In this work, a novel single crystal (3-(4-chlorophenyl)-4,5-dihydroisoxazol-5-yl)methyl benzenesulfonate has been synthetized via a one-pot sequential strategy under sonication. A single crystal X-ray diffraction analysis was reported. In the crystal, a layer structure is generated by C—H···O and C—H···N hydrogen bonds. A Hirshfeld surface analysis indicates that the most important contributions to the crystal packing are from H···H (28.9%), H···O/O···H (26.7%) and H···C/C···H (15.8%) interactions. The optimized structure calculated using density functional theory at the B3LYP/6–311 G+(d,p) level is compared with the experimentally determined structure in the solid state. The calculated highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy gap is 4.6548 eV.

Introduction: Papatasi fever, or three-day fever, is a viral disease transmitted by a species of female sandfly called Phlebotomus papatasi that has symptoms similar to influenza. Robat Karim County, due to the high abundance of Sandfly and climate change in recent years, provides a suitable environment for the growth and reproduction of Sandfly, especially Phlebotomus papatasi Therefore, the aim of this study was molecular monitoring of Papatasi fever virus in Sandfly of Robat Karim County, Tehran province. Materials and methods: In 7 selected areas in Robat Karim County, 679 Sandfly using sampling methods including traps and aspirators were caught and 500 samples were randomly selected according to the fishing location and transferred to the laboratory of the Medical Entomology Department. After fixing Sandfly on the slide surface, identification and percentage of frequency of sandfly species were determined and then by Real-time PCR method, molecular examination of Papatasi virus infection was performed at Tehran Pasteur Institute. Findings: Out of 679 samples taken, 310 (45.65%) belonged to males and 369 (54.35%) belonged to females. 7 species including 3 species of Sandfly of the genus Phlebotomus and 4 species of the genus Sergentomyia were identified among the samples, the highest percentage of catch belonged to Phlebotomus sergenti (28.57%). Of the 500 samples sent to the laboratory for testing for phleboviruses by Real-time PCR, no positive cases of Papatasi virus infection were observed in them. Conclusion: Robat Karim is one of the endemic areas of infectious diseases such as leishmaniasis. Due to climate change in this region that conditions for the growth and reproduction of Sandfly, especially Phlebotomus papatasi as a Vector of sandfly fever and since the sandfly fever disease is not vaccinated therefore, preventive measures to control and reduce diseases transmitted by Sandfly are important.

In the repercussions of the latest financial crisis that have occurred on the years 2008-2009, to fortify the stability of the banking systems, policy makers, and the Basel Committee on Banking Supervision – BCBS, together with national regulators have built up a few safety measures, and structures to guarantee that banks establishments keep up adequate capital levels through using risk management tools, in specific the Internal Capital Adequacy Assessment Processes (ICAAP). They all have called for thorough evaluations and assessments for the structure and components of risk management frameworks, tools, and practices whether by banks, regulators, analysts and risk management experts consistently, to ascertain the adequacy of the banking systems, policies, arrangements and techniques for overseeing risks, and guaranteeing the sufficiency of holding appropriate capital levels for confronting normal, as well as adverse and unexpected situations or emergencies. The main objectives of this research study is to shed the light on the ICAAP as one of the main keys of risk management programs, a process by which banks can use to ensure that they operate with an appropriate levels of capital, forward looking processes for capital planning covering a broad range of risks across banks, activities beyond simple capital management, and brings together risk and capital management activities in a form that can be used to support business decisions. The research study shall evaluate the significant relationship between the Banking System Stability (dependent variable) and the Internal Capital Adequacy Assessment Process (ICAAP – independent variable) with evidence from the Egyptian Banking Sector.

Pancreatic ductal adenocarcinoma (PDAC) is the fifth leading cause of cancer-related death in and presents the lowest 5-year survival rate for any form of cancer in the US. Only 20% of PDAC patients are suitable for surgical resection and adjuvant chemotherapy which remains the only curative treatment. Chemotherapeutic and genetherapy treatments are associated with adverse effects and lack specificity/efficacy. In this study we assess the oncolytic potential of immuno-oncolytic tanapoxvirus (TPV) recombinants expressing mouse monocyte chemoattractant protein (mMCP-1 or mCCL2), and mouse interleukin (mIL)-2, in human pancreatic BxPc-3 cells, using immunocompromised and CD-3+ T-cell reconstituted mice. Intratumoral treatment with TPV/∆66R/mCCL2 and TPV/∆66R/mIL-2 resulted in regression of BxPc-3 xenograft volume as compared to control in immunocompromised mice; mCCL-2 expressing TPV OV resulted in significant difference from control at p

Regulatory B cells (Bregs) with immunosuppressive function are critical in maintaining immune tolerance. In recent years, Bregs is an essential part of the study due to its therapeutic relevance and function in immune tolerance. The positive and negative regulatory role of human Bregs in immune tolerance is being discussed in several pathologies, including in autoimmune diseases, cancers, chronic infections, strokes in multiple reports. The negative regulatory roles of human Bregs are associated with lesser numbers and functional abnormalities in most of these studies, including myasthenia gravis (MG). In this review, the potential findings regarding human Bregs in MG, and Bregs mediated potential therapeutic strategies with its pros and cons have been discussed based on previous and current reports.

A field experiment was conducted on the farm of Abi Jarash in Agricultural Collage, different rates of olive solid waste and cow manure were used, as follows: (control, fresh olive solid waste 100%, fresh olive solid waste 75%+ cow manure 25%, fresh olive solid waste 50%+ cow manure 50%, fresh olive solid waste 25+ cow manure 75%, Fermented Olive Solid Waste 100%, Fermented olive solid waste 75%+ cow manure 25%, Fermented olive solid waste 50%+ cow manure 50%, Fermented olive solid waste 25+ cow manure 75%), wheat was seeded. The impact of fresh and fermented olive solid waste and cow manure on some chemical and fertility soil properties was studied. the olive solid waste treatment 100% which added had more effect on the organic matter, exchange capacity, nitrogen, phosphorus and potassium in soil, plant and productivity, after that the fermented olive solid waste 75% + cow manure, fresh olive solid waste 100% comparing with the control, the values of organic matter were (25% 2.73, 2.39) and the cation exchange capacity (21.76, 20.44, 19.38) and for phosphorus (303.3, 277.8, 171.8) mg / kg, while the values of potassium ​​were (303.3, 277.8, 171.8) mg / kg. In terms of plant content, the plant content of nitrogen, phosphorus and potassium were the same as for grains (2.784, 2.606, 2.126), (0.4535, 0.4226, 0.2753), (1.876, 1.762, 1.234) respectively, (0.2875, 0.2016) respectively for the same previous treatments and elements. olive solid waste 100% was the highest productivity comparing with the other treatments, where the productivity of wheat was (9.513) ton. ha-1.

Despite exhaustive studies, researchers have made little progress in the field of adoptive cellular therapies for relapsed-refractory acute myeloid leukemia (AML), unlike the notable uptake for B cell malignancies. Various single antigen targeting chimeric antigen receptor (CAR) T cell Phase I trials have been established worldwide and have recruited approximately 100 patients. The high heterogeneity at the genetic and molecular levels within and between AML patients resembles a black hole: a great gravitational field that sucks in everything, considering only around 30% of patients show a response but with consequential off-tumor effects. It is obvious that a new point of view is needed to achieve more promising results. This review first introduces the unique therapeutic challenges of not only CAR T cells but also other adoptive cellular therapies in AML. Next, recent single cell sequencing data for AML to assess somatically acquired alterations at the DNA, epigenetic, RNA and protein levels are discussed to give a perspective on cellular heterogeneity, intercellular hierarchies, and the cellular ecosystem. Finally, promising novel strategies are summarized, including more sophisticated next-generation CAR T, TCR-T and CAR-NK therapies; approaches to tailor the microenvironment and target neoantigens; and allogeneic approaches.

With the rapid development of science and technology, many new concepts and terms appear, especially in English. Other languages try to express these concepts with words from their own vocabulary. In the specific case of Arabic, there are many ways to find a counterpart for a particular new concept, such as using an existing word to denote the new concept, derivation, and blending. When these methods fail, the new concepts are simply phonetically transliterated. This has the disadvantage that most of the transliterated terms do not conform to the rules of the Arabic language and lead to a distortion of the language. Some modern linguists call for using the generation strategy to translate the new terms into Arabic by using the unused Arabic roots. Therefore, it is necessary to provide a resource that contains all Arabic roots with a categorization of what is used, what is available for use, and what is rejected according to the phonetic system. This work provides a comprehensive lexicon that contains all possible Arabic triliteral roots, determines the status of each root in terms of usage and acceptability, and provides a mechanism for giving preference to roots when there is more than one root that indicates the desired meaning.

With the rapid development of science and technology, many new concepts and terms appear, especially in English. Other languages try to express these concepts with words from their own vocabulary. In the specific case of Arabic, there are many ways to find a counterpart for a particular new concept, such as using an existing word to denote the new concept, derivation, and blending. When these methods fail, the new concepts are simply phonetically transliterated. This has the disadvantage that most of the transliterated terms do not conform to the rules of the Arabic language and lead to a distortion of the language. Some modern linguists call for using the generation strategy to translate the new terms into Arabic by using the unused Arabic roots. Therefore, it is necessary to provide a resource that contains all Arabic roots with a categorization of what is used, what is available for use, and what is rejected according to the phonetic system. This work provides a comprehensive lexicon that contains all possible Arabic triliteral roots, determines the status of each root in terms of usage and acceptability, and provides a mechanism for giving preference to roots when there is more than one root that indicates the desired meaning.

3D human pose estimation has made significant advancements through the integration of deep learning techniques. This survey provides a comprehensive review of recent 3D human pose estimation methods, with a focus on monocular images, videos, and multi-view cameras. Our approach stands out through a systematic literature review methodology, ensuring an up-to-date and meticulous overview. Unlike many existing surveys that categorize approaches based on learning paradigms, our survey offers a fresh perspective, delving deeper into the subject. For image-based approaches, we not only follow existing categorizations but also introduce and compare significant 2D models. Additionally, we provide a comparative analysis of these methods, enhancing the understanding of image-based pose estimation techniques. In the realm of video-based approaches, we categorize them based on the types of models used to capture inter-frame information. Furthermore, in the context of multi-person pose estimation, our survey uniquely differentiates between approaches focusing on relative poses and those addressing absolute poses. Our survey aims to serve as a pivotal resource for researchers, highlighting state-of-the-art deep learning strategies and identifying promising directions for future exploration in 3D human pose estimation.

Emerging and reemerging pathogens is a global challenge for public health. Recently, a novel coronavirus disease emerged in Wuhan, Hubei province of China, in December 2019. It is named COVID-19 by World Health Organization (WHO). It is known to be caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that affects the lower respiratory tract and manifests as pneumonia in humans. Coronaviruses (CoVs) are structurally more complicated as compared to other RNA viruses. This viral epidemic has led to the deaths of many, including the elderly or those with chronic disease or compromised immunity. Viruses cause infection and diseases in humans of varying degrees, upper respiratory tract infections (URTIs) cause common cold while lower respiratory tract infections induce pneumonia, bronchitis, and even severe acute respiratory syndrome (SARS). The costs of COVID-19 are not limited. It equally affects all the medical, sociological, psychological, and economic aspects globally. This is regarded as the third deadly outbreak in the last two decades after Severe Acute Respiratory Syndrome SARS (2002–2003) and Middle East Respiratory Syndrome MERS (2012). Based on the sequence homology of SARS-CoV-2, different animal sources including bats, snakes, and pangolins have been reported as potential carriers of this viral strain. Real-time RT-PCR represents the primary method for the diagnosis of new emerging viral strain SARS-CoV-2. The transmission dynamics suggest that SARS-CoV-2 is transmitted from person-to-person through direct contact or coughing, sneezing, and by respiratory droplets. Several anti-viral treatments including lopinavir/ritonavir, remdesivir, chloroquine phosphate, and abidor are also suggested with different recommendations and prescriptions. Protective and preventive strategies as suggested by various health organization i.e. WHO and US Center for Disease Control and Prevention (CDC) must be adopted by everyone. This review covers the important aspects of novel COVID-19 including characteristics, virology, symptoms, diagnostics, clinical aspects, transmission dynamics, and protective measures of COVID-19.

Real-time data processing and decision-making are increasingly crucial in various applications, driven by the continuous influx of data streams. Event-driven AI workflows within serverless computing environments offer a promising approach to handle these real-time demands efficiently. This paper presents a framework for simulating and analyzing the performance characteristics of such workflows. Our proposed approach utilizes simulated data with varying event rates and durations to investigate the impact on key performance metrics like latency, throughput, and resource utilization. This enables a comprehensive evaluation of the inherent trade-offs within event-driven AI systems. The key findings reveal a trade-off between latency and throughput. As the event rate increases, average processing latency generally increases while average throughput increases. Resource utilization remains relatively stable across different event rates in the simulated scenarios (e.g., 75.55\% at 2 events/second, 74.51\% at 10 events/second). This framework provides a valuable tool for understanding the performance characteristics of event-driven AI workflows and optimizing resource allocation strategies.

In the present paper, the effect of the non-linear thermal radiation on the neutral gas mixture in the unsteady state is investigated for the first time. The unsteady BGK technique of the Boltzmann kinetic equations for a neutral non-homogenous gas is solved. The solution of the unsteady case makes the problem more general significance than the stationary one. For this purpose, the moments' method, together with the traveling wave method, is applied. The temperature and concentration are calculated for each gas component and mixture for the first time.Furthermore, the study is held for aboard range of temperatures ratio parameter and a wide range of the molar fraction. The distribution functions are calculated for each gas component and the gas mixture. The significant non-equilibrium irreversible thermodynamic characteristics the entire system is acquired analytically. That technic allows us to investigate the consistency of Boltzmann's H-theorem, Le Chatelier principle, and thermodynamics laws. Moreover, the ratios among the different participation of the internal energy alteration are evaluated via the Gibbs formula of total energy. The final results are utilized to the argon-helium non-homogenous gas at different magnitudes of radiation force strength and molar fraction parameters. 3D-graphics are presented to predict the behavior of the calculated variables, and the obtained results are theoretically discussed.

Though inland ships share a small portion of the total global CO₂ emission from shipping, from the individual country’s economic and environmental perspective, this is very important. In order to reduce CO₂ emission from the sea going ships by increasing energy efficiency, International Maritime Organization (IMO) adopted a generalized Energy Efficiency Design Index (EEDI) in 2011. However, due to the variation in the environmental, geographic and economic conditions, a generalized EEDI cannot be established in a similar fashion as established by IMO. Shallow and restricted water effects, different fuel qualities (to reduce operational cost), increase in engine power requirement, reduction in carrying capacity, cargo availability, etc. forbid the use of existing EEDI formulation for inland waterways. So, an EEDI formulation based on revised parameters has been proposed for the inland ships of Bangladesh. This paper focuses on the implementation of the revised EEDI formulation by performing a sensitivity analysis of different ship design parameters. Based on the analysis, suggestions were made on how to design inland oil tankers of Bangladesh using the revised EEDI formulation for reducing CO₂ from the current level. Keeping the same speed and capacity, those vessels were redesigned based on those suggestions. The CFD analysis of those redesigned vessels using ‘Shipflow’ has shown a total resistance reduction of 10-13%.

Water pollution in Iraq has been extended disaster edge; this pollution is caused by wastes and sewages into soil and rivers, pollutant water sources influence the outbreak and serious epidemic status among the population.. The aim of this study is to determine the bacteriological quality of drinking water sources and characteristics of water-borne diseases especially diarrheal cases in Darbandikhan city. 166 water samples, collected from the different sources and areas, were tested for the presences of coliform bacteria as an indicator for pathogen contamination. Most probable number index was used for coliform enumeration. 161 diarrheal cases were taken as a sample from the patients were admitted to the general hospital in Darbandikhan district.. The questionnaire form was planned to view characteristics of diarrheal cases and patients were interviewed directly, the data was analyzed by STATA software application. 46% of the diarrheal cases used tap water for drinking. On the other hand, the reminder (54%) used other sources for the same purpose. All the risk factor such as type of water source, sufficiency of the water, duration of water storage and chlorination were associated with diarrhea. Almost half of the cases were children and three quarters were single. The data was analyzed by STATA version 13.1.This study indicated that the majority of drinking water sources in Darbandikhan city are not suitable for drinking, although net pipe system supplied chlorine significantly it has been proven that the tap water from the homes is not suitable for consumption.

The research aims to improve some of the physical and hydro-physical properties of some Vertisols in the southern region (part of the eastern Houran Plateau) in Sweda Governorate at the south of Syria. Using different quantities of volcanic ash, soil samples were collected from the Al-Thahallah village from a depth of (0-30) cm, The experiment was designed according to the complete random design with one factor that represents the ash quantity (1.25, 2.5, 5) %, with three replicates for each treatment in addition to the control treatment a0. The experiment was carried out within the plastic pots during agricultural season 2018/2019, in which the wheat of the Sham variety 3 were cultivated as a cover plant. The results showed that the addition of volcanic ash at the quantity of 5% led to a significant increase in the infiltration rate by (328.60) %,%, where the filtration rate increased from 0.42 cm/hr -1 to 1.80 cm.h-1, as well as for each of the air porosity by (89) % and the volume of infiltrate water by (40) %, compared with the control. The above-mentioned addition also resulted in a decrease in both dry bulk density, total soil porosity and volumetric swelling coefficient by (18.60, 5.80, 314) % Respectively, compared to the control. The addition also contributed to the reduce in the weighted moisture content when saturation and the field capacity, at the level of significance of 5%. The research recommends adding volcanic ash to the soil at a quantity of 5%, and adding enhancements with volcanic ash at various levels such as organic waste.

Stand biomass in boreal forests has attained recognition for its crucial role in carbon cycling. In this study, we examined the effect of stand age on above- and belowground biomass allocation in downy birch (Betula pubescens Ehrh.) in three drained peatland sites in Central Finland. We used allometric equations to estimate individual-tree above-ground biomass and its various components, including stem wood, stem bark, living branches, leaves, and dead branches. The above-ground biomass ranged from 10.5 t ha-1 to 276.0 t ha-1 and foliage biomass from 0.009 t ha-1 to 0.6 t ha-1. We found that stand age had a strong correlation with above-ground biomass, but foliage biomass appeared to peak at the middle-aged (50 years) stand compared to the young (10 years) or mature (80 years) stands. We observed coarse root biomass production of 45, 250, and 110 g m-2 in the 0–50 cm peat layer for young, middle-aged, and mature stands, respectively. Most coarse root biomass occurred in the top 20-cm layer (77%). These findings improve our understanding of how biomass allocation patterns – specifically those in foliar biomass– change over time, and the impact on litter inputs into the soil.

Reservoirs created by damming rivers significantly modify the environment and problems may arise: the storage of nutrients and organic matter in reservoirs often leads to decreased water quality due to eutrophication. Reservoirs built on lowland rivers are exposed to significant nutrient loads, often leading to eutrophication. In this article, the Sulejów Reservoir, in Central Poland, was the subject of the research, which focused on the use of Sentinel-2 remote sensing data to detect phytoplankton blooms, and on understanding the pattern of wind-driven surface currents using the CCHE2D model (a depth-averaged hydrodynamic model). The calculation of the total phosphorus load has shown that the reservoir mainly acts as nutrient storage. Still, during the low flow and intensive phytoplankton bloom, it can be a source of nutrients. The distribution of phytoplankton bloom on the Sulejów Reservoir was documented using eight Sentinel-2 satellite images from the vegetation season of 2020 and the Normalized Difference Chlorophyll Index (NDCl). Coupling remote sensing data and numerical modelling helps to interpret the hydrodynamic model results and understand nutrients and sediment dynamics within the reservoir. Hydrodynamic modelling combined with remote sensing data can be a valuable tool for selecting appropriate locations for water quality measurements at monitoring stations.

Smartphone devices, particularly android devices used by billions of people everywhere in the world. Similarly, this increasing rate attracts mobile botnet attackers that is a network of interconnected nodes operated by command and control (C&C) method to expand malicious activities. At present, mobile botnet attacks carried Distributed denial of services (DDoS) that causes to steal sensitive data, remote access, spam generation, etc. Consequently, various approaches are defined in the literature to detect mobile botnet using static or dynamic analysis. In this paper, we have proposed a novel hybrid model, which is a combination of static and dynamic method that relies on machine learning to identify android botnet applications having C&C capability. The results evaluated through machine learning classifiers in which Random forest classifier outperform other ML techniques, i.e. Naïve Bayes, Support Vector Machine, and Simple logistics. Our proposed framework can achieve 97.48% accuracy in detecting such harmful applications. Furthermore, we highlight some research directions and possible solutions regarding botnet attacks for the entire community.

The fact is quite transparent that almost everybody around the world is using android apps. Half of the population of this planet is associated with messaging, social media, gaming, and browsers. This online marketplace provides free and paid access to users. On the Google Play store, users are encouraged to download countless of applications belonging to predefined categories. In this research paper, we have scrapped thousands of users reviews and app ratings. We have scrapped 148 apps’ reviews from 14 categories. We have collected 506259 reviews from Google play store and subsequently checked the semantics of reviews about some applications form users to determine whether reviews are positive, negative, or neutral. We have evaluated the results by using different machine learning algorithms like Naïve Bayes, Random Forest, and Logistic Regression algorithm. we have calculated Term Frequency (TF) and Inverse Document Frequency (IDF) with different parameters like accuracy, precision, recall, and F1 and compared the statistical result of these algorithms. We have visualized these statistical results in the form of a bar chart. In this paper, the analysis of each algorithm is performed one by one, and the results have been compared. Eventually, We've discovered that Logistic Regression is the best algorithm for a review-analysis of all Google play store. We have proved that Logistic Regression gets the speed of precision, accuracy, recall, and F1 in both after preprocessing and data collection of this dataset.

Extracellular vesicles (EVs) are membranous vesicles secreted by both prokaryotic and eukaryotic cells and play a vital role in intercellular communication. EVs are classified into several subtypes based on their origin, physical characteristics, and biomolecular makeup. Exosomes, a subtype of EVs, are released by the fusion of multivesicular bodies (MVB) with the plasma membrane of the cell. Several methods have been described in literature to isolate exosomes from biofluids including blood, urine, milk, and cell culture media among others. While differential ultracentrifugation (dUC), has been widely used to isolate exosomes, other techniques including ultrafiltration, precipitating agents such as poly-ethylene glycol (PEG), immunoaffinity capture, microfluidics and size exclusion chromatography (SEC) have emerged as credible alternatives with pros and cons associated with each. In this review, we provide a summary of commonly used exosomal isolation techniques with a focus on SEC as an ideal methodology. We evaluate the efficacy of SEC to isolate exosomes from an array of biological fluids, with a particular focus on its application to adipose tissue-derived exosomes. We argue that exosomes isolated via SEC are relatively pure and functional, and that this methodology is reproducible, scalable, inexpensive, and does not require specialized equipment or user expertise.

Solar energy is a renewable and sustainable source of energy, and it has been used in addition of specified technologies, such as solar cooling. The demand for cooling continues to increase in line with environmental changes and a greater desire for human comfort. This study primarily aimed to analyze the performance of an evaporative cooling system powered by solar energy and assess the economic and environmental impact of this system. In this system, hot, dry incoming air is used to evaporate water, thus transforming part of its sensitive heat into latent heat without any variation in enthalpy or total heat. The outputted air then has a lower temperature and a greater humidity, thus providing a more comfortable, healthier environment for its users. To achieve this study’s objectives, numerical code was developed and implemented in MATLAB. The obtained results reveal that the efficiency of the evaporative cooler exceeds 90%, with maximum efficiency being reached at a high wet-bulb depression, while minimum efficiency was observed when the dry air has a high relative humidity and a low dry-bulb temperature.

During this epidemic of COVID-19, children are in need of much concentration and profound love of the senior family members. Although the measures taken by the organizations are necessary to prevent the spread of the novel coronavirus, they may be causing widespread mental health issues, including depression and loneliness. Therefore, it is imperative that parents have to spend the lion-share of time with children while listening to them cordially. Parents can participate in sports with them to help them stay fit so that they can enjoy commemorating moments. However, in this additional time, the parents can also make them habituated to practice the rules of health, so does social distancing.

The use of the un-indexed web, commonly known as the deep web and dark web, to commit or facilitate criminal activity has drastically increased over the past decade. The dark web is an infamously dangerous place where all kinds of criminal activities take place, despite advances in web forensics techniques, tools, and methodologies, few studies have formally tackled the dark and deep web forensics and the technical differences in terms of investigative techniques and artefacts identification and extraction. This research proposes a novel and comprehensive protocol to guide and assist digital forensics professionals in investigating crimes committed on or via the deep and dark web, the protocol named D2WFP establishes a new sequential approach for performing tasks and subtasks to improve the accuracy and effectiveness of current tools' output. Quantitative and qualitative research has been conducted by testing the protocol following a comprehensive and rigorous process in different scenarios and the obtained results show an apparent increase in the number of artefacts recovered when adopting D2WFP. The second contribution of D2WFP is the artefacts correlation and cross-validation which enables Digital Forensics professionals to better document and structure their analysis of host-based deep and dark web browsing artefacts.

Background: In spinal cord injury, radical treatment is still a persistent hope for patients and clinicians. Our study aimed to determine the different histological changes in central, cranial and caudal sites of compressed spinal cord as a result of neuroectodermal stem cells (NESCs) transplantation in rats. Material and methods: For extraction of NESCs, future brains were extracted from mice embryos (10-days old) and cultured. Eighty, male rats were divided randomly into control, sham (20 rats each); while 40 rats were subjected to compressed spinal cord injury (CSCI). Seven days after spinal cord injury, rats were subdivided into 2 groups (20 rats each); an untreated and treated with NESCs injected cranial and caudal to the site of the spinal cord injury. Rats were sacrificed 4 weeks after transplantations of NESCs and specimens from the spinal cord at the central, cranial and caudal to site of spinal cord injury were proceeded to be stained with haematoxylin & eosin, osmic acid and Immunohistochemistry of glial fibrillary acidic protein (GFAP). Results: Sections of CSCI revealed areas of hemorrhages, necrosis and cavitation limited by reactive astrocytosis, with upregulation of GFAP expression. Evidence of remyelination and mitigation of histopathological features, reactive astrocytosis in CSCI sections were more pronounced in cranial than in caudal region. Conclusions: NESCs transplantation ameliorated the pathological changes, promoted remyelination.

Helicobacter pylori is the most common human gastric infection. H. pylori stool antigen lateral flow immunochromatography assay (HpSA-LFIA) is considered one of the most cost-effective and rapid non-invasive assays (active tests). The evaluation of this test is crucial for accuracy and utility assurance. This study aimed to evaluate the polyclonal antibody-based HpSA-LFIA in comparison to a monoclonal antibody-based ELISA kit. Methodology: Stool samples were collected from 200 gastric patients for HpSA-LFIA and semi-quantitative HpSA-ELISA. Statistical analysis of the diagnostic values was performed using MedCalc software. Chi-square tests were used to determine the effects of gender and age. Results: The obtained results found that HpSA-LFIA achieved promising sensitivity (93.75%) and NPV (98.00%). However, it had poor specificity, PPV, and accuracy, respectively, 59.76%, 31.25%, and 65.31%. LR+ & LR- were 2.33% & 0.1%, respectively. Gender had no significance on the di-agnostic parameters of HpSA-LFIA. Age groups had irrelevant sensitivity; however, specificity was significantly higher in patients over 45 years. Conclusion: It was concluded that HpSA-LFIA was not accurate enough to be the sole test for di-agnosis and needs other confirmatory tests in case of positive conditions

Best horticulture management has been practiced to reduce the amount of inorganic fertilizer in connection with net (mosquito net) for higher production of Indian spinach. Excessive use of chemical fertilizers in agriculture promoted negative effect on the environment and human health in Bangladesh. The experiment was conducted at the Horticulture Farm of Bangladesh Agricultural University (BAU), Mymensingh during the period February to May 2016. Two factor experiments were conducted on nettings: control (N₀), Netting (N₁) and different fertilizers: control (F₀), Vermicompost 10 t/ha (F₁), Vermicompost 15 t/ha (F₂), 2/3^rdof F₂+ 1/3^rdof F₄ (F₃), Inorganic fertilizer (F₄). Combination of mosquito net and combined of organic and inorganic fertilizers (N₁F₃) gave the significantly higher growth and yield of Indian spinach compared to other treatment combination. The maximum vine length (77.71 cm), after 45 days after sowing was found from N₁F₃ which was 72% higher compared to control. The highest yield of Indian spinach was 38.67 t/ha from N₁F₃ which was 80% higher compared to control. The treatment combination of N₁F₃ provided maximum leaf numbers per plant, leaf length.

Weed seedbank is an indication of future weed infestation potential of the species and is essential for making strategic planning for its sustainable management. Parthenium weed (Parthenium hysterophorus L.) is an invasive alien species threatening the biodiversity and the environment in Malaysia. A study was, therefore, conducted to estimate the soil seedbank of the weed at four soil depths of four villages of Kuala Muda, Kedah. The aim was to indicate the critical s of parthenium weed seedbank in Malaysia. Soil samples were collected from the sites using a soil core. The seeds were extracted from the soil samples with sieve shaker at the Universiti Malaysia Kelantan laboratory, Jeli Campus. The study indicates that the weed seedbank is in critical level at the area. The highest number of weed seeds (6915/m2) was found in Kg. Kongsi 6, followed by Kg. Sungai Tok Rawang (4481 seeds/m2). The top layer of soil, 0-5 cm, contained the maximum number of weed seeds (4878 seeds/m2) and a significant number of seeds (316 seeds/m2) were noticed at 10-15 cm soil depth. The study suggests the Malaysian government to take immediate action to control parthenium weed seedbank of the sites.

The present paper deals with the investigation, at conceptual level, of the performance of short-medium-range aircraft with hydrogen propulsion. The attention is focused on the relationship between figures of merit related to transport capability, such as passenger capacity and flight range, and the parameters which drive the design of liquid hydrogen tanks and their integration with a given aircraft geometry. The reference aircraft chosen for such purpose is a box-wing short-medium-range airplane, object of study within a previous European research project called PARSIFAL, capable to cut the fuel consumption per passenger-kilometre up to 22%. By adopting a retrofitting approach, non-integral pressure vessels are sized to fit into the fuselage of the reference aircraft, under the assumption that the main aerodynamic, flight mechanic and structural characteristics are not affected. A parametric model is introduced to generate a wide variety of fuselage-tank cross-section layouts, from a single tank with the maximum diameter compatible with a catwalk corridor to multiple tanks located in the cargo deck , and an assessment work-flow is implemented to perform the structural sizing of the tanks and analyse their thermodynamic behaviour during the mission. This latter is simulated with a time-marching approach that couples the fuel request from engines with the thermodynamics of the hydrogen in the tanks, which is constantly subject to evaporation and, depending on the internal pressure, vent-ed-out in gas form. Each model is presented in detail in the paper and results are provided through sensitivity analyses to both the technology parameters of the tanks and the geometric parameters influencing their integration. The guidelines resulting from the analyses indicate that light materials, such as the Aluminium alloy AA2219 for tanks’ structure and polystyrene foam for the insulation, should be selected. Preferred values are also indicted for the aspect ratios of the vessel components, i.e. central tube and endcaps, as well as suggestions for the integration layout to be adopted depending on the desired trade-off between passenger capacity, as for the case of multiple tanks in the cargo deck, and achievable flight ranges, as for the single tank in the section.

As machine learning and computer vision techniques and methods continue to advance, the collection of naturalistic traffic data from video feeds is becoming more and more feasible. That is especially true for the case of bicycles, for which the collection of naturalistic data is not achievable in the traditional vehicle approach. This study describes a research effort that aims to extract naturalistic cycling data from a video dataset for use in safety and mobility applications. The used videos come from a dataset collected in a previous Virginia Tech Transportation Institute study in collaboration with SPIN in which continuous video data at a non-signalized intersection on the Virginia Tech campus was recorded. The research team applied computer vision and machine learning techniques to develop a comprehensive framework for the extraction of naturalistic cycling trajectories. In total, this study resulted in the collection and classification of 619 bicycle trajectories based on their type of interactions with other road users. The results confirm the success of the proposed methodology in relation to extracting the locations, speeds, and accelerations of the bicycles at a high level of precision. Furthermore, preliminary insights into the acceleration and speed behavior of bicyclists around motorists are determined.

Although train simulation research is vast, most available network simulators do not track the instantaneous movements and interactions of multiple trains for the computation of energy/fuel consumption. In this paper, we introduce the NeTrainSim simulator for heavy long-haul freight trains on a network of multiple intersecting tracks. Trains are modeled as a series of moving mass points (each car/locomotive is modeled as a point mass) while ensuring safe following distances between them. The simulator considers the motion of the train as a whole and neglects the relative movements between the train cars/locomotives. Furthermore, the powers of the different locomotives are transferred to the first locomotive as such a simplification result in a reduced simulation time without impacting the accuracy of energy consumption estimates. While the different tractive forces are combined, the resistive forces are calculated at their corresponding locations. The output files of the simulator contain pertaining information to the train trajectories and the instantaneous energy consumption levels. A summary file is also provided with the total energy consumed for the full trip and the entire network of trains. Two case studies are conducted to demonstrate the performance of the simulator. The first case study validates the model by comparing the output of NeTrainSim to empirical trajectory data using a basic single-train network. The results confirm that the simulated trajectory is precise enough to estimate the electric energy consumption of the train. The second case study demonstrates the train-following model considering six trains following each other. The results showcase the model’s ability in relation to maintaining safe-following distances between successive trains. Finally, the NeTrainSim is demonstrated to be scalable with computational times of O(n) for less than 50 trains (n) and O(n²) for higher number of trains.

Fracture analysis of reinforced concrete deep beam strengthened with carbon fiber-reinforced polymer (CFRP) plates was carried out. The present research aims to find out whether the crack propagation in a strengthened deep beam follows linear elastic fracture mechanics (LEFM) theory or nonlinear fracture mechanics theory. To do so, a new energy release rate based on nonlinear fracture mechanics theory was formulated on the finite element method and the discrete cohesive zone model (DCZM) was developed in deep beams. To validate and compare with numerical models, three deep beams with rectangular cross-sections were tested. The code results based on nonlinear fracture mechanics models were compared with experimental results and ABAQUS results carried out based on LEFM. The predicted values of initial stiffness, yielding point and failure load, energy absorption, and compressive strain in the concrete obtained by the proposed model were very close to the experimental results. However, the ABAQUS software results have greater differences with the experimental results. For example, the predicted failure load for the shear-strengthened deep beam using the proposed model has only 6.3% differences compared to the experimental result. However, the predicted failure load using ABAQUS software based on LEFM has greater differences (25.1%) compared to the experimental result.

Acute kidney injury (AKI), especially if recurring represents a risk factor for future chronic kidney disease. In intensive care units, increased intraabdominal pressure is well-recognized as a significant contributor of AKI. However, the importance of transiently increased intra-abdominal pressures procedures is less commonly appreciated during laparoscopic surgery, the use of which has rapidly increased over the last few decades. Unlike the well-known autoregulation of the renal cortical circulation, medulla perfusion is modulated via partially independent regulatory mechanisms and strongly impacted by changes in venous and lymphatic pressures. In our review paper, we will provide a comprehensive overview of this evolving topic, covering a broad range from basic pathophysiology up to and including current clinical relevance. Key regulators of oxidative stress such as ischemia-reperfusion injury, the activation of inflammatory response and humoral changes interacting with procedural pneumoperitoneum formation and AKI risk will be recounted. Moreover, we present an in-depth review of the interaction of pneumoperitoneum formation with general anesthetic agents and animal models of congestive heart failure. A better understanding of the relationship between pneumoperitoneum formation and renal perfusion will support basic and clinical research, leading to improved clinical care and collaboration among specialists.

Non-enzymatic glucose sensing is a crucial field of study because of the current market demand. This study proposes a novel design of glucose sensor with enhanced selectivity and sensitivity by using graphene Schottky diodes, which is composed of Graphene/Platinum Oxide/n-Silicon heterostructure. The sensor was tested with different glucose concentrations and interfering solutions to investigate its sensitivity and selectivity. Different structures of the device were studied by adjusting the platinum oxide film thickness to investigate its catalytic activity. It was found that the film thickness plays a significant role in the efficiency of glucose oxidation and hence in overall device sensitivity. Moreover, theoretical investigations were conducted using Density Function Theory (DFT) to better understand the detection method and the origins of selectivity. The working principle of the sensors puts it in a competitive position with other non-enzymatic glucose sensors. DFT calculations provided a qualitative explanation of the charges distributed across the graphene sheet within a system of a platinum substrate with D-glucose molecules above. The proposed graphene/PtO/n-Si heterostructure has proven to satisfy these factors, which opens the door for further developments of more reliable non-enzymatic glucometers for continuous glucose monitoring systems.

An advanced driver-assistance system (ADAS) is critical to driver-vehicle-interaction systems. Driving behaviour modelling and control significantly improves the global performance of ADAS. A haptic assistive system assists the driver by providing a specific torque on the steering wheel according to the driving-vehicle-road profile to improve the steering control. However, the main problem is designing a compensator dealing with the high-level uncertainties in different driving scenarios with haptic driver assistance, where different personalities and diverse perceptions of drivers are considered. If not properly accounted for, these differences can lead to poor driving performance. This paper focuses on designing a data-driven model-free compensator considering various driving behaviours with a haptic feedback system. A back propagation neural network (BPNN) models driving behaviour based on real driving data (speed, acceleration, vehicle orientation, and current steering angle). Then using the genetic algorithm (GA) and the integral time absolute error (ITEA) criterion to optimize multiple PID compensation parameters for various driving behaviour (such as speeding/braking, lane-keeping and turning), which are then be combined by the fuzzy logic to provide different driving commands. An experiment was conducted with 5 participants in a driving simulator. During the second experiment, seven participants drove in the simulator to evaluate the robustness of the proposed combined GA-PID offline and the Fuzzy-PID controller applied online. The experiment results evaluated the ITAE of lateral displacement and yaw angle, during various driving behaviour. The results validated the proposed method by significantly enhancing the driving performance.

The outbreak of COVID-19 has brought unprecedented risks and challenges to everyone in the world. Myasthenia gravis is an autoimmune disease of the nervous system. Infection can worsen it and cause severe symptoms such as myasthenia crisis and respiratory failure. At present, the pandemic of COVID-19 may promote the aggravation of patients with MG. This article focuses on the respiratory management of MG patients during the epidemic of COVID-19.

Technological advances such as blockchain, artificial intelligence, big data, social media, geographic information systems represent a building block of the digital transformation that supports the resilience of the food supply chain (FSC) and increases its efficiency. This paper reviews the literature surrounding digitalization in FSCs. A bibliometric and key-route main path analysis was carried out to objectively and analytically uncover the knowledge development in digitalization within the context of sustainable FSCs. The research began with the selection of 2140 articles published nearly over five decades. Then, the articles were examined according to several bibliometric metrics such as year of publication, countries, institutions, sources, authors, and keywords frequency. A keyword co-occurrence network was generated to cluster the relevant literature. Findings of the review and bibliometric analysis indicate that research at the intersection of technology and the FSC has gained substantial interest from scholars. On the basis of keyword co-occurrence network, the literature is focused on the role of information communication technology for agriculture and food security, food waste and circular economy, and the merge of the Internet of Things and blockchain in the FSC. The analysis of the key-route main path uncovers three critical periods marking the development of technology-enabled FSCs. The study offers scholars a better understanding of digitalization within the agri-food industry and the current knowledge gaps for future research. Practitioners may find the review useful to remain ahead of the latest discussions of technology-enabled FSCs. To the authors’ best knowledge, the current study is one of the few endeavors to explore technology-enabled FSCs using a comprehensive sample of journals articles published during the past five decades.

Human intestinal flora refers to a large and diverse microbial population present in the digestive tract of the human body, which plays a significant role in the establishment of human immune homeostasis and the normal function of the immune system. Myasthenia Gravis is an autoimmune disease of the neuromuscular junction, mainly involved in the anti-acetylcholine receptor antibody, cellular immune dependence, and complement¹. At present, studies have found that the intestinal flora of Myasthenia Gravis is different from that of healthy people. Probiotic therapy has been shown effective in the experimental autoimmune Myasthenia Gravis animal models. This article reviews the relationship between intestinal flora and Myasthenia Gravis, to provide new ideas for further study of the pathogenesis and clinical treatment of Myasthenia Gravis.

This study examines the improvement in coupled intercomparison project phase six (CMIP6) models against the predecessor CMIP5 in simulating mean and extreme precipitation over the East Africa region. The study compares the climatology of the precipitation indices simulated by the CMIP models with the CHIRPS dataset using robust statistical techniques for 1981 – 2005. The results display the varying performance of the general circulation models (GCMs) in the simulation of annual and seasonal precipitation climatology over the study domain. CMIP6-MME shows improved performance in the local annual mean cycle simulation with a better representation of two peaks, especially the MAM rainfall relative to its predecessor. Moreover, simulation of extreme indices is well captured in CMIP6 models relative to its predecessor. The CMIP6-MME performed better than the CMIP5-MME with lesser biases in simulating SDII, CDD, and R20mm over East Africa. Remarkably, most CMIP6 models are unable to simulate extremely wet days (R95p). A few CMIP6 models (e.g., NorESM2-MM and CNRM-CM6-1) depicts robust performance in reproducing the observed indices across all analyses. Conversely, OND season shows the overestimation of some indices (i.e., R95p, PRCPTOT), except for SDII, CDD, and R20mm. Consistent with other studies, the mean ensemble performance for both CMIP5/6 shows better performance due to the cancellation of some systematic errors in the individual models. Generally, the CMIP6 depicts improved performance in the simulation of MAM season akin CMIP5 models. However, the new model generation is still marred with uncertainty, thereby depicting substandard performance over the East Africa domain. This calls for further investigation of attribution studies into the sources of persistent systematic biases and a prerequisite for identifying individual models with robust features that can accurately simulate observed patterns for future usage.

This study aims to evaluate the patient’s dose exposure from Computed Tomography Pulmonary Angiography (CTPA) examination and to estimates the cancer risk induced from the examinations based on the patient’s size. One hundred patients were recruited, and data information was collected retrospectively. A multi-detector (MDCT) (Philips Brilliance 128, USA) scanner were utilized for the CTPA examination, and dose data were obtained from the system. The effective diameter of each subjects’ image was measured for the Size-specific dose estimates (SSDEs). All subjects divided into Group 1 (19 – 25 cm), Group 2 (25-28 cm) and Group 3 (28-38 cm), where the association between gender were analysed. Effective dose (E), SSDE, organ dose and cancer risk of each group were evaluated and compared statistically using independent t-test and one-way ANOVA. The range of mean CTDI_vol, DLP and E values were (6.44 – 17.42 mGy), (239 – 631 mGy), (5.19 – 13.90 mSv), respectively. In respective with the patient’s effective diameter, the mean SSDE value for Group 1, Group 2 and Group 3 were 9.93 ± 3.89 mGy, 13.70 ± 9.04 mGy and 22.29 ± 7.35 mGy. The organ dose and cancer risk attained for breast, lung and liver were 17.05 ± 10.40 mGy (194 per one million procedure), 17.55 ± 10.86 mGy (192 per one million procedure) and 15.04 ± 9.75 mGy (53 per one million procedure), respectively. Lung and breast with more massive patient’s effective diameter received the highest dose exposure which increases the probability of the cancer risk. CTDI_vol was found to be underestimated, and SSDE provides more accurate in describing the radiation dose and cancer risk. Body effective diameter found to be significant on the estimation except for gender. Therefore, it is essential to apply optimised protocols in order to reduce patient’s exposure during CTPA examination.

Apple (Malus x domestica) fruit size is dependent on cell division and cell expansion, processes which are subsequently regulated by plant hormones such as auxins, gibberellins, and cytokinins. In this study, we investigated the role of cell division and cell expansion in apple growth and identified which of the two was more deterministic to final fruit size. Three cultivars of different sizes were selected, namely, ‘Twenty Ounce’ (large-sized), ‘Royal Gala’ (medium-sized), and ‘Crabapple’ (small-sized). Gene expression and cell size analyses were conducted over the course of two consecutive seasons. The expression patterns of three classes of genes were markedly similar across all cultivars. Two cell division markers, namely, MdCDKB2;2 and MdANT2, were discovered to be correlatively expressed as both displayed initially high expression levels, which gradually declined from the early to late stages of growth time course. For cell expansion markers, MdEXP3 was upregulated as the cells expanded, while MdARF106 was expressed in both the cell division and expansion stages. Meanwhile, the ripening related gene MdACO1 was expectedly expressed only during the ending stages associated with ripening. Interestingly, the cell measurements taken regularly from each cultivar throughout the same eperimental timespan showed that cell sizes were unaltered and remained constant from initial pollination at the zeroth Days After Pollination (DAP), to ripening at 120 Days After Full Bloom (DAFB).

Currently, algae arouse a growing interest in the pharmaceutical and cosmetic area due to the fact that they have a great diversity of bioactive compounds with the potential for pharmacological, cosmetic, and nutraceutical applications. Many of these bioactive compounds are secondary metabolites whose amounts in the algae vary with varying environmental conditions. Free radicals and other active oxygen derivatives are recognized as a natural by-product of aerobic metabolism. However, reactive oxygen species directly participate in mechanisms related to various pathological states such as cancer, diabetes, atherosclerosis, Alzheimer's, and Parkinson's, among others. Diabetes mellitus (DM) is a metabolic disease resulting from changes in glucose metabolism and/or deficient production/action of insulin. This review has as its main objective to reveal the potential antioxidant and antidiabetic capacity of algae extracts.

Diabetes mellitus (DM) and obesity account for the highest burden of non-communicable diseases. There is increasing evidence showing therapeutic patient education (TPE) as a clinically and cost-effective solution to improve biomedical and psychosocial outcomes among people with DM and obesity. The present systematic review and meta-analysis presents a critical synthesis of development of TPE interventions for DM and obesity and the efficacy of these interventions across a range of biomedical, psychosocial and psychological outcomes. A total of 54 of these RCTs were identified among patients with obesity and diabetes and were thus, qualitatively synthesized. Out of these, 47 were included into quantitative synthesis. There was substantial heterogeneity in reporting of these outcomes (I²= 88.35%, Q= 317.64), with significant improvement (SMD=0.36, 95% CI: 0.23 to 0.49) noted in biomedical outcomes in the intervention group. The effect sizes were comparable across interventions delivered by different modes and delivery agents. These interventions can be delivered by allied health staff, doctors or electronically as self-help programs, with similar effectiveness (P < 0.001). These interventions should be implemented in healthcare and community settings to improve health of patients suffering from DM and obesity.

Purpose: To identify factors linked with nutritional risk via the Malnutrition Universal Screening Tool scale assessment among critically ill patients from a hospital in Cali (Colombia). Materials and methods: A retrospective, analytical observational study was conducted with patients admitted to an intensive care unit (ICU). Sociodemographic, clinical, hematological, and biochemical parameters were analyzed, as well as their association with nutritional risk and patient mortality. Binary logistic regression was applied to outline nutritional risk. Results: Overall, 28.4% prevalence of elevated nutritional risk was observed. An association was found between nutritional risk and hemoglobin and hematocrit values, primary diseases accounting for ICU admission, gastrointestinal symptoms, and nutritional support route (p < 0.05). Mortality was 11.6% and it was correlated with nutritional risk, hemoglobin, and blood urea nitrogen. Conclusions: Gastrointestinal symptoms and the type of nutritional support received during hospitalization may increase nutritional risk, whereas polycythemia was a protective factor. We found an associative model to determine nutritional risk with high specificity and an adequate diagnostic validity index.

Glacial meltwater has been lifeline of agriculture in Gilgit-Baltistan for centuries which is being effected by the climatic changes and associated challenges. The government line institutions and development agencies have been investing to sustain and further extend the cultivated areas by leveraging the available glacial meltwater source. However, approximately 13% arable land, laying mainly along river banks, has limited access to glacial meltwater. Moreover, already cultivated areas also need alternate and sustainable irrigation water supplies to insurefood security. Hence, there is need to explore more potential options to address these challenges and bringing arable land under irrigation for regional prosperity and environmental gains. The International Centre for Integrated Mountain Development (ICIMOD) and its partners piloted solutions for aforementioned issues in Gojal, District Hunza. These solutions included river water lifting through solar and Hydraulic Ram Pumps, uphill water storages and application through drip irrigation systems. In order to assess the technical and economical viabilities of these piloted systems, a semi-structured questionnaire survey, field observation visits to collect data and economic assessment studies were carried out in Morkhun and Khyber. Both piloted systems have been proven as climate resilient, adaptable, environment friendly and economically viable. The cost to benefit ratio for solar powered drip irrigation and Hydraulic Ram Pump drip irrigation systems are 2.96 and 4.21 respectively, with payback period of 9.21 and 8.25 years respectively. The drip irrigation systems at Khyber and Morkhun sites have exhibited excellent hydraulic performance with Coefficient of Uniformity 92.61 and 93 % respectively. However, the field application efficiency of drip irrigation systems estimated for Khyber and Morkhun sites are 85.24 and 88.88% which are lower than the optimal value mainly due to lesser water holding capacity. The Hydraulic Ram Pump can lift four times more water to greater height, while comparing to solar pump of approximately similar capacity and higher capital costs. Both water lifting systems have some limitations and requires local customization for sustainable use.

When implementing SVMs, two major problems are encountered: (a) the number of local minima increases exponentially with the number of samples and (b) the quantity of required computer storage, required for a regular quadratic programming solver, increases by an exponential mag-nitude as the problem size expands. The Kernel-Adatron family of algorithms gaining attention lately which has allowed it to handle very large classification and regression problems. Howev-er, these methods treat different types of samples (Noise, border, and core) in the same manner, which causes searches in unpromising areas and increases the number of iterations. In this work, we introduce a hybrid method to overcome these shortcomings, namely Optimal Recurrent Neu-ral Network Density Based Support Vector Machine (Opt-RNN-DBSVM). This method consists of four steps: (a) characterization of different samples, (b) elimination of samples with a low probability of being a support vector, (c) construction of an appropriate recurrent neural network based on an original energy function, and (d) solution of the system of differential equations, managing the dynamics of the RNN, using the Euler-Cauchy method involving an optimal time step. The RNN remembers the regions explored during the search process thanks to its recurrent architecture. We demonstrated that RNN-SVM converges to feasible support vectors and Opt-RNN-DBSVM has a very low time complexity compared to RNN-SVM with constant time step, and KAs-SVM. Several experiments were performed on academic data sets. We used several classification performances measures to compare Opt-RNN-DBSVM to different classification methods and the results obtained show the good performance of the proposed method.

In diabetic foot infections (DFI), the clinically virulence of skin commensals are generally pre-sumed to be of low virulence. In this single-center study, we divided the wound isolates into two groups: skin commensals (coagulase-negative staphylococci, micrococci, corynebacteria, cutibacteria); and, pyogenicpathogenic pathogens, and followed the patients for ≥ 6 months. In this retrospective study among 1,018 DFI episodes (392 [39%] with osteomyelitis), we identified skin commensals as the sole culture isolates (without accompanying pyogenicpathogenic patho-gens) in 54 cases (5%). After treatment (antibiotic therapy [median of 20 days], hyperbaric oxy-gen in 98 cases [10%]), 251 episodes (25%) were clinical failures. Group comparisons between those growing only skin commensals and controls found no difference in clinical failure (17% vs 24 %, p=0.23) or microbiological recurrence (11% vs 17 %, p=0.23). The skin commensals were mostly treated with non-beta-lactam oral antibiotics. In multivariate logistic regression analysis, isolation of only skin commensals was not associated with failure (odds ratio 0.4, 95% confi-dence interval 0.1-3.8). Clinicians might wish to consider these isolates as potential pathogens when selecting a targeted antibiotic regimen, which may equally base on oral non-beta-lactam antibiotic agents susceptible to the corresponding skin pathogens.

Objectives: To investigate the value of early lactate dynamic monitoring index in predicting prognosis of patients with sepsis and septic shock. Methods: We performed our test on 50 patients. Out of 50 patients, 28 are male, and 22 are female. Prospectively studied pediatric patients with septic shock were performed. Vital signs, Lactate clearance, were obtained at presentation 6 h, 12 h, 24 h over the first 48 h of hospitalization. The therapy received, outcome parameters of mortality and duration of hospitalization were recorded. Results: The statistical data and comparative analysis showed that an average of 16.88 days after admission, 5 patients have died, 17 patients are poorly prognosis leaves the hospital, and the remaining 28 are recovered and discharged. The primary outcome variable of mean 16 days hospitalization mortality rate was 10%. Poor prognosis 34% and fully recovery 56 % were observed. In this retrospective cohort study, a lactate level of more than 2.5mmol/L was the best threshold to predict 28-day mortality among severe sepsis and septic shock patients. In our research, we found mean LC 6 h 3.08mmol/L, and after 48 h mean it is 1.79mmol/L. Significant LC 6 h found, which is 8.08mmol/L in the death group patient where 48 h mmol/L shows significant high. Poor prognosis also presents a clinical increase of lactate level high in the LC 6 h analysis, which is 3.32mmol/L. Recovered patients showed a significant improvement after administering treatment depending on the patient organ involvement and good decrease of lactate reports achieved, which is 1.20mmol/L, where admission reports show it was 1.91mmol/L in LC 6 h. Mean Heart rate 94/51mmhg, pulse 119, temperature 39℃, respiratory rate 32.26, and urine output 456 ml recorded during our study. Death patient shows a remarkable detonation of those reports but has a significant clinical report with the recovered patients. Conclusion: The early lactate dynamic monitoring index has a high value in predicting sepsis and septic shock patients' prognosis, thus worth popularizing.

This study evaluates the historical mean surface temperature (hereafter T2m) and examines how T2m changes over East Africa (EA) in the 21^st century using CMIP6 models. An evaluation was conducted based on mean state, trends, and statistical metrics (Bias, Correlation Coefficient, Root Mean Square Difference, and Taylor skill score). For future projections over EA, five best performing CMIP6 models (based on their performance ranking in historical mean temperature simulations) under the shared socioeconomic pathways SSP2-4.5 and SSP5-8.5 scenarios were employed. The historical simulations reveal an overestimation of the mean annual T2m cycle over the study region with fewer models depicting underestimations. Further, CMIP6 models reproduce the spatial and temporal trends within the observed range proximity. Overall, the best performing models are as follows: FGOALS-g3, HadGEM-GC31-LL, MPI-ESM2-LR, CNRM-CM6-1, and IPSL-CM6A-LR. During the three-time slice under consideration, the Multi Model Ensemble (MME) project many changes during the late period (2080 – 2100) with expected mean changes at 2.4 °C for SSP2-4.5 and 4.4 °C for the SSP5-8.5 scenario. The magnitude of change based on Sen’s slope estimator and Mann-Kendall test reveal significant increasing tendencies with projections of 0.24°C decade-1 (0.65°C decade-1) under SSP2-4.5 (SSP5-8.5) scenarios. The findings from this study illustrate higher warming in the latest model outputs of CMIP6 relative to its predecessor, despite identical instantaneous radiative forcing.

Pseudomonas aeruginosa is an emerging opportunistic pathogen responsible for cystic fibrosis and nosocomial infections. In addition, empirical treatments are become inefficient due to their multiple-antibiotic resistance and extensive colonizing ability. Quorum sensing (QS) plays a vital role in the regulation of virulence factors in P. aeruginosa. Attenuation of virulence by QS inhibition could be an alternative and effective approach to control infections. Therefore, we sought to discover new QS inhibitors (QSIs) against LasR receptor in P. aeruginosa using chemoinformatics. Initially, a structure-based high-throughput virtual screening was performed using the LasR active site that identified 61404 relevant molecules. E-pharmacophore (ADAHH) screening of these molecules rendered 72 QSI candidates. In standard-precision docking, only 7 compounds were found as potential QSIs due to their higher binding affinity to LasR receptor (-7.53 to -10.32 kcal/mol compared to -7.43 kcal/mol of native ligands). The ADMET properties of these compounds were suitable to be QSIs. Later, extra-precision docking and binding energy calculation suggested ZINC19765885 and ZINC72387263 as the most promising QSIs. The dynamic simulation of the docked complexes showed good binding stability and molecular interactions. The current study suggested that these two compounds could be used in P. aeruginosa QS inhibition to combat bacterial infections.

Within the study, magnetic/polyetherimide-acrylonitrile composite nanofibers membrane with effective adsorption of nickel ions in aqueous solution were established, through a simple electrospinning method. Iron oxide nanoparticles were stirred and ultrasonically dispersed into polyetherimide-acrylonitrile solution for homogenous suspension. Afterwards, the polyetherimide-acrylonitrile solution with uniform suspension of iron nanoparticles was used in electrospinning machine to produce uniform and smooth nanofibers composite membrane. The confirmation of nanoparticles incorporation into polymeric membrane were characterized by SEM, EDX, FTIR, XRD and nanoparticles aqueous stability through leach out test. The high adsorption capability of the composite membranes on nickel ions was mainly attributed to the combination of magnetic nanoparticles, polyetherimide-acrylonitrile matrix and nano-sized structure of membrane. Membrane containing magnetic nanoparticles demonstrate the maximum adsorption capabilities (102 mg/g) for nickel ions from aqueous solution. Different kinetics and isotherm models were applied to understand the adsorption behavior during adsorption process, amongst them pseudo second order kinetic and Langmuir isotherm model were well fitted. Additionally, EDX, FTIR and XRD results confirmed the presence of nickel ions onto membrane after adsorption process. Polyetherimide-acrylonitrile composite nanofibers membranes containing magnetic nanoparticles may use as an environmentally-friendly and non-toxic adsorbent for the removal of nickel ions in aqueous medium due to its ease of preparation, easy to use and stability in aqueous medium by retaining the nanoparticles inside the nanofibers membranes.

Without impacting the dental sciences, breakthroughs in technology and applications could not be accomplished. In the advancement of technology and information technology, dentistry and dental materials have been fully active, so much so that they have revolutionized dental techniques. Material & methods; We want to produce the first series of articles in this review on the use of digital techniques and software, such as Smile Concept Digital. The goal is to gather all the findings on the use of this program and to highlight the fields of use. The analysis included forty-nine articles, the latter discussing the use of Digital Smile Design and the area of use. The research aims to classify the dental fields are using "digitization." Change is constant in this field and will be increasing Interest in dentistry by recommending the speed and reliability of outcomes for care planning. Conclusion: As seen in the study, the digital workflow facilitates recovery that is reliable both from an aesthetic and functional point of view. The current area of use of Digital Smile Design techniques in the different branches of medicine and dentistry as well as knowledge have emerged from this research

This study employed 15 CMIP6 GCMs and evaluated their ability to simulate rainfall over Uganda during 1981-2019. The models and the ensemble mean were assessed based on the ability to reproduce the annual climatologyseasonal rainfall distribution, trend, and statistical metrics, including mean bias error, root mean square error, and pattern correlation coefficient. The Taylor diagram and Taylor skill score (TSS) were used in ranking the models. The models performance varies greatly from one season to the other. The models reproduced the observed bimodal rainfall pattern of March to May (MAM) and September to November (SON) rains occurring over the region. Some models slightly overestimated, while some slightly underestimated, the MAM rainfall. However, there was a high rainfall overestimation during SON by most models. The models showed a positive spatial correlation with observed dataset, whereas a low correlation was shown interannually. Some models could not capture the rainfall patterns around local-scale features, for example, around the Lake Victoria basin and mountainous areas. The best performing models identified in the study include GFDL-ESM4, BCC-CMC-MR, IPSL-CM6A-LR, CanESM5, GDFL-CM4-gr1, and GFDL-CM4-gr2. The models CNRM-CM6-1 and CNRM-ESM2 underestimated rainfall throughout the annual cycle and mean climatology. However, these two models better reproduced the spatial trends of rainfall during both MAM and SON. The model spread in CMIP6 over the study area calls for further investigation on the attributions and possible implementation of robust approaches of Machine learning to minimize the biases.

Rare ginsenoside compound K (CK), is an intestinal microbial metabolite with a low natural abundance that is primarily produced by physicochemical processing, side chain modification, or metabolic transformation in the gut. Moreover, CK exhibits potent biological activity compared to primary ginsenosides, which has raised concerns in the field of ginseng research and development as well as ginsenosides-related dietary supplements and natural products. Ginsenosides Rb1, Rb2, and Rc are generally used as a substrate to generate CK via several bio-conversion processes. Current research shows that CK has a wide range of pharmacological actions including boosting osteogenesis, lipid and glucose metabolism, lipid oxidation, insulin resistance, anti-inflammatory, and anti-apoptosis properties. Further research on the bioavailability and toxicology of CK can advance its medicinal application. The purpose of this review is to lay the groundwork for future clinical studies and the development of CK as a therapy for metabolic disorders. Furthermore, the toxicology and pharmacology of CK are investigated as well in this review. The findings indicate that CK primarily modulates signal-ing pathways associated with AMPK, SIRT1, PPARs, WNTs, and NF-kB. It also demonstrates a positive therapeutic effect of CK on nonalcoholic fatty liver disease, obesity, hyperlipidemia, diabetes, and its complications, as well as osteoporosis. Additionally, the analogues of CK showed more bioavailability, less toxicity, and more efficacy against disease states. Enhancing bioavailability and regulating hazardous variables are crucial for its use in clinical trials.

Objective: SARS-Cov-2 infection or COVID-19 is a global pandemic. From the time of identification to till, multiple clinical symptoms and parameters have been identified by the researchers of various countries and regions regarding the diagnosis and presentations of COVID-19 disease. In this manuscript, we investigated the primary symptoms and basic hematological presentations of SARS-CoV-2 infection among the Bangladeshi patients. Methodology: We have collected the disease history of mild to moderate degree of COVID-19 patients; hematological and biochemical on admission reports of moderate degree COVID-19 patients. All of them were tested positive for SARS-CoV-2 by RT-PCR in different institutes in Bangladesh. Results: According to this study though COVID-19 patients in Bangladesh commonly presented with fever, cough, fatigue, shortness of breath, and sore throat, but symptoms like myalgia, diarrhea, skin rash, headache, Abdominal pain/cramp, nausea, vomiting, restlessness, and a higher temperature of >100⁰F have a greater presentation rate and more frequent than other published studies. CRP and Prothrombin time was found to increase in all the patients. Serum ferritin, ESR, SGPT, and D-Dimer were found increased among 53.85%, 80.43, 44%, and 25% patients respectively. 17.39% of the patients had leukocytosis and neutrophilia. 28.26% of patients presented with lymphocytopenia. 62.52% of patients had mild erythrocytopenia. Conclusion: Despite some similarities, our study has evaluated a different expression in presenting symptoms in the case of COVID-19 patients in Bangladesh. CRP, Prothrombin time, serum ferritin, ESR, SGPT, D-Dimer, erythrocytopenia, and lymphocytopenia can be initial diagnostic hematological findings and assessment for prognosis COVID-19 disease. Also, gender variations have a different scenario of clinical and laboratory appearance in this region.

During the 1970s, Tunisian durum wheat landraces were replaced progressively by modern cultivars. These landraces are nowadays maintained by smallholder farmers in some ecological niches and are threatened gradually by extinction resulting on the narrowing of the genetic diversity. This study aims to investigate patterns of phenotypic variability using twelve quantitative traits in a panel of 189 durum wheat landraces and seven checks, based on farmer’s population name attribution and genetic structure. Our results showed high phenotypic variability among and within landraces and checks for the majority of the studied traits. The principal components analysis showed similar grouping using farmers name attribution and genetic structure using K = 6, which confirmed the identification of a new gene pool in the oases of Tunisia, represented by the sub-population Jenah Zarzoura and the robustness and high relationships between phenotypic and genome-wide genetic structure using DArTseq method. These findings will enhance the conservation efforts of these landraces and their use in breeding efforts at national and international levels to adapt to dry conditions.

This study presents PlanteSaine, a novel mobile application powered by Artificial Intelligence (AI) models explicitly designed for maize, tomato, and onion farmers in Burkina Faso. Agriculture in Burkina Faso, like many developing nations, faces substantial challenges from plant pests and diseases, posing threats to both food security and economic stability. PlanteSaine addresses these challenges by offering a comprehensive solution that provides farmers with real-time identification of pests and diseases. Farmers capture images of affected plants with their smartphones, and PlanteSaine's AI system analyzes these images to provide accurate diagnoses. The application's offline functionality ensures accessibility even in remote areas with limited internet connectivity, while its messaging feature facilitates communication with agricultural authorities for guidance and support. Additionally, PlanteSaine includes an emergency alert mechanism to notify farmers about pest and disease outbreaks, enhancing their preparedness to deal with these threats. An AI-driven framework, featuring an image feature extraction phase with EfficientNetB3 and an artificial neural network (ANN) classifier, was developed and integrated into PlanteSaine. The evaluation of PlanteSaine demonstrates its superior performance compared to baseline models, showcasing its effectiveness in accurately detecting diseases and pests across maize, tomato, and onion crops. Overall, this study highlights the potential of PlanteSaine to revolutionize agricultural technology in Burkina Faso and beyond. Leveraging AI and mobile computing, PlanteSaine provides farmers with accessible and reliable pest and disease management tools, ultimately contributing to sustainable farming practices and enhancing food security. The success of PlanteSaine underscores the importance of interdisciplinary approaches in addressing pressing challenges in global agriculture

This study assessed the performance of low-dose CT lung scans across various acquisition parameters and examined the impact of iterative reconstruction (IR) algorithms on image quality for lung cancer screening. The performance of multi-slice CT scanners was assessed by using a Catphan 600 phantom, specifically within the CTP404 test module that contains materials like Teflon, Delrin, Acrylic, Polystyrene, LDPE, PMP, Air, and water. Three protocols were selected and categorized into standard, low dose, and ultra-low dose. The standard protocol featured a tube voltage of 100 kVp for single-detector CT, a pitch of 0.75, detector collimation of 0.60 mm, and a gantry rotation time of 0.33 seconds, with 5 mm slice thickness. Images were reconstructed using standard kernels like B80f and 170f, combined with either FBP or various IR algorithms. Findings indicated that the noise power spectrum (NPS) peak value (HU2mm2) increased with higher IR levels, with FBP showing the highest peak. Additionally, NPS spatial frequency diminished as IR levels rose. Optimizing contrast and spatial resolution for both background and regions of interest involved adjusting the target transfer function (TTF) and contrast-to-noise ratio (CNR), crucial for protocol optimization. Proper adjustment of IR levels is vital, as higher levels can alter image texture and affect NPS spatial frequency. The results of this study showed that the use of IR algorithms in low-dose CT lung scans significantly improved image quality, particularly in terms of noise reduction and spatial resolution. However, the choice of acquisition parameters also played a crucial

Cancer is a devastating disease, causing tremendous morbidity and mortality each year. Cancer can be considered as a genetic disease in the sense that instabilities in protooncogenes and tumor suppressor genes are among the hallmarks of cancer progression and metastasis. However, a particular cancer can express different proteins in different patients, making cancer a heterogeneous disease. This heterogeneity in part influences treatment resistance and failure. Therefore, it is crucial to understand the mechanism by which cancer cells develop and enhance resistance to different agents. This review aims to present the general paradigm and recent updates on cancer cell resistance to different antitumor agents. It demonstrates that tumor resistance results from a myriad of factors, including tumor microenvironment, supporting immune cells, and cancer stem cells. This interaction contributes to cancer cells overcoming the therapeutic effects of different classes of antitumor agents, such as cytotoxic chemotherapeutics, targeted agents, and immunotherapies. With the development of advanced molecular analysis, specialized genomic assessment has assisted clinicians and researchers in choosing selected agents combating cancer cells. Together, this approach can potentially reduce treatment toxicity, health system burden, and financial costs while improving patient quality of life. Understanding the exact mechanism of drug resistance in cancer cells can open the way to new effective and less toxic therapeutics.

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.

Background: The SARS-CoV-2 virus is a new highly pathogen virus that can suppress cell immune response (Poly ADPR process, and interferon releasing in infected cell) by viral macrodomain and create fatal pneumonia. Cytokine storm phenomenon which can create consequence of SARS COV-2 by increase of the performance of human TRPM2, is a dangerous condition for human and its body organ such as kidney, heart, and liver. it seems like prevention of beginning of these events is necessary. Material and methods: in this study drug and drug like database was used for inhibition of the viral macrodomain and human TRPM2 that can initiate of the viral cell cycle infection and human cytokine storm respectively. Ligand base drug designed, pharmacophore modeling, docking and molecular dynamic simulation was performed Results: among up to billion compounds, 20 compounds were screened by infinisee program. Then 7 compounds were selected by pharmacophore modeling. between 7 compounds, 5 compound was removed because of high similarity to ADPR and possibility of toxic effect for human RNA and DNA polymerase. One compound was losartan and selected for docking and molecular dynamic simulation. Conclusion: losartan earned a proper dock score and binding affinity to create the complexes with TRPM2 and macrodomain. Molecular dynamic simulation has shown losartan had an adequate binding free energy for human trpm2 and viral macrodomain. The inhibitory effect of losartan on these protein has shown and it could interfere in several points (PARP, PARG- macrodomain and TRPM2) and decreases oxidative stress, apoptosis, cytokine storm in COVID-19.

The urinary tract infection (UTI) is the most common bacterial infection, especially in women. The increased incidence of UTIs, at the last decades have paralleled with the growing emergence of antibiotic resistance. The aim is to evaluate aqueous garlic extract (AGE) susceptibility against multidrug-resistant (MDR) bacteria isolated in urine of women. The investigation of antibacterial propriety and time kill effect of AGE was performed by the well method, microdilution method and spectrophotometer assay. Antibiotics susceptibility assay revealed that the nine MDR bacteria had high resistance against Amoxicillin/ clavulanic acid (100%) and Erythromycin (100%), Cefotaxime (83.33%) and Ceftazidime (83.33%). AGE exhibited potent antibacterial activity against the nine MDR bacteria tested. In Gram-negative bacteria, the inhibition diameters ranged from 20 ± 3 to 32 ± 4 mm, with Minimum Inhibitory Concentrations (MICs) ranging from 10% to 12.5% (w/v) and Minimum Bactericidal Concentration (MBCs) was 12.5 % (w/v). Gram-positive bacteria exhibited diameters ranging from 38 ± 2 to 45 ± 1 mm; MIC and MBC values ranged from 05 to 10 % (w/v) and were found more susceptible than Gram-negative bacteria. To conclude, this investigation shown that AGE have high potential antibacterial to use as an alternative to treat women UTIs.

The efficacy of an intranasal (IN) bovine respiratory syncytial virus (BRSV) administered in the face of passive immunity was assessed. Pooled colostrum was administered by intubation to fifty (50) beef-dairy crossbred calves the day they were born. The calves were transported to a research facility and were blocked by age and sex and randomly assigned into two groups, a sham-vaccinated intranasally with a placebo (sterile water) or vaccinated with a tri-valent modified live viral (MLV) vaccine. The calves were 92 days old when vaccinated (day 0). The calves were challenged by aerosolized BRSV on day 80 and day 81 as a respiratory challenge. The study was terminated on day 88. Lung lesion scores (LLS) were significantly lower for calves vaccinated with tri-valent MLV vaccine than those for calves that were sham-vaccinated. Serum neutralization (SN) antibody against BRSV in calves vaccinated with the tri-valent MLV vaccine demonstrated an anamnestic response on day 88. After challenge, the calves sham-vaccinated with the placebo lost weight while those vaccinated with the tri-valent MLV vaccine gained weight. In this study colostrum-derived antibodies did not interfere with the immune response or protection provided by one dose of the tri-valent MLV vaccine.

In the realm of artificial intelligence (AI), generative systems, most notably Midjourney, have tremendous power to generate creative images of buildings and sites of Islamic architectural heritage through text-to-image generation based on the internet. The AI-generated representations have significant potential for architects, specialists, and common users. However, the system has considerable limitations when generating images for some buildings and sites where the representations appear too far from their original represented structures. This research article attempts to answer the question: What are the limitations of using the AI system of Midjourney in producing images similar to the original buildings and sites of the Islamic architectural heritage? The research employs prompt engineering techniques based on historical sources as inputs to examine the accuracy of the output of the AI-generated images of selected examples of structures of the Islamic tradition. It compares the output with the original look by employing direct observation and critical analysis of human intelligence (HI). It categorizes these limitations into four groups: (1) limits of the prompt, (2) limits of fame, (3) limits of regionality and historical styles, and (4) limits of architectural elements and details. It concludes that while Midjourney has great capability to represent high-end AI-generated images inspired by the Islamic tradition, it currently falls short of presenting the actual appearance of some of their original structures.

In this investigation magnetic γ-Al2O3 ceramic nanocomposite particles bearing epoxide functionality are prepared following a multistep process. The ultimate nanocomposite particles are named as γ-Al2O3/Fe3O4/SiO2/poly(glycidyl methacrylate (PGMA). The surface property is evaluated by carrying out the adsorption study of Remazol navy (RN), a model reactive azo dye, on both γ-Al2O3/Fe3O4/SiO2 and γ-Al2O3/Fe3O4/SiO2/PGMA nanocomposite particles. The adsorption is carried out at the point of zero charge (PZC) to neutralize the effect of particle surface charge. The adsorption rate is very fast, reached equilibrium (qe) value within five min. Due to mesoporous structure of silica layer γ-Al2O3/Fe3O4/SiO2 nanocomposite particles possessed relatively higher specific surface area and magnitude of adsorption is dependent on the total specific surface area. The introduction of epoxide functionality favored high adsorption capacity in mass per unit surface area. The adsorption process strictly followed Langmuir model. Thermodynamic equilibrium parameters implied that irrespective of surface functionality the adsorption process is spontaneous and exothermic. Pseudo-second-order rate kinetic model is more appropriate to explain the adsorption kinetics.

The study investigated farmers’ perception on pests and diseases management strategies, agricultural practices, production constraints and selection criteria of elite varieties using a survey research design. A total of 700 questionnaires were administered to smallholder farmers who were farming for household consumption, those producing for sale and household consumption and those who were mainly producing for sale because their primary goal was to produce for the market. Findings revealed that the most prevalent pests identified were whiteflies (Bemisia tabaci), grasshoppers (Zonocerus variegatus), aphids (Aphis gossypii), mealybugs (Phenacoccus manihoti), termites (Isoptera), and grasscutters (Thryonomys swinderianus). The three most common diseases of cassava limiting growth and yield with mixed infection include viral, bacterial, and fungal. The study also revealed that only 12.5% of farmers cultivated improved cassava varieties. The management practices implemented encompassed field sanitation and the application of pesticides. Lack of capital and no availability of market were the most important production and marketing constraints faced by farmers in the study area, whereas poundability and high storage root yield are the most preferred traits farmers consider in selecting a new variety. Results suggest that smallholder farmers should endeavor to undergo various developmental programs to develop themselves to increase their competitive advantage in their locality and in the local and global agricultural sectors. In addition, governments and other policy makers should strategize plans and programs that would contribute to smallholder farmers’ agriculture, community and national development.

The leaf essential oils from five Eucalyptus spp.: E. astringens, E. camaldulensis, E. lehmanii, E. leucoxylon and E. sideroxylon growing in the same plantation area and conditions (plants with the same age and subjected to the same agronomic practices) were analyzed and evaluated for their antimicrobial activity. The essential oil yields ranged from 0.14 to 0.96% (w/w), and their chromatographic profiles were resolved into 48 compounds; among them, 11 were common to all essential oils. Terpenoids (oxygenated mono, and sesquiterpenes) dominated (55.66-76.67%) the oil profiles. Although 1,8-cineole (21.97-50.93%) was found as the main oxygenated monoterpene in all examined essential oils, principal component analysis observed and confirmed an interspecific chemical variability. Additionally, a set of distinctive chemical markers that could serve as a reliable tool for discrimination of Eucalyptus species and for authentication and quality control purposes (for commercial samples) has been defined for each essential oil. The antimicrobial disc-diffusion assay results revealed that all essential oils were endowed with a strong antimicrobial activity, with those derived from E. camaldulensis, E. lehmanii and E. leucoxylon being the most active.

Abstract: Insecure and portable devices in the smart city’s Internet of Things (IoT) network are increasing at an incredible rate. Various distributed and centralized platforms against cyber-attacks have been implemented in recent years, but these platforms are inefficient due to their constrained levels of storage, high energy consumption, the central point of failure, underutilized resources, high latency, and etc. In addition, the current architecture confronts the problems of scalability, flexibility, complexity, monitoring, managing & collecting of IoT data, and defend against cyber-threats. To address these issues, the author presents distributed and decentralized Blockchain-Software Defined Networking (SDN) based energy-optimized architecture for IoT in smart cities. Thus, SDN continuous observing, controlling, managing IoT devices activities and detect possible attacks in the network; Blockchain provides adequate security & privacy against cyber-attacks, reduces the central point of failure issues; Network Function Virtualization (NFV) are used to saving energy, load balancing, as well as increasing the lifetime of the entire network. Also, we introduce a Cluster Head Selection (CHS) algorithm to reduce the energy consumption in the presented model. Finally, we analyze the performance using various parameters (e.g. throughput, response time, gas consumption, communication overhead) and demonstrating the result that provides higher throughput, lower response time, lower gas consumption than existing works for smart cities.

Elbow dislocation and instability present significant clinical challenges, necessitating a thorough understanding of the underlying bio-mechanical mechanisms. In this study, a quasi-static three-dimensional finite element model of the human elbow joint is developed to investigate stress distribution and stages of dislocation in the human elbow under various loading conditions. The model simulates the elbow joint in different degrees of flexion (30°, 45°, 60°, and 90°) and forearm positions (pronation and supination), providing detailed insights into the progression of dislocation. Significant findings include the identification of high stress concentrations on the humerus at 90° flexion and on the radial and coronoid processes at 30°, 45°, and 60° flexion. Three reproducible stages of dislocation were observed, particularly in flexed positions with forearm pronation or supination. These stages align with experimental observations and highlight the initial occurrence of bony failures, such as radial head and ulnar coronoid fractures, preceding soft tissue tears. Clinically, the study underscores that early-stage low-impact posterior elbow dislocations retain enough stability to be managed with closed reduction and early mobilization. However, as dislocations progress, significant damage to the medial and lateral collateral ligaments is expected, necessitating more invasive treatments. This research provides valuable bio-mechanical insights into elbow dislocation, aiding in the development of improved treatment strategies and enhancing patient outcomes through precise and timely clinical interventions. The validated FEM serves as a powerful tool for pre-surgical planning offering a comprehensive understanding of elbow joint mechanics.

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, with septic cardiomyopathy being a common and severe complication. Despite its significant clinical impact, the molecular mechanisms underlying sepsis-induced cardiomyopathy (SICM) remain incompletely understood. In this study, we performed a comparative analysis of whole transcriptome profiles in two widely used mouse models of septic cardiomyopathy, the cecal ligation and puncture (CLP) model and the lipopolysaccharide (LPS) model. Our aim was to identify key genes and pathways involved in the development of septic cardiomyopathy and to evaluate the similarities and differences between the two models. Our findings suggested that 1) both methods can induce septic heart dysfunction within 24 hours; 2) distinct whole transcriptome expression profiles are revealed; 3) potentially different pathways are involved in causing heart failure in sepsis. The comprehensive comparison provides valuable insights into the molecular basis of septic cardiomyopathy and contributes to the ongoing search for effective treatment strategies, triggered by different factors for SICM.

Background Acute right heart failure (RHF) is associated with high morbidity and mortality. Temporary mechanical circulatory support (tMCS) is now part of the advanced management strategy for refractory cardiogenic shock (CS). Among such support systems, VA-ECMO remains the fastest MCS system to set up. The ProtekDuo cannula can be used as a temporary and percutaneous right ventricular assist device (RVAD) in relay with VA-ECMO in the context of prolonged weaning. Case Summary This case report describes the clinical course of a 69-year-old patient who underwent elective aortic valve replacement surgery complicated by acute RHF due to iatrogenic ligation of the right coronary artery. VA-ECMO was initiated in the context of refractory cardiogenic shock. Faced with prolonged MCS weaning, due to lack of recovery of the right ventricle associated with the absence of any other therapeutic option, a percutaneous RVAD via a ProtekDuo cannula was implanted as a bridge to recovery. The ProtekDuo was gradually weaned while the patient began rehabilitation. The patient was transferred to the medical ward after 5 weeks in the ICU, stayed 5 months in an acute medical setting, went to a rehabilitation center afterward and returned home 6 months after the initial surgery without any neurological sequalae or organ failures. In total, she remained on MCS for 39 days (21 on VA-ECMO and 18 on ProtekDuo). Discussion In cases of refractory RHF, after stabilization and organ perfusion restoration under VA-ECMO, it is feasible to switch to a percutaneous RVAD, allowing early mobilization of patients during prolonged MCS weaning until the right ventricle adapts to new loading conditions.

The present study analyzed seasonal (i.e., Dec-Jan [DJF] and June – August [JJA]) temperature change for the near (2025-2054) and far future (2070-2099) under SSP245, SSP370, and SSP585 scenarios over Pakistan. The anomalies, Mann-Kendall trend tests, Sequential Mann-Kendall trend test (SQMK), and probability density frequency (PDF) analysis were used to investigate future mean temperature variations. The DJF season projected higher increase in temperature in the northern (3.8 ^oC, 5.1 ^oC and 6.5 ^oC), followed by central regions (3.8 ^oC, 4.9 ^oC and 6.4 ^oC) under SSP245, SSP370 and SSP585 scenarios, respectively. The central region is likely to record significant increase in JJA (3.0 ^oC, 4.4 ^oC and 5.4 ^oC) mean temperature in far future under the given SSP scenarios. Compared to historical (PDF), the far future DJF temperature changes revealed significant higher warming over northern, central and then over southern regions under most of SSP scenarios. The southern regions are projected to possible rise in far future JJA temperatures by 2.7 ^oC, 3.3 ^oC and 4.3 ^oC, under SSP245, SSP370 and SSP585, respectively. The PDFs for JJA further verify the highest positive abrupt shift in temperature across the central region and then southern region. The future diverse seasonal temperature changes supports further examination of the associated mechanisms and factors responsible for temperature changes to address climate change.

Reaction of 2-mercapto-3-phenylquinazolin-4(3H)-one (MPQ) with both 4-vinyl benzyl chloride and allyl bromide furnished the reactive heterocyclic monomers 3-phenyl-2-((4-vinylbenzyl) thio) quinazolin-4(3H)-one (PVTQ) and 2-(allylthio)-3-phenylquinazolin-4(3H)-one (APQ), respectively. Copolymerization of PVTQ monomer with styrene and methyl methacrylate in the presence of 2,2′-azobisisobutyronitrile (AIBN) afforded the copolymers PS-co-PPVTQ and PMMA-co-PPVTQ, respectively. Similarly, copolymerization of monomer APQ with styrene and methyl methacrylate (MMA) afforded the copolymers PS-co-PAPQ and PMMA-co-PAPQ, respectively. The resulted copolymers were characterized by using FT-IR, 1H-NMR and GPC techniques. Silver nanocomposites of PS, PMMA, PS-co-PPVTQ, PMMA-co-PPVTQ, PS-co-PAPQ and PMMA-co-PAPQ were synthesized by the addition of silver nitrate into the polymer solution. The reduction of silver ions into silver nanoparticles was performed in DMF and water. Thermogravimetric (TGA) analysis was used to determine the thermal stability of the copolymers and their silver nanocomposites. The X-ray diffraction (XRD) analysis indicated the amorphous structures of the co-polymers and confirmed the formation of silver nanoparticles. The antitumor and antibacterial activities were screened for the copolymers and enhanced by the formation of their silver nanocomposites. In vivo antitumor activity in Ehrlich Ascitic Carcinoma (EAC) mice model showed that PS-co-PPVTQ/Ag NPs, PMMA-co-PPVTQ/Ag NPs, and PMMA-co-PAPQ/Ag NPs displayed promising inhibitory effects against EAC and induce apoptosis against MCF-7 cells.

Dearth of information on extent of genetic variability in cassava limits the genetic improvement of cassava in Sierra Leone. This study aimed at assessing the genetic variability and relationships within 103 cassava genotypes using agro-morphological and culinary markers. A field trial was conducted in the School of Agriculture and Food Sciences research site. The experiment was laid in an augmented randomized block design. Morphological classification based on qualitative and quantitative traits categorized the germplasm into three different groups. A total of ten principal components (PCs) in the qualitative and six PCs in the quantitative trait sets accounted for 66.74% and 67.27% of the total genetic variation, respectively. Traits with significantly strong and positive correlations included presence of fruit (PFRT) and presence of seed (PSE)(r = 0.86***),root yield per plant (RYPP) and number of storage root (NSR) (r = 0.76***), RYPP and number of commercial root (NCR) (r = 0.68***), length of leaf lobe (LLL) and width of leaf lobe (WLL) (r = 0.66***),and between NSR and NCR (0.84***). Cooking time, cooking percentage, texture, mealiness, taste and aroma varied widely among the accessions. Findings established that the cassava germplasm possess useful genetic variability that could be exploited through selection for short term release programme, genetic conservation of valuable germplasm and genetic improvement of the crop.

Considering the important demand of fresh water and its scarce availability, water desalination is an interesting technology, producing about 44 Mm³/year worldwide, but, in general the most common desalination techniques are highly energy demanding. Freezing-Melting (F/M) desalination uses just up to 70% less thermal energy, but is the least used process mainly, due to the difficulty of the salt separation. This study proposes a model able to analyses the thermodynamic potential that allows the salt diffusion during the F/M process, using an aqueous solution of sodium chloride. This should allow to obtain a sensitive analysis of the process to promote the separation between the high concentration brine and the ice with liquid separation by physical process. The unidimensional model is based on the evolution of both processes: thermal and mass diffusions, depending on temperature and saline gradients, predicting whether the salt will remain inside the ice or not. Thus, the thermal potential is adjusted to frozen only when the salt has been "pushed" towards the brine. Mostly models have base their results on the assumption of a “certain value of saline concentration of the liquid fraction”, value in which there is great disagreement. In this paper the calculations are based on the concentration in the solid-liquid interface, which has been extensively studied and there is a coincidence in those results, being the main advantage of the proposed model.

Adhesion of polymers to surfaces is of upmost importance in timely applications such as protective coatings, biomaterials, sensors, new power sources and soft electronics. In this context, this work examines the role of molecular interactions in the adhesion of polypyrrole thin films to flexible Indium Tin Oxide (ITO) electrodes grafted with aryl layers from various diazonium salts, namely 4-carboxybenzenediazonium (ITO-CO₂H), 4-sulfonicbenzenediazonium (ITO-SO₃H), 4-N,N dimethylbenzenediazonium (ITO-N(CH₃)₂), 4-aminobenzenediazonium (ITO-NH₂), 4-cyanobenzenediazonium (ITO-CN) and 4-N-phenylbenzenediazonium (ITO-NHPh). It was demonstrated that PPy thin layers were adherent to these surfaces, whereas adhesion failure was noted on bare ITO, following simple solvent washing or sonication. Adhesion of the polypyrrole was investigated in terms of the hydrophilic/hydrophobic character of the underlying aryl layer as probed by contact angle measurements. It was found that sulfonic acid doped polypyrrole (PPy-BSA) thin films were preferably deposited on the most hydrophobic surfaces. More importantly, the redox properties and electrochemical impedance of PPy were closely related to the hydrophobic character of the aryl layers. This work demonstrates that diazonium compounds are unique molecular glues for conductive polymers, and permit to tune their interfacial properties. With diazonium-based robust, architectured interfaces, one can design high performance materials for e.g.sensors, printed soft electronics and flexible thermoelectrics.

Climate change (CC) poses severe consequences, particularly in sub-Saharan Africa, where poverty rates may escalate by 2050 without significant climate and development action. The health impacts are diverse, encompassing communicable and non-communicable diseases. Mozambique, a climate-vulnerable nation, has experienced significant natural disasters in the past 42 years, impacting its health system. This study aims to assess Mozambique’s health sector vulnerability and adaptation needs to climate change. Following a methodology proposed by the World Health Organization and Intergovernmental Panel for Climate Change, a six-step vulnerability and adaptation assessment was conducted. The Health Vulnerability Index (HVI), integrating historical climate, epidemiological, and socio-economic data at the district level (n=162), was computed using exposure, sensitivity, and adaptive capacity dimensions. The Results revealed spatial patterns in exposure to climate variables, extreme weather events, and variations in sensitivity and adaptive capacity across the country. The HVI mirrored the exposure findings. Notably, high vulnerability was observed in several districts, while major urban centers displayed lower vulnerability. These findings highlight the country’s vulnerability to climate change and underscore the potential for adverse impacts on livelihoods, the economy, and human health. The study provides a foundation for developing strategies and adaptation actions.

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.

Salinity is one of the major factors responsible for the deterioration of soils, making them unsuitable for agriculture. The application of halotolerant and halophilic plant growth promoting bacteria (PGPR: Plant Growth Promoting Rhizobacteria) with biological control activities as an inoculant of cultivated plants offers a biological alternative to the use of agrochemicals, particularly when subjected to salt stress. In this perspective, 70 bacterial strains were isolated from saline soils (sebkha) in arid and semi-arid areas of eastern Algeria. Three isolates were selected based on their ability to produce bioactive molecules allowing them to promote plant growth, such as hydrolytic enzymes, indole acetic acid, HCN, NH3, etc. Two of these isolates belong to the genus Serratia and the third is a halophilic Halomonas bacteria. These bacteria were identified based on the 16S rDNA sequence. Antagonism tests against phytopathogenic fungi were carried out. The identification of the antifungal molecules produced by these bacteria was done by high performance liquid chromatography. These bacteria are capable of inhibiting mycelial development against phytopathogenic fungi with rates reaching 80.67% against Botrytis cinerea, 76.22% against Aspergillus niger and 66.67% against Fusarium culmorum for Serratia sp. The strain Halomonas sp. inhibited mycelial growth by production of volatile substances of Aspergillus niger at 71.29%, Aspergillus flavus at 75.49% and Penicillium glabrum at a rate of 72.22%. The identification by HPLC of the antifungal molecules produced by these three bacteria reveals that they are polyphenols, which makes these strains the first rhizobacteria capable of producing phenolic compounds. Finally, pot tests to determine the effectiveness of these strains in promoting wheat growth under salinity stress (125 mM, 150 mM and 200 mM) were carried out. The results revealed that a consortium of two isolates (Serratia sp. and Halomonas sp.) performed best at 125 mM. But, at higher concentrations it was the halophilic bacteria Halomonas sp which gave the best result. In all cases, there was a significant improvement in the growth of wheat seedlings inoculated with the bacteria, compared to non-inoculated controls.

Amyotrophic Lateral Sclerosis (ALS) is a prototypical neurodegenerative disease characterized by progressive degeneration of motor neurons to severely effect the functionality to control voluntary muscle movement. Most of the non additive genetic aberrations responsible for ALS make its molecular classification very challenging along with limited sample size, curse of dimensionality, class imbalance and noise in the data. Deep learning methods have been successful in many other related areas but have low minority class accuracy and suffer from the lack of explainailbilty when used directly with RNA expression features for ALS molecular classification. In this paper we propose a deep learning based molecular ALS classification and interpretation framework. Our framework is based on training a convolution neural network (CNN) on images obtained from converting RNA expression values into pixels based on DeepInsight similarity technique. Then we employed Shapley Additive Explanations (SHAP) to extract pixels with higher relevance to ALS classifications. These pixels were mapped back to the genes which made them up. This enabled us to classify ALS samples with high accuracy for a minority class along with identifying genes that might be playing an important role in ALS molecular classifications. Taken together with RNA expression images classified with CNN, our preliminary analysis of the genes identified by SHAP interpretation demonstrate the value of utilising Machine Learning to perform molecular classification of ALS and uncover disease-associated genes.

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.

Thymic stromal lymphopoietin (TSLP) is a cytokine and is closely related to Interleukin (IL) - 7, and hTSLP can activation through the human thymus dendritic cell in thymic to indirectly promote the differentiation of natural Regulatory T cells (Tregs) of the thymus. In this study, we focused on recombinant TSLP to determine its effects on the differentiation of CD4+CD25-T cells separated from the thymus of myasthenia gravis (MG) patients. Our results demonstrated that exogenous TSLP could increase CD4+CD25+T/CD4+T cells ratio, up-regulate the expression of Foxp3 mRNA and protein expression in CD4+CD25+Treg cells. Furthermore, we found that CD4+CD25+ Treg cells induced by exogenous TSLP could secrete IL - 10, Transforming growth factor (TGF) - β and the ability to inhibit CD4+T cell proliferation improved. These results indicate that TSLP may promote the differentiation of thymic CD4+CD25-T cells of MG patient to CD4+CD25+Foxp3+ regulatory T cells and enhance the function of immune suppression.

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.

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.

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 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.

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.

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.

In this paper, we introduce a specialized, fully automated experimental arrangement designed for assessing the effectiveness of augmented and virtual reality technologies in healthcare setting and explore its design principles focusing on depth sensor characterization. The main goal of this project is to establish a robust benchtop platform for the quantitative evaluation of extended reality technologies in a controlled environment, emphasizing the practical assessment of augmented reality head-mounted devices. We outline a design concept and considerations for an experimental configuration aimed at creating a realistic testing environment. This apparatus comprises an observation platform mounted on a three-degree-of-freedom motorized system and a test phantom stage. Focusing on real-case scenarios, we utilized a range of sensors, including readily available range-sensing cameras and commercial augmented reality headsets, such as the Intel RealSense L515 LiDAR camera, mounted on the motion control system. The setup enabled automated data collection and facilitates controlled assessments and validation of various facets of augmented reality technologies, including object, hand, and head tracking, as well as static and dynamic image registration. This paper describes the system architecture, the process of automated data collection, and presents several evaluation studies conducted with this setup, providing insights into the quality and temporal noise associated with static or moving objects or observers in augmented reality applications.

Objective: To investigate the effects and mechanisms of different concentrations of CCCP on mitophagy in human peripheral blood regulatory T cells. Methods: Tregs were isolated, identified and then grouped, treating with CCCP at a concentration of 2.5 μM, 5 μM, 10 μM, 20 μM and 40 μM for 24h in an incubator. Flow cytometry detected the reactive oxygen species (ROS), mitochondrial membrane potential (MMP), mitochondrial quality, and fluorescence microscopy observed the co-localization of mitochondria and lysosomes in each group. Results: The purity of CD4⁺CD25⁺Tregs was (93.36 ± 1.87) %. With the increase of CCCP concentration, the level of ROS gradually increased, while the MMP decreased gradually. About the mitochondria and lysosome fusion, the fluorescence intensity of orange (yellow) was the highest when the concentration of CCCP was in the range of 5-10 μM while decreased with the CCCP concentration continually increasing. The mitochondrial quality decreased with the increase of CCCP concentration. However, there was no significant difference between groups C, D and E. The mitochondrial quality of groups F and G were significantly lower than that of group E. Conclusions: With the concentration of CCCP gradually increased, the level of ROS in Treg cells increased, and MMP decreased, which promoted the mitophagy, mitochondrial quality maintains homeostasis; When ROS accumulated, and MMP decreased significantly, the mitophagy was inhibited, and the mitochondrial quality was significantly decreased.

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.

Intermetallic compounds are increasingly being expected to utilize in tribological environments, but to date the works are hindered by insufficient ductility at low and medium temperature. This paper presents a novel multiphase intermetallic alloy with the chemical composition of Mo-40Ni-13Si (at.%). Microstructure characterization reveals that a certain amount of ductile Mo phases formed during the solidification process of ternary Mo-Ni-Si alloy melt, which is undoubtedly beneficial to the ductility improvement of intermetallic alloy. Tribological properties of the designed alloy, including wear resistance, friction coefficient and metallic tribological compatibility, were evaluated under dry sliding wear test conditions at room temperature. Results suggested that the multiphase alloy possesses an excellent property for room-temperature wear applications, which is attributed to the unique microstructural features and thereby good combination in hardness and ductility. The corresponding wear mechanism is also reported by observing the worn surface, subsurface and wear debris of alloy, which to be found is soft abrasive wear.

With the integrated development of the Internet, wireless sensor technology, cloud computing, and mobile Internet, there has been a lot of attention given to research about and applications of the Internet of Things. A Wireless Sensor Network (WSN) is one of the important information technologies in the Internet of Things; it integrates multi-technology to detect and gather information in a network environment by mutual cooperation, using a variety of methods to process and analyze data, implement awareness, and perform tests. This paper mainly researches the localization algorithm of sensor nodes in a wireless sensor network. Firstly, a multi-granularity region partition is proposed to divide the location region. In the range-based method, the RSSI (Received Signal Strength indicator, RSSI) is used to estimate distance. The optimal RSSI value is computed by the Gaussian fitting method. Furthermore, a Voronoi diagram is characterized by the use of dividing region. Rach anchor node is regarded as the center of each region; the whole position region is divided into several regions and the sub-region of neighboring nodes is combined into triangles while the unknown node is locked in the ultimate area. Secondly, the multi-granularity regional division and Lagrange multiplier method are used to calculate the final coordinates. Because nodes are influenced by many factors in the practical application, two kinds of positioning methods are designed: the unknown node is in the positioning unit or not. When the unknown node is on the side of the positioning unit, we use the method of vector similarity. Moreover, we use the centroid algorithm to calculate the ultimate coordinates of unknown node. When the unknown node is not on the side of the positioning unit, we establish a Lagrange equation containing the constraint condition to calculate the first coordinates. Furthermore, we use the Taylor expansion formula to correct the coordinates of the unknown node. In addition, this localization method has been validated by establishing the real environment.

The electroencephalogram (EEG) is a record of brain activity. Brain Computer Interface (BCI) technology formed by the EEG signal has become one of the hotspots at present. How to extract the feature signal of EEG is the most basic research of BCI technology. In this paper, A new method of recognizing fatigue, conscious, concentrated state of human brain is proposed by the combination of discrete wavelet transform and the neural network based on EEG signal. First of all, the law signal is preprocessed by the wavelet denoising method because the law EEG signal contains a large number of high frequency noise, which is decomposed into multi-layer high frequency signal and low frequency signal. thus, δ wave, θ wave, α wave, β wave are obtained by the wavelet transform. And then, frequency band energy of the different wave is regards as the feature signal of EEG. In the experiment, the feature signal is classified by radial basic function (RBF) and annealed chaotic competitive learning network (ACCLN). RBF and ACCLN networks are trained with 500 sets of sample data and are tested by 100 sets of samples in different mental states. The experimental results show that the average accuracy of RBF network under three conditions are 88.75%, 88.25%, 88.5%, respectively, and the correct rate of ACCLN network is 97%, 98%, 98%, respectively.

Early discharge after childbirth has led to a rise in neonatal readmission, becoming a major concern in recent decades. Our research aimed to identify the risk factors and incidence of neonatal readmission, as well as explore preventive measures. Our study at the Clinical Hospital of Pediatrics in Ploiești, Romania included 108 neonates admitted during the neonatal period. This accounted for 2.06% of all admissions (5226). The most prevalent cases were malnutrition (25%), fever (20.3%) and bronchiolitis (17.5%). Diarrhea and infectious gastroenteritis were also observed (14.8%), along with acute rhinoconjunctivitis (9.2%) and late onset sepsis (3.7%). No deaths were recorded. The most significant characteristics identified were number of children (p&lt;0.001) and age at maternity discharge (p&lt;0.001). By following the prevention rules, malnutrition, feeding errors, and infections can be avoided. This includes practicing proper hand hygiene for both mothers and medical staff, as well as educating and demonstrating to mothers the benefits of breastfeeding. In addition, all newborns discharged from the maternity ward should benefit from follow-up at 7-10 days of life. Our results confirm the effectiveness of a multidisciplinary team and endorse promoting breastfeeding. Implementing quality control measures and regularly evaluating the surveillance program will help improve its effectiveness.