Search

Abstract Background The potential of phytoremediation using garlic monoculture (MC) and intercropping (IC) system with perennial ryegrass to enhance the uptake of cadmium (Cd), chromium (Cr), and lead (Pb) were investigated. Results Positive correlations were found between MC and IC systems, with varying biomass. Production of perennial ryegrass was affected differently depending on the type of toxic metal present in the soil. Root growth inhibition was more affected than shoot growth inhibition. The total biomass of shoot and root in IC was higher than MC, increasing approximately 3.7 and 2.9 fold compared to MC, attributed to advantages in root IC crop systems. Photosystem II efficiency showed less sensitivity to metal toxicity compared to the control, with a decrease between 10.07–12.03%. Among gas exchange parameters, only Cr significantly affected physiological responses by reducing transpiration by 69.24%, likely due to leaf chlorosis and necrosis. Conclusion This study exhibited the potential of garlic MC and IC with perennial ryegrass in phytoremediation. Although the different metals affect plant growth differently, IC showed advantages over MC in term biomass production.

Growing literature on cash holding and managerial ability provides the idea of studying these two concepts in the context of the same model. The effect of cash holding on firm performance is established in this study, which also looked at the moderating effect of managerial ability on the direct relationship between cash holding and firm performance—analyzing 2,858 Chinese non-financial firms, we employ OLS, fixed effect, and robust standard error regression to test the formulated hypotheses. We employ several additional tests to confirm the robustness of our findings. This study offers compelling evidence that managerial ability significantly impacts the relationship between cash holding and firm performance. We show that cash holdings boost the operating performance of firms with exceptional managers. Therefore, managerial expertise is essential when considering the cash and performance relationship. Prior studies focus on the direct relationship between cash holdings and firm performance. However, managerial ability, which is a crucial factor and an effect that affects this relationship, is overlooked. This study shows that firms with highly able managers boost their performance by holding more cash.

Pharmacotoxicology is one of the fields that in recent years is growing exponentially, further reaffirming its proven usefulness in the field of forensic sciences. An interesting goal in this field is to identify and quantify the cause of death. This review paper aims to represent a review of the literature in order to evaluate the state of the art regarding the research in the pharmacotoxicology field in cases of Sudden Cardiac Death (SCD), a frequent problem on several occasions, which can be derived from the use of fatal substances or in such concentrations causing sudden death.In this overview, the most frequently observed biomarkers for SCD were found to be ethanol, illicit drugs, antidepressants, and some common compounds like caffeine and Trenbolone. Concurrently, the most applied instrument configurations is represented by hyphenated liquid (or gas) chromatographic tools coupled with mass spectrometry (LC-MS or GC–MS) in order to reach the high accuracy and confidence levels in the confirmatory analyses, preceded by common sample preparation technique as solid-liquid extraction or liquid-liquid extraction. It was interesting to understand the approaches by which researchers have approached the topic, because on the one hand there are those who have been interested in the comparison between matrices (conventional and not) and on the other hand, who has researched metabolites in order to be able to trace the intake or not of a substance.In particular, this work want to highlight and evaluate, from a medical-legal point of view, which are the main biomarkers and physiological markers of forensic interest and the methods, and instrumental procedures most frequently used for their evaluation. The paper is organized considering the analytical methods divided by types of drugs/substances.

The present study focuses on the isolation of bacterial pathogens from waste disposal sites, and examination of their efficiencies for degrading various plastics. Seven bacterial isolates such as E. coli, Corynebacterium spp., Micrococcus spp., Azotobacter spp., Pseudomonas spp., Staphylococcus spp., and Bacillus spp. were identified. Bacillus spp. exhibited the highest percentage reduction in black plastic weight (47.46 %), while Corynebacterium spp., and E. coli achieved a maximum reduction of 45.76 and 46.42 % for pink plastic respectively. Pseudomonas spp. and Micrococcus spp. demonstrated notable reductions of 46.43 % and 56.60 % in white and Canteen Stores Department (CSD) biodegradable plastics, respectively. Optical density (OD) measurements revealed that bacterial isolates achieved maximum OD values with CSD plastics, emphasizing their proficiency in plastic degradation. Fourier Transform Infrared Spectroscopy (FTIR) confirmed the degradation process, with a decrease in the peak value from 2916 to 2914 cm⁻1 for pink plastic, signifying alkane, and alkene presence. Three new peaks at 1398, 1371, and 1361 cm⁻1 in the FTIR spectrum of CSD plastic indicated presence of alcohol. Scanning Electron Microscopic (SEM) micrographs illustrated bacterial colonization, cracks, and spots on plastic surfaces, while X-ray Diffraction (XRD) spectra showed peaks at 4.083, 3.705, 3.020, and 1.909, suggesting plastic degradation. In conclusion, soil of waste disposal site harbored diverse microbial species, and have highlighted their effectiveness in mitigating environmental pollution by degrading hazardous plastic waste.

Estimating the latent heat flux (λET) accurately is important for water-saving irrigation in arid regions of Northwest China. The Penman-Monteith model is a commonly used method for estimating λET, but the parameterization of canopy resistance in the model has been a difficulty in research. In this study, continuous observation of λET during the growing period of maize and grassland in Northwest China was conducted based on the Bowen ratio energy balance (BREB) method and the Eddy covariance system (ECS). Two methods, Katerji-Perrier (K-P) and Garcıá-Santos (G-A), were used to determine the canopy resistance in the Penman-Monteith model and the estimation errors and causes of the two sub-models were explored. The results indicated that both models underestimated the λET of grassland and maize. The K-P model performed relatively well (R2 > 0.94), with the root mean square errors (RMSE) equaled 37.3 and 28.1 W/m2 for grass and maize, respectively. The accuracy of the G-A model was slightly lower than that of the K-P model, with the determination coefficient (R2) equaled 0.90 and 0.92, and the RMSE equaled 46.2 W/m2 (grass) and 42.1 W/m2 (maize). The vapor pressure deficit (VPD) was the main factor affecting the accuracy of K-P and G-A sub-models. The error of two models increased with the increasing in VPD for both crops.

A low temperature aqueous growth followed by mild pyrolysis was used in this study to synthesize high-quality carbonized materials from the deserted plant Citrullus Colocynthis. It was found that the carbon material prepared for this study contained an abundance of functional groups and surface active sites. A few microns were evidently the size of the carbon material. This study investigated a variety of photocatalytic performance evaluation parameters, including initial dye concentration of methylene blue, pH effect on dye solution, scavenger stability, and recycle stability via irradiating UV light. Methylene blue degradation was found to be significantly affected by pH and concentration of the dye solution. It has been found that pH five is the most effective pH for the removal of dyes. As a result of the study, we found that methylene blue decays according to pseudo first order kinetics and is estimated to remove dye at an almost 100% rate.

Municipal solid waste management is a major concern in developing economies, requiring collective international efforts to achieve carbon neutrality by diverting waste from disposal facilities. This study aims to highlight the importance of the waste sector as it has the potential to significantly contribute to climate change and its toxicity impact on the local ecosystem. Out of the total municipal solid waste generated, only 78 % is collected, either open dumped or thrown in sanitary landfills. The waste sector's ecological impact value is calculated for the Earth's regions, and it is very high at >50 % in Africa, Asia, Latin America and the Caribbean. This sectoral impact value is mainly responsible for greenhouse gas emissions and degradation of the local ecosystem health. Current business‒as‒usual practices attribute 3.42 % of global emissions to the waste sector. Various scenarios are developed based on waste diversion and related emissions modelling, and it is found that scenarios 3 and 4 will support the policymakers of the regions in attaining zero carbon footprints in the waste sector. Our findings conclude that cost-effective nature-based solutions will help low‒income countries reduce emissions from disposal sites and significantly improve the local ecosystem's health. Developed economies have established robust waste‒handling policies and implementation frameworks, and there is a need for collaboration and knowledge sharing with developing economies at the regional level to sustain the sector globally.

Melatonin (MT) participates in plants' responses in plants’ response to cadmium (Cd) tolerance, although its work model remains elusive. Here, the function of MT in adjusting Cd accumulation in Gossypium hirsutum (CCRI12) was investigated. In this research we observed that exogenous 50 μM MT significantly reduced the Cd accumulation under 100 μМ Cd stress for 7 days of treatment in cotton seedlings. Cd markedly induced the ROS (H2O2, O2-) accumulation and elevated the expression of transporters for Cd uptake and translocation. After application of MT reduced ROS and MDA accumulation in response to high induction of antioxidant defense system; the genes encoding superoxide dismutase (GhSOD), catalase (GhCAT), and peroxidase (GhPOD), ascorbate peroxidase (GhAPX), and glutathione S-transferase (GhGST) were significantly upregulated accompanied by their level of content. Furthermore, MT down-regulated transporters for Cd uptake include Natural Resistance-Associated Macrophage Protein 1 (GhNRAMP3), Zinc/Iron-regulated transporter-like protein (GhZIP1/4/6), Heavy Metal ATPase gene (GhHMA2), and ATP-binding Cassette sub family C (GhABCC3/2). Exogenous application of MT raised the hemicelluloses, cellulose and pectin content accompanied by their expression levels, xyloglucan endotransglucosylase/hydrolase (GhXTH28/6/9/B), cellulose synthase like (GhCSLG1/2) and COBRA-like (GhCOBL4), pectin acetylesterases (GhPAE8/7), pectin methylesterases (GhPME31) which in turn increased the cell wall's binding capacity to Cd.

Online grocery shopping has emerged as a prominent choice, significantly accelerated by the COVID-19 pandemic. This study delves into the factors impacting customer satisfaction in the realm of online grocery shopping, focusing on the mediating influence of perceived risk. The research, conducted with a sample size of 462, employed a convenience sampling technique for data collection. The data analysis was performed using Excel, SPSS, and Structural Equation Modeling (SEM) through AMOS. The findings reveal that perceived product quality plays a pivotal role in positively and significantly influencing customer satisfaction within the online grocery shopping sphere. Conversely, perceived convenience, while positively correlated, exhibits insignificance in impacting customer satisfaction. Furthermore, this study highlights the existence of full mediation between perceived convenience and customer satisfaction, mediated by a variable, as evidenced by the non-zero values in the range of .040 to .105. This research underscores the importance for businesses engaged in online grocery retail to prioritize convenience as an essential element to enhance customer satisfaction.

Abstract There is no FDA-approved drug for neurological disorders like spinocerebellar ataxia type 3. CAG repeats mutation in the ATXN3 gene, causing spinocerebellar ataxia type 3 disease. Symptoms include sleep cycle disturbance, neurophysiological abnormalities, autonomic dysfunctions, and depression. This research focuses on drug discovery against ATXN3 using phytochemicals of different plants. Three phytochemical compounds (flavonoids, diterpenoids, and alkaloids) were used as potential drug candidates and screened against the ATXN3 protein. The 3D structure of ATXN3 protein and phytochemicals were retrieved and validation of the protein was 98.1% Rama favored. The protein binding sites were identified for the interaction by CASTp. ADMET was utilized for the pre-clinical analysis, including solubility, permeability, drug likeliness and toxicity, and chamanetin passed all the ADMET properties to become a lead drug candidate. Boiled egg analysis attested that the ligand could cross the gastrointestinal tract. Pharmacophore analysis showed that chamanetin has many hydrogen acceptors and donors which can form interaction bonds with the receptor proteins. Chamanetin passed all the screening analyses, having good absorption, no violation of Lipinski’s rule, nontoxic properties, and good pharmacophore properties. Chamanetin was one of the lead compounds with a − 7.2 kcal/mol binding affinity after screening the phytochemicals. The stimulation of ATXN3 showed stability after 20 ns of interaction in an overall 50 ns MD simulation. Chamanetin (Flavonoid) was predicted to be highly active against ATXN3 with good drug-like properties. In-silico active drug against ATXN3 from a plant source and good pharmacokinetics parameters would be excellent drug therapy for SC3, such as flavonoids (Chamanetin).

Abstract Background Photosystem II (PSII) constitutes an intricate assembly of protein pigments, featuring extrinsic and intrinsic polypeptides within the photosynthetic membrane. The low-molecular-weight transmembrane protein PsbX has been identified in PSII, which is associated with the oxygen-evolving complex. The expression of PsbX gene protein is regulated by light. PsbX's central role involves the regulation of PSII, facilitating the binding of quinone molecules to the Qb (PsbA) site, and it additionally plays a crucial role in optimizing the efficiency of photosynthesis. Despite these insights, a comprehensive understanding of the PsbX gene's functions has remained elusive. Results In this study, we identified ten PsbX genes in Gossypium hirsutum L. The phylogenetic analysis results showed that 40 genes from nine species were classified into one clade. The resulting sequence logos exhibited substantial conservation across the N and C terminals at multiple sites among all Gossypium species. Furthermore, the orthologous/paralogous, Ka/Ks ratio revealed that cotton PsbX genes subjected to positive as well as purifying selection pressure might lead to limited divergence, which resulted in the whole genome and segmental duplication. The expression patterns of GhPsbX genes exhibited variations across specific tissues, as indicated by the analysis. Moreover, the expression of GhPsbX genes could potentially be regulated in response to salt, intense light, and drought stresses. Therefore, GhPsbX genes may play a significant role in the modulation of photosynthesis under adverse abiotic conditions. Conclusion We examined the structure and function of PsbX gene family very first by using comparative genomics and systems biology approaches in cotton. It seems that PsbX gene family plays a vital role during the growth and development of cotton under stress conditions. Collectively, the results of this study provide basic information to unveil the molecular and physiological function of PsbX genes of cotton plants.

Massive MIMO technology is recognized as a key enabler for beyond 5G (B5G) and next-generation wireless networks. By utilizing large-scale antenna arrays at the base station (BS), it significantly improves both system capacity and energy efficiency. Despite these advantages, the deployment of a high number of antennas at the BS presents considerable challenges, particularly in the design of signal detectors that can operate with low computational complexity. While the minimum mean square error (MMSE) detector offers optimal performance in these large-scale systems, it suffers from the computational burden that makes its practical implementation challenging. To mitigate this, various iterative methods and their improved versions have been introduced. However, these iterative methods often converge slowly and are less accurate. To address these challenges, this study introduces an improved variant of traditional accelerated over-relaxation (AOR), called optimized AOR (OAOR). AOR is an over-relaxation method, and its performance is highly dependent on its relaxation parameters. To find the optimal parameters, we have developed an innovative approach that integrates a nature-inspired meta-heuristic algorithm known as Particle Swarm Optimization (PSO). Specifically, we introduce a novel variant of PSO that improves upon basic PSO by enhancing the cognitive coefficients to optimize the relaxation parameters for OAOR. These key modifications to the standard PSO improve its ability to explore various solutions efficiently and help to find the optimal parameters more quickly for signal detection. It facilitates the OAOR with faster convergence towards the optimal solution by reducing the error rate, resulting in high detection accuracy and simultaneously decreasing computational complexity from O(K3) to O(K2) making it suitable for modern wireless communication systems. We conduct extensive simulations across various configurations of massive MIMO systems. The results indicate that our proposed method achieves better performance compared to existing techniques. This improvement is particularly evident in terms of both computational complexity and error rate.

Background: Streptococcus mutans is a leading causative agent of dental caries and exerts pathogenicity by forming biofilms. Dental caries continues to be a significant public health issue worldwide, affecting an estimated 2.5 billion people, showing a 14.6% increase over the past decade. Herein, the antibacterial potential of Chlorophyllin extracted from Spinacia oleracea was evaluated against biofilm-forming S. mutans via in vitro and in silico studies. Methodology: The antimicrobial activity of chlorophyllin extract against S. mutans isolates was tested using the agar well diffusion method. Chlorophyllin extract was also tested against biofilm-forming isolates of S. mutans. Chlorophyllin was docked with the antigen I/II (AgI/II) protein of S. mutans to evaluate its antimicrobial mechanism. The chemical structure and canonical SMILES format of Chlorophyllin were obtained from PubChem. Additionally, adsorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses of Chlorophyllin were performed using ADMETlab 2.0 to assess its pharmacokinetic properties. Results: An agar well diffusion assay revealed that all S. mutans isolates were susceptible to Chlorophyllin extract and showed a variety of inhibition zones ranging from 32 to 41 mm. Chlorophyllin reduces the biofilm strength of four isolates from strong to moderate and six from strong to weak. The antibiofilm potential of Chlorophyllin was measured by a reduction in the number of functional groups observed in the Fourier Transform Infrared Spectrometer (FTIR) spectra of the extracellular polymeric substance (EPS) samples. Chlorophyllin showed binding with AgI/II proteins of S. mutans, which are involved in adherence to the tooth surface and initiating biofilm formation. The ADMET analysis revealed that the safety of Chlorophyllin exhibited favorable pharmacokinetic properties. Conclusions: Chlorophyllin stands out as a promising antibacterial and antibiofilm agent against biofilm-forming S. mutans, and its safety profile highlights its potential suitability for further investigation as a therapeutic agent.

Background: Diabetes mellitus is considered as hypercoagulable state, where hypercoagulability of blood result in acceleration of atherosclerosis and diabetic microvascular complications. Three recognized diabetic microvascular complications include diabetic neuropathy, diabetic nephropathy and diabetic retinopathy. The aim of the present study was to evaluate association of plasma fibrinogen levels with other variables in patients with any of the three-recognized diabetic microvascular complications: diabetic neuropathy, diabetic retinopathy or diabetic nephropathy. Methods: 104 patients of T2DM from in Medical unit-II and ophthalmology ward, Services Hospital, Lahore from April to October 2017 were included in present study. The patients were divided into two groups of 52 patients each. Group 1 comprised of Type 2 Diabetes Mellitus patients without any diabetic microvascular complications and Group II: Type 2 Diabetes Mellitus patients with any of three recognized diabetic microvascular complications: diabetic neuropathy, diabetic nephropathy and diabetic retinopathy (52 patients). Plasma fibrinogen levels, blood sugar fasting (BSF), HbA1c and BMI were evaluated in all patients. Results: Spearman’s rank correlation coefficient, applied for measuring correlation of variables, showed statistically significant correlation (P < 0.05) of BSF r = 0.39; HbA1c r = 0.48 to plasma fibrinogen in patients with any of the three diabetic microvascular complications. Conclusion: Higher fibrinogen levels (Clotting factor I) in plasma contribute significantly to establishment of microvascular complications in type-II diabetes mellitus patients. Fibrinogen levels were positively correlated with HbA1c and blood sugar fasting.

Background: TB has been announced as a global emergency of this millennium. It is one of the leading causes of death among adults due to a single infectious agent. Pakistan is fifth among the twenty two Eastern Mediterranean Region countries with the highest burden of disease which is approximately 270 per 100,000. The emergence of drug resistant MTB poses a serious threat to the ongoing efforts to control the disease epidemic. Drug resistance to the first line drugs such as Isoniazid (INH) and Rifampicin (RIF) needs to be investigated. In this respect the role of various genes conferring resistance should be studied to find better treatment alternatives. The current practice of drug sensitivity testing requiring approximately three weeks is time consuming and a major cause of treatment delay. Objectives: The aim of the present study was to sequence the mutations in katG gene which contribute towards INH resistance and to study association of katG gene with INH resistance in MTB. Methods: In this research sputum samples were collected in wide mouth transparent containers from suspected TB patients. After decontamination samples were inoculated onto LJ medium. The colonies grown on the slopes were identified as MTB by standard biochemical test. Isolates were tested on LJ medium for in vitro DST (Drug Sensitivity Testing). MDR was described as resistance to INH and RIF with or without resistance to other drugs. DNA was extracted from the grown samples using kit method. After extraction of DNA, the region from base 2714 to 3232 of katG gene was amplified through PCR and the amplified products were sequenced. Analysis of the DNA sequences and mutations was done with the help of BLAST - alignment software. A total of 24 MDR MTB samples were sequenced. Sequence analysis revealed the reported mutation Ser → Thr in katG codon 315 in five samples (21%). In this study, an authentic molecular analysis (test) was developed and validated for identification of INH resistant strains in Pakistani population. Conclusion: It was concluded from the study that mutation of some genes particularly point mutation in codon 315 of katG gene is associated with development of resistance to the drug INH in Multi drug resistant TB. Key words: isoniazid, multiple drug resistant tuberculosis

Background: COVID-19 is primarily known as a respiratory illness; however, many patients present to hospital without respiratory symptoms. The association between non-respiratory presentations of COVID-19 and outcomes remains unclear. We investigated risk factors and clinical outcomes in patients with no respiratory symptoms (NRS) and respiratory symptoms (RS) at hospital admission. Methods: This study describes clinical features, physiological parameters, and outcomes of hospitalised COVID-19 patients, stratified by the presence or absence of respiratory symptoms at hospital admission. RS patients had one or more of: cough, shortness of breath, sore throat, runny nose or wheezing; while NRS patients did not. Results: Of 178,640 patients in the study, 86.4 % presented with RS, while 13.6 % had NRS. NRS patients were older (median age: NRS: 74 vs RS: 65) and less likely to be admitted to the ICU (NRS: 36.7 % vs RS: 37.5 %). NRS patients had a higher crude in-hospital case-fatality ratio (NRS 41.1 % vs. RS 32.0 %), but a lower risk of death after adjusting for confounders (HR 0.88 [0.83–0.93]). Conclusion: Approximately one in seven COVID-19 patients presented at hospital admission without respiratory symptoms. These patients were older, had lower ICU admission rates, and had a lower risk of in-hospital mortality after adjusting for confounders.

Wireless Body Area Networks (WBANs) are a cost-effective, low-power technology that has been advancing due to the need to improve their performance. The predominant challenges encompass packet delivery ratio (PDR), packet loss ratio (PLR), and end-to-end (E2D) delay. Advances in wireless technology emphasize the urgency to surmount these issues. Channel congestion and collisions, increased latency, unfairness in access, high energy consumption, performance heterogeneity, QoS degradation, interference and reliability are some of the particular concerns largely caused by CW that influence WBAN performance. Researchers and developers strive to create adaptive CW techniques and protocols that dynamically modify CWsize in response to traffic loads, network conditions, and the particular needs of WBAN applications in order to maximise WBAN performance. In response, we propose GFuCWO—a genetic fuzzy logic technique—for optimizing contention windows in IEEE-802.15.6 WBANs. This study introduces three distinct algorithms to accomplish this. We evaluate the efficiency of the GFuCWO technique against the ABEB and Improved-CSMA/CA algorithms. The approach is implemented in Castalia OMNeT++. The study calculates PDR, PLR, and E2D delay using experimental data from four sensor nodes under different traffic conditions. The GFuCWO technique demonstrated superior performance in PDR, PLR, and E2D, with average enhancements of 4%-11% and 3%-13%, respectively, with a 95% confidence interval, indicating its potential for community benefit and medical performance improvements.

Selecting the right actuator for a portable exoskeleton involves a comprehensive evaluation of various design characteristics. In this study, we introduce a methodology for actuator selection based on specific tasks, enhancing the practical adoption of portable exoskeletons. By examining a range of candidate actuators designed for lower limb exoskeletons, our objective is to engineer a system that is both lightweight and power-efficient. These candidate actuators, developed by integrating diverse motors and transmission systems, were rigorously tested against defined tasks. Our methodology, applied to an assistive exoskeleton catered to the elderly, showed its potential in tailoring an efficient system with matching capabilities. The obtained results indicated that the ideal configuration achieved reductions in weight and power requirements by 35% and 80%, respectively. The present research delineates a strategic approach for actuator selection in portable exoskeletons, contributing to the evolution of high-performing assistive devices.

Social media has revolutionized how businesses connect with consumers, going beyond product promotion to understanding consumer preferences. It is undeniable that social media plays a pivotal role in shaping consumer purchase decisions, as more individuals turn to these platforms to seek advice and opinions from peers. The current study engaged 410 Indian consumers, employing a quantitative approach backed by rigorous statistical methods, including descriptive statistics, correlation analysis, regression analysis, and structural equation modeling (SEM) using AMOS software. The goal was to unravel the intricate dynamics between social media marketing, brand image, and purchase intentions. The findings highlight a significant and positive relationship between social media marketing efforts and brand image perception. Moreover, it was discovered that brand image significantly influences consumers’ purchase intentions. Surprisingly, it did not find a direct and significant impact of social media marketing on purchase intentions.Notably, the study revealed a crucial insight: the influence of social media marketing on purchase intentions is fully mediated by the perception of brand image. In light of these results, businesses are encouraged to establish a strong presence on social media platforms to effectively promote their products and services. Organizations can effectively steer consumer purchase intentions by harnessing the synergy between social media marketing and brand image. Acknowledgment This study is supported via funding from Prince Sattam bin Abdulaziz University project number (PSAU/2023/R/1444).

Background: Hepatitis B Virus (HBV) is one of the leading causes of infectious disease in the global population, and its prevalence has been increasing globally. Human HBV infection is complex, involving both innate and adaptive immune systems. Cytokines play a role in both physiologic and pathologic processes in the liver. This study was designed to screen serum levels using an enzyme linked immunosorbent assay (ELISA) and genetic variants in the TNF-α and IL6 genes using polymerase chain reactions (PCR). The aim of this study was to screen the serum levels and genotype levels with TNF-α (C-308 T/G-308A) and IL-6 (G-174 C) genes in HBV patients and control subjects. Methods: In this study, we have selected 50 HBV patients and 40 control subjects from Saudi Population. Patient serum samples was used for measuring the serum levels and PCR analysis using RFLP analysis. Prior to this, HBV patients were confirmed with PCR analysis followed by Sanger sequencing analysis. Results: The current study results confirmed positive association in serum levels (p 0.05). Positive associations between blood levels of TNF-α and IL-6 were confirmed, while negative associations were found between PCR investigations involving the TNF-α (G-308A) and IL-6 (G-174 C) genes with the HBV prevalence in the Saudi population. Conclusion: This study confirmed serum levels are strongly associated with HBV patients in the Saudi population. However, PCR studies showed the negative association with the couple of variants selected for this study.

Water is considered one of the vital natural resources and factors for performing short- and long-term agricultural practices on Earth. Meanwhile, globally, most of the available freshwater resources are utilized for irrigation purposes in agriculture. Currently, many world regions are facing extreme water shortage problems, which can worsen if not managed properly. In the literature, numerous methods and remedies are used to cope with the increasing global water crises. The use of precision irrigation water-saving systems (PISs) for efficient water management under climate change is one of them and is a highly recommended approach by researchers. It can mitigate the adverse effects of changing climate and help enhance water use efficiency, crop yield, and environmental footprints. Thus, the present study aimed to comprehensively examine and review PISs, focusing on their development, implementation, and positive impacts on sustainable water management. In addition, we searched the literature using different online search engines and reviewed and summarized the main results of the previously published papers on PISs. We discussed the traditional irrigation method and its modernization for enhancing water use efficiency, PIS monitoring and controlling, architecture, data sharing communication technologies, the role of artificial intelligence for irrigation water-saving, and the future prospects of the PIS. Based on the brief literature review, the present study concluded that the future of PISs seems bright, driven by the need for efficient irrigation water management systems, technological advancements, and increasing environmental awareness. As the water scarcity problem intensifies due to climate change and population growth, the PIS is poised to play a critical role in optimizing and modernizing water usage, increasing water use efficiency, and reducing environmental footprints, thus ensuring sustainable agriculture development.

In this article, we investigate and study an extended Cayley–Yosida inclusion problem. We show that our problem is equivalent to a fixed-point equation. Based on the fixed-point equation, we develop a three-step iterative algorithm to solve our problem. Finally, we illustrate the convergence of the proposed algorithm with an example, computational table, and convergence graph by using MATLAB 2018b.

Arsenic (As) contamination is a severe problem in drinking-water sources. This study designed and investigated a novel combined electrocoagulation–filtration (ECF) system to investigate As treatment and filtration in drinking water in collaboration with HANDS-Pakistan and Medico International, Germany. Two separate pilot-scale ECF systems were designed and developed with an electrocoagulation (EC) unit and a commercially available PAUL® filter configured with vertical flat-sheet ultra-low-pressure membranes of 0.04 µm pore size for the combined treatment and filtration of different As concentrations. Real drinking water at different As concentrations, i.e., 100, 200, and 300 μg/L were tested on one ECF system with EC electrodes of iron (Fe) and another system with aluminum (Al), at different treatment times (0, 5, 10, 20, 45, 60, 120, 180 min), at a fixed current density (12 mA/cm2) and water flow rate of 1 L/min. The initial results showed 99% As removal within 5 min with the combined ECF treatment for both electrodes of Fe and Al. In addition, the effect of ECF on different water-quality parameters and the ionic interference on ECF performance and As filtration were analyzed. The results showed the promising potential of combined ECF treatment and filtration for treating and purifying As.

Abstract The development of modern civil industry, energy and information technology is inseparable from the rapid explorations of new materials. However, only a small fraction of materials being experimentally/computationally studied in a vast chemical space. Artificial intelligence (AI) is promising to address this gap, but faces many challenges, such as data scarcity and inaccurate material descriptors. Here, we develop an AI platform, AlphaMat, that can complete data preprocessing and downstream AI models. With high efficiency and accuracy, AlphaMat exhibits strong powers to model typical 12 material attributes (formation energy, band gap, ionic conductivity, magnetism, bulk modulus, etc.). AlphaMat’s capabilities are further demonstrated to discover thousands of new materials for use in specific domains. AlphaMat does not require users to have strong programming experience, and its effective use will facilitate the development of materials informatics, which is of great significance for the implementation of AI for Science (AI4S).

Female infertility (FI) is a global health issue. Polycystic ovary syndrome (PCOS) is a common cause of FI. The renalase gene (RNLS) is associated with FI and other human diseases. Based on the documented missense variants, rs6166 and rs2296545 single-nucleotide polymorphisms (SNPs) were not identified in Saudi women with FI and PCOS. This study aimed to investigate the molecular role of the two SNPs in Saudi women with FI and PCOS. In this cross-sectional study, 96 healthy controls, 96 women with FI, and 96 women with PCOS were recruited. DNA was isolated, and polymerase chain reactions and Sanger sequencing analysis were performed using rs6166 and rs2296545 SNPs. The data obtained from the three groups were used to perform statistical analyses based on genotype, allele frequencies, regression models, and ANOVA analysis. Both rs6166 and rs2296545 had no role in FI or PCOS in Saudi women. A predicted reason for non-association in Saudi women could be the role of elderly women in the controls compared with women with FI and PCOS. Moreover, age, weight, and body mass index were higher in the control group than the FI and PCOS groups. In conclusion, rs6166 and rs2296545 SNPs were not associated with FI or PCOS in Saudi women.

Abstract Introduction Coronavirus disease 2019 (Covid‐19) following venous thromboembolism (VTE) and blood hyperlactatemia are associated with higher mortality. However, reliable biomarkers for this association remain to be elucidated. This study investigated the associations of VTE risk and blood hyperlactatemia with mortality among critically ill Covid‐19 patients admitted to the intensive care unit (ICU). Methods In this single‐centre retrospective study, we included 171 patients aged ≥18 years with confirmed Covid‐19 admitted to the ICU at a tertiary healthcare clinic in the Eastern region of Saudi Arabia between 1 March 2020 and 31 January 2021. Patients were divided into two groups: survivor and non‐survivor. The survivors have been identified as the patients discharged from the ICU alive. The VTE risk was defined using a Padua prediction score (PPS) >4. The blood lactate concentration (BLC) cut‐off value >2 mmol/L was used to determine the blood hyperlactatemia. Results Multi‐factor Cox analysis showed that PPS >4 and BLC >2 mmol/L were more likely to be significantly associated with higher odds of ICU mortality in critically ill Covid‐19 patients (hazard ratio [HR] = 2.80, 95% confidence interval [CI] = 1.00–8.08, p = 0.050; HR = 3.87, 95% CI = 1.12–13.45, p = 0.033, respectively). The Area under the Curve for VTE and blood hyperlactatemia were 0.62 and 0.85, respectively. Conclusion VTE risk and blood hyperlactatemia have been associated with a higher mortality risk in critically ill Covid‐19 patients who are hospitalized in the ICU in Saudi Arabia. According to our findings, these people needed more effective VTE prevention strategies based on a personalized assessment of their risk of bleeding. Moreover, persons without diabetes and other groups with a high risk of dying from COVID‐19 may be recognized by measuring glucose as having elevated glucose and lactate jointly.

The significant contribution of current mechanism is to explore the periodical and fluctuating results of heat and mass flux of Darcy-Forchheimer nanofluid flow along buoyancy-driven porous plate under solar radiation region. Flow through a Darcy-medium has a wide range of applications such as the use of oil in various hydrothermal transfer control, radioactive nuclear disposal systems, water improvement, and filtration of water. The dimensional model is transformed into non-dimension for scaling factors. The primitive-based transformation is applied on steady and oscillatory parts for smooth algorithm in FORTRAN language machine. The convenient model is again reduced into algebraic pattern by using implicit finite difference method. The numerical and graphical results of velocity, temperature and concentration are executed by Gaussian elimination method. To enhance the frequency and wavelength, the impact of solar radiations, thermophoresis, Brownian movement, Schmidt factor, Prandtl factor, porosity and buoyancy pressure is applied on periodic nanoparticles with Darcy Forchheimer relation. The novelty of this proposal to explore the wave oscillations, amplitude and phase angle of thermal and concentration boundary layer of Darcy-Forchheimer nanofluid flow along buoyancy-driven porous plate under solar radiation region. It is noticed that the prominent wavelength and frequency in thermal and concentration boundary layers is generated under porous and solar radiation region. The significance of temperature variation increases as solar radiation, Brownian motion and thermophoresis increases. It is noticed that heat and mass transport enhances as Darcy-Forchheimer and modified buoyancy force increases. In thermodynamic systems, the Darcy-porous materials is prominent assumption that is employed in many domains, especially clinical science, petrochemical and structural engineering, geography, biochemistry and biological physics, and material science. For energy storage and energy conservation, the Darcy-porous material is required for batteries, fuel cells and super capacitors.

IntroductionNon-diabetic women with polycystic ovarian syndrome (PCOS) often have abnormal insulin regulation. Calpain 10 (CALP10) is a biomarker of type 2 diabetes mellitus, with some of its single-nucleotide polymorphisms (SNPs) influencing PCOS development.MethodsIn this case-control study on 90 women each with and without PCOS, we explored the molecular role of five CALP10 SNPs using biochemical parameters and Sanger sequencing analyses.ResultsDifferent genetic models, genotypes, and allele frequencies were significantly associated with UCSNP-19 (rs3842570; p=0.01), UCSNP-44 (rs2975760; p=0.009), UCSNP-56 (rs2975762; p

The aim of this study was to investigate the effectiveness of continuous cold flow and compression device as against traditional icing regimen and without icing after anterior cruciate ligament (ACL) reconstruction. All patients undergoing ACL reconstruction from June 2021 to August 2021 were enrolled in this study. Patients were randomly allocated to three groups: A control group (n=10) with no ice regimen post-operatively, a second control group (n=10) with ice bag, and a third group (n=10) with continuous cold flow and compression device (physiolab). All patients who had isolated ACL tear evident on magnetic resonance imaging were included. Pain intensity, limb girth, Oxford Knee Score, and 12-item survey form were measured pre- and post-operatively. Significant difference was noted between pain scores in all groups at two- and six-week follow-ups with p-value of 0.004 and 0.01. ---Continue

Corporate social responsibility (CSR) is the belief that businesses must consider ethical, social, and environmental issues when making decisions. Several studies have found that CSR improves corporate performance. Moreover, CSR is thought to increase consumer trust and purchase intention. This study investigates the effect of CSR activities on customers’ purchase intentions and the mediating role of trust. It draws linkages and establishes that businesses can improve their bottom lines while positively affecting society by acting responsibly.The present study selected two independent variables (ethical corporate social responsibility and legal corporate social responsibility) alongside one dependent variable (purchase intention) and one intervening variable (trust). The sample comprises two hundred and thirty respondents from India’s National Capital Region (NCR), Delhi, and nearby regions. The data were examined using structural equation modeling (SEM). The results showed that CSR activities significantly positively affected customers’ purchase intention. Furthermore, trust mediated the linkages between CSR activities and customers’ purchase intention. The findings suggest that CSR activities can increase customers’ purchase intention by fostering trust. In other words, when customers trust a firm, they are more likely to intend to purchase its products or services. CSR managers should therefore focus on creating and maintaining trust with their customers. In addition, findings suggest that firms should be conscious of their social image. This study offers significant insights because they show that any business can be successful and socially responsible. Acknowledgment This study is supported via funding from Prince Sattam bin Abdulaziz University project number (PSAU/2023/R/1444).

Among many diseases, allergy appears to be a serious problem for human beings. Various forms of allergic disorders make people tense, leading to some other health issues. Many medications, including nonracemic and racemic ones, are used to treat this problem. It is important to have exact analysis strategies just to see any medication side effects, plasma profiles, and working efficiency. Therefore, efforts are made to review simple and chiral HPLC methods for antiallergic drugs; HPLC is the best analytical technique. The highlights in this article include the world scenario, causes of allergy, the effect of allergy on the economy, the mechanism of allergy in humans, classes of antiallergic drugs, simple drugs, chiral drugs, analysis by HPLC, and the chiral recognition mechanism. Moreover, attempts are also made to highlight the management of allergies and future perspectives.

Abstract Recently, researchers have applied blockchain technology in vehicular networks to take benefit of its security features, such as confidentiality, authenticity, immutability, integrity, and non-repudiation. The resource-intensive nature of the blockchain consensus algorithm makes it a challenge to integrate it with vehicular networks due to the time-sensitive message dissemination requirements. Moreover, most of the researchers have used the Proof-of-Work consensus algorithm, or its variant to add a block to a blockchain, which is a highly resource-intensive process with greater latency. In this paper, we propose a consensus algorithm for vehicular networks named as Vehicular network Based Consensus Algorithm (VBCA) to ensure data security across the network using blockchain that maintains a secured pool of confirmed messages exchanged in the network. The proposed scheme, based on a consortium blockchain, reduces average transaction latency, and increases the number of confirmed transactions in a decentralized manner, without compromising the integrity and security of data. The simulation results show improved performance in terms of confirmed transactions, transaction latency, number of blocks, and block creation time.

Climate change and the resultant environmental deterioration signify one of the most challenging problems facing humankind in the 21st century. The origins of climate change are multifaceted and rooted in anthropogenic activities, resulting in increasing greenhouse gases in the environment and leading to global warming and weather drifts. Extremophilic fungi, characterized by their exceptional properties to survive extreme habitats, harbor great potential in mitigating climate change effects. This review provides insight into the potential applications of extremophilic fungi in climate change mitigation strategies. They are able to metabolize organic biomass and degrade carbon compounds, thereby safely sequestering carbon and extenuating its release into the environment as noxious greenhouse gases. Furthermore, they possess extremozymes, which break down recalcitrant organic species, including lignocellulosic biomass and hydrocarbons. Enzymatic machinery equips these extremophilic fungi to perform the bioremediation of polluted environments. Extremophilic fungi can also be exploited for various biological interventions, such as biofuels, bioplastics, and other bioprocessing applications. However, these fungi characterize a valued but underexplored resource in the arsenal of climate change mitigation strategies.

Plastic products in plant production and protection help farmers increase crop production, enhance food quality, and reduce global water use and their environmental footprint. Simultaneously, plastic has emerged as a critical ecological issue in recent years, and its pollution has significantly impacted soil, water, and plants. Thus, this review examines the multifaceted problems of plastic pollution in agriculture as a risk to food security, the ecosystem, and the environment. The study’s objective was to review and present the most recent information on using different plastic products in agriculture, the sources of plastic pollution, the advantages and drawbacks of using plastic products, and the strategies for mitigating plastic pollution in agriculture. Furthermore, after examining current plastic applications, benefits, adverse effects, and risks to soil, plants, and the environment, we addressed the requirements for technological advancements, regulations, and social processes that could contribute to mitigating plastic pollution in our ecosystems. We identified different pathways toward more sustainable use of plastics in agriculture and discussed future research directions.

Background: Intranasal meningoencephalocele is a rare congenital malformation. It is defined by protrusion of cerebral tissue and meninges through a defect in the skull base. Serious complications usually occur in early childhood, however, symptoms occasionally can wait until adulthood. Case Presentation: We report a case of a 24-year-old male who had a congenital intranasal meningoencephalocele with recurrent episodes of bacterial meningitis. After a delayed diagnosis, he eventually underwent Endoscopic Endonasal Repair of Meningoencephalocele via 'Bath-plug' technique. Conclusions: To prevent improper management, it is crucial that ENT colleagues, to whom these cases are primarily present, are well informed about this unusual condition. For the purpose of preventing further neurological problems, thorough neuroimaging evaluations and successful surgical repair are important. The 'Bath-plug' technique for anterior skull base cerebrospinal fluid leak repair is effective for a wide range of situations.

Rhodococcus jostii RHA1 was engineered to utilise the cellulose component of lignocellulose, as well as the lignin fraction, by introduction of cellulase genes. The genome of R. jostii RHA1 was found to contain two β-glucosidase genes, RHA1_ro01034 and RHA1_ro02947, which support growth on cellobiose as growth substrate. Five Gram-positive endocellulase genes and one exocellulase gene were cloned into expression vector pTipQC2, and expressed in R. jostii RHA1. Endoglucanase activity was detected, with highest activity using Cellulomonas fimi cenA, and this recombinant strain grew on minimal media containing 0.5% carboxymethylcellulose (CMC). The R. jostii RHA1 genome was also found to contain a 3-dehydroshikimate dehydratase gene RHA1_ro01367, which supports growth on quinic acid as growth substrate, and conversion to protocatechuic acid. Therefore, this bacterium shows promise for further engineering to utilise cellulose for conversion to protocatechuic acid-derived bioproducts.

Precision Agriculture (PA) techniques employing Internet of Things (IoT) can significantly improve crop yields and enhance productivity. Radio frequency identification (RFID) based IoT systems can enhance precision livestock farming by enabling livestock traceability and identification in large farms, but congestion is a major challenge. In such conditions, livestock estimation using RFID is a complex task because of high chances of tag collision due to significant increase in interference at the gates. Several anti-collision algorithms have been explored in recent past to address this issue with the aid of a single antenna. However, the throughput gains from a single antenna are limited particularly for dense scenarios like gates at a small ruminant farm. Therefore, we propose a multi-antenna RFID reader system with a dynamic frame slotted ALOHA (DFSA) anti-collision algorithm to address the tag collision problem by exploiting the spatial diversity of the multiple inputs and multiple outputs (MIMO) backscattering channel. The proposed technique is simulated in MATLAB for several tag population figures both with and without interference actions of various intensities. Results have shown that significant throughput gains can be achieved, in comparison with gains attained by anti-collision algorithms based on a single antenna. The simulation testbed enables us to evaluate the proposed technique for multiple receive antenna configurations.

The objective of IEEE 802.15.4 standard is to establish the foundation for a low-rate wireless personal area network that focuses on ubiquitous communication between devices while maintaining a reasonable data rate. Its popularity has increased significantly as a result of its implementation at low power and cheap cost, and the need to improve its performance has become a necessity. The most persistent issues are throughput, packet delivery ratio (PDR), packet loss ratio (PLR), and packet delay (PD). The advances in wireless technology place a strong emphasis on overcoming these problems. To accomplish stated goals, GFCO: A genetic fuzzy-logic approach to optimize channel of IEEE 802.15.4 LR-WPAN is proposed. It employs the $Fuzzy Logic Controller$ (FLC), and the $Genetic Algorithm$ (GA), by doing so, GA optimally modifies the FLC. For this, five algorithms are presented, Algorithm-1: GFCO for LR-WPAN, Algorithm-2: $GA_{1}$ for GFCO, Algorithm-3: $FLC_{1}$ for GFCO, Algorithm-4: $GA_{2}$ for GFCO, and Algorithm-5: $FLC_{2}$ for GFCO. The suggested GFCO approach is assessed for $Random Exponential Backoff$ (REB) algorithm, which was chosen as a fundamental algorithm, along with the $Survivability~Aware~Channel~Allocation$ (SACA) algorithm, taken as a benchmark study. Two scenarios are implemented in NS-3.20 in conjunction with fuzzylite in a hospital environment. First scenario is implemented in randomly deployed 10 sensors on a person’s body ( $2\times 2\,\,m^{2}$ area), whereas second scenario is implemented in $20\times 20\,\,m^{2}$ area of a ward in hospital having 10 to 50 persons. The simulated outcomes of both scenarios were recorded for REB, SACA, and GFCO. Simulated testing demonstrated that the proposed GFCO greatly enhanced performance of throughput 15.11%, SR 3.11%, PLR 3.11%, and PD 5.52% on average for scenario-I, whereas throughput 12.06%, SR 9.0%, PLR 9.0%, and PD 2.23% on average for scenario-II, as compared to SACA. Following that, these results are used to calculate the throughput, PDR, PLR, and PD and to draw a graphical representation. The proposed GFCO technique significantly improved efficiency, according to the results of the simulated testing.

Keeping in view the latest development of anti-Hermitian matrix in mind, we construct some closed form formula for a classical system of matrix equations having anti-Hermitian nature in this paper. We give the necessary and sufficient conditions for the existence of its solution by applying the properties of matrix rank. The general solution to this system is expressed by closed formula based on generalized inverses of given matrices. The novelty of the proposed results is not only obtaining a formal representation of the solution in terms of generalized inverses but the construction of an algorithm to find its explicit expression as well. To conduct an algorithm and numerical example, it is used the determinantal representations of the Moore Penrose inverse previously obtained by one of the authors.

Streptomyces species have been exploited widely as microbial cell factories, especially for antibiotic production. However, their potential for alpha-amylase production has not been extensively studied. This study reports the isolation, molecular identification, and optimization of the physiological conditions for alpha-amylase production from Streptomyces sp., isolated from soil in Kotli Azad Kashmir. The maximum growth of Streptomyces MI-1 was observed at a neutral pH and a temperature of 35 °C. An amylase activity of 1.15 IU/mL was observed when 4% starch was added to the nutrient medium. During the submerged state fermentation, the maximum amylase activity of 2.136 IU/mL/min was observed after 144 h of incubation. The characterization of bacterial amylase revealed an optimum temperature of 40 °C, and its optimum pH was 7.0. Furthermore, during the study, examining the effect of different metal ions found that Mg2+ and Ca2+ ions had a positive effect, while Cu2+ and Fe2+ ions had an inhibitory effect compared to the control. This preliminary study provides basal line information for the discovery of novel microbes from the unexplored natural resources for amylase production, which will be used for many purposes.

The Denitrification-Decomposition (DNDC)-Rice is a mechanistic model which is widely used for the simulation and estimation of greenhouse gas emissions [nitrous oxide (N2O)] from soils under rice cultivation. N2O emissions from paddy fields in South Korea are of high importance for their cumulative effect on climate. The objective of this study was to estimate the N2O emissions and biogeochemical factors involved in N2O emissions such as ammonium (NH4+) and nitrate (NO3−) using the DNDC model in the rice-growing regions of South Korea. N2O emission was observed at every application of fertilizer and during end-season drainage at different rice-growing regions in South Korea. Maximum NH4+ and NO3− were observed at 0–10 cm depth of soil. NH4+ increased at each fertilizer application and no change in NO3− was observed during flooding. NH4+ decreased and NO3− increased simultaneously at end-season drainage. Minimum and maximum cumulative N2O emissions were observed at Chungcheongbuk-do and Jeju-do regions of South Korea, respectively. The simulated average cumulative N2O emission in rice paddies of South Korea was 1.37 kg N2O-N ha−1 season−1. This study will help in calculating the total nitrogen emissions from agriculture land of South Korea and the World. HIGHLIGHTS We successfully simulated N2O emission from rice paddy fields of South Korea.; DNDC model was used to estimate N2O emission in South Korea.; Biogeochemical factors of soil such as NH4+ and NO3− concentration were also focused upon.; Simulated N2O emission in this study was strongly correlated as R2 =0.88–0.90.; Results may help to estimate the nitrogen budget of South Korea as well as the world.;

Intensive use of non-renewable resources like coal and crude oil has created several issues and challenges such as the worsening greenhouse effect, depletion of fossil fuels, air pollution, global warming, and climate change. A few remedies have been implemented to address these issues caused by the heavy use of nonrenewable fuels. Developing and adopting green energy technologies is a step in the same direction. Green energy technologies have the potential to reduce the world’s carbon footprint, and waste and increase the efficiency of energy production. This can lead consumers to save money and the environment. This research work intends to determine important factors affecting the purchase intention of green energy technologies. There are four independent variables and one dependent variable. Data was collected from 342 randomly selected respondents from Delhi and NCR. Structural Equation Modeling (SEM) was used to analyze collected data. The main findings of this study are that perceived risk and functional factors impact the consumers’ green technology purchase intention substantially.

Length of stay (LoS) prediction is deemed important for a medical institution’s operational and logistical efficiency. Sound estimates of a patient’s stay increase clinical preparedness and reduce aberrations. Various statistical methods and techniques are used to quantify and predict the LoS of a patient based on pre-operative clinical features. This study evaluates and compares the results of Bayesian (simple Bayesian regression and hierarchical Bayesian regression) models and machine learning (ML) regression models against multiple evaluation metrics for the problem of LoS prediction of cardiac patients admitted to Tabba Heart Institute, Karachi, Pakistan (THI) between 2015 and 2020. In addition, the study also presents the use of hierarchical Bayesian regression to account for data variability and skewness without homogenizing the data (by removing outliers). LoS estimates from the hierarchical Bayesian regression model resulted in a root mean squared error (RMSE) and mean absolute error (MAE) of 1.49 and 1.16, respectively. Simple Bayesian regression (without hierarchy) achieved an RMSE and MAE of 3.36 and 2.05, respectively. The average RMSE and MAE of ML models remained at 3.36 and 1.98, respectively.

Infertility is a major issue at present and is a common disease that exists in both male and female reproductive systems, described as failure to attain pregnancy. The most important physiological phenomenon for establishing clinical pharmacy is defined as female infertility (FI). Obesity enhances the risks for many chronic disorders, especially causing a high risk for women’s reproductive health. The relationship between infertile women and thrombophilia is characterized by abnormal blood coagulation. Among the thrombophilic variants, Factor V Leiden (FVL), prothrombin (PT) and methyl tetrahydrofolate reductase (MTHFR) in genes such as G1691A (rs6020), G20210A (rs1799963) and C677T (rs1801133) are commonly studied in the majority of human diseases. In this case–control study, we investigated the role of thrombophilic variants such as G1691A, G20210A and C677T in the FVL, PII and MTHFR genes in Saudi infertile women. Based on sample size calculation, 100 female infertile and 100 control (fertile) women were selected based on inclusion and exclusion criteria. Genotyping was performed with polymerase chain reaction and followed with precise restriction enzymes, which can accurately detect the nucleotide amendment variants in G1691A, G20210A and C677T. The required statistics were applied between the case (infertile) and control (fertile) women to document the role of the G1691A, G20210A and C677T variants in Saudi infertile women. In this study, age, weight and BMI were found to be high in the control women in comparison to the infertile women. None of the genotypes, genetic models or allele frequencies were associated with G1691A, G20210A or C677T SNPs (p > 0.05). Furthermore, the regression model and ANOVA analysis also showed negative statistical associations. The combination of genotypes and allele frequencies among G1691A, G20210A and C677T SNPs showed positive associations in the recessive model (p = 0.0006). Finally, the GMDR model showed moderate associations with the gene–gene interaction, dendrogram and depletion models. Finally, this study confirmed that thrombophilic SNPs have no role and may not be involved in Saudi infertile women.

Currently, the challenges that analytical chemistry has to face are ever greater and more complex both from the point of view of the selectivity of analytical methods and their sensitivity. This is especially true in quantitative analysis, where various methods must include the development and validation of new materials, strategies, and procedures to meet the growing need for rapid, sensitive, selective, and green methods. In this context, given the International Guidelines, which over time, are updated and which set up increasingly stringent “limits”, constant innovation is required both in the pre-treatment procedures and in the instrumental configurations to obtain reliable, accurate, and reproducible information. In addition, the environmental field certainly represents the greatest challenge, as analytes are often present at trace and ultra-trace levels. These samples containing analytes at ultra-low concentration levels, therefore, require very labor-intensive sample preparation procedures and involve the high consumption of organic solvents that may not be considered “green”. In the literature, in recent years, there has been a strong development of increasingly high-performing sample preparation techniques, often “solvent-free”, as well as the development of hyphenated instrumental configurations that allow for reaching previously unimaginable levels of sensitivity. This review aims to provide an update of the most recent developments currently in use in sample pre-treatment and instrument configurations in the environmental field, also evaluating the role and future developments of analytical chemistry in light of upcoming challenges and new goals yet to be achieved.

This work is dedicated to the study of a second order evolutionary partial differential variational-like inequality in Banach space. We obtain the mild solution of our problem by applying the concept of strongly continuous cosine family of bounded linear operators, fixed point theorem for condensing multi-valued operators and measure of non-compactness. It is proved that the solution set of mixed variational-like inequalities is non-empty, bounded, closed and convex.

Advertising is an unavoidable reality in the modern consumerist world. The ambivalent nature of advertising has made it the subject of vibrant discussion among the marketing critics. But it is an undeniable fact that it has the sole objective of persuading the people to buy more products more often for more money. Pakistani TV commercials tread the same track and aim at influencing the consumers to the core for grabbing their hearts in order to get access to their wallets. In the quest for persuasion, these commercials make active use of rhetorical devices and logical fallacies. This paper examines some of the TV commercial ads within rhetorical tradition and attempts to show that advertising as a discourse is steeped in maximization of benefits of the stuff with a total disregard to any ethical consideration. The study makes a textual analysis of selected TV ads within rhetorical traditions. It concludes with logical, though not final, findings that ads coax the consumers with sneaky techniques and seductive images in order to attract their eyes.

Ionic liquids are a very important class of compounds due to their remarkable properties and wide range of applications. On the other hand, capillary electrophoresis is also gaining importance in separation science because of its fast speed and inexpensive nature. The use of ionic liquids in capillary electrophoresis is gaining importance continuously. The present review article describes the applications of ionic liquids in capillary electrophoresis. This article also describes the general aspects of ionic liquids and capillary electrophoresis. The use of ionic liquids in capillary electrophoresis, optimization of separation, mechanism of separation, and toxicity of ionic liquids, as well as their future perspectives, have also been discussed. It was observed that not much work has been performed in capillary electrophoresis using ionic liquids. It was also realized that the use of ionic liquids in capillary electrophoresis could revolutionize analytical science. Briefly, there is a great need for the use of ionic liquids in capillary electrophoresis for better and more effective separation.

The idea of Green Chemistry began to take shape in an increasingly important way starting in the 90 s when the impact of chemical products and processes began to be critically evaluated.In the analytical chemistry field, green chemistry represents an essential factor to consider whenever a laboratory procedure is planned. Therefore, from the start it is necessary examine not only green chemistry (GC) but also green analytical chemistry (GAC). The impact of the GAC on publications shows how the trend has seen an exponential increase from 1995 to 2018. From here, it is evident how the GAC is increasingly essential in the analytical chemist work who needs uniform, impartial, and standardized tools and elements to evaluate the ''green profile'' of the procedures, also in order to perform a direct comparison between methods and procedures.The purpose of this review is to report, compare, and critically evaluate the tools available today, such as Life Cycle Assessment (LCA), National Environmental Methods Index (NEMI), Analytical Eco-Scale, Green Analytical Procedure Index (GAPI) and ComplexGAPI, RGB (Red Green Blue) and White Analytical Chemistry (WAC) models, hexagon-CALIFICAMET, and finally Analytical GREEnness Metric approach (AGREE) and AGREEprep. This comparison was performed in the text after a short introduction to the concepts and principles related explicitly to GC, GAC, and Green Sample Preparation (GSP).

The treatment of biological samples, especially from complex matrices, has consistently challenged analytical operators. The classic problems to be faced for any analysis, regardless of the origin of the sample, such as for example contamination and loss of analyte, in biological samples, are particularly emphasized. In particular, the main cause of the error is due to the degradation of the analyte which in several cases due to biological interaction. Many factors can influence the stability of drugs, chief among them the physicochemical properties of the drug, characteristics of the matrix, the tendency to conjugation/deconjugation, sample collection procedure, container characteristics (e.g., oxidation, adsorption), and the use of preservatives or other additives. The problem is severe in the toxicological and forensic fields, especially for analyzes considered ''non-repeatable.'' In this review, we will explore all the major problems in the pre-extraction phase for the chemical-analytical aspect in the pharmacotoxicological and forensic fields.