Course-based Undergraduate Research Experiences (CUREs) provide active and authentic scientific involvement to tens of thousands of students each year. Through this process, CUREs offer the benefits of increased learning outcomes, improved equity, and increased retention in STEM. During the COVID-19 pandemic, however, research and teaching labs have limited capacity. Some universities are closed for in-person learning altogether, and others are likely to face emergency shut-downs throughout the year. In this setting, the inability to conduct experiments limits a core aspect of CUREs. Without experimentation as a basis for student engagement, interest, and broader relevance, true course-based research this year becomes a major challenge. We suggest that this limitation provides a moment to enhance CUREs with research-enriching learning activities that are obtainable while away from the bench. In this essay we outline a variety of these student-centered activities and review their benefits in terms of student interest, learning, and equity. While useful during emergency teaching transitions during COVID-19, we make the case that these new evidence-based practices for CUREs will also be helpful for the enrichment of research-based learning beyond the current crisis.

Many people in the USA have lost their lives or become addicted to opioids via prescription opioids given for chronic pain. The chronic pain epidemic has emerged due to a convergence of factors, including the medicalization of pain as well as injuries happening in the workplace, in the home, or during recreation. Opioid prescriptions rose precipitously from the late 1990’s through to approximately 2020, and despite public awareness, still are increasing. This review examines literature on integrative approaches to chronic pain as delineated by pain type. The review is organized by the most common causes of chronic pain, and randomized controlled trials, meta-analyses and systematic reviews are extracted for each cause of chronic pain. Several promising interventions may alleviate chronic pain of some causes, and some interventions may work across pain causes. Lowering inflammation through dietary or lifestyle regimens may be a general way of reducing pain. Pain can be alleviated through several adjunctive and integrative treatment approaches, which may serve to lower the need for opioid medication.

Herein, we present the design technique of a resonant rectifier for piezoelectric (PE) energy harvesting. We propose two diode equivalents to reduce the voltage drop in the rectifier operation, a minuscule-drop-diode equivalent (MDDE) and a low-drop-diode equivalent (LDDE). The diode equivalents are embedded in resonant rectifier integrated circuits (ICs), which use symmetric bias-flip to reduce the power wasted for charging and discharging the internal capacitance of a PE transducer. The self-startup function is supported by synchronously generating control pulses for the bias-flip from the PE transducer. Two resonant rectifier ICs, using both MDDE and LDDE, are fabricated in a 0.18 μm CMOS process and their performances are characterized under external and self-power conditions. Under the external-power condition, the rectifier using LDDE delivers an output power POUT of 564 μW and a rectifier output voltage VRECT of 3.36 V with a power conversion efficiency (PCE) of 90.1%. Under self-power conditions, the rectifier using MDDE delivers a POUT of 288 μW and a VRECT of 2.4 V with a corresponding PCE of 74.6%. The result shows that the power extraction capability of the proposed rectifier is 5.9 and 3.0 times higher than that of a conventional full-bridge rectifier.

The aging populations observed across numerous countries worldwide necessitate a thorough exploration of interventions aimed at promoting healthy aging. As individuals age, they undergo significant physiological changes that impact their functional capacity and often necessitate increased reliance on external support systems. Enhancing the autonomy and well-being of elderly individuals emerges as a critical imperative, serving not only individual interests but also broader societal goals. This review investigates various interventions designed to optimize the health and independence of aging populations, offering insights into effective strategies for promoting healthy aging and mitigating the societal burdens associated with an aging demographic.

Pipeline conflicts arising from data dependencies are a common issue encountered in the hardware implementation of layered QC-LDPC decoders. This paper proposes an efficient layered decoding architecture to reduce pipeline conflicts without introducing stall cycles, by reordering the processing order offline and using the patch method based on variable-to-check message. The experimental results on the LDPC code of the IEEE802.16 standard in the OFDM-PON system demonstrate that the proposed architecture has a sensitivity improvement of 0.125 dBm and 0.375 dBm, respectively, compared with our previous work and the method described in the other work.

Antidepressants are among the most used medications in the US, with significant deleterious effects on people’s well-being. At any given time, depression impacts approximately 1 in 10 Americans, causing wide and broad societal costs. Interest is developing for non-pharmacological treatments and preventative measures. We summarize the literature on non-invasive dietary and lifestyle approaches for treating depression, including recent work with the psychedelic treatment of depression. This review aims to inform future research and treatment programs for depression. This review provides an evidentiary summary of integrative therapeutic approaches for depression.

On the 9th March 2020, the first patient with COVID-19 was admitted to ICU in the Royal Gwent Hospital, Newport, Wales. We prospectively recorded the rate of ICU admissions of 52 patients with COVID-19 over 60 days, focusing on the epidemiology of ethnicity and deprivation. Patients were 65% (34 of 52) male and had a median (IQR) age of 55 (48-62) years. Prevalent comorbidities included obesity (52%); diabetes (33%), and asthma (23%). COVID-19 hospital and ICU inpatient numbers peaked on days 23 and 39, respectively – a lag of 16 days. The ICU mortality rate was 33% (17 of 52). Black, Asian and Minority Ethnics (BAME) population represented 35% of ICU COVID-19 admissions (18 of 52) and 35% of deaths (6 of 17). Within the BAME group, 72% (13 of 18) were found to reside in geographical areas representing the 20% most deprived in Wales, versus 27% of Caucasians (9 of 33). Less than 5% of the population within the hospital catchment area are of BAME descent, yet they represent a disproportionately high proportion of patients with ICU admission and mortality suffering from COVID-19. The interplay between ethnicity and deprivation, which is complex, may be a factor in our findings. This in turn could be related to an increased prevalence of co-morbidities; higher community exposure; or genetic polymorphisms.

The following are three successful case studies that affected humanity during the COVID-19 pandemic. The key to their success was their swift adaptability to the new confinement regulations and the unyielding determination of those carrying out their plans. Various extraordinary and prompt efforts were required to make the essential logistical preparations and practice for distance learning a reality. The research activities were also reorganized so the thesis students might carry out a few simple experiments at home under the strict supervision of their advisers and supervisors. The findings revealed that the students who participated in these projects applied all the abilities they had gained before the epidemic. In addition, they included crucial knowledge about the project, problem-based, and research-based learning. Furthermore, because they were the primary implementers of the trials, they learned by planning and performing experiments. The culmination of these efforts was displayed in three scientific publications that were published in index journals with a high level of impact. This latter factor is essential for the prestige and visibility of the university, in addition to the acquisition of financing and grants for scientific research.

Studies have established the crucial role of sleep among the students which plays a significant role in their mood. This study aimed to examine the mood disorders and sleep quality among undergraduate students at the University of Georgia (UG) and comparison between students’ nationality.This cross-sectional study was a self-reported questionnaire comprised of demographics including age, gender, year of study, current location, lifestyle data (Exercise and smoking), the Depression, Anxiety, and Stress Scale (DAS21) and the Pittsburgh Sleep Quality Index (PSQI). We performed a descriptive analysis, and the Chi-square was statistically significant at p<0.05. The prevalence was at a 95% confidence interval (95% CI) as multivariate analysis examined the multicollinearity. The female students were most of the respondents, below the age of 20 years. The student's mean age was 20.20 (SD± 3.0). DAS report presented 72.7% of students with depressive symptoms, 77.8% with anxiety symptoms, and 62.2% had stress. Georgian students were more at risk of having depressive complaints (95% Cl[1.567-3.788]), anxiety (95% Cl[1.612-4.285]), and stress symptoms (95% Cl[1.743-3.831]). There was a strong relationship between the students who experienced poor sleeping patterns and depressive complaints (aOR 0.10). The students who were smokers (aOR 0.39) were more likely to report anxiety symptoms than the students that do not exercise (aOR 1.68). It was observed that students with depressive symptoms, anxiety, and complaints of stress had a significantly high risk of poor sleep quality. Further studies are recommended to curb psychological symptoms of mood changes in association with sleep disorders among students.

Cartoons in the era of digital media are among the most prevalent medium of entertainment for the children, parents also encourage them to view such contents to engage the children which make an area need to be explained exhaustively by adopting new approaches. There are lot of studies in the past conducted to explain the impacts of the cartoons on the children however, it is remarkable fact that there is lack of the studies in the literature which directly address the observation about the above mentioned impacts in view of the teacher’s. This study deals with the educational, emotional, behavioral and Religious etc. impacts of cartoons on kids in view of teachers of the primary schools as they are considered as the one who can observer these impacts in a profound way. of the of Multan. Different areas of impacts have been analyzed in this study by using survey technique and analysis is conducted and presented in the teacher’s views in this study to examine what they feel that how cartoons are effecting the personalities of the children.

Chinese texts often feature a substantial volume of normative content, and their analysis has increasingly become a focal point in recent semantic analysis endeavors. Enhancing the effectiveness of text classification and clustering is pivotal in unveiling the intricate semantics within extensive textual data. Empirical research within the realm of computational social science has underscored the need for improved explanatory power when it comes to general text clustering methods applied to normative texts. This study introduces an innovative hierarchical clustering method that incorporates part-of-speech (POS) features and pioneers a novel semantic network model. It achieves this by amalgamating a POS-based feature weight calculation method with hierarchical clustering techniques. To assess its efficacy, the method is rigorously evaluated across three diverse text datasets, encompassing normative reports, news articles, and social media content. The experimental results unequivocally demonstrate the superior performance of the POS-HC method, surpassing the traditional TF and TF-IDF feature extraction methods in terms of clustering accuracy, and surpassing some existing clustering methods. Furthermore, its classification effectiveness exhibits notable advantages, particularly in the semantic classification of normative texts.

Background and Objectives: Most individuals infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are asymptomatic or have mild symptoms of COVID-19, which usually resolve after few days. Regardless of symptoms, infected people can transmit the virus to others especially on the first days of infection. Quantitative reverse transcription-polymerase chain reaction (RT-qPCR) is used to confirm SARS-CoV-2 infection; some individuals show persistent PCR-positivity after recovering from COVID-19. In this study, 12 individuals who showed persistence of COVID-19 symptoms and of SARS-CoV-2 PCR-positivity were followed-up. Methods: nasopharyngeal samples were collected for SARS-CoV-2 detection by RT-qPCR; clinical and epidemiological data were analyzed. Results: that persistence of SARS-CoV-2 PCR positivity was associated with duration of symptoms (r_s 0.81338), which varied between one and 49 days, with 75% of the individuals reporting symptoms for more than two weeks; 83.33% of cases remained positive after two weeks of onset of symptoms, despite decreases in viral load. Conclusion: neither RT-qPCR test nor a symptom-based approach alone are sufficient to evaluate discontinuation of patient isolation; other factors such as viral loads and symptom severity should also be considered. Additional studies are needed to understand how RT-PCR-positivity is related to symptoms and the risk of viral transmission, and to better support isolation guidelines.

This article summarizes the results of a research conducted to create an intelligent platform supporting small farmers growing vegetables. In Bulgaria, many farmers use relatively small areas for their production. Considering this situation, the platform is designed for regional use, trying to make maximum use of the specific climatic features of the monitored microdistrict. Consequently, special attention is paid to the possibilities of adapting the platform to the specific environment in which the observed plants grow. Thus, the platform is implemented as an agent-oriented system providing needed flexibility. The core of the platform is a personal assistant, which is responsible for tracking the vegetation cycle of the monitored crop and, upon detection of anomalies, preparing warnings to the farmer. The general architecture of the platform is also presented. In a distributed knowledge base, agriculture-specific knowledge are stored. Furthermore, a standardized interface for receiving data from the sensor networks located in the production areas is briefly described. Currently, the platform is being tested for monitoring four varieties of tomatoes grown on the territory of the national research center for potato breeding. Special attention is paid to the measurements carried out. Conclusions have been drawn that will help improve the platform.

Globally, there is massive uptake and explosion of data and challenge is to address issues like scale, pace, velocity, variety, volume and complexity of this big data. Considering the recent epidemic in China, modeling of COVID-19 epidemic for cumulative number of infected cases using data available in early phase was big challenge. Being COVID-19 pandemic during very short time span, it is very important to analyze the trend of these spread and infected cases. This chapter presents medical perspective of COVID-19 towards epidemiological triad and the study of state-of-the-art. The main aim this chapter is to present different predictive analytics techniques available for trend analysis, different models and algorithms and their comparison. Finally, this chapter concludes with the prediction of COVID-19 using Prophet algorithm indicating more faster spread in short term. These predictions will be useful to government and healthcare communities to initiate appropriate measures to control this outbreak in time.

Mental healthcare conditions in India are severely deficient, particularly concerning the living conditions of patients. Post-treatment, numerous individuals with mental illness are abandoned by their families, who may lack the willingness or financial means to care for them. These recovered patients often experience setbacks due to the absence of facilities aimed at developing the skills necessary for reintegrating into society. The lack of separate accommodations for recovered individuals forces them to reside with other patients, worsening their condition. The government is struggling to accommodate and finance the care of recovered patients, affecting those in need of treatment as hospital bed space becomes overwhelmed by the increasing number of cured individuals. Therefore, there is an urgent need for halfway homes. These facilities offer a range of services, including social, medical, psychological, and educational support, alongside housing. The term "halfway houses" reflects their position between fully independent living and highly regulated in-patient or correctional facilities. Following treatment, many patients experience abandonment by their families or encounter difficulties returning home due to memory loss. Recovered patients often live in confined spaces, lacking essential social skills. Therefore, establishing a workspace focused on teaching social and other necessary skills before reintegrating them into society would be a beneficial approach. This would provide a structured environment for individuals who have spent significant time in seclusion, assisting them in developing the skills needed to navigate societal challenges effectively. Recent reports indicate that over 2,000 cured patients are still housed in mental hospitals across the country, according to the NHRC. The NHRC has raised concerns about the situation, noting that all 46 Government Mental Healthcare Institutions in India display very poor and inhumane treatment of patients, leading to the issuance of notices. NHRC visits have revealed deplorable conditions in all 46 mental institutes across the country.

Factors responsible of species distribution were intensively investigated in the past, including response at different spatial scales. The aim of the present research is to review the most relevant factors explaining chironomid species distribution focusing to factors operating at different spatial scales, such as latitude, longitude, altitude, water temperature, dissolved oxygen, nutrients acting at regional, country, water basin extension. Data including chironomid species abundances from different lentic and lotic waters from Italy and other surrounding countries were analyzed with different multivariate methods: partial canonical correspondence analysis and multiple discriminant analysis. Spatial analysis included univariate Moran’I correlograms, multivariate Mantel correlograms and Moran’s Eigenvectors Maps (MEM) calculation. The results confirmed previous conclusions, that is habitat type including different running waters reaches (kryal, krenal, rhthral, potamal) and different lake types is the most significant factor in separating chironomid assemblages and spatial factors act only as indirect influencers..

Purpose: We present a theoretical framework that formalizes and defines the constructs of communicative congruence and communicative dysphoria that is rooted within a comprehensive and mechanistic theory of personality. Background: Voice therapists have likely encountered a patient who states that a therapeutic target voice “isn’t me.” The ability to accurately convey a person’s sense of self, or identity, through their voice, speech, and communication behaviors seems to have high relevance to both patients and clinicians alike. However, to date, we lack a mechanistic theoretical framework through which to understand and interrogate the phenomenon of congruence between one’s communication behaviors and their sense of self. Results: We review the initial notion of congruence, first proposed by Carl Rogers. We then review several theories on selfhood, identity, and personality. After reviewing these theories, we explain how our proposed constructs fit within our chosen theory, the Cybernetic Big Five Theory of Personality. We then discuss similarities and differences to a similarly named construct, the Vocal Congruence Scale. Next, we review how these constructs may come to bear on an existing theory relevant to voice therapy, the Trans Theoretical Model of Health Behavior Change. Finally, we state testable hypotheses for future exploration, which we hope will establish a foundation for future investigations into communicative congruence. Conclusion: To our knowledge, the present paper is the first to explicitly define communicative congruence and communicative dysphoria. We embed these constructs within a comprehensive and mechanistic theory of personality and, in doing so, hope to provide a rigorous and comprehensive theoretical framework that will allow us to test and better understand these proposed constructs.

In this research paper, design and development of pyramidal horn antenna for J-band application is reported. It is particularly designed for 17 dB gain and half beam width about 25 degrees at 6.93 GHz. Horn aperture, horn axial length and distance from the throat of the antenna to aperture are the main design constraints which are calculated and used for the antenna design and simulation. Beam width in E-plane and H-plane horn is calculated and it is 19.18 dB and 22.86 dB respectively. The reported antenna design shows good performance for J-band in radiometry, satellite, and radar applications.

Background: Our study investigates the prevalence and causes of injuries among undergraduate dental students during clinical sessions. Methods: The study was conducted at the Department of Dentistry, National and Kapodistrian University of Athens, focusing on injuries reported from 2021 to 2024. Data were collected through self-reported questionnaires and clinical records. The primary variables assessed included the type of injury, the instrument involved, the clinical procedure being performed, and the immediate actions taken post-injury. Serological testing was conducted on both students and patients to assess the risk of bloodborne pathogen transmission. Results: The findings revealed a high prevalence of injuries, with needles being the most common cause, followed by burs and dental probes. The most frequent injury type was piercing, primarily affecting the fingers. Periodontal treatments, restorative procedures, and endodontic treatments were the main activities leading to injuries. Despite normal medical records for most patients treated by injured students, serological testing showed significant positivity rates for HCV and HBV. It is noteworthy that most injured students demonstrated their commitment to safety by adhering to recommended post-exposure protocols, including wound cleaning, disinfecting, and serological testing. Our study highlights the critical need for enhanced biosafety awareness and training among dental students to reduce injury risks. Conclusions: These findings underline the necessity for integrated safety protocols and continuous education to improve clinical practices and ensure student safety.

Statistical denoising techniques have been well studied, however many challenges still remain. This 9 article focuses on determining the least necessary number of significant samples in a statistical pop-10 ulation sampling, while minimizing the impact on the statistical detection of the fiber Bragg grating 11 (FBG) power spectra. This is achieved by using Bayesian decision making, small population statis-12 tics while excluding false detection. First, we investigate the impact of two-sided sliding window 13 technique applied near the cell under the test. The window size varies from 8 to 60 samples. The 14 considered maximum size of population sampling is connected with the number of wavelength 15 samples within the bandwidth of the symmetrical FBG power spectra peaks. Regarding the sym-16 metry of FBG power spectra peaks and the possible reduction of computational demands, we inves-17 tigate the impact of a one-sided sliding window. This enables to achieve less processing latency for 18 real time applications thus brings benefits to FBG-based fiber optical sensing. Both, two- and one-19 sided small population sampling techniques are then experimentally verified. Detection results are 20 analyzed in depth via calculating detection thresholds by using the small size window sliding along-21 side the waveband. From results achieved, it was found that the normality three-sigma rule does 22 not need to be followed while using the small population sampling. Experimental demonstrations 23 and analyses showed that the proposed concept of denoising and statistical threshold detection 24 based on the sliding window does not depend on the prior knowledge of probability distribution 25 functions of the FBG power spectra peaks level and background noise. We have also found that the 26 thresholds’ adaptability mainly depends on the statistical numerical characteristics of the above ad-27 ditive mixture of the FBG power spectra peaks signals and background noise.

The purpose of this paper is to explore the implementation of Retrieval-Augmented Gen- 14 eration (RAG) technology with open-source Large Language Models (LLMs). For this purpose, a 15 web-based application named PaSSER that integrates RAG with three models - Mistral:7b, 16 Llama2:7b: Orca2:7b, is developed. In its development various technologies are used, including 17 Blockchain for managing and storing assessment results of built-in testing modules. PaSSER em- 18 ploys a set of evaluation metrics for LLMs’ performance - METEOR, ROUGE, BLEU, Perplexity, 19 Cosine similarity, Pearson correlation, and F1 score. The specialized knowledge base is in the smart 20 agriculture domain. As an illustration, the paper presents results and analysis of two tests. First one 21 is assessing the performance of LLMs across different hardware configurations, the other is deter- 22 mining the model that delivers most accurate and contextually relevant responses within the RAG. 23 The paper also discusses the integration of blockchain technology with LLMs to manage and store 24 assessment results within a blockchain environment. The tests revealed that Mistral:7b demon- 25 strates the best results across most of the evaluated metrics. The discussion section comments on 26 technical and hardware considerations that affect the performance of LLMs. Future development 27 will focus in leveraging new larger pre-trained open-source LLMs, exploring different finetuning 28 approaches, and further integration with Blockchain and IPFS.

Fractal array antennas are multiband arrays having ultra wide band and space filling facility. But Side lobe levels and large number of antenna elements are the major designing challenges of these arrays. In this paper, design and analysis of octagonal fractal array antenna is investigated with Morse-Thue fractal density tapering technique (MTFDT). Due to the proposed technique, a remarkable improvement has observed in Side lobe levels and thinning of the elements can also be attained at the various iterations of octagonal fractal array antenna. These arrays are analyzed and simulated by MATLAB-15 programming.

Pharmacists must acquire the necessary knowledge to provide better drug therapy to patients. In other words, educational programs need to facilitate behavioral changes among pharmacists. Therefore, this study aimed to evaluate how the behavior of pharmacists changed after attending a palliative care educational program. We conducted a web-based questionnaire survey examining the behavior of pharmacists regarding palliative care before participating in the program, two months after participating in the program, and eight months after participating in the program, to determine the behavior and changes over time. For all questions, scores were higher at two and eight months after attending the program than before attending the program (P &lt;0.05). In addition, no significant difference was observed between two and eight months after attending the program for all questions (P =0.504-1.000). The knowledge gained from the educational program was used to repeatedly intervene with patients with cancer, to address the various symptoms they experienced and maintain their behavior. The proven effectiveness of this program serves as a stepping stone for a nationwide rollout across Japan’s 47 prefectures.

COVID-19 breakout calls for immediate research explorations. The objective of this study is to perform a bibliometric analysis of all COVID-19-related publications in Science Citation Index Expanded (SCI-EXPANDED) in the early stage of the outbreak. Analysis parameters include performances of authors, institutes, and countries as well as distributions of Web of Science categories, journals, languages, and types of publications. Results show that 32% of total papers were published as editorial materials and an overwhelming production from Chinese research institutes. An association of research indexes with the number of cases was also found.

In this work, two plasmonic structures with two different periodic nanostructures (nanodisk and nanostrip arrays) separated from the gold layer by an ultrathin dielectric Al2O3 layer are proposed, and their optical properties are simulated as 3-dimensional models using COMSOL Multiphysics software tool. The optical responses, such as the amplification of the electric field and the scattering, absorption and extinction cross sections of the two structures, are investigated and compared. The results show that both structures show strong field enhancement in their gap layer, and the structure with the periodic array of metal nanodisks shows stronger field enhancement and larger absorption, extinction, and scattering cross sections in its dipole resonance wavelength, which is defined as a bright plasmonic mode. In addition, some weaker resonant modes are observed for both structures and the reason for their generation is dis-cussed. The analysis of different possible modes in such structures is crucial for their application in various fields.

Background: COVID-19 is a disease of the elderly as 95% of deaths related to COVID-19 occur in people over 60 years of age. Despite the urgent need for a preventive treatment there are currently no serious leads, other than the vaccination. Objective: To find a preventive treatment of COVID-19 in elderly patients. Design: Retrospective case-control study. Setting: Robertsau Geriatric Hospital of the University Hospitals of Strasbourg, France. Patients: 179 elderly patients who had been in contact with the SARS-CoV-2, of whom 89 had tested RT-PCR-positive (COVID-pos) for the virus and 90 had tested RT-PCR-negative (COVID-neg). Measurements: Treatments within 15 days prior to RT-PCR (including antihypertensive drugs, antipsychotics, antibiotics, nonsteroidal anti-inflammatory drugs, proton pump inhibitors (PPIs), paracetamol, anticoagulant, oral antidiabetics (OADs), corticosteroids, immunosuppressants), comorbidities, symptoms, laboratory values, and clinical outcome were all collected using the electronic patient record. Results: COVID-pos patients more frequently had a history of diabetes (P=.016) and alcoholism (P=.023), a lower leukocyte count (P=.014) and a higher mortality rate– 29.2% versus 14.4% – (P=.014) when compared to COVID-neg patients. Patients on PPIs were 2.3 times less likely (odds ratio [OR] = 0.4381, 95% confidence interval [CI] [0.2331, 0.8175], P=.0053) to develop COVID-19 infection, compared to those not on PPIs. No other treatment decreased or increased this risk. COVID-19 patients on antipsychotics (P=.0013) and OADs (P=.0166) were less likely to die. Limitations: retrospective study. Conclusion: PPIs treatment lowered the risk of development of COVID-19 infection, and antipsychotics and OADs decreased the risk of mortality in geriatric patients. If further studies confirm this finding, PPIs could be used preventatively in the elderly in this pandemic context. Moreover, OADS and antipsychotics should be tested in clinical trials.

Motion related human activity recognition using wearable sensors can potentially enable various useful daily applications. So far, most studies view it as a stand-alone mathematical classification problem without considering the physical nature of human motions. Consequently, they suffer from data dependencies and encounter the dimension disaster problem and the over-fitting issue, and their models are never human-readable. In this study, we start from a deep analysis on natural physical properties of human motions, and then propose a useful feature selection method to quantify each feature's classification contribution capability. On one hand, the "dimension disaster" problem can be avoid to some extent, due to the affined dimension of key features; On the other hand, over-fitting issue can be depressed since the knowledge implied in human motions are nearly invariant, which compensates the possible data inadequacy. The experiment results indicate that the proposed method performs superior to those adopted in related works, such as decision tree, k-NN, SVM, neural networks.

The enterprise software sector is experiencing a significant transformation driven by rapid technological progress and evolving business needs. An effective release management process is crucial for the solution providers and customers, as they incorporate the principles of Industry 4.0 and 5.0. With the growing dependence on software solutions and services, ensuring their quality, reliability, and security is highly necessary. The release management process incorporates strategic planning, regression testing, accurate deployment, and continuous monitoring of software updates. However, the rapid advancements in artificial intelligence (AI) and machine learning (ML) create a unique challenge to the release management process. The existing research needs to address the necessary adaptations for Industry 5.0, mainly in product-based software organizations, to the release management process without a change management system. After working with several software solution stakeholders, based on the responses from SaaS project stakeholders, we have presented a revised software release readiness workflow by incorporating a change management module. The preliminary result based on data over a limited period of time indicates that the revised workflow has the potential to improve the management of slippage, particularly by more effectively addressing NFR-related issues, thereby resulting in more predictable and reliable release cycles.

Infection with the malaria parasite Plasmodium, remains a major cause of illness and death world-wide. The development of evasion strategies by the parasite from host immunity and its adaptability to antimalarial drugs has raised the urgency for developing new strategies to combat this disease. One promising avenue is targeting telomeres – sequences found at chromosome termini– and telomerase – the enzyme that catalysis synthesis of telomeres using an intrinsic RNA template. As telomeres shorten critically, cells undergo replicative senescence or apoptosis. Plasmodium, lacking telomerase activity in its human stages, exploits alternative mechanisms, accelerating telomere shortening, aging, and immune evasion. Chemical telomerase inhibitors show promise as antimalarials. In this review, we examine the potential of targeting this system in malaria therapy, with telomerase inhibitors offering a novel approach. A systematic search on PubMed using Boolean techniques identified 246 relevant articles from 1985 to March 31, 2024. After filtering, 43 articles met inclusion criteria, supplemented by snowball sampling. The telomerase inhibitor drug strategy is widely applicable against cancer. However, given the drugability of telomerase and the absolute requirement for active telomere maintenance in the vast majority of parasites including plasmodium, telomerase and telomere maintenance could well represent the Achilles heel of the parasite

Abstract This qualitative research study was aimed at exploring Covid-19 pandemic and its impact via online engagement on disadvantaged undergraduate students resulting in digital divide. The study was supported by the connectivism theory. The methodology approach was an eight year (2014-2022) duration systematic literature review using Educational Resources Information Center (ERIC), Google Scholar, Scopus, and Web of Science (WoS) databases as advanced search strategies. Findings from the SLR provided 56 included relevant publications as confirmed in the Reference Section. Here, findings justified factors responsible for digital divide and the digital divide impacts. Connectivism was suggested as an approach to control digital divide. This study recommends connectivism to control digital divide experienced among disadvantaged undergraduate students in South African universities via numerous supports for free trainings in computer skills, while the government provides low data cost and free Wi-Fi services.

Reducing the levels of toxic chemicals that cause adverse health and environmental impacts is a challenge for the international community. There is a need of a global strategy. Indeed, too often the problems associated to the exposure of chemical substances is recognized a posteriori, in the presence of consequences already observed. The prediction of the likely effects of chemical exposure on human health is based on classical tests with animals, which are time and money consuming, may deviate from an accurate prediction towards humans, and arises ethical concerns. Regulations are now considering the adoption of in silico (or computational) methods, which can be used for prioritizing substances according to the probability to be toxic for the biosphere. Several initiatives have prioritized chemicals, typically based according to some criteria, such as chemicals which may be endocrine disruptors, or persistent, bioaccumulative, or toxic (PBT). However, these initiatives focused on a certain range of adverse properties, and covered a certain number of substances only. We applied a set of largely validated and widely used predictive methods to large collections of chemicals: (i) to about 340,000 with a defined function, and (ii) to about 6 millions, which have been synthetized. The aim of this study is to quantify the putative impact of existing and future chemicals on towards human health, ecological and environment properties. The impact on the environment is the cause of major concern. This is the case of pesticides and hazardous, which is quite expected; however, also pharmacologically active candidate compounds of natural origin may have a high level of ecotoxicity. Pesticides and hazardous are also the categories of higher concern for humans, followed by pharmaceuticals. The pesticides and the hazardous are the categories of higher concern also on the environmental point of view. The results of our analysis could be the basis for the identification of new safety rules.

The purpose of this study was to investigate the relationships among student athlete’s identity and mental health during the COVID-19 pandemic. In addition, this study aimed to clarify the relationship between perceived social support from teammates and mental health in student-athletes. Two studies were conducted to investigate to clarify the mental health states of student-athletes in Japan during the COVID-19 pandemic. In Study 1 conducted in April 2020, the participants were 402 male student-athletes, and examined the relationships among student-athlete’s identity and mental health. The results of correlational analyses indicated that there were significant negative correlations between degree of student-athlete’s identity and depression and sports helplessness. In Study 2 conducted in March 2021, the participants were 136 male student-athletes, and examined the relationship between perceived social support from teammates, student-athlete’s identity and mental health. The results indicated that there was significant correlation among social support, student athlete’s identity and mental health. These results suggested that mental health may be improved if student-athletes are strongly aware of their social identity, which is their social role, when unforeseen events such as the COVID-19 pandemic occur. In addition, social support provided by significant others such as teammates may contribute to the improvement of mental health.

Short-range Internet of Things (IoT) sensor nodes operating at 2.4 GHz need to provide ubiquitous wireless sensor networks (WSNs) with energy-efficient, wide-range output power (POUT) and fully integrated on a single chip for wireless body area networks (WBANs) and wireless personal area networks (WPANs) using low-power Bluetooth (BLE) and Zigbee standards. The proposed fully integrated transmitter (TX) utilizes a digitally controllable current-mode class-D (CMCD) power amplifier (PA) with a second harmonic distortion (HD2) suppression to reduce VCO pulling in an integrated system while meeting harmonic limit regulations. The CMCD PA is divided into 7-bit slices that can be reconfigured between differential and single-ended topologies. Duty cycle distortion compensation is performed for HD2 suppression, and an HD2 rejection filter and a modified C-L-C low-pass filter (LPF) reduce HD2 further. Implemented in a 28 nm CMOS process, the TX achieves a wide POUT range of from 12.1 to -31 dBm and provides a maximum efficiency of 39.8% while consuming 41.1 mW at 12.1 dBm POUT. The calibrated HD2 level is -82.2 dBc at 9.93 dBm POUT, resulting in a transmitter figure of merit (TX_FoM) of -97.52 dB. Higher order harmonic levels remain below -41.2 dBm even at 12.1 dBm POUT, meeting regulatory requirements.

Introduction: At the end of 2019 the Covid-19 pandemic caused a huge amount of restrictions across the world which affected teaching around the world as it was not prepared to move from traditional face-to-face to an online conversion overnight, so the aim of this paper is to determine the changes in undergraduate anatomy teaching strategies post-pandemic compared to pre-pandemic. Methods: A systematic review was conducted based on the PRISMA statement. Data were retrieved from the searches conducted in the different databases, and the articles to be retrieved were selected with the help of the Rayyan platform. Using the OPMER and JBI tools, the quality of evidence was assessed for the selection of the articles included in the review. Results: The teaching of medicine, specifically anatomy, presented serious problems due to the fact that throughout history it has been taught in the classroom by means of cadaveric dissection and when this ceased to be available, new methods arose through the use of digital resources to try to make up for the needs of the lack of dissection laboratories which lost a great deal of content in this restructuring, which have been improving with the passing of the courses taught and the development of new material that has been better adapted to the needs of the students. Discussion: The authors agree that in the future the best way to teach anatomy will continue to be face-to-face dissection without neglecting the strategies developed during this pandemic and to be taken if necessary to restructure curricula in the future to improve teaching.

This paper presents the PEnsemble 4 model, a sophisticated machine learning framework that integrates IoT-based environmental data to accurately forecast maize yield. With the projected significant growth in global maize demand over the next decade, the inherent risks posed by the crop’s dependence on weather conditions necessitate improved prediction capabilities. The PEnsemble 4 model, developed with high accuracy, incorporates comprehensive datasets encompassing soil attributes, nutrient composition, weather conditions, and UAV-captured vegetation imagery. By employing a combination of Huber and M estimates, the PEnsemble 4 model effectively analyzes temporal patterns in vegetation indices, specifically CIre and NDRE, which serve as reliable indicators of canopy density and plant height. In addition, this research significantly contributes to precision agriculture by offering an efficient and sustainable alternative to conventional farming practices through precise yield predictions. Notably, the PEnsemble 4 model enables earlier estimation, advancing the timeline for yield prediction from the conventional day 100 in the R6 stage to day 79 in the R2 stage. This improvement enhances decision-making processes in farming operations. The remarkable accuracy rate of 91% underscores the importance of adopting a multifaceted data approach that harnesses IoT-derived environmental insights. Additionally, the PEnsemble 4 model extends its benefits beyond yield prediction, facilitating the detection of water and crop stress, as well as disease monitoring in broader agricultural contexts. Ultimately, the PEnsemble 4 model establishes a new standard in maize yield prediction, revolutionizing crop management and protection through the synergistic utilization of IoT and machine learning technologies.

During the infection by SARS-CoV-2, the virus is changing infected host cell into its own factory producing new viral particles. As infection progresses, infected cell undergoes many changes in various pathways. One of the events caused by changes is cytokine storm, which leads to the severe symptoms. In this study, we investigated transcriptomic changes caused by COVID-19 disease using RNA-seq data obtained from COVID-19-positive patients and COVID-19-negative donors. RNA-seq data were collected for the purpose of identification of potential biomarkers associated with a different course of the disease. Here, the first datasets of 96 samples were analyzed to validate the methods. The aim of this publication is to report pilot results. In search of potential biomarkers associated with different disease severity, we performed differential expression analysis of human transcriptome, focusing on COVID-19 positivity and symptom severity. Since we detected plenty of potential biomarkers, we performed KEGG enrichment analysis to get better view of altered pathways. Results show, that affected were pathways related to immune processes and response to infection, also multiple signaling pathways, while most of them were also reported to be influenced by SARS-CoV-2 infection in previous studies.

The SARS-CoV-2 virus that causes the COVID-19 disease has wreaked havoc on the world community in terms of every imaginable parameter. The research output on COVID-19 has been nothing short of phenomenal, especially in the medical and biomedical sciences, where the search for a potential vaccine is being conducted in earnest. Much of the advanced research has been distributed in the leading medical journals, including the Journal of the American Medical Association (JAMA), where the latest research is distributed on a daily basis. The purpose of this paper is to provide some perspectives on 44 interesting and highly topical research papers that have been published in JAMA, at the time of writing, within the past two weeks. The diverse topics include public health, general medicine, internal medicine, oncology, paediatrics, geriatrics, and biostatistics.

Due to the rapid development of unmanned aerial vehicles (UAVs) communication technology, UAVs are gradually competing with primary users (PUs) for spectrum resources. Cognitive radio (CR) is a promising solution to meet the needs. Cooperative spectrum sensing (CSS) is considered as an effective method to detect the PU signal and identify available spectrum resources for UAVs in a cognitive UAV network (CUAVN). However, the cooperative mode among multiple UAVs may incur a high overhead, resulting in performance degradation. Therefore, we introduce a differential sequential 1 (DS1), which incorporates a differential mechanism and leverages the sequential idea based on the classical voting rule to enhance cooperative performance and efficiency. In view of this, we formulate three scenarios to characterize the PU activity and introduce a multi-slot cooperative mode within a single UAV to realize cooperative gain. Further, only the information change about the PU status is sequentially calculated in DS1, and combined with a sequential idea, the efficiency of the voting rule is greatly improved. Moreover, the application of support vector machines (SVM) in dynamic selection enables the selection of the most suitable voting rule based on diverse sensing parameters. This dynamic selection process ensures optimal performance and efficiency by adapting the voting rule to the specific characteristics of the given scenario. Finally, simulation results demonstrate that the superiority of our proposal with respect to the detection performance, sample size and the energy efficiency is evident, which proves the high performance of the proposed policy.

Background: The novel Coronavirus SARS-CoV-2 (COVID-19) is a global pandemic with an increasing public health concern. Due to the non-availability of a vaccine against the disease, non-pharmaceutical interventions constitute major preventive and control measures. However, inadequate knowledge about the disease and poor perception might limit compliance. Aim: This study examined COVID-19-related knowledge, practices, perceptions and associated factors amongst undergraduate veterinary medical students in Nigeria. Methods: A cross-sectional web survey was employed to collect data from 437 consenting respondents using pre-tested self-administered questionnaire (August 2020). Demographic factors associated with the knowledge and adoption of recommended preventive practices towards COVID-19 were explored using multivariate logistic regression at P ≤ 0.05.Results: The respondents’ mean knowledge and practice scores were 22.7 (SD ± 3.0) and 24.1 (SD ± 2.9), respectively with overall 63.4% and 88.8% displaying good knowledge and satisfactory practice levels. However, relatively lower proportions showed adherence to avoid touching face or nose (19.5%), face mask-wearing (58.1%), and social distancing (57.4%). Being in the 6^th year of study (OR = 3.18, 95%CI: 1.62-6.26, P = 0.001) and female (OR = 2.22, 95% CI = 1.11-4.41, P = 0.024) were significant positive predictors of good knowledge and satisfactory practices, respectively. While only 30% of the respondents perceived the pandemic as a scam or a disease of the elites (24.0%), the respondents were worried about their academics being affected negatively (55.6%). Conclusion: The study revealed good knowledge and satisfactory preventive practices towards COVID-19 among Nigerian Veterinary students; albeit with essential gaps in the key non-pharmaceutical preventive measures recommended by the WHO. Therefore, there is a need to step up enlightenment and targeted campaigns about COVID-19 pandemic.

Aiming at the development of the application of massive and heterogeneous LEO constellations, the influence of typical perturbation forces on the orbit prediction of LEO satellites at different altitudes is analyzed. Firstly, the main perturbation force model of LEO satellites is introduced. Then experiments for analyzing the influence of orbit prediction on LEO satellites at different altitudes are designed. Finally, the influence of typical perturbation forces on the orbit prediction under different prediction durations by numerical analysis is assessed systematically, and the orbit prediction of LEO satellites with different non-spherical gravitational field orders, ocean tide orders and atmospheric density models were compared and calculated. The research results show that different orders of non-spherical gravitational fields should be considered when the altitude of satellites is different, the reasonable gravitational field orders for LEO satellites at 500km, 1000km, 1500km and 2000km under 1-hour forecast time are 140x140, 80x80, 60x60 and 40x40 orders, the reasonable orders of ocean tide perturbation for 1500km and 2000km satellites are 20x20 orders. Under the 24-hour forecast time, atmospheric resistance has a great influence on the precision of LEO satellites at orbit altitude below 1,000km. The forecast deviation of the LEO satellites orbit at 500km reaches 8751.576m. The difference of orbit precision between different atmospheric density models is in the meter level. The orbit deviation by the Standard Atmosphere 1976 and NRLMSISE 2000 atmospheric models respectively reaches 25.494m. Relevant conclusions provide support for the optimization and selection of dynamical models in high precision orbit determination and fast orbit prediction of LEO satellites.

The COVID-19 pandemic caused by the novel coronavirus emerged in Wuhan City, Hubei province of China at the end of 2019, has radically transformed the lives of people around the world. Due to its fast spreading, it is currently considered as a worldwide health, social and economic concern. The lack of knowledge on this area has encouraged academic sphere for extensive research, which is reflected in exponentially growing scientific literature in this area. However, current state of COVID-19 research reveals only early development of knowledge, while a comprehensive and in-depth overview remains neglected. Accordingly, the main aim of this paper is to fill the aforementioned gap in the literature and provide an extensive bibliometric analysis of COVID-19 research across science and social science research landscape, using innovative and sophisticated bibliometric approaches (e.g. Venn diagram, Biblioshiny descriptive statistics, VOSviewer co-occurrence network analysis, Jaccard distance cluster analysis, text mining based on logistic regression). The bibliometric analysis is based on the Scopus database including all relevant and latest information on COVID-19 related publications (n=16,866) in the first half of 2020. The empirical results indicate that there is still a lack of publications of COVID-19 and its implications in less-explored (non-health) sciences, especially in social sciences. Accordingly, the findings emphasize an importance of a comprehensive and in-depth approach considering different scientific disciplines in COVID-19 research. The understanding of the evolution of emerging scientific knowledge on COVID-19 is beneficial not only for scientific community but also for evidence-based policymaking in order to prevent and address the COVID-19 pandemic.

Background: Alfalfa, the most economically important forage legume worldwide, features modest genetic progress due to long selection cycles and large extent of non-additive genetic variance associated with its autotetraploid genome. Methods: To improve the efficiency of genomic selection in alfalfa, we explored the effects of genome parametrization (as autotetraploid and diploid dosage, plus allele ratios) and SNP marker subsetting (all available SNPs; only genic regions; only non-genic regions) on genomic regressions, together with various levels of filtering on reading depth and missing rates. We used Genotyping by Sequencing-generated data and focused on traits of different genetic complexity, i.e., dry biomass yield in moisture-favorable (FE) and drought stress (SE) environments, leaf size, and onset of flowering, assessed on 143 genotyped plants from a genetically-broad European reference population and their phenotyped half-sib progenies. Results: On average, allele ratio improved the predictive ability compared with other genome parametrizations (+7.9% vs. tetraploid dosage, +12.6% vs. diploid dosage), SNP subsetting offered an advantage compared with any tested subsettings (+3.7% vs. genic regions, +7.6% vs. non-genic regions). However, when focusing on specific traits, different combinations of genome parametrization and subsetting reached better performances. We also released Legpipe2, a SNP calling pipeline tailored for reduced representation (GBS, RAD) medium-sized genotyping experiments.

Introduction. Grilling more and more sophisticated dishes is often a popular activity. Marshmallows are confectionery products popular among children and teenagers worldwide. They are available in many supermarkets ready to be grilled. As such, grilled marshmallows can be a source of exposure to harmful compounds, including carcinogenic polycyclic aromatic hydrocarbons (PAHs). Method. PAHs analysis in marshmallows grilled under different conditions included the dilution stage with deionized water and liquid-liquid extraction with cyclohexane and solid- phase extraction (SPE on silica gel columns). PAH fractions were initially analyzed via planar chromatography (HPTLC-high performance thin layer chromatography) and PAH concentrations were determined via GC-MS/MS (gas chromatography with a tandem mass detector) using the selective reaction monitoring (SRM) mode. This study on the consumption of grilled marshmallows was conducted among approximately 300 children and adolescents. Results. The preliminary results of HPTLC and GC-MS/MS analysis indicated that “raw” marshmallows did not contain PAHs. However, the obtained data suggested a high exposure of young people to carcinogenic PAHs from grilled marshmallows. Carcinogenic BaP was determined in all samples and constituted, on average, 36% of total PAH4. Conclusions. The profile of PAH concentrations in the extracts isolated from various grilled types of marshmallows was very similar (r 2 &gt; 0.8), regardless of the grilling method. Compared to the white sugar confection, the higher concentrations of PAHs were determined in multicolored marshmallows. The lack of social awareness about the exposure to carcinogenic substances is alarming.

As the COVID-19 pandemic progresses, new variants of SARS-CoV-2 continue to emerge. This underscores the need to develop optimized tools to study such variants, as well as new coronaviruses that may arise in the future, and to use them for antiviral drug development. Here we introduce microscale thermophoresis (MST) as a reliable and versatile tool for coronavirus research, which we demonstrate through three different applications described in this report: 1) binding of the SARS-CoV-2 spike receptor binding domain (RBD) to peptides as a strategy to prevent virus entry, 2) binding of the RBD to the viral receptor ACE2, and 3) binding of the RBD to ACE2 in complex with the amino acid transporter SLC6A20/SIT1 or its allelic variant rs61731475 (p.Ile529Val). Our results demonstrate that MST is a highly precise approach to study protein-protein and/or protein-ligand interactions in coronavirus research, making it an ideal tool for studying viral variants and developing antiviral agents. The ability to measure interactions with proteins in their near-native plasma membrane environment is a unique advantage of the MST assay over other available binding assays.

This paper focuses on optimal sensor positioning for monitoring activities of daily living and investigates different combinations of features and models on different sensor positions, i.e., the side of the waist, front of the waist, chest, thigh, head, upper arm, wrist, and ankle. Sixteen features are extracted and the feature importance is measured by using the Relief-F feature selection algorithm. Eight classification algorithms are evaluated on a dataset collected from young subjects and that collected from elderly subjects, with two different experimental settings. To deal with different sampling rates, signals with a high data rate are down-sampled and a transformation matrix is used for aligning signals to the same coordinate system. The thigh, chest, side of the waist, and front of the waist are the best four sensor positions for the first dataset (young subjects), with average accuracy values being greater than 95%. The best model obtained from the first dataset for the side of the waist is validated on the second dataset (elderly subjects). The most appropriate number of features for each sensor position is reported. The results provide a reference for building activity recognition models for different sensor positions, as well as for data acquired from different hardware platforms and subject groups.

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

The European Union's recent decision to renew the authorization for the use of glyphosate until 15 December 2033 stimulates the scientific discussion all around the world regarding its toxicity or otherwise for humans. Glyphosate is a chemical used by millions of tons in the last 50 years worldwide to drying weeds in cultivated fields, greenhouses, roadsides. Concern has been raised in many quarters about the possible presence in the food chain and the consequent adverse effects on health: both aspects that argue in favor of toxicity and those that instead may indicate limited toxicity of glyphosate are here discussed. The great debate that has been generated requires further investigations and field measurements to understand its fate once dispersed in the environment and its concentration in the food chain. Hence the need for validated analytical methods that are available to analysts in the field. In the present review, methods for the analytical determination of glyphosate and its main metabolite, AMPA, are discussed, with a specific focus on chromatographic techniques applied to cereal products. The experimental procedures are explained in any detail, including cleanup, derivatization, and instrumental conditions to give the laboratories involved enough information to proceed with the implementation of this line of analysis. The prevalent chromatographic methods used are LC-MS/MS, GC-MS/SIM, and GC-MS/MS but sufficient indications are also given to those laboratories that wish to use the simpler HPLC-FLD, HPLC-UV, GC-NPD or GC-FPD techniques for screening purposes. Concentrations from literature measured in wheat, corn, barley, rye, oats, soybean, and cereal-based foods are reported together with the regulatory status in various parts of the world and the accumulation mechanism. As for the accumulation in cereals, available data show that glyphosate tends to accumulate more in wholemeal flours than in refined ones, that its concentration in the product strictly depends on the treatment period (the closer it is to the time of harvesting, the higher the concentration) and that in cold climates the herbicide tends to persist in the soil for a long time.

In eastern part of Ethiopia groundnut is very commonly intercropped with sorghum. Even though intercropping of sorghum with groundnut is practiced in the eastern part of Ethiopia the population density at what ratio should not be known. Therefore determining the population ratio is found to be crucial to draw management options. The study was conducted at two locations at Fadis (on station) and Babile (sub- station). Sorghum variety (Teshale) and groundnut (Fetene) were used as planting materials. All agronomic data were collected and analyzed by using GenStat software. Significant different were obtained among the treatments. The research result showed that, there were significance difference for both sorghum and ground nut yield per hectare in the years (2014 and 2015) among treatments. The result over time(in 2014 and 2015) at Fadis and Erer showed that the highest sorghum and groundnut yield per hectare were obtained/harvested from the intra row spacing of 25cmx20cm and 30cmx20cm intercropping sorghum with ground nut system with (1.27 and 1.31) respectively. The highest LER (1.31) and highest GMV (10218.00 ETBr/ha) were obtained from the intercropping of 30cmx20cm (Sorghum & groundnut). Clearly showed that, with intercropping of sorghum and Groundnut, it is possible to produce additional yield of sorghum without significant reduction in groundnut yield. As a result of this, the intra spacing of the main crop (sorghum) 25cm and 30cm and for the subsidiary crop (groundnut) 20cm was recommended for further production in the study areas of eastern Harerghe zone and similar agro-ecologies.

This study aimed to delineate the longitudinal antibody responses to the Pfizer- BioNTech COVID-19 vaccine (BNT162b2) within the Ugandan subset of the Sub-Saharan African (SSA) demographic, filling a significant gap in global datasets. We enrolled 48 participants, collecting 320 specimens over 12 months after vaccination. A validated enzyme-linked immunosorbent assay (ELISA) was used to quantify SARS-CoV-2-specific IgG, IgM, and IgA concentrations (ng/ml) and optical densities (ODs). Statistical analyses included box plots, diverging bar graphs, and the Wilcoxon test with Bonferroni correction. We showed a robust SIgG response within 14 days of the primary vaccine dose, consistent with global data. Remarkably, we observed no significant surge in S-IgG levels following the booster, contrasting trends other global populations. The S-IgM response was transient, and predominantly established thresholds, reflecting its typical early emergence and subsequent decline. S-IgA increased initially but declined six months post-vaccination, in line with the temporal dynamics of mucosal immunity. Eleven breakthrough infections occurred; however, all were asymptomatic, indicating a protective effect from the vaccination regardless of the participants' initial S-IgG serostatus. The Pfizer-BioNTech COVID-19 vaccine elicited strong S-IgG responses in the SSA demographic. However, antibody dynamics distinctly differed from global data highlight the significance of region-specific research and the necessity for customized vaccination strategies.

The Covid-19 pandemic was a challenge for the whole world and it had major secondary effects on humans and environmental health. The viral infection induced, in many situations, secondary bacterial infections, especially enteric infections by destabilizing the balance of the gastrointestinal microbiota. The large-scale use of antibiotics and biocides both for curative and preventive purposes has determined an increase in bacterial resistance and at the same time the possibility of pathogenic microorganisms’ multiplication and their dissemination to natural environments. Wastewater is the main vector of faecal microorganisms that favour their dissemination into natural aquatic ecosystems. The present paper aimed to analyze the effect of Covid-19 pandemic on the microbiological quality of wastewater from sewage treatment plants in Romania and its impact on receiving rivers. In order to highlight different and important areas of Romania, 3 cities from the east, center and west were selected for a microbiological evaluation of their WWTPs influent and effluent between ante-Covid-19 and Covid-19 pandemic peak period, when the Covid-19 pandemic had a direct impact on WWTPs microbial composition. Our study showed a higher contamination with fecal bacteria linked to a higher Covid-19 incidence. The increased usage of pharmaceutical compounds, at their turn, increased the number of resistant bacteria reaching the environment via WWTP effluents.

Global research on the Covid-19 vaccine’s effectiveness is using methods that are misleading the scientific community and public opinion. There is a golden rule in medicine: to measure the effectiveness of an experimental medicine you need to have two groups. The group that will take medicine and the group that will not take medicine. You follow the health status of both groups for a few months and you will get objective results. This is the only proper methodology to verify the effectiveness of a new medicine. Articles cited from 1-5 did not use the gold rule. They develop different kinds of methodologies that all have no statistical significance. On the basis of their methodologies, they conclude that Covid-19 vaccines have a positive effect on public health. By comparing graphs of the intensity of vaccination and the rate of mortality we see that after the period of intense vaccination follows the period of higher excess mortality. Basic statistical data are confirming that Covid-19 vaccines increased the mortality rate.

The online learning necessitated by COVID-19 social distancing limitations has resulted in the utilization of hybrid online formats focused on maintaining visual contact among learners and teachers. The preferred option of video conferencing for academic meetings has become that of Zoom. The needs of one voluntary, democratic, self-reflective university research group—grounded in responses to writing prompts—differed in learning focus. Demanding a safe space to encourage and record both self-reflection and creative questioning of other participants, the private Facebook group was chosen over video conferencing to maintain the concentration on group members’ written responses rather than how they saw themselves (and thought others saw them) on screen. A narrative research model initiated in 2015, the 2020/21 interaction of the group in the year’s worth of Facebook entries, and the yearend feedback received from group participants, will be compared with previous years when the weekly group met in-person. The results in relation to COVID-19 limitations indicate that an important aspect of self-directed learning related to trust that comes from team mindfulness is lost when face-to-face interaction is eliminated regarding the democratic nature of these meetings. With online meetings the new standard, maintaining trust requires improvements to online virtual meeting spaces.

The novel coronavirus disease (COVID-19) pandemic has impacted health and wellbeing globally. To strengthen preventive and clinical care amid this pandemic, technological innovations like artificial intelligence (AI) are increasingly used in different contexts. This bibliometric study aimed to assess the current scholarly development and prominent research domains in applications of AI technologies in COVID-19 research. A total of 105 articles were retrieved from MEDLINE database that emphasized on the use of AI in the context of COVID-19. Most articles had multiple authors with a collaboration index of 7.18. Moreover, most of the articles were produced from the USA (22.86%) and China (21.9%), whereas developing countries were underrepresented among the contributing nations. Furthermore, several research domains were identified, including prevention and control, diagnostics, epidemiological characteristics, therapeutics, psychological conditions, and different areas of data sciences related to COVID-19. The current bibliometric evidence shows the early stage of development in this field, which necessitates equitable applications of AI in COVID-19 research emphasizing on health disparities, socio-legal issues, vaccine development, and applied public health research in this pandemic.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

Course-based Undergraduate Research Experiences (CUREs) in high-enrollment, introductory classes are a 37 potentially transformative approach to retaining more students in STEM majors. We developed and piloted a CURE 38 in the introductory biology courses at the University of Washington. This CURE focuses on analyzing experimental 39 evolution of antibiotic resistance in Escherichia coli and generates data on two topics relevant to clinical practice: 40 compensatory mutations and cross-drug effects. By studying mutations in central cellular machinery that confer drug 41 resistance, students not only gain insight into fundamental cellular phenomena, but also recognize the molecular 42 basis of a medically important form of evolutionary change, connecting genetics, microbiology, and evolution.

The emergence of COVID-19 has prompted an unprecedented scientic publication with the aim of better understanding this new disease. This study assessed the scientic impact and disciplinary priorities of the published papers on the pandemic by comparing epidemiological (EP) and social sciences (SS) research interests. Papers were identified via keywords searching using Google Scholar and Scopus databases. From an initial 1720 papers, we identified 597 relevant articles, of which 347 were for EP researches and 250 for SS studies. We extracted information, such as authors' countries, and research thematic related to EP and SS. The results revealed that most papers were authored by Asian (37.5%), European (30.5%) and American (19.6%) scientists. Only 10.1% and 2.3% of authors were aliated with African and Oceanian institutions, respectively, indicating that the regions most affected by the pandemic mainly contributed to the scientic publications. In total, 26 research themes were recorded from both EP and SS studies. There was a high signicant dierence among themes in both research fields (Chi-square = 1204.3, df = 1, p-value < 0.001). EP papers mostly dealt with clinical trials (54.5%) and diagnosis (53.3%). These papers assessed the incidence and epidemiological characteristics of the disease (incubation period, symptomatic period, recovering or death), testing tests developed, drugs and vaccines used. SS papers were mainly concerned with the sociocultural analyses (78%) and economic impact (55.6%) of the pandemic. They mainly focused on behavioral changes induced by the pandemic and strategies developed to mitigate its impacts. This study highlights the difference between regions and gaps between scientific disciplines concerning the proposed responses to control the pandemic. It is important to promote collaborative and interdisciplinary studies for health emergencies.

Whilst large-scale changes in population behaviour are required to reduce the transmission of the SARS-COV-2 virus, the emergency context is not conducive to the sort of careful communications planning that would normally be required to meet such a task. Rapid strategic communications planning in a pandemic by governments is, however, possible and necessary. Steps include setting up a dedicated communications task force, mobilising partners and resources, developing a creative brief and theory of change and overseeing the creation, testing, roll out and revision of content. In this short guide we argue that a minimum of strategic planning can be undertaken rapidly, and that good use can be made of simple principles of behaviour change, even during pandemics. Our aim here is to provide a blueprint that governments and their partners, especially in low-income settings, can follow to design, coordinate and resource national communications efforts to combat the COVID-19 pandemic immediately and for the longer term.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Interpretive Structural Modelling (ISM) is widely used to understand the complex connections between different components. This study presents a bibliometric overview of ISM research with a focus on its linkages to the Sustainable Development Goals (SDG) and the impact of COVID-19. The study analyzed 1988 publications on ISM published between 2012 and 2021, of which 1202 were directly mapped to the SDG and 59 were related to COVID-19. The study identified key authors, institutions, countries, and journals involved in the research and their linkages to the SDG. The results showed that ISM research is strongly linked to SDG 12 (Responsible Consumption and Production) and SDG 9 (Industry, Innovation and Infrastructure). We also identified influential SDG based on centrality measures like betweenness and eigenvector. The top four countries contributing to ISM publications were India, China, the United Kingdom, and the United States. The most frequently cited journals were Benchmarking: An International Journal, Sustainability, Journal of Modelling in Management, and Journal of Cleaner Production. Four main clusters were identified in the ISM research, including (1) integration with AHP & Fuzzy Logic for promoting sustainability alignment, (2) ISM-based strategy development for various stakeholders, (3) ISM-based decision-making in various fields, and (4) ISM-based risk evaluation. For the first time studies that used ISM approach to understand the epidemiological characteristics of COVID-19 were identified and their key findings were discussed. The study also identified several emerging topics for future ISM research, such as blockchain & IoT, environmental management systems, climate change adaptation, smart cities, and humanitarian logistics and their potential linkages to SDG.

Latin America and the Caribbean (LAC) is one of the worst-hit regions globally by COVID-19 pandemic. Yet, scarce literature exists that examines the research strategy of LAC in facing COVID-19. The present study aims to quantify and assess the production of COVID-19 publications in thirty-two countries in LAC during the first half of 2020. A Scopus/PubMed/LILACS search was performed to retrieve research articles related to COVID-19 published from January 1 to July 31, 2020. Subgroup analysis including only original publications was used to better ascertain the contribution of LAC countries, and standardization measures were applied to comparisons of country-specific contributions. We identified 1291 publications across the region. Overall, most articles in the region were non-original (81.6%), and the most productive countries were Brazil (43.9%), Mexico (9.14%), and Colombia (7.98%). This trend shifted to Chile after the standardization. Among original studies, the most common study design was cross-sectional (25.8%). LAC countries generate articles primarily pertaining to diagnosis and treatment (27.4%). In the subgroup analysis, however, epidemiology and surveillance was the most prevalent research focus (24.1%). LAC countries should perform more research with a higher level of evidence to inform health policy making to ease the burden of COVID-19 in the region.

Nurses have experienced several psychological and work-related issues during the COVID-19 pandemic including pandemic burnout and job burnout. The aim of the study was to examine the impact of social support and resilience on COVID-19 pandemic burnout and job burnout among nurses. We conducted a cross-sectional study in Greece. Study population included 963 nurses. We measured social support, resilience, COVID-19 pandemic burnout, and job burnout with the Multidimensional Scale of Perceived Social Support, Brief Resilience Scale, COVID-19 burnout scale, and single item burnout measure respectively. Nurses received high levels of social support, while their resilience was moderate. Additionally, nurses experienced moderate levels of COVID-19 burnout and job burnout. Increased social support (adjusted beta = -0.075, 95% CI = -0.125 to -0.024) and increased resilience (adjusted beta = -0.399, 95% CI = -0.491 to -0.308) were associated with reduced COVID-19 pandemic burnout. We found a negative relationship between social support and job burnout (adjusted beta = -0.263, 95% CI = -0.405 to -0.121). A similar negative relationship was found between resilience and job burnout (adjusted beta = -0.529, 95% CI = -0.785 to -0.272). Social support and resilience can act as protective factors against COVID-19 pandemic burnout and job burnout among nurses. Policy makers should develop and implement appropriate strategies to improve nurses’ social support and resilience since they are the backbone of healthcare systems worldwide.

We report neutralization titer data against contemporary SARS-CoV-2 sublineages from an ongoing, open-label, phase 2/3 trial of a single 30-μg dose of monovalent Omicron XBB.1.5-adapted BNT162b2 vaccine. Healthy participants had previously received ≥3 doses of a US-authorized mRNA vaccine, with the most recent being a bivalent Omicron BA.4/BA.5-adapted vaccine administered ≥150 days before study vaccination. In this analysis, Omicron XBB.1.5, BA.2.86, and JN.1 serum neutralizing titers were assessed at baseline and 1 month after vaccination in a subset of ≥18-year-olds (N = 40) with evidence of previous SARS-CoV-2 infection. Immunogenicity was also evaluated in a demographically matched group of participants who received bivalent BA.4/BA.5-adapted BNT162b2 in another study (ClinicalTrials.gov Identifier: NCT05472038). The XBB.1.5-adapted BNT162b2 vaccine elicited higher XBB.1.5, BA.2.86, and JN.1 neutralizing titers than those elicited by bivalent BA.4/BA.5-adapted BNT162b2. Overall geometric mean fold rises in neutralizing titers from baseline to 1 month after vaccination were higher among participants who received XBB.1.5-adapted BNT162b2 than those who received bivalent BA.4/BA.5-adapted BNT162b2 for XBB.1.5 (7.6 vs 5.6), slightly higher for JN.1 (3.9 vs 3.5), and similar for BA.2.86 (4.8 vs 4.9). ClinicalTrials.gov Identifier: NCT05997290.

This study investigates the land surface temperature (LST) distribution from thermal infrared data for analyzing the characteristics of surface coverage using the Vegetation-Impervious-Soil (VIS) approach. A set of ten images, obtained from Landsat-5 Thematic Mapper, between 2001 and 2010, were used to study the urban environmental conditions of 47 neighborhoods of Porto Alegre city, Brazil. Porto Alegre has had the smallest population growth rate of all 27 state capitals in the last two decades in Brazil, with an increase of 11.55% in inhabitants from 1,263 million in 1991 to 1,409 million in 2010. We applied the environmental Kuznets curve (EKC) theory in order to test the influence of the economically-related scenario on the spatial nature of social-environmental arrangement of the city at neighborhood scale. Our results suggest that the economically-related scenario exerts a non-negligible influence on the physically driven characteristics of the urban environmental conditions as predicted by EKC theory. The linear inverse correlation R2 between household income (HI) and LST is 0.36 and has shown to be comparable to all other studied variables. Future research may investigate the relation between other economically-related indicators to specific land surface characteristics.

With the rapid evolution of SARS-CoV-2, the emergence of new strains is an intriguing question. This paper presents an evolutionary theory to analyze the mutations of the virus and identify the conditions that lead to the generation of new strains. We represent the virus variants using a 4-letter sequence based on amino acid mutations on the spike protein and employ an n-distance algorithm to derive a variant phylogenetic tree. We show that the theoretically-derived tree aligns with experimental data on virus evolution. Additionally, we propose an A-X model, utilizing the set of existing mutation sites (A) and a set of randomly generated sites (X), to calculate the emergence of new strains. Our findings demonstrate that a sufficient number of random iterations can predict the generation of new macro-lineages when the number of sites in X is large enough. These results provide a crucial theoretical basis for understanding the evolution of SARS-CoV-2.

Molnupiravir, a prodrug known for its broad antiviral activity, demonstrated efficacy in animal models of Covid-19, prompting clinical trials where initial results indicated a significant effect against the disease. However, subsequent clinical studies did not confirm these findings, leading to the rejection of molnupiravir for permanent market authorization in many countries. This report critically assessed 19 studies published in 17 reports that investigated the efficacy of molnupiravir in animal models of Covid-19 with the purpose of determining how well the design of these models informed human studies. We found that the administered doses of molnupiravir in most studies involving animal Covid-19 models were disproportionately higher than the dose rec-ommended for human use. Specifically, when adjusted for body surface area, half of the doses of molnupiravir used in the animal studies were more than twice as high as the human dose. Addi-tionally, the drug was frequently given prophylactically or shortly after SARS-CoV-2 inoculation in these models, in contrast to clinical trials where such timing is not consistently achieved. Furthermore, the recommended five-day treatment duration for humans was exceeded in several animal studies. Collectively, we suggest that these design elements in the reported animal studies contributed to a bias favoring molnupiravir, and thus inflated expectations for its efficacy against Covid-19. Addressing these elements may offer avenues to enhance the clinical efficacy of mol-nupiravir for treatment of Covid-19 that include dose increment, early treatment, and admin-istration by inhalation along with use of molnupiravir in antiviral combination therapy.

The aim of our study was a comprehensive comparative assessment of the effect of consumption of 1 and 2% cholesterol as part of a standard diet with and without regular moderate physical activity on the main biomarkers of lipid and cholesterol metabolism, as well as the intestinal microbiota of male Wistar rats. The animals were randomly divided into 5 groups according to body weight and Open Field test results: Control (n=10), 1% Chol (n=10), 2% Chol (n=10), 1% Chol + RUN (n=10) and 2% Chol + RUN. The cholesterol was additionally added in the amount of 1g or 2g/100g, respectively, to the diet of animals. The rats of experimental groups 1% Chol + RUN and 2% Chol + RUN were subjected to regular (2 days a week) physical activity on a Treadmill. In rats of four experimental groups, when compared to the Control, a response of 39 indicators was revealed. The largest number of changes in biomarkers - 29 (statistically significant, p

The pharmaceutical industry is one of the largest pollutants and generator of toxic solvent resi-dues for the environment and human beings. In the last decade, there has been a huge evolution in the design and development of new environmentally friendly products and processes, in re-sponse to the global environmental concern and the growing demand for products with quality ingredients and manufacturing processes aimed at achieving sustainability. Consumers are looking for products with the benefits of natural products, with sustainable and environmentally friendly formulations with few synthetic molecules as possible. Thus, based on the origins of the pharmaceutical industry, it is important to return to Nature and enjoy the benefits that natural products bring to us. Deep eutectic solvents appear as an alternative to toxic solvents commonly used to extract bioactive compounds. These solvents are considered green solvents because they are made up of natural compounds such as sugars, amino acids, and carboxylic acids. In addition, they are simple to prepare, with an atomic economy of 100%, with attractive physicochemical properties. This paper is a comprehensive review in which is described the main properties, characteristics, and production methods of deep eutectic solvents as well as its application to extract from natural sources bioactive compounds with pharmaceutical interest.

It is known for decades that viruses from the Coronoviridae family can adapt to human-to-human transmission. In 2020, SARS-CoV-2 caused a global pandemic of unprecedented scale imposing the loss of millions of human lives and being at the heart of a global economic crisis. Thus, we overviewed key research advances generated from the identification of the etiological agent to a better understanding of its origin, evolution and factors underlying global spread. Furthermore, we analyze the scientific productivity using the PubMed database. We found that the total number of publications increased more than 8% in 2020 when compared with 2019 or the average publications per year in the previous quinquennial. Remarkably, 86,638 publications related with COVID-19 and SARS-CoV-2 were published in 2020. Furthermore, there was also an increase in 2020 of publications in other major infectious diseases, such as AIDS, tuberculosis, or malaria. This success is likely the result from the vigorous, international, collaborative, and multidisciplinary response by the research community. During 2020 it was demonstrated, that with adequate support, it is possible to boost the rate of scientific progress in infectious diseases. Sustained investment in science will be key to address existing and future pandemics as the human population increases.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding, and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are freely available online, either through web applications or public code repositories.

Fires constitute a significant threat due to the pollutants emitted and the destruction they cause. People who take part in fire-fighting operations must be equipped with appropriate tools, including special clothing that will allow them to work and guarantee safety. One of the threats are compounds from the PAH group, which are characterized by high toxicity and carcinogenicity. Therefore, it is important that the materials used constitute a barrier to contamination. Various materials from which individual elements of special firefighter's clothing are made were tested. Additionally, the importance of height on the possibility of sorption of PAH compounds on a given type of material was analyzed. Based on the results obtained, it was found that the type of material and the zone in which the clothing items are used are important in the sorption processes of pollutants. Data in this area may be important for taking further actions regarding the modification of materials used in special fire brigade clothing and in their cleaning processes.

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

The aim of the study was to examine the use of video-based communication and its association with loneliness, mental health and quality of life in older adults (60-69 years versus 70+ years) during the COVID-19 pandemic. A cross-sectional online survey was conducted in Norway, UK, USA and Australia during April/May 2020, and 836 participants in the relevant age groups were included in the analysis. Multiple regression analyses were conducted to examine associations between use of video-based communication tools and loneliness, mental health and quality of life within age groups, while adjusting by sociodemographic variables. Video-based communication tools were found to be more often used among participants aged 60-69 years (60.1%), compared to participants aged 70 or above (51.8%, p < 0.05). Adjusting for all variables, use of video-based communication was associated with less loneliness (β = -0.12, p < 0.01) and higher quality of life (β = 0.14, p < 0.01) among participants aged 60-69 years, while no associations occurred for participants in the oldest age group. The use of video-based communication tools was therefore associated with favorable psychological outcomes among participants in their sixties, but not among participants in the oldest age group. The study results support the notion that age may influence the association between use of video-based communication tools and psychological outcomes amongst older people.

This paper presents a design and performance analysis of a 10-element 5G massive MIMO antenna array for sub-6GHz mobile handsets, specifically for LTE bands 42 (3400-3600 MHz), 43 (3600-3800 MHz), 48/49 (3550-3700 MHz) applications. The proposed antenna array consists of 10 closely spaced linearly polarized inverted-F antennas with a compact size of 20 × 9 mm2 of a single element. The proposed antenna array provides high gain, high efficiency, and low correlation between the antenna elements, which results in improved channel capacity, increased data rate, and enhanced signal quality. The performance of the antenna array is evaluated in terms of the radiation pattern, gain, efficiency, and correlation coefficient. The simulation and measured results show that the proposed antenna array achieves an approximate peak gain of 3.1 dBi at the resonance frequency, a total efficiency of 65 %, and a low correlation coefficient of 0.06 between the antenna elements. Therefore, the proposed 5G massive MIMO antenna array is a promising candidate for sub-6 GHz mobile handsets, particularly for LTE bands 42/43/48/49 applications.

Purpose: To evaluate nursing leaders' perception towards communication and relationship management competencies while using digital platforms during the COVID-19 pandemic. Background: Communication and relationship management competencies among nursing leaders will ensure healthcare models are successfully implemented. Nursing leaders can achieve effective leadership by mastering these competencies leading to an overall improvement in the quality of nursing care. However, digital platforms have been rapidly evolving in the healthcare ecosystem and have been significant during the battle with COVID-19. It is crucial to ensure that nursing leaders can use digital platforms to communicate and practice efficient management in their op-erations, especially during a crisis when their services are vital. Design: Descriptive, comparative study. Methods: The study was conducted between February to March 2021. A 5-item Linkert-type questionnaire was adopted from the American Organization for Nursing Executives (2005) and was sent to identified nursing leaders in Hamad Medical Corporation through the official email. Results: Two hundred fifty nurse leaders were invited to participate, but only 116 responded positively, translating to a response rate of 46.4%. The male participants represented a larger proportion of 64.10%, while the female was 35.90%. Regarding the questionnaire, the Cronbach alpha was α ˃ 0.987, indicating that all items revealed a sufficient level of internal consistency. The respondents had a minimum of 0 and a maximum of 52.6n in the communication and relationship management items. Influencing behavior, relationship management, and effective communica-tion had the lowest scores, which indicate low competency. The F value in ANOVA analysis was close to 1.0, implying that the null hypothesis is true. The significance value is <0.5 implying that there is a difference in response on effective communication proficiency of nurse leaders. Conclusions: Digital platforms are communication tools that are widely adopted to engage and reach nurses on numerous topics. Nurse leaders should capitalize on their benefits and generate critical discussions. The continued need to research nursing leadership competencies is critical as healthcare continues to change and evolve. Educational institutions and healthcare organizations must understand that nursing leaders should strive for professional development and knowledge acquisition to improve their communication and management.

Modern medicine adopted four presumptions when it evolved from ancient experienced-based mind-body medicine. To understand its failure in finding cures for chronic diseases, we examined four presumptions, and found that statistical population of health properties does not exist for most research purposes, mathematical models are misused to model intensive properties, synthetic drugs are inherently more dangerous than nature-made medicines under their respective application conditions, and reductionist treatments are inferior and inherently dangerous. We found that clinical trials are valid only for research where treatment effect is much stronger than the total effects of all interfering or co-causal factors or errors introduced by misused mathematical models can be tolerated. In all other situations, clinical trials introduce excessive errors and fail to detect treatment effects, or produce biased, incorrect or wrong results. We further found that chronic diseases are manifestation of small departures in multiple process attributes in distinctive personal biological pathways networks, that modern medicine lacks required accuracy for accurately characterizing chronic diseases, and that reductionist treatments are good at controlling symptoms and safe for short term uses. For all stated reasons, as long as modern medicine continues relying on the flawed presumptions, it can never find predictable cures for chronic diseases. By implication, predictable cures to chronic diseases are adjustments to lifestyle, dietary, emotional, and environmental factors to slowly correct departures in process attributes responsible for chronic diseases.

Mechanical properties of cardiomyocytes from different transmural regions are heterogeneous in the left ventricular wall. The cardiomyocyte mechanical environment affects this heterogeneity because of mechano-electric feedback mechanisms. In the present study, we investigated the effects of load upon transmural differences in contraction of subendocardial (ENDO) and subepicardial (EPI) single cells isolated from the murine left ventricle. Various loads were applied to the cells using carbon fiber techniques for single myocytes. To simulate experimentally obtained results and to predict mechanisms underlying the cellular response to change in load, our mathematical models of the ENDO and EPI cells were used. Extent of the transmural gradient in the time course of contractions was independent of the loading conditions where unloaded and heavy loaded (isometric) contractions were examined, but the regional gradient of the relaxation time characteristics tended to decrease when the load decreased. Under auxotonic contractions, time to peak contraction (T_max) was significantly longer in ENDO cells than in EPI cells at low preload. An increase in preload (axial stretch) prolonged T_max in both cell types; however, the prolongation was greater in EPI cells, resulting in a decrease in transmural gradient in T_max at high preload. The [Ca²⁺]_i transient decay time constant was consistent with the greater preload dependency in T_max of EPI cells. Our modified mathematical models reproduced experimental results, suggesting that differences in cooperativity of cross bridges and calcium troponin C complex interactions between the ENDO and EPI cardiomyocytes may contribute to the different cellular responses to stretch, which may provide a decrease in transmural dispersion of cellular shortening in the intact heart.

Two new dimacrolide sesquiterpene pyridine alkaloids (DMSPAs), dimacroregelines A (1) and B (2), were isolated from the stems of Tripterygium regelii. The structures of both compounds were characterized by extensive 1D and 2D NMR spectroscopic analyses, as well as HRESIMS data. Compounds 1 and 2 are two rare DMSPAs possessing unique 2-(3′-carboxybutyl)-3-furanoic acid units forming the second macrocyclic ring, representing the first example of DMSPAs bearing an extra furan ring in their second macrocyclic ring system. Compound 2 showed inhibitory effects on the proliferation of human rheumatoid arthritis synovial fibroblast cell (MH7A) at a concentration of 20 μM.

Computer simulation of normal and diseased human heart activity requires a 3D anatomical model of the myocardium, including myofibres. For clinical applications, such a model has to be constructed based on routine methods of cardiac visualisation such as sonography. Symmetrical models are shown to be too rigid, so an analytical non-symmetrical model with enough flexibility is necessary. Based on previously made anatomical models of the left ventricle, we propose a new, much more flexible spline-based analytical model. The model is fully described and verified against DT-MRI data. We show a way to construct it on the basis of sonography data. To use this model in further physiological simulations, we propose a numerical method to utilise finite differences in solving the reaction-diffusion problem together with an example of scroll wave dynamics simulation.

Less aligned emphasis has been given to the COVID-19 infodemic coordinating with the COVID-19 outbreak. Global profusion of tangled monikers and hashtags has found their ways in daily communication and contributed to backlash against Chinese. Official naming efforts against infodemic should be meet with a fair share of identification. Based on brief critical reviews on previous multifarious naming practices, we punctuate heuristic introspection in scientific conventions and sociocultural paradigms. Infodemiological analysis promises to articulate that people around the globe are divided in their favor stigmatized monikers in the public and scientific communities because of perceptual bias. There is no positive correlation between the degree of infection in their territories and collective perceptual bias to COVID-19. The official portfolio “COVID-19” and “SARS-CoV-2” has not become de facto standard usages, but full-fledged official names are excepted to duly contribute to the resilience of negative perceptual bias and collective behavioral propensities.

Sustainability is a concept shrouded in abstraction. While we have definitions in existence, it is often difficult to explain the concept itself. The current definition of ‘sustainable development’ was given by the Brundtland Commission’s report in 1987. The Earth Summit at Rio in 1992 gave us Agenda 21, an action plan to achieve sustainable development. Now in the 21^st century, philosophers, academicians, and researchers across the globe are paving the way for a new understanding of the term ‘sustainability’, its contextual nature, and its relation to humans, politics, and ecology. This article investigates the origins of the term ‘sustainability’, its derivatives, and the concept of sustainable development. A semantical analysis is carried out to understand the differences between ‘sustainability’ and ‘sustainable development’. Next, the development of the three pillars of sustainability and the application of these concepts in the field of architecture and design is also investigated.

During the Covid 19 pandemic, we saw a huge impact on the lives of individuals in cities. The way people responded was controlled and limited. The lockdown restricted a lot of movements in the cities as well as contained the citizens in their houses. Through a semi-structured interview, the research aims to understand the change in behaviour and response of individuals across various cities. The paper aims to understand how people change their day-to-day life in cities during the pandemic and while the restrictions getting released post the first wave. The paper also understands how the pandemic impacted urban spaces and what value they hold for people. By interviewing individuals from different cities, the data were transcribed and analysed to understand this behavioural change and the attitude of people. The outcome of the research was derived as a concept map through the codes generated during the research.

Human infection caused by the SARS-CoV-2 virus, called COVID-19, is a new pandemic with devastating effects worldwide. Science seeks the rational and systematic explanation of phenomena. In pandemics, decisions on prevention and treatment of people should be consistently taken, supported by scientific knowledge and ethical principles to produce more good than harm. At first, prospective observational studies to systematically collect patient data, correlating protective or therapeutic interventions with outcomes to assess effectiveness and safety, should be prioritized as the most appropriate type of study. The proposed protocol in this article aims to provide doctors with information on the reduction of harm in early COVID-19 patients by applying individualized interventionist or expectant therapeutic strategies, respecting the autonomy and preferences of physicians and patients in clinical decision-making. The evaluation of the clinical status, besides laboratory confirmation of COVID-19, comprises an individualized symptom score for each patient, a global self-perception scale of the severity of the disease, a clinical progression scale developed by the WHO for clinical studies in COVID-19 and, at the first consultation, doctors´ overall impression on the clinical prognosis. The analysis of anonymized data should preferably use descriptive and inferential statistical resources. The case report form is available for free use in the protocol, along with examples of patient informed consent forms for the prescription of off-label medications and authorization to use the data. Their results may be useful to indicate interventions that are candidates for efficacy trials, in randomized controlled trials, with a higher chance of success. It respects the autonomy and preferences of doctors and patients to decide the best options for treatment in uncertain situations. It also allows the gathering of useful information for future more rigorous clinical trials, trying to link science, ethics, and personal clinical experience.

In this paper, we draw on recent experiences from the Young Lives study to discuss some of the ethical and practical challenges facing longitudinal cohort studies in low- and middle-income countries in the time of coronavirus. We argue that COVID-19 has instigated an ‘ethics of disruption’ for social researchers across the world, and for longitudinal cohort studies like Young Lives, this requires navigating three core considerations: first, managing research relationships and reciprocity within an observational study design; second, maintaining methodological continuity and consistency across time; and third, balancing an immediate short-term response to COVID-19 against the longer-term perspective. We refer to the study’s plan to implement a new COVID-19 phone survey to illustrate how the team are navigating this altered ethical terrain.

Introduction: Hypertension is a serious public health problem in Morocco. The objective of this pilot study was to estimate the salt intake of Moroccan adults by measuring 24-hour urinary sodium excretion. Methods: 132 participants were recruited from the central region of Morocco. Sodium, potassium and creatinine levels were measured using the 24-hour urine samples. Additional data included anthropometric measurements and socio-demographic questionnaire. Results: The daily sodium, potassium and creatinine excretions were 2779.1±1334.9 mg, 1350.0±642.8 mg and 820.3 ± 381.2 mg, respectively. Data analysis revealed that 71.2% of the participants had a daily sodium intake more than 2000 mg (5g of salt) recommended by the WHO. The mean of potassium excretion was 1350.0±642.8 mg /day, this average was lower than 3.51g per day recommended by the WHO. Conclusion: Public health measures to reduce sodium and increase potassium consumption in order to decrease the population’s risk of high blood pressure and heart disease are recommended.

In this study, a basic study was performed to analyze the seasonal temperature status of a research room in the Global Environment Research Building where ceiling-embedded indoor units are installed to study the room temperature status of the building as well as to improve its thermal environment. In addition, a direction for improvement of the indoor thermal environment in the winter was proposed through a CFD (computational fluid dynamics) simulation and was proven by an additional experiment. Through the results of this study, it appeared that if the ceiling-embedded indoor unit was installed in the small indoor space without considering the thermal vulnerability of its perimeter boundary, the air temperature of the upper part was greatly different from that of the bottom part in the winter. Hence, in this study, as a means to improve it, convectors were installed to minimize the effect of the external thermal environment and angle-controllable air flowing fans were installed to mitigate the stratification distribution. With such result, it was intended to present the essential data for improvement of the thermal environment as well as conservation of heating energy in the winter for buildings by reviewing the use of the ceiling-embedded indoor unit in the future.

There is evidence that kidney involvement is frequently observed in COVID-19 patients, and can manifest as mild proteinuria to advancing acute kidney injury (AKI). One of the mechanisms is microvascular and macrovascular thrombosis caused by the hypercoagulation phase of the disease. Thromboelastography (TEG) is a valuable examination to detect significant hemostatic abnormalities, including the hypercoagulable state. This study analyzed the coagulation profiles, including TEG parameters, in COVID-19 patients who developed AKI compared to those who did not during their intensive care unit (ICU) stay, to identify predictors of AKI. Our single-center cohort retrospective study involved adult patients of COVID-19 in the ICU of Sardjito Hospital in Yogyakarta, Indonesia between May and September 2021. Patients were divided into two groups of AKI and non-AKI based on 2012 KDIGO definition and the elaboration by Indonesian Society of Nephrology. Variables showing a significant difference in the two groups were then analyzed using univariate and multivariate binary logistic regression. A total of 60 COVID-19 patients were included in the study, and 35% of them developed AKI. Compared to non-AKI patients, those with AKI exhibited a greater prevalence of diabetes mellitus (66.7% versus 35.9%, P = 0.023), higher D-Dimer levels (970 versus 685 ng/mL, P = 0.045), and higher values in TEG parameters of maximum amplitude/MA (74.6 versus 65.9 mm, P = 0.001) and coagulation index/CI (2.3 versus 1.0, P = 0.033). TEG parameter of MA emerged as the sole significant predictor for the development of AKI (OR, 6.33; 95% CI, 1.56 to 25.64). Our study validated the kidney involvement of COVID-19 infection, and showed that diabetes mellitus, high D-Dimer levels, and hypercoagulability serve as prominent risk factors in the development of AKI. Furthermore, TEG parameter of MA exceeding 70 mm is the single independent significant predictor of AKI.

ABSTRACT Background: To date, the COVID-19 pandemic has been the foremost health concern for humankind in the new millennia. This paper aims to describe the related hospitalizations in Italy during the first two years of the health emergency. Design and methods: This is a retrospective, population-based study of Italian hospitalizations for patients diagnosed with COVID-19 during the 2020-2021 period, extracted from the National Hospital Discharge Registry. The outcome variables considered include hospital admissions, costs, and length of stay, among other hospitalization-level variables. Costs were estimated through the charges associated with the Diagnosis-Related Group and Major Diagnostic Categories coding system, plus an additional cost attributed to COVID-19 admissions. To these charges was added an extra cost defined by the ministry of health. Results: In Italy, there were 357,354 hospitalizations for COVID-19 attributed to 298,856 patients in 2020 and 399,043 hospitalizations for COVID-19 attributed to 333,447 patients in 2021. COVID-19 patients faced a transfer rate thrice that of other patients. Hospitalizations were concentrated predominantly in the northern regions, particularly in the first year. Hospitalization rates varied by age in a sine wave pattern, peaking in the youngest and oldest age groups, with mortality rates escalating with age— tending to remain below 3% for those under 44 but surging to 40% in individuals over 75. The financial impact of COVID-19 hospitalizations was substantial, with total costs reaching €3.97 billion in 2020 and €4.99 billion in 2021. Costs per admission and per day also rose, from €11,112 and €807 in 2020 to €12,503 and €844 in 2021, respectively. Excluding the added financial burden of COVID-19, costs would have been notably lower. Hospitalizations involving continuous invasive mechanical ventilation were particularly costly (about 24.000 euros x admission), reflecting the significant resources required for these treatments. Conclusion: Implementing a protective pad around the entire health system that leverages networks of family doctors and nurses, connected in real time to the entire health system, can be crucial. Such a network, tasked with monitoring the local epidemiological situation, protecting vulnerable individuals also through telehealth visits, and establishing a triage system for infections in the initial phase, may effectively help in managing virus spread and protecting hospitals from unpredictable waves of admission demand. Strengthening primary health care could be a decisive factor for the future and enhance the system's resilience in facing new challenges.

Many types of banana (Musa spp.)—one of the most economically important horticultural crops—exist, and their ploidy (diploid, triploid, and tetraploid, usually) and genome types (containing A or/and B genome in most cases) differ. At present, observation and genome type detection are commonly used to identify banana germplasm resources. However, the former is tedious, while the latter cannot distinguish categories below genome types. It is therefore urgent that a simple and effective method for identifying banana germplasm resources is established. We sequenced and analyzed the ribosomal DNA internal transcribed spacer (ITS) sequences of 62 banana germplasm and found that the sequencing peaks, especially the 20 bp region near the 420 bp position (referred to as the “420 bp region”), exhibited relatively recognizable and repeatable polymorphism characteristics. Using the “420 bp region” as a marker, we were able to quickly distinguish bananas belonging to different genome type groups (comprising the AA, AB, AAA, ABB, AAB, ABBB, AAAB, and AAAA groups) or different subgroups in the same genome type group (for example, the Cavendish, Gros Michel, Red, Lakatan, and Ibota Bota subgroups in the AAA group; and the Pisang Raja, Plantain, Pome and Silk subgroups in the AAB group). Moreover, it appeared that Sanger sequencing of ITS could be used for identifying banana hybrid offspring. These results demonstrated that the banana ITS region contains rich genetic information that is useful for genotyping. In general, ITS sequencing simplifies the classification of banana germplasm resources and has potential application in several areas of Musa improvement.

Health services research is a multidisciplinary discipline that aims to improve population health by studying healthcare services' organization, delivery, and financing. Over time, the field has worked to define its boundaries and establish a set of core research topics and methods addressing population wellbeing, access, quality, and cost. Although the influence of health technology is significant, our literature survey on health services research showed that SCs in general—containing their management, cost, and policy—had received little attention. Importantly, our assessment also showed that the system’s readiness to handle supply policy and supply device deficiencies like those encountered during pandemic was hardly ever mentioned. Reduced open areas and water bodies, deteriorating infrastructure, and changes in the biological morphology all affect cities’ uncontrollable and unplanned growth. Urban amenities, facilities, and healthcare services were unevenly distributed due to this unchecked urban population development. In light of this, this research suggests two reliable models for site selection issues for one of Hong Kong’s main hospitals. Levels of uncertainty, infeasibility tolerance, and reliability are taken into consideration. Then, two categories of uncertainty—symmetric and bound-ed—were examined. As a result, the challenge of scheduling in uncertainty has been considered, and potential solutions have been presented using a specified probability distribution function. The paper concludes by introducing the specific justice and health problems and outlining four typical strategies. In order to ensure that medications and other healthcare supplies are produced, distributed, and given to patients, a vast network of systems, components, and procedures must be effectively managed. This research contributes in this regard. Also, its grantee fairness in health systems and the populations health locally, nationally, and globally. It highlights health inequity, advances the measurement of health inequity, and promotes public dialogues on health inequity.

We introduce a series of twisted donor-acceptor (D-A) carbazole-benzophenone based electroactive bipolar derivatives that were synthesized through the reaction of 4-fluorobenzophenone with various partially alkylated 3,3’-bicarbazoles. The comprehensive structural characterization of these compounds is provided. These amorphous materials exhibit suitable glass transition temperatures ranging from 57 to 102 °C and demonstrate high thermal stability, with decomposition temperatures reaching 400 °C. Moreover, the developed materials exhibit elevated photoluminescence quantum yields (PLQY) of up to 75.5% and favorable HOMO-LUMO levels, along with suitable triplet-singlet state energy values. Due to their good solubility and suitable film-forming properties, all the compounds were evaluated as blue emitters dispersed in 4,4’-bis(N-carbazolyl)-1,10-biphenyl (CBP) host for the fabrication of organic light-emitting diodes (OLEDs) in concentration dependent experiments. Among these experiments, the device containing 15 wt% of the guest 4-(9’-{2-ethylhexyl}-[3,3’]-bicarbazol-9-yl)benzophenone demonstrated the best characteristics, achieving maximum brightness of 3581 cd/m2, current efficiency of 5.7 cd/A, power efficiency of 4.1 lm/W and external quantum efficiency of 2.7%.

Coxsackievirus A6 (CV-A6) has emerged as the predominant causative agent of hand, foot, and mouth disease (HFMD) in young children. Since the declaration of coronavirus disease 2019 (COVID-19) as a global pandemic, the incidence of infectious diseases, including HFMD, has decreased markedly. When social mitigation was relaxed during the COVID-19 pandemic in 2022, re-emergence of HFMD was observed in Gwangju, South Korea, and seasonal characteristics of the disease appeared to have changed. To investigate the molecular characteristics of enterovirus (EV) associated with HFMD during 2022, 277 specimens were collected. Children aged under 5 years accounted for the majority of affected individuals. EV detection and genotyping were performed using real-time RT-PCR and nested RT-PCR followed by sequence analysis. EV detection rate was found to be 82.3%, and the main genotype identified was CV-A6. Sixteen CV-A6 samples were selected for whole genome sequencing. According to phylogenetic analysis, all CV-A6 strains from this study belonged to the sub-genotype D3 clade based on VP1 sequences. Analysis of 3D polymerase phylogeny showed that only the recombinant RF-A group was identified. In conclusion, circulating EV types should be continuously monitored to understand pathogen emergence and evolution during the post-pandemic era.

Continuous technological progress places significant demands on the materials used in increasingly modern devices. An important parameter is often the long-term thermal resistance of the material. The use of heat-resistant polymer materials worked well in technologically advanced products. An economically justified direction in searching for new materials is the area of polymer nanocomposite materials. It is necessary to appropriately select both the polymer matrix and the nanofillers best able to demonstrate the synergistic effect. A promising area of exploration for such nanocomposites is the use of organosilicon polymers, which results from the unique properties of these polymers related to their structure. This review presents the results of the analysis of the most important literature reports regarding organosilicon polymer nanocomposites with increased thermal resistance. Particular attention was paid to modification methods of silicone nanocomposites focused on the increase of their thermal resistance related to the modification of siloxane molecular structure and by making nanocomposites using inorganic additives, carbon nanomaterials. Attention was also paid to such important issues as the influence of the dispersion of additives in the polymer matrix on the thermal resistance of silicone nanocomposites and the possibility of modifying the polymer matrix and permanently introducing nanofillers thanks to the presence of various reactive groups. The thermal stability mechanism of these nanocomposites was also analysed.

Cisplatin is a widely used anticancer drug for treating solid tumors, but it is associated with severe side effects, including nephrotoxicity. Various studies have suggested that the nephrotoxicity of cisplatin could be overcome; nonetheless, an effective adjuvant drug has not yet been established. Oleanolic acid acetate (OAA), a triterpenoid isolated from Vigna angularis, is commonly used to treat inflammatory and allergic diseases. This study aimed to investigate the protective effects of OAA against cisplatin-induced apoptosis and necroptosis using TCMK-1 cells and a mouse model. In cisplatin-treated TCMK-1 cells, OAA treatment significantly reduced Bax and cleaved-caspase3 expression, whereas increased Bcl-2 expression. Moreover, in cisplatin-induced kidney injury mouse model, OAA treatment alleviated weight loss in the body and major organs and also relieved cisplatin-induced nephrotoxicity symptoms. RNA sequencing analysis of kidney tissues identified lipocalin-2 as the most upregulated gene by cisplatin. Additionally, necroptosis-related genes such as receptor interacting protein kinase (RIPK) and mixed lineage kinase domain like (MLKL) were identified. In vitro study, the phosphorylation of RIPKs and MLKL was reduced by OAA pretreatment in both cisplatin-treated cells and cells boosted by co-treatment with z-VAD-FMK. In conclusion, OAA could protect the kidney from cisplatin-induced nephrotoxicity and may serve as an anticancer adjuvant.

Aspalathin (ASP) can protect H9c2 cardiomyocytes against high glucose (HG)-induced shifts in myocardial substrate preference, oxidative stress and apoptosis. While the protective mechanism of aspalathin remains unknown, nuclear factor (erythroid-derived 2)-like 2 (Nrf2) has emerged as a key factor for intracellular responses against oxidative stress. Therefore, we hypothesized that aspalathin protects the myocardium against hyperglycemia-induced oxidative damage by up-regulating Nrf2 expression in H9c2 cardiomyocytes and diabetic (db/db) mice. Using an oxidative stress RT2 Profiler PCR array, ASP at a dose of 1 µM was demonstrated to protect H9c2 cardiomyocytes against HG-induced oxidative stress, but silencing of Nrf2 abolished this protective response of ASP and exacerbated cardiomyocyte apoptosis. Db/db mice and their non-diabetic (db/+) littermate controls were subsequently treated daily for 6 weeks with either a low (13 mg/kg) or high (130 mg/kg) ASP dose. Compared to nondiabetic mice the db/db mice presented increased cardiac remodeling and enlarged left ventricular wall that occurred concomitant to enhanced oxidative stress. Daily treatment of mice with ASP at a dose of 130 mg/kg for 6 weeks was more effective at reversing complications than both a low dose ASP or metformin, eliciting enhanced expression of Nrf2 and its downstream antioxidant genes. These results indicate that ASP maintains cellular homeostasis and protects the myocardium against hyperglycemia-induced stress through activation of Nrf2 and its downstream target genes.

Objective. To examine the relationship between experience and knowledge acquired in research methodology (RM) courses and attitudes toward research in a sample of undergraduate psychology students from a public university in Mexico City. Methods. A cross-sectional study was carried out with 261 students. A 10-unit analog scale to assess perceived experience in RM courses and two measures of attitudes toward research were used. Between the two attitude scales, four attitude dimensions were identified: positive appraisal, negative appraisal, meaningless and boring. Four multivariate models were estimated, one for each attitude dimension. Results. A positive correlation was found between learning experiences in RM courses and positive appraisal of research (p < 0.01). Negative associations were also found between RM course experience and two of the three negative research attitudes (p < 0.01). Conclusion. Results highlight the significance of teaching in the knowledge and attitude development of students' research competencies. An approach to teaching RM at the undergraduate level that places more emphasis on encouraging evidence-based practice than on developing and carrying out research projects seems to be a promising subject for study, with implications for changing teaching methods and contents.

The main objective of this study was to compare the removal efficiency of nutrients using Lactuca sativa, Medicago sativa and Phragmites australis in subsurface flow constructed wetlands with horizontal flow. In order to test water quality, fabricated reactors designed and the plants cultivated in the soil while their root were inside the wastewater. A long time study carried out from spring till end of autumn (9 months) in order to evaluate the difference in removal rate based on the seasonal changes. The highest removal rate was during summer which followed by spring and autumn. Thus, the effect of plants on the removal efficiency of organic matter (COD, BOD), TSS and nutrient (P and TN) appeared to be dependent on the seasonal growth. Phragmites australis the most sensitive species in order the removal of nutrient from wastewater.

This paper presents a study about the integration of Piezoelectric Energy Harvesting Systems (PE-EHS) in building envelopes for powering Fiber Bragg Grating (FBG) sensors, enabling efficient and low-consumption monitoring with the objective to leverage Structural Health Monitoring (SHM). The research includes preliminary tests conducted in a real environment to validate the PE-EHS when fully integrated into the façade, capturing mechanical vibrations generated mainly by wind loads. Based on these activities, the final configuration of PE-EHS is defined to provide a complete system for façade monitoring. This integrated system includes the Piezoelectric Generator (PEG), Supercapacitor (SC), Power Conditioner Circuit (PCC), Fibre Optic Sensing (FOS) Interrogator, and the IoT Gateway trans-mitting measurement data within an Internet of Things (IoT) monitoring platform. This configuration is tailored to address the challenges related to the structural integrity of building envelopes. Results demonstrate a potential for a stand-alone solution in the façade sector, but, raising issues for certain limitations, requiring further investigation. In particular, the study emphasizes constraints related to the energy production of PE-EHS for façade integration. It highlights the necessity to carefully consider these limitations within the broader context of their applicability, providing insights for the informed deployment of Piezoelectric Energy Harvesting technology in building envelope monitoring.

Wavelength selective switches (WSSs) are essential elements for wavelength division multiplexing (WDM) optical networks, as they offer cost-effective, high port-count and flexible spectral channel switching. This work proposes a new hybrid WSS architecture that leverages the beam shaping and steering features of uniform silicon nitride (SiN) based end-fire optical phased arrays (OPAs). By introducing beamforming to a WSS system, the spectral channels on the liquid crystal on silicon (LCoS) panel can be tailored and arranged properly, depending on the optical configuration, using the beam control capabilities of OPAs. Combining 3D-FDTD and ray tracing simulations, the study shows that by reducing the input beam dimensions with proper sizing of the OPAs, the WSS design with the null-steering OPAs layout and 4×No switch size features increased spectral resolution. This extensive beamforming study on the steering-enabled layout reveals the acquirement of an even higher input channel number, achieving up to the 8×No WSS scheme with flexible channel routing on the LCoS panel. Such implementation of beamsteerers can unlock an extra degree of freedom for the switching capabilities of hybrid WSS devices. The results show great promise for the introduction of OPAs in WSS systems and provide valuable insight for the design of future wireless communication links and WDM systems.

In this study, we investigated the features of co-infection with SARS-CoV-2 and nonpathogenic strain LEV8 of coxsackievirus A7 or enterovirus A71 for Vero E6 cells and Syrian hamsters. The investigation of co-infection with SARS-СoV-2 and LEV-8 or EV-A71 in the cell model was shown that a competitive inhibitory effect for these viruses were especially significant against SARS-CoV-2. Pre-infection with enteroviruses in animals caused more than a 100-fold decrease in the levels of SARS-CoV-2 virus replication in the respiratory tracts and more rapid clearance of the lower respiratory tract from infectious SARS-CoV-2. Co-infection with SARS-CoV-2 and LEV-8 or EV-A71 also reduced the severity of clinical manifestations of the SARS-CoV-2 infection for animals. Additionally, the histological data illustrated that co-infection with nonpathogenic coxsackievirus decreased the level of pathological changes by SARS-CoV-2 in the lungs. Research into the chemokine/cytokine profile demonstrated that the studied enteroviruses efficiently triggered this part of antiviral immune response, which can be associated with significant inhibition of SARS-CoV-2 infection. These results demonstrate that there exists a strong viral interference between the studied nonpathogenic strain of coxsackievirus A7 or enteroviruses A71 and SARS-CoV-2 pathogenic for humans in vitro and in vivo.

This study aimed to learn disturbance information to effectively control multiple small unmanned surface vehicles (USVs) for marine research purposes at sea. The learned disturbance information was used to investigate the control of multiple USV swarms based on the leading–following formation technique. Numerous studies have already been conducted on swarm control using drones in the air; however, there has been a paucity of studies on swarm control in the sea. Contrary to swarm control in aviation, the fluid density of the sea is high, and the environment is constantly changing; thus, a robot system would be significantly affected by disturbances. This ultimately influences the maintenance of swarm formations and the accomplishment of missions [1,2]. Therefore, it is difficult to control numerous moving objects while maintaining a formation at sea by using the existing aerial drone swarm control technology. To solve this problem, we learned a long short-term memory (LSTM) model with time-series marine environmental data to predict maritime disturbances. Thereafter, the model was applied to a mission-based position control algorithm of each USV constituting the swarm to design a marine unmanned floating vessel swarm control system that can be applied to various marine environments. Specifically, to effectively control numerous small USVs for marine research purposes, ocean currents are learned using the LSTM algorithm, and the predicted ocean currents are used to generate a swarm USV control system for USV formations. In this study, a control system model of several small USVs equipped with two rear thrusters and a front lateral thruster was designed. The LSTM algorithm was learned using the previous ocean current data, and the velocity of the following ocean currents was predicted. The predictions were then used as a system disturbance to determine the thrust of the controller. To measure ocean currents in the sea when each USV moves, the velocity, azimuth, and position (latitude, longitude) data from the GPS mounted on the USV were used to measure the velocity and direction of the hull's movement. Further, the flow rate was measured using a flow rate sensor on a small USV. The USV movement and position were controlled using an artificial neural network-PID (ANN-PID) controller. This study entailed a comparative analysis of the designed USV model results and those generated by the simulator, including the behavior control rule of the USV swarm and the path of the actual USV swarm at sea. It was verified that the effectiveness of the USV mathematical model and behavior control rules. By comparing the movement path of the swarm USV with and without the disturbance learning algorithm and ANN-PID control algorithm applied to the designed simulator, the position error and maintenance performance of the swarm formation were analyzed, and the application results were compared.