Search Results (77)

The abundance of powered semiconductor devices has increased with the introduction of renewable energy sources into the grid, causing power quality disturbances (PQDs). This represents a huge challenge for grid reliability and smart city infrastructures. Accurate detection and classification are important for grid reliability and consumers’ appliances in a smart city environment. Conventionally, power quality monitoring relies on trivial machine learning classifiers or signal processing methods. However, recent advancements have introduced Deep Convolution Neural Networks (DCNNs) as promising methods for the detection and classification of PQDs. These techniques have the potential to demonstrate high classification accuracy, making them a more appropriate choice for real-time operations in a smart city framework. This paper presents a voting ensemble approach to classify sixteen PQDs, using the DCNN architecture through transfer learning. In this process, continuous wavelet transform (CWT) is employed to convert one-dimensional (1-D) PQD signals into time–frequency images. Four pre-trained DCNN architectures, i.e., Residual Network-50 (ResNet-50), Visual Geometry Group-16 (VGG-16), AlexNet and SqeezeNet are trained and implemented in MATLAB, using images of four datasets, i.e., without noise, 20 dB noise, 30 dB noise and random noise. Additionally, we also tested the performance of ResNet-50 with a squeeze-and-excitation (SE) mechanism. It was observed that ResNet-50 with the SE mechanism has a better classification accuracy; however, it causes computational overheads. The classification performance is enhanced by using the voting ensemble model. The results indicate that the proposed scheme improved the accuracy (99.98%), precision (99.97%), recall (99.80%) and F1-score (99.85%). As an outcome of this work, it is demonstrated that ResNet-50 with the SE mechanism is a viable choice as a single classification model, while an ensemble approach further increases the generalized performance for PQD classification. Full article

The aim of this paper is to obtain a fractal set of ℑ-iterated function systems comprising generalized ℑ-contractions. For a variety of Hutchinson–Wardowski contractive operators, we prove that this kind of system admits a unique common attractor. Consequently, diverse outcomes are obtained for generalized iterated function systems satisfying various generalized contractive conditions. An illustrative example is also provided. Finally, the existence results of common solutions to fractional boundary value problems are obtained. Full article

Automated Essay Scoring (AES) systems face persistent challenges in delivering accuracy and efficiency in evaluations. This study introduces an approach that combines embeddings generated using RoBERTa with handcrafted linguistic features, leveraging Lightweight XGBoost (LwXGBoost) for enhanced scoring precision. The embeddings capture the contextual and semantic aspects of essay content, while handcrafted features incorporate domain-specific attributes such as grammar errors, readability, and sentence length. This hybrid feature set allows LwXGBoost to handle high-dimensional data and model intricate feature interactions effectively. Our experiments on a diverse AES dataset, consisting of essays from students across various educational levels, yielded a QWK score of 0.941. This result demonstrates the superior scoring accuracy and the model’s robustness against noisy and sparse data. The research underscores the potential for integrating embeddings with traditional handcrafted features to improve automated assessment systems. Full article

In recent decades, the use of pesticides has become fundamental to agricultural growth. However, the persistent and toxic nature of pesticides has led to significant concerns regarding their ecological and human health consequences. Therefore, for a better understanding of pesticide contamination and its potential risks, here we assessed the levels of five emerging pesticides—acetochlor, imidacloprid, MCPA, atrazine, and allethrin—in soil samples from ponds used for irrigation and in drinking water samples from nearby areas in Lahore, Pakistan. Our findings revealed that 100% of the samples were contaminated, posing substantial ecological and human health risks. Based on the toxic units (TU_sum), all the soil samples showed higher toxic pressure, exceeding acute and chronic toxicity thresholds for earthworms, while 100% of water samples posed chronic toxicity risks to crustaceans and 10% to algae. Pollution index (PI) analysis further classified 100% of the soil samples and 10% of the water samples as highly polluted. These findings show high-pesticide residues in both soil and water and highlight immediate risk assessment and mitigation measures to protect non-target organisms. This preliminary information can be used to adopt risk assessment monitoring programmes and help higher authorities in making policies and guidelines to mitigate the escalating risk for ecology and humans. Full article

Groundwater Arsenic (As) data are often sparse and location-specific, making them insufficient to represent the heterogeneity in groundwater quality status at unsampled locations. Interpolation techniques have been used to map groundwater As data at unsampled locations. However, the results obtained from these techniques are affected by various inherent and external factors, which lead to uncertainties in the interpolated data. This study was designed to determine the best technique to interpolate groundwater As data. We selected ten interpolation techniques to predict the As concentration in the groundwater resources of Punjab, Pakistan. Two external factors, the spatial extent of the study area and data density, were considered to assess their impact on the performance of interpolation techniques. Our results show that the Inverse Distance Weighting (IDW) and Spline interpolation techniques demonstrate the highest accuracy with the lowest RMSE (13.5 ppb and 16.7 ppb) and MAE (87.8 ppb and 89.5 ppb), respectively, while the Natural Neighbor technique shows the lowest accuracy with the highest RMSE (2508.7 ppb) and MAE (712.1 ppb) to interpolate groundwater As data. When the study area’s extent was modified, IDW showed the best performance, with errors within ±1.5 ppb for 95% of the wells across the study area. While data density has a positive correlation with interpolation accuracy among all techniques, the IDW remained the best method for interpolation. It is therefore concluded that IDW should be used to interpolate groundwater quality data when observed data are sparse and randomly distributed. The utilization of IDW can be useful for As monitoring and management in groundwater resources. Full article

This review explores the challenges brought about by emerging foodborne pathogens and the strategies employed to ensure food safety. This study conducted a comprehensive literature review to gather information on the latest trends in foodborne pathogens, their impact on public health, and the measures taken to mitigate their risks. Various scientific databases were utilized to identify relevant articles, research papers, and reports. The research findings highlight the emergence of new and re-emerging foodborne pathogens such as Salmonella, Campylobacter, Escherichia coli, Listeria monocytogenes, and norovirus. These pathogens pose significant health risks and can lead to outbreaks and foodborne illnesses. This study examines the factors contributing to the emergence of these pathogens, including changes in food production, globalization, climate change, and antimicrobial resistance. Furthermore, this study explores the challenges faced in controlling and preventing the spread of these pathogens throughout the food supply chain. It examines issues related to contamination during production, processing, transportation, and consumption. The study also investigates the limitations of current detection methods and the need for improved surveillance systems to identify and respond to emerging pathogens effectively. In terms of strategies for ensuring food safety, this study highlights the importance of implementing preventive measures such as good agricultural practices, proper sanitation, and hygiene protocols. It emphasizes the significance of robust food safety regulations and policies to enforce compliance across the industry. Additionally, this study explores the role of education and awareness campaigns in promoting safe food handling practices among consumers. Full article

Pedilanthus leaf curl virus (PeLCV) is a monopartite begomovirus (family Geminiviridae) discovered just a few decades ago. Since then, it has become a widely encountered virus, with reports from ca. 25 plant species across Pakistan and India, indicative of its notable evolutionary success. Viruses mutate at such a swift rate that their ecological and evolutionary behaviors are inextricably linked, and all of these behaviors are imprinted on their genomes as genetic diversity. So, all these imprints can be mapped by computational methods. This study was designed to map the sequence variation dynamics, genetic heterogeneity, regional diversity, phylogeny, and recombination events imprinted on the PeLCV genome. Phylogenetic and network analysis grouped the full-length genome sequences of 52 PeLCV isolates into 7 major clades, displaying some regional delineation but lacking host-specific demarcation. The progenitor of PeLCV was found to have originated in Multan, Pakistan, in 1977, from where it spread concurrently to India and various regions of Pakistan. A high proportion of recombination events, distributed unevenly throughout the genome and involving both inter- and intraspecies recombinants, were inferred. The findings of this study highlight that the PeLCV population is expanding under a high degree of genetic diversity (π = 0.073%), a high rate of mean nucleotide substitution (1.54 × 10⁻³), demographic selection, and a high rate of recombination. This sets PeLCV apart as a distinctive begomovirus among other begomoviruses. These factors could further exacerbate the PeLCV divergence and adaptation to new hosts. The insights of this study that pinpoint the emergence of PeLCV are outlined. Full article

The rapid adoption of hydrogen as an eco-friendly energy source has necessitated the development of intelligent power management systems capable of efficiently utilizing hydrogen resources. However, guaranteeing the security and integrity of hydrogen-related data has become a significant challenge. This paper proposes a pioneering approach to ensure secure hydrogen data analysis by integrating blockchain technology, enhancing trust, transparency, and privacy in handling hydrogen-related information. Combining blockchain with intelligent power management systems makes the efficient utilization of hydrogen resources feasible. Using smart contracts and distributed ledger technology facilitates secure data analysis (SDA), real-time monitoring, prediction, and optimization of hydrogen-based power systems. The effectiveness and performance of the proposed approach are demonstrated through comprehensive case studies and simulations. Notably, our prediction models, including ABiLSTM, ALSTM, and ARNN, consistently delivered high accuracy with MAE values of approximately 0.154, 0.151, and 0.151, respectively, enhancing the security and efficiency of hydrogen consumption forecasts. The blockchain-based solution offers enhanced security, integrity, and privacy for hydrogen data analysis, thus advancing clean and sustainable energy systems. Additionally, the research identifies existing challenges and outlines future directions for further enhancing the proposed system. This study adds to the growing body of research on blockchain applications in the energy sector, specifically on secure hydrogen data analysis and intelligent power management systems. Full article

A biologically effective study regarding the synthesis of a library of hybrids based on a triazole ring, propanamide and azinane was performed in this study. The targeted hybrids, 9a–9l, were synthesized through a multistep protocol followed by two methodologies, that is, conventional and microwave-assisted ones. Initially, compound 3 was synthesized via the room-temperature stirring of 4-methoxybenzenesulfonyl chloride (1) and ethyl ester (2). Resulting carboxylate was converted into carbohydrazide 4, which was refluxed with phenyl isothiocyanate and KOH to synthesize product 5. A library of amides, 8a–8l, was stirred at room temperature with compound 5 to avail the targeted library of hybrids 9a–9l. The designed hybrids were screened for their antioxidant, urease, AChE and BChE inhibition potential. All the compounds were found to be active with variable potential. The best antioxidant agent was compound 9c with an IC₅₀ value of 45.2 ± 0.15. The compound 9e (63.27 ± 1.21) was the best AChE inhibitor; 9g (20.2 ± 0.21) and 9k (19.2 ± 0.09) were the best anti-urease agents; and 9d (15.5 ± 0.39) and 9e (15.9 ± 0.67) were the best BChE inhibitors. The computational and BSA binding studies of the selected synthesized compounds against urease, BChE and AChE enzymes were carried out to elaborate the strong and weak enzyme-inhibition potential through the binding forces of the synthesized compounds with the different enzymatic sites that are responsible for their activity. Full article

Lumpy skin disease (LSD) is a contagious infection of cattle caused by a virus of the Poxviridae family, genus Capripoxvirus. In Pakistan, recent outbreaks have resulted in significant nationwide mortality and economic losses. A 20-day prospective cohort study was performed on sixty infected cattle with the aim to evaluate LSD-induced oxidative stress’s genotoxic role and to determine the ameliorative effect of antioxidant therapy using principal component analysis (PCA) and a multivariable ordinal logistic regression model. LSDV was identified from scab samples and nodular lesions using RPO30-specific gene primers. The infected cattle were divided into control and treated groups. The animals were observed initially and finally on day 20 to evaluate the homeostatic, oxidative, and genotoxic changes. The animals in the treated group were administered a combination of selenium (Se) and vitamin E at the standard dose rate for five consecutive days. A substantial (p < 0.05) improvement in the hematological indices was observed in the treated group. The treated group also showed a significant (p < 0.05) reduction in levels of serum nitric oxide (NO) and malondialdehyde (MDA) post-therapy. The PCA at the final sampling data of the treated group showed that Principal Component (PC1 eigenvalue 1.429) was influenced by superoxide dismutase (SOD; 0.3632), catalase (CAT; 0.2906), and glutathione (GSH; 0.0816) and PC2 (eigenvalue 1.200) was influenced by CAT (0.4362), MDA (0.2056), and NO (0.0693). A significant correlation between serum NO (76%) and MDA levels (80%) was observed with genetic damage index (GDI) scores. The ordinal logistic regression model regarding the use of antioxidant therapy revealed 73.95-times (95%CI; 17.36–314.96) improvement in the GDI in treated animals. The multivariable ordinal logistic regression showed that each unit increase in NO and MDA resulted in a 13% increase in genotoxicity in infected individuals. In conclusion, our study revealed that LSD-induced oxidative stress and lipid peroxidation product causes genotoxicity in affected animals. Furthermore, the combined Se and vitamin E therapy significantly alleviated oxidative stress and genotoxicity in LSD-affected cattle. Full article

Promotion of durable materials and products is a common approach to enhance sustainability. However, the effectiveness of such efforts lies on shifts in user behavior and consumption patterns, and these patterns are influenced not only by material aspects but also by social and experiential dimensions. It has been observed that the consumers’ consumption pattern, i.e., post-consumption behavior, is as harmful as production. However, this area remains largely unexplored. The primary purpose of this study is to explore sustainable garment design strategies to enhance emotional durability of garments and reduce pre-consumer and most importantly, the post-consumer waste. For this purpose, 18 garments were produced using ZWPC for pre-consumption waste reduction and DFD for post-consumption waste minimization. Three hypotheses were developed. Quantitative and qualitative data were collected through questionnaires and wear trials on the practicality of DFD implementation in garments. The results demonstrated that the combination of these strategies has the potential to curb both pre-consumer and post-consumer waste by designing garments that can enter the biological as well as technical cycle of circular fashion (CF). Furthermore, DFD is a success in increasing the use-life of a garment. Full article

Background and Objectives: Dermatological disorders are highly prevalent among children in Pakistan. The present cross-sectional study aims to identify the spectrum of dermatological conditions among children and adolescents in Pakistan. Materials and Methods: A total of 582 patients (50.9% males; 49.1% females) were included in the study based on their age (5.7 ± 4.1 years), dermatological condition, and epidemiology. The youngest patient was aged ten days, whereas the eldest was seventeen. Age criteria were further stratified into three categories: infants and toddlers (≤5 years), children (≥5 to <12 years), and adolescents (≥12 to <18 years). Amongst them, the majority was from Punjab (81.6%), while the other regions included were Azad Jammu and Kashmir (14.4%), Islamabad (3.3%), and Khyber Pakhtunkhwa (0.7%). Results: Scabies was the highest reported skin condition with 281 (45.55%) patients, followed by 114 (19.6%) with eczema, 60 (10.3%) with dermatitis, 33 (5.7%) with tinea capitis, 17 (2.9%) with tinea corporis, 16 (2.7%) with impetigo, and 15 (2.6%) with folliculitis. Other conditions include urticaria, burns, infections, pediculosis, tinea inguinalis, tinea faciei, nappy rashes, alopecia, warts, tinea incognito, tinea cruris, and acne vulgaris. The chi-squared test showed a high prevalence of tinea corporis and acne among adolescents (12–17 years), whereas eczema, dermatitis, and impetigo were more prevalent among infants and toddlers. Conclusions: Pets or livestock and poor hygiene were found to be highly reported risk factors for many dermatological conditions like scabies and fungal infections. Dermatological conditions are common in younger individuals, but unfortunately, many children do not receive the desired medical assistance. Full article

This study aims to explore the relationship between food quality and mental health by comprehensively analyzing existing research. A systematic review was conducted to identify relevant studies published between 2010 and 2022. The selected studies encompassed various populations, including adults, adolescents, and elderly individuals, and examined the impact of food quality on mental health outcomes such as depression, anxiety, and cognitive function. The findings of the analysis revealed a significant association between food quality and mental health. Several studies indicated that a diet rich in fruits, vegetables, whole grains, and lean proteins was positively correlated with better mental health outcomes. Conversely, a diet high in processed foods, sugar, and saturated fats was associated with an increased risk of mental health disorders. Furthermore, the analysis highlighted the role of specific nutrients in mental health. Omega-3 fatty acids, found in fatty fish and nuts, were consistently linked to improved mood and cognitive function. Additionally, the consumption of antioxidants, vitamins, and minerals from fruits and vegetables showed positive effects on mental well-being. However, it is important to note that the relationship between food quality and mental health is complex and influenced by various factors such as socioeconomic status, cultural background, and individual differences. Future research should consider these factors to obtain a more comprehensive understanding of the topic. In conclusion, this study provides evidence supporting the relationship between food quality and mental health. Adopting a healthy diet rich in nutrient-dense foods may have a positive impact on mental well-being. Further research is needed to explore the underlying mechanisms and develop targeted interventions to improve mental health outcomes through dietary interventions. Full article

In this paper, we derive the coincidence fixed-point and common fixed-point results for ℑ-type mappings satisfying certain contractive conditions and containing fewer conditions imposed on function ℑ with regard to generalized metric spaces (in terms of Jleli Samet). Finally, a fractional boundary value problem is reduced to an equivalent Volterra integral equation, and the existence results of common solutions are obtained with the use of proved fixed-point results. Full article

The generalized Petersen graphs are a type of cubic graph formed by connecting the vertices of a regular polygon to the corresponding vertices of a star polygon. This graph has many interesting graph properties. As a result, it has been widely researched. In this work, the edge metric dimensions of the generalized Petersen graphs GP(2l + 1, l) and GP(2l, l) are explored, and it is shown that the edge metric dimension of GP(2l + 1, l) is equal to its metric dimension. Furthermore, it is proved that the upper bound of the edge metric dimension is the same as the value of the metric dimension for the graph GP(2l, l). Full article