Search Results (268)

Background: Worldwide, the awareness about childhood obesity as a public health concern is increasing, particularly in developing countries like Pakistan. Obesity during early childhood may persist into later ages, increasing the risk of chronic illnesses such as diabetes and hypertension. Objective: The aim of this study was to examine the relationship of different types of food groups with obesity among children with normal and stunted growth trajectories in Pakistan. Methods: This cross-sectional study conducted a secondary analysis of Pakistan Demographic and Health Surveys (PDHSs) conducted in the years 2012–2013 and 2017–2018. Data of 1230 healthy and obese children with either normal or stunted growth were analysed after excluding those who were aged below six months, wasted, underweight, or had missing anthropometric or dietary data. The relationship of different food groups with obesity among the children with normal and stunted growth was analysed by bivariate logistic regression. Results: The prevalence of paediatric obesity dropped from 7.3% in 2012–2013 to 2.4% in 2017–2018. However, the coexistence of stunting with obesity—termed the nutritional paradox—slightly increased from 2.8% in 2012–2013 to 3% in 2017–2018. Among the different food groups, the continuation of breastmilk was associated with lowering the odds of obesity by 69% (25% to 88%) among children with normal growth. Conversely, among children with stunted growth, the continuation of breastmilk was associated with an increase in the odds of obesity by 3.71 (1.08 to 12.62) times. Conclusion: Despite the 4.9% reduction in paediatric obesity, cases of the nutritional paradox are still escalating in Pakistan. This reflects an urgent need for targeted nutritional interventions to mitigate the impact of obesogenic diets and reduce the prevalence of childhood obesity in Pakistan. Full article

The water regime in Pakistan’s northern region has experienced significant changes regarding hydrological extremes like floods because of climate change. Coupling hydrological models with remote sensing data can be valuable for flow simulation in data-scarce regions. This study focused on simulating the snow- and glacier-melt runoff using the snowmelt runoff model (SRM) in the Gilgit and Kachura River Basins of the upper Indus basin (UIB). The SRM was applied by coupling it with in situ and improved cloud-free MODIS snow and glacier composite satellite data (MOYDGL06) to simulate the flow under current and future climate scenarios. The SRM showed significant results: the Nash–Sutcliffe coefficient (NSE) for the calibration and validation period was between 0.93 and 0.97, and the difference in volume (between the simulated and observed flow) was in the range of −1.5 to 2.8% for both catchments. The flow tends to increase by 0.3–10.8% for both regions (with a higher increase in Gilgit) under mid- and late-21st-century climate scenarios. The Gilgit Basin’s higher hydrological sensitivity to climate change, compared to the Kachura Basin, stems from its lower mean elevation, seasonal snow dominance, and greater temperature-induced melt exposure. This study concludes that the simple temperature-based models, such as the SRM, coupled with improved satellite snow cover data, are reliable in simulating the current and future flows from the data-scarce mountainous catchments of Pakistan. The outcomes are valuable and can be used to anticipate and lessen any threat of flooding to the local community and the environment under the changing climate. This study may support flood assessment and mapping models in future flood risk reduction plans. Full article

As cities grow denser, the demand for efficient parking systems becomes more critical to reduce traffic congestion, fuel consumption, and environmental impact. This paper proposes a smart parking solution that combines deep learning and algorithmic sorting to identify the nearest available parking slot in real time. The system uses several pre-trained convolutional neural network (CNN) models—VGG16, ResNet50, Xception, LeNet, AlexNet, and MobileNet—along with a lightweight custom CNN architecture, all trained on a custom parking dataset. These models are integrated into a mobile application that allows users to view and request nearby parking spaces. A merge sort algorithm ranks available slots based on proximity to the user. The system is validated using benchmark datasets (CNR-EXT and PKLot), demonstrating high accuracy across diverse weather conditions. The proposed system shows how applied mathematical models and deep learning can improve urban mobility through intelligent infrastructure. Full article

Background: The World Health Organization (WHO) defines stillbirth as the loss of a fetus after 28 weeks of gestation. Annually, approximately 2 million stillbirths occur worldwide. Projections indicate that by 2030, this figure could rise to nearly 15.9 million, with half of these stillbirths expected to take place in Sub-Saharan Africa. In the global literature, causes include placental complications, birth defects, and maternal health issues, though often the cause is unknown. Stillbirths have significant emotional and financial impacts on families. Methods: The process involves using chi-square tests to identify candidate covariates for model building. The relative risk (RR) measures the association between variables using the sample data of 1435 mothers collected retrospectively. Since these tests are independent, covariates might be interrelated. The unadjusted RR from the bivariate analysis is then refined using stepwise logistic regression, guided by the Akaike Information Criterion (AIC), to select the best subset of covariates among the candidate variables. The logistic model’s regression coefficients provide the adjusted RR (aRR), indicating the strength of the association between a factor and stillbirth. Results: The model fit results reveal that heavy bleeding in the second or third trimester increases stillbirth risk by 4.69 times. Other factors, such as water breaking early in the third trimester (aRR = 3.22), severe back pain (aRR = 2.61), and conditions like anemia (aRR = 2.45) and malaria (aRR = 2.74), also heightened the risk. Further, mothers with a history of hypertension faced a 3.89-times-greater risk, while multifetal pregnancies increased risk by over 6 times. Conversely, proper mental and physical relaxation could reduce stillbirth risk by over 60%. Additionally, mothers aged 20 to 35 had a 40% lower risk than younger or older mothers. Conclusions: This research study identifies the significant predictors for forecasting stillbirth in pregnant women, and the results could help in the development of health monitoring strategies during pregnancy to reduce stillbirth risks. The research findings further support the importance of targeted interventions for high-risk groups. Full article

This study investigates the impact of perceived corporate social responsibility (CSR) on brand image within the automotive industry. It also examines how company reputation (CR) and product quality (PQ) mediate the relationship between CSR and brand image (BI). Utilizing a sample of 243 clients from the Pakistani automotive sector, data were collected through a survey and analyzed using structural equation modeling (SEM) with AMOS version 24.0. The results indicate that perceived CSR positively influences brand image, with both company reputation and product quality acting as significant mediators. This underscores the importance of CSR initiatives for enhancing brand image. The findings have significant implications for auto manufacturers, highlighting the need to integrate CSR into their strategic brand management to improve company reputation, product quality, and, ultimately, brand image. This study expands the conventional understanding of CSR’s impact on consumer perceptions and addresses a critical gap in the literature. Full article

Cloud gaming has rapidly transformed the gaming industry, allowing users to play games on demand from anywhere without the need for powerful hardware. Cloud service providers are striving to enhance user Quality of Experience (QoE) using traditional assessment methods. However, these traditional methods often fail to capture the actual user QoE because some users are not serious about providing feedback regarding cloud services. Additionally, some players, even after receiving services as per the Service Level Agreement (SLA), claim that they are not receiving services as promised. This poses a significant challenge for cloud service providers in accurately identifying QoE and improving actual services. In this paper, we have compared our previous proposed novel technique that utilizes a deep learning (DL) model to assess QoE through players’ facial expressions during cloud gaming sessions in a virtual reality (VR) environment. The EmotionNET model technique is based on a convolutional neural network (CNN) architecture. Later, we have compared the EmotionNET technique with three other DL techniques, namely ConvoNEXT, EfficientNET, and Vision Transformer (ViT). We trained the EmotionNET, ConvoNEXT, EfficientNET, and ViT model techniques on our custom-developed dataset, achieving 98.9% training accuracy and 87.8% validation accuracy with the EmotionNET model technique. Based on the training and comparison results, it is evident that the EmotionNET model technique predicts and performs better than the other model techniques. At the end, we have compared the EmotionNET results on two network (WiFi and mobile data) datasets. Our findings indicate that facial expressions are strongly correlated with QoE. Full article

Powering wearable and portable devices, triboelectric nanogenerators (TENGs) are a considerably promising technology. Low-cost production, ease of fabrication, optimal efficiency, and high output performance are always key concerns in developing energy harvesting technologies. Optimum efficiency and high output are always key concerns. This research addresses the ongoing challenge of raising efficient, flexible, and lightweight energy harvesting systems for recent wearable technologies. In this research, a triboelectric nanogenerator is proposed for harvesting the triboelectric effect. Using polyurethane (PU), a bendable TENG that is in the vertical contact separation mode was developed. UV-curable PU forms the basis of TENGs. A sponge, repurposed from landfill waste, acts by means of a spacer to maintain a consistent air gap between the tribo-layers for enhanced triboelectrification. The triboelectric nanogenerators formed a V_oc approaching 500 V and a current of ~2 µA and also showed high performance with a power density of 8.53 W/m². In addition, the triboelectric nanogenerator can light LEDs and charge capacitors, making it a self-powered energy source for portable devices, Wi-Fi, and monitoring systems. The proposed TENG provides a capable solution for sustainable, self-powered wearable electronics and has the potential for further development in energy-efficient and eco-friendly applications. Full article

Additive manufacturing (AM) techniques make fabricating complex designs, prototypes, and end-user products possible. Conductive polymer composites find applications in flexible electronics, sensor fabrication, and electrical circuits. In this study, thermoplastic polyurethane (TPU)-based conductive polymer composite samples were fabricated via fused filament fabrication (FFF). The effects of three important process parameters, including infill density (ID), layer thickness (LT), and fan speed (FS), on various mechanical properties (tensile and compressive properties) were investigated. It was observed that all the considered process parameters affect the mechanical properties, and they are significant parameters, as per the analysis of variance (ANOVA). From scanning electron microscopy (SEM) and optical microscopy, various combinations of parameters such as low ID, high LT, and high FS resulted in the formation of defects such as voids, cracks, and warping, which resulted in low mechanical properties. Finally, process parameter optimization was performed, resulting in a conductive polymer composite with the best possible combination of mechanical properties at high ID, low LT, and medium FS. Full article

The melon fruit fly, Bactrocera cucurbitae, is an important insect pest responsible for significant yield losses in vegetables. Conventional control methods, like pesticide applications, have certain limitations, including environmental contamination. This study evaluated the chemosterilant potential of five new insect growth regulators (IGRs)—Pyriproxyfen; Novaluron; Lufenuron; Buprofezin; and Flubendiamide—at concentrations ranging from 50 to 300 ppm in a 5 mL diet against B. cucurbitae. Laboratory trials identified Lufenuron as the most effective IGR, which reduced fecundity by 68.4% and adult emergence by 70.97% at a 300 ppm concentration. Other IGRs, Pyriproxyfen; Novaluron; Buprofezin; and Flubendiamide, also significantly reduced fecundity and adult emergence at higher concentrations. Based on laboratory performance, Lufenuron was selected for field trials using six bait traps per 0.4 hectares. The field trials demonstrated a higher number of B. cucurbitae adult captures in Lufenuron-based bait traps compared to the control and reductions in crop damage, with fruit fly damage decreasing by 7.01% in August and 4.25% in September. This study highlights the potential of chemosterilant baited traps as a promising approach for integrated fruit fly management programs in cucurbitaceous vegetables. Full article

The lesser grain borer, Rhyzopertha dominica (F.) (Coleoptera: Bostrichidae) and khapra beetle, Trogoderma granarium E. (Coleoptera: Dermestidae) are primary stored-grain insect pests. Differences in certain biological and physical parameters of both pest species and wheat genotypes were investigated under laboratory conditions. Zinc (Zn)-biofortified (Zincol-2016 and Akbar-2019) and conventional (Arooj-2022, Nawab-2021, Dilkash-2021, Bhakkar Star-2019) wheat genotypes were used in this study. Zn-biofortified genotypes outperformed the conventional ones, with significant differences observed in fecundity, percent adult emergence, total developmental duration, percent grain damage, and weight loss of both insect species. The results further revealed that the fecundity of R. dominica and T. granarium were lowest on Akbar-2019 in both the free-choice test (42.50 and 33.17) and no-choice test (35.50 and 32.50), respectively. Similarly, percent adult emergence of both insect species was also lowest on Akbar-2019 in both the free-choice test (69.78 and 70.28%) and no-choice test (67.38 and 70.71%). The total developmental period also showed significant variation among the tested genotypes. The longest developmental period was recorded in Akbar-2019, i.e., 44.33 and 58.83 days, for R. dominica and T. granarium, respectively. Similarly, percent grain damage (13.23 and 10.33%) and weight loss (3.62 and 2.12%) were found to be minimum in Akbar-2019 for both pest species, respectively. Additionally, a positive correlation was observed between grain moisture content and damage parameters, suggesting that the higher moisture content may aggravate the percent grain damage and weight loss. These findings indicate that the nutritional qualities of Zn-biofortified wheat genotypes negatively affected the development of both insect species; thus, it can be an efficacious approach not only for ensuring food security but also for protecting grains against storage pests. Full article

As the fashion industry faces increasing scrutiny over its environmental impact, collaborative consumption models such as online fashion renting offer potential solutions for fostering sustainability. This study examines the role of environmental, social, and governance (ESG) factors alongside behavioral drivers in shaping consumer intentions toward online fashion renting in China, a model of collaborative consumption that contributes to sustainability by reducing new product demand and promoting the reuse of fashion items. The data was gathered from 403 Chinese customers using a standardized questionnaire. Structural equation modeling (SEM) was used to examine the given study hypotheses. The current study empirically demonstrates that customers’ attitudes, past sustainable behavior, and subjective norms are significant indicators of consumers’ intentions toward online fashion renting. The results further indicate that relative advantage, compatibility, perceived ownership, psychological risk, green self-identity, and experience value are the key drivers of consumers’ attitudes toward online fashion renting. Additionally, the ESG factors were found to have a significant positive impact on consumer attitudes toward online fashion renting, underscoring their importance in driving sustainable consumption patterns. By integrating behavioral and ESG perspectives, the study contributes to the growing discourse on how sustainable consumption patterns can be encouraged within the fashion industry, offering theoretical and managerial implications for fostering sustainable behavior. Directions for future research are also suggested. Full article

Background/Objectives: The current research work aimed to evaluate the cryptic walnut genotypes of the Hazara region in Pakistan by using DNA barcoding and phylogenetic analysis. Methods: Based on morphological traits such as nut size, nut shape, and the number of leaflets, five genotypes were chosen and samples were collected for the current study. For molecular analysis, gDNA was isolated from the fresh leaves, and the five most effective angiosperm-specific markers, ITS2, rbcLa, rbcLc, rpoC1, and UBE3, were utilized. Based on amplification, sequencing, and identification success rates, ITS2 and UBE3 were recorded as the most efficient markers followed by rbcLa, rbcLc, and rpoC1. Results: During phylogenetic analysis, the query genotype-1 based on ITS2 and genotype-2 based on UBE3 clustered with (KF454101.1-Juglans regia) and (KC870919.1-J. regia) with bootstraps of 56 and 100, respectively. Genotype-3 based on rbcla clustered in a major clade with J. regia L., cultivars (MN397935.1 J. regia ‘Vina’) and (MN397934.1-J. regia ‘Serr’), (MN397933.1 J. regia ‘Pedro’), (MN397932.1 J. regia ‘Lara’), (MN397931.1 J. regia ‘Howard’), and (MN397930.1 J. regia ‘Hartley’) with bootstrap of 100. Meanwhile, genotype-4 and genotype-5 based on rbclc and rpoC1 clustered with (MN397935.1 J. regia ‘Vina’) and (MN397934.1 J. regia ‘Serr’), across the database sequences. To clarify the taxonomic status of cryptic walnut genotypes, it is necessary to combine diverse DNA barcodes. The results of ITS2 and UBE3, followed by rbcL barcoding markers, are promising taxonomic tools for cryptic walnut genotypes in Pakistan. Conclusions: It has been determined that the genotypes of walnuts in the study area are both J. regia L. and its cultivars and that the accuracy of discrimination regarding the genus Juglans L. is greater than 90%. The reported DNA barcodes are recommended for the correct identification and genetic evaluation of Juglans taxa and its population. Full article

This study investigates the impact of exogenous calcium and gamma-aminobutyric acid (GABA) supplementation on rice growth and stress tolerance under white-backed planthopper (WBPH) infestation. We evaluated several phenotypic traits, including shoot/root length, leaf width, tiller number, panicle length, and relative water content, alongside physiological markers such as oxidative stress indicators, antioxidant enzymes activities, hormonal levels, and amino acids biosynthesis. Our results indicate that WBPH stress significantly reduces growth parameters but calcium and GABA supplementation markedly enhance shoot length (by 26% and 36%) and root length (by 38% and 64%), respectively, compared to WBPH-infested plants. Both supplementations also reduced oxidative stress, as evidenced by decreased H₂O₂ and O₂^•− levels and a lower electrolyte leakage. Notably, calcium and GABA treatments increased antioxidant enzyme activities, with GABA boosting catalase (CAT) activity by 800%, peroxidase (POD) by 144%, and superoxide dismutase (SOD) by 62% under WBPH stress. Additionally, calcium and GABA enhanced the accumulation of stress hormones (abscisic acid ABA) and salicylic acid (SA) and promoted stomatal closure, contributing to improved water conservation. This study reveals that calcium regulates the GABA shunt pathway, significantly increasing GABA and succinate levels in both root and shoot. Furthermore, calcium and GABA supplementation enhance the biosynthesis of key amino acids and improve ion homeostasis, particularly elevating calcium (Ca), iron (Fe), and magnesium (Mg) levels under WBPH stress. Overall, this study highlights the potential of exogenous calcium and GABA as effective strategies for enhancing rice plant tolerance to WBPH infestation by modulating various physiological and biochemical mechanisms. Further research is warranted to fully elucidate the underlying mechanisms of action. Full article

The rapid global transition toward renewable energy necessitates innovative solar PV deployment strategies beyond conventional roof installations. In this context, commercial building facades represent an expansive yet underutilized resource for solar energy harvesting in urban areas. However, existing studies on commercial rooftop solar PV predominantly focus on European contexts, neglecting the unique design constraints and performance trade-offs present in regions such as the Middle East. This study addresses this gap by specifically investigating the impact of architectural and structural features on the utilizable facade area for PV deployment in commercial buildings within the hot desert climate of Saudi Arabia. Detailed case studies of twelve representative buildings are conducted, combining architectural drawing analysis, on-site measurements, and stakeholder surveys. The methodology identified sixteen parameters across three categories—facade functionality, orientation suitability, and surrounding obstructions—that impose technical and non-technical restrictions on photovoltaic integration 3D modeling, and irradiance simulations revealed that, on average, just 31% of the total vertical facade area remained suitable for PV systems after accounting for the diverse architectural and contextual limitations. The study considered 698 kWh/m² of solar irradiance as the minimum threshold for PV integration. Shopping malls displayed the lowest utilizability, with near-zero potential, as extensive opaque construction, brand signage, and shading diminish viability. Offices exhibited the highest utilizability of 36%, owing to glazed facades and unobstructed surroundings. Hotels and hospitals presented intermediate potential. Overall, the average facade utilizability factor across buildings was a mere 16%, highlighting the significant hurdles imposed by contemporary envelope configurations. Orientation unsuitability further eliminated 12% of the initially viable area. Surrounding shading contributed an additional 0.92% loss. The results quantify the sensitivity of facades to aspects such as material choices, geometric complexity, building form, and urban context. While posing challenges, the building facade resource holds immense untapped potential for solar-based urban renewal. The study highlights the need for early architectural integration, facade-specific PV product development, and urban planning interventions to maximize the renewable energy potential of commercial facades as our cities rapidly evolve into smart solar energy landscapes. Full article