As a member of smart materials, electrorheological elastomers (EREs) formed by pre-treating active electrorheological particles are attracting more and more attention. In this work, four Mg-doped strontium titanate particles with spherical, dendritic, flake-like and pinecone-like morphorlogies were obtained by hydrothermal and low-temperature co-precipitation. XRD, SEM, Raman and FT-IR were used to characterize the obtained products. The results showed that the sizes of Mg-doped strontium titanates are about 1.5‒2.0 μm, and the phase structure are dominated by cubic crystal. These Mg-doped strontium titanates were dispersed in a hydrogel composite elastic medium. Then, Mg-doped strontium titanate/glycerol/gelatin electrorheological composite hydrophilic elastomers were obtained with or without electric field. The electric field response properties of Mg-doped strontium titanate composite elastomers were investigated. It concluded that dendritic Mg-doped strontium titanate composite elastomers is high-performance EREs. And the maximum value of energy storage modulus of Mg-doped strontium titanate composite elastomers has achieved 8.70 MPa. This high electrorheological performance of the products is helpful for their applications in vibration control, force transducers, smart structures, dampers, and other fields.

Hydrogen plays an important role in the implementation of Australia’s Net-Zero Strategy. It competes with lithium-ion rechargeable batteries in the electrification of Australian land transportation sector, and can provide an alternative energy storage medium for the greening of the country’s electrical grid system. This paper reviews the role hydrogen plays in the current government’s Net-Zero strategy, and investigates the potential role of other bioenergy sources. It is found that hydrogen and batteries play essentially complementary roles in reducing transport emissions, and that the former energy source is more suited to the operation of long-distance commercial service vehicles than batteries. It is suggested that bioenergy fuels such as biomethane, second generation biofuels and HVO can provide suitable bridging alternatives in the event that Australia’s EV strategy is unable to meet the 2030 target.

Exergy analysis evaluates the efficiency of system components by quantifying the rate of entropy generation. In general, the exergy destruction rate or irreversibility rate was directly obtained through the exergy-balance equation. However, this method cannot determine the origin of the component's entropy generation rate, which is a very important factor in system design and improvement. In this study, a thorough energy, exergy thermoeconomic analysis of a proton exchange membrane fuel cell (PEMFC) was performed, providing the heat transfer rate, entropy generation rate and cost loss rate of each component. The irreversibility rate of each component is obtained by the Gouy-Stodolar theorem. Detailed and extensive exergy and thermoeconomic analyses of PEMFC system have determined that water cooling units experience the greatest heat transfer among the components in the studied PEMFC system, resulting in the greatest irreversibility and thus the greatest monetary flow loss.

The global agricultural sector is increasingly pressured to adopt sustainable practices and reduce its environmental impact. In this context, greenhouses play a crucial role in enabling year-round crop production, ensuring food security, and minimizing reliance on traditional open-field farming. However, the energy consumption associated with greenhouse operations poses a significant challenge to achieving sustainability goals. As a result, there is a growing emphasis on transitioning greenhouses towards near-zero energy consumption. Near-zero energy consumption in greenhouses refers to the ambitious objective of minimizing energy usage to the greatest extent possible while maintaining optimal growing conditions for crops. This goal encompasses reducing energy consumption for heating, cooling, lighting, and other operational needs, as well as exploring renewable energy sources to power greenhouse operations. This review article offers a comprehensive overview of greenhouse energy consumption, with the main goal of analyzing the present situation, identifying key challenges, exploring potential opportunities, and proposing future perspectives for decreasing energy usage in greenhouse environments. As the focus on sustainable agricultural practices grows, the need to reduce energy consumption in greenhouses becomes increasingly important. The review critically examines current technological models and strategies applied in smart greenhouse applications, as well as the monitoring of microclimatic conditions inside the greenhouse, encompassing factors such as temperature, humidity, CO2 levels, soil quality, and crop cultivation. Moreover, it aims to present existing literature that investigates the advancement of greenhouses toward achieving significant reductions in energy consumption.

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.

Aim: This study aimed to understand the role of workforce agility as a coping strategy to curtail the COVID-19 pandemic. Method: The study reviewed and integrated two lines of literature to develop a theoretical framework to help business organizations to respond, adapt, and recover from the COVID-19 pandemic crisis. Results: The results showed that there are several commonalities between the workforce agility literature and the crisis management literature, mostly manifested in the speed of responding to uncertain and unpredictable, adverse events in the business environment. A thorough review of key themes in both kinds of literature led to developing a theoretical framework that links crisis drivers, crisis enablers, crisis capabilities, and response strategy. Workforce agility can be used as a coping strategy to deal with the COVID-19 pandemic crisis. Both kinds of literature evolve to respond to any crisis; the crisis management literature focuses on Meso-level (organizational level) or collective actions to mitigate the crisis, while the workforce agility literature focuses on the Micro-level (individual level). However, the successful response to any crisis requires the synergy of both actions. Future Studies: The results of this research are of prime importance for both researchers and practitioners. Researchers can use the theoretical framework as a baseline for building empirical research design. The current study also sets the context for future researchers who are interested in workforce agility to test the validity of agile work behaviors in real adverse context. It also opens a new stream of debate by deconstructing understudied links between workforce agility, resilience, and crisis management. Mangerial implication: For practitioners to ensure a successful response to any impending crisis, they must develop their employees’ agile behaviors. Practitioners can also redesign their recruitment strategy to select the right individuals with the right agile attributes, abilities, and behaviors to easily alter their behaviors according to the progressing crisis phases. Finally, practitioners can design continual learning interventions to include required agile skills and competencies to prepare their employees for future crises.

Background: Early-stage interventions in a potential pandemic are important tounderstand as they can make the difference between runaway exponential growththat is hard to turn back and stopping the spread before it gets that far. COVID-19 is an interesting case study because there have been very different outcomesin different localities. These variations are best studied after the fact if precisionis the goal; while a pandemic is still unfolding less precise analysis is of value inattempting to guide localities in the early stages to learn lessons of those that pre-ceded them. Methods: I examine three factors that could differentiate strategy: asymptomaticspread, differences in use of the Bacillus Calmette-Guerin (BCG) tuberculosis vac-cine and cloth face masks.Results:Differences in disease progression as well as the possibility of alternativestrategies to prevent COVID-19 from entering the runaway phase or damping itdown later can be elucidated by a study of asymptomatic infection. A study todemonstrate not only what fraction are asymptomatic but how contagious they arewill also inform policy on universal mask wearing. Conclusions: While a COVID-19 outbreak is at a level that makes accurate trace-and test possible, investigation of asymptomatic transmission is viable and shouldbe attempted to enhance understanding of spread and variability in the disease aswell as policy options for slowing the spread.

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.

There are two contrary opinions regarding the risk if mainland China (MC) moves away from its zero-COVID policy. Some experts think the risk shall be much lower than influenza as per MC’s own COVID-19 case fatality rate (CFR), while some other experts think the risk shall be much higher than influenza as per the COVID-19 CFRs of other regions. We elucidate here that this and multiple other striking differences in the CFR between various scenarios all support and substantially resulted from the view that good IDM is highly powerful to mitigate COVID-19, where IDM (isolation-disinfection-maintenance) means isolation of COVID-19 cases from other people, disinfection of their living environments, and health maintenance (e.g., rest, nutrition, breathing). The high effect of good IDM is also supported by the theoretic functions of IDM in minimizing co-infections and maintaining body functions, and the fact that all the 505 COVID-19 deaths reported in MC in 2022 before May 5 died directly of severe underlying diseases with COVID-19. Although it is tough for people in poverty to obtain good IDM, good IDM can be feasible at home for the most mild cases and in hospitals for the most severe cases. Therefore, good IDM can be crucial to mitigating COVID-19 worldwide. It also suggests that the risk for China to end its zero-COVID policy depends on China’s control policies or measures. Based on the effect of IDM, the cautious co-existence policy was proposed for COVID-19 control. This policy could reduce the whole death toll in MC because good IDM is non-specific and can reduce deaths of various other diseases. The cautious co-existence policy (non-specific) and the vaccination policy (specific) aid each other to mitigate COVID-19, and they cannot replace each other. Those who are qualified in health for vaccination should be vaccinated against COVID-19 timely.

A COVID-19 disease threatens the population and the economies of the countries significantly. Till now, this pandemic has affected 215 counties or territories. Unavailability of vaccine is the primary concern for the society. To avoid the spread of this disease, social isolation must be preserved and the inter and intra-population movement must be minimized. To reduce the possibility of transmission, the categorization of regions based on susceptibility to COVID-19 infection is a must.Due to the unavailability of a large amount of paper collection for this novel COVID-19 diseases, we used current literature available on a COVID-19 susceptibility of the diabetic patient, human reproductivity, hemodialysis patient’s, pregnant women and meteorological factors and geographical location. Countries in the cold region are more susceptible to the risk of COVID-19 transmission. There was no evidence of the spread of this disease from non-respiratory bodies. Diabetic patients and pregnant women were found to be more susceptible to COVID-19 infection. Anosmia was observed in the majority of the COVID-19 infected cases in European countries. No evidence indicates COVID-19's impact on the human reproductive system explicitly. No cases of vertical transmission of this disease have been observed until now. All the studies available till now is the small scale study. Correlation with something always does not mean causation. There are certain factor like pollution level, temperature Diurnal temperature range, geographical factor, humidity, pollution level, wind speed, population density, medical healthcare facilities social and political factor plays a critical role in transmitting the SARS-COV-2 virus. Besides the adverse effects, it has taught us to shed our selfish goals and to promote the welfare of all.

Hypertension is a global public health challenge, with a high prevalence across various regions and significant implications for cardiovascular risk. This article reviews the effectiveness of herbal medicine as a potential therapeutic approach for hypertension, offering an alternative or complementary solution to conventional pharmacological treatments. It highlights several natural agents that have demonstrated efficacy in lowering systolic blood pressure (SBP) in clinical and meta-analytical studies. The methodology involved a systematic review of articles that discuss herbal therapeutics for hypertension, focusing on their efficacy compared to placebo and standard treatments. The findings suggest that certain nutraceuticals, such as garlic, hawthorn, and CoQ10, can significantly reduce SBP, presenting a viable option for managing hypertension. This review underscores the need for further research to validate these findings and optimize herbal treatment strategies, potentially expanding the use of these natural products in clinical practice. The article aims to increase awareness among medical professionals and patients about the benefits and applications of herbal medicines in treating hypertension.

The spread of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already taken on pandemic proportions, affecting over 150 countries in a matter of months. Even though containment measures in China have reduced new cases by more than 90%, this reduction is not the case elsewhere, as the US, Spain and Italy have come off worse-off by the spread of the virus, and there is serious concern regarding the national health systems' capacity around the world and Africa, in particular, to effectively respond to the needs of infected patients who require intensive care for the COVID-19 illness. As a result, authorities around the world have resorted to the lockdown strategy to curb the spread of the virus. Therefore, the study aimed at investigating the effect of the lockdown strategy in curbing the spread of the COVID-19 virus in Nigeria. Consequently, the study found daily relative risk increase in cases, and daily relative risk increase in mortality. Also observed is the growth in cases in areas where active measures were not taken. Further, halt in business activities has rendered many penniless and unable to provide for themselves basic amenities. The study recommends that there is need to implement community-level measures of social distancing which may include closing schools, need for individuals with COVID-19 case or respiratory symptoms be properly taken care of, trace and quarantine those who must have come in contact with affected persons and introducing stay at home palliatives for the general public.

In the context of the COVID-19 pandemic, thousands of healthcare workers (HCWs) infected with COVID-19 have lost their lives worldwide. At the early stage of the epidemic, when COVID-19 was still not considered as a pandemic, a large number of Chinese HCWs were infected. Officials reported that more than 3,000 HCWs in Hubei contracted the virus at the early stage of the outbreak due to limited knowledge of the virus. Following reports of overloaded local hospitals, more than 42,000 medical staff, including those from the military, were dispatched to Hubei from across the country. At the peak of the fight, one in 10 intensive care medics in China were working in Wuhan. During fighting against COVID-19 in China, although a large number of HCWs were infected by SARS-CoV-2 in the early stages of the epidemic, the timely adoption of measures indicated that, a faster rate of diagnosis could be achieved, patients were isolated in-time, HCWs’ safety was prioritized, training on basic protective knowledge and unified management of HCWs was strengthened, and effective protective measures were implemented. This resulted in the accomplishment of zero SARS-CoV-2 infection among the 42,632 members of the national medical teams sent to Hubei, and the number of COVID-19 cases among HCWs in local hospitals also significantly decreased, thereby indicating that hospital-acquired infections of SARS-CoV-2 among HCWs are fully preventable.

This paper introduces a novel framework for zero-shot learning (ZSL), i.e., to recognize new categories that are unseen during training, by distilling knowledge from foundation models. Specifically, we first employ ChatGPT and DALL-E to synthesize reference images of unseen categories from text prompts. Then, the test image is aligned with text and reference images using CLIP and DINO. Finally, the predicted logits are aggregated according to their confidence to produce the final prediction.Experiments are conducted on multiple datasets, including CIFAR-10, CIFAR-100, and TinyImageNet. The results demonstrate that our model can significantly improve classification accuracy compared to previous approaches, achieving AUROC scores above 96\% across all test datasets. Our code is available at https://github.com/1134112149/MICW-ZIC.

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.

Objectives to assess COVID-19 mortality rates per country population. To determine what if any independent country-specific variables from 9 different databases were correlated. Design population based retrospective cohort study. Setting analysis of global COVID-19 treatment and containment strategies using data from 9 worldwide websites. Participants 108 countries worldwide. Interventions none. Main Outcome Measures were COVID-19 death rates per country population analyzed by univariate and multivariate analysis. The main outcome parameters were to determine if there are any correlations between the percentage of countrywide COVID-19 deaths/population by the countries’ percent vaccinated. Secondary outcome measures include the effect of other independent variables on COVID-19 death rates per country population including: health expenditures per capita, annual income per capita, COVID-19 tests per 1000 people, stringency index (a measure of each countries containment strategies), hydroxychloroquine score (a measure of each countries use), ivermectin score (a measure of each countries use), hypertension, obesity, diabetes, and specific countries and geographic locations. Results COVID-19 vaccination rates ranged from 0-99% in 108 countries. Univariate analysis demonstrates the following independent variables to correlate with COVID-19 deaths/population (correlation coefficient, p value): countrywide COVID-19 vaccination rates (+0.2936, p=0.002); healthcare costs per capita (+0.3212, p=0.0007), income per capita (+0.3051, p=0.0013), COVID-19 tests per 1000 population (+0.6981 p=0.0307); stringency index (+0.3098, p=0.0011); hydroxychloroquine index (-0.1337, p=0.0678); and ivermectin index (-0.1383, p=0.1535). Conclusions Increasing rates of COVID-19 vaccination are associated with increase COVID-19 death rates per country population (p=0.002). Other variables associated include healthcare costs per capita (+0.3212, p=0.0007), income per capita (+0.3051, p=0.0013), COVID-19 tests per 1000 population (+0.6981 p=0.0307); and stringency index (+0.3098, p=0.0011).

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 modern supply chain (SC) is growing in terms of data, devices, users, and stakeholders, which introduced new security challenges and threats, especially with the reliance on centralized servers or cloud platforms. In addition, increased trust among system participants exposes the SC to a higher risk of vulnerabilities which require strong security measures. This article proposes a hybrid security framework for SC systems, BC-DRLzSC, that integrates Blockchain (BC) and Deep Reinforcement Learning (DRL) designed to operate in a zero trust (ZT) environment. In particular, we propose a decentralized BC-based approach integrated with smart contracts to manage system participant registration and authentication and to control access to system resources. BC-DRLzSC adopts a ZT architecture to reinforce SC security, which can be achieved with an advocate to verify each entity’s trustworthiness before granting or retaining access to system resources. Incorporating the ZT architecture, with BC and DRL, can potentially and significantly bolster SC system security. DRL is employed to develop a proactive attack detection model that continuously monitors the incoming traffic from authenticated nodes within the network and predicts any malicious actions. Finally, we evaluate the performance of our proposed DRL solution using the NSL-KDD dataset.

To decrease privacy risks, consumers may choose to misrepresent when they are asked to offer personal information. This paper examines the impact of consumer misrepresentation on a monopolistic firm and consumers with an economic model. The results show that consumer misrepresentation may benefit the firm but hurt consumers. In addition, consumers misrepresentation may encourage the firm to provide higher personalized service level in certain scenarios, such as, when the unit cost of personalized service is low. Thirdly, when consumers misrepresent, and the firm only covers part of the market, a greater unit value of consumer’s privacy information will reduce the firm’s profit, but a greater unit cost of personalized service increases the firm’s profit.

We generate numerically on a lattice an ensemble of stationary metrics, with spherical symmetry, which have Einstein action S_E « ħ. This is obtained through a Metropolis algorithm with weight exp(-β²S_E²) and β » ħ^-1. The squared action in the exponential allows to circumvene the problem of the non-positivity of S_E. The discretized metrics obtained exhibit a spontaneous polarization in regions of positive and negative scalar curvature. We compare this ensemble with a class of continuous metrics previously found, which satisfy the condition S_E=0 exactly, or in certain cases even the stronger condition R(x)=0 for any x. All these gravitational field configurations are of considerable interest in quantum gravity, because they represent possible vacuum fluctuations and are markedly different from Wheeler's ''spacetime foam''.

Background: Studying anxiety, stress and the selection of coping strategies in the COVID-19 pandemic is necessary to minimize the adverse changes associated with the risk of infection and the consequences of the disease. Objective: To investigate the level of anxiety, stress perception and coping strategies in relation to the presence of illness. Material and Methods: The anonymous cross-sectional online survey was conducted among 3950 university students of northeastern Poland (1822), Lithuania (232) and the Russian exclave of Kaliningrad (1896). Due to the almost identically applied anti-epidemic measures, the respondents were treated as a unified group. The State-Trait Anxiety Inventory, Perceived Stress Scale-10 and Coping Orientations to Problems Experienced questionnaires were used. Results: Among 1212 men and 2738 women, COVID-19 was diagnosed in 348 (28.7%) and 1020 (37.3%) individuals, respectively, according to the clinical protocol. The prolonged nature of the process and the longer consequences of the disease were indicated by an increase in anxiety levels. Conclusions: The risk of possible infection and coping with illness required the adoption of active anti-stress strategies, which was observed regardless of going through the disease. Convalescents differed from non-diseased individuals in having higher levels of concern about their own emotions and their more frequent turn to religion, notably among the females. The repertoire of strategies among women was broader, with elevated levels of helplessness and avoidance seen as integral strategies.

There is an urgent need to identify effective therapies for COVID-19. The SARS-CoV-2 host factor protease TMPRSS2 is required for viral entry and thus an attractive target for therapeutic intervention. In mouse, knockout of tmprss2 led to protection against SARS-CoV-1 with no deleterious phenotypes, and in human populations genetic loss of TMPRSS2 does not appear to be selected against. Here, we mined publicly available gene expression data to identify several compounds that down-regulate TMPRSS2. Recognizing the need for immediately available treatment options, we focused on FDA-approved drugs. We found 20 independent studies that implicate estrogenic and androgenic compounds as transcriptional modulators of TMPRSS2, suggesting these classes of drugs may be promising therapeutic candidates for clinical testing and observational studies of COVID-19. We also note that expression of TMPRSS2 is highly variable and skewed in humans, with a minority of individuals having extremely high expression. Combined with literature showing that inhibition of TMPRSS2 protease activity reduces SARS-CoV-2 viral entry in human cells, our results raise the hypothesis that modulation of TMPRSS2 expression is a promising therapeutic avenue for COVID-19.

The decarbonization of the built environment, both in new construction and renovation, is crucial to mitigate its relevant impact on climate change and achieve the Paris agreement goals. This study presents a systematic LCA-based methodology to assess the whole life carbon emissions of buildings, applied to a proposal for the regeneration of one of Milan’s disused railway yards. As an entry for the 2020 Reinventing Cities competition, Scalo Lambrate is a project for a mainly residential neighborhood with a public park. Strategies to reduce carbon emissions deriving both from the operational energy and construction and maintenance were evaluated and their effects compared to a reference scenario over a time horizon of 100 years. The results show that, while the opportunities to reduce carbon emissions during the use phase are somehow limited due to the already stringent performance requirements for new builds, the use of fast-growing biogenic materials for construction materials, even if mixed with more traditional ones, can provide a significant reduction of the global warming potential over the whole life cycle, with a reduction of 70% over the baseline. The remaining emissions can be offset with afforestation initiatives that, however, must be assessed against land use issues.

The pursuit of Artificial Intelligence (AI) that emulates human cognitive processes is a cornerstone of ethical AI development, ensuring that emerging technologies can integrate seamlessly into societal frameworks requiring nuanced understanding and decision-making. Zero-Shot Instance Retrieval (ZSIR) stands at the forefront of this endeavour, potentially providing a robust platform for AI systems, particularly large visual language models, to demonstrate and refine cognition-aligned learning without the need for direct experience. In this paper, we critically evaluate current cognition alignment methodologies within traditional zero-shot learning paradigms, using visual attributes and word embedding generated by large AI models. We propose a unified similarity function that quantifies the cognitive alignment level, bridging the gap between AI processes and human-like understanding. Through extensive experimentation, our findings illustrate that this similarity function can effectively mirror the visual-semantic gap, steering the model towards enhanced performance in zero-shot instance retrieval. This work not only benchmarks the cognition alignment of AI, but also sets a new precedent for the development of visual language models attuned to the complexities of human cognition.}

The detection, characterization, and monitoring of SARS-CoV-2 recombinant variants is a challenge to public health authorities worldwide. Recombinant variants, composed of two or more SARS-CoV-2 lineages, often have unknown impacts on transmission, immune escape, and virulence in the early stages of emergence. We examined 4,213 SARS-CoV-2 recombinant SARS-CoV-2 genomes collected between 2020 and 2022 from California to describe regional and statewide trends in prevalence. Many of these recombinant genomes, such as those belonging to the XZ lineage, or novel recombinant lineages, likely originated within the state of California. We discuss the challenges and limitations surrounding Pango lineage assignments, the use of publicly available sequence data, and adequate sample sizes for epidemiologic analyses. Although these challenges will continue as SARS-CoV-2 sequencing volumes decrease globally, this study enhances our understanding of SARS-CoV-2 recombinant genomes to date while providing a foundation for future insights into emerging recombinant lineages.

The COVID-19 pandemic has posed an unprecedented challenge to healthcare and the available solutions are unsatisfactory. Classical homeopathy may have a role to play in alleviating this burden. Covid cases treated with homeopathy was curated with the intention to provide basic information for further studies. The results are promising although far from being definitive. 367 patients considered were for statistical analysis, the mean age of the participants was 42.75 years, and males and females were 166 and 201 respectively. The mean follow-up period was 6.5 (SD 5.3) days, with a median of 1 homeopathic remedy used per case. 192 patients were diagnosed by RT–PCR, 111 by the WHO clinical criteria and 64 via retrospective antibodies. According to the WHO criteria, 255 were confirmed cases, 61 were probable cases, and 51 were suspected cases. It was seen that 73.8% of covid patients improved under homeopathic treatment, even those among severe disease 78.6%. Correlational analyses showed that presence of fever was associated with more likelihood of improvement and increasing age and a greater number of homeopathic remedies required in a case were associated negatively with improvement. However, it was seen that severe cases were more likely to improve under homeopathic treatment.

In the advent of COVID-19 pandemic, testing is highly essential to be able to isolate, treat infected persons, and finally curb transmission of this infectious respiratory disease. Group testing has been used previously for various infectious diseases and recently reported for large-scale population testing of COVID-19. However, possible sample dilution as a result of large pool sizes has been reported, limiting testing methods’ detection sensitivity. Moreover, the need to sample all individuals prior to pooling overburden the limited resources such as test kits. An alternative proposed strategy where test is performed on pooled samples from individuals representing different households is presented here. This strategy intends to improve group testing method through the reduction in the number of samples collected and pooled during large-scale population testing. Moreover, it introduces database system which enables continuous monitoring of the population’s virus exposure for better decision making.

The Bacillus Calmette-Guerin vaccine (BCG vaccine) designed to prevent tuberculosis in children has been shown to induce a trained immune response in the body to fight against bacteria as well as other parasites and viruses. This knowledge has been reciprocated to generate the idea that this vaccine can also offer protection against severe acute respiratory syndrome coronavirus-2 (SARS-COV-2). Some recent pre-print articles have highlighted that countries with mass BCG immunizations seems to have a lower incidence of coronavirus disease 2019 (COVID-19) compared to those without BCG immunization. There are yet no experimental proof of any such association and the world health organisation (WHO) is currently testing the theory with clinical trials on selected cohorts. Epidemiologists and other scientific experts has expressed both their hope and concern simultaneously regarding the success theory of BCG vaccination to prevent COVID-19. Though its still not verified in any way whether the BCG vaccination can actually prevent COVID-19 or not but we believe a thorough analytical research in this regard is indeed worth a shot.

Fluorescent bioprobes are invaluable tools for visualizing live cells and deciphering complex biological processes by targeting intracellular biomarkers without disrupting cellular functions. In addition to protein-binding concepts, fluorescent probes utilize various mechanisms, including membrane, metabolism, and gating-oriented strategies. This study introduces a novel fluorescent mechanism distinct from existing ways. Here, we developed a B-cell selective probe, CDrB, with unique transport mechanisms. Through SLC-CRISPRa screening, we identified two transporters, SLCO1B3 and SLC25A41, by sorting out populations exhibiting higher and lower fluorescence intensities, respectively, demonstrating contrasting activities. We confirmed that SLCO1B3, with comparable expression levels in T and B cells, facilitates the transport of CDrB into cells, while SLC25A41, overexpressed in T lymphocytes, actively exports CDrB. The observation suggests that SLC25A41 plays a crucial role in discriminating between T and B lymphocytes. Furthermore, it reveals the potential for reversible localization of SLC25A41 to demonstrate its distinct activity. This study is the first report to unveil a novel strategy of SLC by exporting the probe. We anticipate that this research will open up new avenues for developing fluorescent probes.

Abstract: This study aims to evaluate the effectiveness of plant-based diets and supplement interventions in mitigating the severity and mortality of COVID-19 patients. Observational research suggests that a diet high in plant-based foods may decrease the likelihood and severity of SARS-CoV-2 infection. However, several studies have faced criticism regarding the accuracy of obtaining dietary questionnaires and the insufficient intake of essential vitamins and minerals in such diets. To address these issues, this study employed a prospective interventional design that strictly controlled the quality, quantity, and processing of plant-based foods provided. Furthermore, the study incorporated supplementation, which enhanced the anti-viral, anti-inflammatory, antioxidant, antithrombotic, and immunomodulatory properties of a plant-based diet against the SARS-CoV-2 virus. Of the 3,470 COVID-19 elderly patients, half already followed a plant-based diet, and the other half new patients, both with various comorbidities, were intervened with a plant-based diet and supplementation. The results showed that the participants in the non-plant-based diet group were twice as likely to have experienced moderate disease (with 95% confidence limit: 1.42-3.12) and 2.4 times more likely to have experienced severe disease (with 95% confidence limit: 1.2-5.0) with a significant p-value of less than 0.0005 and 0.016 respectively, compared to those in the PBD group. During the interventions, none of the participants experienced disease progression or hospitalization, and there were no reported deaths by the end of the study. The outcome was highly favorable and aligned with the researchers' expectations, as COVID-19 morbidity and mortality rates in Indonesia were among the highest in Asia. This research may provide significant insights into the prevention and management of COVID-19 and aid in better preparation for future pandemics.

Over the years, the need for autonomous systems such as drones, also known as unmanned aerial vehicles (UAVs), has significantly increased in popularity across several industries, including the military. The Internet of Battlefield Things (IoBT) represents a modern technological advancement that significantly enhances the operational efficacy of defense systems. It establishes an integrated military force by connecting individuals to intelligent technology in drones, radios, equipment, antennas and ground stations. This is achieved through the utilization of cloud and edge computing, sensors, mobile devices, embedded systems, and IoT-based systems. However, IoBT security is significantly compromised by enemies that exploit the vulnerabilities and malicious intrusions that specifically target the external environment or to obtain sensitive data. In addition, a comprehensive understanding of cyberattacks and countermeasures is essential for assuring the security of IoBT. On the other hand, as cyber threats get more complicated, trust becomes increasingly important for the security of digital systems. Within this context, the zero trust architecture contends that the security of a complex network is inherently vulnerable to internal and external threats. In defense, UAV security system applications, for example, the primary purpose of the zero trust architecture is to limit the vulnerability of military UAV systems to cyberattacks, hence reducing the possibility of data breaches and illegal entry. This study conducts a systematic review aimed at identifying different aspects of cybersecurity strategies for protecting UAV systems within the IoBT domain. Furthermore, zero trust architecture is presented in the study as an effective prospective solution to the security issues that develop in defense UAV systems.

Compared to the general population, patients with inflammatory bowel disease (IBD) are less likely to be vaccinated, putting them at an increased risk of vaccine-preventable illnesses. This risk is further compounded by the immunosuppressive therapies commonly used in IBD management. Therefore, developing new treatments for IBD that maintain immune function is crucial, as successful management can lead to better vaccination outcomes and overall health for these patients. Here, we investigate the potential of recombinant banana lectin (rBanLec) as a supporting therapeutic measure to improve IBD control and possibly increase vaccination rates among IBD patients. By examining the therapeutic efficacy of rBanLec in a murine model of experimental colitis, we aim to lay the foundation for its application in improving vaccination outcomes. After inducing experimental colitis in C57BL/6 and BALB/c mice with 2,4,6-trinitrobenzene sulfonic acid, we treated animals orally with varying doses of rBanLec 0.1-10 µg/ml (0.01 – 1 µg/dose) during the course of the disease. We assessed the severity of colitis and rBanLec’s modulation of the immune response compared to control groups. rBanLec administration resulted in a dose-dependent reduction in colitis severity (less pronounced weight loss, less shortening of the colon) and an improved recovery profile, highlighting its therapeutic potential. Notably, rBanLec-treated mice exhibited significant modulation of the immune response, favoring anti-inflammatory pathways (primarily reduction in a local [TNFα]/[IL-10]) crucial for effective vaccination. Our findings suggest that rBanLec could mitigate the adverse effects of immunosuppressive therapy on vaccine responsiveness in IBD patients. By improving the underlying immune response, rBanLec may increase the efficacy of vaccinations, offering a dual benefit of disease management and prevention of vaccine-preventable illnesses. Further studies are required to translate these findings into clinical practice.

A novel strategy is presented for reliable diagnosis and progression prediction of diseases with special attention to COVID-19 pandemy. A plan is presented for how the model can be implemented worldwide in healthcare and how novel treatments and targets can be detected. The idea is based on poikilosis, pervasive heterogeneity and variation at all levels, systems and mechanisms. Poikilosis in diseases can be taken account in pathogenicity model, which is based on distribution of three independent condition measures – extent, modulation and severity. Pathogenicity model is a population or cohort-based description of disease components. Evidence-based thresholds can be applied to the pathogenicity model and used for diagnosis as well as for early detection of patients in risk of developing the most severe forms of the disease. Analysis of patients with differential course of disease can help in detecting biomarkers of diagnostic and prognostic significance. A practical and feasible plan is presented how the concepts can be implemented in practice. Collaboration of many actors, including the World Health Organization and national health authorities, will be essential for success.

Background: Facial features are the first basic spring of medical knowledge in children and adults with congenital malformation. Children born with multiple contractures almost always receive the misdiagnosis of arthrogryposis multiplex. Larsen syndrome can easily be diagnosed at birth via the proper interpretations of its characteristic facial features and multiple dislocations. Instant diagnosis can facilitate the orthopaedic strategy for early treatment and follow-ups. Material and Methods: Six children (four boys and two girls, age range from a few months to 7 year-old) have been referred to our departments for diagnosis and treatment. All children received their first misdiagnosis by the paediatricians as having arthrogryposis multiplex congenita. The clinical phenotype was our first decisive tool for diagnosis. All children exhibited the classical phenotype of Larsen syndrome, dish-like facies associated with multiple joint dislocations. Radiological phenotypic characteristics confirmed our clinical diagnosis. three children out of six showed unpleasant cervical spine deformities. The first child of a-2- year old became tetraplegic after minor trauma. One child presented with rigid cervical kyphosis. The third child wasa product of first related marriage and was born congenital tetraplegia. genotype has been carried out for confirmation. Results: Three children underwent open reduction for congenital hip and knee dislocations. one child underwent spinal fusion CO-C7 because of tetraplegia. 3D reformatted and reconstruction CT scan of the craniocervical junction in two children showed unusual male segmentations along C2-3 causing effectively the development of rigid cervical kyphosis and one child with congenital tetraplegia showed serious malsegmentation of C1/C2 associated with hypoplasia of the anterior and the posterior rings of the atlas. These findings in the last two children made any surgical intervention quite sophisticated. Four of these children were compatible with the autosomal dominant type of Larsen syndrome and manifested heterozygous mutation in FLNB mapped 3p14.3, encoding and actin-binding protein, filamin B. One child showed no mutations in the FLNB, though his clinical and radiological phenotype and his family history of first related marriage were totally compatible within the diagnosis of autosomal recessive type of Larsen syndrome. Conclusion: The orthopaedic strategy in patients with Larsen syndrome can not be achieved unless a precise diagnosis is has to be established as early as possible. Arthrogryposis multiplex congenita has been the first false diagnosis which was the reason for improper management.The most diagnostic confusion /error occurs to the paediatricians is the multiple contractures which are akin to arthrogryposis multiplex congenita. In practice, arthrogryposis multiplex congenita is a symptom complex rather than a precise diagnostic entity. The second diagnostic misconception is the generalized ligamentous hyperlaxity which can mimic hypotonia. Hypotonia in a newborn can be falsely categorized within the floppy infant syndrome. We used 3D reformatted CT scan to further understand the craniocervical junction pathology in three children with cervical spine kyphosis. Strikingly, mal segmentation and defective ossifications of the atlanto-axial spine segments in a child with Larsen syndrome and congenital tetraplegia.

Innovation is an essential key factor in the technology development history. Past research on innovation focused more on the innovation behavior of technology, but seldom described knowledge assets which also influence innovation behavior greatly. The effect of knowledge assets attribute and result on disruptive innovation is therefore regarded as the research topic in this study, where disruptive innovation is divided into outbound and inbound to combine combination-embeddednessandmajor business specificityof knowledge assets as the research model. Manufacturing enterprises in China are proceeded the questionnaire survey, and 173 valid copies are collected. The empirical analysis shows that combination-embeddedness of knowledge assets presents significantly positive effects on major business specificity and outbound innovationof an enterprise but reveals remarkably negative effects on inbound innovation. Enterprises are suggested to constantly accumulate knowledge assets with low major business specificity before disruptive innovation in order to reduce ineffective inbound innovation.

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 study investigates the impact of circular economy (CE) strategies on organizational resilience (OR) within the metal industry, focusing on a case study of a forging department in a large man-ufacturing company. The idea of the paper is to link the macroeconomic topic of circular economy (CE) with microeconomic and practical activities in the organization, exploring how CE principles can improve resource efficiency, sustainability, and organizational resilience. A systematic literature review and case study methodology were used to assess the relationship between CE and OR. The findings reveal that companies with higher circularity demonstrate better resilience, both in normal operations and during crises. Specifically, in the case study, the closure of the forging department, following a detailed analysis using the Inputs-Mediators-Outputs (IMO) model, emerged as the most sustainable option, yielding financial, environmental, and operational benefits. This decision aligned with the company’s long-term goals of energy efficiency and carbon neutrality. The research highlights the significance of integrating CE strategies with business processes to not only achieve sustainability but also to build a more adaptable and resilient organization. Future research should explore broader applications of this framework across different industries to strengthen the links between circular economy practices and organizational resilience.

While the knowledge about the development of understanding positive integers is rapidly growing, the development of understanding zero is not well-known. Here we tested several components of preschoolers’ understanding zero: whether they can use empty sets in numerical tasks, whether they can use empty sets soon after they understand the cardinality principle, whether they know what the word “zero” refers to, and whether they categorize zero as a number. The results show that preschoolers can handle empty sets in numerical tasks as soon as they understand the cardinality principle or even earlier, and some of them know that these sets are labeled as “zero.” However, they are unsure whether zero is a number. These results identify three components of knowledge about zero: operational knowledge, linguistic knowledge, and meta knowledge. To account for these results we propose that preschoolers might understand numbers as the properties of items or objects in a set. In this view, zero cannot be a number, because an empty set does not include any items, and the missing items cannot have any property, excluding also the number property. This model might explain why zero is handled correctly in numerical tasks, while it is not regarded to be a number.

This paper is motivated by spatio-temporal pattern in the occurrence of Leishmaniasis in Afghanistan and the relatively high number of zero counts. We hold the view that correlations that arise from spatial and temporal sources are inherently distinct. Our method decouples these two sources of correlations, there are at least two advantages in taking this approach. First, it circumvents the need to inverting a large correlation matrix, which is a commonly encountered problem in spatio-temporal analyses. Second, it simplifies the modelling of complex relationships such as anisotropy, which would have been extremely difficult or impossible if spatio-temporal correlations were simultaneously considered. We identify three challenges in the modelling of a spatio-temporal process: (1) accommodation of covariances that arise from spatial and temporal sources; (2) choosing the correct covariance structure and (3) extending to situations where a covariance is not the natural measure of association. Moreover, because the data covers a period that overlaps with the US invasion of Afghanistan, the high number of zero counts may be the result of no disease incidence or lapse of data collection. To resolve this issue, a model truncated at zero built on a foundation of the generalized estimating equations was proposed.

The wellness economy has developed rapidly recently, particularly in wellness tourism. Wellness tourism transforms sustainable strategy through the availability of extended multi-actor engagement in service innovation to further the tourism experience. Therefore, when operating a wellness tourism destination, it is necessary to encourage multi-actor engagement in service innovation to achieve sustainable development. This paper introduces a mixed research method with the SWOT-AHP-QSPM, as it qualitatively analyzes the advantages, disadvantages, opportunities, and threats, constructs an evaluation index system, conducts quantitative analysis using the analytic hierarchy process, determines the index weight and weighted score, and calculate the sustainable development strategy, which is appropriate for wellness development of Chongqing Tea Mountain and Bamboo Forest National Forest Park. Purposive field surveys and personal interviews were conducted in Chongqing forest tourism destinations, involving 356 effective respondents. The research reveals that multi-actor engagement significantly enhances sustainable development. These findings bridge service innovation knowledge gaps and provide valuable insights for forest tourism destination management and sustainable policy strategies to elevate multi-actor engagement in forest sites.

The use of privileged scaffolds as starting point for the construction of libraries of bioactive compounds is a widely used strategy in drug discovery and development. Scaffold decoration, morphing and hopping are additional techniques that allow to modify the privileged framework chosen and better explore the chemical space around it. In this study, two series of highly functionalized pyrimidine and pyridine derivatives were synthesized by scaffold morphing approach of triazine compounds obtained previously as antiviral agents. Newly synthesized azines were evaluated against lymphoma, hepatocarcinoma, and colon epithelial carcinoma cells showing in five cases acceptable to good anticancer activity associated to low cytotoxicity on healthy fibroblasts. Finally, ADME in vitro studies were conducted on the best derivatives of the two series showing good passive permeability and resistance to metabolic degradation.

The COVID-19 pandemic has had a significant impact on every individual in the United States. The launch of the COVID-19 vaccines is estimated to have averted millions of deaths and reduced over 18 million COVID-19 related hospitalizations. In September 2023, the updated 2023-2024 COVID-19 vaccine that include a monovalent component that corresponding to the omicron variant XBB.1.5 reflecting the predominant circulating variant at the time of strain selection, was approved and was recommended for use in all people ≥ 6 months of age. Despite this recommendation, the US uptake of the updated COVID vaccines over the 2023-2024 season has been far from optimal, placing many people at unnecessary risk of severe COVID-19 outcomes. This paper provides an overview of the current state of COVID-19 in 2023-2024, and barriers to vaccine uptake. With the continued evolution of the virus, the potential for more virulent variants and the lower public acceptance of vaccination, the potential barriers that contributed to low vaccine uptake are explored, as well as to provide solutions for improving COVID-19 protection for future seasons.

This study introduces an advanced dual-mode composite attitude control framework for reusable launch vehicles (RLVs), underpinned by an enhanced particle swarm optimization (PSO) algorithm. This innovative strategy is tailored to meet the stringent demands for precision and robust anti-interference capabilities across the entire flight envelope of RLVs. The research commences with the formulation of a comprehensive attitude dynamics model and diverse heterogeneous actuator representations, meticulously crafted to reflect the distinct phases of RLV flight. Building upon this foundation, a synergistic control paradigm is engineered, integrating PID and fuzzy PID controllers, complemented by a refined fitness evaluation function. The crux of the study is the application of an upgraded PSO algorithm to fine-tune the controllers' weighting coefficients, culminating in an optimized dual-mode composite attitude control system. A series of comparative simulation analyses are meticulously executed to appraise the system's responsiveness, stability, precision, and resilience to interference. The findings unequivocally substantiate the superior performance of the proposed control system, affirming its substantial contribution to the advancement of RLV attitude control.

This study evaluates the incidence and characteristics of adverse events (AEs) following the second COVID-19 booster dose, leveraging Taiwan's distinctive approach of extending booster vaccinations to all citizens, unlike the targeted high-risk group strategies in other countries. Utilizing data from Taipei Veterans General Hospital's Vaccine Adverse Event Reporting System (VAERS) from October 27, 2022, to January 19, 2023, the research examines AEs in 441 out of 1711 second booster recipients, considering factors like age, vaccine brands, and booster combinations. The findings reveal incidence rates (IR) of 25.6% (95% CI: 21.1-30.8) after the first booster and 24.9% (95% CI: 20.5-30.0) after the second, mostly non-serious, with those having AEs post-first booster 5 times more likely to report them again (Incidence rat rato, 5.02, P<0.001). Significantly, switching from the mRNA1273 vaccine to another brand reduced AE risk by 18%. The study underscores that AEs are more repetitive than cumulative with additional booster doses, advocating for personalized vaccination strategies based on individual medical histories and previous vaccine reactions. These insights are valuable for healthcare providers in discussing potential AEs with patients, thereby improving vaccine compliance and public trust, and for policymakers in planning future booster vaccination strategies.

COVID-19 severity is heterogeneously distributed over age strata, but current mitigation strategies are homogeneously applied to all population. Social-distancing and stay-home are effective conservative approaches but lack economic sustainability on long term. Conversely, herd-immunity is a nonrestrictive strategy which can cost remarkable number of human lives and can melt the healthcare system down. Here I propose an Age Adaptive Social Distancing (AASD) engineering strategy to mitigate COVID-19 outbreak. AASD is based on the scientific evidence that the fatality rate grows nonlinearly with age, hence also the containing strategy should adapt nonlinearly. Essentially, AASD suggests that ‘silent spreaders’ (age 0-39) should avoid/minimize direct and indirect contacts with individuals in ‘dangerous zone’ (age 40+). The rationale is: 0-19 should follow parents strategy, healthy 20-39 (low fatality rate) might conduct screened life under active surveillance, to sustain economy and acquire rational immunity; 40-59 should respect social distancing (waiting a therapy); 60+ should stay at home (waiting a vaccine). This might save human lives, reduce healthcare demand and improve economic sustainability. The final take-home message is that future studies should design precision and personalized strategies for specific contagious diseases that integrate different social constrains, active surveillance and contact tracing.

The Energy Performance of Buildings Directive 2010 calls for the Nearly Zero Energy Standard for new buildings from 2021 onwards: Buildings using “almost no energy” are powered by renewable sources or energy produced by the building itself. For residential buildings, this ambitious new standard has already been reached. But for other building types this goal is still far away. The potential of these buildings to meet a Nearly Zero Energy Standard was investigated by analyzing ten case studies representing non-residential buildings with different uses. The analysis shows that the primary characteristics common to critical building types are a dense building context with a very high degree of technical installation (such as hospital, research and laboratory buildings). The large primary energy demand of these types of buildings cannot be compensated by building and property-related energy generation including off-site renewables. If the future Nearly Zero Energy Standard were to be defined with lower requirements because of this, the state related properties of Bavaria suggest that the real potential energy savings available in at least 85% of all new buildings would be insufficiently exploited. Therefore, it would be useful to instead individualize the legal energy verification process for new buildings to distinguish critical building types such as laboratories and hospitals.

The energy efficiency of existing buildings is a crucial factor in addressing Europe’s energy con-sumption challenges, accounting for nearly 40% of the total energy usage. The ongoing energy crisis, driven by the reliance on fossil fuels and increasing prices, has underscored the urgency of adopting sustainable and energy efficient practices especially to the existing building stock. Cyprus is par-ticularly vulnerable due to its heavy dependence on imported fuels for electricity generation and faces significant challenges in transforming its existing building stock into energy-efficient and sustainable structures. Extensive focus has been made by the government on the energy-efficient retrofit of non-residential public buildings. This study examines an existing cultural hall. The case study of the Cultural Hall represents the building stock before 2010 which is lacking thermal in-sulation, double glazing and any energy efficient element. It then offers an ideal case study to ex-plore sustainable solutions which can be easily adopted from the construction industry and from the building owners. The primary objective of this research is twofold: first, to develop a comprehensive retrofit plan to transform the cultural hall into a net-zero energy building; and second, to explore how this transformation can give value back to the local community. After running two simulation scenarios and providing two energy performance certificates, one with at the existing state and one with the intended retrofit measures, it is clear that the building can be a net zero energy consump-tion building. Some interesting results derived, present also how this building can provide value back to the community i.e. through solar carports for EV charging.

In response to the increasing complexity and sophistication of cyber threats, particularly those enhanced by advancements in artificial intelligence, traditional security methods are proving insufficient. This paper explores the zero-trust cybersecurity framework, which operates on the principle of "never trust, always verify" to mitigate vulnerabilities within organizations. Specifically, it examines the applicability of zero-trust principles in environments where large volumes of information are exchanged, such as schools and libraries, highlighting the importance of continuous authentication, least privilege access, and breach assumption. The findings highlight avenues for future research that may help preserve the security of vulnerable organizations.

This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. Under low-temperature environments, EVs suffer a sharp driving range loss resulted from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then given a certain ambient temperature, a target temperature of preheating is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with a decreasing ambient temperature; however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save total vehicle operation cost.

Autonomous navigation in dynamic environments poses a significant challenge in the field of ro-botics with the primary goals of ensuring both smooth and safe movement. This study introduces control strategy based on an Adaptive Neuro-Fuzzy Inference System (ANFIS) to enhance au-tonomous robot navigation in dynamic environments, emphasizing on collision-free path plan-ning. This strategy employs, a path planning technique to develop a trajectory that allows the ro-bot to navigate smoothly while avoiding collisions with both static and dynamic obstacles. The developed control system incorporates four ANFIS controllers: two are tasked with guiding the robot toward its end point, and the other two are activated for obstacle avoidance. The experi-mental setup conducted in CoppeliaSim involves a mobile robot equipped with ultrasonic sensors navigating in an environment with static and dynamic obstacles. Simulation experiments are conducted to demonstrate the model's capability in ensuring collision-free navigation, employing a path planning algorithm to ascertain the shortest route to the target destination. The simulation results highlight the superiority of the ANFIS-based approach over conventional methods, partic-ularly in terms of computational efficiency and navigational smoothness.

This prospective cohort study aimed to evaluate the efficacy of COVID-19 vaccine schemes, ho-mologous versus heterologous vaccine strategies, and vaccine-induced anti-S-RBD-IgG antibody response in preventing COVID-19 among 942 healthcare workers one year after vaccination with the inactivated and/or mRNA vaccines. All participants received the first two primary doses of vaccines, 13.6% of them lacked the dose-3, 50.5% the dose-4, and 90.3% the dose-5. Antibody lev-els increased with the increase in number of vaccine doses and also in heterologous vaccine regi-mens. In both inactive and mRNA vaccines, infection rates were significantly higher in 2-dose-receivers, but lower in 4- or 5-dose receivers and increasing the total number of vaccine doses resulted in more protection against infection: the 3-dose regimen yielded 4.71 times more protection, the 4-dose 11.76 times and 5-dose 38.46 times more protection from COVID-19 infec-tion, compared to any 2-dose vaccination regimens. Antibody levels at the end of the first year of 4- or 5-dose-receivers were significantly higher than 2- or 3-dose-receivers. To conclude; increased number of total vaccine doses and anti-S-RBD antibody levels increased the protection from COVID-19 infection. Therefore, four or more doses are recommended in one year, for effective protection, especially in risk groups.

This research focuses on optimization of coupled solar production and battery storage system to achieve Nearly Zero-Energy Building (nZEBs) based on building load behavior patterns. Moni-toring data from an office building with 120kW peak and 40kW average load consumption equipped with a 160kW solar photovoltaic (PV) system and a 50kW-45kWh energy storage system (ESS). The primary objective is to the primary objective is to analyze collected data from existing system and setup guideline to optimize ESS capacity to maximize clean energy consumption and thus minimize excess production losses, progressing the building toward Nearly ZEB Level 1 status (87.5%-100% energy usage). The study outcome has identified parameter impacts and demonstrates additional optimized cases with various PV and ESS installed capacity. Further analysis is performed based on working day load profile and appliance patterns. This ap-proach aims to learn the usage HVAC, lighting, and electronics, enabling the optimization scheme to be applied to buildings with different load patterns. Additionally, the analysis predicts other building behavior patterns and optimized clean energy system. The findings are then validated against actual data and the results demonstrate good model accuracy, especially daytime predic-tion. These insights also provide guidelines and strategies for further interventions on HVAC operations and adjusting concerned schedules to achieve desired ZEB level.

The Electric Fish Optimization (EFO) Algorithm is inspired by the predation behavior and communication of weak electric fish. It is a novel meta-heuristic algorithm that attracts researchers because it has few tunable parameters,high robustness,and strong global search capabilities. Nevertheless, when operating in complex environments, the EFO algorithm encounters several challenges including premature convergence, susceptibility to local optimum, and issues related to passive electric field localization stagnation. To address these challenges, this study introduces an Adaptive Electric Fish Optimization Algorithm Based on Standstill Label and Level Flight (SLLF-EFO). This hybrid approach incorporates the Golden Sine Algorithm and Good Point Set Theory to augment the EFO algorithm’s capabilities, employs a variable step size Levy flight strategy to efficiently address passive electric field localization stagnation problems, and utilizes a standstill label strategy to mitigate the algorithm’s tendency to fall into local optimum during the iterative process. By leveraging multiple solutions to optimize the EFO algorithm, this framework enhances its adaptability in complex environments. Experimental results from benchmark functions reveal that the proposed SLLF-EFO algorithm exhibits improved performance in complex settings, demonstrating enhanced search speed and optimization accuracy This comprehensive optimization not only enhances the robustness and reliability of the EFO algorithm but also provides valuable insights for its future applications.

This paper proposes a novel hybrid control strategy for quadrotor unmanned aerial vehicles (UAVs) based on bio-inspired neural dynamics. This strategy addresses the velocity jump issue prevalent in traditional backstepping control and the control signal chattering problem common in traditional sliding mode control. The control system comprises an outer-loop bio-inspired backstepping controller and an inner-loop bio-inspired sliding mode controller, ensuring smooth trajectory tracking even in the presence of external disturbances. The stability of the quadrotor UAV control system is rigorously analyzed using Lyapunov stability theory. Extensive comparative simulation experiments are conducted to assess the robustness and effectiveness of the control system. Results demonstrate superior trajectory tracking performance of the proposed control system compared to other control systems for quadrotor UAVs.

The excessive intake of sodium (Na) and insufficient intake of potassium (K) are major concerns to prevent hypertension. Using low-Na/K seasonings (reducing 25% of the NaCl and adding K salt) may improve the dietary Na/K ratio and help prevent hypertension. To devise an intervention study using low-Na/K seasonings at a company cafeteria, we calculated the Na and K contents of the meals served at the cafeteria and estimated changes in the intakes when suitable low-Na/K seasonings were used. We also considered using milk as a good source of K. We used an ingredient list of a company cafeteria and calculated Na and K contents in each dish. The average amounts of NaCl and K per use were 5.04 g and 718 mg, respectively. Seasonings contributed 70.9% of the NaCl. With the use of low-Na/K seasonings, an estimated reduction in NaCl of 0.8 g/day and an estimated increase in K of 308 mg/day was achieved. An additional serving (200 mL) of milk, NaCl was reduced by 0.57 g/day and K was increased by 610 mg/day, with an overall decrease in the dietary Na/K ratio from 3.20 to 2.40. The use of low-Na/K seasonings and dairy may improve the dietary Na/K ratio among cafeteria users and help prevent hypertension.

The incremental sheet forming represents a relatively recent technology that guarantees high customization, thanks to the layered manufacturing principle typical of rapid prototyping, and cost-effectiveness, because it does not require dedicated equipment. Research has initially shown that this process is effective in metal materials capable of withstanding plastic deformation but, in recent years, the interest in this technique has been increasing for the manufacture of complex polymer sheet components as an alternative to the conventional technologies, based on heating-shaping-cooling manufacturing routes. Conversely, incremental formed polymer sheets can suffer from some peculiar defects, for example twisting. To reduce the risk of this phenomenon and the occurrence of failures, a viable way is to choose toolpath strategies that make the tool/sheet contact conditions less severe, and this represents the main goal of the present research. Polycarbonate sheets were worked by incremental forming; in detail, cone frusta with a fixed wall angle were manufactured with a reference and a stair toolpath strategy, and both the forming forces and the twist angle were monitored. The analysis of the results highlighted that a stair toolpath involving an alternation of diagonal up and vertical down steps represents a useful strategy to mitigate the forming forces and, with them, the occurrence of the twisting phenomenon in incremental formed thermoplastic sheets.

Zero-day threats are a more severe and constantly developing menace to various participants including large companies, government offices, and educational establishments. These entities may contain valuable information and essential operations that attract cyber attackers. These exploits are especially devastating as they target weaknesses that an organization’s vendors are not even aware of, making them have no protection against them. This paper focuses on the background and use of zero-day exploitation and the structure and technologies of these complex malware attacks. We examine two notable real-life cases: the case of ‘HAFNIUM targeting Exchange Servers with zero-day exploits’ that was investigated by Microsoft 365 Security and Microsoft Threat Intelligence, and the ‘Log4j vulnerability’ case that was reported by the National Cyber Security Centre. These cases show the critical effects of zero-day vulnerabilities and measures taken to combat them. Additionally, this paper outlines different strategies that can be used to prevent zero-day attacks with the help of modern technologies. These are fast patch release, effective IDS/IPS, and a security model that involves constant vigilance and use of behavioral analytics. Thus, by studying the lifecycle of zero-day vulnerabilities and the structure of the exploits, one can enhance the protection of the organization against the threats that are invisible to traditional security systems. This extensive survey is designed to be useful in understanding the characteristics of zero-day vulnerabilities, the technologies for their mitigation, and the constant threat and development in the field of cybersecurity. Thus, it is possible to strengthen the protection against these threats that are constant and develop with time by analyzing the previous events and predicting potential problems.

COVID-19 has become a severe global public health concern. The critical illness has a mortality rate of 61.5%, and thus, reducing the severity and mortality is top priority. Currently, inflammatory storms are considered as the cause of critical illness and death due to COVID-19. However, After systematical review of the literature, we proposed that cross-reactive antibodies-associated antibody-dependent enhancement (ADE) may actually be the cause of cytokine storms. If the activation of memory B cells can be selectively inhibited in high-risk patients at an early stage of COVID-19 to reduce the production of cross-reactive antibodies of the virus, we speculate that the ADE can be avoided and severe symptoms can be prevented. The mammalian target of rapamycin (mTOR) inhibitors satisfy such conditions. We recommend that pharmaceutical companies conduct clinical trials urgently.

The combination of several therapeutic strategies is often seen as a good way to decrease the resistance rates, since bacteria overcome better single-drug treatments than multi-drug ones. This strategy is especially attractive when several targets and subpopulations are affected, as it is the case of Klebsiella pneumoniae persister cells, a subpopulation of bacteria able to transiently survive antibiotic exposures. This work aims to evaluate the potential of a repurposed anticancer drug, mitomycin C, combined with the K. pneumoniae lytic phage vB_KpnM-VAC13 in vitro and the safety in an in vivo murine model against two clinical isolates of this pathogen, one of them exhibiting an imipenem-persister phenotype. At the same time, we verified the absence of toxicity of mitomycin C at the concentration using the human chondrocyte cell line T/C28a2. The viability of these human cells was checked both by cytotoxicity assays and flow cytometry.

We revisit a 2023 JAMA-published analysis of data from patients admitted for either COVID-19 or influenza to U.S. Veterans Administration (VA) hospitals in the fall/winter of 2022-2023. We note that baseline characteristics between the cohorts were similar, and the difference in vaccination rates was minimal, even after propensity score weighting. Had the vaccines been even minimally effective, significant differences in vaccination percentages would be expected. These findings call into question any efficacy claims associated with either the COVID-19 or influenza vaccines. Furthermore, the lack of efficacy of the influenza vaccines in reducing hospitalization is consistent with an earlier detailed study that found the same lack of efficacy, further validating the current result. This suggests that comparing vaccination rates between those hospitalized for different vaccine-preventable diseases can serve as a practical method for validating the vaccine efficacy claims of different vaccines.

We study a two-echelon supply chain made up of a supplier and a manufacturer, both of which can reduce their component/product carbon emissions. With the vertical technology spillovers, we explore the optimal decisions of centralized and decentralized supply chains with price dependent demand and propose coordination strategy for the decentralized supply chain. Considering the cost contraction effectiveness of the technology spillovers, the centralized and decentralized game theoretic models of a two-echelon supply chain are developed to investigate optimal decisions of pricing and carbon emissions reduction. Through a systematic comparison and numerical analysis, we show that the profits of both players and the entire supply chain improve with the effect of technology spillovers increasing. Carbon emissions reduction will be taken by various protective measures so that the supplier and the manufacturer who do not innovate can hardly share the results of innovating via the “free-riding” methods when the technology spillover is relatively small. We also propose a revenue-cost sharing contract through bargaining to enhance the performance of the decentralized supply chain.

Draconian defensive measures have been implemented to combat the COVID-19 pandemic outbreak. These important measures constitute a vital current priority but do little to increase communal immunity and avoid future outbreaks. A longer-term exit strategy for a sustainable return to normalcy has yet to be identified. The development of vaccines or effective therapeutics could largely solve the problem, but their timely development cannot be guaranteed. In this setting, and under the expected societal isolation fatigue from extended social distancing, we here propose the idea that at some point after the outbreak’s peak, hospitals, in addition to providing care for infected people who need it, could also be involved in the development of a controlled exit strategy designed to avoid future outbreaks. We postulate that controlled voluntary deliberate infection in a hospital setting and under continuous and close medical observation may offer a safer alternative compared to random en-masse exposure. We discuss potential risks and benefits, highlighting the need for careful consideration of the associated critical ethical issues.

Methicillin-resistant Staphylococcus aureus (MRSA) infections, in particular biofilm-organized bacteria, remain a clinical challenge and a serious health problem. Rifabutin (RFB), an antibiotic of the rifamycins class, has shown in previous work excellent anti-staphylococcal activity. Here, we proposed to load RFB in liposomes aiming to promote the accumulation of RFB at infected sites and consequently enhancing the therapeutic potency. Two clinical isolates of MRSA, MRSA-C1 and MRSA-C2, were used to test the developed formulations, as well as the positive control, vancomycin (VCM). RFB in free and liposomal forms displayed high antibacterial activity, with minimal inhibitory concentrations (MIC) ranging from 0.009-0.013 μg/mL and MBIC50 values ranging from 0.008-0.012 μg/mL, in planktonic and biofilm bacteria, respectively. Confocal microscopy studies demonstrated the rapid internalization of unloaded and RFB-loaded liposomes in the bacterial biofilm matrix. In murine models of systemic MRSA-C1 infection, Balb/c mice were treated with RFB formulations and VCM at 20 and 40 mg/kg of body weight, respectively. Obtained data proved the superior therapeutic effectiveness of RFB formulations compared to Control and VCM groups even using a two-fold lower therapeutic dose as demonstrated by significantly reduced bacterial burden and growth index values in major organs. In addition, RFB formulations were the only formulations associated with 100% survival. Globally, this study emphasizes the potential of RFB nanoformulations as an effective and safe approach against MRSA infections.

Objectives: In December 2019 a novel human-infecting coronavirus, SARS-CoV-2, has emerged. The WHO has stated the epidemic as a “public health emergency of international concern”. A dramatic situation has emerged with thousands of deaths, occurring mainly in the aged and very ill people. Epidemiological studies suggest that immune system function is impaired in elderly individuals and these subjects often present a severe deficiency in nutrients as fatsoluble and hydrosoluble vitamins. Design: In this second part of the review about Cov2 in aged people, we searched for studies describing the possible efficacy of vitamins A, D, E and C in improving the immune system function and their possible activities against viruses. Results: Vitamins may shift the proinflammatory Th17 mediated immune-response arising in the autoimmune diseases towards a T-cell regulatory phenotype. These diseases may serve as a paradigm for the study of CRS emerging in the course of SARS CoV-2 infection. Conclusion: This review discusses about the possible activity of Vitamin A, D, E and C in restoring normal antiviral Immune System function or the potential therapeutic role of these micronutrients as a part of a multi-treatment strategy against SARS-CoV-2 infection.

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

Starting from the fact that one of the global control strategies of the Permanent Magnet Synchronous Motor (PMSM), namely the Direct Torque Control (DTC) type control strategy, is characterised by the fact that the inner flux and torque control loop usually uses hysteresis ON-OFF type controllers and the oscillations introduced by them have to be cancelled out by the outer speed loop controller (which is usually a PI speed controller and whose performance is good around the global operating points and for relatively small variations of the external parameters and disturbances caused in particular by the load torque variation), while retaining the advantages of the DTC strategy, this paper presents the improvement of the performance of the PMSM sensorless control system using Proportional Integrator (PI), PI Equilibrium Optimizer Algorithm (EOA), Fractional Order (FO) PI, Tilt Integral Derivative (TID) and FO Lead-Lag for constant flux, and Sliding Mode Control (SMC) and FOSMC for variable flux. The performance indicators of the control system are the usual ones: response time, settling time, overshoot, steady-state error and speed ripple, plus another one given by the fractal dimension (FD) of the PMSM rotor speed signal, and the hypothesis that the FD of the controlled signal is higher when the control system provides better performance is verified. The paper also presents the basic equations of the PMSM, based on which the synthesis of integer and fractional controllers, the synthesis of an observer for estimating the PMSM rotor speed, electromagnetic torque and stator flux are presented. The comparison of the performance of the proposed control systems and the demonstration of the parametric robustness are performed by numerical simulations in Matlab/Simulink using Simscape Electrical and Fractional Order Modelling and Control (FOMCON). Real-time control based on an embedded system using a TMS320F28379D controller demonstrates the good performance of the PMSM sensorless control system based on the DTC strategy in a complete hardware-in-the-loop (HIL) implementation.

The paper examines the various uncertainties encountered in high-frequency trading (HFT) environments and delves into the multiple challenges faced by HFT firms in navigating the Dodd-Frank Wall Street Reform and Consumer Protection Act (referred to as the "Dodd-Frank Act"), particularly during the initial stages of its enactment. These challenges include the ambiguity surrounding the definition of HFT, the lack of clarity regarding regulatory requirements and boundaries, inconsistencies in enforcement resulting from deviations in understanding the content, and the absence of detailed descriptions of the Act’s provisions. These hurdles significantly impact not only the daily operations of HFT firms but also pose higher demands on their long-term strategic planning and risk management. Drawing upon the Data, Information, Knowledge, Wisdom, and Purpose (DIKWP) model, this study employs an innovative analytical framework. Through the comprehensive application of conceptual space, cognitive space, and semantic space, it provides a systematic methodology for identifying and analyzing the aforementioned issues. This approach not only aids firms in better comprehending and adhering to complex regulatory requirements but also enables them to explore new business opportunities and competitive advantages while ensuring compliance.

Zero-shot learning ability robotics enables robots to generalize their knowledge and perform tasks for which they have not been explicitly trained. This ability is extremely helpful because in classic learning approaches, robots are trained on specific tasks and require extensive data and labeled examples to perform accurately. However, in real-world scenarios, robots often encounter new or unseen tasks that were not part of their training data. We briefly survey works in this area to give the reader a perspective about progresses in this area.

New setting is introduced to study failed zero-forcing number and failed zero-forcing neutrosophic-number. Leaf-like is a key term to have these notions. Forcing a vertex to change its color is a type of approach to force that vertex to be zero-like. Forcing a vertex which is only neighbor for zero-like vertex to be zero-like vertex but now reverse approach is on demand which is finding biggest set which doesn’t force. LetNTG : (V,E,σ,μ) be a neutrosophic graph. Then failed zero-forcing number Z(NTG) for a neutrosophic graph NTG : (V,E,σ,μ) is maximal cardinality of a set S of black vertices (whereas vertices in V (G) \ S are colored white) such that V (G) isn’t turned black after finitely many applications of “the color-change rule”: a white vertex is converted to a black vertex if it is the only white neighbor of a black vertex. Failed zero-forcing neutrosophic-number Zn(NTG) for a neutrosophic graphNTG : (V,E,σ,μ) is maximal neutrosophic cardinality of a set S of black vertices (whereas vertices in V (G) \ S are colored white) such that V (G) isn’t turned black afterfinitely many applications of “the color-change rule”: a white vertex is converted to a black vertex if it is the only white neighbor of a black vertex. Failed zero-forcing number and failed zero-forcing neutrosophic-number are about a set of vertices which are applied into the setting of neutrosophic graphs. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs namely path-neutrosophic graphs, cycle-neutrosophic graphs, complete-neutrosophic graphs, star-neutrosophic graphs, bipartite-neutrosophic graphs, and t-partite-neutrosophic graphs are investigated in the terms of maximal set which forms both of failed zero-forcing number and failed zero-forcing neutrosophic-number. Neutrosophic number is reused in this way. It’s applied to use the type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number to compare with other vertices. Summation of three values of vertex makes one number and applying it to a comparison. This approach facilitates identifying vertices which form failed zero-forcing number and failed zero-forcing neutrosophic-number. In path-neutrosophic graphs, the set of vertices such that every given two vertices in the set, have distance at least two, forms maximal set but with slightly differences, in cycle-neutrosophic graphs, the set of vertices such that every given two vertices in the set, have distance at least two, forms maximal set. Other classes have same approaches. In complete-neutrosophic graphs, a set of vertices excluding two vertices leads us to failed zero-forcing number and failed zero-forcing neutrosophic-number. In star-neutrosophic graphs, a set of vertices excluding only two vertices and containing center, makes maximal set. In complete-bipartite-neutrosophic graphs, a set of vertices excluding two vertices from same parts makes intended set but with slightly differences, in complete-t-partite-neutrosophic graphs, a set of vertices excluding two vertices from same parts makes intended set. In both settings, some classes of well-known neutrosophic graphs are studied. Some clarifications for each result and each definition are provided. Using basic set not to extend this set to set of all vertices has key role to have these notions in the form of failed zero-forcing number and failed zero-forcing neutrosophic-number. The cardinality of a set has eligibility to form failed zero-forcing number but the neutrosophic cardinality of a set has eligibility to call failed zero-forcing neutrosophic-number. Some results get more frameworks and perspective about these definitions. The way in that, two vertices don’t have unique connection together, opens the way to do some approaches. A vertex could affect on other vertex but there’s no usage of edges. These notions are applied into neutrosophic graphs as individuals but not family of them as drawbacks for these notions. Finding special neutrosophic graphs which are well-known, is an open way to pursue this study. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

Myelin protein zero (P0), a type I transmembrane protein, is the most abundant protein in peripheral nervous system (PNS) myelin – the lipid-rich, periodic structure that concentrically encloses long axonal segments. Schwann cells, the myelinating glia of the PNS, express P0 throughout their development until the formation of mature myelin. In the intramyelinic compartment, the immunoglobulin-like domain of P0 bridges apposing membranes together via homophilic adhesion, forming a dense, macroscopic ultrastructure known as the intraperiod line. The C-terminal tail of P0 adheres apposing membranes together in the narrow cytoplasmic compartment of compact myelin, much like myelin basic protein (MBP). In mouse models, the absence of P0, unlike that of MBP or P2, severely disturbs the formation of myelin. Therefore, P0 is the executive molecule of PNS myelin maturation. How and when is P0 trafficked and modified to enable myelin compaction, and how disease mutations that give rise to incurable peripheral neuropathies alter the function of P0, are currently open questions. The potential mechanisms of P0 function in myelination are discussed, providing a foundation for the understanding of mature myelin development and how it derails in peripheral neuropathies.

This research investigates the relationship between the long-term orientation of top managers and their strategic decision-making processes, emphasising the comprehensiveness, speed, and inventiveness of decisions. The study employed structural equation modelling to look into the suggested connections using a sample of CEOs. The findings demonstrated a high and positive correlation between long-term orientation and decision comprehensiveness and speed, but not for decision creativity. The study contributes to the growing body of research on how human variations, such as temporal orientation, affect business outcomes and strategic decision-making. Moreover, the fact that a number of the results differed from those of other studies carried out in other contexts highlights how important it is to consider the industry and cultural environment when assessing these connections.

Since its emergence in March 2020, the SARS-CoV-2 global pandemic has produced more than 65 million cases and one point five million deaths worldwide. Despite the enormous efforts carried out by the scientific community, no effective treatments have been developed to date. We created a novel computational pipeline aimed to speed up the process of repurposable candidate drug identification. Compared with current drug repurposing methodologies, our strategy is centered on filtering the best candidate among all selected targets focused on the introduction of a mathematical formalism motivated by recent advances in the fields of algebraic topology and topological data analysis (TDA). This formalism allows us to compare three-dimensional protein structures. Its use in conjunction with two in silico validation strategies (molecular docking and transcriptomic analyses) allowed us to identify a set of potential drug repurposing candidates targeting three viral proteins (3CL viral protease, NSP15 endoribonuclease, and NSP12 RNA-dependent RNA polymerase), which included rutin, dexamethasone, and vemurafenib among others. To our knowledge, it is the first time that a TDA based strategy has been used to compare a massive amount of protein structures with the final objective of performing drug repurposing

Market crises pose significant challenges for businesses, emphasizing the importance of effective crisis management strategies. Central to these strategies is the ability to identify and retain loyal customers, who often serve as the bedrock of stability during tumultuous times. This paper investigates the application of deep meta-learning analysis to predict loyal customers as a cornerstone of market crisis management. Drawing upon an extensive literature review, the study explores previous research on market crises, customer loyalty, and the evolution of deep learning and meta-learning in crisis management contexts. Methodologically, the paper outlines data collection, model development, and evaluation procedures tailored for deep meta-learning-based customer prediction. In results, the overall accuracy of model 85%, a precision 0.88, recall 0.82, and F1-score 0.85 were obtained. The analysis demonstrates the effectiveness of deep meta-learning models in accurately identifying loyal customers during market crises, offering insights into their performance and applicability compared to traditional methods. Practical implications include potential applications in crisis management for businesses and considerations for real-world implementation.

A model that predicts levels of coronavirus (CoV) respiratory/fecal-oral transmission potentials based on the outer shell hardness has been built using neural network (artificial intelligence, AI) analysis of the percentage of disorder (PID) in the nucleocapsid, N, and membrane, M, proteins of the inner and outer viral shells, respectively. Based mainly on the PID of N, SARS-CoV-2 is categorized as having intermediate levels of both respiratory and fecal oral transmission potential. Related to this, other studies have found strong positive correlations between virulence and inner shell disorder among numerous viruses, including Nipah, Ebola, and Dengue viruses. There is some evidence that this is also true for SARS-CoV-2 and SARS-CoV, which have N PIDs of 48% and 50%, and are characterized by case-fatality rates of 7.1% and 10.9%, respectively. The link between levels of respiratory transmission and virulence lies in viral load of body fluids and organ respectively. A virus can be infectious via respiratory modes only if the viral loads in saliva and mucus exceed certain minima. Likewise, a person may die, if the viral load is too high especially in viral organs. Inner shell proteins of viruses play important roles in the replication of viruses, and structural disorder enhances these roles by providing greater efficiency in protein-protein/DNA/RNA/lipid binding. This paper outlines a novel strategy in attenuating viruses involving comparison of disorder patterns of inner shells of related viruses to identify residues and regions that could be ideal for mutation. The M protein of SARS-CoV-2 has one of the lowest M PID values (6%) in its family, and therefore this virus has one of the hardest outer shells, which makes it resistant to antimicrobial enzymes in body fluid. While this is likely responsible for its contagiousness, the risks of creating an attenuated virus with a more disordered M are discussed.

The persistence of geographic inequities in vaccination coverage often evidences the presence of zero-dose and missed communities and vulnerabilities to vaccine-preventable diseases. These inequities were exacerbated in many places during the COVID-19 pandemic, due to severe disruptions to vaccination services. Understanding changes in zero-dose prevalence and associated risk factors in the context of the COVID-19 pandemic is, therefore, critical to designing effective strategies to reach vulnerable populations. Using data from nationally representative household surveys conducted before the COVID-19 pandemic in 2018 and during the pandemic in 2021 in Nigeria, we fitted Bayesian geostatistical models to map the distribution of three vaccination coverage indicators: receipt of DTP1, MCV1 and any of the four basic vaccines (BCG, OPV0, DTP1 and MCV1), and corresponding zero-dose estimates independently at 1x1 km resolution and the district level during both time periods. We also explored changes in the factors associated with non-vaccination at the national and regional levels using multilevel logistic regression models. Our results revealed no increases in zero-dose prevalence due to the pandemic at the national level, although considerable increases were observed in a few districts. We found substantial subnational heterogeneities in vaccination coverage and zero-dose prevalence both before and during the pandemic, showing broadly similar patterns in both time periods. Areas with relatively higher zero-dose prevalence occurred mostly in the north and a few places in the south in both time periods. We also found consistent areas of low coverage and high zero-dose prevalence using all three zero-dose indicators, revealing areas in greatest need. At the national level, risk factors related to socioeconomic/ demographic status (e.g., maternal education), maternal access to and utilization of health services and remoteness were strongly associated with the odds of zero dose in both time periods, while those related to communication were mostly relevant before the pandemic. These associations were also supported at the regional level, but we additionally identified risk factors specific to zero dose in each region; for example, communication and cross-border migration in the northwest. Our findings can help guide tailored strategies to reduce zero-dose prevalence and boost coverage levels in Nigeria.

Zero-dose children, or children who have not received any routine vaccination, are a priority population for global health policy makers as these children are at high risk of mortality from vaccine-preventable illnesses. We conducted a narrative review to identify potential interventions, both within and outside of the health sector, to reach zero-dose children. We reviewed peer-reviewed and grey literature and identified 59 relevant resources. Additionally, we interviewed six key informants to enhance synthesis of our findings. Data were organized into three priority settings: (1) urban slums, (2) remote or rural communities, and (3) conflict settings. We found that zero-dose children in the three-priority settings face differing barriers to vaccina-tion and, therefore, require context-specific interventions, such as leveraging slum health commit-tees for urban slums or integrating with existing humanitarian response services for conflict set-tings. Three predominant themes emerged for grouping the various interventions: (1) community engagement, (2) health systems strengthening and integration, and (3) technological innovations. The barriers to reaching zero-dose children are multifaceted and nuanced to each setting, there-fore, no one intervention is enough. Technological interventions especially must be coupled with community engagement and health systems strengthening efforts. Evaluations of the suggested interventions are needed to guide scale up, as the evidence-base around these interventions is rel-atively small.

The purpose of this project was to demonstrate the potential of converting an existing internal combustion engine for hydrogen operation at relatively low cost and to optimize the combustion process for ultra-low NOx emissions. The conversion has been carried out on a 450cc naturally aspirated single cylinder engine. The first baseline measurements and setup have shown lower NOx emissions than the baseline gasoline engine (without catalytic converter) for similar power output and engine efficiency. Further optimization of the combustion process allowed to achieve Euro VI and (latest European Commission proposal) Euro VII heavy-duty NOx limits without exhaust gas aftertreatment system (EATS) in steady state conditions. The concept is very promising and the knowledge gained should allow for further optimization to achieve near zero NOx emissions at high engine efficiency and power output with supercharging. It should also allow an efficient conversion of other engine types for different applications. In particular, a project with the aim to convert a heavy duty 6 cylinder engine intended for public transport buses has started. It follows a feasibility study which has shown the competitiveness of the hydrogen engine for this application.

Confronting the dual challenges of rapid urbanization and climate change, although extensive research has investigated the influencing factors and practical strategies of urban carbon emissions and urban vibrancy, respectively, the unclear mutual nexus between them and the development strategy of collaborative optimization requires further in-depth analysis. This study explores the delicate balance between urban vibrancy and low-carbon sustainability within the confines of Beijing’s Fifth Ring Road. By integrating OpenStreetMap, land use, population, and building carbon emission data, we have developed a reproducible method to estimate total carbon emission and emission intensity per capita. Furthermore, we have introduced vibrancy index data to distinguish the vibrancy evaluation of residential and non-residential land and applied cross-combinational classification technology to dissect the spatial correlation between urban carbon emissions and urban vibrancy. The results reveal that the four combination typologies show more significant differences and regularity in residential land. Based on the discovery of spatial correlation, this study puts forward corresponding development strategy suggestions for each typology based on geographical location and the requirements of urban development policies of these four combination typologies. In conclusion, our study highlights the importance of integrating carbon emissions and urban vibrancy comprehensively in sustainable urban planning and proposes that various land use combinations need targeted development strategies to achieve this goal, which need to consider population, energy, service facilities, and other diverse aspects.

This paper explores the potential of using the SAM segmentator to enhance the segmentation capability of known methods. SAM is a promptable segmentation system that offers zero-shot generalization to unfamiliar objects and images, eliminating the need for additional training. The open-source nature of SAM on GitHub allows for easy access and implementation. In our experiments, we aim to improve the segmentation performance by providing SAM with checkpoints extracted from the masks produced by DeepLabv3+, then merging the segmentation masks provided by these two networks. Additionally, we examine the \enquote{oracle} method (as upper bound baseline performance), where segmentation masks are inferred only by SAM with checkpoints extracted from ground truth. In addition, we tested in the CAMO datasets an ensemble of PVTv2 transformers; combining the ensemble and SAM yields state-of-the-art performance in that dataset. The results of our study provide valuable insights into the potential of incorporating the SAM segmentator into existing segmentation techniques. We release with this paper the open-source implementation of our method.

This study aimed to evaluate the mixed and homogeneous application of the inactivated SARS-CoV-2 vaccine CoronaVac (CV) and the mRNA vaccine BNT162b2 (BNT). This prospective cohort study included 235 health care workers, who had received two prime shots with CoronaVac. They were divided into three cohorts after the third month: Cohort-I (CV/CV); Cohort-II (CV/CV/CV) and Cohort-III (CV/CV/BNT). Anti-S-RBD-IgG and total an-ti-spike/anti-nucleocapsid-IgG antibody concentrations were examined in vaccinated health workers at the 1st, 3rd and 6th months following the second dose of the vaccination. The mean age of 235 health care workers who participated in the project was 39.51±10.39 (min-max: 22-64). At the end of the 6th month, no antibodies were detected in 16.7% of Cohort-I participants, and anti-S-RDB IgG levels showed a decrease of 60% compared to the levels of the 3rd month. The antibody concentrations of the 6th month were found to have increased by an average of 5.13 times compared to the 3rd-month levels in the Cohort-II and 20.4 times in Cohort-III. The heterologous vaccination strategy “CoronaVac and BNT162b2 regimen” is able to induce a stronger immunity and it will help remove inequalities in the developing world where CoronaVac was the initial prime.

The epidemiological situation generated by COVID-19 has highlighted the importance of applying non-pharmacological measures. Among these, mass screening of the asymptomatic general population has been established as a priority strategy by carrying out diagnostic tests to limit the spread of the virus. In this article, we aim to evaluate the economic impact of mass COVID-19 screenings of an asymptomatic population through a Cost-Benefit Analysis based on the estimated total costs of mass screening versus health gains and associated health costs avoided. Excluding the value of monetized health, the Benefit-Cost ratio was estimated at approximately 0.45. However, if monetized health is included in the calculation, the ratio is close to 1.20. The monetization of health is the critical element that tips the scales in favour of the desirability of screening. Screenings with the highest return are those that maximize the percentage of positives detected.

Background: The uptake of COVID-19 booster vaccines has been significantly low. Therefore, it is questionable whether combining the COVID-19 booster vaccines with Influenza vaccines can increase the population's interest in taking such vaccines and manage the health pandemic effectively. Methodology: In this systematic review and meta-analysis, a synthesis of the findings and summary of a total of 30 research articles based on the topic, ‘combining influenza and COVID-19 booster vaccination strategy’ was undertaken. The research articles were identified from three databases, namely, PubMed, Cochran Library, and Google Scholar using specific keywords and inclusion criteria. However, research articles that were not peer-reviewed and not published in English were excluded from the systematic review and meta-analysis. The average risk ratio of the included articles was 0.78% based on a 95% CI. On the other hand, the heterogeneity between such studies was I² = 35%, while the statistical significance of their findings occurred at p < 0.05. The average p-value of the included research studies was p = 0.62, implying that the null hypothesis was not rejected in almost all the studies. Results: A synthesis of the chosen research articles revealed that when influenza and COVID-19 booster vaccines are combined, there is potential for an increase in the uptake of the latter, mainly because many populations have already been accustomed to taking influenza vaccines on an annual basis. Conclusions: In this way, through such findings, medical health experts can make informed decisions to increase the population's willingness to receive the COVID-19 booster vaccines.

The growing use of proton-exchange membrane fuel cells (PEMFC) in hybrid propulsion systems, aimed at replacing traditional internal combustion engines and reducing greenhouse gas emis-sions. Effective power distribution between the fuel cell and the energy storage system (ESS) is crucial, which has led to a growing emphasis on developing energy management systems (EMS) to efficiently implement this integration. To address this goal, this study examines the performance of a fuzzy logic rule-based strategy for a hybrid fuel cell propulsion system in a small hydro-gen-powered passenger vessel. The primary objective is to optimize fuel efficiency, with particular attention to reducing hydrogen consumption. The analysis is carried out under typical operating conditions encountered during a river trip. Comparisons between the proposed strategy with other approaches —control-based, optimization-based and deterministic rule-based— are con-ducted to verify the effectiveness of the proposed strategy. Simulation results indicated that EMS based on fuzzy logic mechanisms was the most successful in reducing fuel consumption. The superior performance of this method stems from its ability to adaptively manage power distri-bution between the fuel cell and energy storage systems.

We assessed depression, anxiety, and stress in healthcare workers (HCWs) in 2023 and the evo-lution of depression in 2023 compared with 2022. In September-November 2023, 181 HCWs from the Infectious Diseases Hospital, Cluj-Napoca, Romania, completed the Depression, Anxiety, and Stress 21 Scale (DASS-21 R), the Patient Health Questionnaire-9 (PHQ-9), and the Hamilton Anxiety Rating Scale (HAM-A). The prevalence of moderate-to-severe levels was 13.81% for DASS-Depression, 18.79% for DASS-Anxiety, 16.02% for DASS-Stress, 19.89% for PHQ-9, and 12.16% for HAM-A. Moderate-to-severe PHQ-9 clinical depression was found in 19.89% of respondents, and moderate-to-severe HAM-A clinical anxiety in 12.16%. Moderate-to-severe PHQ-9 depres-sion was significantly lower in the 2023 study group (19.89%, N=181) compared with 2022 (30.60%, N=114) (p=0.036), also within the 2022-2023 follow-up study group (N=88) (p=0.026). We did not find significant statistical differences between those infected vs. non-infected, vaccinated vs. non-vaccinated, working with vs. non-working with SARS-CoV-2 infected patients. Males were significantly more stressed (p=0.018) and anxious (p=0.034), and physicians in training had the highest prevalence of moderate-to-severe depression (31.60%), followed by physicians (25.64%). In 2023, depression, anxiety, and stress symptoms decreased but remained within a concerning range. By addressing these psychological issues, we can prevent professional crises in the healthcare system.

This study assesses the impact of nurse-originated changes in central venous catheter (CVC) management on the incidence of central line-associated bloodstream infections (CLABSI) and catheter-related bloodstream infections (CRBSI). It is a single-center retrospective cohort study conducted at an urban, tertiary referral, and academic center serving pediatric patients. The study cohort comprised 236 patients and 323 CVCs seen between 2012 and 2022. CLABSI and CRBSI were defined according to the Centers for Disease Control and Prevention definitions. Oncology nurse leaders developed CVC-specific educational modules for CLABSI prevention. All relevant information during the CVC maintenance period was noted in the patient's CVC logbook. 24 (7%) cases of confirmed CLABSI were identified. The incidence of CVC-related infections was 0.32 cases per 1000 catheter days. The incidence decreased by 40% between the first and second three-year study period. Documented exit-site infection was reported in 32 (10%) cases. The correlation between exit-site infection and CLABSI was found in 9 (28%) cases. Our CVC-related infection rates are significantly lower than the incidence reported by the Italian Association of Pediatric Hematology and Oncology, which settles at 3-5 cases per 1000 catheter days. Our data confirm the effectiveness of local CVC management guidelines in preventing CVC-related infectious complications.

Direct and indirect effects after mine operations cease must ideally be subject to perpetual monitoring routines in order to detect possible risks or avoid adverse effects on the surrounding ecosystems at an early stage. In this contribution, mining subsidence lakes created inside the nature reserve Kirchheller Heide and Hilsfeld Forest are subjected to analysis for a long-term monitoring scheme. For this purpose, we employ high-resolution unmanned aerial system (UAS)-based multispectral and thermal mapping tools to provide a fast, non-invasive and multitemporal environmental monitoring method. Specifically, we propose to monitor vegetation evolution through multispectral analysis, biotypes identification using machine learning algorithms, and water surface extent detection, together with their thermal behavior. The aim of this contribution is to present the proposed workflow and first results to establish a baseline for future analyses and subsequent surveys for longterm multi-temporal monitoring

The growing threat of antibiotic pollution in water systems demands innovative and sustainable remediation strategies. Nanocellulose-based magnetic metal-organic frameworks (MOFs) represent a cutting-edge solution for the adsorption and removal of antibiotics, leveraging their high porosity, magnetic properties, and environmentally friendly nature. This paper provides an in-depth review of recent advancements in nanocellulose-based MOFs, focusing on their synthesis, adsorption mechanisms, and applications in environmental remediation between 2020 and 2024. By summarizing key studies, we highlight their performance in targeting widely used antibiotics such as tetracyclines and fluoroquinolones. The integration of nanocellulose with MOFs not only enhances adsorption capacity but also offers easy recovery, recyclability, and environmental compatibility. This review explores their adsorption mechanisms, practical applications, and future research directions, contributing to the advancement of scalable and sustainable water treatment technologies.

Sweat rate and electrolyte losses have a large inter-individual variability, a personalized approach to hydration can overcome this issue to meet an individual’s needs. This study aimed to investigate the effects of personalized hydration strategy (PHS) on fluid balance and intermittent exercise performance. Twelve participants conducted 11 laboratory visits including a VO2max test and two 5-day trial arms under normothermic (NOR) or hyperthermic (HYP) environmental conditions. Each arm began with 3-day of familiarization exercise following by two random exercise trials with a either PHS or control (CON). Then, participants crossed-over to the second arm for: NOR+PHS, NOR+CON, HYP+PHS, and HYP+CON. The PHS was prescribed according to participants’ fluid and sweat sodium losses. CON drank ad-libitum of commercially-available electrolyte solution. Exercise trials consisted of two phases: 1) 45min constant workload; 2) high-intensity intermittent exercise (HIIT) until exhaustion. PHS had a significantly greater fluid intake compared to CON. HYP+CON produced the lowest sweat sodium concentration. HYP+PHS had a lower thirst perception and a longer HIIT compared to HYP+CON. Thus, PHS reinforces fluid intake and successfully optimizes hydration status, regardless of environmental conditions. PHS may be or is an important factor to preventing negative physiological consequences during high-intensity exercise in the heat.

Many corporations aspire to become Net Zero Carbon Dioxide by 2030-2050. This paper examines what it will take. It requires understanding where energy is produced and consumed, the magnitude of CO2 generation, and the Carbon Cycle. Reviews are provided for prior technologies for reducing CO2 emissions from fossil to focus on their limitations and to show that none offer a complete solution. Both biofuels and CO2 sequestration reduce future CO2 emissions from fossil fuels. They will not remove CO2 already in the atmosphere. Planting trees has been proposed as one solution. Trees are a temporary solution. When they die, they decompose and release their carbon as CO2 to the atmosphere. The only way to permanently remove CO2 already in the atmosphere is to break the Carbon Cycle by growing biomass from atmospheric CO2 and sequestering biomass carbon. Permanent sequestration of leaves is proposed as a solution. Leaves have a short Carbon Cycle time constant. They renew and decompose every year. Theoretically, sequestrating a fraction of the world’s tree leaves can get the world to Net Zero without disturbing the underlying forests. This would be CO2 capture in its simplest and most natural form. Permanent sequestration may be achieved by redesigning landfills to discourage decomposition. In traditional landfills, waste undergoes several stages of decomposition, including rapid initial aerobic decomposition to CO2, followed by slow anaerobic decomposition to methane and CO2. The latter can take hundreds to thousands of years. Understanding landfill chemistry provides clues to disrupting decomposition at each phase.

A prospective clinical-epidemiological study was conducted to evaluate the dynamics of biomarkers in hospitalized patients with moderate to severe COVID-19 (according to the National Institute of Health severity scale) treated with Anakinra, compared to those receiving standard treatment. The study included 65 patients with a mean age of 75.51±9.54 years, ranging from 44 to 99 years. Among the study participants, 38 (58.5%) were male and 27 (41.5%) were female. The patients were divided into two groups: control group (standard treatment): 24 patients (36.9%) and target group (Anakinra treatment): 41 patients (63.1%). The results showed a significant relationship between the dynamics of leukocytes, ASAT, LDH, D-dimer, ferritin, and IL-6 and the administration of Anakinra. In the control group, no significant dynamics were observed in leukocyte count, D-dimer, ferritin, or IL-6. A statistically significant decrease in ASAT and LDH values in the control group was noted only on Day 7. In the Anakinra group, significantly (or with borderline statistical significance, p&lt;0.1) lower mean values were observed for leukocytes, NLR, D-dimer, ferritin, and IL-6 on Days 3 and 7 compared to the control group. Additionally, significantly lower CRP values were detected in the Anakinra group on Day 7 compared to the control group.

The influenza virus has been the primary cause of the pandemic, posing a constant threat to human society. Due to its genetic evolution and continuous outbreak, antiviral research currently focuses on exploring a novel lead agent. A comprehensive antiviral screening discovered a marine bacterium whose extract exerted excellent efficacy against influenza viruses. Parerythrobacter sp. M20A3S10, a novel strain under the family Erythrobacteraceae, could produce carotenoids exhibiting antiviral and anticancer activity by enhancing the cellular immune system. Post-treatment of M20A3S10 extract showed outstanding therapeutic indexes: against influenza virus A/PR8 (H1N1) [selectivity index (SI) = 24.0], A/Wisconsin/15/2009 (H3N2) (SI = 30.1) and B/Florida/78/2015 (SI = 38.2). Comparably, the effectiveness was demonstrated against Zika virus (ZIKV) and dengue virus type 2 (DENV2) with an SI of 22.5 and 24.1, respectively, namely broad-spectrum activity. Of note, the antiviral responses resulted from the common replication mechanism between IAV, ZIKV, and DENV2. The stimulation of apoptosis-mediated cellular immunity prevented the viral release and protected the host, suggesting that switching from necroptosis to apoptosis is a novel antiviral target. Although the specific compound affecting the antiviral activity was not identified, its promising efficacy with broad activity will contribute to developing a strategy for preventing future pandemics.

To enable net zero sustainable thermal building energy this study develops an open-source thermal house model to couple solar photovoltaic (PV) and heat pumps (HP) for grid-connected residential housing. The calculation of both space heating and cooling thermal loads and the selection of HP is accomplished with a validated Python model for air-source heat pumps. The capacity of PV required to supply the HPs is calculated using an System Advisor Model integrated Python model. Self-sufficiency and self-consumption of PV and the energy imported/exported to the grid for a case study are provided, which shows that simulations based on the monthly load profile have a significant reduction of 43% for energy sent to/from the grid compared to the detailed hourly simulation and an increase from 30% to 60% for self-consumption and self-sufficiency. These results show the importance of more granular modeling and also indicate mismatches of PV generation and HP load based on hourly simulation datasets. The back-calculation PV sizing algorithm combined with HP and thermal loads presented in this study exhibited robust performance. The results indicate this approach can be used to accelerate the solar electrification of heating and cooling to offset the use of fossil fuels in northern climates.

The COVID-19 pandemic has underscored the intricate interplay between viral infections and opportunistic bacterial pathogens such as Klebsiella pneumoniae. K. pneumoniae harbors various antibiotic resistance determinants like extended-spectrum and plasmid-mediated AmpC β-lactamases and carbapenemases. In the two years following the pandemic, carbapenemase producing K. pneumoniae isolates obtained routinely in outpatient and inpatient setting demonstrated similar resistance patterns which prompted research. The aim was to compare and subsequently analyze carbapenem-resistant hospital and outpatient’s K. pneumoniae isolates’ resistance mechanisms, traits and molecular epidemiology, following the COVID-19 pandemic. Disk diffusion and broth dilution method were the methods of choice to determine antibiotic susceptibility. β-lactamases were screened by phenotypic methods and confirmed with PCR. In total 113 isolates were analysed. Resistance to amoxicillin-clavulanate and ertapenem was confirmed in all strains. High resistance rates (over 90%) were observed for extended-spectrum cephalosporins, and ciprofloxacin. OKNV testing and PCR detected OXA-48 in 106, NDM in 7 and KPC in only one isolate. ESBLs accompanied carbapenemases in 103 isolates. Carbapenem resistance in K. pneumoniae is becoming a global problem, hence careful monitoring of its resistance traits is of utmost importance in order to combat the arising threat. OXA-48 seems to continue predominating in the turbulent period after pandemic.

The ongoing conflict in Syria and Iraq has caused many residents of these countries to flee. This study explored how these refugees cope with traumatic experiences from pre-migration to post-migration phases and how they develop resilience experiences at the individual, familial, and community levels. Data were collected through individual interviews and analyzed using Interpretative Phenomenological Analysis. A discussion of the findings revealed (1) a cumulative effect of prolonged adversity from pre-migration to resettlement phases; (2) the impacts of post-migration context as it facilitates refugees’ adjustment or leads to re-traumatization through increased marginalization; and (3) finally, an overview of refugees’ ongoing survival. Clinical implications are presented along with policy implications and future directions for research.

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.

Despite the increase in popularity of Zero Waste (ZW) concept, the successful implementation of this concept in waste management is still facing many challenges. The plastic recycling rate in Australia is currently only about 9.4%, which could leave up to 90.6% of plastic consumption being sent to landfills. The state of Victoria (in Australia) has proposed an ambitious plan to upgrade its waste and recycling system and to divert about 80% of waste from landfills by 2030. The aim of this research is to study Victoria’s current waste management plan and to develop a simulation model to assess the feasibility of it achieving zero plastic waste by 2035. In this direction, a fundamental knowledge of global ZW implementation needs to be acquired in order to understand the challenges, obstacles, and uncertainties in achieving ZW target. A simulation model is established using a method called double baselines. This method was developed as an improvisation to address the limitation of data availability for the model development. The model will run on 4 scenarios including one from Victoria’s current plan. Outcomes from the model are produced in comparative charts covering 6 key considerations including the rates of plastic consumption, waste to landfill, diversion, recycling, relative accumulative cost and effort. The findings of this study pointed out that Victoria’s current plan are feasible for its goal and presented with opportunities for improvement especially towards zero plastic waste. Besides, study results also reveal that the Victoria’s current plan to achieve 80% diversion rate by 2030 is possible but the zero plastic waste target by 2035 is less likely to happen.

This article explores how digitalisation is impacting the hospitality industry and assesses the evolving role of Information Technology (IT) strategy in the digitalisation process. The research approach is qualitative and inductive, based on six in-depth interviews with senior IT professionals in the hospitality industry. Findings indicate significant differences in the role of IT strategy in guiding digitalisation in the companies studied. The depth of information provided by the interviewees supports the development and application of a model that profiles the companies regarding their degree of digitalisation and technology integration. Analysis of interview material allows the identification of key properties for successful digitalization: process agility, workforce adaptability, and technology manageability, along with a clear data culture and ensured cybersecurity. However, disparate systems and technologies, and a lack of data integrity, are key issues that leave hospitality companies with difficult choices in progressing digitalisation initiatives. The applied model and identification of key properties for successful digitalisation contribute to the development of related theory and can also be used as a reference point for senior IT professionals working in the industry.

Nodes in wireless sensor networks (WSN) are characterized particularly by their limited power and memory capabilities. Limited memory is an important parameter as it defines the size of the operating system and the processing code. As established previously, energy and memory efficiency is the most important evaluation factors of WSNs as they are directly related to data loss and network lifetime. However, based on our simulation results, memory efficiency determines the selection or abandon of nodes by the botmaster for the propagation of bots in an IoT infrastructure. Consequently, the node’s memory efficiency determined the spread of bots in the network and provides defense actors with an insight of the botmaster behavior for mitigation of the attack. Conventional botnet propagation and mitigation models did not consider the impact of node’s memory efficiency in the IoT platform. To address this gap, we build IoT-SIEF, a novel propagation model with forensic capability that will analyze command and control propagation behavior based on the perspective of the node’s memory efficiency. IoT-SIEF model used to explore the dynamics of propagation using numerical simulation with more than 50% outperform other models in mitigating the number of secondary bots. Consequently, it can serve as a basis for assisting the planning, design, and defense of such networks from the investigator's point of view.

COVID-19, a rapidly spreading new strain of coronavirus, has affected more than 150 countries and received worldwide attention. The lack of efficacious drugs or vaccines against SARS-CoV-2 has further worsened the situation. Thus, there is an urgent need to boost up research for the development of effective therapeutics and affordable diagnostic against COVID-19. The crystallized form of SARS-CoV-2 main protease (Mpro) was demonstrated by a Chinese researcher Liu et al. (2020) which is a novel therapeutic drug target. This study was conducted to evaluate the efficacy of medicinal plant-based bioactive compounds against COVID-19 Mpro by molecular docking study. Molecular docking investigations were performed by using Molegro Virtual Docker 7 to analyze the inhibition probability of these compounds against COVID-19. COVID-19 Mpro was docked with 80 flavonoid compounds and the binding energies were obtained from the docking of (PDB ID: 6LU7: Resolution 2.16 Å) with the native ligand. According to obtained results, hesperidin, rutin, diosmin, apiin, diacetylcurcumin, (E)-1-(2-Hydroxy-4-methoxyphenyl)-3-[3-[(E)-3-(2-hydroxy-4- methoxyphenyl)-3-oxoprop-1-enyl]phenyl]prop-2-en-1-one, and beta,beta'-(4-Methoxy-1,3- phenylene)bis(2'-hydroxy-4',6'-dimethoxyacrylophenone have been found as more effective on COVID-19 than nelfinavir. So, this study will pave a way for doing advanced experimental research to evaluate the real medicinal potential of these compounds to cure COVID-19.

In large-capacity energy storage systems, instructions are decomposed typically using an equalized power distribution strategy, where clusters/modules operate at the same power and durations. When dispatching shifts from stable single conditions to intricate coupled conditions, this distribution strategy inevitably results in increased inconsistency and hastened system aging. This paper presents a novel differentiated power distribution strategy comprising three control variables: the rotation status, the operating boundaries for both Depth of Discharge (DOD) and C-rates (C) within a control period. The proposed strategy integrates an aging cost prediction model developed to express the mapping relationship between these control variables and aging costs. Additionally, it incorporates the multi-colony particle swarm optimization (Mc-PSO) algorithm into the optimization model to minimize aging costs. The aging cost prediction model consists of three functions: predicting health features (HFs) based on the cumulative charge/discharge throughput quantity and operating boundaries, characterizing HFs as comprehensive scores, and calculating aging costs using both comprehensive scores and residual equipment value. Further, we elaborated on the engineering application process for the proposed control strategy. In the simulation scenarios, this strategy prolonged the service life by 14.62%, reduced the overall aging cost by 6.61%, and improved module consistency by 21.98%, compared with the traditional equalized distribution strategy. In summary, the proposed strategy proves effective in elongating service life, reducing overall aging costs, and increasing the benefit of energy storage systems in particular application scenarios.