The opportunities and advantages of implementing Artificial Intelligence (AI) and Machine Learning (ML) to optimize the process control of wastewater treatment in the Oil and Gas industry are discussed in this work. Discussion is centered around five major points: 1) Various types of Oil and Gas wastewater (Sour, Oily, Produced) and industry standards/methods for treatment, including specific case studies and challenges when treating certain wastewater. This section aims at the common types of wastewater in the Oil and Gas industry and how they are generally treated. 2) How AI/ML has been implemented in wastewater treatment in various industries; summary of which AI/ML languages were used along with a brief overview of how they work. This article focused on an understanding of the specific case studies and AI explanations to understand the effectiveness of wastewater treatment using AI/ML. 3) AI that is currently implemented in Oil and Gas such as personal protective equipment (PPE), smartwatches radiofrequency identification etc. This showed that AI/ML already plays a successful role in the Oil and Gas industry and has proven to help optimize many processes and components. Many of these AI/ML implementations are now industry standards and have greatly benefitted the industry. This section demonstrates that the implementation and the use of AI/ML have been proven to be a successful endeavor and that expanding the role of AI/ML would be beneficial. 5) Using the established points from the previous sections the paper outlines why AI/ML is ideal for Oil and Gas wastewater treatment; this argument centers around fit-for-purpose treatment, and the possible uses of the treated water. A determination of the best-suited AI languages, possible implementation scenarios, and how this would shift the way Oil and Gas industries treat and approach wastewater is presented to the reader.

Buildings consume 30% of the total energy consumption around the globe and 29% of the energy consumption in Egypt which in 2022 had a total population of 102 million, out of which 43 % live in urban areas . The operation of buildings contributes to around 30% of global CO2 emissions due to their high energy consumption (IEA, 2022a). Among the efforts made towards improving the energy efficiency of buildings are Advanced Energy Design Guides (AEDGs), building rating systems, codes, and standards. Furthermore, numerous research studies that are either literature review studies, experimental studies, or computational studies addressed the topic of energy efficiency in buildings. These are all examined in this literature review with the purpose of identifying the research gap in available research with a focus on Egypt. The identified gap is the development of a prescriptive path for the GPRS energy efficiency category based on whole building energy simulations.

Organic solar cells are contributing extensively to the production of future large area and cost-effective sources of renewable energy with a compact environmental impact. Moreover, due to tunable optical properties of the active medium, the semi-transparent organic solar cell can be fabricated and become a promising nominee for building Integrated Photovoltaics (BIPV), vehicles, and mobile electronic devices. Therefore, three newly synthesized polymers used as were host materials for the active medium and blended with beetroot dye. Hence, based on BHJ structure two ternary systems have been constructed and utilized to fabricate semitransparent solar cells and characterized. The results show that the natural dye has a crucial impact on solar cell characteristic parameters. Consequently, large value of V_OC close to 1V were obtained for ternary systems and acceptor material named PINDOLE exhibits potentials for electron transport layer (ETL) and shows an improvement in both fill factor and device efficiency.

Traditional path planning algorithms have drawbacks in unmanned vehicle path planning, such as low efficiency, unsuitability for dynamic environments, and high computational complexity. To address these issues, this paper proposes a dynamic path planning method for unmanned vehicles that combines the A* algorithm with an improved Dynamic Window Approach (DWA). Firstly, a collision risk function is incorporated into the DWA algorithm to evaluate scores based on the braking distance corresponding to the current vehicle speed and the distance to obstacles, determining whether timely braking or obstacle avoidance is feasible. The earlier the braking or obstacle avoidance, the higher the score, thereby enhancing the evaluation algorithm of the DWA. Secondly, the key points extracted by the A* algorithm are used as temporary target points for the DWA algorithm, reducing the eight search directions to five. Finally, the key points of the A* algorithm’s path are set as the temporary end points for the DWA algorithm, integrating the two algorithms to plan a smoother curved path that can avoid unknown and dynamic obstacles. Simulation data demonstrates that compared to traditional artificial potential field methods, RRT, and Dijkstra’s algorithm, the new fusion algorithm reduces time by 11.71 seconds, a decrease of 6.9%, and shortens path length by 3.093 meters, a reduction of 4.16%, while increasing average linear velocity by 2.9%. The proposed algorithm ensures smoother paths while also making paths more rational and efficient

Visual Sensor Networks (VSNs) have been the focus of numerous studies, emphasizing the quality of the information they generate. The primary goal of these networks is to capture data from an area, extract the pertinent information from the visual scene, and facilitate communication. However, the presence of objects in the study area can impacted the network's efficiency, linking the quality of acquired data directly to the positioning of the cameras. Strategically positioning multiple cameras in a potentially complex area, while ensuring effective communication between nodes, presents a challenging issue in VSNs applications. This paper introduces a specific method to enhance the deployment of visual sensors in indoor environments. The research addresses the theme of multi-objective optimization of VSN deployment, integrating various criteria: maximizing overall visual coverage, maximizing the observation of zones of interest, maximizing observation redundancy of zones of interest and ensuring communication connectivity for data transfers. To tackle this problem, we simulate the observed environment incorporating cameras, obstacles, and considering zones of interest. Camera positioning is performed while considering visual constraints and the scene's characteristics. The quality of positioning is evaluated based on the defined objective functions. Initially, a comparative study is conducted with a state-of-the-art approach, integrating the first three objective functions. Subsequently, we incorporate the fourth objective function to ensure data transfers. The proposed method demonstrates efficient camera network deployments in indoor areas, considering global coverage and observation redundancy. In contrast to the state-of-the-art, these results are achieved in areas with visual obstacles while ensuring communication connectivity between the different cameras.

The company strategic procurement function makes a significant contribution to overall corporate success, and yet remains under-researched in terms of digitalisation and digital maturity. This research adopts an inductive case study approach, using qualitative data from in-depth inter-views with industry practitioners, to develop and apply a digital maturity model for the deployment of strategic procurement analytics. The research presents a snapshot of the digital maturity of the strategic procurement function of a global aircraft manufacturer, and finds that current exploitation of analytics remains constrained by a range of factors, including the need for close compliance with regulatory norms. Thematic analysis of the interview material provides the basis for the development of the maturity model, which - although geared to a specific industry context - is nevertheless of relevance in other business environments. The research thus con-tributes to the existing literature in this field, and will also be of interest to procurement professionals. However, the research clearly has its limitations, not least in that it is based on just one industry case, and cross-industry generalisations from the findings must therefore be treated with caution.

Driven by environmental sustainability concerns, the integration of biobased components in curtain wall systems is gaining traction in both research and the construction market. This paper explores the development and validation of a bio-based façade system within the Basajaun H2020 project. The project aimed to demonstrate the feasibility of introducing environmentally friendly bio-based components into the mature curtain wall façade industry. The paper focuses on identifying technological solutions for replacing key components such as profiles, insulation, and the tightness system with bio-based and less environmental impact alternatives presenting the results achieved in the façade system design of the Basajaun project funded by European Union. These solutions aimed at creating a bio-composite-based curtain wall façade that adheres to current building envelope standards and normative; to implement diverse façade typologies for vision panels, opaque sections, and integrated windows; to engineer the prefabrication process for industrialization, enabling wider market replication and simplified transport and installation. The results demonstrate that the Basajaun façade successfully integrates selected components and meets the performance requirements set by regulations. However, questions remain regarding the workability of bio-based profiles as a commercially viable, ready-to-market solution that can replace traditional aluminum profiles in the curtain wall façade industry.

This study provides a comprehensive comparison of the Peter Chew Sum method and Newton's Sum in Quadratic Root Function Computations. Both methods offer significant advancements by alleviating the need for memorization of multiple formulas. However, when confronted with higher-order quadratic root functions such as +. Newton's Sum method proves cumbersome due to its requirement of all previous answers for final computation, leading to increased steps and error risks. In contrast, the Peter Chew Sum method simplifies the computational process by requiring only a few previous answers, resulting in a more straightforward series of operations. We contextualize our analysis within the historical progression of mathematical techniques, highlighting the transformative leap represented by the Peter Chew Sum method in quadratic root function computations. Peter Chew Sum addressing the limitations of Newton's Sum , especially concerning higher-order functions such as+ . Furthermore, study demonstrates that the innovative approach of the Peter Chew Sum method not only simplifies complex computations but also fosters enhanced conceptual understanding among students. In conclusion, study findings underscore the profound impact of the Peter Chew Sum method on quadratic root function computations.

This article serves as a preliminary introduction to the design of a new, open-source applied and computational category theory framework, named Categorica, built on top of the Wolfram Language. Categorica allows one to configure and manipulate abstract quivers, categories, groupoids, diagrams, functors and natural transformations, and to perform a vast array of automated abstract algebraic computations using (arbitrary combinations of) the above structures; to manipulate and abstractly reason about arbitrary universal properties, including products, coproducts, pullbacks, pushouts, limits and colimits; and to manipulate, visualize and compute with strict (symmetric) monoidal categories, including full support for automated string diagram rewriting and diagrammatic theorem-proving. In so doing, Categorica combines the capabilities of an abstract computer algebra framework (thus allowing one to compute directly with epimorphisms, monomorphisms, retractions, sections, spans, cospans, fibrations, etc.) with those of a powerful automated theorem-proving system (thus allowing one to convert universal properties and other abstract constructions into (higher-order) equational logic statements that can be reasoned about and proved using standard automated theorem-proving methods, as well as to prove category-theoretic statements directly using purely diagrammatic methods). Internally, Categorica relies upon state-of-the-art graph and hypergraph rewriting algorithms for its automated reasoning capabilities, and is able to convert seamlessly between diagrammatic/combinatorial reasoning on labeled graph representations and symbolic/abstract reasoning on underlying algebraic representations of all category-theoretic concepts. In this first of two articles introducing the design of the framework, we shall focus principally upon its handling of quivers, categories, diagrams, groupoids, functors and natural transformations, including demonstrations of both its algebraic manipulation and theorem-proving capabilities in each case.

Dengue is one the most significant mosquito-borne viral diseases globally, with its prevalence extending across tropical and subtropical regions, exerting a considerable financial strain on health systems. Despite decades of research leading to the development of a vaccine implemented in endemic countries, its usage remains restricted to a fraction of the population at risk of contracting dengue. Due to these limitations, there is a growing focus on research aimed at unraveling the cellular mechanisms crucial for Dengue virus (DENV) infection to pinpoint potential host targets. Multiple studies propose a pivotal role of cytoskeletal remodeling in DENV infection. Specifically, DENV alters the organization of actin to facilitate viral entry, replication, and release. In this study, we investigated the involvement of the protein c-Abl, a kinase crucial in actin dynamics, in the context of DENV infection. Our findings suggest that either silencing or pharmacological inhibition of the kinase c-Abl leads to accumulation of dengue ENV protein in vitro, associated with actin remodeling. These results illuminate cellular mechanisms that could serve as potential therapeutic alternatives for dengue management.

Geopolitical situations, such as the Ukraine–Russia war, the Israel–Hamas war, and pandemics, can disrupt supply chains, such as the rerouting of oil tankers via South Africa to avoid the impact of the Israel–Hamas conflict. These events will probably occur again, but they are black swan events and difficult to predict. How can firms manage these events to minimise disruption to their supply chains? This paper proposes that a blockchain architecture has the potential to build resilience in supply chains and give them the flexibility to withstand the challenges of black swan events. The decentralisation ability of blockchain technology enables separation of the discrete elements of a sustainable supply chain so contagion does not impact the overall sustainable supply chain. To achieve flexibility in a sustainable supply chain ecosystem requires governance, leadership, and management. Also, artificial intelligence (AI), in conjunction with blockchain, is a technology that can enhance the flexibility and resilience of the supply chain. Thus, AI can act as a controller, co-ordinator, and an integrator in sustainable supply chain systems.

We study epidemic spreading in complex networks by a multiple random walker approach. Each walker performs an independent simple Markovian random walk on a complex undirected (ergodic) random graph where we focus on Barabási-Albert (BA), Erdös-Rényi (ER) and Watts-Strogatz (WS) types. Both, walkers and nodes can be either susceptible (S) or infected and infectious (I) representing their states of health. Susceptible nodes may be infected by visits of infected walkers, and susceptible walkers may be infected by visiting infected nodes. No direct transmission of the disease among walkers (or among nodes) is possible. This model mimics a large class of diseases such as Dengue and Malaria with transmission of the disease via vectors (mosquitos). Infected walkers may die during the time span of their infection introducing an additional compartment D of dead walkers. Infected nodes never die and always recover from their infection after a random finite time. This assumption is based on the observation that infectious vectors (mosquitos) are not ill and do not die from the infection. The infectious time spans of nodes and walkers, and the survival times of infected walkers, are represented by independent random variables. We derive stochastic evolution equations for the mean-field compartmental populations with mortality of walkers and delayed transitions among the compartments. From linear stability analysis, we derive the basic reproduction numbers R M , R 0 with and without mortality, respectively, and prove that R M < R 0 . For R M , R 0 > 1 the healthy state is unstable whereas for zero mortality a stable endemic equilibrium exists (independent of the initial conditions) which we obtained explicitly. We observe that the solutions of the random walk simulations in the considered networks agree well with the mean-field solutions for strongly connected graph topologies, whereas less well for weakly connected structures and for diseases with high mortality. Our model has applications beyond epidemic dynamics, for instance in the kinetics of chemical reactions, the propagation of contaminants, wood fires, among many others.

Objectives: To study sociodemographic and clinical variables including psychiatric comorbidities in patients with irritable bowel syndrome. Methods: A total of 150 patients were screened to select 100 patients for the study who were attending a medical gastroenterology clinic in a tertiary care centre in north India. Diagnosis of IBS was made using Rome IV criteria and severity of symptoms were assessed by the Irritable Bowel Syndrome Symptom Severity Scale (IBS-SSS). Clinical evaluation was done for screening of psychiatric comorbidities and diagnosis was made as per DSM 5. Depression, Anxiety and Stress Scale - 21 Items (DASS-21) and Somatic Symptom Scale–8 (SSS-8) were used to assess depression, anxiety, stress and somatic symptoms. Result: The mean age of cases was 35.6 years and majority were i.e., 38.0% in 18-29 years. Males were 62.0% and females were 38.0%. 61.0% of the cases were diagnosed with Moderate IBS. Evaluation on DASS-21 revealed 53.0% were in moderate category in depression, 43.0% were having moderate anxiety and 36.0% were having moderate stress. 48% cases were in high category in somatic symptom scale. Psychiatric comorbidities were present in 29.0% of cases. Depressive disorders were most common psychiatric comorbidity. Conclusion: Patients with IBS presenting to tertiary care centre in Northern India were mostly young males living in semi-urban area, belonging to hindu region, married and had a nuclear family. Patients with IBS commonly have associated psychiatric disorders; anxiety disorders and depression are most common.

A self-propelled electric tea seed-planter is designed to address the lack of tea seed seeding equipment, low seeding efficiency, and poor seeding uniformity. Based on the physical characteristics of the tea seeds and the agronomic requirements of tea planting, the key structure of the planter is designed, and the structural parameters are determined. The motor and battery configurations are determined by calculating the power consumption of the entire machine. In a field experiment, the driving gear (A), ditching depth (B), and planting gear position (C) are used as test factors, and the acceptance index (AI), replay index (RI) and leakage index (LI) are used as test indexes. The test results showed that the driving speed and planting gear position significantly affect the acceptance index, replay, and leakage index, whereas the ditching depth has little effect on the performance indexes. When the driving speed was medium, ditching depth was 30 mm, and planting gear position was in the third gear, the corresponding acceptance index was 87.22%, the replay index was 8.89%, and the leakage index was 3.89%. The test prototype has a good working quality and can provide theoretical guidance for production practices.

Visits to coastal and inland-waterways have strong associations with many health and economic benefits but are also opportunities for exposure to environmental pollution. In England, few balanced survey samples exist which can facilitate accurate identification of correlates with recreation in blue spaces. This information could support risk assessment for likelihood of exposure and message targeting in case of environmental threats. We process data from a recent (2022-2023) and large (n = 177,551) survey of English residents to describe demographic, seasonal and regional correlates with any participation in water-based recreational activities in previous year (logistic regression model), and in the previous 28 days (zero-inflated negative binomial regression). Activities studied were: surfing and paddleboarding; open water swimming; scuba-diving and snorkelling; canoeing and kayaking; angling. Summer was associated with most frequent participation, winter with fewest sessions except for rowing. Anglers were group most likely to be socially vulnerable: less likely to be university educated, more likely to be disabled and especially likely to be male. People resident in rural locations were more likely to participate at least once in prior year, but did not have higher participation rates in the previous 28 days. Regional variations in specific activities may suggest where demand for water recreation is unmet. The results provide a reference description of outdoor water-recreationalists doing specific types of activity in England and may be useful when designing emergency messages and otherwise setting policy with regard to management of microbiological, radiological or chemical hazards in coastal and inland waters.

Neonatal sepsis is a leading cause of morbidity and mortality in neonates, particularly in low and middle-income countries. The emergence of antimicrobial resistance is a rapidly growing global problem. A significant proportion of the pathogens that commonly cause neonatal sepsis are resistant to multiple antibiotics. Therefore, for the empirical treatment of neonatal sepsis, the repurposing of older antibiotics that are effective against multidrug-resistant pathogens is being investigated. This review aims to provide an overview of current research and experience using the repurposed antibiotics, Colistin and Fosfomycin, for the empirical treatment of neonatal sepsis. Based on current knowledge, Colistin and Fosfomycin may be potentially helpful for the empirical treatment of sepsis in neonates due to their efficacy against a wide range of pathogens and acceptable safety profile.

Angola is vulnerable to climate change, as most of its agriculture is rain-fed and repre-sents the backbone of the people of the southern region of the country, and many peo-ple’s livelihoods depend on it. All crops can suffer from the impacts of climate change, which can lead to challenges in agricultural production and food security in different regions of the world. The work consisted of a systematic review of the impacts of climate change on agriculture in Angola, particularly in the southern region. To achieve this objective the PRISMA2020 methodology was used, using the flowcharts for the selection of studies evaluated from the databases that are: Scopus and Web Sci-ence, resulting in 431 documents published between 1996 and 2023, and of these only 63 were included in the systematic review, with inclusion and exclusion criteria. Research on the short and long-term effects of climate change impacts in agriculture in Angola and in particular the southern region is scarce and insufficient. Temperatures are pre-dicted to rise and precipitation generally decreases over time (approximately -2% by 2100), with the southern region experiencing a stronger drop in precipitation. Agri-culture in Angola will be hit hard and some models show that agricultural productiv-ity will be up to 7% lower by 2050 owing to climate change.

Lower urinary tract dysfunction is clinically important because it may cause urinary tract infections, mainly due to accumulation of residual urine, and adversely affect renal function. In addition, it may cause urinary incontinence, strongly affecting the child’s quality of life. The function of the lower urinary tract is closely associated with function of the bowel because constipation is commonly present with bladder dysfunction. The interplay between the lower urinary tract and bowel function, coupled with common conditions such as detrusor overactivity and voiding dysfunction, requires a nuanced diagnostic approach. Detrusor overactivity, a benign but socially harmful condition, is the principal cause of daytime urinary incontinence in childhood. It needs to be differentiated from more serious conditions such as neurogenic bladder dysfunction or urethral obstruction. Voiding dysfunction, a habitual sphincter contraction during voiding, is common in children with detrusor overactivity, may be selflimiting but may also result in residual urine and urinary tract infections. It may resemble, in severe cases, the neurogenic bladder dysfunction, most often caused by spinal dysraphism which very often leads to recurrent urinary tract infections and high intravesical pressures, jeopardizing renal function. Voiding diary is crucial in the initial evaluation of lower urinary tract function in children.

Anticipating and planning for the urgent response to large-scale disasters is critical to increase the probability of survival in these events. These incidents present various challenges that complicate the response, such as unfavorable weather conditions, difficulties in accessing affected areas, and the geographical spread of the victims. Furthermore, local socioeconomic factors such as insufficient prevention education, limited disaster assets, and inadequate coordination between public and private emergency services may complicate these situations. In large-scale emergencies, multiple hotspots are usually observed, which requires efforts to coordinate the strategic allocation of human and material resources in different geographical areas. Therefore, the precise management of these resources based on the specific needs of each area becomes fundamental. To address these complexities, this paper proposes a methodology that models these scenarios as an optimization problem, focusing on the location and allocation of resources in mass casualty incidents. The proposed case study is Mexico City in a post-earthquake scenario, using voluntary geographic information, open government data, and historical data from the September 19, 2017 earthquake. Additionally, it is assumed that the resources that require optimal location and allocation are ambulances, which focus on medical issues that affect the survival of victims. The designed solution involves the use of a metaheuristic optimization technique, along with a parameter tuning technique, to find configurations that perform at different instances of the problem, i.e., different hypothetical scenarios that can be used as a reference for future possible situations. Finally, the objective is to present the different solutions graphically, accompanied by relevant information to facilitate the decision-making process of the authorities responsible for the practical implementation of these solutions.

The intricate mechanisms of the immune response elicited by vaccines and the interplay between the immune system and the central nervous system (CNS) are poorly understood. This review explores these mechanisms, emphasizing the interplay between the immune system and the central nervous system (CNS). A critical aspect is the examination of how vaccine-induced immune responses can interact with the CNS, influencing neuroinflammation and neuroimmune interactions. Furthermore, the link between vaccination and persistent symptoms observed in long-COVID patients is discussed. Vaccination initiates a complex cascade of events, starting with the production of specific proteins, such as S1/S2 spike proteins, leading to robust immune activation in the axillary lymph nodes. The role of macrophages and antigen-presenting cells (APCs) in cytokine production, antigen presentation, and the stimulation of B and T cells highlights the sophistication of the adaptive immune response. The migration of immune cell-derived exosomes to the brain plays a dynamic role in CNS inflammation, neurodegenerative processes and long COVID. On the other hand, the prolonged presence of viral and vaccine-derived spike proteins may contribute to the complex pathophysiology of Long-COVID, shedding light on the delicate balance between beneficial immune responses and possible adverse neurological outcomes of vaccination. It is worth rigorous monitoring and further research to understand the mechanisms of neuroinflammation and the persistence of spike proteins and their long-term effects on the brain, emphasising the importance of a nuanced approach to vaccine safety and efficacy in the context of COVID-19 and beyond.Principio del formulario

It has been well established that hypertension is considered as a predominant risk factor for the development of cardiovascular diseases. Despite the link between hypertension and cardiovascular diseases, hypertension may directly affect the cardiac function leading in heart failure, mostly with preserved ejection fraction (HFpEF). There are echocardiographic findings indicating hypertensive heart disease (HHD) defined as altered cardiac morphology (left ventricular concentric hypertrophy, left atrium dilatation) and function (systolic or diastolic dysfunction) in patients with persistent hypertension irrespective of cardiac pathologies to which it contributes, such as coronary artery disease and kidney function impairment. In addition to classical echocardiographic parameters, novel indices, like speckle tracking of the left ventricle and left atrium, 3D volume evaluation, myocardial work in echocardiography may provide more accurate and reproducible diagnostic and prognostic data in patients with hypertension. However, their use is still underappreciated. An early detection and prompt therapy of HHD will greatly improve the prognosis. Hence, in the present review, we shed light on the role of echocardiography in the contemporary diagnostic and prognostic approach of HHD.

Pseudomonas aeruginosa infections are the focus of new treatment alternatives due to their frequent development of resistance to antibiotics and formation of biofilms. Recently, emphasis has been placed on combinations of antibiotics with drugs used for different indications. In this study the combined effects of metformin with imipenem, ceftazidime, cefepime, ciprofloxacin and levofloxacin has been investigated. 50 P. aeruginosa isolates isolated from patients with cystic fibrosis come to Gaziantep University Microbiology Laboratory were included in the study. The susceptibilities of the isolates to antibiotics were investigated by the liquid microdilution method and the combined effect of metformin and antibiotics by the chequerboard synergy test. In our study, as a result of the chequerboard synergy test; synergy between ceftazidime and metformin 6%, partial synergistic 22% isolates; while no synergistic effect was detected between cefepime and metformin in any isolate, partially synergy 46%; synergy between imipenem and metformin 4%, partial synergy 10%; synergy between ciprofloxacin and metformin 6%, partial synergy 6%, antagonist effect 2%; synergy was detected between levofloxacin and metformin 2% and a partial synergy was detected 12%. This study shows that metformin could be a potential antibiotic in its current form or in different chemical forms to be produced synthetically.

Neutrophil elastase (NE) is taken up by macrophages, retains intracellular protease activity and induces a pro-inflammatory phenotype. However, the mechanism of NE-induced pro-inflammatory polarization of macrophages is not well understood. We hypothesized that intracellular NE degrades histone deacetylases (HDAC) and Sirtuins, disrupting the balance of lysine acetylation and deacetylation, and resulting in nuclear to cytoplasmic translocation of a major alarmin, High Mobility Group Box 1 (HMGB1), a pro-inflammatory response in macrophages. Human blood monocytes were obtained from healthy donors, or from subjects with cystic fibrosis (CF) or chronic obstructive pulmonary disease (COPD). Monocytes were differentiated into blood monocyte derived macrophages (BMDM) in vitro. Human BMDM were exposed to NE or control vehicle and the abundance of HDACs and Sirtuins was determined by western blotting of total cell lysates or nuclear extracts, or determined by ELISA. HDAC, Sirtuin, and Histone acetyltransferase (HAT) activities were measured. NE degraded most HDACs and Sirtuin (Sirt)1, resulting in decreased HDAC and sirtuin activities, with minimal change in HAT activity. We then evaluated whether the NE-induced loss of Sirt activity or loss of HDAC activities would alter the cellular localization of HMGB1. NE-treatment or treatment with Trichostatin A (TSA), a global HDAC inhibitor, both increased HMGB1 translocation from the nucleus to the cytoplasm, consistent with HMGB1 activation. NE significantly degraded Class I and II HDAC family members and Sirt 1 which shifted BMDM to a pro-inflammatory phenotype.

DNA barcoding has emerged as a transformative tool in the realm of biodiversity assessment, facilitating rapid and precise species identification. This review article delves into the evolving landscape of DNA barcoding, with a particular focus on the emergence of mini-barcodes and alternative genes as innovative approaches. Traditional DNA barcoding, anchored in the COI gene, has significantly advanced our understanding of species diversity; however, inherent challenges persist, especially when dealing with degraded samples or taxonomic groups where COI falls short. The introduction of mini-barcodes, characterized by their reduced sequence length, has revolutionized DNA barcoding by expanding its applicability. We explore the utility of mini-barcodes in various scenarios, ranging from DNA extraction from ancient or fragmented specimens to in-field identification using portable sequencing technologies. Case studies and practical insights into their effectiveness are presented, emphasizing their role in overcoming traditional limitations. Alternative genes, a complementary facet of DNA barcoding, offer a novel avenue for enhancing taxonomic resolution and accuracy. This review showcases instances where researchers have harnessed alternative genes to overcome COI's constraints, particularly in diverse taxonomic groups, such as fungi, plants, and microorganisms. The selection of these genes is discussed, along with their potential to uncover hidden biodiversity and improve species delimitation. Examining the broader implications of mini-barcodes and alternative genes, we unveil their pivotal roles in advancing conservation efforts, forensic science, and citizen science initiatives. The adaptable nature of these approaches empowers a diverse range of stakeholders, from scientists conducting critical research to concerned citizens contributing to our collective understanding of the natural world. Looking ahead, we envision an exciting future for DNA barcoding, as these innovations continue to evolve. Integration with cutting-edge sequencing technologies, data analysis methods, and the harnessing of big data hold immense potential. Nonetheless, challenges related to standardization, scalability, and data sharing persist.

The exploration of three-dimensional (3D) DNA structures marks a pivotal shift in genomics, offering unprecedented insights into the intricacies of cellular regulation, disease genesis, and the potential for novel diagnostic and therapeutic strategies. This study delves into the dynamic nature of 3D genome organization, investigating how these structures influence cellular functions in response to environmental changes and over time. Through a combination of real-time imaging and advanced computational models, we aim to unravel the complex interplay between 3D DNA structures, non-coding RNAs, and chromatin organization, and their collective impact on gene expression and cellular differentiation. A significant focus is placed on understanding the role of 3D DNA structures in the development and progression of genetic disorders. By employing comprehensive genomic and epigenomic profiling, this research seeks to identify structural aberrations linked to diseases, paving the way for the development of targeted diagnostics and therapies. Additionally, the study explores the potential of genome editing technologies, such as CRISPR-Cas systems, in correcting these structural abnormalities, while also addressing the ethical, legal, and social implications (ELSI) of such interventions. Integrating data from various genomic analyses, we propose the development of advanced computational models to predict the effects of 3D DNA structures on gene expression and cellular function. This integrative approach not only promises to enhance our understanding of genomic regulation but also sets the stage for groundbreaking advances in genomics-based diagnostics and therapeutics. The findings of this study have the potential to revolutionize our approach to treating genetic disorders, offering a new frontier in personalized medicine.

Fetal growth restriction (FGR) is a major concern in perinatal care. Various medications have been proposed as potential treatments for this serious condition. Nonetheless, there is still no definitive treatment. We studied tadalafil, a phosphodiesterase-5 inhibitor, as a therapeutic agent for FGR in clinical studies and animal experiments. In this review, we summarize our preclinical and clinical data on the use of tadalafil for FGR. Our studies in mouse models indicated that tadalafil improved FGR and hypertensive disorders of pregnancy. In addition, tadalafil protected cerebral nerve development in FGR offspring. The clinical trials we have conducted to date, including a case–control study, a phase I trial, and a phase II trial, have indicated the efficacy of tadalafil in prolonging pregnancy, as well as a good safety profile for fetuses and neonates. The number of fetal, neonatal, and infant deaths was significantly lower in those receiving tadalafil treatment group than that in controls, and no severe adverse maternal events associated with tadalafil were observed. Although further studies are needed to establish the usefulness of tadalafil in FGR treatment, our research indicates that the use of tadalafil in FGR treatment may be a paradigm shift in perinatal care.

We bring a strength-based and socially-oriented lens to behaviors observed in profound autism. Social deficits are a defining characteristic of autism. Yet humans’ biological drive for social connection is sufficiently strong that is should be observable, in some form at least, in individuals with autism. We describe a case that validates this view. Mahad is a 20-year-old Pakistani-American male, with intellectual disability, and minimal verbal abilities. Mahad has an intense interest in food and the steps involved in food preparation. He employs and capitalizes on his family’s meal routines to ensure continual social attention from his mother. When not immersed in food, Mahad uses his limited capacities to pursue the additional biological needs of exploring his environment, seeking information, and developing his cognitive abilities.

This study analyzes the efficacy of trapezius muscle electromyography (EMG) in discerning mental states, namely stress and meditation. Fifteen healthy participants were monitored to assess their physiological responses to mental stressors and meditation. Sensors were affixed to both the right and left trapezius muscles to capture EMG signals, while simultaneous electroencephalography (EEG) was conducted to validate cognitive states. Our analysis of various EMG features, considering frequency ranges and sensor positioning, revealed significant changes in trapezius muscle activity during stress and meditation. Notably, low-frequency EMG features facilitated enhanced stress detection. For accurate stress identification, sensor configurations can be limited to the right trapezius muscle. Furthermore, the introduction of a novel method for determining asymmetry in EMG features suggests that applying sensors on bilateral trapezius muscles can improve the detection of mental states. This research presents a promising avenue for efficient cognitive state monitoring through compact and convenient sensing.

During the last decade, the demand for lithium has been growing exponentially with its widespread uses in manufacturing, especially with the worldwide deployment of electric vehicles. Thus, lithium is considered integral to the U.S. economy, technological advancement, and the pursuit of sustainable and clean energy solutions. The produced water is known to be rich in several minerals and valuable elements, such as potassium and magnesium, and a trace amount of precious elements including lithium. However, the existence of metals in the produced water is one of the challenges to extract lithium, especially magnesium which is located in diagonal positions within the periodic table that exhibit similarities. The produced water was first purified, resulting in the complete removal of magnesium, and then lithium was precipitated by phosphate. The effects of operating conditions on the Li₃PO₄ precipitation behaviors were evaluated. The effect of different precipitating reagents was evaluated on the percentage of lithium extracted, Na₃PO4 (TSP) was found to be a promising Li precipitating reagent. The highest percentage of lithium extracted was reached when the Li concentration of produced water was enriched and increased up to 350 mg/l, then Li removal was 53% at 7 grams of TSP and 200 rpm for 2 hours. The results indicated that temperature is a more important factor than stirring speed. The novelty of the current work is not only by the results obtained that may create additional financial benefits to oil-producing areas but on that the sustainable disposal of produced water may encourage the recycling and reuse practice, ultimately reducing the use of freshwater for hydraulic fracturing.

Our environment has been impacted by man-made pollutants mainly industries make substantial use of synthetic dyes which exhibit cytotoxicity and have significant environmental consequences. Effective photocatalyst-based approaches for degrading synthetic dyes into less toxic chemical are of great interest. Synthesizing NPs using biological approaches, particularly plant-based approaches offer advantages, decreasing the risk of NPs losing biocompatibility during synthesis, cost-effectiveness, and eco-friendliness. In this study, we employed a green synthesis method to produce manganese oxide nanoparticles (MnO NPs) utilizing leaf extract from the Lathyrus Aphaca plant. The synthesized MnOx NPs were characterized through various techniques; X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), Fourier-transform infrared spectroscopy (FTIR), and UV–visible spectroscopy. XRD analysis showed distinct peaks, indicated the presence crystallographic planes within the MnO₂ nanoparticles, thus confirming their crystalline structure. SEM study highlighted closely packed configurations with average size of approximately ≥ 50-70 nm, with well-defined boundaries. EDX analysis showed the presence of elemental manganese (Mn) in the samples, with peaks corresponding to Mn detected at lower energy levels, predominantly represented by MnO. FTIR, showed the presence of the O-O stretching mode at a frequency of 719 cm^-1, the presence of MnO₆ oxides of manganese, and peak at 548 cm^-1 corresponded to the Mn-O stretching mode. Furthermore, the green-synthesized manganese oxide nanoparticles exhibited promising photocatalytic and adsorption capabilities against Methylene Blue (MB) dye, leading to approximately 93.21% degradation of MB when treated with the green-synthesized MnO nanoparticles derived from plant extract. This highlights the efficacy and potential of these nanoparticles in environmental remediation applications, particularly in the degradation of methylene blue contaminants.

New biomedical technologies are examined in depth and the legal and ethical challenges they pose. Key issues such as gene editing, the application of artificial intelligence in the medical field, and the protection of biological information data are analyzed. At the same time, we also found that technological advances in the development of the enormous potential of biomedicine, but also raises a series of ethical and legal issues. To this end, the paper proposes a series of effective response strategies aimed at providing guidance to policy makers, researchers, and healthcare professionals to ensure the rational and safe application of new technologies. Solutions to these challenges are elaborated. When it comes to gene editing, the article stresses the responsibility of scientists not only to push the boundaries of technology, but also to ensure that edited genes are in the public interest and respect individual rights. To this end, strict regulatory mechanisms should be put in place to ensure that gene editing is carried out only in certain and ethical circumstances. Although AI technology has brought many conveniences to the medical field, it also involves data privacy protection, the transparency of the AI decision-making process, and the impact of AI on traditional medical models. Therefore, it is necessary to formulate corresponding regulations to regulate its application, ensure the fairness and transparency of AI decision-making, and promote its integration and development with traditional medicine. The importance of the protection of biometric data was also emphasized. In biomedical research, a large number of personal biological information data, such as genome and proteome, are often involved. This data should be effectively protected to prevent data leakage and misuse. To this end, it is necessary to strengthen data security measures and establish standards and norms for data sharing and utilization to ensure the rational use and protection of data.

This study investigates the pivotal areas where Artificial Intelligence (AI) integration in healthcare warrants further exploration, leveraging insights from Boston Specialists, a forefront healthcare provider in AI adoption. Employing a qualitative case study approach, enriched by in-depth interviews and comprehensive literature reviews, we identify three main domains for potential AI expansion: scheduling efficiency, clinical documentation, and AI-driven medical research. Our results underscore the substantial enhancements AI brings to operational workflows and patient care, notably through improved scheduling systems, accuracy in medical documentation, and the facilitation of data-driven research methodologies. These findings suggest a critical need for healthcare institutions to further invest in AI technologies, focusing on these key areas to harness AI's full potential in personalizing care, optimizing efficiency, and advancing medical knowledge. The study concludes with a call for continued investigation into AI's integration within healthcare settings, emphasizing the importance of a supportive organizational infrastructure, ethical considerations, and data security in realizing AI's transformative impact on healthcare delivery and patient outcomes.

Shape-shifting polymers usually require not only reversible stimuli-responsive ability, but also strong mechanical properties. A novel shape-shifting photochromic hydrogel system was designed and fabricated through embedding hydrophobic spiropyran (SP) into double polymeric network (DN) by micellar copolymerization. Here, sodium alginate (Alg) and poly acrylate-co-methyl acrylate-co-spiropyran (P(SA-co-MA-co-SPMA)) were employed as the first network and the second network respectively to realize high mechanical strength. After soaked in the CaCl2 solution, the carboxyl groups in the system undergo metal complexation with Ca2+ to enhance the hydrogel. Moreover, after the hydrogel is exposed to UV-light, the closed isomer of spiropyran in the hydrogel network can be converted into an open zwitterionic isomer MC, which is considered to interact with Ca2+ ions. Interestingly, Ca2+ and UV-light responsive programmable shape of the copolymer hydrogel can recover to its original form by immersing in pure water. Since its excellent metal ion and UV-light stimuli-responsive and mechanical properties, the hydrogel has potential applications in the field of soft actuators.

In the digital era, enhancing the heritage resources of a tourist route means describing and networking them to promote their visibility and attractiveness. Prior studies mainly assess mountainous region’s natural resources through multi-indicator descriptive evaluation. This study aims to develop a comprehensive measurement of indicator’s value while assessing the tourism development potential of mountainous rural area. It concerns the main tourist route of the UNESCO M'Goun Geopark, located in the central High Atlas of Morocco. It also involves analyzing the criteria for choosing this destination by segmenting tourists' consumption experiences. Statistical analysis of the collected data reveals five dimensions of destination choice and four visitor groups. This article proposes to discuss findings and their applicability in terms of tourism destination management and decision-making, which can help local governments to rationally allocate tourism resources and land use.

Due to the growth of tourism, mining and manufacturing, economy of the Hainan Island, southern China has swiftly expanded, but also poses a risk of soil pollution by mercury (Hg) due to the traffic and mineral processing. In order to investigate the characteristics of soil Hg pollution in the Hainan Island and assess the health risk, a total of 239 samples were gathered from five representative regions across the island. A vehicle-mounted potable mercury analyzer was used to measure the atmospheric Hg and soil Hg concentrations in the collected samples. The results indicate that the soil Hg concentration of the five sub-study areas exhibits notable fluctuations, which was found to be influenced by various factors, including wind direction, mining activities, and economic development conditions. The degree of Hg pollution was assessed using both the Single Pollution Index Method and the Geoaccumulation Index Method. The results showed that although nearly half of the sampling points were contaminated, the current soil Hg level does not pose a non-carcinogenic risk to human health.

Automation is the key aspect of science and technology field and refers to controlling the systems for efficient output requirements. The development of robotics and similar, technologies in 21st century is a vast topic of research and significant progress has been made on this field. This research study focuses on building a ribbon-cutting robot with a Bluetooth interface for event inaugurations. The entire system hinges on constructing a prototype that is mounted on a robotic car frame with four wheels and an Arduino controller. In this case, ribbons are cut using a nickel wire, and it may be paired with an Android device via Bluetooth or an application. The robot is one of the first steps toward the development of autonomous, cognitive robots and can be used in a variety of events. Efficient temperature monitoring is done with help of LM35 sensor and Bluetooth based communication in order to monitor the conditions and effectively control the actions for which robot is designed. The robot has significantly allowed authors for desired tests on ribbon cutting and final results obtained were very exciting for its desired application target. Ribbon-cutting robots find applications in various events, including inaugurations, exhibitions, and ceremonies. Their precision and novelty add value to such occasions.

Although charcoal production is a source of income, it is often associated with deforestation due to the felling of trees in rural areas. The study quantifies the yield of carbonization in the rural area of Lubumba-shi, DRC, and identifies its determinants. By analyzing 20 kilns from professional producers in different villages, the study reveals that these charcoal producers build large kilns, containing an average of 46.9±21.5 m3 of wood from 19 species of miombo trees. The average carbonization yield is 10.2%, varying from village to village due to parameters such as kiln size, quantity of wood used, kiln coverage time, wind exposure, substrate type and tree species. It was noted that the moisture content and size of the wood did not correlate significantly with the quantity of charcoal harvested per kiln. Yield improvement should therefore take these parameters into account to enable charcoal producers to increase their income while adopting sustainable production practices.

Despite advances in our understanding of molecular aspects of oncogenesis, cancer remains a leading cause of death. The malignant behavior of a cancer cell is driven by the inappropriate activation of transcription factors. In particular, signal transducers and activators of transcription (STATs), which regulate many critical cellular processes such as proliferation, apoptosis, and differentiation, are frequently activated inappropriately in a wide spectrum of human cancers. Multiple signaling pathways converge on the STATs, highlighting their importance in the development and progression of oncogenic diseases. STAT3 and STAT5 are two members of the STAT protein family that are the most frequently activated in cancers and can drive cancer pathogenesis directly. The development of inhibitors targeting STAT3 and STAT5 has been the subject of intense investigations in the last decade, although effective treatment options remain limited. In this review, we investigate the specific roles of STAT3 and STAT5 in normal physiology and cancer biology, discuss the opportunities and challenges in pharmacologically targeting STAT proteins and their upstream activators, and offer insights into novel therapeutic strategies to identify STAT inhibitors as cancer therapeutics.

Hemodynamics is the eternal theme of the circulatory system. Abnormal hemodynamics and cardiac and pulmonary development intertwine to form the most important features of children with congenital heart diseases (CHDs), thus determining these children’s long-term quality of life. However, due to the lack of neonatal rodent models of CHDs, it is unclear how CHD-associated hemodynamics shape postnatal cardiac and pulmonary development. Here, we review the varieties of hemodynamic abnormalities that exist in children with CHDs, the recently developed neonatal rodent models of CHDs, and the inspirations these models have brought us in the areas of cardiomyocyte proliferation and maturation, and in alveolar development. Furthermore, current limitations, future directions, and clinical decision-making based on these inspirations are highlighted. Understanding how CHD-associated hemodynamic scenarios shape postnatal heart and lung development may provide a novel path to improving the long-term quality of life of children with CHDs, transplantation of stem cell–derived cardiomyocytes, and cardiac regeneration.

With the growing trend of urbanization and the growing number of people migrating to cities, the demand for the development and construction of new buildings as well as the infrastructure has risen, meaning that the construction industry must adapt to the trends. The growing demands with shorter deadlines for an industry already known for high costs and not delivering on time means that productivity must be increased without increasing the cost. The solution for this might lie in the application of the Lean philosophy to the construction industry. This paper analyses the application of the Lean philosophy in order to increase the productivity in the airport construction site. The paper highlights the potential for enhancing productivity in construction workplaces by concurrently fostering continuous improvement and sustainability through the implementation of the A3 methodology and Lean principles, resulting in waste reduction and increased value.

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.

In this study, the effect of NaOCl (10–200 ppm of Cl2) on the inactivation of human norovirus (HuNV) GII.4 and hepatitis A virus (HAV) in groundwater was investigated using PMA/RT­qPCR. Initially, 4.00 log copies/μL of HuNV GII.4 or 5.50 log copies/μL of HAV were artificially inoculated in ground water. The titers of HuNV GII.4 and HAV decreased significantly (p < 0.05) with increasing Cl2 concentrations. Ground water was treated with 10, 30, 50, 100, 150, and 200 ppm of Cl2, and the viable HuNV GII.4 was significantly (p < 0.05) reduced to 3.28 (0.21 log reduction), 3.18 (0.31 log reduction), 3.01 (0.48 log reduction), 2.75 (0.74 log reduction), 2.54 (0.95 log reduction), and 2.34 (1.15 log reduction) log copies/μL, respectively. The viable HAV was also significantly (p < 0.05) reduced to 4.99 (0.23 log reduction), 4.76 (0.46 log reduction), 4.55 (0.67 log reduction), 4.21 (1.01 log reduction), 3.89 (1.33 log reduction), and 3.64 (1.58 log reduction) log copies/μL, respectively. The decimal reduction time (D-value) (1-log reduction) of HuNV GII.4 and HAV infectivity in ground water was predicted as 116.7 and 98.9 ppm of Cl2, respectively using the first-order kinetics model (HuNV GII.4 ; y = - 0.0054x + 3.3585, R2= 0.97, HAV ; y = - 0.0091x + 5.0470, R2= 0.97). The result specifically suggests that 150–200 ppm Cl2 can potentially be used for the inactivation of > 1 log copies/μL HuNV GII.4 and HAV in ground water.

In a densely populated country like Bangladesh, universities grapple with the challenge of efficiently addressing myriad queries from a large student body, leading to a heightened workload for university stakeholders. To tackle these challenges, we introduce PixieGPT, a tailor-made Generative Pre-Trained Transformer for Bangladeshi universities. PixieGPT significantly mitigates workload by adeptly handling common university-related queries, thereby enhancing user experience. The hierarchical structure plays a crucial role in managing diverse queries from thousands of students about the university system. The solution introduces a modular hierarchical knowledge base (KB) with simpler complexities, addressing the intricacies of efficiently managing large volumes of queries. PixieGPT is designed in a modular way so that the solution is also adaptable for the implementation of other universities worldwide based on the requirements of a particular administrative system. The modular nature facilitates easy adaptation with minor changes based on specific university requirements, ensuring a seamless integration process. This paper delves into the intricacies of PixieGPT's design, emphasizing its pivotal role in mitigating workload challenges for university stakeholders in Bangladesh. The incorporation of BERT for Natural Language Understanding(NLU) and GPT models for Natural Language Generation(NLG) enhances PixieGPT's capabilities, contributing to the scalability and efficiency of the system. The presented use case underscores the practical benefits of PixieGPT, positioning it as a promising solution for universities globally with similar operational frameworks.

Entropy as a mathematical concept is the first of its own kind, and second to none. Barely one or two papers in literature have investigated fractal dimensions of very basic entropies, such as Shannon, Tsallis, and Rényi entropic expressions. This was a thoughtful inspiration to delve into a step forward towards a unified information- theoretic fractal theory. The storytelling of this current paper starts by introducing my third entropy formula, namely Ismail’s entropy, , as a novel generalization to Shannonian entropy with a visionary link to both long- and short-range interactions, (LRIs), (SRIs) respectively. Clearly, this would generate a fourfold unification with statistical mechanics as well as contemporary physics. Hence, this adds more credibility and weight for this study. The fractal dimension of , is identified in this paper. As an essential part of this work, it was influential to spotlight the importance of fractal geometry to space industry as well as education, which is crucial to develop our societies. Thus, some potential fractal applications to CubeSat Technologies and Education are highlighted. So, will the deep search for more ground-breaking research has come to an end. Certainly, not. This was another inspiration to propose new open problems to widen research gates to the scientific community for more research pathways. Consequently, the paper ends with closing remarks combined with some challenging open problems and the next phase of research.

The production of high-quality castings without foundry defects at minimal production costs is a constant priority for foundries. Innovation and optimization of production processes are key to achieving this goal. Computer simulation of foundry processes offers a modern alternative to expensive and time-consuming experiments in real foundries and provides a reliable representation and analysis of casting and solidification processes. A detailed analysis of the casting and solidification simulation results allows the prediction of various risks that can cause defects in cast castings, thereby reducing their quality and, last but not least, the cost of their production. The paper deals with the analysis of a computer simulation of the casting of a brake disc in the Slovak foundry. This brake disc has had shrinkages and micro shrinkages that reduce the internal quality of the casting. These defects occurred in the ribs in the upper part of the casting under the feeders. A computer simulation of the casting and solidification of this casting was made according to real conditions. It turned out that the designed ingate system with a system of feeders was not sufficient to eliminate emerging defects. A new layout of the feeders was proposed, which ultimately eliminated the occurrence of defects based on the results of computer simulation. The input parameters were set to be as close as possible to the actual needs of the foundry. 3D models of the assemblies were designed in SolidWorks CAD software, and filling and solidification simulations were performed using the NovaFlow &amp; Solid CV 4.6r42 simulation program.

The cassava whitefly, Bemisia tabaci, causes direct damage to cassava in the tropics by feeding on the phloem of leaves, inducing leaf chlorosis and abscission which can result in considerable yield loss of up to about 50% on susceptible varieties. The pest is also known to impart its indirect damage through sooty mold formation. Most of the improved cassava varieties in Uganda were developed for CMD resistance and CBSD tolerance and little is known about their reaction to whitefly infestation. A study was conducted to evaluate the reaction of 24 improved cassava varieties which were sourced from 5 different countries in the region (Uganda, Kenya, Tanzania, Malawi, and Mozambique) to whitefly infestation. These varieties were evaluated in three agro-ecological zones of Uganda, namely; North-Western Savannah Grassland, Lake Victoria Crescent and the Kyoga Plains in the second rains of 2016. Monthly data were taken on adult and nymph counts, whitefly and sooty mold damage, CMD and CBSD severities from 2 up-to 9 Months after planting (MAP). Results show that the whitefly population was highly significantly (P

The flywheel is a widespread mechanical component used for the storage of kinetic energy and angular momentum. It typically consists of a cylindrical inertia rotating about its axis on rolling bearings, which involves undesired friction, lubrication, and wear. This paper presents an alternative mechanism that is functionally equivalent to a classical flywheel while relying exclusively on limited-stroke flexure-joints. This novel 1-degrees-of-freedom zero-stiffness mechanism has no wear and requires no lubrication: it is thus compatible with extreme environments, such as vacuum, cryogenics, or ionizing radiation. The mechanism is composed of two coupled pivoting rigid bodies whose individual angular momenta vary during motion but whose sum is constant at all times when the pivoting rate is constant. The quantitative comparison of the flexure-based flywheel to classical ones based on a hollow cylinder as inertia shows that the former stores typically 6 times less angular momentum and kinetic energy for the same mass while occupying typically 10 times more volume. The freedom of design of the shape of the rigid bodies offers the possibility of modifying the ratio of the kinetic energy stored versus angular momentum, which is not possible with classical flywheels. For example, a flexure-based flywheel with rigid pivoting bodies in the shape of thin discs stores 100 times more kinetic energy than a classical flywheel with the same angular momentum. A proof-of-concept prototype was successfully built and characterized in terms of reaction moment generation, which validates the presented analytical model.

Prokaryotic genomes are dynamic tapestries that are strongly influenced by mobile genetic elements (MGEs), including transposons (Tn’s), plasmids, and bacteriophages. Of these, miniature inverted-repeat transposable elements (MITEs) are undoubtedly the least studied MGEs in bacteria and archaea. This review explores the diversity and distribution of MITEs in prokaryotes and describes what is known about their functional roles in the host and involvement in genomic plasticity and evolution.

Online teaching is considered an important approach for achieving sustainable learning and education, and college teachers’ attitude and behavioral intention are essential for the sustainable adoption of online teaching practice in higher education institutions. To examine the influencing factors that sustain teachers’ attitude toward online teaching and behavioral intention, we conducted a cross-sectional study based on a sample of 1,102 college teachers in central China, using hierarchical linear regression analysis to explore possible influencing factors in four levels: individual experience, environmental support, self-perception, and technology acceptance. The study results show that the subjective norms, readiness, beliefs, and perceived usefulness of online teaching had a significant impact on teachers’ attitude toward online teaching and behavioral intention. Nevertheless, the effect varied with factors like online-teaching load and teachers’ technology self-efficacy, as their influence seemed to be singular, affecting the teachers’ attitude toward online teaching or behavioral intention exclusively. In contrast, previous online-teaching experience did not notably affect either. The findings of this study reveal the complex interactions of factors that influence college teachers’ disposition toward and decisions about online-teaching practices and emphasize the need for targeted strategies to maintain and enhance online education in the post-pandemic era.

A persistent idea in cosmology is that the universe originated and then continued to evolve as a black hole. While the notion of a black hole universe has generally been framed within the standard cosmological model, the latter has had numerous problems related to dark matter, dark energy and other issues. To avoid such problems an alternative is proposed which omits cosmic expansion, dark matter and dark energy. The observable universe is cast instead as primarily a thin spherical shell of cold (~29 K) baryonic matter situated near the Hubble radius. This shell of plasma holds 95% of the observable universe’s mass, the remaining 5% existing in the interior galaxies and gas clouds. A key premise of the model is that spacetime is fundamentally photonic in nature. This allows photon energy to be transferred to spacetime in the Hubble redshift and to be transferred back to photons in a novel blueshift. These exchanges together drive a cosmic energy cycle for gravity and the cosmological constant, Λ. Photons of the cosmic microwave background originating in the plasma shell lose energy to ‘cooler’ regions of spacetime in interior zones via the Hubble redshift. This gives rise to gravity through the optical gravity approach. The depleted photons moving back towards the shell are then reenergized in ‘hotter’ spacetime regions via the Hubble blueshift. These photons eventually exert outward pressures on the shell which perfectly balance the inward forces of gravity, in this manner functioning as Einstein’s cosmological constant. The observable universe behaves as a closed system in thermodynamic equilibrium with constant energy and entropy and indeterminate age. Black holes are suggested to have analogous plasma shell structures and gravity/Λ cycles.

Gas leakage can occur for various reasons, including a gas leak in the distribution line, damaged regulators, service connection failures, fluctuations in inlet gas pressure, and other factors leading to millions in losses to the state. The objective is to develop a general and intelligent model for tracking and monitoring LPG distribution based on the Internet of Things and Business Intelligence technology. Devices such as sensors and actuators reduce risks and prevent accidents. IoT can also access automatic control of machines and infrastructure, and sensors’ data helps make intelligent decisions. The quantitative approach is used in the systematic review methodology based on the PRISMA statement; the architecture design is based on analytical research that studies the feasibility of a measure through empirical evidence; and the architecture description uses a qualitative approach. The Y.4908 Standard evaluates an IoT network’s interoperability, usability, and security. A targeted group of thirty IT professionals was surveyed to assess the Business Intelligence model. Forty scientific papers were selected for analysis. A model with IoT components and a four-level business intelligence system was found. At the overall average level, 49% strongly agree, 38% agree, 12% neither agree nor disagree, and 1% disagree. In other words, the model has an overall average approval rating of 87%.

Cadmium (Cd) is a metal with no nutritional or physiological value, but is found in most people because it is a contaminant in nearly all food types. The intestinal absorption rate determines the body burden of Cd because humans lack a physiologic mechanism for excretion of the metal. Most acquired Cd accumulates in the kidneys, in which the Cd content increases through age 50 but falls thereafter. The decline from maximal kidney content is probably due to release of Cd from injured tubular cells into urine and replacement of destroyed nephrons by scar tissue. Chronic kidney disease is diagnosed when the estimated glomerular filtration rate (eGFR) falls below 60 mL/min/1.73 m2, or when albuminuria is present. Albuminuria is defined as an albumin-to-creatinine ratio ≥ 30 mg/g creatinine in women or ≥ 20 mg/g creatinine in men that persists for at least 3 months. Generally, Cd-induced reductions in eGFR are not reversible, and Cd nephropathy may progress to end-stage kidney disease. There is no evidence that elimination of current environmental exposure can reverse Cd nephropathy, and no theoretical reason to believe that such a reversal is possible. This review provides an update of knowledge concerning CKD in population environmentally exposed to Cd. Special attention is devoted to mechanisms of Cd-induced albuminuria concurrently with eGFR reductions, and the difficult challenge of exposure guidelines sufficient to eliminate the risk of Cd-induced CKD is addressed.

Owing to the rising demand for vegetable soybean products, there is an increasing need for high-yield soybean varieties to raise the output. However, complex correlation patterns among quantitative traits with genetic interactions bring a challenge for vegetable soybean breeding. Here, a genome-wide association study (GWAS) was applied for six yield-related traits with 188 vegetable soybean accessions. A total of 81 SNPs were identified for pod length, plant height, pods number, pod thickness, pod width, and seed weight per plant by Blink model. Among these significant SNPs, 79 were novel SNPs, while 2 overlapped with previously reported SNPs. A total of 220 genes were found in 100 kb upstream and downstream regions of significant SNPs, of which 17 genes were functional proteins. Among these function proteins, four candidate genes, Glyma.13G109100, Glyma.03G183200, Glyma.09G102200, and Glyma.09G102300 were analyzed as significant haplotype variations, which encode MYB-related transcription factor, auxin-responsive family protein, F-box protein and CYP450, respectively. In addition, the relative expression with four candidate genes in the V030 and V071 (Among them, the plant height, pod number and fresh pod weight of V030 were lower than V071 strains) vegetable soybean were significantly different and these genes could be involved in plant growth and development via various pathways. Therefore, we proposed four genes from vegetable soybean germplasm that could be the key candidate genes for pod yield and plant height and these studies will accelerate the process of high-yield vegetable soybean breeding.

In recent years, growing attention has been directed towards the potential of plant extracts as great therapeutic agents in controlling oxidative stress and inflammation. Gymnema inodorum (Lour.) Decne, an indigenous plant locally grown in Northern Thailand, is known for its anti-diabetic activity. This study aims to explore the antioxidant properties and phenolic profile of column chromatographic fractionated G. inodorum leaf extract. The ethanolic-reflux extracts of G. inodorum leaves were subjected to column chromatography for the isolation of bioactive molecules. Total phenolic and flavonoid content were assessed using Folin–Ciocalteu and aluminium chloride colorimetric methods, respectively. Total antioxidant activity was evaluated by employing different antioxidant assays, including 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic)acid (ABTS) scavenging assay and ferric reducing antioxidant power (FRAP) assay. High-Performance Liquid Chromatography (HPLC) with a C18 column was employed to determine the level of gymnemic acid, while Liquid Chromatography Quadrupole Time-of-Flight/Mass Spectrometry (LC-QTOF/MS) was used to identify potential phenolic compounds. The three separated fractions indicating A, B, and C, exhibited remarkable antioxidant activity, with total phenolic content of 0.294 ± 0.056, 0.085 ± 0.039, and 0.227 ± 0.041 mg QE/mL, and total flavonoid content of 0.274 ± 0.050, 0.309 ± 0.110, and 0.384 ± 0.007 mg QE/mL, respectively. Fraction A exhibited the highest DPPH and ABTS scavenging activity, while fraction C demonstrated significantly higher ferric-reducing power. HPLC analysis revealed a highest concentration of gymnemic acid in fraction C (0.393 ± 0.003 mg/g) compared to fraction A (0.159 ± 0.003 mg/g) and fraction B (0.142 ± 0.000 mg/g). The LC-QTOF/MS phenolic screening showed seven potential phenolic compounds in fraction A, seven compounds in fraction B, and four compounds in Fraction C. A significant relationship is found between antioxidant potential and total phenolic content, suggesting that phenolic compounds are the major contributors to the antioxidant activity of G. inodorum.

Applying the iterative methodology for dimensionality reduction/feature selection using categorical gradient boosted trees, as it has been defined in and has been successfully applied on similar datasets in and , on a dataset consisted of 12708 gene expressions coming from 5052 individuals from 105 studies, we classify whether a person has acute myeloid leukaemia (AML) or is healthy. A CatBoost model on a dataset with reduced dimensions of 72 genes reached a ROC-AUC score of 0.9973 using ten fold cross validation (10CV) and ROC-AUC: 0.9988 on an inference dataset. We further investigate the options of using less genes that potentially could be used in clinical practise and genes than have not been associated to AML yet, or to blood cancer in general. On the same folds of the 10CV and on the same inference dataset the performance of the tuned CatBoost models show that it could be the case that not all genes with an association to AML have been found yet and 19 genes could be enough to predict AML: CatBoost63 (ROC-AUC: 0.9941, Test: 0.9942), CatBoost19: (ROC-AUC: 0.9946, Test: 0.9941) and CatBoost15: (ROC-AUC: 0.9922, Test: 0.9900). In addition, our results verify that a gene diagnostic test for AML could be possible in the future as well as further research is needed on these 15 genes that it could lead to new and better drugs.

Population growth, climate change, changes to land use, and the advent of emerging infectious disease agents has put our abilities to feed the growing global population at risk, which is of particular concern in low- or middle-income countries. Research to improve the profitability and sustainability of common livestock production systems is key to tackling this issue. However, despite considerable research investment to address this concern, there has been no attention to development of robust methodologies for the synthesis of existing research evidence and its re-use. Syntheses of evidence are critical for fostering best practices, minimising wastage of valuable research resources, and enabling informed decision and policy making. Whilst the use of evidence syntheses is well entrenched in human healthcare, their use within animal sciences is limited and specific methodologies for performing them are underdeveloped. In this call to action, we propose some methodological development activities that should be undertaken within this field of research to increase the potential of evidence syntheses to contribute to tackling pressing societal issues relating to livestock agriculture.

Ovariectomy appears to be the best method to control the density of wild ungulate populations. The aim of the present study was to compare two surgical approaches, via the flank and midline, in mouflon’s ovariectomy in field conditions. Twenty female mouflons were enrolled in the study. The animals were divided randomly in two groups, Group F animals were gonadectomized via flank approach, while Group A animals were sterilized via linea alba access. The parameters evaluated were duration of surgery, duration of anaesthesia, recovery time, intra- and post-operative complications, intra-operative nociception and pain in the post-operative period. There were no intra- and post-operative complications. The evaluated parameters showed a very similar trend in both groups. Both techniques are found to be effective and safe in execution.

Composites, and especially carbon fiber reinforced plastics (CFRPs), are increasingly used in the automotive, aerospace, and aviation industries, and as a result, CFRP production has increased dramatically, leading to a corresponding increase of waste. Landfill and incineration of waste are likely to be restricted as a result of the legislation, thus highlighting the need for efficient recycling methods for CFRPs. However, the recycling of CFRP is very challenging, mainly due to the difficulty of removing the thermosetting matrix. This study reports a pre-screening of the solvolysis recycling process for CFRPs based on the mechanical properties of the recovered fibers. To this end, solvolysis tests were conducted on unidirectional CFRP samples under supercritical and subcritical conditions using acetone and water. The solvolysis tests were conducted for various conditions of temperature, pressure, and reaction time. The efficiency of the recycling processes has been evaluated through a morphological and a mechanical characterization of the recovered fibers. In most cases, the decomposition efficiency of the epoxy resin, measured in terms of mass, ranged between 90 and 100%. Moreover, the scanning electron microscopy images of the recovered fibers showed negligible traces of resin residues and no detectable signs of physical damage or any changes in morphology with regard to diameter. Finally, the single-fiber tension tests revealed that that the recovered fibers retained more than 61% of their initial Young's modulus and 70% of their tensile strength.

Extreme-mass-ratio inspirals (EMRIs) are significant observational targets for spaceborne gravitational wave detectors, namely, LISA, Taiji, and Tianqin, which involve the inspiral of stellar-mass compact objects into massive black holes with a mass range of approximately 104∼107M⊙. EMRIs are estimated to produce long lived gravitational wave signals with more than 105 cycles before plunge, making them an ideal laboratory for exploring the strong-gravity properties of the spacetimes around the MBHs, stellar dynamics in galactic nuclei, and properties of the MBHs itself. However, the complexity of the waveform model, which involves the superposition of multiple harmonics, as well as the high-dimensional and large-volume parameter space, make the fully coherent search challenging. In our previous work, we proposed a 10-dimensional search using Particle Swarm Optimization (PSO) with local maximization over the three initial angles. In this study, we extend the search to an 8-dimensional PSO with local maximization over both the three initial angles and the angles of spin direction of the MBH where the latter contribute a time independent amplitude to the waveforms. Additionally we propose a 7-dimensional PSO search by using a fiducial value for the initial orbital frequency and shifting the corresponding 8-dimensional Time Delay Interferometry responses until a certain lag returns the corresponding 8-dimensional log-likelihood ratio maximum. The reduced dimensionality likelihoods enable us to successfully search for EMRI signals with duration of 0.5 years and signal-to-noise ratio of 50 within a wider search range than our previous study. We discuss further developments, such as using a hierarchical search to narrow down the search ranges of certain parameters, and applying Graphics Processing Units to speed up the code. These advances aim to improve the efficiency and accuracy of the EMRI search algorithm.

The increased cultivation of high THC-containing Cannabis sativa L. (cannabis), particularly in greenhouses, has resulted in a greater incidence of diseases and molds that can negatively affect the growth and quality of the crop. Among them, the most important diseases are root rots (Fusarium and Pythium spp.), Botrytis bud rot (Botrytis cinerea), powdery mildew (Golovinomyces ambrosiae), cannabis stunt disease (caused by Hop latent viroid), and a range of microbes that reduce post-harvest quality. An integrated management approach to reduce the impact of these diseases/microbes requires combining different approaches that target the reproduction, spread and survival of the associated pathogens, many of which can occur on the same plant simultaneously. These approaches will be discussed in the context of developing an integrated plan to manage the important pathogens of greenhouse-grown cannabis at different stages of plant development. These stages include maintenance of stock plants, propagation through cuttings, vegetative growth of plants, and flowering. The cultivation of cannabis genotypes with tolerance or resistance to various pathogens is a very important approach, followed by the maintenance of pathogen-free stock plants. When combined with cultural approaches (sanitation, management of irrigation, and monitoring for diseases) and environmental approaches (greenhouse climate modification), a significant reduction in pathogen development and spread can be achieved. The use of preventive applications of microbial biological control agents and reduced risk biorational products can also reduce disease development at all stages of production in jurisdictions where they are registered for use. The combined use of promising strategies for integrated disease management on cannabis plants during greenhouse production will be reviewed. Future areas for research are identified.

Detecting gear rim fatigue cracks using vibration signal analysis is often a challenging task, which typically requires a series of signal processing steps to detect and enhance fault features. This task becomes even harder in helicopter planetary gearboxes due to the complex interactions between different gear sets, and the presence of vibration from sources other than the planetary gear set. In this paper, we propose an effectual processing algorithm to isolate and enhance rim crack features and to trend crack growth in planet gears. The algorithm is based on using cepstrum editing (or liftering) of the hunting tooth synchronous averaged signals (angular domain) to extract harmonics and sidebands of the planet gears, and low-pass filtering and minimum entropy deconvolution (MED) to enhance extracted fault features. The algorithm has been successfully applied to a vibration dataset collected from a planet gear rim crack propagation test undertaken in the Helicopter Transmission Test Facility (HTTF) at DSTG Melbourne. In this test, a seeded notch generated by an electric discharge machine (EDM) was used to initiate a fatigue crack that propagated through the gear rim body over 94 load cycles. The proposed algorithm demonstrated a successful isolation of incipient fault features and provided a reliable trending capability to monitor crack progression. Results of a comparative analysis showed that the proposed algorithm outperformed the traditional signal processing approach.

This is a SARS-CoV-2 seroepidemiological study in pediatric population(0-16 years) during BA.5 Omicron predominance period in Athens metropolitan area. Serum samples were tested for SARS-CoV-2 nucleocapsid antibodies(Abs-N), representing natural infection during three sub-periods of BA.5 predominance: 01/05/2022-31/08/2022(period A), 01/09/2022-31/12/2022(period B) and July 2023(period C) and epidemiological data were collected. Additionally in period C Abs-N seronegative samples were tested for SARS-CoV-2 spike antibodies(Abs-S). A total of 878 children were tested (males:51.3%) with median age(IQR): 108(36-156) months and seropositivity during the 3 subperiods was: A:292/417(70%), B:288/356(80.9%), C:89/105(84.8%), P-value<0.001. SARS-CoV-2 seropositivity increased for from period A to C for 0-1-year (P-value: 0.044), 1-4 years (P-value: 0.028) and 6-12 years children (P-value: 0.003). Children 6-12y had the highest seroposi-tivity rates in all subperiods (A: 77.3%, B: 91.4% and C: 95.8%). A significant correlation of monthly SARS-CoV-2 median antibody titers with monthly seropositivity rates was detected (rs:0.812, P-value:0.008). During period C, an additional 12/105 (11.4%) Abs-S seropositive and Abs-N ser-onegative samples were detected and total seropositivity was estimated at 96.2% (101/105). The increased SARS-CoV-2 seropositivity detected in current seroepidemiology study illustrates a high exposure rate during BA.5 predominance period. These data could guide public health decisions regarding immunization strategies and protection measures.

Porcine sapovirus (PoSaV) is a significant pathogen causing diarrhea with high morbidity and mortality rates. Given its zoonotic characteristics, this study conducts a comprehensive genetic evolutionary analysis of PoSaV. Results confirmed PoSaV as the primary RNA virus in piglet feces (27.54%). Phylogenetic analysis identifies the prevalent PoSaV strain SHCM/Mega2023 in the GIII genogroup, involving a recombinant event with MK962338 and KT922089. The time tree revealed that the GIII genogroup exhibits the widest divergence time span, indicating a high likelihood of viral recombination. Further selective pressure calculations demonstrate that PoSaV was under purifying selection (dN/dS &lt; 1), with seven positively selected sites in VP1 protein which might be related to the antigencity. In conclusion, this study presents a novel genomic evolution of PoSaV, offering valuable insights into antigenicity and vaccine research.

The main aims of this study were (1) to identify and compare the major biologically active compounds in the metabolome of ligulate and tubular flowers of two C. officinalis cultivars, ‘Golden Sea’ (GS) and ‘Paradise Garden’ (PG), and (2) to investigate the effect of different proportions of ligulate and tubular flowers in the inflorescences on their metabolome. Ultra-performance liquid chromatography with photodiode array detection and a Q Exactive Orbitrap high-resolution mass spectrometer were used to analyse the flower metabolome. Analysis of the metabolomics data revealed that polar lipids showed the most significant differences between flowers. Tubular flowers of PG and GS cultivars contained higher levels of 31 and 34 out of 36 lipids, respectively. Furthermore, tubular flowers of both cultivars contained significantly higher levels of phenolamides and caffeoylquinic acids, but lower levels of triterpenoids. To compare the metabolite content of the two C. officinalis cultivars, we analysed the data for their inflorescences. The study showed that GS inflorescences contained significantly higher levels of phenolic compounds and lipids than PG inflorescences. This GS advantage was due to two factors: firstly, the higher content of these metabolites in tubular flowers and, secondly, the higher proportion of tubular flowers in GS inflorescences.

Therapies targeting amyloid, such as monoclonal antibodies like Lecanemab, Aducanumab, and Donanemab, have garnered FDA approval but remain controversial due to limited clinical benefits and significant side effects against Alzheimer. The present theorical work utilized Virtual Screening and Docking techniques to explore potential small natural molecules' interactions with the KIBRA protein, a promising target for drug development. Kibra protein is considered a biomarker for synaptic dysfunction and cognitive decline. Employing Autodock Vina and Pyrx software, on several natural compounds and found Hypericin to exhibit the lowest binding energy of approximately -9 kcal/mol. Previous studies have highlighted Hypericin's strong affinity for Alzheimer's Disease-associated targets like ABAD and BACE1. These findings suggest Hypericin could be as a potential therapeutic agent for Alzheimer's Disease. Further research is warranted to validate its efficacy and safety for clinical use.

Contemporary cities are facing many challenges, from social and economic issues to the new risks related to the impacts of climate change. Focusing on energy consumptions, and the related GHG emissions, cities are considered not only the main global contributors but also the areas most exposed to risks, because of their density of population and economic activities. Implementing urban planning strategies with the purpose of increasing energy efficiency and resilience overall are, for all these reasons, considered a top priority. This paper investigates the innovative contents about energy-efficient and energy-resilient urban planning solutions that have started to be implemented in the cities of the Emilia-Romagna region. Two kinds of planning instruments are therefore analyzed: the voluntary Sustainable Energy and Climate Action Plans (SECAPs) and the mandatory General Urban Plans (GUPs), recently approved in several cities of Emilia-Romagna. A comparative analysis of three cities in the Emilia-Romagna region, Bologna, Modena and Ravenna, is proposed on the strategies of their newly local city plans and SECAPs with focus on energy management and planning. The aim is to assess whether the new structure of local city plans and the influence of SECAPs could be useful in implementing such urban energy resiliency solutions.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Background: The incidence of spinal metastatic disease has risen with improved cancer survivorship. Separation surgery, the current standard surgical treatment, does not fully address spinal deformity. Advances in operative management warrant reevaluating maximal tumor resection and anterior column reconstruction with corpectomy. Methods: An IRB-approved retrospective single-center review of 63 patients was performed. Demographics, tumor characteristics, clinical and radiographic data, treatments, and neurological and survival outcomes were analyzed. Results: The mean age at presentation was 63.5 ± 9.6 years (range, 37-84 years) and 28 patients (44.4%) were female. Functional outcomes, measured by KPS, RAND-36 survey scores and Oswestry Disability Index all improved postoperatively (pre- vs postop: 70 to 80 (p=0.0056), 26.5 to 46.4 (p=0.0081), and 28.9 to 16.9 (p=0.0613), respectively). Spinal alignment also improved, with Cobb angle measurements showing a reduction in spinal kyphosis from -5 to 0 (p=0.021). Nine patients (14.5%) had non-fatal postoperative complications. The median OS for this cohort was 14.4 months (range, 0.6-145.0 months) with median follow-up time of 15.5 months. Conclusion: In oligometastatic spinal disease patients with good functional status, corpectomy for decompression of neural elements, deformity correction, and spinal stabilization is associated with improvements in pain and functional outcomes without overwhelming morbidity.

This study aimed to develop a high-quality dry emulsion incorporating omega-3, 6, and 9 fatty acid-rich ostrich oil for use as a dietary supplement. Extracted from abdominal adipose tissues using a low-temperature wet rendering method, the ostrich oil exhibited antioxidant properties, favorable physicochemical properties, microbial counts, heavy metal levels, and fatty acid compositions, positioning it as a suitable candidate for an oil-in-water emulsion and subsequent formulation as a dry emulsion. Lecithin was employed as the emulsifier due to its safety and health benefits. The resulting emulsion, comprising 10% w/w lecithin and 10% w/w ostrich oil, was stable, with a droplet size of 3.93 ± 0.11 μm. This liquid emulsion underwent transformation into a dry emulsion to preserve the physicochemical stability of ostrich oil, utilizing Avicel® PH-101 or Aerosil® 200 through a granulation process. Although Aerosil® 200 exhibited superior adsorption, Avicel® PH-101 granules surpassed it in releasing the ostrich oil emulsion. Consequently, Avicel® PH-101 was selected as the preferred adsorbent for formulating the ostrich oil dry emulsion. The dry emulsion, encapsulated with a disintegration time of 3.11 ± 0.14 min for ease of swallowing, maintained microbial loads and heavy metal contents within acceptable limits. Presented as granules containing butylated hydroxytoluene, the dry emulsion showcased robust temperature stability, suggesting the potential incorporation of animal fat into dry emulsions as a promising dietary supplement.

Caused by pathogenic microorganisms, such as bacteria, parasites, fungi, among others, infectious diseases can spread directly or from one individual to another. According to the World Health Organization, these diseases are known to cause high mortality rates, severe burdens of disability and serious worldwide aftermaths. The inappropriate use of antibiotics in humans are the main origins of the development of drug-resistant pathogens, which reduce the efficacy of these therapies, thus accentuating the need to search for effective antimicrobials. Medicinal plants have served as starting material for the preparation of a number of antimicrobial agents. To this end, the present study highlights the green synthesis of Cocos nucifera-based nanomaterials and evaluation of the mechanistic basis of their antimicrobial action. Accordingly, Cocos nucifera extract was used to reduce different concentrations (5, 10 and 20 mM) of silver nitrate solution to afford silver nanoparticles (AgNPs). These entities were further incorporated onto activated carbons (obtained by chemical activation using sulphuric acid as activation agent) to generate the nanocomposites. The antimicrobial activity of the as-prepared nanomaterials was evaluated using the broth microdilution method, while, the antioxidant activity was assessed through standard methods, such as 2,2-diphenyl-1-picrylhydrazyl (DPPH), and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) assays. Cytotoxicity of potent nanomaterials was assessed on Vero cells by spectrophotometric method. As a result, nanoparticles were successfully synthesized as evidenced by the color change of the solution from transparent to dark brown. Further characterization was carried out by UV-visible spectroscopy that showed an intense absorption spectrum at 433 nm. Fourier Transform Infrared Spectroscopy (FTIR) revealed the functional group moieties involved as a capping and reducing agent in the synthesis of AgNPs. The incubation of nanomaterials with selected bacterial and fungal strains led to significant inhibitory effects of these pathogens with minimum inhibitory concentrations ranging from 7.813 to 250 μg/ml. In antioxidant assays, the nanocomposites presented scavenging activities comparable to that of ascorbic acid. Cytotoxicity experiment revealed no toxic effects on the human mammalian cells Vero (range of selectivity indices: from &gt;4 to &gt;128). These results provide evidence of the implication of Cocos nucifera-based nanomaterials in targeting bacterial or fungal systems that mediate free-radical damage or by inhibiting the oxidative damage caused by selected bacteria and fungi, the most susceptible being Escherichia coli and Candida albicans, respectively.

The present review compared the efficacy of soft tissue substitutes (STS) and autogenous free gingival graft (FGG) or connective tissue graft (CTG) in mucogingival procedures to increase keratinized tissue (KT) width around teeth and implants. Two independent examiners performed the electronic search on Medline and Cochrane Library based on the following PICO’s format: (P) adult patients; (I) soft tissue substitutes and FGG/CTG; (C) STS vs CTG; STS vs FGG; STS vs CTR; (O) KT width gain; (S) Systematic Reviews, Randomized Controlled Trials. Results showed that around teeth, all biomaterials showed superior performance compared to CAF alone for treating gingival recessions. However, when compared to CTG, ADM yields the most similar outcomes to the gold standard (CTG), even though in multiple recessions CTG still continue to be considered the most favorable approach. Use of STSs (acellular matrix or tissue engineered) in combination with an apically positioned flap resulted in a significantly less gain of KTW compared to what achieved with FGG and APF. Around dental implants, free gingival grafts were deemed more effective than soft tissue substitutes in enhancing keratinized mucosa width.

Grain legumes are fair sources of protein, amino acids and energy, and can be used as a replacement for soybean meal in poultry feed formulations as the soybean meal becomes short in supply and costly. However, a concern associated with the use of grain legumes in poultry feeding is the presence of antinutritional factors. Effective processing and utilisation of these grain legumes in poultry feeding are well documented. The current review focuses on four selected grain legumes (lupins [Lupinus albus and Lupinus angustifolius], field peas [Phaseolus vulgaris], faba beans [Vicia faba] and chickpeas [Cicer arietinum]) and their nutrient content, the presence of antinutritional factors, processing methods and feeding value, including updated data based on recent research findings.

Breast cancer is the most common cancer in women globally, often necessitating mastectomy and subsequent breast reconstruction. Silicone mammary implants (SMIs) play a pivotal role in breast reconstruction, yet their interaction with the host immune system and microbiome remains poorly understood. This study investigates the impact of SMI surface topography on host antimicrobial responses, wound proteome dynamics, and microbial colonization. Biological samples were col-lected from ten human patients undergoing breast reconstruction with SMIs. Mass spectrometry profiles were analyzed for acute and chronic wound proteomes, revealing a nuanced interplay between topography and antimicrobial respondseproteins. 16S rRNA sequencing assessed mi-crobiome dynamics, unveiling topography-specific variations in microbial composition. Surface topography alterations influenced wound proteome composition. Microbiome analysis revealed heightened diversity around rougher SMIs, emphasizing topography-dependent microbial inva-sion. In vitro experiments confirmed staphylococcal adhesion, growth, and biofilm formation on SMI surfaces, with increased texture correlating positively with bacterial colonization. This comprehensive investigation highlights the intricate interplay between SMI topography, wound proteome dynamics, and microbial transmission. The findings contribute to understanding host-microbe interactions on SMI surfaces, essential for optimizing clinical applications and minimizing complications in breast reconstruction.

Daptomycin is one of the last therapeutic resources for multidrug-resistant gram- positive bacteria. Despite its structural similarities with glycopeptides, its mechanisms of action and resistance are different, and in some respects are not completely understood. Mutations in several genes have been associated to daptomycin resistance, especially in mprF, walkR, rpoB and rpoC, but their role and importance remain to be elucidated. We have studied mutations in 11 genes, which have been previously associated to daptomycin non- susceptibility, in 9 daptomycin non-susceptible Staphylococcus aureus clinical isolates (daptomycin MIC: > 1mg/L). Susceptibility to daptomycin, vancomycin, linezolid, oxacillin, telavancin and dalbavancin were studied. walkR, agrA, cls1, cls2, fakA, pnpA, clpP, prs, rpoB, rpoC and mprF were amplified by PCR and sequenced. The sequences were compared with the S. aureus ATCC 25923 complete genome (GenBank gi: 685631213) by using BLAST® software. We did not find any changes in walkR, pnpA, prs and clpP. All isolates excepting isolate 5 showed a high number of significant mutations (between 13 and 25 amino acid changes) in mprF. Most isolates also showed mutations in rpo genes, cls genes and fakA. Daptomycin non-susceptibility in S. aureus clinical isolates seems to be reached through different mutations combinations when compared to S. aureus ATCC 25293. Especially mprF and cls1 showed a very high polymorphism in most isolates. Meanwhile, one isolate, St5, showed only single mutation in mprF (P314T).

The aim of this study was to describe the trend of traffic accident mortality and social inequalities in Ecuador for the period 2011-2020, distributed by year, gender, age group, geographic location, and type of accident, alongside social disparities. An ecological approach was used to evaluate traffic accident mortality data. The average traffic accident mortality rate in the country during this period was 19.1 per 100,000 inhabitants, with rates being significantly higher in males (31.3) than in females (7.2). The highest mortality rate was recorded in 2011, predominantly impacting the 60 and older age group, the Santo Domingo de los Tsáchilas province, and the Amazon region. The study also noted a declining trend in these rates over the years, with an Annual Percentage Variation of -1.2%. A notable finding was the decrease in traffic accident mortality inequality based on per capita income in 2019, compared to 2011, which rose by 247.7%, whereas the inequality based on illiteracy rates decreased by 18.9% from 2014 to 2019. These findings highlight the significant decrease in traffic accident mortality rates across Ecuador, though marked disparities remain evident across different genders, age groups, and provinces.

The modifications in planting structure and continuous land use adjustments have significant implications for the structure, diversity, and functioning of arthropod communities in farmland landscapes, particularly regarding the biological control of pest insects by natural enemy species. Therefore, there is an urgent need to comprehensively and accurately assess insect community diversity in croplands. In this study conducted between 2022-2023, we utilized Malaise traps and sweep netting to collect insects from three different double-cropping paddy fields. We extracted DNA from preservative ethanol of Malaise traps and tissue samples of selected parasitoid wasps, followed by amplification using DNA barcoding primers to prepare high-throughput sequencing libraries. As a result, we annotated a total of 4956 operational taxonomic units (OTUs) belonging to 174 genera and 32 families of parasitoid wasps. Our findings demonstrate that the ethanol filter method efficiently captures a wide range of information diversity. However, it demonstrates a lower resolution and may result in a reduction of species abundance. Furthermore, we have identified additional insect species in the parasitoid samples. This demonstrates that high throughput sequencing from adult parasitoid wasps can effectively detect host specie, enabling a comprehensive understanding of host species and providing novel insights into food web construction.

In the era of large data, the cloud is increasingly used as a computing environment, necessitating the development of cloud-compatible pipelines that can provide uniform analysis across disparate biological datasets. The WDL Analysis Research Pipelines (WARP) repository is a GitHub repository of open-source, cloud-optimized WDL workflows for biological data processing that are semantically versioned, tested, and documented. A companion repository, WARP-Tools, hosts Docker containers and custom tools used in WARP workflows.

Software-defined networking (SDN) divides a traditional network into a programmable data plane and a centralized control plane. This technology is expected to transform traditional network companies that provide flexible and intelligent network operations. The core component utilized to oversee every data plane action is the controller in the control plane. In order to achieve optimal performances, the controller’s performance and capabilities are therefore crucial. There are lots of controller research available in existing literature. Nevertheless, no qualitative comparison study of OpenFlow-enabled distributed but logically centralized controllers exists for them. This article also includes a quantitative investigation of the performance of several distributed but logically centralized SDN controllers in custom network scenarios using Mininet, as well as a thorough qualitative comparison of them. More precisely, we give a qualitative evaluation of their attributes and classify and categorize 13 distributed but logically centralized SDN controllers according to their capabilities. Additionally, we offer a comprehensive SDN emulation tool called Mininet-based SDN controller performance assessment in this study. Using six performance metrics—bandwidth, round- trip time, delay, jitter, packet loss, and throughput—this work also assesses five distributed but logically centralized controllers against two custom network scenarios (uniform and non-uniform host distribution). Our investigation shows that the OpenDayLight controller performs the best across all performance criteria, with the exception of delay, packet loss and round trip time, where the Ryu controller excels. In the entire experiment, the HyperFlow and ONOS controller performs the worst in terms of all performance metrics. Finally, we discuss detailed research findings on the performance. These experimental results provide a decision-making guideline when selecting a controller.

Alzheimer's disease (AD) is the first cause of dementia worldwide and represents a public health challenge. Current diagnostic methods still rely on extended interviews and paper tests. We aim to create a novel, quick cognitive-screening tool on a numerical tablet. This program, built and edited with Unity®, runs on Android® for the Samsung Galaxy Tab S7 FE®. Composed of seven tasks inspired by the Mini-Mental Status Examination and the Montréal Cognitive Assessment, it browses several cognitive functions. The architectural design of this tablet application is distinguished by its multifaceted capabilities, encompassing not only seamless offline functionality but also a mechanism to ensure the singularity of data amalgamated from diverse sites. Additionally, a paramount emphasis is placed on safeguarding the confidentiality of patient information in the healthcare domain. Furthermore, the application empowers individual site managers by allowing them to access and peruse specific datasets, thereby enhancing their operational efficacy and decision-making processes. We performed a usability assessment among 24 healthy patients with a final F-SUS score of "excellent". Participants perceived the tool as simple to use and achieved the test in a mean time of 142 seconds, confirming that a short assessment on a numerical tablet is possible.

This research hypothesised that the use of Virtual Reality (VR) applications can be used to train people in the ability to acquire targets faster, with greater accuracy when using motion controllers than compared with a traditional pointing device (mouse) on a 2D display. User performance was defined and measured using Reaction Time and Accuracy. The research findings suggests that the use of motion controllers in VR improved Reaction Time but not Accuracy when compared against the traditional pointing device and 2D display. This suggests that VR can be used specifically in training scenarios where Reaction Times are more important than Accuracy. It is recommended that further research is conducted using a wider range of hardware and software configurations with a stratified sample that takes into account age and gender to expand the collective understanding of factors that impact on VR aiming and target acquisition in VR.

Analyzing horse behavior is crucial for assessing training quality, particularly in accurately identifying actions like standing, walking, and running. Research has been conducted both domestically and internationally in this regard; however, challenges persist, including reliance on single sensors, poor real-time performance, and low identification accuracy. In view of these challenges, this study investigated real-time identification of horse behavior based on wearable devices. The system, centered around a microcontroller and utilizing a 4G network as a carrier, employs multi-axis IMU sensors as input sources to perceive horse posture. The study proposed a behavior classification method based on analysis of acceleration thresholds. The method consists primarily of two sequential stages: first, the resultant acceleration interval counting method, which employs a nonlinear segmentation approach for initial behavior classification; and second, the statistical analysis of variance parameters between segments, which when coupled with multi-level threshold processing, achieves a refined classification. Experimental results indicated that the interval counting method alone achieved an accuracy of 87.55%, while for the variance analysis method alone the accuracy was 90.87%. The proposed method, comprising the two stages, reached a classification accuracy of 91.57%, underpinning its usefulness in supporting future equine research.

The work presented in this paper makes multiple scientific contributions related to the investigation of the global fear associated with COVID-19 by performing a comprehensive analysis of a dataset comprising survey responses of participants from 40 countries. First, the results of subjectivity analysis of responses where participants indicated their biggest concern related to COVID-19 showed that the average subjectivity in responses by the age group of 41-50 decreased from April 2020 to June 2020, the average subjectivity in responses by the age group of 71-80 drastically increased from May 2020, and the age group of 11-20 indicated the least level of subjectivity in their responses between June 2020 to August 2020. Second, subjectivity analysis also revealed the percentage of highly opinionated, neutral opinionated, and least opinionated responses per age-group where the analyzed age groups were 11-20, 21-30, 31-40, 41-50, 51-60, 61-70, 71-80, and 81-90. For instance, the percentage of highly opinionated, neutral opinionated, and least opinionated responses by the age group of 11-20 were 17.92%, 16.24%, and 65.84%, respectively. Third, data analysis of responses from different age groups showed that the highest percentage of responses indicating that they were very worried about COVID-19 came from individuals in the age group of 21-30. Fourth, data analysis of the survey responses also revealed that in the context of taking precautions to prevent contracting COVID-19, the percentage of individuals in the age group of 31-40 taking precautions was higher as compared to the percentages of individuals from the age groups of 41-50, 51-60, 61-70, 71-80, and 81-90. Finally, a deep learning model was developed to detect if the survey respondents were seeing or planning to see a psychologist or psychiatrist for any mental health issues related to COVID-19. The deep learning model used the responses to multiple questions in the context of fear, preparedness, and response related to COVID-19 from the dataset and achieved an overall performance accuracy of 91.62% after 500 epochs.

Red mud (RM), a bauxite residue, contains hazardous radioactive wastes and alkaline material and poses severe surface water and groundwater contamination risks, necessitating recycling. Pretreated RM can be used to make adsorbents for water treatment. However, its performance is affected by many factors, resulting in a nonlinear correlation and coupling relationship. This study aimed to identify the best formula for an RM adsorbent using a mathematical model that examines the relationship between 11 formulation types (e.g., pore-assisting agent, component modifier, and external binder) and nine properties (e.g., specific surface area, wetting angle, and Zeta potential, among others). This model was built using a back-propagation neural networks(BP) based on single-factor experimental data and orthogonal test data. The model trained and predicted the established network structure to obtain the optimal adsorbent formula. The RM particle adsorbents had a pH of 10.16, specific surface area(BET) of 48.92 m2·g−1, pore volume of 2.10 cm3·g−1, compressive strength(ST)) of 1.12 KPa, and 24-h immersion pulverization rate(η_m) of 3.72%. In the removal of total phosphorus in flotation tailings backwater, it exhibited a good adsorption capacity (Q)and total phosphorous removal rate(η) of 48.63 mg·g−1 and 95.13%, respectively.

This study comprehensively investigates Al2O3's mechanical properties, focusing on fracture toughness, surface energy, Young's modulus, and crack propagation. The density functional theory (DFT) is employed to model the vacancies in Al2O3, providing essential insights into this material’s structural stability and defect formation. The DFT simulations reveal a deep understanding of vacancy-related properties and their impact on mechanical behavior. In conjunction with molecular dynamics (MD) simulations, the fracture toughness and crack propagation in Al2O3 are explored, offering valuable information on material strength and durability. The surface energy of Al2O3 is also assessed using DFT, shedding light on its interactions with the surrounding environment. The combination of DFT and MD simulations provides a robust framework for a comprehensive understanding of Al2O3's mechanical properties, with implications for material science and engineering applications.

Estimating the infection risks in indoor environments comprises the assessment of the behavior of virus-laden aerosols, i.e. spreading, mixing, removal by air purifiers etc. A promising experimental approach is based on using non-hazardous surrogate aerosols of similar size, e.g. salt particles, to mimic the virus aerosol behavior. This manuscript addresses the issue how a successful transfer of such experiments can be accomplished. Corresponding experiments in two very different environments, a large community hall and a seminar room, with optional use of air purifiers in various constellations were conducted. While high particle concentrations are advantageous in terms of avoiding influence of background aerosol concentrations, it is shown that appropriate consideration of aggregation and settling are vital to theoretically describe the experimentally determined course of particle concentrations. A corresponding model equation for a well-mixed situation is derived and the required parameters are thoroughly determined in separate experiments independently. It is demonstrated that clean air delivery rates (CADR) of air purifiers determined with this approach may differ substantially from common approaches not explicitly taking into account aggregation.

The numerous biological activities of phenothiazine and sulphonamide derivatives, especially their antibacterial qualities, have attracted so much interest. In this study, the synthesis and characterization of phenothiazine-3-sulphonamide derivatives and evaluation their antimicrobial activity against the following pathogenic microorganisms is reported. Two gram-positive bacteria; (Staphylococcus aureus, and Streptococcus pyogenes), two gram-negative bacteria; (Escherichia coli, and Salmonella typhi) as well as one fungus (Aspergillus fumigatus) were used while ciprofloxacin, gentamycin and ketoconazole served as standard drugs. The synthesis of the derivatives was achieved through a base catalyzed the reaction of 4-chloroaniline with 1-naphthylamine to form 1-(naphthalen-1-yl) benzene-1,4-diamine. This intermediate was then treated with sulphur and iodine to yield the phenothiazine derivative while subsequent treatment of the phenothiazine compound with sulphonyl chlorides gave the final products. The synthesized compounds were characterized via proton nuclear magnetic resonance (1HNMR), carbon-13 nuclear magnetic resonance (13C NMR) and Fourier-transform infrared (FTIR) spectroscopic techniques. The minimum inhibitory concentration (MIC) of each compound was then determined using the agar well diffusion method. To predict the binding energies and patterns of the synthesized compounds with target proteins of the above mentioned microorganisms, molecular docking simulations were run using Autodock Vina software (version 4.2). The spectra data of the compounds for FTIR, 1H NMR and 13C NMR (δ) spectral data were consistent with the assigned structures of the synthesized compounds. The binding energies (kcal/mol) for in silico antimicrobial studies were in the range -5.1 to -7.6 kcal/mol. The MIC values were in the range -3.5 to 1.0 mg/L. The results of the in vitro test revealed that the synthesized compounds exhibits promising antimicrobial activity, and showed excellent bactericidal and fungicidal activities. The results obtained showed that the synthesized compounds possess drug-like properties and are good starting materials for drug production.

Federated learning trains a neural network model using the client's data to maintain the benefits of centralized model training, while maintaining the privacy. However, if the client data are not independently and identically distributed (non-IID) because of different environments, the accuracy of the model may suffer from client drift during training owing to discrepancies in each client's data. This study proposes a personalized federated learning algorithm based on the concept of multitask learning to divide each client model into two layers: a feature extraction layer and a category prediction layer. The feature extraction layer maps the input data to a low-dimensional feature vector space. Furthermore, the parameters of the neural network are aggregated with those of other clients using an adaptive method. The category prediction layer maps low-dimensional feature vectors to the label sample space, with its parameters remaining unaffected by other clients to maintain client uniqueness. The proposed personalized federated learning method produces faster learning model convergence rates and higher accuracy rates for the non-IID datasets in our experiments.

Background: The circadian system, a vital temporal regulator influencing physiological processes, has implications for cancer development and treatment response. Our study assesses circadian timing's impact on whole-brain radiotherapy outcomes in brain metastases for personalized cancer therapy insights. Aim: Evaluate circadian influence on radiation treatment timing and its correlation with clinical outcomes. Identify patient populations benefiting from interventions synchronizing circadian rhythms, considering subgroup differences and potential disparities related to social determinants of health (SDoH). Design: IRB-approved retrospective analysis of 237 patients undergoing whole-brain radiotherapy for brain metastases (2017–2021), receiving over 80% of treatments in the morning or afternoon. Survival analyses utilized Kaplan–Meier curves. Setting/Participants: Single-institution study involving patients receiving whole-brain radiotherapy. Collected demographic, disease, and socioeconomic parameters from electronic medical records. Results: Morning treatment (n=158) showed a trend towards improved overall survival vs. afternoon (n=79), median survival 158 vs. 79 days (p=0.20, HR=0.84, CI95% 0.84–0.91). Subgroup benefits for morning treatment in females (p=0.04) and trends in controlled primary disease (p=0.11) and breast cancer metastases (p=0.08). SDoH-based disparities observed, with Black and lower-income patients exhibiting diminished circadian influence. Conclusions: Emphasizes chronobiological factors' relevance in brain metastases radiation therapy. Morning treatment correlates with improved survival, particularly in specific subgroups. Identifies potential circadian influence disparities based on SDoH, laying a foundation for personalized cancer therapy and interventions synchronizing circadian rhythms for enhanced treatment efficacy.

Trimeresurus albolabris, also known as the white-lipped pit viper or white-lipped tree viper, is a highly venomous snake distributed across Southeast Asia and the cause of many snakebite cases. In this study, we report the first whole genome assembly of T. albolabris obtained with next-generation sequencing from a specimen collected in Mengzi, Yunnan, China. After genome sequencing and assembly, the genome of this male T. albolabris individual was 1.51 Gb in length and included 38.42% repeat-element content. Using this genome, 21,695 genes were identified, and 99.17% of genes could be annotated using gene functional databases. Our genome assembly and annotation process was validated using a phylogenetic tree, which included six species and focused on single-copy genes of nuclear genomes. This research will contribute to future studies on Trimeresurus biology and the genetic basis of snake venom.

The nano size, physical and chemical properties of Au and Ag nanoparticles (NPs) allow them to be used in medicine or plant protection, but chemical solvents used during synthesis makes them toxic and pose a threat to the environment. Chemical NPs synthesis can be replaced by in vivo synthesis in which independently growing plants such as alfalfa take up and then split the precursor in their cells down to nano size using synthesis-promoting solvents–biomolecules, which can break down materials without free radicals and has anti-inflammatory, antioxidant effects, making NPs environmentally benign. In this study, two-week-old seedlings of two Medicago sativa L. genotypes, ‘Kometa’ and ‘la Bella’, were exposed to two precursors (AgNO3, HAuCl4) for 24 and 48 h to determine whether in vivo synthesis is possible. Double-blazed and certain wavelength spectrophotometry and confocal microscopy confirmed, statistically significant (P<0.05) changes in light absorption and light fluorescence compared to the control. Confocal microscopy showed both precursors visible in the roots of both genotypes. Currently, NPs synthesis and visualisation methods require a complex, expensive and time-consuming sequence of methods. It is important to find an effective, environmentally friendly, and as cheap and simple as possible method for the biosynthesis of NPs.

Summer annual species are the most widely grown crops in the Upper Midwest, but reliance on a summer annual system has led to excessive soil and nutrient loss when crops are not present. Integrating winter rye (Secale cereale L.), known for its hardiness and environmental benefits, into the rotation can address these issues. However, there's limited understanding of the phenotypic diversity in winter rye during key growth stages that overlap with the typical planting dates for corn (Zea mays L.), soybean [Glycine max (L.) Merr], and late-planted crops like dry bean (Phaseolus vulgaris L.). Thus, the objectives of this study were to evaluate changes in biomass accumulation and quality of winter rye and triticale (x Triticosecale Wittmack) cultivars at three growth stages. Twenty cultivars were assessed over the 2014-2015 and 2015-2016 growing seasons across three environments in Minnesota. Winter rye and triticale were harvested for biomass at the tillering, booting, and soft dough growth stages and rye biomass yield and quality [i.e., crude protein, neutral detergent fiber (NDF), and 48-hour digestibility (NDFD)] were determined following harvest. Overall, there was little variation in each parameter among the cultivars within a location and growth stage. NDFD had some variation at the soft dough stage where digestibility ranged from 273 to 324 g kg-1 at the Crookston site and 332 to 406 g kg-1 at the St. Paul site. The lack of difference between cultivars indicates a wide range of choice when selecting a winter rye cultivar.

Long COVID–19 syndrome is another vicious feature of COVID-19 infection, the mechanism remains unidentified. Several observational studies suggest that vaccinations might have protective and therapeutic effect on long COVID-19 and our study aimed to assess the influence of vaccination on COVID-19 patients. We performed an observational cohort study from October 2020 to July 2022, which included 503 patients (291 males and 212 females) with a median age of 65. They were hospitalized due to COVID-19 pneumonia and had persistent symptoms (after 1 month of COVID-19 infection. The clinical and demographic data including vaccination status collected during hospitalization and regular visits at the Community Healthcare Center dr. Adolf Drolc Maribor were analyzed. More non-vaccinated patients acquired long COVID-19 than vaccinated. Patients with type 2 diabetes suffered from long COVID-19 in a smaller percentage than patients without diabetes. Gender, inhalational therapy due to chronic pulmonary disease and the number of complications have significantly influenced long COVID-19 development and the mostly vaccinated patients were older and with asthma/COPD. Our study confirmed that vaccination is a safe and effective measure to prevent the severe progression of acute disease and to lower the incidence of developing long COVID.

Recent technological advancements such as IoT and Big Data have granted industries extensive access to data, opening up new opportunities for integrating Artificial Intelligence (AI) across various applications to enhance production processes. We can cite two critical areas where AI can play a key role in industry such as product quality control and predictive maintenance. This paper presents a survey of AI applications in the domain of Industry 4.0, with a specific focus on product quality control and predictive maintenance. Experiments were conducted using two datasets, incorporating different machine learning and deep learning models from the literature. Furthermore, this paper provides an overview of the AI solution development approach for product quality control and predictive maintenance. This approach includes several key steps, such as data collection, data analysis, model development, model explanation, and model deployment.

Since 2015, community forests have been promoted in Togo as an alternative to protected areas degradation and as a means of contributing to forest landscape restoration. The study focuses on the Nakpadjouak Community Forest (NCF) in Tami (Togo, West Africa) which contributes to community forests sustainable management. It aims in (i) mapping forest ecosystems and analysing their dynamic and (ii) characterizing the floristic diversity of the NCF. The ecosystems were mapped and their dynamic evaluated based on Google Earth images of 2014 and 2020. Floristic and forestry inventories were carried out using the transect technique in a sample of 20 plots of 50 m x 20 m. The NCF was made up mainly by wooded/shrub savannahs (95.37%) and croplands/fallow (4.63%) in 2014. These two land use types undergone changes over the 6 years prior to 2020. By 2020, the NCF had 3 land use types: wooded/shrub savannahs (77.59%), open forest/wooded savannahs (22.23%), and croplands/fallows (0.18%). A total of 89 plant species belonging to 70 genera and 28 families were recorded within the NCF. The dominant species are: Hetopogon contortus (L.) P.Beauv. and Combretum collinum Fresen. followed by Pteleopsis suberosa Engl. & Diels, Annona senegalensis Pers. The most common species are: Lannea acida A.Rich. s.l., A. senegalensis, Vitellaria paradoxa C.F.Gaertner subsp. paradoxa, C. collinum and Acacia dudgeonii Craib ex Holland. Due to its small area of just 40 hectares and its diverse plant life, this community forest of Savannahs Region is a significant biodiversity hotspot and warrants conservation efforts.

Industry 4.0 is in continuous technological growth that benefits all sectors of industry and society in general. This article reviews the concept of Digital Twin (DT) and the interest of its application in photovoltaic installations. A comparison is made on how other authors use the DT approach in photovoltaic installations to improve the efficiency of the renewable energy generated and consumed, the energy prediction and the reduction of the operation and maintenance costs of the photovoltaic installation. It is reviewed how, by providing real-time data and analysis, DTs enable more informed decisions in the solar energy sector. The objectives of the review are to study the digital twin technology and to analyze its application and implementation in photovoltaic systems.

In the empirical dimension, the authors' intention was to define the criteria that should be taken into account by universities to meet the requirements of sustainable university development - in terms of activities and reporting through the analysis of good practices developed by top Polish universities. The aim was also to select activities that, based on benchmarks, could be used by universities at every stage of implementing SDG goals. This is not an easy task, considering that for educational institutions the priority is the educational process, and the implementation of the principles of sustainable development is only possible through an intensive educational process combined with the application of knowledge in practice. This is a challenge for the university because it requires remodeling the current culture, changes in processes and the perception of certain cultural and social phenomena, and will involve a change in the teacher-student relationship, a change in the traditional education process to practice-based education, and will also require an interdisciplinary context. in the content provided. But this is precisely the challenge for outstanding educators. The authors compared three significant world rankings to which Polish universities also report. They collected information and data mainly regarding the activities undertaken by the reporting Polish universities in the area of ​​developing good practices. Many ideas and tips will enable the preparation of further material, which the authors plan to deepen with a detailed analysis of SD indicators.

Three types of the composites were tested for electromagnetic interference (EMI) absorption shielding effectiveness, curing process and physical-mechanical properties. In the first type of composites, manganese-zinc ferrite, nickel-zinc ferrite, and both fillers in their mutual combinations were incorporated into acrylonitrile-butadiene rubber. The overall content of the filler, or fillers combinations was kept on 200 phr. Then, carbon black, or carbon fibres, respectively were incorporated into each rubber formulation in constant loading - 25 phr, while the content of magnetic fillers was unchanged - 200 phr. The work was focused on the understanding of correlation among electromagnetic shielding parameters and electrical conductivity of composites in relation to their EMI absorption shielding effectiveness. The absorption shielding ability of materials was evaluated within the frequency range from 1 MHz to 6 GHz. The study revealed good correlation among permittivity, conductivity, and EMI absorption effectiveness. Although, the absorption shielding efficiency of composites filled only with ferrites seems to be the highest, the absorption maxima of those composites were reached over 6 GHz. The application of carbon based fillers resulted in higher electrical conductivity and higher permittivity of composites, which was reflected in their lower absorption shielding performance. Though, the composites with filled with ferrites and carbon based fillers absorbed electromagnetic radiation within the desired frequency range. The presence of carbon based fillers caused the improvement in tensile behavior of composites. The study also demonstrated that the higher was the ratio of nickel-zinc ferrite in magnetic fillers combinations, the higher was the absorption shielding performance.

Performance of the overhead squat may affect golf swing mechanics associated with golf-related low back pain. This study investigates the difference in lumbar kinematics and joint loads during the golf downswing between golfers with different overhead squat abilities. Based on the per-formance of the overhead squat test, 21 golfers aged 18 to 30 years were divided into the highest-scoring group (HS, N=10, 1.61 ± 0.05 cm, and 68.06 ± 13.67 kg) and lowest-scoring group (LS, N=11, 1.68 ± 0.10 cm, and 75.00 ± 14.37 kg). Data collection used a motion analysis system, two force plates, and TrackMan. OpenSim software was used to simulate the joint loads for each lum-bar joint. An independent t-test was used for statistical analysis. Compared to golfers demonstrat-ing limitations in the overhead squat test, golfers with better performance in the overhead squat test demonstrated significantly greater angular extension displacement on the sagittal plane, smaller lumbar extension angular velocity, and smaller L4-S1 joint shear force. Consequently, the overhead squat test is found to be a useful index to reflect lumbar kinematics and joint loading patterns during the downswing, and provides a good training guide reference for reducing the risk of a golf-related low back injury

Out of a worldwide annual incidence of ~150 million cases for urinary tract infection (UTI), >25% of outpatient prescriptions of oral antimicrobial treatment (OAT) are for cystitis not complicated by sepsis. OAT aids the immune cells infiltrating urothelium to eliminate uropathogens attaching and invading urothelium amidst hyperosmotic urine. This adaptability of uropathogens and the short interval between Penicillin sale and the first antimicrobial resistance (AMR) report suggests that AMR is a 3.8 billion years old evolutionary conserved heritable trait of surviving environmental threats through exponential proliferation of mutant strains selected by Darwinian principle. Therefore, OAT success with minimal AMR can be ensured by antimicrobial stewardship (AMS) following the principle of 5Ds -drug, dose, duration, drug-route, and de-escalation. While convenient to administer, the onset of minimum inhibitory concentration (MIC) for OAT in urine is a window of opportunity for uropathogens to survive the first contact with OAT and the descendant colonies armed with AMR are likely to survive subsequent higher urine OAT levels. Meanwhile, intravesical antimicrobial treatment (IAT) delivers the first strike well above MIC. The root cause analysis of AMR dovetails with the strengths, weaknesses, opportunity, and threat (SWOT) analysis of OAT in this interdisciplinary review.

The goal of this study was to determine the relative susceptibility of four common equine wound pathogens to ten different types of antimicrobial agents based on minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). Additionally, to describe the comparison of bactericidal activity of medical grade Manuka honey, local honey, and commercial, food-grade honey to other commonly used wound dressings. The objective is to provide veterinary practitioners with comparative data on the use of a variety of antimicrobial dressings for inhibiting growth of common wound bacteria. MIC and MBC for Manuka, store, and local honeys were comparable to those of sterile gauze, sugar, and hypertonic saline. Across bacterial species, local honey proved to have more bactericidal activity when compared to Manuka and commercial, food-grade honey. The MIC and MBC for PHMB gauze and foam was consistently at a higher dilution compared to the other antimicrobials. The majority of antimicrobials exhibited stronger inhibitory and bactericidal activity against a Streptococcus zooepidemicus isolate obtained from a wound compared to other bacteria that were ATCC lab acclimated. Additional research for in-vivo applications needs to be done to see whether differences exist in effective wound management.