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Meeting the growing global electricity demand in remote and off-grid regions requires cost-effective and reliable power solutions that overcome the intermittency of renewable energy sources. This paper presents a comprehensive techno-economic optimization framework for the design and operation of off-grid hybrid renewable energy systems (HRES) integrating photovoltaic (PV), wind turbine, biomass generator, diesel backup, and a dual-chemistry hybrid battery energy storage system (HBESS) combining lithium-ion and nickel-iron batteries. A detailed mathematical modeling approach is employed to capture the nonlinear dynamics, stochastic renewable behavior, battery degradation, and temperature-adjusted component efficiencies. The system is formulated as a multi-objective mixed-integer nonlinear programming problem targeting the minimization of life cycle cost (LCC), levelized cost of energy (LCOE), and CO2 emissions while satisfying reliability constraints such as loss of power supply probability (LPSP < 0.01). To solve the optimization problem, advanced metaheuristic algorithms—Particle Swarm Optimization (PSO), Genetic Algorithms (GA), Grey Wolf Optimizer (GWO), and Differential Evolution (DE), and Salp Swarm Algorithm (SSA)—and a Deep Q-Network (DQN)-based reinforcement learning energy management strategy are implemented and benchmarked. The proposed DQN-based controller demonstrates superior performance over conventional rule-based and static dispatch methods by maintaining more stable battery state-of-charge (SOC) profiles, reducing degradation, and enabling intelligent real-time decision-making. Simulation results based on realistic meteorological and demand profiles reveal that the integrated DQN and HBESS strategy reduces total LCC by over 20%, CO2 emissions by up to 30%, and battery degradation costs by over 10% compared to baseline systems. The Salp Swarm Algorithm (SSA) achieves the fastest convergence and the highest-quality Pareto-optimal solutions among all metaheuristics evaluated. Sensitivity analysis identifies diesel price and interest rate as the most influential parameters on LCOE, while load shifting through aggressive demand-side management further minimizes battery usage, operating costs, and emissions. The proposed framework not only addresses key challenges in off-grid microgrid design but also provides a scalable and robust pathway for sustainable rural electrification using hybrid storage and intelligent control.

The ongoing COVID-19 pandemic is caused by SARs-CoV-2. The virus is transmitted from person to person through droplet infections i.e. when infected person is in close contact with another person. In January 2020, first report of detection of SARS-CoV-2 in faeces, has made it clear that human wastewater might contain this virus. This may illustrate the probability of environmentally facilitated transmission, mainly the sewage, however, environmental conditions that could facilitate faecal oral transmission is not yet clear. We used existing Pakistan polio environment surveillance network to investigate presence of SARs-CoV-2 using three commercially available kits and E-Gene detection published assay for surety and confirmatory of positivity. A Two-phase separation method is used for sample clarification and concentration. An additional high-speed centrifugation (14000Xg for 30 min) step was introduced, prior RNA extraction, to increase viral RNA yield resulting a decrease in Cq value. A total of 78 wastewater samples collected from 38 districts across Pakistan, 74 wastewater samples from existing polio environment surveillance sites, 3 from drains of COVID-19 infected areas and 1 from COVID 19 quarantine center drainage, were tested for presence of SARs-CoV-2. 21 wastewater samples (27%) from 13 districts turned to be positive on RT-qPCR. SARs-COV-2 RNA positive samples from areas with COVID 19 patients and quarantine center strengthen the findings and use of wastewater surveillance in future. Furthermore, sequence data of partial ORF 1a generated from COVID 19 patient quarantine center drainage sample also reinforce our findings that SARs-CoV-2 can be detected in wastewater. This study finding indicates that SARs-CoV-2 detection through wastewater surveillance has an epidemiologic potential that can be used as supplementary system to monitor viral tracking and circulation in cities with lower COVID-19 testing capacity or heavily populated areas where door-to-door tracing may not be possible. However, attention is needed on virus concentration and detection assay to increase the sensitivity. Development of highly sensitive assay will be an indicator for virus monitoring and to provide early warning signs.

Purpose This paper aims to address the need for a more in-depth empirical investigation of exploring the link between the adoption of corporate social responsibility (CSR) practices and different aspects of customer behavior in a developing country. This paper develops a research framework and assesses the mediating role of trust, customer-company identification (CCI) and electronic-service quality (E-SQ) between customer perceptions of CSR and customer loyalty. Design/methodology/approach Working with a sample of 280 banking customers in Pakistan, partial least square based structural equation modeling is used to test the conceptual model. Findings Surprisingly, results suggest that CSR is not directly related to customer loyalty, which is contradictory to previously established findings conducted in developed countries. Thus, confirming a full mediation of CCI, E-SQ and trust in enhancing the effect of CSR on customer loyalty. The study also confirms that CSR is positively related to E-SQ, and E-SQ also directly affects CCI. Practical implications Banks should adhere to honest CSR practices and effectively communicate and advertise these practices to increase awareness and knowledge among the customers. Similarly, banks should advance in technological expertise to generate customer identification, which then leads to their loyalty. Originality/value Previous studies conferred short-term customer’s reactions, such as purchase intention and brand image. Still, this research discusses the long-term effect of CSR on customer behavior, such as the loyalty of the customers. Moreover, this is the pioneer study that investigates how CSR actions influence customer perceptions about E-SQ and how electronic services affect customer identification with a bank.

Citations in scientific literature act as channels for the sharing, transfer, and development of scientific knowledge. However, not all citations hold the same significance. Numerous taxonomies and machine learning models have been developed to analyze citations, but they often overlook the internal context of these citations. Moreover, it is worth noting that selecting the appropriate word embedding and classification models is crucial for achieving superior results. Word embeddings offer n-dimensional distributed representations of text, striving to capture the nuanced meanings of words. Deep learning-based word embedding techniques have garnered significant attention and found application in various Natural Language Processing (NLP) tasks, including text classification, sentiment analysis, and citation analysis. Current state-of-the-art techniques often use small datasets with fixed window sizes, resulting in the loss of contextual meaning. This study leverages two benchmark datasets encompassing a substantial volume of in-text citations to guide the selection of an optimal word embedding window size and classification approaches. A comparative analysis of various window sizes for in-text citations is conducted to identify crucial citations effectively. Additionally, Word2Vec embedding is employed in conjunction with deep learning models and machine learning models such as Convolutional Neural Networks (CNNs), Gated Recurrent Units (GRUs), Long Short-Term Memory (LSTM) networks, Support Vector Machines (SVM), Decision Trees, and Naive Bayes.The evaluation employs precision, recall, F1-score, and accuracy metrics for each combination of window sizes. The findings reveal that, particularly for lengthy in-text citations, larger citation windows are more adept at capturing the semantic essence of the references. Within the scope of this study, window sizes of 10 achieve superior accuracy and precision with both machine and deep learning models.

Exopolysaccharide (EPS) show remarkable properties in various food applications. In this review paper, EPS composition, structural characterization, biosynthesis pathways, and recent advancements in the context of application of EPS-producing Lactobacillus spp. in different food industries are discussed. Various chemical and physical properties of Lactobacillus EPS, such as the structural, rheological, and shelf-life enhancement of different food products, are mentioned. Moreover, EPSs play a characteristic role in starter culture techniques, yogurt production, immunomodulation, and potential prebiotics. It has been seen that the wastes of fermented and non-fermented products are used as biological food for EPS extraction. The main capabilities of probiotics are the use of EPS for technological properties such as texture and flavor enhancement, juiciness, and water holding capacities of specific food products. For these reasons, EPSs are used in functional and fermented food products to enhance the healthy activity of the human digestive system as well as for the benefit of the food industry to lower product damage and increase consumer demand. Additionally, some pseudocereals such as amaranth and quinoa that produce EPS also play an important role in improving the organoleptic properties of food-grade products. In conclusion, more attention should be given to sustainable extraction techniques of LAB EPS to enhance structural and functional use in the developmental process of food products to meet consumer preferences.

The concentration of greenhouse gases (GHGs) in the atmosphere has been increasing since the beginning of the industrial revolution. Nitrous oxide (N2O) is one of the mightiest GHGs, and agriculture is one of the main sources of N2O emissions. In this paper, we reviewed the mechanisms triggering N2O emissions and the role of agricultural practices in their mitigation. The amount of N2O produced from the soil through the combined processes of nitrification and denitrification is profoundly influenced by temperature, moisture, carbon, nitrogen and oxygen contents. These factors can be manipulated to a significant extent through field management practices, influencing N2O emission. The relationships between N2O occurrence and factors regulating it are an important premise for devising mitigation strategies. Here, we evaluated various options in the literature and found that N2O emissions can be effectively reduced by intervening on time and through the method of N supply (30–40%, with peaks up to 80%), tillage and irrigation practices (both in non-univocal way), use of amendments, such as biochar and lime (up to 80%), use of slow-release fertilizers and/or nitrification inhibitors (up to 50%), plant treatment with arbuscular mycorrhizal fungi (up to 75%), appropriate crop rotations and schemes (up to 50%), and integrated nutrient management (in a non-univocal way). In conclusion, acting on N supply (fertilizer type, dose, time, method, etc.) is the most straightforward way to achieve significant N2O reductions without compromising crop yields. However, tuning the rest of crop management (tillage, irrigation, rotation, etc.) to principles of good agricultural practices is also advisable, as it can fetch significant N2O abatement vs. the risk of unexpected rise, which can be incurred by unwary management.

Rapid industrialization is consuming too much energy, and non-renewable energy resources are currently supplying the world’s majority of energy requirements. As a result, the global energy mix is being pushed towards renewable and sustainable energy sources by the world’s future energy plan and climate change. Thus, hydrogen has been suggested as a potential energy source for sustainable development. Currently, the production of hydrogen from fossil fuels is dominant in the world and its utilization is increasing daily. As discussed in the paper, a large amount of hydrogen is used in rocket engines, oil refining, ammonia production, and many other processes. This paper also analyzes the environmental impacts of hydrogen utilization in various applications such as iron and steel production, rocket engines, ammonia production, and hydrogenation. It is predicted that all of our fossil fuels will run out soon if we continue to consume them at our current pace of consumption. Hydrogen is only ecologically friendly when it is produced from renewable energy. Therefore, a transition towards hydrogen production from renewable energy resources such as solar, geothermal, and wind is necessary. However, many things need to be achieved before we can transition from a fossil-fuel-driven economy to one based on renewable energy.

Global warming in this century increases incidences of various abiotic stresses restricting plant growth and productivity and posing a severe threat to global food production and security. The plant produces different osmolytes and hormones to combat the harmful effects of these abiotic stresses. Melatonin (MT) is a plant hormone that possesses excellent properties to improve plant performance under different abiotic stresses. It is associated with improved physiological and molecular processes linked with seed germination, growth and development, photosynthesis, carbon fixation, and plant defence against other abiotic stresses. In parallel, MT also increased the accumulation of multiple osmolytes, sugars and endogenous hormones (auxin, gibberellic acid, and cytokinins) to mediate resistance to stress. Stress condition in plants often produces reactive oxygen species. MT has excellent antioxidant properties and substantially scavenges reactive oxygen species by increasing the activity of enzymatic and non-enzymatic antioxidants under stress conditions. Moreover, the upregulation of stress-responsive and antioxidant enzyme genes makes it an excellent stress-inducing molecule. However, MT produced in plants is not sufficient to induce stress tolerance. Therefore, the development of transgenic plants with improved MT biosynthesis could be a promising approach to enhancing stress tolerance. This review, therefore, focuses on the possible role of MT in the induction of various abiotic stresses in plants. We further discussed MT biosynthesis and the critical role of MT as a potential antioxidant for improving abiotic stress tolerance. In addition, we also addressed MT biosynthesis and shed light on future research directions. Therefore, this review would help readers learn more about MT in a changing environment and provide new suggestions on how this knowledge could be used to develop stress tolerance.

Citrus production is harmed worldwide by yellow dragon disease, also known as Huanglongbing (HLB), or citrus greening. As a result, it has negative effects and a significant impact on the agro-industrial sector. There is still no viable biocompatible treatment for Huanglongbing, despite enormous efforts to combat this disease and decrease its detrimental effects on citrus production. Nowadays, green-synthesized nanoparticles are gaining attention for their use in controlling various crop diseases. This research is the first scientific approach to examine the potential of phylogenic silver nanoparticles (AgNPs) to restore the health of Huanglongbing-diseased ‘Kinnow’ mandarin plants in a biocompatible manner. AgNPs were synthesized using Moringa oleifera as a reducing, capping, and stabilizing agent and characterized using different characterization techniques, i.e., UV–visible spectroscopy with a maximum average peak at 418 nm, scanning electron microscopy (SEM) with a size of 74 nm, and energy-dispersive spectroscopy (EDX), which confirmed the presence of silver ions along with different elements, and Fourier transform infrared spectroscopy served to confirm different functional groups of elements. Exogenously, AgNPs at various concentrations, i.e., 25, 50, 75, and 100 mgL−1, were applied against Huanglongbing-diseased plants to evaluate the physiological, biochemical, and fruit parameters. The findings of the current study revealed that 75 mgL−1 AgNPs were most effective in boosting the plants’ physiological profiles, i.e., chl a, chl b, total chl, carotenoid content, MSI, and RWC up to 92.87%, 93.36%, 66.72%, 80.95%, 59.61%, and 79.55%, respectively; biochemical parameters, i.e., 75 mgL−1 concentration decreased the proline content by up to 40.98%, and increased the SSC, SOD, POD, CAT, TPC, and TFC content by 74.75%, 72.86%, 93.76%, 76.41%, 73.98%, and 92.85%, respectively; and fruit parameters, i.e., 75 mgL−1 concentration increased the average fruit weight, peel diameter, peel weight, juice weight, rag weight, juice pH, total soluble solids, and total sugarby up to 90.78%, 8.65%, 68.06%, 84.74%, 74.66%, 52.58%, 72.94%, and 69.69%, respectively. These findings enable us to develop the AgNP formulation as a potential citrus Huanglongbing disease management method.