IoT is a computational perception that defines a situation, where smart objects are interconnected to the internet/ network. In the last few years, IoT objects have increased in all sectors/ fields and use in all domains of our lives. As the number of devices increases, the privacy of data becomes an important issue. To deal with this issue different techniques have been used by researchers in this field. Unfortunately, these methods have less traceability, privacy of data, and accountability. This paper aims to design a blockchain-based network architecture for Traceability, Data privacy, and Accountability (TDA). Technologies of blockchain are known as a distributed ledger of transactions record, which record the life span information with a timestamp. The major features of blockchain are persistency, decentralization, and audibility. These features help to decrease the budget and increase efficiency. Moreover, to strengthen the TDA architecture, this paper also discusses the performance of the proposed architecture.

Climate risk is one of the confronting factors in Indian agriculture. To overcome this distrust, a large number of sensors can be installed in the fields,The extensive IoT platform can process the data sent by these sensors.The Data stream can be processed in real-timeusing Fuzzylogic, to offer smart solution. Network coding can enhance throughput and security. Thus reducing human interaction and improve efficiency.

The significance of Kashmir conflict as one of the world’s longest running conflicts has frequently drawn the attention of both communication and international relations’ scholars which makes it an important issue from the perspective of interdisciplinary approach. The researchers have attempted to assemble a brief history of the Indian held Jammu and Kashmir Conflict from the time of partition in 1947 to the developments which took place till 2019 in the light of the available literature. The paper provides substantial historical context of the important events like instrument of accession, UN resolutions on Kashmir conflict, Simla Accord, Gawkadal Massacre , Lahore Declaration, Kargil War, killing of Burhan Wani, Uri attack and Article 370’s abrogation .

The microgrid is a small-scale, autonomous decentralized power plant with its own distributed generation, storage capacity and multiple loads, with the capacity to function in grid interconnected and an island mode. The decentralized control of microgrids with parallel operated voltage source converters (VSCs) is proposed in this paper to improve power quality using a machine learning approach. The DNN based MPPT controller is proposed and its best performance is presented. The SRF-PLL is utilized for AC side synchronization in VSC control. The proposed microgrid involves two PV arrays fed to two voltage source converters along with their independent controls, connected in parallel through LC filters and line coupling transformers and serves the loads at PCC. The proposed model is simulated using MATLAB/Simulink. The dq-framed inner loop control is employed to individually regulate the real and reactive power at the point of common coupling. Furthermore, the proposed model is analyzed and compared by employing a mathematical model of AC system dynamics, inner loop control, output voltage quality, AC harmonic spectrum analysis, and total harmonic distortion (THD) in both grid interconnected and island mode. In island mode, AC harmonic spectrum and THD are accomplished within the permissible range.

Studies evaluating candidate tick-derived proteins as anti-tick vaccines in natural hosts have been limited due to high costs. To overcome this problem, animal models are used in immunization tests. The aim of this article was to review the use of rabbits as an experimental model for the evaluation of tick-derived proteins as vaccines. A total of 57 tick proteins have been tested for their immunogenic potential using rabbit as model for vaccination. The most commonly used rabbit breeds were New Zealand (73.8%), Japanese white (19%), Californians (4.8%) and Flemish lop-eared rabbit (2.4%). Anti-tick vaccines efficacy resulted in up to 99.9%. Haemaphysalis longicornis (17.9%) and Ornithodoros moubata (12.8%) were the most common tick model in vaccination trials. Experiments in rabbits have revealed that some proteins (CoAQP, OeAQP, OeAQP1, Bm86, GST-Hl, 64TRP, serpins and voraxin) can induce immune responses against various tick species. In addition, in some cases it was possible to determine that the vaccine efficacy in rabbits was similar to experiments performed in natural hosts (e.g. Bm86, IrFER2, RmFER2, serpins and serine protease inhibitor). In conclusion, results have shown that prior to performing anti-tick vaccination trials using natural hosts, rabbits can be used as suitable experimental models for these studies

Task sharing approaches are challenged by the barriers fundamental to the use of non-specialists who lack specialist mental health training required to triage the candidates who could benefit from task-shared treatments. However, these challenges could be offset by using standardized and easy-to-implement algorithmic devices (e.g., nomograms) to help with the targeted dissemination of interventions. Therefore, the present investigation posits a prognostic model and a nomogram to predict the prognosis of perinatal depression among women in rural Pakistan. This secondary analysis utilizes data based on 903 pregnant women with depression who participated in a cluster randomized controlled trial that tested the effectiveness of the Thinking Healthy Program in rural Rawalpindi, Pakistan. The participants were recruited from 40 union councils in two sub-districts of Rawalpindi and randomly assigned to intervention and enhanced usual care. Sixteen sessions of the THP intervention were delivered by trained community health workers to women with depression over pregnancy and the postnatal period. A trained assessment team used the Structured Clinical Interview for the DSM-4 current major depressive episode module to diagnose depression at the baseline and post-intervention. The intervention received by the participants emerged as the most significant predictor in the model. Among clinical factors, baseline severity of core-emotional symptoms emerged as an essential predictor, followed by atypical symptoms and insomnia. Higher severity of these symptoms was associated with a poorer prognosis. Other important predictors of a favorable prognosis included living with paternal and maternal grandmothers, financial empowerment, higher socioeconomic class, and living in a joint family system. This prognostic model yielded acceptable discrimination (c-statistic =0.75) and calibration to aid in personalized delivery of psychological treatment.

Covid-19 is an airborne disease, with the vast majority of infections occurring indoors. By comparison, little transmission occurs outdoors. Here, we investigate the airborne transmission pathways that differentiate the indoors from outdoors, and conclude that profound differences exist, which help to explain why SARS-CoV-2 transmission is much more prevalent indoors. Near and far-field transmission pathways are discussed along with factors that affect infection risk, with aerosol concentration, air entrainment, thermal plumes, and occupancy duration all identified as being influential. In particular, we present the fundamental equations that underpin the Wells-Riley model, and show the mathematical relationship between inhaled virus particles and quanta of infection. A simple model is also presented for assessing infection risk in spaces with incomplete air mixing. Transmission risk is assessed in terms of aerosol concentration using simple 1D equations, followed by a description of thermal plume-ceiling interactions. With respect to this, we present new experimental results using Schlieren-visualisation and Computational Fluid Dynamics (CFD) based on the Eulerian-Lagrangian approach. Pathways of airborne infection are discussed, with the key differences identified between indoors and outdoors. In particular, the contribution of thermal and exhalation plumes is evaluated, and the presence of near-field/far-field feedback loop postulated, which is absent outdoors.

Almond (Prunus dulcis (Mill.) D.A.Webb) is one of the largest nut crops in the world. Recently, phenolic compounds, mostly stored in almond skin, have been associated with much of the health-promoting behavior associated with their intake. The almond skin enriched fraction obtained from cold-pressed oil residues of the endemic Moroccan Beldi ecotypes is particularly rich in chlorogenic acid. In this study, both almond skin extract (AE) and chlorogenic acid (CHL) supplements, similar to traditional positive control resveratrol, significantly increased the replicative life-span of yeast compared to the untreated group. Our results showed that AE and CHL significantly reduced the production of reactive oxygen and nitrogen species (ROS/RNS), most likely due to their ability to maintain mitochondrial function during aging, as indicated by the maintenance of normal mitochondrial membrane potential in treated groups. This may be associated with the observed activation of the anti-oxidative stress response in treated yeast, which results in activation at both gene expression and enzymatic activity levels for SOD2 and SIR2, the latter being an upstream inducer of SOD2 expression. Interestingly, the differential gene expression induction of mitochondrial SOD2 gene at the expense of the cytosolic SOD1 gene confirms the key role of mitochondrial function in this regulation. Furthermore, AE and CHL have contributed to the survival of yeast under UV-C-induced oxidative stress, by reducing the development of ROS / RNS, resulting in a significant reduction in cellular oxidative damage as evidenced by decreased membrane lipid peroxidation, protein carbonyl content and 8-oxo-guanine formation in DNA. Together, these results demonstrate the interest of AE and CHL as new regulators in the replicative life-span and control of the oxidative stress response of yeast.

The Internet of Things (IoT) is an emerging technology that aims to enable the interconnection of a large number of smart devices and heterogeneous networks. Ad hoc networks play an important role in the designing of IoT-enabled platforms due to their efficient, flexible, low-cost, and dynamic infrastructures. These networks utilize the available resources efficiently to maintain the Quality of Service (QoS) in a multi-hop communication. However, in a multi-hop communication, the relay nodes can be malicious, thus requiring a secured and reliable data transmission. In this paper, we propose a QoS-aware secured communication scheme for IoT-based networks (QoS-IoT). In QoS-IoT, a Sybil attack detection mechanism is used for the identification of Sybil nodes and their forged identities in multi-hop communication. %by high-power and mobile nodes. After Sybil nodes detection, an optimal contention window (CW) is selected for QoS provisioning, i.e., to achieve per-flow fairness and efficient utilization of the available bandwidth. In a multi-hop communication, the MAC layer protocols do not perform well in terms of fairness and throughput, especially when the nodes generate a large amount of data. It is because the MAC layer has no capability of providing QoS to prioritized or forwarding flows. We evaluate the performance of QoS-IoT in terms of Sybil attack detection, fairness, throughput, and buffer utilization. The simulation results show that the proposed scheme outperforms the existing schemes and significantly enhances the performance of the network with a large volume of data. Moreover, the proposed scheme is resilient against Sybil attack.

The Chat Generative Pre-training Transformer (GPT), also known as ChatGPT, is a powerful generative AI model that can simulate human-like dialogues across a variety of domains. However, this popularity has attracted the attention of malicious actors who exploit ChatGPT to launch cyberattacks. This paper examines the tactics that adversaries use to leverage ChatGPT in a variety of cyberattacks. Attackers pose as regular users and manipulate ChatGPT’s vulnerability to malicious interactions, particularly in the context of cyber assault. The paper presents illustrative examples of cyberattacks that are possible with ChatGPT and discusses the realm of ChatGPT-fueled cybersecurity threats. The paper also investigates the extent of user awareness of the relationship between ChatGPT and cyberattacks. A survey of 253 participants was conducted, and their responses were measured on a three-point Likert scale. The results provide a comprehensive understanding of how ChatGPT can be used to improve business processes and identify areas for improvement. Over 80% of the participants agreed that cyber criminals use ChatGPT for malicious purposes. This finding underscores the importance of improving the security of this novel model. Organizations must take steps to protect their computational infrastructure. This analysis also highlights opportunities for streamlining processes, improving service quality, and increasing efficiency. Finally, the paper provides recommendations for using ChatGPT in a secure manner, outlining ways to mitigate potential cyberattacks and strengthen defenses against adversaries.

Self-adaptive systems are capable of reconfiguring themselves while in use to reduce the risks forced by environments for which they may not have been specifically designed. Run-time validation techniques are required because complex Self-adaptive systems must consistently offer acceptable behavior for important services. The run-time testing can offer further confidence that a Self-adaptive system will continue to act as intended even when operating in unknowable circumstances. This article introduces an evolutionary framework that supports adaptive testing for Self-adaptive systems. To ensure that the adaptive systems continue to operate following its requirements and that both test plans and test cases continuously stay relevant to shifting operational conditions. The proposed approach using the SPEA2 algorithm facilitates both the execution and adaptation of run-time testing operations.

Currently, software development is more associated with families of configurable software rather than the single implementation of a product. Due to the numerous possible combinations in a software product line, testing these families of software product lines (SPLs) is a difficult undertaking (SPL). Moreover, the presence of optional features makes the testing of SPLs impractical. Several features are presented in SPLs, but due to the environment's time and financial constraints, these features are rendered unfeasible. Testing subsets of configured products is thus one approach to solving this issue. In order to reduce testing effort and get better results, alternative methods of testing SPLs are required, such as the combinatorial interaction testing (CIT) technique. Unfortunately CIT method produces unscalable solutions for large size SPLs with excessive constraints. The CIT method costs more because of feature combinations. The optimization of the various conflicting testing objectives, such as reducing the cost and configuration number, have also been considered. In this article, we have proposed a search-based software engineering solution using multi-objective optimization algorithms (MOEAs). In particular, the research is applied to different types of MOEA methods; Indicator-Based Evolutionary Algorithm (IBEA), Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D), Non-Dominated Sorting Genetic Algorithm II (NSGAII), NSGAIII, and Strength Pareto Evolutionary Algorithm 2 (SPEA2). The results of the algorithms are examined in the context of distinct objectives and two quality indicators. The results revealed how feature model attributes, implementation context and the number of objectives affect the performance of the algorithms.

Nizatidine is a gastroprotective drug with a short biological half-life and narrow absorption window. This study aimed at developing floating tablets of nizatidine using various HPMC viscosity grades, namely K4M, E4M, K15 and K200M. Directly compressed tablets revealed an excellent uniformity in hardness, thickness and weight and nizatidine was evenly distributed within the matrix floating tablets. Buoyancy study revealed floating lag time as low as 18–38 s, and tablets remain buoyant for upto 24 h. However, the later depended upon viscosity grade of HPMC and that the higher the viscosity, the less was the total floating time. In vitro dissolution indicated viscosity dependent nizatidine release from the floating tablets. HPMC K4M and E4M based floating tablets released almost 100% drug in 12 h, whilst higher viscosity polymers such as K15 and K200M only released 81.88% and 75.81% drug, respectively. The drug release followed non-Fickian diffusion from tablets formulated with K4M, K15 and K200M, whilst super case II transport was observed with E4M based tablets. More interestingly, K4M and E4M polymers have similar viscosity yet exhibited different drug release mechanism. This was attributed to the difference in degree of substitution of methoxyl- and hydroxypropoxyl- groups on polymer backbone.

Backyard chickens are the most popular poultry in Bangladesh due to their production potential, and income generation. However, this farming can be a factor in zoonotic disease transmission. This study aimed to assess the knowledge, attitudes, and practices (KAP) related to biosecurity and management among backyard chicken households in Bangladesh. A cross-sectional survey was conducted among 295 households in six sub-districts of different six divisions of Bangladesh. The study used a convenient sampling technique to choose the divisions, then the districts and sub-districts. A well-structured pre-tested questionnaire was used to interview randomly selected households. In this study, most of the respondents relied on agriculture crop production (n=128) as their primary source of income, relied on scavenging for their birds’ feeding (34%), or fed their chickens whole or broken rice (32%), used tube well water (58%), used ash (38%) or sand (28%) as litter material. A significant proportion of households (40%) did not use any nest box at all. Results also showed that the most reported poultry diseases among backyard poultry farmers were Newcastle disease (49%), followed by coccidiosis (30%), fowl cholera (12%), and fowl pox (9%). In the multivariate logistic regression model, knowledge of biosecurity was associated with the household type (OR=1.4, p=0.04), knowledge of vaccination (OR=3.7, p=0.02), don’t know category (OR=4.2, p=<0.001), provision of the nest box (OR=9.5, p<0.001), training (OR=0.1, p=0.04), and air pollution (OR=0.1; p=0.04). The study found a huge knowledge gap on management and biosecurity practices present among backyard chicken farmers, which can negatively impact public health for instance in the outbreak of zoonotic diseases. Increasing farmers' biosecurity awareness through education and outreach activities could minimize the risk of disease transmission and improve both public and poultry health.

Enteric viruses are the major cause of gastroenteritis and enteric hepatitis worldwide, but in some areas like Saudi Arabia little data is known about their presence in water sources. The available information from clinical samples is not enough to figure their actual prevalence. The aim of this study was to gather information for the first time in Saudi Arabia on the presence of Norovirus (NoV) genogroup GI and GII, hepatitis A virus (HAV) and hepatitis E virus (HEV) in water. For this purpose, thirteen monthly samples were collected in lake Wadi Hanifa and surrounding wells from December 2014 to November 2015. Viruses were detected and quantified by Real-time RT-qPCR. Despite HEV findings were anecdotic, our results highlight interesting behaviors of the other viruses. There was a higher prevalence of noroviruses in Wadi Hanifa samples than in well water samples (46.43% vs12.5% of NoV GI; 66.67% vs8.33% of NoV GII). On the contrary, similar levels of HAV positivity were observed (40.48% in surface water vs 43.06% in well water). Also, a strong influence of flooding events on HAV and NoV GI occurrence was observed in both surface and well water samples, being NoV GII apparently not affected.

In videos, the human's actions are of three-dimensional (3D) signals. These videos investigate the spatiotemporal knowledge of human behavior. The promising ability is investigated using 3D convolution neural networks (CNNs). The 3D CNNs have not yet achieved high output for their well-established two-dimensional (2D) equivalents in still photographs. Board 3D Convolutional Memory and Spatiotemporal fusion face training difficulty preventing 3D CNN from accomplishing remarkable evaluation. In this paper, we implement Hybrid Deep Learning Architecture that combines STIP and 3D CNN features to enhance the performance of 3D videos effectively. After implementation, the more detailed and deeper charting for training in each circle of space-time fusion. The training model further enhances the results after handling complicated evaluations of models. The video classification model is used in this implemented model. Intelligent 3D Network Protocol for Multimedia Data Classification using Deep Learning is introduced to further understand space-time association in human endeavors. In the implementation of the result, the well-known dataset, i.e., UCF101 to, evaluates the performance of the proposed hybrid technique. The results beat the proposed hybrid technique that substantially beats the initial 3D CNNs. The results are compared with state-of-the-art frameworks from literature for action recognition on UCF101 with an accuracy of 95%.

Effective pandemic management requires understanding the level of community knowledge, attitude of people and preparedness towards COVID-19. This study aimed to assess the knowledge, attitude and preparedness toward COVID-2019 among Bangladeshi general people. A cross sectional survey was conducted from 20th March 2020 to 20th April 2020 among 1007 Bangladeshi adult people. A convenience sampling strategy was utilized and the data was collected through a self-administered questionnaire. Chi-square test was used to identify the gender differences regarding knowledge, attitude and preparedness towards COVID-19. Respondents predominately used social media to inform themselves about COVID-19 (68.10%) and female used social media more than male (p<0.001). Female had more correct knowledge about staying home with sickness and/or symptoms to contain the COVID-19 transmission (p=.02). While male had more negative attitude about staying out during the pandemic than female (<0.001) and men were less likely to take preventative measures than female counterparts. A number of people were still believing the myths like “COVID-19 can transmit via mosquito” (9.14%) and male had more incorrect knowledge regarding this (p<0.001). Moreover, 17.81% of the respondents thought that COVID-19 can spread in warm weather. Some findings are directing us to a knowledge gap among general population in Bangladesh which calls for uncovering those aspects. Adequate and effective communication are necessary so that general people can stay alert with positive attitude and hygienic practices to fight against this ongoing crisis.

Previously reported atomic data (spectral lines, wavelengths, energy levels, and transition probabilities) have been collected and systematically analyzed for the Cs VI. The present theoretical analysis is supported by extensive calculations made for Cs VI with a pseudo-relativistic Hartree--Fock (HFR) method together with the superposition of configuration interactions implemented in Cowan's codes. In this critical evaluation, we provided several possibly observable lines with Ritz-wavelengths, computed from the optimized energy levels, and theoretical transition probabilities with their estimated uncertainties. In addition, we provided the radiative transition parameters for several forbidden lines within the ground configuration $5s^25p^2$ of Cs VI.

This study examined the effect of colleagues uncivil behavior on extra-role performance of teachers. The study further explored the mediating role of emotional exhaustion to intensify the effect. In parallel, moderation of psychological hardiness to absorb the negative shocks was also determined. For examining the direct, mediating, and moderating effects, primary data were collected through mailed questionnaires. To overcome the issues of common method biases, dyadic and time lagged approaches were used for collection of data. Responses were collected in three phases, with appropriate time intervals. Data of independent, mediating, and moderating variables were collected from teachers while of dependent variable form their immediate supervisors, i.e. HoDs. The study found a significant effect of colleagues’ discourteous behavior on extra-role performance of victims at job. Significant mediation of emotional exhaustion in the effect was also observed. In the meantime, hardiness of targets absolutely moderated the effect to minimize the associated consequences. Based on results, several policy implication and interventions were suggested.

Objectives: Human herpes viruses can cause life-threatening diseases in immunocompromised children, especially leukemic patients. Therefore, the aim of this study is to detect the human herpes viruses (HHV1-7) and to investigate its clinical significance in Middle Eastern Pediatric Leukemia Patients by using 2 Independent PCR assays. Methods: Detection of human herpes virus DNA has been done in blood samples of 200 pediatric leukemia patients in addition to 90 blood donors as a control group using multiplex PCR assays. When a ‘‘positive’’ result was observed, real-time PCR was performed to measure the viral load. Results: The most frequent herpes virus infection in Middle Eastern Pediatric Leukemia cases was CMV, followed by EBV, then HHV6, VZV, HHV7, HSV1, and HSV2, where they were 92/200 (46%), 76/200 (38%), 72/200 (36%), 48/200 (24%), 12/200 (6%), 8/200 (4%), and 2/200 (1%) respectively. Also, there was a statistically significance difference between leukemic patients and their controls regarding CMV, EBV, HHV6, and VZV (P <0.05). Correlation between percentage of co-infection, and clinical parameters for the 7 herpes viruses has been studied, and there is an increase in absolute neutrophilic count (ANC), total leukocyte count (TLC) and duration of fever and neutropenia in age group 6-11 years for HHV6/CMV, then in age group 12-18 years especially for EBV/CMV and CMV/HHV6. Also, our results show that multiplex PCR assay is close to single PCR assay in relation to specificity and sensitivity which in turn prove its validity for early diagnosis of herpes viral infection. Conclusions: Adopting multiplex PCR technique is helpful in screening of virus infections. It will save time, effort, cost effective and will assist in rapid diagnosis. However, the clinical relevance of the virus infection needs to be evaluated by quantitative real-time PCR which in turn will help patient's management by using appropriate antiviral treatment.

Bovine coronavirus (BCoV) is one of the most common pathogens affecting cattle of all ages. BCoV possesses multiple tissue tropism in cattle, particularly in the respiratory and enteric tracts of the affected animals. Viral entry is a crucial step in the replication cycle of all viruses, including BCoV. The process of viral entry requires the orchestration between several proteins from the virus and the host side. The coronavirus spike glycoproteins contributed substantially to other viral infections and the molecular pathogenesis of coronaviruses, including BCoV. Meanwhile, among all corona-viruses, the hemagglutinin esterase enzyme is found in only BCoV and the human corona-virus-OC43 (HCoV-OC43). The viral receptors are among the key players in the viral entry and could explain the viral tropism, at least in part. The presence of some host cell proteases also en-hances the virus replication from the entry until the release of the virus from the host cells. Previous studies have shown that the 9- O-acetylated sialic acids could potentially act as receptors for the BCoV. However, little is known about the BCoV receptors and if other co/receptors might be needed to ensure viral entry to the host cells. In addition to that, the roles of other host cell proteases, such as Furin and TMPRSS2, in BCoV infection have not yet been well studied. The main objectives of the current study are to identify some novel receptors for BCoV and some host cell proteases that might enhance virus replication. We used some in silico docking tools to predict some new BCoV receptors out of some known other coronavirus receptors (ACE-2, NRP1, DPP4, APN, and CEACAM1). Our results postulated the potential actions of the host Furin and TMPRRS2 enzymes in the activation of BCoV-S glycoprotein, which potentially enhances BCoV replication. Our modeling confirms the high binding affinities of both the 9- O-acetylated sialic and the NRP1 with the BCoV-S and BCoV-HE compared to the ACE-2, DPP4, and CEACAM-1, suggesting their roles as receptors for BCoV. Our prediction models show the potential bindings of the Furin and TMPRSS2 to the BCoV-S polybasic cleavage site (RRSRR|A). To our knowledge, this is the first study to investigate the bovine coronavirus interaction with some other potential host receptors, particularly ACE-2, NRP1, DPP4, APN and CEACAM1, TMPRSS2, and the bovine Furin protease.

Laminitis is considered as an important underlying cause of lameness diseases, yet its specific pathogenesis remains unclear. Autophagy is an intracellular degradation mechanism that controls recycling of membrane-associated integrin and may aid in the progression of metabolic diseases. But the significance of autophagy for initiation and development of laminitis is unknown. The present study aimed to explore autophagy activity in the laminar tissue of dairy cows with oligofructose-induced laminitis. Twelve healthy non-pregnant Holstein cows were randomly divided to 2 groups of 6 cows each, entitled the control group and the oligofructose overload group (OF group), respectively. At 0 h, cows in OF group were gavaged with oligofructose (17 g/kg BW) dissolved in warm deionized water (20 mL/kg BW) through oral rumen tube, and dairy cows in control group were gavaged with the same volume of deionized water by the same method. At -72 h before perfusion as well as 0 h, 6 h, 12 h, 18 h, 24 h, 36 h, 48 h, 60 h, and 72 h after perfusion, clinical evaluations in both groups were monitored. After 72 h, laminar tissues of dairy cows in both groups were collected to examine genes and proteins. We found the significantly higher (P<0.05) levels of mRNA ATG5, ATG12, and Becilin1, but P62 and mTOR were extensively lower (P<0.01) in the laminar tissue of the OF group than the control group. Protein expression level of Becilin-1 was higher significantly (P<0.05), and the protein expression level of LC3II was lower significantly (P<0.05) in OF group than control group. However, the expression of P62 reduced (P>0.05) non-significantly in OF group than control group. The distribution of Beclin1 protein in laminar tissue increased (P<0.01) significantly, and distribution of P62 protein decreased (P<0.05) significantly in OF group than control group. In conclusion, laminar tissue damage occurred during the onset of laminitis, which promoted the occurrence of autophagy, and confirmed that autophagy was involved in the regulation and pathogenesis of laminitis in dairy cows.

This study aimed (1) to map the immunogenic epitopes (B and T cells) within the major BCoV structural proteins. These epitopes are believed to induce a robust im-mune response through the interaction with major histocompatibility complex (MHC class II) molecules (2) to design some novel BCoV multi-epitope-based vac-cines. To achieve these goals, we applied several integrated In-silico prediction computational tools to map these epitopes within the major BCoV structural pro-teins. The predicted epitopes were linked to some immunostimulants such as Toll-like receptors-2 (TLR2) and TLR-4. The tertiary structure of each epitope was modeled through the Alpha fold-2 colab machine learning tools. The stability and purity of each epitope were assessed using the Ramachandran plot and the Z Score values. Each multiepitope-based vaccine candidate conjugated with the Chlorotox-in B toxin as an adjuvant. We designed the vaccine constructs using various expres-sion vectors. We also predicted the affinity binding of these vaccines with the target protein using molecular docking. Our designed multiepitope vaccine candidates per each BCoV structural protein showed high antigenicity, immunogenicity, non-allergic, non-toxic, and high water solubility. Further studies are highly en-couraged to validate the efficacy of these novel BCoV vaccines in the natural host.

In the present study, a simple approximation expression is given for the relationship between the period and amplitude of a simple pendulum under magnetic action. The analytical solution presented for the given problem. Two numerical quadrature methods Simpson's and Boole's method were utilized to demonstrate a new approximation of the problem. The results of the numerical quadrature have been compared to the exact solution. Absolute and relative mistakes of the problem have been presented. The Matlab program 2013R has created a numerical method that is used to analyze the outcome, It has been determined that the comparison's outcomes attest to the method's suitability and correctness. Moreover, the results show that numerical solution is suitable for the problem.

Kiwifruit vines are generally sensitive to waterlogging stress. So far, molecular responses of different kiwifruit genotypes for waterlogging stress are less well-explored. In this study, using RNA-sequencing, we examined transcriptional regulation in the roots of a waterlogging-tolerant genotype KR5 (Actinidia valvata), and a sensitive genotype ‘Hayward’ (Actinidia deliciosa) subjected to 0, 12, 24, and 72 h of waterlogging. Compared with 0 h, transcriptional adjustments of these two genotypes occurred as early as 12 h and became notably pronounced 72 h after waterlogging. Waterlogging stress for 72 h promoted the expression of genes involved in ethylene biosynthesis, sucrose and hexose transport, anaerobic fermentation, nitrate reduction, alanine accumulation, and reactive oxygen scavenging in both genotypes. The differential regulation of genes encoding 9-cis-epoxycarotenoid dioxygenase, phosphoglucomutase, alanine-glyoxylate transaminase, and other enzymes pointed to their diverse strategies upon waterlogging in these two genotypes. In addition, more sucrose and trehalose contents, as well as a higher activity of alcohol dehydrogenase and manganese superoxide dismutases were stimulated in KR5 roots after 72h of waterlogging than that in ‘Hayward’. Overall, our results provided more insights into the molecular basis of the waterlogging response in kiwifruit.

Almond (Prunus dulcis (Mill.) D.A.Webb) is one of the most important nut crops both in terms of area and production. Over the last decades, an important part of the beneficial actions for health associated with their consumption was attributed to the phenolic compounds, mainly accumulated in almond skin. Interestingly, after cold-pressed oil extraction, most of these antioxidant phenolic compounds are retained in a skin-enriched by-product, so-called almond cold-pressed oil residue. In Morocco, ranked fifth producer in the world, this production generates an important part of this valuable byproduct. In the present study, using a multivariate Box-Behnken design, an ultrasound-assisted extraction (USAE) method of phenolic compounds from Moroccan almond cold-pressed oil residue was developed and validated. Response surface methodology resulted in the optimal extraction conditions: the use of aqueous EtOH 53.0% (v/v) as green solvent, applying an US frequency of 27.0 kHz for an extraction duration of 29.4 min. The present USAE allowed substantial gains in terms of extraction efficiency compared to conventional heat reflux extraction. Applied to 3 different local Beldi genotypes growing at 3 different experimental sites, the optimal USAE conditions led to a total phenolic content of 13.86 mg/g dry weight (DW). HPLC analysis revealed that the main phenolic compounds from this valuable byproduct were: chlorogenic acid followed by protocatechuic acid, p-hydrobenzoic acid and p-coumaric acid. The accumulation of these phenolic compounds appeared to be more dependent on the genetic background than on the environmental impact here represented by the 3 experimental culture sites. Both in vitro cell free and cellular antioxidant assays were performed, and revealed the great potential of these extracts. In particular, correlation analysis evidenced the prominent roles of chlorogenic acid, protocatechuic acid and p-hydrobenzoic acid. To summarize, the USAE method presented here is a quick, green, simple and efficient validated USAE for the possible valorization of antioxidant phenolic compounds from Moroccan almond cold-Pressed oil residues, making it possible to generate extracts with attractive antioxidant activities for future nutraceutical and/or cosmetic applications.

To drive safely, the driver must be aware of the surroundings, pay attention to the road traffic, and be ready to adapt to new circumstances. Most studies on driving safety focus on detecting anomalies in driver behavior and monitoring the cognitive capabilities of drivers. In our study, we proposed a classifier for basic activities in driving a car, based on a similar approach that could be applied to the recognition of basic activities in daily life, that is, using electrooculographic (EOG) signals and a one-dimensional convolutional neural network (1D CNN). Our classifier achieved an accuracy of 80% for the 16 primary and secondary activities. The accuracy related to primary activities in driving, including crossroad, parking, roundabout was 97.9%, 96.8%, 97.4%, and 99.5%, respectively. The F1 score for secondary driving actions (0.99) was higher than for primary driving activities (0.93–0.94). Furthermore, using the same algorithm, it was possible to distinguish four secondary activities related to activities of daily life and secondary when driving a car.

Perovskite solar cells (PSCs) are vital for their optical and electrical properties, with lead-based PSCs reaching a remarkable efficiency of 26.1%, while tin-based counterparts achieve 18.71%. Due to lead's toxicity, there's a push for alternatives like tin. However, tin-based PSCs suffer from stability issues and high defect density states, necessitating the development of cost-effective, high-performance, and eco-friendly alternatives. In this study, we designed a hetero-junction architecture using MASnI3-based Perovskite, opti-mized with SCAPs-1D. After exhaustive analysis, our device achieved a power conversion efficiency of 24.18%, with enhanced parameters including Voc of 0.09323V, Jsc of 30.8360 mA/cm2, and FF of 84.10%. Recombination rates, particularly Shockley-Read Hall recom-bination, were significantly reduced. Parametric analyses, encompassing absorber layer thickness, band gap, defect density, doping concentration, and operating temperature, in-dicate potential efficiency enhancements. This underscores the viability of Sn-based PSCs as a cost-effective, efficient, and environmentally benevolent alternative to lead-based counterparts, promising advancements in future research and development efforts.

Cardiovascular diseases (CVD) are chronic diseases associated with a high risk of mortality and morbidity. Early detection of CVD is crucial to initiating timely interventions, such as appro- priate counseling and medication, which can effectively manage the condition and improve patient outcomes. Preventive measures should be implemented at the general public level, promoting a healthy lifestyle, and at the individual level, that is, in people with moderate to high risk of CVD or patients already diagnosed with CVD by addressing an unhealthy lifestyle. Personalized early diagnostic systems based on artificial intelligence (AI), ontologies, and other medical information processing systems may prove to be a great preventive measure. In this paper, we focus on the use of ontology-inspired database models in the diagnosis of cardiovascular disease, as well as their potential for use in web application development.

Tandemly organized rRNA genes are the typical example of a multigene family, where individual members evolve coordinately within but independently between species due to gene conversion and unequal crossing over. More frequently, in eukaryotic species with an inter-species hybrid origin, expression of unhomogenized rRNA genes from one progenitor is epigenetically silenced because of nucleolus dominance, and distinct rRNA genes may lose functionality and evolve faster. Interestingly, we obtained unusual ribosomal gene sequences from Oryza species that showed great diversity and did not appear in the present rice genomic sequence. The diversity of rDNA sequences indicated that the homogenization in rice is incomplete and explains the introgression of distinct rRNA gene families into ancestral rice genome before speciation and continent separation. The divergent large subunit (LSU) ribosomal genes are expressed, some of them differentially, depending on the N-fertilization of plants. Detection of differential transcripts of the rRNA genes suggested that rRNA gene families are not functionally equivalent. Phylogenetic analysis assigned Oryza species branching order to monocots, and monocot lineages probably have the same ecological origin by molecular clock calculation. Therefore, our results suggested that the geographical distances of continents separation cause barriers to the gene flow and homogenization among Oryza species which requires further explanation,

The predominant management approach for municipal solid waste (MSW) remains disposal, given significant increases in generation and disposal rates of MSW in recent decades. In addition to the well-documented carbon emissions from disposal sites, these sites accumulate numerous elements, the masses of which are substantial globally yet inadequately quantified. The unique combinations of waste constituents, elements, diverse environments, and confined spaces in disposal sites create distinct biogeochemical conditions, setting them apart from any other infrastructure or geological feature on Earth. This review first presents a global summary of the cumulative masses and disposal rates of MSW constituents and associated elements. The five dominant transformation and transport processes influencing disposed elements are examined: biochemical degradation, physicochemical transformation, gas migration, leachate migration, and solid spillage. The magnitudes and rates of the processes corresponding to major disposed elements, including carbon, nitrogen, sulfur, chlorine, and several metals, are systematically summarized. We examine and quantify the potential environmental impacts and health risks associated with element transformation and transport. We also explore the existing knowledge and techniques for resource recovery and site remediation of disposal sites. The distilled compilation of measurements and insights herein serves as a valuable primer for researchers, practitioners, and decision-makers involved in MSW management.

The botanical species Ceratonia siliqua L., commonly referred to as the Carob tree, and locally as “L’Kharrûb”, holds significance as an agro-sylvo-pastoral species, and is traditionally utilized in Morocco for treating a variety of ailments. This current investigation aims to ascertain the antioxidant, antimicrobial, and cytotoxic properties of the ethanolic extract of C. siliqua leaves (CSEE). Initially, we analyzed the chemical composition of CSEE through high-performance liquid chromatography with Diode-Array Detection (HPLC-DAD). Subsequently, we conducted various assessments, including DPPH scavenging capacity, β-carotene bleaching assay, ABTS scavenging, and total antioxidant capacity assays, to evaluate the antioxidant activity of the extract. In this study, we investigated the antimicrobial properties of CSEE against five bacterial strains (two gram-positive, Staphylococcus aureus, and Enterococcus faecalis; and three gram-negative bacteria, Escherichia coli, Escherichia vekanda, and Pseudomonas aeruginosa) and two fungi (Candida albicans, and Geotrichum candidum). Additionally, we evaluated the cytotoxicity of CSEE on three human breast cancer cell lines (MCF-7, MDA-MB-231, and MDA-MB-436) and assessed the potential genotoxicity of the extract using the comet assay. Through HPLC-DAD analysis, we determined that phenolic acids and flavonoids were the primary constituents of the CSEE extract. The results of the DPPH test indicated a potent scavenging capacity of the extract with an IC50 of 302.78 ± 7.55 µg/mL, which was comparable to that of ascorbic acid with an IC50 of 260.24 ± 6.45 µg/mL. Similarly, the β-carotene test demonstrated an IC50 of 352.06 ± 12.16 µg/mL, signifying the extract's potential to inhibit oxidative damage. The ABTS assay revealed IC50 values of 48.13 ± 3.66 TE µmol/mL, indicating a strong ability of CSEE to scavenge ABTS radicals, and the TAC assay demonstrated an IC50 value of 165 ± 7.66 µg AAE/mg. The results suggest that the CSEE extract had potent antioxidant activity. Regarding its antimicrobial activity, the CSEE extract was effective against all five tested bacterial strains, indicating its broad-spectrum antibacterial properties. However, it only showed moderate activity against the two tested fungal strains, suggesting it may not be as effective against fungi. The CSEE exhibited a noteworthy dose-dependent inhibitory activity against all the tested tumor cell lines in vitro. The extract did not induce DNA damage at the concentrations of 6.25, 12.5, 25, and 50 µg/ml, as assessed by the comet assay. However, the 100 µg/ml concentration of CSEE resulted in a significant genotoxic effect compared to the negative control. A computational analysis was conducted to determine the physicochemical and pharmacokinetic characteristics of the constituent molecules present in the extract. The Prediction of Activity Spectra of Substances (PASS) test was employed to forecast the potential biological activities of these molecules. Additionally, the toxicity of the molecules was evaluated using the Protox II webserver.

The information about the BCoV receptors, co/receptors that might be involved in the BCoV entry to the host cells is inconceivable. In addition to that, the roles of other host cell proteases, such as Furin and TMPRSS2, have not yet been well studied during BCoV replication. The current study’s main objectives are to identify some novel BCoV receptors and host cell proteases that might fine-tune the BCoV replication, tissue tropism, and molecular pathogenesis. We used a combination of some in silico prediction, molecular docking, and gene expression profile tools to predict some new BCoV receptors out of some known other coronavirus receptors and some host cell enzymes that are potentially involved in BCoV replication. To achieve these goals, we applied the in-silico prediction tools to check the potential interactions between eh BCoV/S glycoprotein and some known coronaviruses receptors (ACE2, APN1, NPR1, CECAM-1, AXL, and DPP4). We also established some potential models for the interaction between the BCoV/S and some common host cell proteases proved to play important roles in other coronavirus replication cycle (Furin, TMPRRS2, and Cathepsin-L). To confirm our prediction models, we assessed the gene expression profiles of these potential receptors and proteases in some bovine cell lines infected with BCoV using the next generation sequencing and the qRT-PCR assay. Our results show that the NPR1, AXL1 and the ACE2 have the strongest and firm binding affinities to the BCoV-S protein. Our prediction models and gene expression profiles show the potential bindings of the Furin and TMPRSS2 to the BCoV-S polybasic cleavage site (RRSRR|A). Notably, high expression of the host cell Furin was observed in response to both BCoV/Ent and BCoV/Resp infection, whereas TMPRSS2 expression was upregulated in the case of the BCoV/Ent infection, positioning Furin as a common receptor for different BCoV isolates. Further research is needed to study the roles of these top-ranked receptors and host cell proteases in molecular pathogenesis, and tissue tropism.

Background: Chronic Myeloid Leukemia (CML) is initiated in bone marrow due to chromosomal translocation t(22;9) leading to fusion oncogene BCR-ABL. Targeting BCR-ABL by tyrosine kinase inhibitors (TKI) have changed fatal CML into an almost curable disease. Despite that, TKIs lose their effectiveness due to disease progression. Unfortunately, mechanism of CML progression is poorly understood and common biomarkers for CML progression are unavailable. This study was conducted to find out novel biomarkers of CML progression by employing whole exome sequencing (WES).Materials and Methods: WES of accelerated phase (AP-) and blast crisis (BC-) CML patients was carried out, with chronic phase CML (CP-CML) patients as control. After DNA library preparation and exome enrichment, clustering and sequencing was carried out using Illumina platforms. Statistical analysis was carried out using [SAS/STAT] software version 9.4 and R package employed to find mutations shared exclusively by all AP-/BC-CML. Confirmation of mutations was carried out using Sanger sequencing and protein structure modelling using I-Tasser followed by mutant generation and visualization using PyMOL. Results: Three novel genes (ANKRD36, ANKRD36B and PRSS3) were mutated exclusively in all AP-/BC-CML patients. Only ANKRD36 gene mutations (c.1183_1184 delGC and c.1187_1185 dupTT) were confirmed by Sanger sequencing. Protein modelling studies showed that mutations induce structural changes in ANKRD36 protein. Conclusions: Our studies show that ANKRD36 is a potential common biomarker and drug target of early CML progression. ANKRD36 is yet uncharacterized in human. It has the highest expression in bone marrow, specifically myeloid cells. We recommend carrying out further studies to explore the role of ANKRD36 in biology and progression of CML.

Dengue infection is caused by the Dengue virus (DENV) and is transmitted to humans by infected female Aedes aegypti and Aedes albopictus mosquitoes. There are nearly 100 million new dengue cases yearly in more than 120 countries with a five-fold increase in incidence over the past four decades. While many patients experience a mild illness, a subset suffer from severe disease which can be fatal. Dysregulated immune responses are central to the pathogenesis of dengue, and haematologic manifestations are a prominent feature of severe disease. While thrombocytopaenia and coagulopathy are major causes of bleeding in severe dengue, leucocyte abnormities are emerging as important markers of prognosis. In this review, we provide our perspective on the clinical aspects and pathophysiology of haematologic manifestations in dengue. We also discuss the key gaps in our current practice and areas to be addressed by future research.

The pervasive presence of atmospheric pollution, particularly polycyclic aromatic hydrocarbons such as 7,12-dimethylbenz(a)anthracene, instigates aberrant cellular and tissue conditions, precipitating oxidative damage and inflammatory cascades conducive to the onset of cancer, notably mammary cancer. Given the hepatic metabolism of 7,12-dimethylbenz(a)anthracene, liver damage can be found and the imperative of employing natural antioxidants becomes apparent. In this study, we first showed that 7,12-dimethylbenz(a)anthracene-intoxication escalates body weight, disrupts lipid profiles, and incites serum oxidative damage. Concurrently, hepatic and renal oxidative stress ensue, accompanied by heightened antioxidant enzyme activity in the 7,12-dimethylbenz(a)anthracene-exposed group compared to controls (p&lt;0.05). Interestingly, P.lentiscus co-administration rectifies biochemical imbalances, significantly attenuates oxidative stress aberrations, and augments antioxidant enzyme responses (p&lt;0.05). Importantly, histological analysis evinces P.lentiscus's shielding effect against 7,12-dimethylbenz(a)anthracene induced hepatocyte injury and steatosis. Furthermore, our investigations unveil P.lentiscus’s anti-proliferative efficacy against different human breast cancer cell lines. Thus, our findings underscore P.lentiscus‘s robust anti-proliferative, antioxidant, and hepato-protective capacities, mitigating metabolic disturbances, oxidative stress propagation in liver and kidney functions, and potential histological alterations, thereby impeding 7,12-dimethylbenz(a)anthracene induced mammary cancer initiation. We posit that P.lentiscus may serve as a prophylactic agent against breast cancer and liver oxidative damage instigated by this carcinogen.

The pervasive presence of atmospheric pollution, particularly polycyclic aromatic hydrocarbons such as 7,12-dimethylbenz(a)anthracene, instigates aberrant cellular and tissue conditions, precipitating oxidative damage and inflammatory cascades conducive to the onset of cancer, notably mammary cancer. Given the hepatic metabolism of 7,12-dimethylbenz(a)anthracene, the imperative of employing natural antioxidants becomes apparent. In this study, we delve into the antioxidant and hepato-protective properties of Pistacia lentiscus against 7,12-dimethylbenz(a)anthracene-induced toxicity, alongside exploring its potential anticancer attributes. Our investigations unveil Pistacia lentiscus's anti-proliferative efficacy against human breast cancer cell lines. Notably, 7,12-dimethylbenz(a)anthracene-intoxication escalates body weight, disrupts lipid profiles, and incites serum oxidative damage. Concurrently, hepatic and renal oxidative stress ensue, accompanied by heightened antioxidant enzyme activity in the 7,12-dimethylbenz(a)anthracene-exposed-group compared to controls (p&lt;0.05). Nonetheless, Pistacia lentiscus co-administration rectifies biochemical imbalances, significantly attenuates oxidative stress aberrations, and augments antioxidant enzyme responses (p&lt;0.05). Importantly, histological analysis evinces Pistacia lentiscus's shielding effect against 7,12-dimethylbenz(a)anthracene induced hepatocyte injury and steatosis. Our findings underscore Pistacia lentiscus's robust anti-proliferative, antioxidant, and hepato-protective capacities, mitigating metabolic disturbances, oxidative stress propagation in liver and kidney functions, and potential histological alterations, thereby impeding 7,12-dimethylbenz(a)anthracene-induced mammary cancer initiation. We posit that Pistacia lentiscus may serve as a prophylactic agent against breast cancer instigated by this carcinogen.

Contamination in coastal regions attributed to fluoride and nitrate cannot be disregarded, given the substantial environmental and public health issues they present worldwide. Maintaining water quality is crucial for environmental well-being. This comprehensive study was performed to assess the spatial as well as indexical water quality, identify contamination sources, and evaluate associated health risks pertaining to nitrate and flouride in AlHassa region, KSA. The physiochemical results revealed a pervasive pollution of the overall groundwater. The dominant water type was Na-Cl, indicating saltwater intrusion and reverse ion exchange impact. Spatiotemporal variations in physicochemical properties suggest diverse hydrochemical mechanisms, with geogenic factors primarily influencing groundwater chemistry. The groundwater pollution index varied between 0.8426 and 4.7172, classifying samples as moderately to very highly polluted. Similarly, the synthetic pollution index (in the range of 0.5021-4.0715) revealed that none of the samples had excellent water quality, with various degrees of pollution categories. Nitrate Health Quotient (HQ) values indicated chronic human health risks ranging from low to severe, with newborns being the most vulnerable. Household use of nitrate-rich groundwater for showering and cleaning did not pose significant health risks. Fluoride HQ decreased with age, and children faced the highest risk of fluorosis. The Hazard Index (HI) yielded moderate to high-risk values. Nitrate risks were 1.21 times higher than fluoride risks, as per average HI assessment. All samples fell into the vulnerable category based on the Total Hazard Index (THI), with 88.89% classified as very high risk. This research provides valuable insights into groundwater quality, guiding water authorities, inhabitants, and researchers in identifying safe water sources and vulnerable human populations. The results highlight the need for appropriate treatment techniques and long-term coastal groundwater management plans.