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Author(s): Norazwani binti Ali [sup.1], Loong Chuen Lee [sup.1] [sup.2], Ab Aziz Ishak [sup.1] Author Affiliations: (1) grid.412113.4, 0000 0004 1937 1557, Forensic Science Program, CODTIS, Faculty of Health Sciences, [...], Soil is useful physical evidence for linking a suspect/victim to a particular crime scene. However, the discrimination of soils from neighboring locations can be a very challenging task. In this work, we evaluated four row-wise manipulations (RWMs) on chromatographic data of soils for improving the discriminative ability of the data. Five red, brown, and yellowish-brown soils were collected from five nearby locations in Bangi, Malaysia. Then, the non-volatile organic compounds of soils extracted via acetonitrile were determined using an ultra-performance liquid chromatography (UPLC) system. Eventually, three sets of UPLC data were obtained at 254 nm and independently pre-processed using the four RWMs, respectively. The improvements caused by the RWMs were first derived from visual inspection on the mean chromatograms and scores plot of principal component analysis. Next, the two most desired principal components were determined using a one-way ANOVA-least significant difference test and inspected via composite box plots. Results showed that standard normal variate is the only one that caused the positive impacts though not always. Normalization to sum appeared to reduce the quality of the raw data. Hence, in conclusion, the use of RWMs on the UPLC chromatogram must be carefully evaluated.

Abstract Background Nomophobia, the fear of being without a smartphone or disconnected from mobile networks, has become a growing concern in today’s digital era, impacting mental health and professional productivity. This study assesses the prevalence of nomophobia among respiratory therapy (RT) staff in Saudi Arabia and examines sociodemographic factors associated with moderate to severe levels of nomophobia, offering insights into digital dependency within this healthcare workforce. Methods A nonprobability cross-sectional survey, utilizing the Nomophobia Questionnaire (NMP-Q), was distributed via social media platforms to respiratory therapists (RTs) in Saudi Arabia from October 17, 2022, to January 13, 2023. Data were presented in terms of frequency and percentage, and logistic regression analysis was conducted to identify factors associated with moderate to severe nomophobia. Results Overall, 1,001 RTs completed the online survey. The prevalence of nomophobia among RT staff was 95% (95% CI 67–94), with a mean ± SD of 56 ± 20, indicating a mild level of nomophobia among the participants. Female RT staff were one time more likely to experience moderate to severe levels of nomophobia [OR: 1.4 (95% CI 1.06–1.85); p = 0.019]. RT staff with work experience ≥ 11 years were twice as likely to experience moderate to severe levels of nomophobia [OR: 2.07 (95% CI 1.28–3.34); p = 0.003]. Staff who reported active smoking status were almost twice as likely to experience moderate to severe levels of nomophobia [(OR): 1.79 (1.24–2.60); p = 0.045]. Finally, RT staff who worked in private hospitals were one time more likely to experience moderate to severe levels of nomophobia [(OR): 1.4 (1.01–1.95); p = 0.002]. Conclusions Nomophobia is prevalent among respiratory therapy staff in Saudi Arabia, with a majority experiencing moderate to severe levels. The identification of key sociodemographic risk factors associated with this condition underscores the need for targeted interventions and support strategies to improve both the well-being and productivity of the workforce.

Abstract The purpose of this study was to test the effectiveness of using IVR to help Indonesian EFL students cope with the twenty-first century. We examined 53 Indonesian university students in this study to see how immersive virtual reality (IVR) impacts their English as a Foreign Language (EFL) proficiency and transferable skill development. The pre-experimental design used a mixed methodology approach, combining qualitative and quantitative methods. Statistical analysis, using paired sample t-test and ANOVA, showed that post-test scores (mean = 84.72, SD = 7.83) were significantly higher than pre-test scores (mean = 58.96, SD = 8.16, p

Abstract Background Maternal health remains a critical public health concern in Ghana, with significant disparities in healthcare access between rural and urban areas. Women in rural regions face a higher risk of maternal mortality, preterm births, and pregnancy complications due to limited health care services. Migration patterns further exacerbate these issues by disrupting access to essential reproductive and maternal services. While some women travel specifically for medical care and later returned, others migrate due to family-related reasons.This study investigates the association between migration patterns and access to reproductive and maternal healthcare services among Ghanaian women aged 15–49. Methods Data from the 2022 Ghana Demographic Health Survey was used for this study. Bivariate and multivariable logistic regression models were used to investigate the association between migration patterns and access to reproductive and maternal healthcare services. Results There was no significant association between the migration stream and unmet family planning needs in both unadjusted and adjusted logistic models. The odds of adequate antenatal care were higher among rural to urban, urban to urban, and urban non-migrants than rural non-migrants. In the adjusted model, however, it only remained significant for rural to urban migrants. The odds of institutional delivery were significantly higher among rural to urban and urban to rural migrants than rural non-migrants. However, in the adjusted model, the odds of institutional delivery only remained significant for urban to urban, rural to urban, and urban non-migrants. Conclusion Migration patterns are associated with access to reproductive and maternity healthcare in Ghana. Women who migrate from urban to urban areas experience the most significant improvement in accessing antenatal care and institutional delivery services. Regardless of migration history, urban residents have better access than rural non-migrants. To improve maternal healthcare, the government should enhance rural healthcare infrastructure and staffing, support rural to urban migrants in navigating urban healthcare, and implement comprehensive maternity education campaigns for all women.

Abstract Aims Antimicrobial resistance (AMR) has been declared one of utmost matters of importance in global health by WHO. Awareness of AMR is essential in controlling the spread of resistance. This study is aimed at access the awareness in knowledge attitude and practice of AMR in population of province of Gilgit and Baltistan, Pakistan to help develop initiatives and policies. Subject and methods This cross-sectional study was conducted in Gilgit-Baltistan, Pakistan and a sample of 261 was collected by convenience sampling. Questionnaire was adopted from “Antibiotic Resistance, Multi-country Public Awareness Survey” published by WHO. Pearson’s Chi-Square test and Fischer-Freeman-Halton Exact test were used to analyze the relationship of SES, Highest Education level and residence location with KAP questions. α-Level of ≤ 0.05 was used as significant Results 261 responses were analyzed, majority being female (52.1%) and male (47.5%) with most of them aged from 20 to 40 years (34.9%) and low economic status (83.5%). It was found that although 79.69% had known about antibiotics before, 73.18% never heard about antimicrobial resistance (AMR). Self-medication is reported by 36.4%, and 68.33% obtained antibiotics from a doctor. Higher socioeconomic and educational status were associated with higher knowledge of antibiotics and AMR. Urban respondents demonstrated greater knowledge of AMR and were less likely to self-medicate compared to suburban participants (68.7% vs. 54.5%). Conclusions Results showed that proactive efforts are needed to educate people about the awareness of AMR and all its harms. Campaigns should target people from Low SES, Low education groups and rural areas.

Abstract Background Patients with Non-small Cell Lung Cancer (NSCLC) presenting with Mesenchymal–epithelial transition exon 14 skipping mutation (MET ex14) have an unfavorable prognosis with traditional therapies. MET inhibitors have altered the therapeutic paradigm of NSCLC. MET ex14 skipping alteration is reported in 3–4% cases (N Engl J Med 383(10):944-957, 2020, Cancer Discov 5(8):842-9, 2015). Randomized controlled trials have reported noteworthy outcomes of selective MET tyrosine kinase inhibitors (TKIs), however real-world data from the Indian sub-continent is lacking. Methods The current study is a non-interventional retrospective multi-centre analysis reporting on real-world data of NSCLC patients with MET ex14 skipping alteration from two apex cancer centers from India. Data of 49 eligible NSCLC patients with MET ex14 mutations fulfilling the inclusion and exclusion criteria were reviewed and analysed. Kaplan Meier (KM) estimating method was used to estimate the overall survival (OS) and progression free survival (PFS). Log rank test was used to compare the survival curves between the groups. A p-value 49% 20 40.8 MET exon 14 skipping DNA only 0 0 RNA only 30 61.2 Both DNA & RNA 19 38.8 Conclusion The current study comprises of the largest MET ex14 mutated NSCLC patient cohort reporting on the real-world data of MET TKI therapy from the Indian subcontinent. MET TKI showed higher systemic and intracranial efficacy with manageable safety profile. The current study represents an unmet need for more clinical phase 3 study for rare genomic alterations as well as patient access programs in the Indian subcontinent.

Abstract Coal Bed Methane (CBM) is a kind of natural gas found in coal seams as adsorbed gases, unlike free gases in a conventional reservoir. These coal beds are complex, with a wide distribution of porosity from nano to micro and permeability in order of change. This review study examines complexities associated with understanding CBM reservoirs and important processes that must be considered during production. CBM extraction requires methane desorption from the coal surface, which is achieved by lowering the CBM reservoir pressure by dewatering the associated groundwater. The reservoir pressure reduction due to dewatering and subsequent production of CBM gas results in significant modification of the reservoir properties, particularly porosity and permeability. Thus, it has been recommended from the present study that an improved understanding of the storage and transmission of gas from a coal-seam requires a coupled effect of geo-mechanical stresses and desorption effect for a spatially and temporally varying pore network coal-seam geometry. Given the complexities and associated challenges in modelling these effects at the field scale, we present a set of practical queries for further investigation. This discussion addresses the need to study the environmental impacts associated with producing natural gas from a CBM reservoir.

Abstract Background Asthma is a chronic inflammatory disease characterized by recurrent and fluctuating airflow limitations. The objective of the study was to assess the association between stress and asthma symptoms among students enrolled at public universities in Riyadh, Saudi Arabia. Methodology A cross-sectional study was conducted, utilizing the Arabic-validated questionnaires of the asthma control test (ACT), the Perceived Stress Scale (PSS), and the European Community Respiratory Health Survey (ECRHS) as the primary instrument for data collection. Statistical analysis was performed using RStudio software. Appropriate ethical guidelines were followed throughout the research process. Results The study included 156 public university students in Riyadh, Saudi Arabia. The participants were predominantly female (84.0%) with a median age of 21 years. Using PSS, 3.2% had low, 80.1% had moderate, and 16.6% had high perceived stress levels. In total, 127 participants (81.4%) reported experiencing respiratory symptoms. After adjusting for age, sex, BMI, and smoking status, students with high perceived stress were found to be more likely to report respiratory symptoms compared to those with moderate stress (OR: 6.85, 95% CI 1.20–130.0). This demonstrated a significant association between increased stress and asthma related symptoms. Conclusion High perceived stress levels were associated with respiratory symptoms. These findings should be utilized to build strategies for improving the management and control of asthma symptoms in this population.

Abstract Every year, high salinity reduces agricultural yields by a substantial amount owing to osmotic and ionic impacts that prevent plants from absorbing the required water and promote the hyperaccumulation of ions, which enter the transpiration stream and injure plant cells. Several crops have been shown to benefit from the application of green or biogenic NPs of varying shapes, sizes, and concentrations, which are intended to protect crops against salt stress through enhanced growth metrics, seed germination and yield, improved root architecture, and defensive changes in biochemical/physiological indices. Although the underlying molecular basis of this phenomenon remains unclear, some studies have shown that exposing cells to NPs can alter the expression of several genes that generally respond to salt stress. As a result, biogenic NPs are considered viable alternative techniques for reducing the adverse effects of salinity stress on agricultural production. In the present review, keen emphasis has been placed on how biogenic NPs are helpful in decreasing the adverse effects of salinity stress on crops, which might be useful for the agriculture sector in the coming climate change era.

Abstract This review explores the recycling of used cooking oil, a global waste product with an annual production ranging from 41 to 67 million tons, for waste management and resource recovery. It examines the sources and composition of used cooking oil, focusing on its potential as a feedstock for valuable products. The review analyzes biochemical, thermal, and chemical conversion methods for their application in valorization of UCO (Used Cooking Oil). The advanced techniques such as catalytic upgrades, electrochemical conversion, membrane separation, and supercritical fluid extraction have also been investigated for their role in improving efficiency. Although biodiesel is the widely produced product, the review also sheds light on the recent researches for development of plastic, soap and other value-added products from UCO. Using a case study methodology and a review of recent research, the article also addresses challenges like feedstock variability and environmental impacts. It discusses market trends, regulatory frameworks, and potential research directions, aiming to integrate used cooking oil valorization into sustainable waste management and circular economy practices. Graphical Abstract

Abstract This study investigates the impacts of natural resources, financial development, and non-renewable energy consumption on the quality of the environment by including renewable energy consumption, globalization, and industrialization into the model for full sample countries over the 1985–2019 time spans. This study employs dynamic fixed effects (DFE), dynamic seemingly unrelated regressions (DSUR), and dynamic system generalized method of moments (DSGMM) approaches. The results of the study revealed that globalization and financial development `deteriorate the environmental quality by increasing CO2 emissions. Similarly, non-renewable energy consumption and natural resource depletion also worsen the environmental quality while increasing the usage of renewable energy improves environmental quality due to emitting less CO2 emissions. It is recommended that these countries' governments should focus on globalization. The government should create regulations that force business sectors to adopt more productive and effective technology. Furthermore, to reduce CO2 emissions in full sample countries, energy efficiency could be achieved through adopting energy-saving initiatives, outsourcing energy infrastructure, foreign direct investment in the renewable energy sector, financial development to encourage green infrastructure, and energy production using renewable energy sources and energy conservation measures. Graphical Abstract

Abstract This study examines the effects of hybrid biomass-derived fillers on the mechanical, thermal, and water absorption properties of polylactic acid (PLA) matrix. The sustainable composites are made by the injection molding process by varying rice husk flour and its biocarbon percentage. The present hybrid composite, with 5% and 10% biocarbon reinforcement, achieves maximum tensile and flexural strengths of 61.2 MPa and 135.8 MPa, respectively, surpassing those of neat PLA by 105.6% and 104.8%. Beyond 10% biocarbon reinforcement, higher modulus values with a lower elongation percentage are seen, indicating that the material is stiffer and more brittle. The peak impact strength of 5.25 kJ/m2 is obtained with 10% carbon reinforcement but decreased at higher biocarbon percentages. Despite this, the biocarbon's increased stiffness resulted in superior hardness measurements at higher carbon percentages. Biocarbon's higher thermal stability also improves thermal transition and degradation properties. When the biocarbon content increased from 5 to 25%, the water absorption percentage is decreased. In comparison to hybrid composites with rice husk and biocarbon reinforcement, the composite containing 30% biocarbon exhibits poorer mechanical, thermal, and water-resistive properties. This indicates that the properties of PLA are significantly improved by filler hybridization using biocarbon, compared to using a single filler.

Abstract Pakistan has experienced a notable increase in the frequency and intensity of weather-related events and natural hazards, including floods, driven by multiple factors. This study aims to bridge the gap between hydrological sciences and community resilience by evaluating the impacts of natural hazards in the Upper Indus Basin (UIB), Pakistan. The research aligns with Sustainable Development Goal 13: Climate Action, emphasizing the importance of proactive measures in addressing climate challenges. The factors considered include climate change, examining early warning systems and flood risk management, hydrological forecasting and policies, local awareness, preparedness, and adaptive responses to GLOFs and other natural hazards in UIB, including floods, earthquakes, and landslides. By using the scientific questionnaire from well-educated respondents, this study assesses local awareness, preparedness, and adaptive responses to natural hazards in the UIB. The study is also backed by descriptive analysis, frequency analysis, Relative Importance Index, and correlation analysis. The findings highlight significant public awareness and training gaps, with 30.55% of respondents highlighting deficiencies in existing hazard management practices. Additionally, 98.15% of participants gave their opinion that climate change and global warming are major contributors to GLOF events, and 78.70% reported frequent flood encounters over the past ten years. The study advocates aligning Pakistan's hazard management guidelines with international standards to optimize environmental monitoring, disaster management, and communication systems. The research offers critical insights for community resilience and sustainable climate management, providing a pathway for more informed and efficient regional decision-making.

Abstract Efficient prediction of citrus fruit diseases is essential for maintaining orchard health and productivity. Traditional diagnostic methods, often relying on manual inspection, are labor-intensive and prone to inaccuracies. Deep learning techniques, especially Convolutional Neural Networks (CNNs), offer an automated and accurate alternative. This study introduces a novel model integrating CNN with Gradient Boosting (GB) and optimized using the Nesterov-Accelerated Adaptive Moment Estimation (Nadam) optimizer to enhance prediction accuracy. The model employs a custom CNN architecture combined with GB, leveraging Nadam for faster convergence and improved performance. Trained on a dataset of 3,000 citrus fruit images sourced from Kaggle, the model follows a structured process of preprocessing, feature extraction, integration of GB with CNN, and optimal prediction. Comparative analysis using metrics such as accuracy, precision, F1 score, and recall demonstrates the model's effectiveness, achieving an accuracy of 98.03% and precision of 98.04%. This robust approach addresses limitations of traditional methods by enabling automated feature extraction and reliable disease prediction. The proposed CNN-GB-Nadam model significantly enhances efficiency and reliability, providing a valuable tool for protecting citrus fruit health and improving orchard management practices.

Abstract This study investigates the effects of strength and durability of concrete for different water-cement ratios, aggregate contents, and partial replacement of biomedical waste ash at 5%, 10%, 15%, 20%, and 25% by weight of cement. At 7, 14, and 28 days, the control mix showed inferior mechanical properties, particularly compressive strength, compared to concrete mixtures containing Biomedical Waste Ash (BWA). The replacement of cement by 5% and 10% increased the compressive strength but it is decreasing from 15%. Additionally, BWA modified concrete demonstrated a slower water absorption rate and minimal weight loss under acid test curing conditions, indicating enhanced durability. The economic and environmental benefits of incorporating biomedical waste into concrete promote sustainable construction practices. Using three machine learning approaches—K-Nearest Neighbors (KNN), Random Forest (RF), and CatBoost—the compressive strength of concrete with biomedical waste ash was simulated. Cement, biomedical waste, water absorption, slump, and the water-to-cement ratio were key input variables. Among the models tested, the RF model emerged as the most accurate, with a predictive performance of R2 = 0.9945 and RMSE = 0.7080. Its unparalleled reliability, consistency, and accuracy in predicting compressive strength make it a top choice for this task.

Abstract Chaos theory, with its unique blend of randomness and ergodicity, has become a powerful tool for enhancing metaheuristic algorithms. In recent years, there has been a growing number of chaos-enhanced metaheuristic algorithms (CMAs), accompanied by a notable scarcity of studies that analyze and organize this field. To respond to this challenge, this paper comprehensively analyzes recent advances in CMAs from 2013 to 2024, proposing a novel classification scheme that systematically organizes prevalent and practical approaches for integrating chaos theory into metaheuristic algorithms based on their strategic roles. In addition, a list of 27 standard chaotic maps is explored, and a summary of the application domains where CMAs have demonstrably improved performance is provided. To experimentally demonstrate the capability of chaos theory to enhance metaheuristic algorithms that face common issues such as susceptibility to local optima, non-smooth transitions between global and local search phases, and decreased diversity, we developed a chaotic variant of the recently proposed RIME optimizer, which also encounters these challenges to some extent. We tested C-RIME on the CEC2022 benchmark suite, rigorously analyzing numerical results using statistical metrics. Non-parametric statistical tests, including the Friedman and Wilcoxon signed-rank tests, were also used to validate the findings. The results demonstrated promising performance, with 14 out of 21 chaotic variants outperforming the non-chaotic variant, whereas the piecewise map-based variant achieved the best results. In addition, C-RIME outperformed ten state-of-the-art metaheuristic algorithms regarding solution quality and convergence speed.

Abstract The construction industry is negatively impacted by inefficient energy practices; therefore, sustainable home development requires energy efficiency which is crucial for a sustainable future. Despite previous research in Pakistan looked at each aspect separately, for optimal efficiency benefits, an integrated analysis is required. The objective of this study is to investigate how orientation, glass, HVAC systems, and Smart Composite Insulated Panels (SCIP) work together to maximize residential energy performance. The study builds verified energy models of a case study house in Pakistan using Autodesk Revit and Insight 360. Improvements in efficiency are measured by statistical analysis of design combinations. As compared to baseline, a 45° northeast orientation lowers annual energy costs by 2.35%, according to the results. Windows with triple glazing have a 42.5% lower U-value than those with double glazing. The energy cost of high-efficiency heat pumps is 50.7, whereas that of regular systems is 61.9. Brick walls have a U-value that is 64.2% higher than that of SCIP wall panels. The combined strategy allows for a 20.4% increase in efficiency. Renewable integration, data unique to climates, tenant behavior, governmental incentives, and life cycle sustainability should all be evaluated in future research. The use of multi-parameter energy modelling facilitates the adoption of integrated technology solutions by architects, engineers, and regulators by offering reliable statistical data to guide residential building design and enhance energy efficiency.

Abstract Harmine is a β-carboline alkaloid derived from Peganum harmala, showing a solid antitumor potential in different types of human cancer cells. Unfortunately, the clinical application of this natural alkaloid has been impeded till now by severe toxic side effects, especially neurotoxicity, besides its poor water solubility. Therefore, over the recent years, several semisynthetic derivatives of harmine have been prepared and studied concerning their abilities to inhibit tumor cell proliferation, survival, angiogenesis, migration, and invasion in diverse preclinical models. This review article summarizes the anticancer effects of harmine and its synthetic derivatives, demonstrating their high potential to be developed as novel anticancer drugs to supplement our current therapeutic arsenal in the fight against the globally increasing rate of malignant disorders.

Abstract For sustainable development, wastewater treatment and recycling are inevitable; using adsorbents to treat wastewater is widely accepted. This article is aimed to synthesize adsorbents (novel biochars) from agricultural wastes and to investigate the adsorption behaviours of Pb(II) and Cd(II) on novel biochars. Nitrogen purged biochar (NPBC) was synthesized by pyrolysis with nitrogen purgation of wheat straw; whereas, steam activated biochar (SABC) was synthesized by pyrolysis-cum-hydrothermal (steam) activation. Synthesized NPBC and SABC were characterized by physical, chemical, XRD, FTIR, and SEM–EDX methods. SABC was more porous and amorphous in nature with higher specific surface area (SSA), but consisted relatively less polar surface functional groups than that of NPBC. The external layer of both NPBC and SABC were negatively charged (pH > pHPZC). Results revealed that SABC exhibited 97% and 80% recovery efficiency of Pb(II) and Cd(II), respectively, while NPBC demonstrated Pb(II) and Cd(II) removal efficiencies of 87.6% and 69.4%, respectively, at initial concentrations of 50 and 5 mg L−1. Adsorption of Pb(II) and Cd(II) upon SABC and NPBC occurred spontaneously, also exothermically, but decreased with increased reaction temperature. The maximum adsorption capacities (qmax) of NPBC and SABC for Pb(II) were 452.13 and 1117 mg g−1, whereas for Cd(II) those were 314.9 and 470.43 mg g−1, respectively, according to the Langmuir isotherm approach (R2 > 0.989). So, SABC performed better than NPBC for removing both metals from wastewater. Both NPBC and SABC exhibit substantial prospects for regeneration and consequent adsorbent recovery. Hence, the designed adsorbents can be very effective towards cationic toxic heavy metal removal from wastewater.

Abstract The current study includes the design of soluplus stabilized, lipid-coated, and fucoidan-oleylamine conjugate modified paclitaxel nanocrystals. The nanocrystals (Lipid-NCs) were about 100 nm, homogeneous, stable and showed improved drug release compared to pure PTX. The nanocrystals were subsequently loaded in an in situ gel-forming hydrogel for the intratumoral injection. The resulting hydrogel exhibited a sol-form at the lower temperature of 2–8 °C while converted to a gel-form at the body temperature. The injectable hydrogel had a reasonable viscosity, an acceptable pH, good syringeability, and a quick sol–gel transition. The hydrogel demonstrated high payload potential, homogeneous distribution, and controlled long-term drug release. In vivo studies revealed the higher efficacy of Lipid-NCs hydrogel in tumor inhibition while avoiding systemic toxicity, compared to pure PTX-loaded hydrogel and intravenously administered PTX. In conclusion, nanocrystal-loaded hydrogel is a promising localized drug delivery system for breast cancer therapy. Graphical abstract

Abstract This study aimed to analyze price instability in Bangladesh’s primary staple crops, rice, and wheat, focusing on (1) the effects of food price volatility and inflation on food security and; (2) the importance of prioritizing food price stability in national policy. Using data from the Food and Agriculture Organization's (FAO) Global Information and Early Warning System (GIEWS), the Ministry of Food, and the Bangladesh Bureau of Statistics (BBS), we examined price trends, seasonality, volatility, consumer price index, and food inflation. Our findings show that medium-grade rice in Dhaka experienced frequent price spikes and volatility, with coarse-grade rice showing similar trends. Wheat prices were generally more stable compared to rice. Despite increased rice production over the years, significant price instability and seasonal fluctuations continue in production, imports, and pricing. Seasonality has a limited effect on rice prices, while the private sector dominates imports of both rice and wheat. The consumer price index (CPI) demonstrates that food inflation is gradually rising in rural areas and corresponds with the trend in urban Bangladesh. A review of national policy reveals that food stability, a key pillar of food security, is often overlooked, with no structured system for monitoring market prices. Integrating agricultural and climate policies could enhance resilience and productivity in agriculture. To combat hunger and support sustainable development, the government should monitor both global and local food markets, accounting for demand, scarcity, and market instability. To achieve Sustainable Development Goal (SDG) 2 (Zero Hunger) and ensure food security, the government must update existing policies to address market contradictions.

Abstract Introduction Even before the COVID-19 pandemic, Somalia’s national laboratory services had insufficient diagnostic capacities. We describe how the country moved rapidly from no testing capability to molecular testing and genomic sequencing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other pathogens. Methods We reviewed primary sources information as well as data and records from secondary sources from 1 January 2020 to 31 December 2023. We also analyzed laboratory surveillance data of cases of COVID-19 and other epidemic diseases reported during the same period and the number of laboratory tests performed during the same period. We used this information to demonstrate improvements in laboratory diagnostic capacity in Somalia before, during and after the COVID-19 pandemic. Results The country was able to rapidly scale up testing for SARS-CoV-2 using reverse-transcriptase polymerase chain reaction assays. At the same time, other innovative solutions were used for testing, such as repurposing tuberculosis GeneXpert diagnostic platforms to increase access to testing at points-of-care and introducing antigen rapid diagnostic tests for hard-to-reach communities. Somalia also acquired new generation sequencing capability for detection and characterization of circulating SARS-CoV-2. These laboratory and testing enhancements have enabled Somalia to participate in surveillance for priority diseases and detection of outbreaks caused by emerging pathogens. Conclusion Somalia’s strategic approach to COVID-19 is an inspiring example of resilience and adaptability. Utilizing resources, technology and lessons from COVID-19 enabled the country to increase and improve laboratory services, expand testing capacity, and strengthen workforce capability. As such, Somalia can now better respond to other infectious disease threats and has significantly improved national health security.

Abstract The rise of multidrug-resistant tuberculosis (MDR-TB) remains a critical public health challenge, particularly in developing countries like Ethiopia. This systematic review and meta-analysis aimed to estimate the pooled prevalence of MDR-TB with co-infections and assess its effects among different co-infections in Ethiopia. The systematic review and meta-analysis were conducted from August to October 2024. The study adhered to PRISMA guidelines and utilized various academic databases including PubMed, Web of Science and Science Direct to identify relevant articles. To check for publication bias and small study effects, a funnel plot and Egger’s test were employed. The statistical analysis was performed with R software version 4.4.1. From an original pool of 6,461 papers, 15 studies published between 2014 and 2024 were considered after applying certain inclusion and exclusion criteria. The analysis revealed an overall pooled prevalence of MDR-TB in the context of co-infections at 20% (95% CI: 14.0–26.0). Notably, the prevalence was higher among individuals with HIV co-infection at 23.2% (95% CI: 18.3–28.0), while it was lower in those with diabetes co-infection at 10% (95% CI: 3.0-17.3). The study found significant heterogeneity among the reported prevalence rates (I² = 94.93%, p

Abstract The anti-corrosion properties of Moringa oleifera extract (MOE) have been extensively studied for Al in two molar HCl solution using a variety of techniques, including atomic force microscopy, potentiodynamic polarization, electrochemical impedance spectroscopy, Fourier-transform infrared spectroscopy, and weight loss analysis. According to the study, the inhibitory efficiency (% IE) increases with extract dose but decreases with temperature rise from 25 to 40 °C. The highest 90.1 percent inhibitory efficiency was achieved at 25 °C extract dosage of 300 ppm. MOE functions as a mixed-type inhibitor, affecting both anodic and cathodic processes, according to PDP research. The double layer capacitance (Ceff) declines from 214 to 56 µFcm−2 and the charge transfer resistance (Rct) increases from 3.1 to 27.2 sΩ cm2 with increasing MOE dose, as demonstrated by the Nyquist plot. The Langmuir adsorption isotherm is followed by MOE's adsorption on Al surfaces. The AFM and FTIR measurements corroborate MOE's adsorption on the Al surface. Based on the findings, it can be said that MOE can be utilized as a green inhibitor to reduce metal corrosion in harsh environments.

Abstract The rapid growth of the halal food (HF) industry has created a pressing need for a comprehensive synthesis of the existing body of knowledge. However, there remains a significant gap in the literature regarding the key themes, patterns, and emerging areas in HF research. This study addresses this gap by systematically analyzing the HF literature to identify key themes, patterns, and emerging areas of interest in the HF field. The study employs latent Dirichlet allocation (LDA)-based topic modeling to uncover and map the underlying themes in the HF literature, analyzing 738 publications from Scopus to determine the main topics and trends in HF research. The analysis reveals six main topics in HF research: (1) HF quality, safety assessment, and production methods; (2) HF supply chain management; (3) HF detection and authentication methods; (4) HF and Islamic culture; (5) HF and consumer behavior; and (6) HF and tourism and hospitality. The study identifies an overall increasing trend in HF research over the years, with particular emphasis on HF supply chain management and consumer behavior, while HF and Islamic culture received comparatively lower levels of attention. This study offers a novel and comprehensive analysis of the HF literature using LDA-based topic modeling, highlighting the key themes and patterns in the field. The insights derived from this study hold significant theoretical and practical implications for researchers, policymakers, manufacturers, retailers, and consumers in the rapidly growing HF industry. By identifying the main areas of focus and research gaps, the study serves as a valuable foundation for further research and analysis in the field, ultimately contributing to the ongoing development and evolution of HF research.

Abstract Purpose Transcranial magnetic stimulation (TMS) has emerged as a promising treatment for various neuropsychiatric conditions, including depression, obsessive–compulsive disorder, and Parkinson's disease. Recent research has focused on evaluating its effectiveness in treating patients with anorexia nervosa (AN). This systematic review and meta-analysis examined the impact of TMS on patients with AN and evaluated any potential adverse effects. Methods We conducted search according to PRISMA guidelines and comprehensively analyzed data from multiple databases, including Pubmed, Scopus, Embase, Web of Science, and the Cochrane Library, up to September 13th. Statistical analysis utilized the Comprehensive Meta-analysis software version 3.0. Results The systematic review encompassed 17 studies, with nine undergoing meta-analyses. The primary target for TMS was the dorsolateral prefrontal cortex, with two studies targeting the dorsomedial prefrontal cortex, one targeting the insula and one targeting the inferior parietal lobe. The findings revealed a significant increase in body mass index (BMI) following TMS (SMD: −0.025, 95% CI: −0.0505 to −0.005, P-value = 0.045). Additionally, the Eating Disorder Examination Questionnaire (EDE-Q) score was quantitatively reported in six studies, which permitted its inclusion in the meta-analysis. The analysis exhibited a significant decrease in EDE-Q score after TMS (SMD: 0.634, 95% CI: 0.349–0.919, P-value

Abstract Climate change has contributed to an increase in natural catastrophes over the past five years in Indonesia, causing various forms of damage in urban areas and posing a severe danger to multi-risk governance for municipal governments in Indonesia. This study explores how multi-risk governance strategies encourage sustainable adaptation to climate change and increase urban resilience in Bandung and Makassar City, Indonesia. This study method uses a qualitative-exploratory approach with a case study in two (2) climate-vulnerable cities in Indonesia. Data analysis uses qualitative-interactive analysis. The results of this study show that the impact of climate change in Bandung and Makassar City, Indonesia has caused an increase in the potential for erosion, reduced wetlands along the coast, an increase in the rate of seawater intrusion, a decrease in food production, damage to infrastructure, a reduction in clean water sources, an increase in disease. respiratory, floods, droughts, and other hydrological disasters. This has resulted in many climate approaches and actions being taken to respond to the impact of climate change in Indonesia (Bandung and Makassar City), the results of which are still not optimal to date. This study suggests a sustainable adaptation approach to climate action in Bandung and Makassar City which prioritizes social justice and environmental integrity so that it has a real impact on community vulnerability and environmental damage due to the impacts of climate change. The contribution of this study provides sufficient insight into the institutional approaches and adaptive sustainability measures needed to promote resilience in Indonesia. At the same time, this study will be a useful reference in future research on multi-risk governance and sustainable adaptation strategy for climate action and enhancing urban governance.

Abstract For a long time, researchers have worked to improve the qualities of cement-based mixes. Because of their small size, strong reactivity, and huge surface area, nanoparticles are becoming more and more regarded as one of the greatest substitutes for cement because of their capacity to increase durability and strength. This work presents the results of an experimental investigation into the strength and durability properties of fiber-reinforced concretes with polypropylene (PP) fibers added to the concrete by volume and nano Al2O3 and nano TiO2 are used as partial substitutes for cement. Nano Al2O3 and nano TiO2 particles used ranged in size from 30 to 300 nm. The specimens were cast using cement blended nano Al2O3 and nano TiO2 percentages of 1%, 2%, 3%, and 4% by weight of cement. M55 grade concrete was employed for the casting process. The addition of PP fibers to the concrete was 0.5% by volume. The specimens underwent a battery of mechanical tests, including microstructural testing, compression testing, split tensile strength testing, and rupture modulus testing. Furthermore, tests for durability factors such as porosity, sorptivity, and degradation were conducted, and the findings are presented. By comparing the outcomes, it was shown that the inclusion of 0.5% PP fibers and 2% nano Al2O3 or nano TiO2 improved the mechanical qualities, but a decrease followed this in strength. The findings demonstrated that 2% nano Al2O3 combined with 0.5% PP fiber had a greater mechanical strength than 2% nano TiO2.

Abstract Nowadays, biochar is well recognized for its multiple promising effects on the soil quality and plant health. However, there are limited studies on the utilization of invasive plants for biochar production. In the present study, silicon (Si)-modified biochar was synthesized from Solidago canadensis L., an invasive alien plant in southern China, at different pyrolysis temperatures (450, 550, and 650 ℃). The role of biochar in controlling bacterial wilt, improving soil quality and plant health was assessed. The results revealed that Si-modified biochar had higher wilt suppressive effects than unmodified biochar. Si-modified biochar synthesized at 450 ℃ was found to be the most effective in reducing the abundance of R. solanacearum in soil (66.0%) and the incidence rate of bacterial wilt (59.1%). The Si-modified biochar increased soil available Si (58.2%–147.8%), C/N ratio (85.8–105.0%), and cation exchange capacity (19.7–54.5%). Additionally, it also enhanced the abundance of beneficial bacteria in the soil, such as Bacillus (341.7%), Streptomyces (222.0%), Gaiellales (255.4%), and Gaiella (133.3%). These findings suggest that Si-modified biochar derived from the invasive plant Solidago canadensis L. holds promise as a soil additive for disease control. Graphical Abstract

Abstract Over the past two decades, machine learning (ML) has transformed manufacturing, particularly in optimizing production and quality control. A significant challenge in ML applications is obtaining sufficient training data, which data augmentation aims to address. While widely applied to image, text, and sound data, data augmentation for numerical data in manufacturing has seen limited investigation. This paper empirically compares three data augmentation techniques—generative adversarial networks, variational auto-encoders mixed with long-short-term memory, and warping—on four manufacturing datasets. It also provides a literature review, highlighting that generative models are the most common technique for numerical manufacturing data. Preliminary findings suggest that generative adversarial networks are effective for non-time-series numerical data, especially with datasets featuring many correlated model features, multiple machines, and sufficient instances and labels. This research enhances the understanding of data augmentation in manufacturing ML applications, emphasizing the need for tailored strategies.

Abstract 3-Amino-1-(3,4-dimethoxyphenyl)-8-methoxy-1H-benzo[f]chromene-2-carbonitrile (3-ABC, 4) was prepared and affirmed through the spectral data and single crystal X-rays diffraction. The molecule spatial attributes were revealed by the three-dimensional Hirshfeld surface, which is validated by comprehensive statistical evaluations. The key interactions that contribute to the crystal's stability and properties, such as π–π stacking and H⋯X contacts, were highlighted. The dominant forces in the crystal were explained by energy framework calculations and density functional theory analyses, which also show the geometric optimization aspects and molecular reactivity indicators. The focus is on the investigation of frontier molecular orbitals, aromaticity, and π–π stacking abilities. The research concluded by identifying electron density distributions, aromatic features, and possible reactivity sites, offering a complete picture of the compound's structural and electronic landscape. Compound 4 was screened for its antimicrobial capability against three Gram-positive, three Gram-negative bacteria, and three fungi, utilizing the reference antibiotic drug Ampicillin, Gentamycin, and Ketoconazole. Compound 4 exhibited favorable antimicrobial activities that were lower/resembled the reference antimicrobial agents with an IZ range of 15–31 mm. In addition, MIC, MBC, and MFC were assessed and screened for the target molecule 4, unveiling its revealing antimicrobial activities. Lastly, the molecular docking evaluation was implemented for the molecules interaction with the DHFR protein. The compounds exhibit significant interactions with the EGFR protein's active site.

Abstract In the current landscape, there is a rapid increase in the creation of new algorithms designed for specialized problem scenarios. The performance of these algorithms in unfamiliar or practical settings often remains untested. This paper presents a new development, the multi-objective Runge–Kutta optimizer (MORKO), which is built upon the principles of elitist non-dominated sorting and crowding distance. The goal is to achieve superior efficiency, diversity, and robustness in solutions. MORKO effectiveness is further enhanced by incorporating various strategies that maintain a balance between diversity and execution efficiency. This approach not only directs the search toward optimal regions but also ensures that the process does not become stagnant. The efficiency of MORKO is compared against renowned algorithms like the multi-objective marine predicator algorithm (MOMPA), multi-objective gradient-based optimizer (MOGBO), multi-objective evolutionary algorithm based on decomposition (MOEA/D), and non-dominated sorting genetic algorithm (NSGA-II) on several test benchmarks such as ZDT, DTLZ, constraint (CONSTR, TNK, SRN, BNH, OSY and KITA) and real-world engineering design (brushless DC wheel motor, safety isolating transformer, helical spring, two-bar truss, welded beam, disk brake, tool spindle and cantilever beam) problems. We used unique, non-overlapping performance metrics for this comparison and suggested a fresh correlation analysis technique for exploration. The MORKO algorithm outcomes were rigorously tested and confirmed using the non-parametric statistical evaluations. The MORKO algorithm proves to excel in deriving comprehensive and varied solutions for many tests and practical challenges, owing to its multifaceted features. Looking ahead, MORKO has potential applications in complex engineering and management tasks.

Questioned documents, e.g. letters, contracts and insurance claims, are one of the most common types of evidences found in a variety of criminal investigations. Kinds of inks that can be [...], As a non-destructive analytical method, Raman spectroscopy often provides insufficient information to identify or differentiate the ink used for the preparation of a questioned document. In this study, blue and black ballpoint pen inks deposited on paper substrate were examined in situ by conventional Raman spectroscopy. Inks were successfully classified based on the total number of prominent bands in Raman spectra. It was found that more than 90% of the samples of the same type and color could be differentiated visually using only Raman spectra, i.e. 94 and 95% for blue and black inks, respectively. As a result of this study, a flow chart has been constructed for blue and black ballpoint pen inks allowing their systematic identification. Raman spectroscopy proved to be a fast and precise technique for forensic ink analysis. Keywords: questioned documents, Raman spectroscopy, ballpoint pen inks, forensic ink analysis

Abstract The appearance of COVID-19 in December, 2019 in China and its rapid spread all over the globe, forced the governments to severely curb the social and economic activities of their respective countries. Barring the essential services, most of the business activities and transport sectors have been suspended and an unprecedented lockdown imposed over major economies in the world. South-East Asian regions, such as India and China, were no different. As a result, the pollutant level has gone down over these regions, and the air quality improved somewhat better than it was before the lockdown. This study uses satellite retrievals and attempts to estimate the extent of the reduction of major pollutants, like carbon monoxide (CO), nitrogen dioxide (NO2) and sulfur dioxide (SO2) in India and China during January to April, 2020. We have calculated anomalies of pollutants during the lockdown period relative to their long-term records. NO2, which has significant emissions from the transport sector, is reduced on an average by 17% over India and 25% over China. SO2, which mainly emits from power plants, shows significant reductions (approx. 17%) especially over the Eastern sector of India. CO is found to be reduced by 6.5% over north-central China. The differential reduction was attributed to man made versus natural activities. This study is helpful to policy makers in mitigating the air-pollution on a long-term perspective.

Abstract Introduction Potentially Inappropriate Prescribing (PIP) poses a significant risk to patient safety and associated with poor healthcare outcomes in Gulf Cooperation Council (GCC) countries. This study aimed to assess PIP prevalence and patterns in older adults across all care settings in GCC. Methods A comprehensive search was conducted on six medical databases to identify studies assessing the PIP prevalence in older adults using validated criteria in GCC. Pooled prevalence estimates and odds ratios were calculated using STATA Software (version 16). Statistical heterogeneity was evaluated with the I² statistic, and publication bias was assessed using funnel plot symmetry and Egger’s regression test. The risk of bias was assessed using the JBI Prevalence Critical Appraisal Tool. Results Fourteen eligible studies conducted over ten years included 18,647 patients. The median prevalence of PIP was 54.4% (IQR: 37.6–62.1%), higher in hospital settings (59.5%; IQR: 53.7–65.3%) compared to primary care (44.2%; IQR: 18.5–54.4%). Cardiovascular medications were the most common PIP (15,353 occurrences). Polypharmacy was significantly associated with PIP exposure (OR: 5.26; 95% CI: 2.33–11.84). The odds of PIP exposure were significantly increased among older individuals with chronic kidney disease (OR: 1.87; 95% CI: 1.19–2.54) and diabetes (OR: 1.74; 95% CI: 1.18–2.30). Conclusion This study highlights high PIP prevalence among older adults in GCC countries, particularly in hospital settings. Polypharmacy and certain chronic conditions were significantly associated with PIP exposure. These findings emphasize the need for targeted interventions to improve prescribing practices and medication safety.

Abstract Purpose This research aims to explore the transmission of seismic surface waves through a two magneto-strictive materials i.e. cobalt ferrite and Terfenol-D when embedded in a plate-substrate configuration with non-ideal interface. The study focuses on understanding the impact of width of the plates, imperfect parameter, heterogeneity parameter on both the materials cobalt ferrite and Terfenol-D under magnetically open and short conditions. Methodology To achieve this, the study employs a variable-separable technique following Direct Sturm-Liouville method and appropriate boundary conditions to derive frequency relations for both magnetically open and short circuit scenarios. Numerical simulations are conducted to investigate the effects of width of the plates, imperfect parameter, heterogeneity parameter on both the materials cobalt ferrite and Terfenol-D under magnetically open and short conditions. Findings The research findings indicate that the phase velocity is increasing more in Terfenol-D as compared to Cobalt ferrite, either the case magnetically open or closed. Graphical comparisons highlight the impact of width plates, imperfect parameter, heterogeneity parameter on the characteristics on wave propagation clearly. Research limitations The study is confined to linear wave propagation and does not consider nonlinear effects. Additionally, the analysis is based on idealized material properties and interface conditions. Practical implications The results of this research can contribute to the design and optimization of sensors, energy harvesters, and wave manipulation devices utilizing piezomagnetic materials. Understanding the behaviour of surface waves in these structures is crucial for their effective application. Originality This study offers a comprehensive analysis of surface wave propagation in two different types of piezomagnetic composite structure by considering heterogeneity and interface conditions. The comparative study of different piezomagnetic models and the incorporation of heterogeneity and interface conditions contribute to the originality of the research.

Abstract Marine pollution from anthropogenic activities poses a severe threat to aquatic environments globally. Contaminants such as microplastics, hydrocarbons, heavy metals, and pesticides pervade coastal and ocean waters, causing significant harm to marine life and ecosystems. To address this, biological approaches present sustainable remediation alternatives. This review systematically evaluates recent advancements in bioaugmentation strategies for mitigating marine pollution. We begin by discussing key pollutant types, their sources, and their impacts. The review then explores various biological techniques, including microbial degradation, plant-assisted methods, and nano-enabled approaches. Significant advancements in predictive modeling, genetic engineering, and 'omics tools are also examined. Our comprehensive literature analysis (2010–2024) highlights progress in several areas: the optimization of tailored microbial consortia, development of pollution sensors, and integration of nanotechnologies. Notable achievements include the enhanced functional range and resilience of genetically engineered agents and the discovery of novel degraders through 'omics tools. Despite these advancements, challenges remain. Knowledge gaps exist regarding the interactions between diverse marine microbes, and scaling bioaugmentation to address complex pollutant mixtures poses ongoing difficulties. Addressing these challenges requires sustained efforts across scientific, policy, and social domains to fully realize the potential of bioaugmentation for ocean protection. Graphical Abstract