Managing energy transition alongside environmental protection by making use of AI-led butanol powered SI engine optimization in compliance with SDGs.

Enormous consumption of fossil fuel resources has risked energy accessibility in the upcoming years. The price fluctuation and depletion rate of fossil fuels instigate the urgent need for searching their reliable substitute. The current study tries to address these issues by presenting butanol as a replacement for gasoline in SI engines at various speeds and loading conditions. The emission and performance parameters were ascertained for eight distinct butanol-gasoline fuel blends. The oxygenated butanol substantially increases engine efficiency and boosts power with lower fuel consumption. The carbon emissions were also observed to be lower in comparison with gasoline. Furthermore, the Artificial Intelligence (AI) approach was used in predicting engine performance running on the butanol blends. The correlation coefficients for the data training, validation, and testing were found to be 0.99986, 0.99942, and 0.99872, respectively. It was confirmed that the ANN predicted results were in accordance with the established statistical criteria. ANN was paired with Response Surface Methodology (RSM) technique to comprehend the influence of the sole design parameters along with their statistical interactions controlling the responses. Similarly, the R2 value of responses in case of RSM were close to unity and mean relative errors (MRE) were confined under specified range. A comparative study between ANN and RSM models unveiled that the ANN model should be preferred. Therefore, a joint utilization of the RSM and ANN can be more effective for reliable statistical interactions and predictions.

Experiences of Participation in a Study Investigating Feasibility of the Implantable Doppler Probe in Kidney Transplantation: An Embedded Qualitative Study.

OBJECTIVES: Kidney transplant survival can be improved with better graft surveillance postoperatively. In the quest to explore new technologies, we explored the feasibility of an implantable Doppler probe as a blood flow monitoring device in kidney transplant patients. This qualitative study was embeddedin a feasibility trial and aimed to test the device's clinical acceptability and obtain suggestions for the development of the intervention. Objectives included exploring the experiences of feasibility study participants and identifying barriers to the implementation of implantable Doppler probes in clinical practice. MATERIALS AND METHODS: We conducted semi-structured interviews containing open-ended questions with 12 feasibility study participants recruited by purposive sampling. All interviews were audio-recorded with verbatim transcription. Thematic data analysis was performed at the latent level by using an inductive approach with a previously published 6-phase guide. RESULTS: Three key themes emerged: (1) perceived value of the intervention in clinical practice, (2) challenges and barriers to implementation of the intervention, and (3) suggestions forthe development of the intervention. Due to functional limitations and lack of research, medical professional participants revealed clinical equipoise regarding the utility of implantable Doppler probes. However,the device was well received by patient participants. Challenges included device training needs for medical professionals and educational sessions for patients. Innovative ideas for development included the insertion of a display screen, adopting disposable units to reduce overall cost, online access allowing remote monitoring, decreasing external monitoring unit size, and integrating a wireless connection with the probe to reduce signal errors and increase patient safety. CONCLUSIONS: The clinical need for blood flow sensing technology in kidney transplants has been widely acknowledged. Implantable Doppler probes may be a beneficial adjunct in the early postoperative surveillance of kidney transplant patients. However, the device's technical limitations are the main challenges to its acceptance in clinical practice.

Association of latent autoimmune diabetes of adults with type 3 polyglandular autoimmune syndrome-a diagnostic challenge.

Autoimmune polyendocrine syndromes (APS) encompass m ultiple e ndocrin e gland ins ufficiencies asso ci ated wit h auto immune disease. This c as e report underscores the importance of recognising the association between latent auto immune di a betes of ad ults (LADA) and type 3 polyglandular syndrome. A 42-year-old man belonging to R awalpi ndi, Pakistan, p resented to th e out patient department (OPD) of Ali Medi cal Centre, Islamab ad, i n Januar y 2023 with the complaints o f e xtreme thirs t and frequent urination. The patient reported consistently raised app etite an d eating four to five meals a day along with abrupt weight loss, dry mouth, fatigue occasional dizziness, an d dyspnoea. He was diagno s ed with type 3 polygla ndular syndrome w ith associat io n of LADA. Daily administration of 10 units of glargine insulin, along with six units of rapid-acting insulin, was prescribed. The patient's H bA1c level reduce d in a few months afte r succe ssive follow-up. Patients who exhi bit uncontrol led diabe tes despite dietar y and oral hypoglycaemic management should be further investigated for multiple au toimmune endocrine disorders.

Effects of curcumin in patients with non-alcoholic fatty liver disease: A systematic review and meta-analysis.

Background: Curcumin is an anti-inflammatory that is proposed to have a positive impact on patients with non-alcoholic fatty liver disease (NAFLD). We aim to assess the effects of curcumin in patients with NAFLD. Methods: Clinical trials from PubMed, Scopus, the Web of Science, and Cochrane CENTRAL with variables alanine transferase, aspartate transaminase, alkaline phosphatase, glycated hemoglobin (HBA1c), BMI, waist circumference, total cholesterol, total glycerides, high-density lipoproteins, and low-density lipoproteins were included. Homogeneous and heterogeneous were analyzed under a fixed-effects model and the random-effects model, respectively. Results: Fourteen clinical trials found that curcumin has no statistically significant effect on alanine transferase (MD = -2.20 [-6.03, 1.63], p = 0.26], aspartate transaminase (MD = 1.37 [-4.56, 1.81], p = 0.4), alkaline phosphatase (MD = 3.06 [-15.85, 9.73], p = 0.64), glycated hemoglobin (HBA1c), (MD = -0.06 [-0.13, 0.02], p = 0.16], and BMI (MD = 0.04 [-0.38, 0.46], p = 0.86). Curcumin reduced the waist circumference (MD = -4.87 [-8.50, -1.25], p = 0.008). Lipid profile parameters were not significant, except the total glycerides (MD = -13.22 [-24.19, -2.24], p = 0.02). Conclusions: Curcumin significantly reduces total glycerides and waist circumference in NAFLD.

Efficacy and safety of laparoscopic Heller's myotomy versus pneumatic dilatation for achalasia: A systematic review and meta-analysis of randomized controlled trials.

BACKGROUND AND OBJECTIVES: Achalasia has several treatment modalities. We aim to compare the efficacy and safety of laparoscopic Heller myotomy (LHM) with those of pneumatic dilatation (PD) in adult patients suffering from achalasia. METHODS: We searched Cochrane CENTRAL, PubMed, Web of Science, SCOPUS and Embase for related clinical trials about patients suffering from achalasia. The quality appraisal and assessment of risk of bias were conducted with GRADE and Cochrane's risk of bias tool, respectively. Homogeneous and heterogeneous data was analyzed under fixed and random-effects models, respectively. RESULTS: The pooled analysis of 10 studies showed that PD was associated with a higher rate of remission at three months, one year, three years and five years (RR = 1.25 [1.09, 1.42] (p = 0.001); RR = 1.13 [1.05, 1.20] (p = 0.0004); RR = 1.48 [1.19, 1.82] (p = 0.0003); RR = 1.49 [1.18, 1.89] (p = 0.001)), respectively. LHM was associated with lower number of cases suffering from adverse events, dysphagia and relapses (RR = 0.50 [0.25, 0.98] (p = 0.04); RR = 0.33 [0.16, 0.71] (p = 0.004); RR = 0.38 [0.15, 0.97] (p = 0.04)), respectively. There is no significant difference between both groups regarding the lower esophageal pressure, perforations, remission rate at two years, Eckardt score after one year and reflux. CONCLUSION: PD had higher remission rates than LHM at three months, one year and three years, but not at two years or five years. More research is needed to determine whether PD has a significant advantage over LHM in terms of long-term remission rates.

Microorganism-mediated biodegradation for effective management and/or removal of micro-plastics from the environment: a comprehensive review.

Micro- plastics (MPs) pose significant global threats, requiring an environment-friendly mode of decomposition. Microbial-mediated biodegradation and biodeterioration of micro-plastics (MPs) have been widely known for their cost-effectiveness, and environment-friendly techniques for removing MPs. MPs resistance to various biocidal microbes has also been reported by various studies. The biocidal resistance degree of biodegradability and/or microbiological susceptibility of MPs can be determined by defacement, structural deformation, erosion, degree of plasticizer degradation, metabolization, and/or solubilization of MPs. The degradation of microplastics involves microbial organisms like bacteria, mold, yeast, algae, and associated enzymes. Analytical and microbiological techniques monitor microplastic biodegradation, but no microbial organism can eliminate microplastics. MPs can pose environmental risks to aquatic and human life. Micro-plastic biodegradation involves fragmentation, assimilation, and mineralization, influenced by abiotic and biotic factors. Environmental factors and pre-treatment agents can naturally degrade large polymers or induce bio-fragmentation, which may impact their efficiency. A clear understanding of MPs pollution and the microbial degradation process is crucial for mitigating its effects. The study aimed to identify deteriogenic microorganism species that contribute to the biodegradation of micro-plastics (MPs). This knowledge is crucial for designing novel biodeterioration and biodegradation formulations, both lab-scale and industrial, that exhibit MPs-cidal actions, potentially predicting MPs-free aquatic and atmospheric environments. The study emphasizes the urgent need for global cooperation, research advancements, and public involvement to reduce micro-plastic contamination through policy proposals and improved waste management practices.

Exploring mosquito abundance and Plasmodium infection through nested-PCR: implications for disease surveillance and control.

The Plasmodium is responsible for malaria which poses a major health threat, globally. This study is based on the estimation of the relative abundance of mosquitoes, and finding out the correlations of meteorological parameters (temperature, humidity and rainfall) with the abundance of mosquitoes. In addition, this study also focused on the use of nested PCR (species-specific nucleotide sequences of 18S rRNA genes) to explore the Plasmodium spp. in female Anopheles. In the current study, the percentage relative abundance of Culex mosquitoes was 57.65% and Anopheles 42.34% among the study areas. In addition, the highest number of mosquitoes was found in March in district Mandi Bahauddin at 21 °C (Tmax = 27, Tmin = 15) average temperature, 69% average relative humidity and 131 mm rainfall, and these climatic factors were found to affect the abundance of the mosquitoes, directly or indirectly. Molecular analysis showed that overall, 41.3% of the female Anopheles pools were positive for genus Plasmodium. Among species, the prevalence of Plasmodium (P.) vivax (78.1%) was significantly higher than P. falciparum (21.9%). This study will be helpful in the estimation of future risk of mosquito-borne diseases along with population dynamic of mosquitoes to enhance the effectiveness of vector surveillance and control programs.

ProtTrans and multi-window scanning convolutional neural networks for the prediction of protein-peptide interaction sites.

This study delves into the prediction of protein-peptide interactions using advanced machine learning techniques, comparing models such as sequence-based, standard CNNs, and traditional classifiers. Leveraging pre-trained language models and multi-view window scanning CNNs, our approach yields significant improvements, with ProtTrans standing out based on 2.1 billion protein sequences and 393 billion amino acids. The integrated model demonstrates remarkable performance, achieving an AUC of 0.856 and 0.823 on the PepBCL Set_1 and Set_2 datasets, respectively. Additionally, it attains a Precision of 0.564 in PepBCL Set 1 and 0.527 in PepBCL Set 2, surpassing the performance of previous methods. Beyond this, we explore the application of this model in cancer therapy, particularly in identifying peptide interactions for selective targeting of cancer cells, and other fields. The findings of this study contribute to bioinformatics, providing valuable insights for drug discovery and therapeutic development.

Molecular Mechanisms of Ischemic Stroke: A Review Integrating Clinical Imaging and Therapeutic Perspectives.

Ischemic stroke poses a significant global health challenge, necessitating ongoing exploration of its pathophysiology and treatment strategies. This comprehensive review integrates various aspects of ischemic stroke research, emphasizing crucial mechanisms, therapeutic approaches, and the role of clinical imaging in disease management. It discusses the multifaceted role of Netrin-1, highlighting its potential in promoting neurovascular repair and mitigating post-stroke neurological decline. It also examines the impact of blood-brain barrier permeability on stroke outcomes and explores alternative therapeutic targets such as statins and sphingosine-1-phosphate signaling. Neurocardiology investigations underscore the contribution of cardiac factors to post-stroke mortality, emphasizing the importance of understanding the brain-heart axis for targeted interventions. Additionally, the review advocates for early reperfusion and neuroprotective agents to counter-time-dependent excitotoxicity and inflammation, aiming to preserve tissue viability. Advanced imaging techniques, including DWI, PI, and MR angiography, are discussed for their role in evaluating ischemic penumbra evolution and guiding therapeutic decisions. By integrating molecular insights with imaging modalities, this interdisciplinary approach enhances our understanding of ischemic stroke and offers promising avenues for future research and clinical interventions to improve patient outcomes.

Incidence of Post-operative Gastro-esophageal Reflux Disorder in Patients Undergoing Laparoscopic Sleeve Gastrectomy: A Systematic Review and Meta-analysis.

Gastroesophageal reflux disease (GERD) is a common concern following laparoscopic sleeve gastrectomy (LSG). This paper aimed to assess the incidence of reflux disease following these bariatric procedures. A literature search was conducted to identify observational studies and clinical trials reporting patients developed GERD disease after LSG. Twenty-two studies included in the analysis, involve 20,495 participants, indicated that the estimated proportion of patients who developed post-surgery GERD was 0.35 (95% CI 0.30-0.41). Subgroup analysis revealed a proportion of 0.33 (95% CI 0.27-0.38) in observational studies and 0.58 (95% CI 0.39-0.75) in clinical trials. High heterogeneity was noted across studies (I2 = 98%). Sensitivity analyses and publication bias assessments were performed to enhance the robustness of the results. Our findings highlight a moderate to high risk of developing GERD following LSG surgery.

Simulation analysis of non-respondent information in context of small domain.

In the real-world, there are various situations when all units are not accessible of the respondent called unit non-response. The effect of unit non-response is a tricky matter for estimating the total number of unit. The present work highlights the interest about subpopulations (domains) in two affairs: i. if domains total of the supportive information is accessible ii. if domains total of the supportive variable does not access. The government needs to be introducing the actual facilities in these small domains. The supportive information is used to find out the estimate of the non respondent information and to apply this information for desired domains. Sometimes, it has been found that the accessible auxiliary variable for the domains might be positive shape. Therefore, it develops an appropriate model that has positive skewness. The present context highlighted the indirect method using a power-based estimation with calibration approach. By combining power based estimation and calibration technique, it is possible to obtain more accurate estimates for intended small domains. Even the supportive information is positively biased. This approach helps us in mitigating the effect of non-respondent and improving the overall reliability of the estimators. The simulation was conducted for different sizes 70 and 90 when nonresponse variable in the study variable. The results show that investigated power-based estimate provides better option over relevant exponential, ratio, and generalized regression estimators for intended domains.

DeepPLM_mCNN: An approach for enhancing ion channel and ion transporter recognition by multi-window CNN based on features from pre-trained language models.

Accurate classification of membrane proteins like ion channels and transporters is critical for elucidating cellular processes and drug development. We present DeepPLM_mCNN, a novel framework combining Pretrained Language Models (PLMs) and multi-window convolutional neural networks (mCNNs) for effective classification of membrane proteins into ion channels and ion transporters. Our approach extracts informative features from protein sequences by utilizing various PLMs, including TAPE, ProtT5_XL_U50, ESM-1b, ESM-2_480, and ESM-2_1280. These PLM-derived features are then input into a mCNN architecture to learn conserved motifs important for classification. When evaluated on ion transporters, our best performing model utilizing ProtT5 achieved 90% sensitivity, 95.8% specificity, and 95.4% overall accuracy. For ion channels, we obtained 88.3% sensitivity, 95.7% specificity, and 95.2% overall accuracy using ESM-1b features. Our proposed DeepPLM_mCNN framework demonstrates significant improvements over previous methods on unseen test data. This study illustrates the potential of combining PLMs and deep learning for accurate computational identification of membrane proteins from sequence data alone. Our findings have important implications for membrane protein research and drug development targeting ion channels and transporters. The data and source codes in this study are publicly available at the following link: https://github.com/s1129108/DeepPLM_mCNN.

Coherent multi-band MIMO radar: robustness analysis to SSMF-based RF signal delivery.

A numerical evaluation is conducted to assess the impact of distributing radio frequency (RF) signals through optical fiber links on the performance of a coherent multi-band multiple-input multiple-output (MIMO) radar system. The analysis focuses on scenarios where the antennas are widely separated in comparison to the employed signal wavelengths. The development of a model to quantify the phase noise (PN) induced on each RF band due to the signal transmission through optical fiber links between the centralized base station and each radar peripheral is described. Monte Carlo simulation results are collected to estimate the key performance indicators (KPIs) for varying standard single-mode fiber (SSMF) length and different PN contributions. The main contributors to the PN are revealed to be chromatic dispersion (CD), double Rayleigh scattering (DRS), and mechanical vibrations. In a shipborne scenario, a significant performance degradation occurs only when the length of the fiber links reaches approximately 20 km. Further, the PN impact has also been studied in a shipborne scenario to analyze the robustness of the system for worse phase noise level assumptions. The results reveal excellent robustness of the proposed centralized acquisition and processing approach in the presence of both very long fiber links and economically employed RF oscillators.

Geographical distribution of radon and associated health risks in drinking water samples collected from the Mulazai area of Peshawar, Pakistan.

Geospatial methods, such as GIS and remote sensing, map radon levels, pinpoint high-risk areas and connect geological traits to radon presence. These findings direct health planning, focusing tests, mitigation, and policies where radon levels are high. Overall, geospatial analyses offer vital insights, shaping interventions and policies to reduce health risks from radon exposure. There is a formidable threat to human well-being posed by the naturally occurring carcinogenic radon (222Rn) gas due to high solubility in water. Under the current scenario, it is crucial to assess the extent of 222Rn pollution in our drinking water sources across various regions and thoroughly investigate the potential health hazards it poses. In this regard, the present study was conducted to investigate the concentration of 222Rn in groundwater samples collected from handpumps and wells and to estimate health risks associated with the consumption of 222Rn-contaminated water. For this purpose, groundwater samples (n = 30) were collected from handpumps, and wells located in the Mulazai area, District Peshawar. The RAD7 radon detector was used as per international standards to assess the concentration of 222Rn in the collected water samples. The results unveiled that the levels of 222Rn in the collected samples exceeded the acceptable thresholds set by the US Environmental Protection Agency (US-EPA) of 11.1 Bq L-1. Nevertheless, it was determined that the average annual dose was below the recommended limit of 0.1 mSv per year, as advised by both the European Union Council and the World Health Organization. In order to avoid the harmful effects of such excessive 222Rn concentrations on human health, proper ventilation and storage of water in storage reservoirs for a long time before use is recommended to lower the 222Rn concentration.

Effects of silymarin use on liver enzymes and metabolic factors in metabolic dysfunction-associated steatotic liver disease: a systematic review and meta-analysis.

Background: Fatty liver disease comprises a wide range of related liver disorders affecting mainly people who drink no or minimal amounts of alcohol. Silymarin is a member of the Carduus marianum family that has been used for centuries to treat different diseases. There is little evidence supporting its efficacy in humans. Objectives: To evaluate the effects of Silymarin in patients with non alcoholic fatty liver disease (NAFLD) or recently renamed metabolic dysfunction-associated steatotic liver disease (MASLD). Methods: We searched PubMed, SCOPUS, Web of Science, and Cochrane Library for relevant clinical trials assessing the use of silymarin in patients with NAFLD. A risk of bias assessment was performed using Cochrane's risk of bias tool. We included the following outcomes: alanine aminotransferase (ALT), aspartate aminotransferase (AST), γ-glutamyl transferase (GGT), total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL) (mg/dL), degree of fibrosis resolution, low-density lipoprotein (LDL), and HOMA-IR. We analyzed continuous data using mean difference (MD) and relative 95% confidence interval (CI). Results: We included nine clinical trials. We found that silymarin significantly reduced the levels of ALT (MD= -17.12 [-28.81, -4.43]), (P < 0.004), AST (MD= -12.56 [-19.02, -6.10]), (P < 0.0001) and TG (MD = -22.60 [-23.83, -21.38]) (p < 0.00001). It also improved HDL (MD= 2.13 [1.60, 2.66]), (P < 0.01)). There was no significant difference regarding GGT (P=o.07), TC (P= 0.52), LDL (P= 0.06), HOMA-IR (P= 0.06) and BMI (p=0.1).One study reported significant improvement in the degree of fibrosis (P = 0.023). Conclusion: Silymarin treatment significantly reduces biochemical and transaminase levels in patients with MASLD.

Modulating plant-soil microcosm with green synthesized ZnONPs in arsenic contaminated soil.

Biogenic nanoparticle (NP), derived from plant sources, is gaining prominence as a viable, cost-effective, sustainable, and biocompatible alternative for mitigating the extensive environmental impact of arsenic on the interplay between plant-soil system. Herein, the impact of green synthesized zinc oxide nanoparticles (ZnONPs) was assessed on Catharanthus roseus root system-associated enzymes and their possible impact on microbiome niches (rhizocompartments) and overall plant performance under arsenic (As) gradients. The application of ZnONPs at different concentrations successfully modified the arsenic uptake in various plant parts, with the root arsenic levels increasing 1.5 and 1.4-fold after 25 and 50 days, respectively, at medium concentration compared to the control. Moreover, ZnONPs gradients regulated the various soil enzyme activities. Notably, urease and catalase activities showed an increase when exposed to low concentrations of ZnONPs, whereas saccharase and acid phosphatase displayed the opposite pattern, showing increased activities under medium concentration which possibly in turn influence the plant root system associated microflora. The use of nonmetric multidimensional scaling ordination revealed a significant differentiation (with a significance level of p < 0.05) in the structure of both bacterial and fungal communities under different treatment conditions across root associated niches. Bacterial and fungal phyla level analysis showed that Proteobacteria and Basidiomycota displayed a significant increase in relative abundance under medium ZnONPs concentration, as opposed to low and high concentrations, respectively. Similarly, in depth genera level analysis revealed that Burkholderia, Halomonas, Thelephora and Sebacina exhibited a notably high relative abundance in both the rhizosphere and rhizoplane (the former refers to the soil region influenced by root exudates, while the latter is the root surface itself) under medium concentrations of ZnONPs, respectively. These adjustments to the plant root-associated microcosm likely play a role in protecting the plant from oxidative stress by regulating the plant's antioxidant system and overall biomass.

Efficacy and safety of terlipressin and albumin vs. noradrenaline and albumin in adult patients with hepatorenal syndrome: A systematic review and meta-analysis.

INTRODUCTION AND OBJECTIVES: Hepatorenal syndrome (HRS) is a serious complication of cirrhosis treated with various medications. We aim to evaluate terlipressin and albumin's effectiveness and safety compared to albumin and noradrenaline in adult hepatorenal disease patients. MATERIALS AND METHODS: Clinical trials from four databases were included. Cochrane's approach for calculating bias risk was utilized. We rated the quality evaluation by Grading of Recommendations Assessment, Development, and Evaluation (GRADE). We included the following outcomes: serum creatinine (mg/dl), urine output (ml/24 h), mean arterial pressure (mmHg), reversal rate of HRS, mortality rate, blood plasma renin activity (ng/ml/h), plasma aldosterone concentration (pg/ml), urine sodium (mEq/l), and creatinine clearance (ml/min). RESULTS: Our analysis of nine clinical studies revealed that the noradrenaline group was associated with higher creatinine clearance (MD = 4.22 [0.40, 8.05]), (P = 0.03). There were no significant differences in serum creatinine levels (MD = 0.03 [-0.07, 0.13]), urinary sodium (MD = -1.02 [-5.15, 3.11]), urine output (MD = 32.75 [-93.94, 159.44]), mean arterial pressure (MD = 1.40 [-1.17, 3.96]), plasma renin activity (MD = 1.35 [-0.17, 2.87]), plasma aldosterone concentration (MD = 55.35 [-24.59, 135.29]), reversal rate of HRS (RR = 1.15 [0.96, 1.37]), or mortality rate (RR = 0.87 [0.74, 1.01]) between the two groups (p-values > 0.05). CONCLUSIONS: Noradrenaline is a safe alternative medical therapy for HRS.

Categorization of tweets for damages: infrastructure and human damage assessment using fine-tuned BERT model.

Identification of infrastructure and human damage assessment tweets is beneficial to disaster management organizations as well as victims during a disaster. Most of the prior works focused on the detection of informative/situational tweets, and infrastructure damage, only one focused on human damage. This study presents a novel approach for detecting damage assessment tweets involving infrastructure and human damages. We investigated the potential of the Bidirectional Encoder Representations from Transformer (BERT) model to learn universal contextualized representations targeting to demonstrate its effectiveness for binary and multi-class classification of disaster damage assessment tweets. The objective is to exploit a pre-trained BERT as a transfer learning mechanism after fine-tuning important hyper-parameters on the CrisisMMD dataset containing seven disasters. The effectiveness of fine-tuned BERT is compared with five benchmarks and nine comparable models by conducting exhaustive experiments. The findings show that the fine-tuned BERT outperformed all benchmarks and comparable models and achieved state-of-the-art performance by demonstrating up to 95.12% macro-f1-score, and 88% macro-f1-score for binary and multi-class classification. Specifically, the improvement in the classification of human damage is promising.

Consanguineous Marriages and the Perception of Wife-Beating Justification in Pakistan: An Application of Fairlie Decomposition Analysis.

Pakistan has a significant occurrence of both consanguineous marriages and intimate partner violence (IPV), which may be interlinked. The practice of consanguineous marriages could potentially influence women to rationalize and accept instances of IPV. Such attitudes perpetuate a culture of violence against women, creating difficulties for victims to reject or escape from it. Pakistan has high prevalence rate of consanguineous marriages and IPV. However, no research has been done to explain the difference in acceptance of IPV between women in consanguineous and non-consanguineous marriages. This study used Pakistan Demographic and Health Survey data and applied association tests, logistic regression, and the Fairlie decomposition analysis. The Fairlie decomposition helps us identify the relative contribution of different socioeconomic factors in the inequalities in IPV between the two types of marriages. Five dimensions of wife-beating justification are used as outcome variables. Age, education, and empowerment of women, husband education, woman witness parental violence, region, place of residence, and household wealth status are used as independent variables. The logistic regression results indicated that women in consanguineous marriages of younger age and who witnessed parental violence are more likely to justify wife-beating than those who belong to wealthy households and enjoy more empowerment. Compared to the Punjab province, women residing in Sindh and Baluchistan are less likely and in the Khyber Pakhtunkhwa province are more likely to justify wife-beating. The Fairlie decomposition analysis shows that household wealth status, woman education, and empowerment are the main contributors in explaining the gap between the wife-beating justification of the two groups. The IPV gap can be reduced up to 77% if the distribution of women in different wealth quantiles of the consanguineous marriage group is identical to the non-consanguineous marriage group. Furthermore, woman education level is the second highest contributor. Consanguineous marriages are a prevalent cultural practice in Pakistan and are associated with several negative health and social outcomes. Addressing this issue requires a sustained and comprehensive effort by the government, civil society, and international partners, with a particular focus on women from poor households with less education.

Gold nanoparticle-based selective and efficient spectrophotometric assay for the insecticide methamidophos.

A reliable, rapid, and inexpensive nano-sized chemosensor is presented for methamidophos (MET) - an insecticide. Poly(lactic acid) (PLA)-stabilized gold nanoparticles (AuNPs) were synthesized by a simple one-pot, two-phase chemical reduction method. The synthesized PLA-AuNPs were subsequently employed for selective, efficient, and quantitative detection of MET. MET is one of the highly toxic pesticides used for eradication of agricultural and urban insects. Upon the addition of MET, the wine-red color of PLA-AuNPs swiftly transformed into greyish-blue, further corroborated by a significant bathochromic and hyperchromic shift in the SPR band. The presence of other interfering insecticides, metal salts, and drugs did not have any pronounced effect on quantitative MET detection. The detection limit, the quantification limit, and linear dynamic range of MET utilizing PLA-AuNPs were  0.0027 µM, 0.005 µM, and 0.005-1000 µM, respectively. The PLA-AuNP-based assay renders an efficient, rapid, accurate, and selective quantification of MET in food, biological, and environmental samples. The proposed sensor provides an appropriate platform for fast and on-the-spot determination of MET without requiring a well-equipped lab setup.