban congestion by standing on one of the firmer foundations in physics. The obstacle has been the interpretation of the thermal energy of the gas-particle system, which remains unknown. This paper proposes the flow of cars through the network as a viable interpretation, where the fundamental diagram for traffic flow would be analogous to the coexistence curve in gas-liquid phase transitions. Thanks to the power-law form of the coexistence curve, it was possible to formalize that the resulting network traffic model belongs to the Kardar-Parisi-Zhang universality class. The scaling relationships arising in this universality class are found to be consistent with West's scaling theory for cities. It is shown that congestion costs (delays + fuel consumption) scale superlinearly with city population, possibly and worryingly more so than predicted by West's theory. Implications for sustainability and resiliency are discussed.

In this note we, first, recall that the sets of all representatives of some special ordinary residue classes become $\left( m,n\right) $-rings. Second, we introduce a possible $p$-adic analog of the residue class modulo a $p$-adic integer. Then, we find the relations which determine, when the representatives form a $\left( m,n\right) $-ring. At the very short spacetime scales such rings could lead to new symmetries of modern particle models.

Mature B cells notably diversify immunoglobulin (Ig) production through class switch recombination (CSR), allowing the junction of distant “switch” (S) regions. CSR is initiated by activation-induced deaminase (AID) which targets cytosines adequately exposed within single-stranded DNA of transcribed targeted S regions, with a specific affinity for WRCY motifs. In mammals, G-rich sequences are additionally present in S regions, forming canonical G-quadruplexes (G4s) DNA structures which favor CSR. Small molecules interacting with G4-DNA (G4 ligands), proved able to regulate CSR in B lymphocytes, either positively (such as for nucleoside diphosphate kinase isoforms) or negatively (such as for RHPS4). G4-DNA is also implicated in the control of transcription, and due to their impact on both CSR and transcriptional regulation, G4-rich sequences likely play a role in the natural history of B cell malignancies. Since G4-DNA stands at multiple locations in the genome, and notably within oncogene promoters, it remains to be clarified how it can more specifically promote legitimate CSR in physiology, rather than pathogenic translocation. The specific regulatory role of G4 structures in transcribed DNA and/or in corresponding transcripts and recombination hereby appears as a major issue for understanding immune responses and lymphomagenesis.

Smartphone-based mobility apps enable users to make informed transportation decisions, offering instant access to transport-related information. This development has created a smartphone-enabled ecosystem of mobility services in developed countries while it is slowly picking up pace in the global south, which can contribute towards the decarbonization of urban transport. Work on this has already started in India, and there is considerable evidence indicating the profound impact of these apps on the perceived utility and usage of transport modes, with far-reaching implications for sustainable development goals (SDGs). However, for most users, the use of smartphone apps is a novel trend, and the knowledge of the impacts of usage of existing apps on the usage pattern of transport modes by various user groups is essential for positioning new consolidated app-based services soon. Against this backdrop, the present study uses latent class cluster analysis to empirically investigate the impacts of mobility apps on transport mode usage patterns in Delhi by classifying users into latent classes based on socioeconomic characteristics, attitudes/preferences, smartphone app usage, and mode usage pattern. The characteristics of the latent class and factors affecting the individual’s probability of being classified to these cluster have been discussed, along with some measures to encourage app-based mobility for each cluster.

The last series of Raven's standard progressive matrices (SPM-LS) test were studied with respect to its psychometric properties in a series of recent papers. In this paper, the SPM-LS dataset is analyzed with regularized latent class models (RLCM). For dichotomous item response data, an alternative estimation approach for RLCMs is proposed. For polytomous item responses, different alternatives for performing regularized latent class analysis are proposed. The usefulness of the proposed methods is demonstrated in a simulated data illustration and for the SPM-LS dataset. For the SPM-LS dataset, it turned out the regularized latent class model resulted in five partially ordered latent classes.

This study presents a novel technique utilizing high frequency vibration to shorten treatment time and preserve alveolar bone in challenging orthodontic cases treated with Invisalign® clear aligners. Four non-growing orthodontic patients (age range 14-47 years old) with Class II skeletal patterns (convex profiles with retrognathic mandibles) who sought correction of their crowded teeth and non-surgical correction of their convex profiles were included in this study. These patients were treated using Invisalign clear aligners together with high frequency vibration (HFV) devices (120 Hz) (VPro5™) that were used by all patients for five minutes per day during active orthodontic treatment. Vertical control and forward rotation of the mandible for each patient was achieved through pre-programming the Invisalign to produce posterior teeth intrusion. Successful forward rotation of the mandibles achieved in all patients led to improvement of their facial convex profiles (ANB improved 2.1 + 0.5 degrees; FMA improved 1.2 +1.1 degrees). Dental decompensation was achieved by lingual tipping of the lower incisors and palatal root torque of upper incisors. The use of HFV together with Invisalign facilitated achieving these results within a 12+6 month period. In addition, more bone labial to the lower incisors after their lingual movement was noted. In conclusion, the use of HFV concurrent with SmartTrack Invisalign aligners allowed complex tooth movement and forward projection without surgery in non-growing patients with skeletal Class II relationships. The clinical impact and implications of this case series is that the use of HFV facilitates complex orthodontic tooth movement including posterior teeth intrusion and incisor decompensation in addition to increased bone formation labial to lower incisors that may minimize future gum recession due to their labial inclination.

The present novel corona virus (2019-nCoV) infection has created a global emergency situation by spreading all over the world in a large scale within very short time period. The infection induced death rate is also very high. There is no vaccine or anti-viral medicine for such infection. So at this moment a major worldwide problem is that how we can control this pandemic. On the other hand, India is a high population density country, where the corona virus disease (COVID-19) has started to spread from $1^{st}$ week of March, 2020 in a significant number of COVID-19 positive cases. Due to this high population density human to human social contact rate is very high in India. So control of the pandemic COVID-19 in early stage is very urgent and challenging problem. Mathematical models are employed in this paper to study the COVID-19 dynamics, to identify the influential parameters and to find the proper prevention strategies to reduce the outbreak size. In this work, we have formulated a deterministic compartmental model to study the spreading of COVID-19 and estimated the model parameters by fitting the model with reported data of ongoing pandemic in India. Sensitivity analysis has been done to identify the key model parameters. The basic reproduction number has been estimated from actual data and the effective basic reproduction number has been studied on the basis of reported cases. Some effective preventive measures and their impacts on the disease dynamics have also been studied. Future trends of the disease transmission has been Predicted from our model with some control measures. Finally, the positive measures to control the disease have been summarized.

Sleep disorders (SD) have a complex aetiology, and socioeconomic status (SES) as determined by social class, household income, ethnicity and education plays an important role in their development. As SD are associated with cognitive impairment and mood disorders, they in turn impact SES. Socioeconomic status also influences allostatic load caused by chronic accumulation of stress throughout life. Environmental and psychological stressors have a direct effect on SD, and they are modulated by SES, in combination with comorbidities like obesity and cardiovascular disease. This review explores the recent theories about the influence of SES on the development of SD in the general population, whether or not occurring with comorbidities, and also focusses on the interplay between socioeconomic status, circadian rhythms, aging and clinical outcomes like metabolic diseases and cancer.

Curcumin, a hydrophobic polyphenol compound derived from the rhizome of the Curcuma genus, has a wide spectrum of biological and pharmacological applications. Previously, curcumin nanoparticles with different stabilizers had been produced successfully in order to enhance solubility and per oral absorption. In the present study, we tested the anti-inflammatory effect of D-α-Tocopheryl polyethylene glycol 1000 succinate (TPGS)-stabilized curcumin nanoparticles in vivo. Lambda-carrageenan (λ-carrageenan) was used to induce inflammation in rats; it was given by an intraplantar route and intrapelurally through surgery in the pleurisy test. In the λ-carrageenan-induced edema model, TPGS-stabilized curcumin nanoparticles were given orally one hour before induction and at 0.5, 4.5, and 8.5 h after induction with two different doses (1.8 and 0.9 mg/kg body weight (BW)). Sodium diclofenac with a dose of 4.5 mg/kg BW was used as a standard drug. A physical mixture of curcumin-TPGS was also used as a comparison with a higher dose of 60 mg/kg BW. The anti-inflammatory effect was assessed on the edema in the carrageenan-induced paw edema model and by the volume of exudate as well as the number of leukocytes reduced in the pleurisy test. TPGS-stabilized curcumin nanoparticles with lower doses showed better anti-inflammatory effects, indicating the greater absorption capability through the gastrointestinal tract.

The process of establishing secure communication between devices in the Internet of Things (IoT) can be approached by using a One-time-Pad (OTP) protocol. We propose using a known secure multiparty sum protocol for generating a One-time-Pad key using true (physical) random numbers in each device (party). We implemented the proposal using ZeroC-Ice, a middleware for distributed computing. The protocol security properties were analyzed under the assumptions of the Dolev-Yao threat model.

Staphylococcus aureus are commensal bacteria present on skin and mucosae in both humans and animals, but they can also be found in food, water and in various environments. They are also considered a major pathogen having a great morbidity leading to a wide range of infections. They are included in the list of most virulent and antimicrobic resistant bacterial pathogens (ESKAPE, Escherichia coli, Staphylococcus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterococcus faecalis and faecium)) by the Center for Disease Control and Prevention (CDC), and S. aureus is part of the worldwide threat represented by the presence of antimicrobial resistance (AMR). The outcomes of an epidemiological investigation on 26,430 S. aureus isolates from a global public database (NPDIB; NCBI Pathogen Detection Isolate Browser) support the evidence of significant differences in the distribution of isolates and ARGs (Antimicrobial Resistance Genes) clusters among geographical areas of origin and among sources of the isolates. Moreover, the ARGs cluster patterns suggest an association between the isolates from human and animal populations. This outcome and the large diffusion of the pathogens among human and animal populations support the importance of gaining information on the epidemiology of these infections with a One Health approach.

The sustainability of agroecological systems, biodiversity protection, animal welfare and consumer demand for higher-quality products from alternative and extensive farming methods, have reinforced interest in local breeds that are well adapted to low-input environments. However, food safety needs to be safeguarded to reinforce consumer confidence. The aim of this study was to conduct a preliminary investigation on the occurrence of Salmonella spp. in eggshells, hen’s cloaca and litter materials from autochthonous Portuguese laying hens raised in a semi-extensive system for small-scale production. A total of 279 samples were obtained, with 63 samples from the “Preta Lusitânica” breed, and 72 samples each from the remaining autochthonous breeds, namely “Branca”, “Amarela” and “Pedrês Portuguesa”. None (0%) of the samples analyzed were positive for Salmonella spp.. To the best of our knowledge, these are the first results of Salmonella evaluation from hen’s cloaca, eggshells, and litter materials in autochthonous Portuguese chickens, suggesting that a semi-extensive production system can contribute to better food security and a lower risk to public health and the environment.

In recent years Pd-containing catalytic systems for tandem processes has drawn special attention due to the enhanced catalytic properties and possibility to perform several reactions without the necessity to separate the intermediates. In this review, recent progress in Pd-catalyzed tandem processes is considered. Three types of catalytic systems were described: homogeneous catalysts (including immobilized Pd complexes); heterogeneous catalysts supported on oxides, MOFs, COFs, etc. with particular attention to the supports containing acid/base sites; metal-enzyme catalysts for chemoenzymatic tandem processes applied in fine organic synthesis and biotechnology. For homogeneous Pd-catalyzed reactions different tandem reactions were considered, i.e. cross-coupling, cyclization, carbonylation, isomerization, alkylation, arylation, etc.

In recent years, with the popularity of smart mobile devices, the interaction between devices and users, especially in the form of voice interaction, has become increasingly important. If smart devices can understand more users' emotional states through voice data, more customized services can be provided for users. This paper proposes a novel machine learning model for speech emotion recognition, which combines convolutional neural networks (CNN), long short-term memory neural networks (LSTM), and deep neural networks (DNN), called CLDNN. To make the designed system can recognize the audio signal closer to the human auditory system does, this article uses the Mel frequency cepstral coefficients (MFCCs) of audio data as the input of the machine learning model. First, the MFCCs of the voice signal is extracted as the input of the model, and the feature values of the data are calculated using several local feature learning blocks (LFLB) composed of one-dimensional CNN. Because the audio signals are time-series data, the feature values obtained from LFLBs then input into LSTM layer to enhance the learning on time-series level. Finally, fully connected layers are used for classification and prediction. Three databases RAVDESS, EMO-DB and IEMOCAP are used for the experiments in this paper. The experimental results show that the proposed method can improve the accuracy compared to other related researches in speech emotion recognition.

As a result of the COVID-19 pandemic, as well as other outbreaks such as SARS and Ebola, bats are recognized as a critical species for mediating zoonotic infectious disease spillover events. While there is a growing concern of increased antimicrobial resistance (AMR) globally during this pandemic, knowledge of AMR circulating between bats and humans is limited. In this paper, we have reviewed the evidence of AMR in bats and discussed the planetary health aspect of AMR to elucidate how this is associated with the emergence, spread and persistence of antibiotic resistance at the human-animal interface. The presence of clinically significant resistant bacteria in bats and wild life has reflective and broad impact on zoonotic pandemic surveillance, disease transmission and treatment modalities. We searched MEDLINE through PubMed and Google Scholar to retrieve relevant studies (n=38) that provided data on resistant bacteria in bats till September 30, 2022. There is a substantial variability in the results from studies measuring the prevalence of AMR based on geographic location, bat types and time. We found all major groups of gram positive and gram negative bacteria in bats which are resistant to commonly used antibiotics. The most alarming issue is- recent studies have increasingly identified Methicillin Resistant Staphylococcus aureus (MRSA), ESBL producing and Colistin resistant Enterobacteriaceae in samples from bats. This evidence of superbugs abundance in both humans and wild mammals like bats, could facilitate a greater understanding of which specific pathways of exposure should be targeted. We believe that these data will also facilitate future pandemic prepareness as well as global AMR containment during the pandemic events and beyond.

Antimicrobial resistance (AMR) due to community carriage of antibiotic-resistant bacteria is highly prevalent in the WHO South-East Asia region. One of the major reasons is the misuse of antibiotics in animal farming practices and at community level, which threatens both human and animal health. However, this multifaceted One Health (OH) problem of antibiotic use (ABU) in poultry farms and respective farmers is not well studied in countries like Pakistan. Therefore, we conducted n OH cross-sectional study in rural Punjab to explore the current practices of ABU in poultry and poultry farmers, associated factors, their healthcare-seeking behaviour and biosecurity practices. We found all the participating farmers using antibiotics for poultry, 60% of which were Colistin sulphate and Amoxicillin trihydrate. The significant consumption of antibiotics in poultry farms (60%) and poultry farmers (50%) was without prescription. Most of the farms (85%) had no wastewater drainage system, causing direct shedding of poultry waste and antibiotic residue in the surrounding environment. Lack of farmers’ education, professional farm training and duration of farming experience were the significantly associated factors with ABU and knowledge of AMR. Our study implies the necessity of an integrated OH-AMR policy with the inclusion of farmers’ education, mass awareness, and strict antibiotic usage guidelines.

Pet ownership is common in modern society. In Portugal, 38% and 31% of all households own, at least, one dog or cat, respectively. Few studies have ascertained the knowledge of pet owners about pet ownership and zoonoses, and none of them was carried out in Portugal. The aim of the present study was to assess household knowledge and practices related to pet ownership and zoonoses in the North of Portugal. A questionnaire was completed by 424 pet owners, during November 2019 to February 2020. Most respondents (97.2%) considered pets as an important part of the family, especially women (p = 0.036); 73.1% allowed their pets free access to indoors; 41.3% denied sharing the bed with their pets and 29% assumed they did it daily; 20.3% reported never kissing their pets/pets licking their faces; 73.6% considered animals as potential sources of diseases to humans, but only 25.9% reported knowing the definition of zoonoses; 96.9% considered important the role of veterinarians in protecting public health. The low level of knowledge of pet owners and the occurrence of high-risk behaviors indicate a need to strengthen communication between veterinarians, physicians, pet owners and the general public to reduce the risk of acquisition and transmission of zoonoses.

In mathematics, the Riemann hypothesis is a conjecture that the Riemann zeta function has its zeros only at the negative even integers and complex numbers with real part 1/2. Many consider it to be the most important unsolved problem in pure mathematics. It is one of the seven Millennium Prize Problems selected by the Clay Mathematics Institute to carry a US 1,000,000 prize for the first correct solution. We prove the Riemann hypothesis using the Complexity Theory. Number theory is a branch of pure mathematics devoted primarily to the study of the integers and integer-valued functions. The Goldbach's conjecture is one of the most important and unsolved problems in number theory. Nowadays, it is one of the open problems of Hilbert and Landau. We show the Goldbach's conjecture is true using the Complexity Theory as well. An important complexity class is 1NSPACE(S(n)) for some S(n). These mathematical proofs are based on if some unary language belongs to 1NSPACE(S(log n)), then the binary version of that language belongs to 1NSPACE(S(n)) and vice versa.

$P$ versus $NP$ is considered as one of the most important open problems in computer science. This consists in knowing the answer of the following question: Is $P$ equal to $NP$? The precise statement of the $P$ versus $NP$ problem was introduced independently by Stephen Cook and Leonid Levin. Since that date, all efforts to find a proof for this problem have failed. Another major complexity class is $\textit{P-Sel}$. $\textit{P-Sel}$ is the class of decision problems for which there is a polynomial time algorithm (called a selector) with the following property: Whenever it's given two instances, a $``yes"$ and a $``no"$ instance, the algorithm can always decide which is the $``yes"$ instance. It is known that if $NP$ is contained in $\textit{P-Sel}$, then $P = NP$. We consider the problem of computing the sum of the weighted densities of states of a Boolean formula in $3CNF$. Given a Boolean formula $\phi$ with $m$ clauses, the density of states $n(E)$ for some integer $0 \leq E \leq m$ counts the number of truth assignments that leave exactly $E$ clauses unsatisfied in $\phi$. The weighted density of states $m(E)$ is equal to $E \times n(E)$. The sum of the weighted densities of states of a Boolean formula in $3CNF$ with $m$ clauses is equal to $\sum_{E = 0}^{m} m(E)$. We prove that we can calculate the sum of the weighted densities of states in polynomial time. Given two Boolean formulas $\phi_{1}$ and $\phi_{2}$ in $3CNF$ with $n$ variables and $m$ clauses, the combinatorial optimization problem $\textit{SELECTOR-3SAT}$ consists in selecting the formula which is satisfiable, where every clause from $\phi_{1}$ and $\phi_{2}$ can be unsatisfied for some truth assignment. We assume that the formula that is satisfiable has the minimum sum of the weighted densities of states. In this way, we solve $\textit{SELECTOR-3SAT}$ with an exact polynomial time algorithm. We claim this problem is a selector of $3SAT$ and thus, $P = NP$.

Photoelectrocatalytic water splitting by using various TiO₂ nanostructures is a promising approach to generate hydrogen without harmful byproducts. However, their effective performance is restricted by some drawbacks such as high rapid electron-hole pair recombination and backward reaction producing H₂O. Thus in this study, the probability of enhancing hydrogen generation rate by adding methanol as a sacrificial agent to the anodic chamber of a two-compartment photoelectrochemical cell is investigated. Herein, one-dimensional elongated TiO₂ nanorods that were fabricated via a facile one-pot hydrothermal method are utilized as potent photoanode. Voltammetric characterizations confirm that addition of alcoholic sacrificial agent has a significant effect on photoelectrochemical properties of TiO₂ nanorods which by adding 10 wt% of methanol, the photocurrent density and photoconversion efficiency increased from 0.8mA.cm^-2 to 1.5mA.cm^-2 and from 0.28% to 0.45%, respectively. The results of photoelectrocatalytic water splitting indicated that the hydrogen generation rate in the presence of methanol was about 1.2 times higher than that from pure water splitting. These enhancements can be attributed to the key role of methanol. Methanol molecules not only inhibit the electron-hole pair recombination but also accelerate the hydrogen generation rate by sharing their hydrogen atoms.

There are increasing calls in education for deeper integration of disciplines and better preparation for the personal and job challenges of a fast-changing and smarter society. Thus, we need to search for new effective didactic strategies. However, current classrooms are isolated. They practically never connect. This hinders the exchange of ideas. It inhibits imitation and recombination, the basic blocks of cultural evolution and innovation. In this paper, we analyze online inter-class tournaments. These are lessons where entire elementary or middle school classes interconnect synchronously and play an educational game. These are new types of academic activities, and only possible thanks to digital communication technology. In this paper, we examine four online tournaments, we analyze how feasible it is to carry them out and the benefits they bring. One tournament is for teaching machine learning and statistics. The second one teaches the conservation of momentum in physics and an engineering optimization challenge. The third tournament is for learning to solve word problems. The fourth one is for teaching natural and sexual selection along with developing statistical and population thinking. We found that these inter-class tournaments are feasible to implement in schools and that they are a promising mechanism to facilitate imitation, recombination, and innovation of teaching strategies.

The fractional Hilbert transform, a generalization of the Hilbert transform, has been extensively studied in the literature because of its extensive use in optics, engineering, and signal processing. In the present work, we aimed to expand the fractional Hilbert transform to a space of generalized functions known as Boehmians. We introduce a new fractional convolution operator for the fractional Hilbert transform to prove a convolution theorem similar to the classical Hilbert transform and also to extend the fractional Hilbert transform to Boehmians. We also construct a suitable Boehmian space on which the fractional Hilbert transform exists. Further, we investigate convergence of the fractional Hilbert transform for the class of Boehmians and discuss the continuity of the extended fractional Hilbert transform.

Emerging infectious diseases are a major threat to biodiversity and an important public health issue. West Nile virus (WNV) is an emerging vector-borne zoonotic arbovirus that is currently broadening its distribution in Europe. The evidence of WNV circulating in resident and migratory species has implications for both animal and public health, and should therefore be studied in depth. An integrated surveillance program, namely in birds, is essential for reducing the risk of infection in human populations within the One Health principles. In the present study, wild birds admitted to wildlife rehabilitation centres in Portugal were sampled. Two-hundred and eight blood samples were assayed serologically to antibodies to WNV, by using a commercial ELISA kit. An overall seroprevalence of 19.6% (95% confidence interval [CI]: 13.7-26.7%) was observed. Antibodies to WNV were detected in 13 (35.1%) different species of wild birds. Accipitriformes (26.7%; 95% CI: 18.5-36.2%) and Strigiformes (26.7%; 95% CI: 14.6-42.0%) were the orders with the highest seroprevalence recorded. There were no statistically significant differences (p = 0.725) between the geographical regions (NUTS II) studied, but statistically significant difference (p = 0.017) was found between gender (male: 34.4%; female: 4.8%). A higher seroprevalence was found in adults (32.1%) compared to juvenile birds (9.3%) (p = 0.014), and age was considered a risk factor to WNV infection in wild birds (odds ratio 1.4; 95% CI: 0.5–4.0). More epidemiological studies are needed in Portugal, since the actual spread of the WNV throughout the country is unknown.

The collaboration of multimodal transport documents is the foundation for conducting multimodal transport operations. Blockchain technology can effectively address trust issues and information sharing difficulties in current multimodal transport document collaboration. However, in current blockchain-based electronic document research, the bottleneck problem lies in the collaboration of multiparty in multimodal transport under the "one-bill coverage system". We design a blockchain platform architecture for multimodal transport, reshaping collaboration processes for different modes of transport based on the blockchain platform. It proposes a collaboration model for multimodal transport under the "one-bill coverage system" and performs model solving and case analysis. The obtained collaboration strategies are embedded into the platform's application layer. Finally, using Solidity language, it writes smart contracts related to multimodal transport under the "one-bill coverage system " and deploys and executes them on the Remix platform.

Introduction: Bovine tuberculosis is a zoonotic disease of considerable impact, especially in livestock countries, which can cause human disease. Despite its importance, Colombia is a country in which few studies analyse its behaviour, and none develop maps using geographic information systems to characterise it. Objective: To describe the temporal-spatial distribution of bovine tuberculosis in Colombia between 2001 and 2019. Methods: Retrospective cross-sectional descriptive study, based on reports by the Colombian Agricultural Institute, of tuberculosis surveillance in cattle on farms in Colombia from 2001 to 2019. The data were converted into databases in Microsoft Access 365®, and multiple epidemiological maps were generated with the Kosmo RC1®3.0 software coupled to shape files of all the country's departments. Results: During the study period, 5,273 tuberculosis cases in bovines were identified in the different departments of Colombia (mean 278 cases/year). Regarding its temporal distribution, the number of cases varied from a maximum of 903 cases (17.12% of the total) in 2015 to a minimum of 0 between 2001 and 2004 and between 2017 and 2019 (between 2005 and 2016, the minimum was 46 cases, 0.87%). Conclusions: GIS is an essential tool for understanding the temporospatial behaviour of zoonotic diseases in Colombia, as is the case of bovine tuberculosis, with its potential implications for Human and One Health.

Abstract: One of the most significant medical advancements of the 20th century was the discovery of antibiotics, which continue to play a vital tool in the treatment and prevention of diseases in humans and animals. However, the imprudent use of antibiotics in all fields of One-Health and concerns about antibiotic resistance among bacterial pathogens have raised interest in antibiotic use restrictions on a global scale. Despite the failure of conventional antimicrobial agents, only about 15 new antibiotics have been introduced clinically since year 2000 to date. Moreover, there have been reports of resistance to some of these new antibiotics. This has necessitated a need to search for an alternative strategy to combat antimicrobial resistant pathogens. Thus, this review compiles and evaluates the approaches—natural compounds, phage treatment, and nanomaterials—that are being used and/or suggested as the potential substitutes for conventional antibiotics. These strategies include those that focus on the enzymes or proteins, as well as the physiology and metabolism of resistant bacteria

Antibiotic Resistance (ABR) is increasing the mortality and morbidity associated with infectious diseases, besides increasing the cost of healthcare, saturating health-system capacity, and adversely affecting food security. Framing an appropriate narrative and engaging local communities through ‘One Health’ approach is essential to complement the top down measures. However, the absence of objective criteria to measure the performance of ABR interventions at community settings make it difficult to mobilize interest and investment for such interventions. An exercise was therefore done to develop an indicator framework for this purpose. An exhaustive list of indicators was developed from experiences gathered through community engagement work in a local panchayat (small administrative area) in Kerala, India, and a consultative process with health, veterinary, environment, and development experts. A prioritization exercise was done, looking at appropriateness, feasibility and validity, by global experts on ABR. A 15-point indicator framework was designed based on the prioritization process. The final set of indicators covers human health, animal health, environment management and Water Sanitation and hygiene (WASH) domains. The indicator framework was piloted in the panchayat(located in Kerala), which attained a score of 34 (maximum 45). The score increased when interventions were implemented to mitigate the ABR drives, indicating the framework is sensitive to change. Simultaneously, the indicator framework was tested in four sites from three other Indian states with different socioeconomic and health profiles, yielding different scores. Those collecting the field data were able to use it with minimal training. To conclude, this indicator framework can help policymakers broadly understand the factors contributing to ABR and measure the performance of interventions they choose to implement in the community

The Galápagos archipelago is a vast reservoir of terrestrial and marine biodiversity and is particularly susceptible to human, animal, and environmental impacts. Climate change, globalization, and the blurring of human-domestic animal-wildlife interfaces are poised to bring new threats and challenges to the region. A One Health perspective that simultaneously considers human, animal, and environmental health is imperative in assessing and mitigating the challenges facing the Galápagos Islands. Many challenges facing biodiversity in the Galápagos Islands can ultimately be linked to anthropogenic factors. In Part I of this review, we reviewed the impacts of invasive species and identified infectious diseases of importance. In Part II of this review, we discuss the impacts of climate change and ocean acidification, and highlight the effects of several direct human activities, including tourism, overfishing, pollution, land use, and human-wildlife conflict. We also review the socioeconomic and political context of the Galápagos Islands, including current challenges in water and energy use, sanitation, and economic stability. We examine the importance of investment in local development for building resiliency and sustainability in the archipelago. Finally, we discuss the impact of the COVID-19 pandemic in the region. Throughout this two-part review, we build a cohesive picture of One Health in the Galápagos Islands by integrating past work, current needs, and emerging threats. We also consider overarching goals for conservation, ecosystem management, and socioeconomic sustainability that have been previously defined by both governmental and non-governmental stakeholders, and identify discrete, implementable, and interdisciplinary recommendations that will facilitate achievement of those goals.

The Galápagos archipelago is a vast reservoir of terrestrial and marine biodiversity, owing in large part to its relatively recent volcanic genesis and colonization by humans. This unique ecological system is particularly susceptible to human, animal, and environmental impacts. Climate change, globalization, and the blurring of human-domestic animal-wildlife interfaces are poised to bring new threats and challenges to the region. A One Health perspective that simultaneously considers human, animal, and environmental health is imperative in assessing and mitigating the challenges facing the Galápagos Islands.In Part I of this review, we provide the historical context for biodiversity in the archipelago; discuss the role of invasive species in habitat destruction, fragmentation, and competition with endemic species; and summarize the established and emerging infectious disease threats. We also discuss the imperative to implement research, surveillance, and preventative measures to identify and manage future threats from a One Health perspective, with a specific emphasis on implications for wildlife health. In Part II, we outline the socioeconomic context of life in the Galápagos Islands, evaluate the current and predicted effects of climate change, and discuss direct anthropogenic factors affecting Galápagos biodiversity, such as tourism, fishing, pollution, and the illegal wildlife trade. We also examine the impact of the COVID-19 pandemic in the region. Throughout this two-part review, we build a cohesive picture of One Health in the Galápagos Islands by integrating past work, current needs, and emerging threats. We also consider overarching goals for conservation, ecosystem management, and socioeconomic sustainability that have been previously defined by both governmental and non-governmental stakeholders, and we identify discrete, implementable, and interdisciplinary recommendations that will facilitate achievement of those goals.

The cubic nonlinearity of graphene oxide (GO) monolayer was characterized by open and closed Z-scan using a nano-second laser of 10 Hz repetition rate with a Gaussian spatial beam profile. The reverse saturable absorption or positive nonlinearity from open Z-scan and valley-peak traces or positive nonlinearity from closed Z-scan was displayed. The reverse saturable absorption could be from a two-photon or two-step excitation process due to the larger absorption in the lower visible and upper UV wavelength region compared with the excitation source. The nonlinear absorption and nonlinear refraction coefficient were estimated to be ~ 2.62x10-8 m/W and 3.9x10-15 m2/W, respectively. This study also reveals the effect of nonlinear absorption on nonlinear refraction traces.

The invariant mass of free particles is used to derive a bound-state equation for several particle atomic systems at rest. This relativistic-kinematic bound-state equation is applied to the hydrogen and helium atoms. The derived equation has the well-known solutions for the single-electron bound states of the hydrogen atom, and the two-electron states of the helium atom. For the hydrogen atom, existence of the two-particle bound states, for which the electron and the proton kinetic energies are of the same order of magnitude, is predicted. The three-particle bound states with the same feature of the kinetic energies can exist in the helium atom. Radiative operators for processes involving the hydrogen two-particle bound states, are obtained. It is discussed that these new two- and three-particle bound states should be optically inactive.

Poultry eggs are a critical source of protein, vitamins, and minerals for people worldwide; facing the current global egg shortage is a significant concern. The shortage results from various factors, including avian flu outbreaks, changes in consumer demand, and supply chain disruptions caused by the COVID-19 pandemic. The economic crisis caused by the pandemic has also impacted the availability and affordability of eggs, particularly in low-income countries. The global egg shortage has implications for public health, particularly for vulnerable populations who rely on eggs for essential nutrients. One Health, an approach that recognizes the interconnectedness of human, animal, and environmental health, provides a useful framework for understanding and addressing the egg shortage. One Health approaches to the egg shortage involve collaboration between agriculture and environmental sectors to address the root causes of the lack and ensure the sustainable production and distribution of eggs. Addressing the global egg shortage requires a multifaceted approach considering the complex social, economic, and environmental factors. One Health perspectives offer a way to understand and address the interconnected factors contributing to the shortage to ensure access to affordable, nutritious eggs for all in a healthy way

In the context of market relations in agriculture in the Kyzylorda region, in order to meet the needs of animal husbandry in complete feed, it is necessary to create a solid forage base. The successful solution to the tasks of increasing the number of livestock and increasing the productivity of animal husbandry in the ecological conditions of the Aral Sea region largely depends on the timely procurement of feed and the transfer of feed production to an industrial basis. It is possible to increase the production of high-quality feeds through the introduction of high-yielding varieties, the use of new resource-saving cultivation and harvesting technologies, the optimal organization of cultivation production processes, and increasing the efficiency of the use of technical means. Of all the harvested types of feeds, alfalfa has the best effect on increasing milks yield and meat gains. The green mass of alfalfa is well-eaten by all farm animals. For example, when feeding cattle, its utilization rate is 92.6%. In terms of protein richness, alfalfa hay surpasses many other feeds, so 100 kg of alfalfa hay contains 11.6 kg of digestible protein, 1.77 kg of calcium, 0.22 kg of phosphorus, and 4.5 g of carotene. In addition, in the conditions of rice crop rotation, according to its biological characteristics, alfalfa (Medicago sativa L.) is considered indispensable in agrotechnical and reclamation relations, especially in saline soils. The economic value of alfalfa lies in its wide ecological plasticity, the ability to grow back quickly after mowing, and high productivity.