Introduction: Isolated terminal ileitis (ITI) is commonly found associated with Crohn’s disease but it has other etiologies too. Other common causes of ITI include nonsteroidal anti-inflammatory drug (NSAID) use, tuberculosis and other bacterial/parasitic infections, neoplasia, radiation or other autoimmune disorders. Methods: After obtaining IRB approval, a retrospective chart review was conducted on patients with biopsy proven ITI from May 2011 to May 2016 at our academic medical Centre. Data was collected pertaining to demographics, body mass index (BMI), associated Crohn’s disease or ulcerative colitis, treatment received and other causes of ileitis noted. Data was analyzed using SPSS software with chi square used to analyze categorical variables. P<0.05 was considered statistically significant. Results: A total of 229 patients with clinical symptoms and ITI on biopsy were reviewed. The mean age of our patients was 43.7 years old. Of the patient group, 49% (n=113/229) were males and the rest were females. Only 42% of patients with ITI were eventually diagnosed with Crohn's disease. Stool cultures were performed in 37% (n=86/229) of patients with positive results in 0.04% (n=4/86) of the patients. Most patients were treated with antibiotics after diagnosis of ileitis without determination of the exact etiology of the condition. Amongst those evaluated, one had tuberculosis, one had ischemic ileitis and one had Meckel’s diverticulum. NSAID use accounted for 26% (n=59/229) of ITI cases. Treatment generally involved antibiotics, initiation of biologics or use of 5-aminosalicylic acid products. The mean length of hospitalization was 1.25 days. Mean BMI of our patients was 25 kg/m2 and there was no statistically significant association noted between ITI and BMI. Presence of Crohn’s disease with ITI had a statistically significant association with positive clostridium difficile infection and subsequent need for treatment with biologics for isolated disease (p<0.001). Conclusions: Isolated terminal ileitis is commonly associated with Crohn’s disease but there are other conditions that should be suspected and can mimic Crohn’s disease histologically and endoscopically in the Ileum. NSAIDS are an important cause of ITI and need to be specifically inquired from the patient. If not considered it can result in misdiagnosis of Crohn’s disease and inappropriate treatment. Hence being aware of the wide range of differential diagnoses that can present with inflammation of the terminal ileum is important to avoid this inadvertent mislabeling. This retrospective study highlights the importance of other differentials when considering the management of a patient with ITI and not just focusing on only Crohn’s disease as the possible etiology.

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by the loss of dopaminergic neurons and the buildup of misfolded alpha-synuclein proteins. While its exact cause remains unknown, several factors may influence its development. This review examines how factors like chronic constipation, head injuries, cholesterol and uric acid levels, pesticide exposure, smoking, NSAIDs, and caffeine intake may affect PD risk. Chronic constipation appears to be linked to a higher risk of PD, potentially serving as an early warning sign. Head injuries, especially mild-to-moderate ones, may also play a role in increasing PD risk. Surprisingly, higher levels of cholesterol seem to protect against PD, while lower levels of uric acid might increase the risk in the presence of some differences according to gender type. Exposure to certain pesticides is associated with a higher PD risk. NSAIDs, on the other hand, may or may not have a protective effect, with conflicting evidence. Interestingly, caffeine and tobacco smoking appear to lower the PD risk. Further studies are needed to fully understand the complex interplay between these factors and PD. It's also important to remember that these are just general trends, and individual risk factors will vary depending on a person's unique genetic makeup, medical history, and overall health.

Rapid post-earthquake damage diagnosis of bridges can guide decision-making for emergency response management and recovery. This can be facilitated using digital technologies to remove the barriers of manual post-event inspections. Prior mechanics-based Finite Element (FE) models can be used for post-event response simulation using the measured ground motions at nearby stations; however, the damage assessment outcomes would suffer from uncertainties in structural and soil material properties, input excitations, etc. For instrumented bridges, these uncertainties can be reduced by integrating sensory data with prior models through a model updating approach. This study presents a sequential Bayesian model updating technique, through which a linear/nonlinear FE model, including soil-structure interaction effects, and the foundation input motions are jointly identified from measured acceleration responses. The efficacy of the presented model updating technique is first examined through a numerical verification study. Then, seismic data recorded from the San Rogue Canyon Bridge in California are used for a real-world case study. Comparison between the free-field and the foundation input motions reveals valuable information regarding the soil-structure interaction effects at the bridge site. Moreover, the reasonable agreement between the recorded and estimated bridge responses shows the potentials of the presented model updating technique for real-world applications. The updated FE model is considered as the digital twin of the bridge and can be used to analyze the bridge and monitor the structural response at element, section, and fiber levels to diagnose the location and severity of any potential damage mechanism.

Context: As software industries, adopted different frameworks where Scrum is play a vital role in different software industries. Scrum basis the three main stakeholders i.e. Product Owner, Scrum Master and Development. Where Scrum Master is a very crucial role for any agile project. However, in the past Scrum Master Faces different challenges, which discovered in several studies. However, we need to measure the effectiveness of the Scrum master in Agile Projects, how presently Scrum Master are performing in Pakistani software industries. Objective: The main objective of this research to identify the effectiveness of the Scrum Master in agile projects in Pakistani software industries. Method: Research Method (Qualitative Research) For this purpose, we gathered the facts from Pakistani software industries by using the qualitative method. We conducted a survey from different software industries; almost 12 participants responded the survey as per their best knowledge as well as they agreed for face- to-face interviews. Results: The results indicated that, mostly organization compliance with the Scrum ceremonies. In addition, 65% Scrum Masters has a great effectiveness in any agile project. 21% of Scrum Master generates negative impact in agile project. Conclusion: The main highlights of this research, we have presented the compliance of the Scrum in different software organization. Further, we explore the both positive and negative impact of the Scrum master in Pakistani software organizations.

Abstract: Background: Our goal was to evaluate whether wearing personal protective equipment (PPE) such as an N95, or a surgical mask during the (COVID-19) pandemic had really reduced the cases of influenza in the state of Wisconsin. Methods: Respiratory Virus Surveillance Reports from the Wisconsin Department of Health Services (DHS) and the Centers for Disease Control and Prevention (CDC) were used to compare the rates of Influenza during the seasons of 2018-2019 and 2020-2021. Results: The number of cases, hospitalizations, and mortality rates with Influenza had significantly decreased in the 2020-2021 season compared to the Influenza season of 2018-2019. Discussion: Reducing the burden of influenza illnesses, hospitalizations, and deaths on the health care system is imperative. Wearing masks should be addressed for the most vulnerable.

Electric energy has become essential nowadays not only for the daily life of each of us but also for the economy of different countries. The dissemination of geographic information plays an important role in national development as it facilitates communication between managers, investors, and consumers in this sector. Since the management of electricity network data was previously done in Tunisia based on paper maps and plans, the purpose of this article is to present a case of planning based on GIS, Web, and 3D Web GIS, which would have significant positive consequences on this sector from a technical and financial sides with an improvement in customer satisfaction and the creation of an intelligent electricity network which will be a real decision-making tool. This work draws up an inventory of the network MV (Medium Voltage)/LV (Low Voltage) of the region of Medjez El Bab which routes electricity to the big centers of consumption with access to MV/LV subscribers. The analysis of the network's impedance allowed carrying out different scenarios to optimize performance and obtain more realistic routes. Many thematic maps were produced as part of this project (Slope map, Land use map, map of the MV voltage domains, map of the MV/LV transformer stations power, etc.). A three-dimensional virtual city has been developed to visualize the graphical and attribute data for the study area. A Web and 3D Web GIS applications that allows the publication of the interactive maps on the Web as well as the database information have been developed to offer users the possibility of consulting the produced products by internet. Finally, a website related to the study was developed.

Various kinds of primary metabolisms in plants are modulated through sulfate assimilation that the uptake of this inorganic compound can be regulated via the sulfate transporters, such as sulfotransfer-ases (SOTs), engaged in the sulfur metabolism. In the current study a genome-wide approach has been utilized for recognition and characterization of SOT family genes in the significant nutritional crop po-tato (Solanum tuberosum L.). As a result, 29 StSOT genes were identified in the potato genome, which were mapped onto the nine S. tuberosum chromosomes. The protein motifs structure demonstrated two highly conserved 5' PSB region and 3' PB motif that are essential for sulfotransferase and catalytic ac-tivities. The protein-protein interaction networks also significantly demonstrated an interesting collabo-ration between SOTs and the other genes, such as PRTase, APS-kinase, protein phosphatase and APRs, in sulfur compounds biosynthesis and regulation of the flavonoid and brassinosteroid metabolic pro-cesses, which clearly detected the importance of sulfotransferases for potato proper growth/development and stress dealing. Notably, the homology modeling of StSOT proteins and dock-ing analysis of their ligand-binding sites revealed the presence of some stress-responsive residues, such as proline, glycine, serine and lysine, in their active sites. The expression assay of StSOT genes via the potato RNA-seq data clearly suggested the engagements of these gene family members in plants growth and extension as well as responses to various hormones and biotic/abiotic stimulus circum-stances. Our predictions can be informative for the functional characterization of the SOT genes in po-tato and may the other nutritional crops.

The average age of in-service bridges has increased in recent years in the United States. To address this issue, structural health monitoring and damage identification approaches can be employed to prioritize maintenance/replacement of aging bridges. Among the damage identification and operational health monitoring approaches, finite element (FE) model updating methods can offer a solution to evaluate the mechanics-based characteristics of bridges. However, in a real-world setting, unidentifiability and mutual dependency between model parameters, modeling errors, especially due to boundary conditions, as well as ill-conditioning of updating algorithms can pose challenges to the application of FE model updating methods. To address these challenges, this study presents a two-step FE model updating approach. In the first step, modal-based model updating is used to estimate linear model parameters mainly related to the stiffness of boundary conditions and material properties. In the second step, in order to refine parameter estimation accounting for nonlinear response behavior of the bridge, a time-domain model updating is carried out. In this step, boundary conditions are fixed at their final estimates using modal-based model updating. To prevent the convergence of updating algorithm to local solutions, the initial estimates for nonlinear material properties are selected based on their corresponding final estimates in the modal-based model updating. To validate the applicability of the two-step FE model updating approach, a series of forced-vibration experiments are designed and carried out on a pair of decommissioned and deteriorated prestressed bridge I-girders. After carrying out the two-step FE model updating, the final estimates of concrete compressive strength are shown to provide reasonable assessment of the damage extent in the girders.

We present a finite element model updating technique for soil-structure system identification of the Millikan Library building using the seismic data recorded during the 2002 Yorba Linda earthquake. A detailed finite element (FE) model of the Millikan Library building is developed in OpenSees and updated using a sequential Bayesian estimation approach for joint parameter and input identification. A two-step system identification approach is devised. First, the fixed-base structural model is updated to estimate the structural model parameters (including effective elastic modulus of structural components, distributed floor mass, and Rayleigh damping parameters) and some uncertain components of the foundation-level motion. Then, the identified structural model is used for soil-structure model updating wherein the Rayleigh damping parameters, the stiffness and viscosity of the soil subsystem (modeled using a substructure approach), and the foundation input motions (FIMs) are estimated. The identified model parameters are compared with state-of-practice recommendations. While a specific application is made for the Millikan Library, the present work offers a framework for integrating large-scale FE models with measurement data for model inversion. By utilizing this framework for different civil structures and earthquake records, key structural model parameters can be estimated from the real-world recorded data, which can subsequently be used for assessing and improving, as necessary, state-of-the-art seismic analysis and structural modeling techniques. This paper presents an effort towards using real-world measurements for large-scale FE model updating in the soil and structure, uniform soil time domain for joint parameter and input estimation, and thus paves the way for future applications in system identification, health monitoring and diagnosis of civil structures.

The ever-evolving landscape of technology continually drives the demand for more robust and secure systems. Intrusion Detection and Prevention Systems (IPS) play a pivotal role in safeguarding digital infrastructures. IPS harnesses a blend of cutting-edge technologies, specifically Network-Based, Wireless-Based, and Host-Based Intrusion Detection Systems (IDS), to fortify network security. This multifaceted approach enhances the system's capacity to scrutinize incoming data and network traffic, effectively reducing the risk of intrusion. In the realm of malicious activity detection, IPS employs a diverse array of techniques and mechanisms. Our proposed IPS integrates both anomaly-based and signature-based analysis approaches. In signature-based analysis, intrusions are identified by matching data collected from various activities with pre-defined signatures, employing rule-based methods to detect anomalies effectively. In the anomaly-based analysis approach, the system juxtaposes current activities with a baseline of normal behaviour to flag any deviations. This is achieved through distance-based methods, ensuring a well-rounded approach to threat detection. Our comprehensive prevention system encompasses a suite of security measures, including anti-virus software, Deep Packet Inspection, and Quarantine. These components work in synergy to detect and thwart malicious activities effectively. Even when concealed or hidden, the IPS remains a reliable sentinel, ensuring the integrity of your digital ecosystem. This review delves into the intricate web of terminologies and concepts surrounding Intrusion Detection and Prevention Systems, shedding light on the evolving technology landscape and the critical role IPS plays in bolstering cybersecurity.

The main treatment for pyridoxine nonresponsive cystathionine-β-synthase deficiency is a strict diet. Most centers prescribe low-protein diets based on gram-protein exchanges, and all protein sources are weighed. The purpose of this study is to investigate the effects of a more liberal methionine (Met)-based diet with relaxed consumption of fruits and vegetables on metabolic outcomes and dietary adherence. Ten patients previously on a low-protein diet based on a gram-protein exchange list were enrolled. The natural protein exchange lists were switched to a "Met portion exchange list". Foods containing less than 0.005 g methionine per 100 g of the food were accepted as exchange-free foods. A questionnaire was conducted to assess the effects of the new dietary approach on dietary compliance. The switch to Met portioning had no adverse effects on the control of plasma homocysteine levels in terms of metabolic outcomes. It resulted in a significant reduction in patients' daily betaine dose. The questionnaire results indicated significantly increased dietary compliance, and all patients preferred to continue with this modality. In conclusion, methionine portion-based medical nutrition therapy with relaxed consumption of fruits and vegetables seems to be a good and safe option to achieve good metabolic outcomes and high treatment adherence.

In this article, we calculate the deflection angle of tidal charged black hole (TCBH) in weak field limits. First we obtain the Gaussian optical curvature and then apply the Gauss-Bonnet theorem on it. With the help of Gibbons-Werner method, we are able to calculate the light's deflection angle by TCBH in weak field limits. After calculating the deflection angle of light, we check the graphical behavior of TCBH. Moreover, we further find the light's deflection angle in the presence of plasma medium and also check the graphical behavior in the presence of plasma medium. Moreover, we investigate the shadow of TCBH.For calculating the shadow, we first find the null geodesics around the TCBH and then find its shadow radius. We also obtain TCBH's shadow in the plasma medium. Hence, we discuss the shadow of the TCBH using the $M87^{*}$ parameters announced by the Event Horizon Telescope.

In this paper, we calculate the deflection angle of photon by Casimir wormhole in the weak field limit approximation. First we calculate Gaussian optical curvature with the help of optical spacetime geometry and so we use the Gauss-Bonnet theorem on the Gaussian optical metric. Then we find the deflection angle of photon by Casimir wormhole. Moreover, we calculate the photon's deflection angle in the presence of plasma medium and we also see the graphical nature of deflection angle in both cases. Second, we move towards the shadow of Casimir wormhole. After the observations of Event Horizon Telescope, the study of shadow become very important so that we plot the shapes of shadow of Casimir wormhole, and we calculate the photon geodesic around the Casimir wormhole.

The Internet of Things (IoT) is a concept based on the integration of various devices and methods of communication to exchange information in order to contribute to the improvement of everyday life, business and environment. This paper focuses on the establishment of a modern Internet of Things platform to ensure secure collection, processing and storage of data, under unexpected events. This platform establishes reliable connectivity which enhance system uptime; the key to success when implementing an IoT strategy. For this purpose, we proposed a hybrid approach combining different connectivity technologies to ensure the availability and smooth operation of the system and the prevention of data loss in unforeseen cases.

The objective of this study is to examine a nonparametric estimate , using the kernel approach, of the conditional distribution function of a scalar response variable that is given a random variable whose values take place in a separable real Hilbert space. The observations will be dependent on one another in a quasi-associated fashion. The pointwise practically perfect consistencies with rates of this estimator are established by us under some broad conditions. The study’s major objective is to investigate the convergence rate of the proposed estimator and its application in the convergence rate and asymptotic normality of the hazard function. The asymptotic normality of the developed estimator is established precisely. Simulation studies were conducted to investigate the behavior of the asymptotic property in the context of finite sample data.

Background: Catalase is a vital antioxidant enzyme that dismutates H₂O₂ into water and molecular oxygen. Many protocols have been developed to measure catalase enzyme activity. Spectrophotometric methods are the most common assays that used to assess catalase enzyme activity. Methods: Because the rate-limiting step during catalase enzyme activity depends upon the dissociation of hydrogen peroxide, the developed assay measures the reaction between a hydroquinone/anilinium sulfate/ammonium molybdate reagent and Unreacted Hydrogen Peroxide, which results in the production of a purple, disubstituted quinone compound with a maximum absorbance value at 550 nm. Results: To clarify the precision of the developed method, the coefficients of variation were determined to be 2.6% and 4.7% for within run measurements and between run measurements, respectively. This method returned results that correlated well (r = 0.9982) with the results returned using the peroxovanadate method to assess catalase enzyme activity. Additionally, we examined the use of the newly developed hydroquinone assay to measure catalase enzyme activity in liver and bacterial homogenate samples. Conclusion: These results demonstrated that this assay can be used for scientific research and routine health applications because it is inexpensive, simple, accurate, and rapid. This method is suitable for use in clinical pathology laboratories because it is simple and produces precise and reproducible results.

In this work, we investigate the weak deflection angle of light from exact black hole within the non-linear electrodynamics. First we calculate the Gaussian optical curvature using the optical spacetime geometry. With the help of modern geometrical way popularized by Gibbons and Werner, we examine the deflection angle of light from exact black hole. For this desire, we determine the optical Gaussian curvature and execute the Gauss-Bonnet theorem on optical metric and calculate the leading terms of deflection angle in the weak limit approximation. Furthermore, we likewise study the plasma medium's effect on weak gravitational lensing by exact black hole. Hence we expose the effect of the non-linear electrodynamics on the deflection angle in the weak gravitational field.

Bitumen is produced from non-renewable natural resources, continuously deplete and intrigues researchers to look for alternative binders. Annually, tons of waste engine oil (WEO) and crumb rubber (CR) are discarded unsustainably and pose a significant environmental threat. Adding these industrial waste products to asphalt provides a safe and cost-effective way for their disposal and improves the bitumen's performance in parallel. This study uses various combinations of waste engine oil and crumb rubber with 60/70 penetration grade bitumen to produce a partially synthetic bitumen. Adhesion being one of the critical characteristics of the bituminous binder has been assessed using the bitumen bond strength test along with physical and rheological properties. Results showed that waste engine oil with crumb rubber inclusion increases penetration and decreases the softening point, viscosity, complex modulus, and bonding strength. Additionally, polyphosphoric acid (PPA) in smaller dosages was also incorporated into the optimum percentage of CR + WEO to improve the properties of the binder. The results confirm that binder modification with waste engine oil and crumb rubber can be more effective with PPA. It is concluded that 35% of waste can replace the virgin binder giving a cost-effective and environmentally friendly solution.

Background: In recent years, whole blood parameters and derivatives have been used as prognostic criteria in the course of the disease in various diseases. The prognostic nutritional index (PNI), the systemic immune-inflammation index (SII), the neutrophil-lymphocyte ratio (NLR) have been adapted as an indicator of inflammation and have been widely studied to define the severity of inflammation in some diseases. The aim of this study was to evaluate the relationship between parameters such as NLR, SII, PNI, controlling nutritional status (CONUT) score, nutritional risk index (NRI) and with immunonutrition status and disease activity in patients with ischemic stroke of small vessel, large vessel and other etiologies. Methods: We retrospectively evaluated the records of 1454 consecutive ischemic stroke patients hospitalized in the emergency department of Gaziosmanpasa Education and Research Hospital from 2019 to 2023. Results: Of the 1350 SVO patients included in the study, 58.8% had small vessel, 29.3% had large vessel and 11.9% had other etiologies. There was a significant difference between the 3 etiology groups for PNI and CONUT. The median PNI was 47.03 (41.33-52.85) in the other etiology group, 35.29 (33.69-37.25) in the small vessel group, and 34.11 (30.23-36.87) in the large vessel group. The CONUT median was 5(5-6) in the small vessel group, 5(4-6) in the large vessel group and 4(4-4) in the other etiology group. In addition, CONUT and PNI were also found to be independent risk factors for death. A negative significant correlation was observed between PNI and NLR (r:-0.692), SII (r:-0.591), CONUT (r:-0.685). Significant correlations were observed between CONUT and NLR (r:0.402), SII (r:0.312). Conclusion: PNI and SII were significantly associated with disease activity. PNI, CONUT and NRI as a more accurate prognostic indicator of nutritional status in patients with ischemic stroke of small vessel, large vessel and other etiologies. NLR and SII may be important predictive markers in the course and prognosis of stroke.

Overlap coefficient (OVL) represents the proportion of overlap between two probability distributions, as a measure of the similarity between them. In this paper, we define a new overlap coefficient Λ based on KullbackLeibler divergence and compare its performance to three known overlap coefficients, namely Matusia’s Measure ρ, Morisita’s Measure λ, Weitzman’s Measure δ. We study their properties, relations between them, and give approximate expressions for the biases and the variances.

Organophilic nano clay is the composition of mostly clay and organic molecules designed to improve various materials' physical and chemical properties. Permanent deformation in asphalt pavements is primarily the result of inadequate compaction, excessive loading, and high temperatures. Rutting can result in aquaplaning, leading to accidents and costly maintenance and rehabilitation works that drain the economy. Such behavior of asphalt pavements may be attributable to poor selection of aggregate, asphalt binder, or substandard asphalt binders. This study used different percentages of organophilic nano clay ranging from 3.0% - 5.0% with two penetration grade bitumen, i.e., N.R.L 60-70 &amp; N.R.L 80-100. Adding organophilic nano clay to asphalt binder significantly reduced the rutting potential under cyclic loading at high temperatures (55 °C). Ten modified formulations and two virgin bitumen specimens were prepared. The modified binders' viscosity and rutting were tested using the Rotational Viscometer and Wheel Tracker Test (W.T.T.), respectively. The results were analyzed using software for Statistical Analysis. It was recorded that organophilic nano clay-modified bitumen significantly affected rutting to interpret the results. The results indicated that rutting decreased and viscosity increased in all nano clay-modified bitumen samples, with a 4.5% O.N.C modified binder showing the most significant improvement.

This paper explores the effect of climate change on the regression of the Argan tree (Argania spinosa L. Skeels) woodland, focusing on the Argan Biosphere Reserve and especially in the Souss plain (Western Morocco). Rainfall and temperature data of four sites within the Argan Biosphere Reserve were analyzed over the last 60 years to assess any climatic change. Regression curves applied to the dataset showed an important decrease in rainfall (18 to 26 %) in the four locations as well as an increase in temperature (1 to 2 °C). These changes may have a detrimental effect on the Argan woodland although human factors have been reported to be the main factor of its regression. It can therefore be concluded that the reduction in rainfall and the increase in temperature should now be considered as factors of Argan woodland regression.

Every firm is devoted to polishing and fine-tuning its maintenance strategy. More exactly, when we develop robust and efficient preventive and conditional maintenance approaches, our objective is to combine performance and robustness to increase maintenance decision-making. This, in turn, leads to a reduction in system failures and a subsequent drop in related expenses. This impulse drives the origin of this essay: to provide fresh criteria that allow us to improve and optimize maintenance techniques. Furthermore, our study has been realistically utilized via the deployment of condition-based maintenance (CBM) techniques, which are commonly regarded as a critical lever that allows firms to gain a competitive advantage in the context of the fourth industrial revolution. Combining both perfect and imperfect maintenance actions into CBM strategies appears to be an effective technique to obtain high economic performance and robustness in the maintenance strategies of the companies. Following this idea, we propose and optimize in this paper a set of criteria enabling the combined assessment of the mean economic performance and the resilience of various kinds of maintenance techniques. The advantage of the proposed criterion is that it adapts to different types of maintenance strategies and provides access to a simple and relevant evaluation model. Thanks to this new criterion, we will be able to choose the better maintenance strategies that have more performance and robustness between these strategies for a system with more or less stable behavior. The Monte Carlo Method is incorporated into the comparative assessment of maintenance methods, adding a layer to the evaluation of the performance and robustness of each adaptation in decision-making.

COVID-19 pandemic has caused a large-scale havoc in almost every country across the globe, putting major challenges for the healthcare system in many parts of the world. Several of the laboratories are running in the race with undying efforts for developing potential vaccine, drugs or therapeutics to treat or prevent the infection. However, with the limited time window and high rate of infection, the task is very big for humanity to find a cure. With hundreds of genomic data of SARS-CoV-2 virus isolates from humans are being submitted almost every day, it is coming into knowledge that virus is mutating, slower in countries with sporadic cases, but higher in countries experiencing large outbreak. These types of mutations in virus may bring challenges in vaccine or therapeutic development for use in each and every country, as each hotspot region may have their own pattern of mutations in virus with ongoing outbreak. In our current study, we retrieved non-synonymous mutation data of around 12,225 SARS-CoV-2 virus samples isolated from humans globally, and discovered all mutations that are collectively happening in antibody epitope regions of the virus country-wise. We found a few numbers of epitope regions in SARS-CoV-2 that are highly conserved collectively in all variants and may be used for epitope-based vaccine development for whole world. We also found epitope regions that are conserved collectively in SARS-CoV-2 variants country-wise and can be used for customized epitope-based vaccine development in each different country.

Election Algorithm (EA) is a powerful metaheuristics model motivated by phenomena of the socio-political mechanism of the presidential election conducted in many countries. EA is selected as a topic of discussion due to its capability and robustness to carry out complex problems in the random-2SAT logic program. This paper utilizes a hybridized EA assimilated with the Hopfield neural network (HNN) in carrying out random logic program (HNN-R2SATEA). The efficiency of the proposed method was compared with the existing traditional exhaustive search (HNN-R2SATES) model and the recently introduced HNN-R2SATICA model. From the result obtained, clearly proven that based on our proposed hybrid model outperformed other existing model based on the Global Minima Ratio (ZM), Mean Absolute Error (MAE), Bayesian Information Criterion (BIC) and Execution Time (ET). The expected outcome portrays that the EA algorithm outperformed the other two algorithms in doing random-kSAT logic program. The results proved the robustness, effectiveness, and compatibility of the HNN-R2SATEA model.

Being a great source of protein, B-vitamins and minerals, meat and fish are staple foods in many cultures. However, cooking at high temperatures can produce chemicals associated with an increased risk of developing cancer. This review investigates the possible carcinogenic activity of chemicals formed during the cooking of meat and fish including heterocyclic amines (HCAs), polycyclic aromatic hydrocarbons (PAHs), and advanced glycation end products (AGEs). High-temperature cooking methods for meat, including grilling or frying, result in the formation of HCAs. Meat that has been smoked, grilled, or cooked over an open flame produces PAHs whereas, dry heat methods including roasting, grilling, and frying results in formation of AGEs. In vitro studies have shown that these compounds can damage DNA, cause mutations, and promote the growth of cancer cells. Research shows that thoroughly cooked meat increases the risk of cancer, particularly colorectal, pancreatic, and prostate cancer. Alternative cooking techniques, marinades, and incorporating fruits and vegetables can help to mitigate this risk. For determining the efficacy of these measures, additional studies are required. For the purpose of lowering the potential carcinogenic activity of chemicals formed during the cooking of meat and fish, mitigation techniques must be understood and put into practice. Cancer can be avoided by informing people about the dangers of eating meat and fish that have been cooked at high temperatures and by encouraging better diets and cooking styles. In order to lessen the possible health concerns related to the eating of meat and fish, further studies are required.

As urban populations and transport demand expand, Pakistani metropolitan centers face traffic congestion and environmental challenges. This research aims to assess carpooling (CP) to alleviate traffic congestion, fuel demand, and pollution. This study was conducted in Islamabad, a fast-growing city with a high percentage of personal cars in Pakistan, to assess the travelers’ perceptions, and public acceptance of CP and determine the effects on traffic congestion, fuel consumption, and CO2 emissions. The investigation of travelers' perceptions towards CP was conducted through a stated preference questionnaire survey. A total of 700 responses from one million population of Islamabad were collected as per Sloven's Formula. SPSS and Smart PLS software were used for data analysis. Various factors influencing peoples’ travel perceptions, mode choice, and tendency to carpool, were categorized to evaluate the relationship between travelers’ perception and the tendency to carpool in the presence of mode choice as a mediating variable. Confirmatory factor analysis was conducted in SMART PLS to refine the number of scale items for each variable. One-way ANOVA, step-wise and mediated multiple regression analysis was conducted in SPSS to check the direct and mediating relationship between different variables. Moreover, the probability of reducing traffic congestion and assessing fuel reduction resulting from CP was also analyzed. The findings imply that travelers’ mode choice acts as a mediator between the relationship between travelers’ perception and tendency to carpool. Furthermore, results predicted that CP might reduce 0.25 million cars on the road, about 33.6% of the total private vehicles. Thereby, saving up to 546,810 barrels per year, about 3.42% of Pakistan's total petrol consumption. The findings of this study could be helpful for transport planners, environmentalists, and policymakers to implement carpool systems. Thus, reducing traffic congestion and harmful CO2 emissions and maintaining a sustainable environment.

Gesture recognition has always been a technique to decrease the distance between the physical and the digital world. In this work, we introduce an Arduino based vehicle system which no longer require manual controlling of the cars. The proposed work is achieved by utilizing the Arduino microcontroller, accelerometer, RF sender/receiver, and Bluetooth. Two main contributions are presented in this work. Firstly, we show that the car can be controlled with hand-gestures according to the movement and position of the hand. Secondly, the proposed car system is further extended to be controlled by an android based mobile application having different modes (e.g., touch buttons mode, voice recognition mode). In addition, an automatic obstacle detection system is introduced to improve the safety measurements to avoid any hazards. The proposed systems are designed at lab-scale prototype to experimentally validate the efficiency, accuracy, and affordability of the systems. We remark that the proposed systems can be implemented under real conditions at large-scale in the future that will be useful in automobiles and robotics applications.

In recent years, the focus of disease resistance and susceptibility studies in cattle have been on determining patterns in the innate immune response of key proteins, such as Toll-like receptors (TLR). In the bovine genome, there are 10 TLR family members and, of these, TLR2, TLR4 and TLR6 are specialized in recognition of bacterial ligands. Indigenous cattle breeds of Anatolia have been reported to show fewer signs of clinical bacterial infections, such as bovine tuberculosis and mastitis, and it is hypothesized that this might be due to a less stringent genetic selection during breeding. In contrast, Holstein-Friesian cattle have been under strong selection for milk production, which may have resulted in greater susceptibility to diseases. To test this hypothesis, we have compared the TLR2, TLR4 and TLR6 genes of Anatolian Black (AB), East Anatolian Red (EAR), South Anatolian Red (SAR), Turkish Grey (TG), and Holstein (HOL) cattle using Next Generation Sequencing. The SAR breed had the most variations overall, followed by EAR, AB, TG and HOL. TG had the most variations for TLR2 whereas SAR had the most variations in TLR4 and TLR6. We compared these variants with those associated with disease and susceptibility traits. We used exon variants to construct haplotypes, investigated shared haplotypes within breeds and determined candidate haplotypes for disease resistance phenotype in Anatolian cattle breeds.

Identifying ambient noise-based (ANb) signatures of streams can help in the estimation of their erosive potential (EP) that promotes reverie landslides and soil losses in the fluvial valleys. This is particularly imperative on flooding or rainy days, leading to stronger erosion-prone conditions (colluvium and boulders) of the valley beds inferred from georadar attribute analysis. Developing such research direction can benefit the local communities, as is the case with the Cerrado region of Brazil, where these phenomena have high destructive potential with social, economic, and climatic implications. For the present study, a seasonal stream in the Federal District of Brazil was investigated by ANb monitoring supported by Ground Penetration Radar (GPR) for site characterization. The ANb monitoring was conducted (at a safe distance) with a seismometer over several durations of dry and rainy conditions. The power spectral density (PSDs) was computed as a function of several variables, including weather conditions (rainfall, wind speed, and pressure), time-frequency spectrograms, and ambient noise displacement root mean square (RMS). This analysis also considered the single station horizontal-to-vertical spectral ratio (HVSR), where rain, wind, pressure, river flow and anthropogenic signatures were evident (at selective frequency ranges). Multi-peaks that emerged on the HVSR curve were further analyzed to identify amplitude and frequency changes, and the three peaks shift on average to a lower position during the rainy period. The GPR amplitude and waveform variation features were attributed to the stratigraphy (i.e., the boundary between valid and invalid regions and coherence value) of the floodplain and regions susceptible to erosion (erosion-prone lithological spots). This approach provides the basis for non-destructive monitoring tools enabling the detection of 'seismic signatures' and weak spots of the fluvial channels for improving environmental management.

Cell migration crucial contributor to metastasis, a critical process associated with the mortality of cancer patients. The initiation of metastasis is triggered by epithelial-mesenchymal transition (EMT), along with the changes of the expression of EMT marker proteins. Inflammation plays a significant role in carcinogenesis and metastasis. Lipopolysaccharide (LPS), a typical inflammatory agent, promoted the generation of superoxide through the activation of p-Tyr42 RhoA, Rho-dependent kinase 2 (ROCK2) and the phosphorylation of p47phox. In addition, p-Tyr42 RhoA activated phospholipase D1 (PLD1), with PLD1 and phosphatidic acid (PA) being involved in superoxide production. PA also regulated the expression of EMT maker proteins. Consequently, we have identified MHY9 (Miosin IIA, NMIIA) as a PA-binding protein in response to LPS. MYH9 also contributed cell migration and the alteration of the expression of EMT marker proteins. P-Tyr42 RhoA, PLD1 and MYH9 associated to form a complex, which was distributed in both the cytosol and nucleus. In addition, we have found that p-Tyr42 RhoA and PLD1 associated with the ZEB1 promoter. Taken together, we propose that p-Tyr42 RhoA and PLD1, responsible for producing PA, and PA-bound MYH9 are involved in the regulation of ZEB1 expression, thereby promoting cell migration.

Enhanced oil recovery (EOR) refers to the various techniques used to increase the amount of crude oil that can be extracted from an oil field. These techniques are used after the primary and secondary recovery methods have been depleted. There are three main types of EOR: thermal, gas injection, and chemical. EOR techniques can be expensive and complex, but they can help to recover additional oil that would otherwise be left in the reservoir. EOR can also extend the life of an oil field and increase the overall production from a given field. The parameters affecting oil recovery are a major concern in EOR systems, and these parameters need more consideration with the factors affecting them. In this study, the influence of permeability variations on fluid flow in a sandstone reservoir was explored, as well as an up-to-date description of three states of EOR with thorough explanations of the methods utilized and the mechanisms driving their oil recovery application. The difficulties encountered in the use of the different standard EOR Mechanisms were noted, and solutions to these difficulties were proposed. Furthermore, the contemporary trend of adding nanotechnology and its synergistic effects on the stability and efficiency of traditional chemicals for EOR were examined and analysed. Finally, laboratory findings and field initiatives were discussed. The review went into detail about the transport of nanoparticles across reservoirs, as well as the evaluation of EOR, mobility ratio, and fluid displacement efficiency. This review provides thorough information on the uses of improved oil recovery mechanisms for sustainable energy production.

This study addresses the central question that how can a precise measurement of the gluon Parton Distribution Function (PDF) be attained, thereby enhancing our understanding of the intricate quark-gluon composition within nucleons? Through a dual approach involving Quantum Chromodynamics (QCD) and high-energy particle collisions, the research combines computational tools and experimental techniques, focusing on protons and neutrons. Scattering experiments and advanced detectors are utilized to probe nucleon structure. Theoretical frameworks like QCD equations and the Momentum Sum Rule investigate Parton Distribution Functions at specific momentum fractions and energy scales. The primary goal is to achieve an accurate measurement of the gluon PDF, crucial for unraveling strong force complexities and internal nucleon dynamics. The study's theoretical plots and equations illustrate hypothetical behaviors of gluon distribution, quark distribution, and splitting functions, contributing to a deeper understanding of fundamental particles.

This study explores the dynamics of liquid holdup in a lab-scale co-current two-phase upflow moving packed bed reactor, specifically examining how superficial gas velocity influences the line average external liquid holdup at a fixed superficial liquid velocity. Utilizing Gamma-ray Densitometry (GRD) for precise measurements, this research extends to determining line average internal porosity within catalyst particles and the overall external bed porosity. Conducted with an air-water system within a bed packed with 3 mm extrudate porous particles, the study presents a novel methodology to calculate liquid holdup, grounded in Beer–Lambert's law. Findings reveal a decrease in liquid holdup corresponding with increased superficial gas velocity across axial and radial locations, with a notable transition from bubbly to pulse flow regime at a critical velocity of 3.8 cm/sec. Additionally, the lower sections of the packed bed exhibited higher external liquid holdup compared to the middle sections at varied gas velocities. The liquid holdup distribution appeared uniform at lower flow rates, whereas higher flow rates favored the middle sections.

Over the past decade, Deep Learning (DL) had been applied in a large number of optical sensors’ applications. DL algorithms can improve the accuracy and reduce the noise level in optical sensors. Optical sensors are considered as promise technology for the modern intelligent sensing platforms. These sensors are widely used to process monitoring, quality prediction, pollution, defense, security and many other applications. However, they suffer major challenges such as the large generated data and low processing speed for that data and moreover the much cost of these sensor. These challenges can be mitigated by integrating deep learning system with the optical sensor technologies. This paper presents recent studies that integrate DL algorithms with optical sensors applications. This paper also highlights several of DL algorithms directions that promise a considerable impact on use for optical sensor applications. Moreover, this study provides new directions for the future related research development.

Although carbon (C) efflux from soils treated with organic wastes was widely covered in temperate and cold regions, still such data is not sufficient from arid and semi-arid regions. Saudi Arabia produces more than 335,000 tons/year of cow manure (CM), this CM either left as raw manure or being composted. The application of high C/N amendments is expected to increase soil organic carbon and reduce CO₂ fluxes. A 90-day incubation experiment was conducted to study CO₂ efflux, organic C microbial biomass C, available NH₄+and NO₃-when added to agricultural soil. Six manure types were added: cow manure, cow manure compost, cow manure biochar, cow manure stripped ammonia at pH 12 with a temperature of 95oC, cow manure stripped ammonia at pH 9 with a temperature of 95oC and control. The application of CM resulted in a considerable increase in soil available nitrogen, CO₂ efflux compared to other treatments. Cow manure biochar showed the lowest CO₂ efflux. Cumulative CO₂ effluxes of cow manure effluents were lower than CM this possibly due to the relatively high C:N ratio of manure effluent. The content of, P, Fe, Cu, Zn and Mn were decreased as incubation time increased. microbial biomass C of cow manure stripped ammonia at pH 12 with a temperature of 95oC were increased at 7 and 60 days illustrating to temperature effect on the decomposing of manure materials.

Multiple sclerosis (MS) is an immune-mediated, chronic inflammatory disease of the central nervous system (CNS), characterized by demyelination, axonal degeneration, and cognitive impairment. It also has an important impact on the quality of life of patients and their family members. An estimated 2,500,000 people in the world have multiple sclerosis. Neurophysiological parameters, like sensitivity to demyelination and the strength of excitatory and inhibitory synaptic interactions in the cerebral cortex, can be identified through transcranial magnetic stimulation (TMS) in patients affected by multiple sclerosis (MS). These parameters can be valid and objective parameters that can be correlated with the progression of MS, and can provide reliable indices for the severity of illness and the efficacy of drugs used to treat it. The discovery of specific and detailed neurophysiological parameters as surrogate end points for disease activity could represent an important step in clinical trials. Changes in cortical connectivity have already been demonstrated in MS, but in clinical practice, other measures are usually used to evaluate disease activity. We speculate that TMS may be more effective in identifying disease progression that leads to long-term disability, compared to standard surrogate markers, due to the fact that it represents a direct measure of synaptic transmission(s) in MS.

The potential impact of a specific physical activity program on biomechanical gait parameters and neuromuscular strategies around the ankle joint in older adults with sarcopenic obesity (SO) remains largely unexplored. The objective of this study was to investigate the effectiveness of a 24-week Posture, Strengthening, and Motricity (PSM) program in improving neuromuscular strategies and biomechanical gait parameters in older adults with SO. 40 Participants were randomly assigned to either the trained group (TG) and the control group (CG). Only the TG received the PSM program. Standardized evaluations were performed before and after the intervention, including walking tests on an instrumented gait analysis treadmill to evaluate biomechanical gait parameters and EMG activity of ankle muscles. After the PSM program, TG exhibited an increase in comfortable walking speed (+80%, p<0.001) and step length (+38%, p<0.05). Moreover, TG demonstrated a reduction in CoP velocity (-26%, p<0.01). These gait modifications were associated with a decreased muscle activity during the different gait phases (p<0.05). The PSM program effectively improved gait, and neuromuscular capacities in older adults with SO. Notably, Results sheds light on the remarkable trainability of neuromuscular capacities in older adults with SO, despite the adverse effects of aging and obesity.

Antioxidants reduce arterial stiffness but the effects previously reported are weak. The present study evaluated the effects of 2 weeks of therapy with a combination of antioxidants (l-cysteine, thiamine, pyridoxine and ascorbic acid) compared to placebo on stiffness index (SI) a measure of arterial stiffness that is strongly correlated with central pulse wave velocity (PWV), using a Pulse Trace recorder in a diverse group of 78 volunteers. SI fell by 1.7 m/sec relative to placebo (95% confidence intervals 0.6 to 2.7 m/sec), a reduction of 19% (95% confidence intervals 9% to 31%). The Glass effect size was 1.4, indicating a very strong treatment effect which was substantially greater than found in previous studies of the effects of antioxidant therapy on arterial stiffness. The magnitude of reduction in SI was positively correlated with increasing age (r = 0.362 P = 0.02). The change in RI, a measure of compliance of small to medium size arteries, did not differ between the antioxidant and placebo groups The combination of antioxidants studied reduced PWV to a much greater extent than reported for other antioxidants. This combination may be of value in the treatment of cardiovascular disease.

There are not many exhaustive works emphasizing the amount of genetic diversity among the strawberry tree (Arbutus unedo L.) genotypes in Morocco. This work aims to assess the biochemical composition of strawberry tree fruits, as well as to establish the variation of this composition among them. In this study, total phenols, total flavonoids, condensed and hydrolyzable tannins, total anthocyanins and free radical scavenging activity through ABTS were investigated in strawberry tree fruits. Furthermore, qualitative and quantitative analyses of individual phenolic compounds by high-performance liquid chromatography (HPLC) were carried out. Color parameters such as lightness (L*), Chroma (c*) and hue angle (h°) were also investigated. All studied variables showed highly significant differences among all samples with the exception of hydrolyzable tannins and chromatic coordinates. Total phenolics varied from 22.63 ± 1.74 to 39.06 ± 2.44 mg GAE/g dry wt, total flavonoids varied from 3.30 ± 0.60 to 8.62 ± 1.10 mg RE/g dry wt and total anthocyanins ranged between 0.12 ± 0.06 and 0.66 ± 0.15 mg cya-3-glu/100g dry wt. In addition, condensed and hydrolyzable tannins amounts were in the range of 10.41 ± 1.07 - 16.08 ± 1.50 mg TAE/g dry wt and 4.08 ± 2.43 - 6.34 ± 3.47 respectively. Moreover, the IC50 value (ABTS) ranged between 1.75 and 19.58 mg AAE/g dry wt. 17 phenolic compounds were detected in strawberry tree fruits. Gallocatechol and catechin were the most abundant phenolic compound. Matrix of correlations revealed significant positive and negative correlations among variables particularly c*, a* and b*. Principal component analysis showed that the first three components formed than 68% of the total inertia. The following variables gallic acid, protocatechuic, gallocatechin, gallic acid derivative, chlorogenic acid, syringic acid, ellagic acid derivative II, L* and h* were the most involved in the total variance explained. Hierarchical clustering classified samples into one main cluster, with a single branch. The results highlight a high biochemical diversity within studied strawberry genotypes, which is probably more genetically related

We conducted a comparative study on the development of two synthetic methods. The solvent-free synthesis is a green chemistry method developed in a bid to ameliorate environmental adverse effects of the conventional solvent-based synthesis. The synthesis of novel dichloro and polymethoxy p-nitrophenylhydrazones through solvent free technique gave moderate to high yields which were however lower than those of the solvent-based method. The established solvent-free approach has several benefits, including universality and simplicity of the approach, catalyst-free conditions, non-use of an organic solvent, quick reaction time, fast and efficient workup, and un-solvated pure products in moderate to high yields.

.Background: Neither radiological phenotypic characteristics nor reconstruction CT scan to study the cranial contour in children with the so called the idiopathic type of West syndrome has been implemented to reach the etiology understanding. Material and Methods: The basic diagnostic measures and the traditional antiepileptic treatments have been applied to these children in accordance with the conventional protocol of investigations and treatment for children with West syndrome. Boys from three unrelated families were given the diagnosis of idiopathic type of West syndrome. Three boys aged 6,7,9 and three parents (age range of 28-41 year) were included in this study. These children and their parents were referred to our orthopedic departments because of variable skeletal deformities. All showed the history of intellectual disabilities, cryptogenic epileptic spasms and fragmented hypsarrhythmia. Recently, variable forms skeletal deformities of flat foot, torticollis and early onset osteoarthritis. We performed detailed clinical and radiological phenotypic characterization of every affected child, siblings and parents. All affected children underwent whole exome sequence analysis Results: The craniofacial phenotype of all children revealed apparent disruption of development of the cranial bones. Palpation of the skull bones showed unusual palpable boney ridges along different sutural locations. A-7-year-old child showed abnormal bulging over the sagittal suture associated with bilateral boney ridges over the sequamosal sutures. Examining his parents, we noticed a similar skull radiographic abnormality in his mother radiographs. A-10-year-old boy showed an extremely narrow frontal area, facial asymmetry and a well palpable ridge over the lambdoid sutures. 3D reconstruction CT scan confirmed the diagnosis of early closure . His mother showed typical radiographic skull phenotype with a history of postadulthood scoliosis. A- 12-year-old boy showed brachycephaly. Investigating his parents revealed a brachycephalic mother with border line intellegence. We affirm that the pattern of inheritance in the three boys was compatible with X-linked recessive pattern of inheritance . Whole exome sequencing showed non definite phenotype/genotype correlation. Conclusion: The aim of this study was fivefold. First, to refute the common usage of the term idiopathic and we affirm that our findings are Novel. Second, it could be possible that West syndrome is a symptom complex rather than a separate diagnostic entity. Third, to further detect the genetic carrier , we explored the connection between the cranial bones in the children with West syndrome with what is seen in parents.. Fourth, the differences in cranial bones abnormalities among every child and another seems to be heterogeneous. Fifth, it seems that the progressive deceleration in the development of this group of children is highly connected to the progressive closure of the cranial sutures.

The commercial cultivation of microalgae began in the 1960s and Chlorella was one of the first target organisms. The species has long been considered a potential source of renewable energy, an alternative for phytoremediation, and more recently, as a growth and immune stimulant. However, Chlorella vulgaris, which is one of the most studied microalga, has never been comprehensively profiled chemically. In the present study, comprehensive profiling of the Chlorella vulgaris metabolome grown under normal culture conditions was carried out, employing tandem LC-MS/MS to profile the ethanolic extract and GC-MS for fatty acid analysis. The fatty acid profile of C. vulgaris was shown to be rich in omega-6, -7, -9, and -13 fatty acids, with omega-6 being the highest, representing more than sixty percent (>60%) of the total fatty acids. This is a clear indication that this species of Chlorella could serve as a good source of nutrition when incorporated in diets. The profile also showed that the main fatty acid composition was that of C₁₆-C₁₈ (>92%), suggesting that it might be a potential candidate for biodiesel production. LC-MS/MS analysis revealed carotenoid constituents comprising violaxanthin, neoxanthin, lutein, β-carotene, vulgaxanthin I, astaxanthin, and antheraxanthin, along with other pigments such as the chlorophylls. In addition to these, amino acids, vitamins, and simple sugars were also profiled, and through mass spectrometry-based molecular networking, 48 phospholipids were putatively identified.

Google play store allow the user to download a mobile application (app) and user get inspired by the rating and reviews of the mobile app. A recent study analyzes that user preferences, user opinion for improvement, user sentiment about particular feature and detail with descriptions of experiences are very useful for an application developer. However, many application reviews are very large and difficult to process manually. Star rating is given of the whole application and the developer cannot analyze the single feature. In this research, we have scrapped 282,231 user reviews through different data scraping techniques. We have applied the text classification on these user reviews. We have applied different algorithms and find the precision, accuracy, F1 score and recall. In evaluated results, we have to also find the best algorithm.

The diffusion of molecules in aqueous solutions in the domain of membrane technology is very critical in the efficiency of chemical engineering and purification processes. In this study, the diffusion in high and low concentration regions is simulated with finite difference method (FDM), and then the results of numerical computations are coupled with adaptive network-based fuzzy inference system (ANFIS) and bilayered neural network method (BNNM). Machine learning approach can individually predict diffusion phenomena across the domain based on understanding of the machine instead of the discretization of an ordinary differential equation (ODE). The findings of the machine learning method are in good agreement with those of FDM at different times of the simulation. In addition to numerical computation, the error of the system is computed for different iterations. The results show that by increasing the number of iterations and training datasets, all errors reduce significantly for both training and testing. BNN method is also used to train the prediction process of diffusion for a more accurate comparison. This technique is similar to ANFIS method in terms of prediction capability. According to the findings, ANFIS approach predicts diffusion slightly better than BNN method. In this regard, ANFIS technique produces R>0.99 while BNN method produces R around 0.98. Both machine learning methods are accurate enough to predict diffusion throughout the domain for different time steps. The computational time for both algorithms is less than that of FDM method to predict low and high concentrations in the domain. Besides, based on the results, artificial intelligence (AI) can find the relationship between inputs and outputs and determine which input has the main influence on the output in this study to optimize the process. As such, future studies can be focused on AI and other methods for faster prediction and optimization processes.

Since the advent of the Internet, there has been a significant shift from wired to wireless communication between devices. The volume of data transmitted has surged, primarily driven by the exponential growth of network services, Internet of Things (IoT) devices, and online users. This trend became especially pronounced with the onset of the COVID-19 pandemic, as the Internet's role and significance expanded dramatically. People began to spend more time online, engaging in activities like e-learning, remote work, and online shopping. Concurrently, concerns about the security of wireless communication channels have escalated. As more data is stored and transmitted over the Internet, cybercriminals are actively seeking unauthorized access to it to further their malicious objectives. Through a comprehensive literature review in the realm of wireless network security and privacy, it has become evident that several factors render these networks susceptible to vulnerabilities. The aim of this paper is to shed light on the major and common security and privacy challenges faced by existing wireless networks. Additionally, it seeks to demonstrate the array of techniques available to mitigate these issues. Ultimately, this paper will culminate in an in-depth analysis of cybersecurity measures to address the issues in wireless networks.

Monkeypox virus belongs to the Orthopoxvirus genus, which belongs to the Poxviridae family. The Monkeypox virus is responsible to cause monkeypox, a developing zoonotic disease that has been identified as the most common orthopoxvirus infection in humans in the post-eradication era of smallpox. The virus can be transmitted by a variety of animals, including monkeys and rodents as well as person-to-person. Monkeypox has a clinical presentation that is quite similar to smallpox but mortality is low, in that the febrile prodrome is followed by a period of skin eruption. Monkeypox cases have extended outside the forests of central Africa, where they were first discovered, to other regions of the globe, where they have been imported. This pattern of transmission is most likely related to a global reduction in orthopoxvirus immunity following the discontinuation of smallpox vaccination in 1980, when smallpox was proclaimed eliminated. As a result, monkeypox might become the very common orthopoxvirus infection that affect humans. The emergence of epidemics outside of Africa emphasizes the disease's global significance. Increased monitoring and identification of monkeypox cases are critical tools for gaining a better knowledge of the disease's ever-changing epidemiology.

A multicenter, prospective cohort study conducted in 5 physiotherapy clinics in the UAE from January 2021 to March 2023 to assess coronal lumbar spine radiographic parameters as a predictor of conservative therapy outcomes in patients suffering from low back and leg pain due to lumbar disc herniation (HNP). Ninety patients (mean age 44 yrs., 54% male) with lumbar HNP underwent conservative therapy. All participants received lumbar spine MRI and radiography to assess spine alignment. Interventions included specific exercises, diathermy, traction, education, a home-based exercise pro-gram, and medications. Detailed demographic data was collected. Follow-up was 6-months after discharge. A successful outcome was based on a minimum of the following four outcomes: (1) reduction of pain by 17.5 points (0–100 NRS); (2) fatigue reduction by 7.5 points; (3) distress reduction by 5 points; and (4) interference reduction by 9.5 points. At 6-month follow-up it was found that patient age, education, and radio-graphic determined lumbosacral angle measures significantly affected the odds of a successful outcome. Increasing age 1-year significantly decreased the odds of success of improving pain, fatigue (OR = 0.85, p = 0.016) and interference scores (OR = 0.89, p = 0.042) by 15%, 15%, and 11% respectively. Lower education significantly increased the odds of success for improving pain, fatigue, and interference by 26.18, 26.18, and 7.5 (p = 0.006, = 0.006, and = 0.029 respectively). Increasing (worsening) the radiographic lumbosacral angle by each 1° significantly reduced the odds of success for improving pain, fatigue, distress, and interference by 3.52, 3.52, 27.99, and 2.55, respectively (p < 0.001, < 0.001, = 0.003, = 0.001). Our findings indicate that younger age, less education, and better coronal radiological lumbar spine alignment all had a substantial impact on the likelihood of success of 6-month outcomes in patients suffering from chronic lower back pain and radiculopathy due to HNP.

Abstract: Autophagy has a dual role in gliomagenesis in a microRNA-modulated environment. We investigated the potential relevance of autophagy in glioma development and survival by exploring the association of autophagy-associated genes and microRNAs in low- and high-grade gliomas. Real-time PCR (qPCR) was used to determine the expression of genes and microRNAs in 50 fresh glioma tissues while Formalin-fixed paraf-fin-embedded tissues of the same patients were used for immunohistochemistry. The Mann-Whitney U-test test, Spearman correlation test, and Kaplan-Meier survival analysis were performed to evaluate the expression, association, and overall survival in patients respectively. The expression of LC3, AKT, and miR-21 was increased in high-grade glioma compared to low-grade glioma while ULK2 expression was decreased in high-grade glioma. A strong positive correlation was observed for ULK2 with UVRAG, PTEN, miR-7, and miR-100, while the moderate correlation with mTOR, Beclin1, miR-30, miR-204, miR-374, miR-21 and miR-126 in low-grade glioma, while a moderate positive correlation between ULK2 and PI3K, PTEN, ULK1, VPS34, mTOR, Beclin1, UVRAG, AKT and miR-374, and between AKT and ULK1, VPS34, UVRAG, and miR-7 in high-grade gliomas. The low ULK2 and LC3 expression group was significantly associated with better overall survival in gliomas while miR-21 overexpression showed a poor prognosis in glioma patients. Therefore, miR-21, ULK2, and LC3 may serve as prognostic biomarkers for survival outcomes in glioblastoma.

A 2-year prospective study carried out on ventilator-associated pneumonia (VAP) patients in the intensive care unit at King Khalid hospital, Hail, Kingdom of Saudi Arabia (KSA), revealed a high prevalence of extremely drug-resistant (XDR) Acinetobacter baumannii. About a 9% increase in the incidence rate of A. baumannii has occurred in the VAP patients between 2019 and 2020 (21.4% to 30.7%). In 2019 the isolates were positive for IMP-1 and VIM-2 (31.1% and 25.7%, respectively) as detected by PCR. In comparison, a higher proportion of isolates produced NDM-1 in 2020. Here, we observed a high resistant proportion of ICU isolates towards the most common antibiotics in use. Colistin sensitivity dropped to 91.4% in the year 2020 as compared to 2019 (100%). Thus, the finding of this study has a highly significant clinical implementation in the clinical management strategies for VAP patients. Furthermore, strict implementation of antibiotic stewardship policies, regular surveillance programs for antimicrobial resistance monitoring, and screening for genes encoding drug resistance phenotypes have become imperative.

Background: The rate of force development (RFD) plays a pivotal role not only in preventing falls but also in ensuring successful completion of many functional tasks that demand swift muscle power rather than prolonged strength. Despite its importance, there is limited compre-hensive research on the relationship between RFD and walking speed, especially in older adults with Sarcopenic Obesity (SO). Objective: to investigate the influence of obesity on neuromuscular markers in older adults with SO and to assess the relationship between neuromuscular markers and gait speed in older adults with SO. Methods: a cohort of 42 participants was categorized based on their BMI into two groups: the sarcopenic non-obese group (CG, n=22; age=81.13±4.02; BMI=25.13±3.35) and the sarcopenic obese group (SOG, n=20; age=77.71±2.95; BMI=34.46±3.25). Gait speed was measured using a 10-meter test. Additionally, the isometric strength of the plantar flexor muscles was assessed during maximal voluntary contractions. Absolute Peak force (aPeak, N) were documented at intervals of 50 ms (a50, N), 100 ms (a100, N), and 200 ms (a200, N), subsequently normalized to body mass (r50, r100, r200, N). The RFD was derived in two phases: from the start of the contraction to 50 ms (RFD50-100) and from 100 to 200 ms (RFD100-200) and calculated from the linear slop of the force – time curve (Δ force/Δ time). Conclusion: Obesity negatively impacts neuromuscular markers in older adults. Notably, RFD emerges as the dominant factor influencing gait speed, accounting for an impressive 51% of its variability, far surpassing the impact of relative peak force. This underscores the imperative of evaluating neuromuscular health in older adults with SO to provide insights into mobility out-comes.

Current and dynamic developments in green technologies have led to several innovation practices in the manufacturing sector only to become the top approaches used for achieving and accelerating sustainable development (SD) in the current business markets. In addition, manufacturing firms is in need of green innovation to be able to monitor and control their operations and enhance their environmental performance. However, regardless of its many benefits, the level of green innovation adoption and implementation is still lower than expected among manufacturing industries. Thus, this study aimed to minimize the gap by developing and validating a study model underpinned by Resource based view and Institutional theories, along with the Technology-Organization-Environment (TOE) framework in combination to convince firms to adopt green innovation. The study gathered data from 179 respondents using a survey distributed to manufacturing firms, after which data was exposed to Structural Equation Modeling (PLS-SEM) approach, for analysis. Based on the approach deliverables, all the integrated constructs of the model, namely perceived benefits, top management support, coercive pressure, normative pressure and mimetic pressure all predicted green management accounting practices. Moreover, green management accounting practices were found to directly and significantly affect green environmental performance. The developed integrated model provides a clear implication to decision-makers, indicating the importance of adopting and using green practices and innovative technologies for enhancing environmental performance. Based on the results from the reviewed advanced green technologies studies, there is considerable connection between green management accounting practices and environmental performance in the context of developing economies.

Introduction: COVID-19 pandemic has affected HCPs in multiple way. It has caused psychological impact in form of anxiety, depression, and insomnia. In this study, we aim to study and compare the stress level, anxiety and depression among HCPs who are posted in special COVID-19 units with the HCPs who are not posted in COVID-19 units.Methods: This cross-sectional study was conducted in June 2020, at various hospitals of Karachi, Pakistan. All health care professionals (HCPs) were invited to participate. A total of 301 HCPs completed this study, who were divided into two groups; those who are posted in COVID-19 ward (Group A) and those who are not (Group B). Psychological Impact was English version of the Depression Anxiety Stress Scale - 21 (DASS-21).Results: In Group A, 70.5% had moderate, severe, or extremely severe depression compared to 49.2% in group B. In Group A, 75.4% had moderate, severe, or extremely severe anxiety compared to 44.7% in group B. In Group A, 80.3% had moderate, severe or extremely severe stress compared to 54.2% in group B. Anxiety, depression and stress were significantly higher in HCPs who were posted in COVID-19 ward compared to those who were not posted in COVID-19 wardConclusion: There was significantly higher anxiety, stress and depression in health care professionals posted in COVID-19 ward. Both the government and health care agencies should take responsibility for protecting the psychological well-being of health care communities all over the world and ensuring a healthy work environment.

Computed tomography (CT) offers detailed insights into the internal anatomy of patients, partic-ularly for spinal vertebrae examination. However, CT scans are associated with higher radiation exposure and cost compared to conventional X-ray imaging. In this study, we applied a Genera-tive Adversarial Network (GAN) framework to reconstruct 3D spinal vertebrae structures from synthetic biplanar X-ray images, specifically focusing on anterior and lateral views. The synthetic X-ray images were generated using the DRRGenerator module in 3D Slicer, by incorporating segmentations of spinal vertebrae in CT scans for the region of interest focussing. The approach leverages a novel feature fusion technique based on X2CT-GAN to combine information from both views and employs a combination of Mean Squared Error (MSE) loss and adversarial loss to train the generator, resulting in high-quality synthetic 3D spinal vertebrae CTs. A total of n=440 CT data were processed. We evaluated the performance of our model using multiple metrics, in-cluding Mean Absolute Error (MAE) (for each slice of the 3D volume [MAE0] and for the entire 3D volume [MAE]), Cosine Similarity, Peak Signal-to-Noise Ratio (PSNR), 3D Peak Sig-nal-to-Noise Ratio (PSNR-3D), and Structural Similarity Index (SSIM). The average PSNR was 28.394 dB, PSNR-3D was 27.432, SSIM was 0.468, cosine similarity was 0.484, MAE0 was 0.034, and MAE was 85.359. The results demonstrated the effectiveness of the approach in reconstruct-ing 3D spinal vertebrae structures from biplanar X-rays, although some limitations in accurately capturing the fine bone structures and maintaining the precise morphology of the vertebrae were present. This technique has the potential to enhance the diagnostic capabilities of low-cost X-ray machines while reducing radiation exposure and cost associated with CT scans, paving the way for future applications in spinal imaging and diagnosis.

Introduction: Exams are a relatively stressful period for all students, especially undergraduate medical students. Exams bring anxiety and stress for the students. Some students experience such high stress that it hinders their academic productivity and reduces their exam performance. The aim of this study is to assess the effects of pre-exam anxiety on the academic performance of medical students. Methods: Two hundred and twenty-five final year medical students completed Westside Test Anxiety (WTA) Scale one month before their exams. Grade Point Average (GPA) of these students was noted when the results were announced. Data was processed and analyzed using SPSS v 22.0Results: The mean anxiety score on WTA scale was 3.46 ± 0.87. All students (100%) who scored ≤ 2.50 GPA were highly-extremely highly anxious. In the 2.51-3.00 GPA group, 46% were highly-extremely highly anxious, 32% were moderately anxious, and 21% had low to normal anxiety. In the 3.01-3.50 GPA group, 30% were highly-extremely highly anxious, 30% were moderately anxious, and 39% had low to normal anxiety. In the 3.51-4.00 GPA group, 29% were highly-extremely highly anxious, 23% were moderately anxious, and 47% had low to normal anxiety. The correlation coefficient between GPA and test anxiety of students was -.314 which shows inverse relationship.Conclusion: Pre-exam anxiety and stress imparts negative effects on the exam performance of final year medical students. Poor academic performance was associated with high to extremely high pre-exam anxiety while high achievers had relatively lower anxiety levels.

In the Lemongrass (Cymbopogon citratus), the investigations showed a wide range of active molecules their biological properties. However, most of these studies were conducted on the wid varieties, while cultivated plan addressed. This study aimed to characterize the biomolecules and biological activities of Lemongrass growing us African conditions sons in in Marocco. Marocco. Phenolic compound profiles of aqueous (AE) E) ethanol ethanol (EE), (EE), and methanol (ME) extract: fractions were obtained with steric exclusion chromatography on Sephadex 050 gel and identified by LC-MS/MS polyphenols (TPC), flavonoids (TFC), and antioxidant activities (FRAP: scavenging value and TAC: Total Antioxidant C the fraction were evaluated as well as the antimicrobial activity Obtained results showed that the ME contained e compounds (ie. Apigenine-7-0-rutinoside and myricitine-3-0-rutinoside). The AE showed the presence of five mole kaemiferol-3-0-glucuronide), while EE showed the presence of three molecules (Le. Quercetine-3-0-rutinoside). Reg chemical characterization, the rization, e highest value of Total phenolic content (TPC) was obtained in conten btained in AE ΑΕ (25) (4.60-0.29 mg highest value of Total flavonoids content (TFC) was obtained Ined in ME (29) (0.7±0.08 mg/g). Concerning the antioxide the highest FRAP was obtained in ME (29) (97.89%) and the highest total antioxidant capacity (TAC) was obtained (89.89%) Correlation between FRAP, TPC, and TFC was noted poly in fractions of AE and ME. All tested extracts of and their fractions showed a significant antimicrobial effect. The lowest minimum inhibitory concentration (MIC) wa for ME against E. col. Extracts biological activities and their fractions were governed by their active molecules. Ther new and clarify a novel aspect of bioactive molecules in the extracts of cultivated C. citratus Equaly, throughout this we clarified the relationship between identified molecules and their biological properties including antioxidant and comparative studies new activities, which is new for the study area. This study is suggested to be a reference. assays of other biological activities for the study plant

The literature offers limited information on the effect of obesity on the rate of force development, a critical parameter for mobility in older adults. The objectives of this study were; to explore the influence of obesity on RFD in older adults and to examine the association between this neuromuscular parameter and walking speed. 42 older adults were classified into two groups: the control group (CG, n=22; age=81.13±4.02 years; Body mass index (BMI)=25.13±3.35 kg/m²), and the obese group (OG, n=20; age=77.71±2.95 years; BMI=34.46±3.25 kg/m²). Walking speed (m/s) was measured using the 10-meter walking test. Neuromuscular parameters of the plantar flexors were evaluated during a maximal voluntary contraction test using a dynamometer. The RFD was calculated from the linear slop of the force – time curve in two phases: from the onset of the contraction to 50 ms (RFD50-100) and from 100 to 200 ms (RFD100-200). The gait speed was lower in the OG compared to the CG (p

A 1-year prospective study was carried out on patients in the ICU unit at a tertiary care hospital, Hail, Kingdom of Saudi Arabia. A total of 163 bacterial isolates were obtained from different clinical specimens with a high proportion of bacteria found associated with ventilator-associated pneumoniae (70, 43%), followed by catheter-associated urinary tract infection (39, 24%), central line-associated bloodstream infection (25, 15%), and surgical site infection (14, 8.6%). Klebsiella pneumoniae was the most common isolate (39, 24%), followed by Acinetobacter baumannii (35, 21.47%), Pseudomonas aeruginosa (25, 15%), and Proteus spp (23, 14%). Among the highly prevalent bacterial isolates, extended-spectrum beta-lactamase was predominant (42, 42.4%). Proper use of antibiotics, continuous monitoring of drug sensitivity patterns, and taking all precautionary measures to prevent beta-lactamases-producing organisms in the clinical settings are crucial and significant factors to fend off life-threatening infections and for a better outcome.

Catheter-associated urinary tract infection (CAUTI) is one of the most common hospital-acquired infections (HAIs). Prolonged hospitalization, invasive devices such as catheters, and irrational use of antimicrobial agents are believed to be the major causes of high rates of HAIs. Infections such as pyelonephritis, urethritis, cystitis, and prostatitis are the main concern in catheterized ICU patients. In these cases, Gram-negative bacteria are the most common. The present study is undertaken to determine the frequency, antibiograms, disease pattern, and risk factors involved in providing an advocacy recommendation to prevent CAUTI. A total of 1078 patients were admitted to the hospital ICU, out of which healthcare-associated infection was reported in 316 patients. CAUTI was reported only in 70 patients. Klebsiella pneumoniae (20%) was the predominant isolate, with Serratia (3%) and Providencia (3%) species as the least common in this study. The present study provides CAUTI incidence rates in a tertiary care hospital in Hail, Saudi Arabia. Furthermore, information on risk factors of CAUTI common causative organism associated, and their antibiogram patterns are also presented. This study provides vital information that can be used to formulate an effective antibiotic stewardship program that can be implemented throughout the kingdom.

Salmonella is a foodborne pathogen associated with localized outbreaks that potentially pose a huge risk to the public health in some countries such as Africa and India, especially in the regions lacking health care measures. The focus of the present study is the molecular detection method of salmonella. The study was conducted to identify Salmonella strains by PCR targeting flagellin specific gene from suspected patient’s clinical blood samples. Serologically, Widal test results showed that all serum samples except one patient (ID 7) were positive for O antigen. The serum of three patients (ID 4, 5 and 10) were found to be positive for H and O antigens while one patient (ID 9) showed agglutination for antigen H. The PCR approach used in this study was successful for fast and precise detection of clinically related Salmonella Typhi. Seven samples out of 10 were positive for Salmonella Typhi as fragments of 458-497bp were observed on the gel-agarose 0.8% corresponds to flagellin gene of S. Typhi. Relatively, smaller amplicons of 366-343bp were observed utilizing nested PCR as well, which seems more sensitive than the conventional PCR. Therefore, we recommend the PCR approach performed in this study to be used as a fast, cost-effective, and time-consuming tool for diagnostic purposes of Salmonella.

Post-traumatic stress disorder (PTSD) is a debilitating mental health disorder that causes significant dysfunction in individuals. Currently, there are many approved Pharmacotherapy and Psychotherapy treatment options for PTSD, but unfortunately, half of the patients do not respond to traditional therapies. In this article, we reviewed clinical trials and research on 3,4-methylenedioxymethamphetamine (MDMA) assisted Psychotherapy in PTSD patients, its pharmacokinetics and current treatment guidelines for PTSD. Based on the results of the efficacy of MDMA assisted Psychotherapy from six phases II Randomized controlled trials. MDMA-assisted Psychotherapy for PTSD has received the “Breakthrough Therapy” designation from the FDA. MDMA can potentially reduce PTSD symptoms even in treatment-resistant cases by increasing certain neurohormones, i.e. dopamine, serotonin, norepinephrine and oxytocin. It also modulates activities in the brain regions involved in fear and anxiety. Future research is needed to show whether the advantages outweigh the disadvantages and whether its use can be integrated into available treatment options for PTSD.

This study aimed to introduce a novel machine learning (ML) model designed to predict the need of interventions during endoscopy in patients with upper gastrointestinal bleeding (UGIB). The risk stratification tools in current use, such as the Glasgow Blatchford Score (GBS) and pre-endoscopic Rockall score, have limitations in accurately predicting the need for endoscopic interventions. All patients diagnosed with UGIB from January 2013 to October 2023 who underwent endoscopy were included in the study. Variables extracted included demographics, social history ,clinical history, clinical presentation and symptoms, drug history, management prior to endoscopy, findings during endoscopy, laboratory variables and vitals, and post-endoscopic results. Three machine learning models including Random Forest Classifier (RFC), Gradient Boosting Classifier (GBC), and AdaBoost Classifier were used to evaluate the need for intervention during endoscopy in our study. A total of 1372 patients were included from three major hospitals in Jordan, of whom 242 underwent endoscopic intervention. The GBC outperformed all other models and pre-endoscopic scores in predicting the need for endoscopic intervention with an area under the curve of 0.861. Findings during endoscopy, platelet count, pulse rate and systolic blood pressure during admission were the most contributing features in predicting the need for the need of endoscopic intervention. This study highlights the potential of machine learning models in enhancing decision making for UGIB management.

Members of the Ebolavirus genus demonstrate a marked differences in pathogenicity in humans with Ebola (EBOV) being the most pathogenic, Bundibugyo (BDBV) less pathogenic and Reston (RESTV) causing no severe disease in humans. The VP24 protein encoded by members of the Ebolavirus genus blocks type I interferon (IFN-I) signaling through interaction with host karyopherin alpha nuclear transporters, potentially contributing to virulence. Previously we demonstrated that BDBV VP24 (bVP24) binds with lower affinities to karyopherin alpha proteins relative to EBOV VP24 (eVP24), and this correlated with reduced inhibition of IFN-I signaling. We hypothesized that modification of eVP24-karyopherin alpha interface to make it similar to bVP24 would attenuate the ability to antagonize IFN-I response. We generated a panel of recombinant EBOVs containing single or combinations of point mutations in the eVP24-karyopherin alpha interface. Most of the viruses appeared to be attenuated in both IFN-I-competent 769-P and IFN-I-deficient Vero-E6 cells in the presence of IFNs. However, the R140A mutant grew at reduced levels even in the absence of IFNs in both cell lines, as well as in U3A STAT1 knockout cells. Both the R140A mutation and its combination with the N135A mutation caused almost complete inhibition of genome replication and transcription suggesting the role of these mutations in an IFN-I-independent attenuation. Additionally, we found that unlike eVP24, bVP24 does not inhibit interferon lambda 1 (IFN-λ1), which potentially explains the lower pathogenicity of BDBV relative to EBOV. Thus, the VP24 residues binding karyopherin alpha affect ebolavirus pathogenicity by IFN-I-dependent and independent mechanisms.

The emergence of SARS/MERS drug resistant COVID-19 with high transmission and mortality has recently been declared a deadly pandemic causing economic chaos and significant health problems. Like all coronaviruses, SARS-CoV-2 is a large virus that has many druggable components within its proteome. In this study, we focused on repurposing approved and investigational drugs by identifying potential drugs that are predicted to effectively inhibit critical enzymes within SARS-CoV-2. We shortlisted seven target proteins with enzymatic activities known to be essential at different stages of the virus life cycle. For virtual screening, the energy minimization of a crystal structure or modeled protein was carried out using Protein Preparation Wizard (Schrödinger LLC, 2020-1). Following active site selection based on data mining and COACH predictions, we performed a high-throughput virtual screen of drugs (n=5903) that are already approved by worldwide regulatory bodies including the FDA, using the ZINC database. Screening was performed against viral targets using three sequential docking modes (i.e. HTVS, SP and XP). Our in-silico virtual screening identified ~290 potential drugs based on the criteria of energy, docking parameters, ligand and binding site strain and score. Drugs specific to each target protein were further analyzed for binding free energy perturbation by molecular mechanics (prime MM-GBSA) and pruning the hits to the top 32 candidates. A top lead from each target group was further subjected to molecular dynamics simulation (MDS) using the Desmond module to validate the efficacy of the screening pipeline. All of the simulated hit-target complexes were predicted to strongly interact and with highly stable binding. Thus, we have identified a number of approved and investigational drugs with high likelihood of inhibiting a variety of key SARS-CoV-2 proteins. Follow-up studies will continue to identify inhibitors suitable for combination therapy based on drug-drug synergy to thwart resistance. In addition, the screening hits that we have identified provide excellent probes for understanding the binding properties of the active sites of all seven targets, further enabling us to derive consensus molecules through computer-aided drug design (CADD). While infections are expanding at a rampant pace, it must be recognized that resistance will grow commensurately through either genetic shift and/or genetic drift to all small molecule drugs identified. Vaccines should provide a more permanent solution through prevention, but resistivity is still a possible scenario. Nevertheless, a persistent multi-target drug development program is essential to curb this ongoing pandemic and to keep reemergence in check.

Optimizing warehouse operations and leveraging data insights are driving forces behind the rise of automation. This research explores the development of the SWIF warehouse management system (WMS) using the Agile methodology, a departure from traditional software development approaches. Agile’s iterative and step-by-step approach facilitated a streamlined development process. It allowed for quick adjustments based on evolving needs and feedback from stakeholders. This resulted in a substantial decrease in development time and a noticeable improvement in the final product’s quality. The study emphasizes the positive effect of Agile on teamwork and customer satisfaction. Developers reported enhanced communication and collaboration, leading to a stronger sense of ownership and engagement. Customers expressed greater satisfaction with the features and functionalities delivered in stages. The successful implementation of Agile in SWIF’s development showcases its effectiveness in managing complex and ever-changing software development projects. The study encourages the adoption of Agile methodology for similar projects to boost responsiveness, quality, and overall project success.

Evolution remains an incessant process in viruses, allowing them to elude host immune response and induce severe diseases, impacting the diagnostic and vaccine effectiveness. Predicting emerging viral genomes is crucial, particularly in diseases like dengue, where viruses disrupt host cells, leading to fatal outcomes. Deep learning has been applied to predict dengue fever cases; there has been relatively less emphasis on its significance in forecasting emerging Dengue Virus (DENV) serotype. While Recurrent Neural Networks (RNN) were originally designed for modeling temporal sequences, our proposed DL-DVE generative and classification model, trained on complete genome data of DENV, transcends traditional approaches by learning semantic relationships between nucleotides in a continuous vector space instead of representing contextual meaning of nucleotide characters. Leveraging 2000 publicly available DENV complete genome sequences, our Long Short-Term Memory (LSTM) based generative and Feedforward Neural Network (FNN) based classification DL-DVE model showcases proficiency in learning intricate patterns and generating sequences for emerging serotype of DENV. The generative model showed accuracy of 93% and the classification model provided insight into the specific serotype label, corroborated by BLAST search verification. Evaluation metrics such as ROC-AUC value 0.818, accuracy, precision, recall and F1 score all to be around 99.00%, demonstrated the classification model’s reliability.  Our model classified the generated sequences as DENV-4, exhibiting 65.99% similarity to DENV-4 and around 63-65% similarity with other serotypes, indicating notable distinction from other serotypes. Moreover, the intra-serotype divergence of sequences with a minimum 90% similarity underscored their uniqueness. We analyzed the conserved motifs in the genome through MEME Suite (version 5.5.5). Our research strives to contribute to the ongoing fight against the Dengue virus by offering predictive insights into its genomic evolution. Looking ahead, proactive predictive modeling before mutations occur holds potential for guiding vaccine design and diagnostic kit development.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

The impact of interaction SS with MJO on rainfall along Java Island to East Nusa Tenggara has been studied using daily rainfall observation data from 2140 weather observation stations, which are also equipped with GSMaP, OLR, and ERA5 data. There were 61 SS events found, 17 during active MJO and 44 in inactive MJO. Rainfall increases more in the western study area when the active MJO and more in the eastern study area when the inactive MJO is due to SS. SS reduces rainfall in the Jakarta region, regardless of the activity or inactivity of the MJO. SS causes extreme rainfall to only occur in a small part of certain areas, so it tends to significantly reduce the possibility of extreme rainfall. In the southern part of the IMC, SS predominates over MJO in supporting increased water vapor transport. Large-scale synoptic circulations like the monsoon, SS, and MJO can interact with local land-sea wind circulation to produce spatiotemporal variability in rainfall on Java Island. Rainfall mostly increases in the afternoon and decreases in the morning when SS occurs, whether there is MJO or not. Convective instability analysis indicates that SS increases precipitation, most likely by lowering CIN and raising VIMFC.

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

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

Currently there are fewer depth models applied to pepper picking detection, while the existing generalized neural networks have problems such as large model parameters, long training time, and low model accuracy.In order to solve the above problems, this paper proposes a Yolo-chili target detection algorithm for chili pepper detection. First, the classical target detection algorithm yolov5 is used as a benchmark model, and an adaptive spatial feature pyramid structure combining the attention mechanism and the idea of multi-scale prediction is introduced to improve the model's detection effect on occluded peppers and small target peppers. Secondly, a three-channel attention mechanism module is introduced to improve the algorithm's long-distance recognition ability and reduce the interference of redundant testers. Finally, the quantized pruning method is used to reduce the model parameters and realize the lightweight processing of the model. Applying the method to the homemade chili pepper dataset, the AP value of chili pepper reaches 93.11%; the accuracy rate is 93.51% and the recall rate is 92.55%.The experimental results show that yolo-chili is able to achieve accurate and real-time pepper detection under complex orchards.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Pyrops candelaria is one of the common pests of fruit trees, but the research on the pathogenic microorganisms it may carry is very limited. Therefore, it is essential to reveal the pathogenic microbes it carries and their potential hazards. This study found a new virus from the transcriptome of P. candelaria, which was first reported in P. candelaria and named as PyCaV (Pyrops candelaria associated virus). RACE and bioinformatics assay revealed that the full-length of PyCaV is 10855 bp with the polyA tail, containing a single open reading frame (ORF) encoding a polyprotein consisting of 3171 amino acid (aa). The virus has a typical Iflavirus structure, including two rhv domains, a RNA helicase domain (HEL), a 3C cysteine protease domain (Pro), and a RNA-dependent RNA polymerase domain (RdRp). Further phylogenetic analysis revealed that this virus belongs to family Iflaviridae and sequence alignements analysis suggedted PyCaV is new member in unassigned genus of family Iflaviridae. Further in-depth analysis of virus-infection-part showed that PyCaV is distributing in the whole longan lanternfly, including its head, chest, and abdomen, but more PyCaV was identified in the chest. The distribution of PyCaV in different parts of P. candelaria was further explored, which showed that more PyCaV were detected in its piercing-sucking mouthparts and chest viscera. Statistical analysis showed that the PyCaV infection was affected by time and locations.

With the burgeoning growth of online retail, the issue of counterfeit products has become a significant threat to both consumer trust and brand integrity, posing challenges to sustainable market practices. Online retail platforms are promoted to redesign their channel structures and enhance brand traceability to tackle counterfeits using blockchain technology. To investigate the interactions between blockchain technology and the channel structures of online retail platforms, we design a game theory model incorporating a manufacturer with(out) blockchain participation selling products via an online retail platform that operates an agency channel and/or a reselling channel. We show that the critical trade-off of blockchain participation comprises the brand assurance effect of the blockchain, the channel competition intensification effect, and the blockchain adoption cost. The platform is capable of strategically designing the channel structure to encourage (while discouraging) blockchain participation by the manufacturer. Our analysis highlights the complementarity between blockchain participation and the channel structure. Furthermore, the effect of the consumer’s belief in the reselling channel, the commission fee in the agency channel, and the substitutability between channels are investigated in depth. The research provides valuable insights for online retail platforms and policymakers seeking to foster a sustainable and trustworthy e-commerce ecosystem.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p &lt; 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

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

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

The paper describes the new method for image compression based on coordinated group signal transformation. The algorithm is a type of difference coding. Coordinated processing significantly simplifies the difference signal conversion scheme using a single group codec for all signals. The described method considers color channels as correlated signals of a multi-channel communication system. The specifics of the processed data required modification of the coordinated group processing algorithm. First, we changed how to calculate the difference signals to prevent data loss. Secondly, the group codec was supplemented with a neural network to improve the quality of reconstructed images. We considered the following types of neural networks: fully connected, recurrent, convolution, and convolution in the Fourier space. Based on the simulation results, it is best to use fully connected neural networks if the goal is to minimize processing delay time. These networks have a response time of 13 ms. On the other hand, if the priority is to improve quality in cases where delays are not critical, then convolution neural networks in the Fourier space should be used. These networks have a response time of 140 ms and are of significant interest.

The studied solar pot is a recent invention, which gained a utility model protection in 2021 from the Hungarian Intellectual Property Office under patent number 5489. The device is made for environmentally friendly cooking or heating (by utilizing solar energy) of foods and liquids. Its structure is similar to a double pipe heat exchanger, it has an outer mantle and an inner cooking tank. The goals of the paper are proposing a new physically-based mathematical model describing the solar pot and carrying out computer experiments with it, assembling an experimental system of the pot connected with a solar collector and performing measurements on it. Based on the results, the solar pot can successfully be used for cooking or sterilizing foods or liquids during the studied time period, in Hungary.

The research reported on this paper was aimed at improving the overall efficiency of a PDO certified artisanal cheese production process. Being a PDO certified foodstuff by the EU, it is considered to have properties and qualities determined by the geographical environment in which is made, with its production taking place in a specific and determined geographical location, in this case the Serra da Estrela region. In that sense, the authors conducted a mapping according to a systemic perspective of the processes involved in the context of manufacturing and distribution of certified Serra da Estrela cheese. Numerous methods were used throughout the process, such as a systemic design analysis, and techniques derived from ethnographic methods, which led to the collection of data in the field and consequently provided the immersion of the researcher in genuine work situations. Critical points were identified and emphasized in the systemic map with the purpose of encouraging initiatives to address and overcome the gaps and inefficiencies detected. The systemic design analysis triggered the development of design work. Observations following an ethnographic approach identified ergonomic risks in cheese making during the process of cutting excess chips, fostering the emergence of musculoskeletal disorders at the wrist. A tool that fits best to the task at hand was developed. A prototype of the new tool enabled collecting feedback from use in the work context, in order to inform product development. The domains of agricultural production and microbiology, considering the specific microorganisms developed trough the ripening process of the cheese, turned out to be aspects of high importance for the issue under focus, contributing to a broader understanding of the ripening process and its risks, simultaneously improving the efficiency and success of cheese production. If it were not for the systemic analysis, which served as a link between the boundaries of distinct domains such as the risk of microorganism contamination, ergonomics, energy efficiency, legislation and regulation policies, transportation challenges and economic viability, approached throughout the research. Simultaneously creating bridges between them, the various problems might not have been detected in the first place, as they are usually addressed in specialized disciplines, predetermined by the restrictions of each specific area of knowledge. As a consequence of the development of this research, which was based on an analysis that sought to establish possible connections between various disciplines and tried to constantly maintain a holistic perspective, making new connections and observing the issues from a new angle, apart from the already established methodologies. All this allowed to lay out the seeds for the development of a plan to tackle the critical points identified by the systemic analysis reported in this paper.

This paper is focused on typical rural settlements in the Stara Planina Mountain area in Serbia. They are distinguished by their authenticity, identity and character, and they have still not been destroyed by inappropriate development as is the case in some other mountain areas in Serbia, where the effects of urbanization, globalization and homogenization are obvious. Consequently, there is a need to prevent these effects in mountain areas where there is a threat of disbalance between development and the inherited natural and cultural values. The paper starts from several important concepts that relate contemporary approaches to cultural heritage preservation, place morphology and planning future development. The concept definitions from recent documents from related fields are used. These concepts are then applied to the area of Stara Planina Mountain and its rural settlements. The necessity for an integrative approach to planning this area with significant natural and anthropogenic potential is pointed out, including its integration into international programs of sustainable development.

The wetlands in northeastern Bangladesh are home to some of the most prolific and valuable ecosystems on the planet, offering a wide range of benefits to both the local and wider communities. A limited number of research on this topic have been carried out in various wetlands in coastal hilsa, but none have been located in the northeastern region of Bangladesh. Thus, the goal of this study was to better understand the most commercially relevant species (anadromous hilsa) in northeastern Bangladesh as well as to assess the wetland ecosystem services more thoroughly with the contribution of their fish genetic resources. In addition to laboratory studies, fieldwork was done in the fishing settlements along the Surma River, Hakaluki Haor, and Tanguar Haor. The study classified 77 fish species into 21 subcategories of ecosystem services, of which 56% were not threatened, 17% were vulnerable, and 10% were highly endangered. The species Hilsa was found to be the most economically significant, accounting for 1% of the GDP overall. The study determined if the hilsa stock of the examined wetlands maintains a single or several subpopulations in comparison to other parts of the country when they migrate from saline water to northeastern Bangladesh (freshwater). But when compared to other groups, the FST score was between 0.000 to 0.017, indicating that the populations are identical and that there is genetic material sharing between them. Additionally, these statistics imply that the Sylhet haor and adjacent river systems contain a single stock of Hilsa fish. Nevertheless, a number of stresses and risks, including overexploitation, illicit and destructive fishing, siltation, and natural disasters like flash floods, have been linked to changes in the supply of hilsa and other ecosystem services. This study also emphasizes the necessity of policy attention and research to address the concerns.

The continuous casting process of helical fiber reinforced metal matrix composites was proposed, and the experimental equipment was designed and manufactured. The relationship model be-tween the process parameters and the helical shape of the fibers in the metal matrix is analyzed by differential geometry. Helical carbon fiber reinforced lead matrix composites were prepared under different conditions. When the melting temperature and cooling intensity were increased, the helical radius of helical carbon fiber in lead matrix was increased. When the fiber rotation speed was increased, the helical radius was decreased, and the helical pitch was de-creased proportionally. The experimental results are consistent with the process model. Carbon fiber rein-forced aluminum composites were prepared. Scanning electron microscopy showed that the infiltration between the aluminum matrix and the carbon fiber was not complete. As the volume fraction of carbon fiber which was added in composites is too small, the mechanical properties of the composites have not been significantly improved.

This article presents an innovative approach to the design of a safe adaptive backstepping control system. Tailored specifically for underactuated marine robots, the system utilizes simple sensors for enhanced practicality and efficiency. Given their operation in diverse oceanic environments fraught with various sources of uncertainties, ensuring the system's safe and robust behavior holds paramount importance in the control literature. To address this concern, this paper introduces a control strategy designed to ensure robustness at both the kinematic and dynamic levels. By emphasizing the compensation for the system uncertainties, the design integrates a straightforward fuzzy system structure. To further ensure the system's safety, a funnel surface is defined, followed by the design of a suitable nonlinear sliding surface as a function of the funnel and tracking error. Specifically leveraging the Lyapunov function, the study formally establishes the Semi-globally Practically Finite-time Stability of the closed-loop system, validated through simulations conducted on underactuated marine robots.

Several types of guided bone regeneration materials are available with various properties and clinical indications. Among them, dentin-derived matrix from extracted teeth is an excellent alternative to traditional graft materials, such as allografts and xenografts. Different clinical preparation protocols exist: block form versus powder form, demineralized versus non-demineralized form. Out of these methods, demineralization protocols for dentin-derived matrix from extracted teeth have been noted for a wide range of successful clinical outcomes. The purpose of this animal study was to find out the most effective method of demineralizing dentin-derived matrix to result in the highest regenerative ability in the bone graft material in rabbit calvaria. The study conducted a comparative histomorphometric analysis of four groups in distinguished matrix conditions: a control group without graft placement, a non-demineralized dentin-derived matrix graft placement group, a 15-minute demineralized dentin-derived matrix graft placement group, and a 30-minute demineralized dentin-derived matrix graft placement group. Regenerative processes were evaluated three times at 2, 4, and 8 weeks post-graft placement. These groups of rabbits were evaluated randomly in a blinded setting to prevent bias. Among the four groups compared, the group with a 15-minute demineralized dentin-derived matrix graft showed the most efficient bone regeneration in the histomorphometric analysis. Based on this animal study, it was apparent that a 15-minute demineralization of dentin-derived matrix is the preferred preparation protocol to maximize the regenerative potential in the matrix.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) continues to be a global threat due to its ability to evolve and generate new subvariants, leading to new waves of infection. Additionally, other coronaviruses like Middle East respiratory syndrome coronavirus (MERS-CoV, formerly known as hCoV-EMC) which first emerged in 2012, persists and continues to present a threat of severe illness to humans. The continued identification of novel coronaviruses, coupled with the potential for genetic recombination between different strains, raises the possibility of new coronavirus clades of global concern emerging. As a result, there is a pressing need for pan-CoV therapeutic drugs and vaccines. After extensive optimization of an HCV protease inhibitor screening hit, a novel 3CLPro inhibitor (MK-7845) was discovered and subsequently profiled. MK-7845 exhibited nanomolar in vitro potency with broad spectrum activity against a panel of clinical SARS-CoV-2 subvariants and MERS-CoV. Furthermore, when administered orally, MK-7845 demonstrated a notable reduction of viral burdens by &gt;6 log orders in the lungs of transgenic mice infected with SARS-CoV-2 (K18-hACE2 mice) and MERS-CoV (K18-hDDP4 mice).

Oral squamous cell carcinoma (OSCC) is a highly prevalent and aggressive malignancy, with mortality rates that reach 60%, mainly due to an excessive diagnostic delay. MiRNAs, a class of crucial epigenetic gene-expression regulators, have emerged as potential diagnostic biomarkers, with >200 molecules reported to be dysregulated in OSCC. We had previously established an in silico methodology for the identification of the most disease-specific molecules by bridging genetics and epigenetics. Here, we identified the stage-specific miRNAs that govern the asymptomatic early stages of oral tumorigenesis by exploiting the reverse interplay between miRNA-levels and their target-genes’ expression. Incorporating gene expression data from our group’s experimental hamster model of sequential oral oncogenesis, we bioinformatically detected the miRNAs that simultaneously target/regulate >75% of the genes that are characteristically upregulated or downregulated in the consecutive stages of hyperplasia, dysplasia and early-invasion OSCC, while exhibiting the opposite expressional dysregulation in OSCC-derived tissue and/or saliva specimens. We found that all stages share the downregulation of miR-34a-5p, miR124-3p, and miR-125b-5p, while miR-1-3p is underexpressed in dysplasia and early-invasion. Malignant early-invasion stage is distinguished by the downregulation of miR-147a and the overexpression of miR-155-5p, miR-423-3p and miR-34a-5p. The identification of stage-specific miRNA molecules may facilitate their utilization as biomarkers for presymptomatic OSCC diagnosis.

Cocoa (Theobroma Cacao, L.) represents an important market that gained relevance and became an esteemed commodity thanks to cocoa powder, chocolate, and other related products. This work has analyzed 59 cocoa powder samples from the European market. Three distinct subgroups were identified: organic or conventional, alkalized or not alkalized, and raw or roasted processing. The impact of the technological process was evaluated on the pH, color, and compositional traits, as content of biogenic amines and salsolinol. The phenolic fraction was also investigated trough both common and emerging methods. Results depict that the influence of the agronomical practices (organic/conventional) did not affect significatively (p&lt;0.05) the composition of cocoa powders; similarly, the roasting process was not discriminative for the compounds traced. On the other hand, the alkalinization process greatly impacted on color, and pH, no matter of cocoa provenience, obtention, or other processes, also resulting reducing the phenolic fraction of treated samples. Principal components analysis confirmed that the alkali process acts on pH, color, and phenolic composition, but not on other bioactives molecules (BAs and salsolinol). All samples resulted safe while alkalized powders have a great reduction in beneficial biocompounds. A novel strategy could be to emphasize non-alkalized powders in the label, to meet the demand for more beneficial products.

The normal growth and development of skeletal muscle is essential for the health of the body. The regulation of skeletal muscle by intestinal microorganisms and their metabolites has been continuously revealed. Acetate is the predominant short-chain fatty acid synthesized by gut microbiota through the fermentation of dietary fiber, however, the underlying molecular mechanisms governing the interaction between acetate and skeletal muscle during rapid growth stage remain to be further elucidated; Here, specific pathogen-free (SPF) mice, germ-free (GF) mice, and germ-free mice supplemented with sodium acetate (GS) were used to evaluate the effects of acetate on skeletal muscle growth and development of young mice with gut microbiota deficiency; We found the concentration of serum acetate, body mass gain, succinate dehydrogenase activity and expression of myogenesis maker gene of skeletal muscle in the GS group was higher than GF group following sodium acetate supplement. Furthermore, the transcriptome analysis revealed that acetate activated biological processes regulating skeletal muscle growth and development in GF group that are inhibited due to gut microbiota deficiency. In vitro experiment, we proved that acetate up-regulated Gm16062 to promote skeletal muscle cell differentiation; Overall, our findings proved that acetate promote skeletal muscle growth and development in young mice via increase Gm16062 expression.

Phased injection of natural gas into internal combustion marine engines is a promising solution for optimizing performance and reducing harmful emissions, particularly unburned methane, a potent greenhouse gas. This innovative practice distinguishes itself from continuous injection because it allows for more precise control of the combustion process with only a slight increase in system complexity. By synchronizing the injection of natural gas with the intake and exhaust valve opening and closing times while also considering the gas path in the manifolds, methane release into the atmosphere is significantly reduced, making a substantial contribution to efforts to address climate change. Moreover, phased injection improves the efficiency of marine engines, resulting in reduced overall fuel consumption, lower fuel costs, and increased ship autonomy. This technology has been tested on a single-cylinder, large-bore, four-stroke research engine designed for marine applications, operating in dual-fuel mode with diesel and natural gas. Performance was compared with that of the conventional continuous feeding method. Evaluation of the effect on equivalent CO2 emissions indicates a potential reduction of up to approximately 20%. This reduction effectively brings greenhouse gas emissions below those of the diesel baseline case, especially when injection control is combined with supercharging control to optimize the air-fuel ratio.

In numerical simulations, achieving high accuracy without significantly increasing computational costs is often challenging. To address this, this paper presents an improved finite volume weighted essentially non-oscillatory (WENO) scheme tailored for applicability in computational fluid dynamics (CFD) and implemented in the flow solver NUAA-Turbo for simulating turbomachinery flows using both RANS and RANS/LES coupling. Firstly, the new WENO scheme is validated against classic numerical test cases to assess its stability and reliability in handling discontinuities, the Double problem, and Raleigh-Taylor (RT) instability issues. Compared to the original format, this enhanced finite volume WENO scheme demonstrates superior stability near discontinuities and resolves flow features with the same grid resolution more effectively. Next, for engineering applications related to turbomachinery, such as compressor and turbine characteristics, computations are performed using RANS, and the results obtained using WENO-ZQ3 and WENO-JS3 are compared. Finally, the new fifth-order WENO scheme is applied to RANS/LES coupled simulations of turbine wakes and film cooling. The results show that the enhanced finite volume WENO scheme offers improved stability and accuracy in engineering applications, allowing for high-precision calculations with fewer grid points to capture more detailed flow physics, thereby reducing computational costs in aerodynamic applications.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

To secure logic circuits against the illegal copying the insertion of the so-called key bit inputs using XOR/XNOR gates has been proposed in . The inserted gates modify (lock) the behavior of the original circuit and only the correct choice of the secret key bits guarantees the equivalent behaviour of the locked circuit to the original circuit. To break this kind of security, i.e. to find the secret key bits, there was a SAT solver based attack proposed in . The aim of this work is to experimentally verify this attack on several locked circuits with various number of primary inputs and outputs and with various number of gates. Except for the random placement of the key gates we evaluate also the positioning with chaining elimination. The obtained and presented results show that we were able to unlock 10 of 11 circuits within few minutes on a common PC.