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The escalating global demand for clean and sustainable energy sources has trusted solar energy into the forefront of renewable energy (RE) solutions. Solar power generation, however, is profoundly influenced by ever-changing meteorological conditions, notably solar irradiation and temperature. These fluctuations have a direct impact on the voltage and current characteristics of photovoltaic arrays. To achieve optimal power transfer, a harmonious interface between the utility grid or load and solar panels is essential. In this research, the authors propose the integration of LCL filter to ameliorate harmonics emanating from inverter outputs. Additionally, a nonlinear control methodology is employed to maximize power extraction from Photovoltaic (PV) arrays at the Maximum Power Point (MPP) and to ensure a stable and less fluctuating injection of power into the grid. The primary goal of this work is to examine the effectiveness of nonlinear control techniques that assist in reducing harmonics and smoothing the output of solar power systems utilizing LCL filter. The controllers used here are nonlinear Super Twisting Reachability law-based Finite Time Sliding Mode Control (STR-FTSMC) and Arbitrary Order Finite Time Sliding Mode Control (AO-FTSMC) for the three-phase single-stage on-grid PV system in addition to sliding mode observer. The efficacy of the employed control techniques is highlighted via a comparative study in a MATLAB/Simulink environment.

Smart grids (SG) constitute a revolutionary concept within the energy sector, enabling the establishment of a bidirectional communication infrastructure. This infrastructure significantly improves control, efficiency, and overall service quality in power systems. The study provides an in-depth survey on the classification of EVs, including both plug-in and non-plug-in EVs, and the integration process of V2G, including bidirectional power flow analysis. Moreover, various control strategies for EV integration are explored, ranging from centralized and decentralized to hierarchical control structures. Further, the research thoroughly examines the potential benefits of EV integration and addresses associated challenges, such as battery degradation, infrastructure requirements, cybersecurity and communication issues, grid congestion, and consumer behavior. The study goes beyond theoretical exploration and offers a comprehensive simulation analysis. This analysis leverages the storage capabilities of EVs to provide grid support services. A real-time dynamic dispatch strategy is formulated to integrate EVs into the automatic generation control of multi-energy systems. The findings demonstrate that EVs can effectively mitigate forecasting errors in a power network heavily reliant on wind energy sources. Consequently, the storage capabilities of EVs contribute to enhancing grid flexibility in managing the intermittency of renewable energy resources.

Organochlorine pesticides (OCPs) in surface and groundwater are an environmental problem with substantial human health risk reports in many developing countries, including Pakistan. OCPs are known for their long life, harmful effects, and slow decomposition. Therefore, this study aimed to investigate the water quality of River-Ravi and Sutlej concerning (OCPs) along with main drains and groundwater sources. The total OCPs ranged from 2.1 to 3120.4 (386.9 ± 806.3) µg/L, with the most prevalent compounds being o,p'-DDD, o,p'-DDE. Principal component analysis (PCA) results reveal that agricultural and industrial activities are the primary cause of OCPs pollution in surface and groundwater. Cancer risk of every pollutant in the groundwater was observed in the order of p,p'-DDE > dieldrin > heptachlor > p,p′-DDD > p,p′-DDT; the presence of p,p′-DDE, dieldrin, and heptachlor mostly in aquifer showed that these three OCPs are the most frequent cancer-causing chemicals. The concentrations of OCPs in surface and groundwater were compared with the standard of the United States Environmental Protection Agency (US-EPA). It is found that the concentrations of heptachlor, endrin, dieldrin, HCB, aldrin, mirex, α-BHC, β-BHC, γ-BHC7, δ-BHC, trans-chlordane, cis-chlordane, as well as DDTs (isomers and metabolites) in all water samples were beyond standard water quality guidelines. Ecotoxicological assessments following established water quality guidelines (WQGs) show that OCPs compounds provide a significant threat to the aquatic environment in the study area.

The present study aimed to investigate the physicochemical parameters, potentially toxic elements (PTEs) and Escherichia coli(E. coli) contamination with associated health risks in drinking water sources from the disaster affected areas of Khyber Pakhtunkhwa (Pakistan). Total water samples (n= 120) were collected from different water distribution schemes, such as non-government organizations (NGOs), government (GOV) and self-based scheme (SBS). The results showed that physicochemical parameters were found to be in decreasing order; NGOs > SBS > GOV in drinking water sources. PTEs concentrations were found to be in order; Zn > Pb > Cu > Cr > Co > Ni > Hg, Cu > Zn > Pb > Cr > Co > Ni > Hg, and Zn > Cu > Cr > Pb > Co > Ni > Hg for NGOs, GOV and SBS, respectively. Hg and Cr in SBS, while Co in GOV and SBS exceeded the WHO and Pak-EPA limits. Hazard quotient (HQ) showed no potential health risk, except for Co and Hg (> 1) in GOV and SBS. Principal component analysis (PCA) revealed high anthropogenic activities and less geogenic sources. The questionnaire survey showed that local communities were highly vulnerable due to poor pipelines system and domestic sewage within the areas of GOV and SBS water sources. Numerous diseases, such as dysentery contributed for (14%, 12%, and 18%), diarrhea (25%, 21%, and 18%), and stomach problems (48%, 33%, and 27%) due to consumption of E. colicontaminated water in NGOs, GOV and SBS, respectively, in the study area.

Deficiency of micronutrients is a major problem faced by nearly half of the world population due to intake of poor-quality food. To overcome the problem of malnutrition, biofortification of cereal crops is believed to be a good approach to increase nutrient contents in our daily food. The purpose of the current study was therefore to investigate the effect of foliar applied copper and boron alone and in combination with Trichoderma harzianumon yield attributes, grain quality, and nutrient contents of wheat. Wheat plants were treated with copper and boron in combination with or without T. harzianum. The applied treatments included Cu (0.05 M), Cu (0.1 M), T. harzianum, Cu (0.05 M)/T. harzianum, Cu (0.1 M)/T. harzianum, B (0.05 M), B (0.1 M), B (0.05 M)/T. harzianum, B (0.1 M)/T. harzianum, Cu (0.05 M)/B (0.05 M)/T. harzianum, and Cu (0.1 M)/B (0.1 M)/T. harzianumalong with a control set for comparison. Results revealed significant enhancement in different studied growth traits including plant height, spike length, kernels per spike, harvest index, and chlorophyll content. In addition, this approach also enriched wheat grains with various micro/macronutrients including Cu, Fe, Zn, K, and P. This study concludes that the bioreagent T. harzianumalong with foliar copper and boron may lead to reasonably enhanced grain quality and growth characteristics of wheat, further suggesting that the combined application of micronutrients along with T. harzianumunder suitable conditions will make it an acceptable approach for crop improvements.

AbstractIn this study, the effect of thermal exposure on the mechanical, physicochemical, microstructural and self-cleaning properties of photocatalytic cement mortars was investigated. 1%, 2%, 3% and 4% of the ordinary Portland cement weight was replaced with nano-TiO2particles. Mortars were heated at a rate of 2 °C/min to 200 °C, 400 °C, 500 °C, 600 °C, 700 °C and 800 °C. Compressive and flexural strengths, mass, water porosity, ultrasonic pulse velocity, optical microscopy, scanning electron microscopy, X-ray diffraction and thermogravimetric analysis tests were conducted before and after heating the mortars. The experimental results showed that nano-TiO2particles have a significant influence on the residual properties of the mortars. The addition of TiO2increased the resistance of the mortars to thermal deteriorations and preserved the residual mechanical, physicochemical and microstructural properties of the mortars. Additionally, for the first time, the influence of thermal exposure on the photocatalytic performance of cement composites was evaluated in this study by evaluating the degradation of rhodamine B. The photocatalytic performance was unaffected up to 400 °C, however, further heating deteriorated the photocatalytic performance of cement mortars.

•Developed a comprehensive power grid model incorporating various generating units•Centralized AGC system to provide frequency support during grid balancing operation•AGC model is incorporated with the dispatch-designed strategies of CES, WPES and CSU•Quantitative comparative analysis is performed to assess each AGC dispatch strategy

A brain tumor is one of the fatal cancer types which causes abnormal growth of brain cells. Earlier diagnosis of a brain tumor can play a vital role in its treatment; however, manual segmentation of the brain tumors from MRI images is a laborious and time-consuming task. Therefore, several automatic segmentation techniques have been proposed, but high inter-and intra-tumor variations in shape and texture make accurate segmentation of enhanced and core tumor regions challenging. The demand for a highly accurate and robust segmentation method persists; therefore, in this paper, we propose a novel fully automatic technique for brain tumor regions segmentation by using multiscale residual attention-UNet (MRA-UNet). MRA-UNet uses three consecutive slices as input to preserve the sequential information and employs multiscale learning in a cascade fashion, enabling it to exploit the adaptive region of interest scheme to segment enhanced and core tumor regions accurately. The study also investigates the application of postprocessing techniques (i.e., conditional random field and test time augmentation), which further helps to improve the overall performance. The proposed method has been rigorously evaluated on the most extensive publicly available datasets, i.e., BraTS2017, BraTS2019, and BraTS2020. Our approach achieved state-of-the-art results on the BraTS2020 dataset with the average dice score of 90.18%, 87.22%, and 86.74% for the whole tumor, tumor core, and enhanced tumor regions, respectively. A significant improvement has been demonstrated for the core and enhancing tumor region segmentation showing the proposed method's evident effectiveness. [ABSTRACT FROM AUTHOR]

Composite construction materials are widely utilized and have demonstrated superior efficiency compared to their constituent materials, such as steel and concrete. Despite their structural integrity and energy efficiency, reinforced concrete sandwich panels face limited adoption in numerous rural areas of developing countries like Pakistan, primarily due to the financial constraints of the population. Hence, this study proposes economical reinforced mud sandwich panels (RMSPs) incorporating mud wythes and investigates their flexure behavior. Mud being the commonly used construction material in rural areas, is readily available, making reinforced mud sandwich panels a potential viable alternative to conventional concrete sandwich panels. Three full-scale models of RMSPs were fabricated. The panels consist of an expanded polystyrene (EPS) layer reinforced with welded galvanized steel wires forming a mesh structure and shear connectors. In addition, both sides of the EPS were plastered with a layer of stabilized mud to create wythes of RMSPs. A stabilized mud mixture was prepared by combining constituents in the following proportions by weight: 67% soil, 10% cement, 1% wheat straw, and 22% water. All three RMSPs were tested under four-point loading. Two RMSP panels (RMSP-1 and RMSP-2) were tested by increasing the load gradually until failure. While the third panel (RMSP-3) was subjected to cyclic loading up to 7 kN, the load was then progressively increased till failure. According to the results obtained, the failure of the RMSPs occurred due to the EPS (core) fracture and crack propagation in the lower wythe under flexural stresses. Nonetheless, the panel resisted structural collapse despite experiencing significant midspan deformation. Numerical analysis of RMSP was also performed using finite element software (ABAQUS). The results demonstrated a strong correlation between numerical simulation and experimental results. RMSP exhibits promise as a potential alternative in sustainable construction technology, offering sufficient load-bearing capability and favorable structural properties such as ductility.

Plant species diversity patterns and vegetation structure are influenced by climatic and other environmental factors. We hypothesized that a combination of edaphic and topographic factors affect not only plant community patterns, vegetation structure and heterogeneity but also the indicator species in the dry temperate zone of the Liakot forests, Hindu Raj series of Hindu Kush Mountains, Pakistan. Quadrat along the elevation gradient were used for vegetation sampling. Soil samples were collected from each quadrat and analyzed by using standard protocols. All the collected data were analyzed using Cluster Analysis, Indicator Species Analyses and Data attribute plots via Canonical Correspondance Analyses. Cluster Analysis using Sorensen distance measurements grouped the plant species into three communities based on microclimatic indicators. These communities were: (1) Celtis caucasica-Lonicera hispida-Pennisetum orientale, (2) Juglans regia-Rubus idaeus-Tragopogon gracilis, and (3) Abies pindrow-Parrotiopsis jacquemontiana-Agrostis gigantea. Elevation, aspect, organic matter, electrical conductivity and potassium were the strong ecological factors responsible for different communities’ formation and their associated indicators in the region. Techniques and criteria used in the current study for communities formation and their respective indicator identification could be used further for management and conservation of the Liakot forest of the Hindu Raj series of Hindu Kush Mountains and other adjacent ecosystems of the northern Pakistan. Findings of the study can also be utilized in the reforestation drives.

Liquid insulation media is used for insulation and cooling purpose inside the transformer. Currently, transformers are using petroleum based mineral oil, which poses a serious hazardous environmental impact, since the mineral oil is non-renewable and non-biodegradable. Although, the increased cost and depleting nature of mineral oil cause an emergent need to use suitable alternatives to mineral oils that are biodegradable and environmentally friendly. In response to this resource issue, various vegetable oils, namely Sunflower oil, Soya bean oil, and a blend of Sunflower and Olive (BSO) oil are suitable alternatives for transformer insulation in high voltage systems. The afore-mentioned vegetable oils are subjected to multi-aging and comparative analysis is performed with mineral oil. Further, the dielectric and thermal properties of vegetable oils are tested before and after aging. Fourier Transform Infrared spectroscopy, water content, breakdown voltage, viscosity, flash point, tan delta, and pour point tests are performed on vegetable oils before and after aging. Finally, a comparative analysis of vegetable oils with mineral oil is provided to prove the efficacy of the proposed vegetable oils. The BSO oil resulted in higher breakdown strength and good thermal behavior when subjected to the abovementioned various diagnostic measurement tests in comparison to other oils.

The growing prominence and emphasis of renewable energy to decrease carbonization in the power system and reduce the dependability of fossil fuel for energy needs play an important role in the development of smart grids. Many technological advancements are integrated into smart grid to optimize the power system and renewable energy sources. Smart grid leverages electricity and energy consumption data exchange to establish a significantly advanced, automated, and decentralized electricity network. However, this brings numerous vulnerabilities to the power system, including cyber-attacks, grid blackouts, and electricity theft. While the most significant concern is energy theft, where some culprit’s consumers manipulate their energy meters to reduce their readings. This destabilizes the country’s electricity utility and economic development and causes a high tariff on energy for consumers who pay the bill. Therefore, developing an advanced framework for electricity theft detection is necessary. To address this problem, we propose a machine learning-based stacked framework to detect malicious activity in the smart grid. The proposed data-based stacked ensemble model detects honest and anomalous consumers in two stages. In the first stage, the model employs four individual classifiers at the base level to analyze data and a single classifier at the meta-level to classify the results of the base learners for the second stage classification. Furthermore, the Borderline SMOTE and Principle Component Analysis techniques are employed to address the class imbalance and curse of dimensionality issues respectively. Through experimental analysis, we proved the effectiveness of the proposed framework in detecting suspicious activity in four different experiments, including preprocessed data, feature extracted data, balanced data, and lastly, both feature engineering and data balancing. The simulation outcomes demonstrate that our proposed framework enhanced energy security and overcomes the impact of theft attacks on the smart grid.

In this article, we address the challenge of solving the nonlinear fractional Burger’s KdV equation, time-fractional Burger’s equation, and the fractional modified Burger’s equation. This is achieved by employing the Caputo and conformable derivatives. To tackle these equations, we introduce a new numerical method which is the combination of the local fractional Mohand transform and the Adomian decomposition method. This choice is driven by its straightforward methodology and reduced computational complexity. Moreover, to demonstrate the versatility of this technique, we provide several illustrative examples along with their corresponding exact or approximate solutions. These solutions are accompanied by graphical representations, further enhancing the clarity of the presented approach.

The development of intelligent applications using sensing technology in cooperation with the Internet of Things (IoT). In combination, they allow Internet users to get the necessary data from cloud systems by transmitting information from objects to web servers. The community demands, such as response times and reliable remote connections for accessing the information from IoT networks. Although, the majority of proposed solutions provide the optimal way to direct network traffic toward cloud storage. However, most of them are still needed to manage resources efficiently while handling huge amounts of data. Moreover, distributed IoT services must be intelligent and also be secure against malicious data access. This study introduces an autonomous approach using trusted sensing technologies to provide reliable remote sensing and aggregation for future-generation systems. In the first phase, the proposed model looks at an artificial intelligence-based method for negotiation between IoT devices and mobile stations for transferring the data. The second phase involves the creation of a robust security method that supports digital certificates for peer-to-peer mutual authentication. Additionally, to maintain the integrity of certificates, they are sent securely in the form of a chain. Finally, a combination of trust and privacy is used while storing data on cloud servers. Simulation-based experiments have shown that the proposed model significantly outperforms I-AREOR and MCNA in terms of energy consumption, packet delivery ratio, malicious threats, and overhead.

In the present era of Big Data, with continuously increasing amounts of user-generated content, it is becoming a challenge to understand the relation between the content that is available on the Web and the users who are generating that content. Researchers have come up with many ways to understand today's Web better. One of the recently introduced concepts is a Web observatory (WO). This article provides a deep understanding about web observatories. It discusses the status of existing WO systems. The article investigates and gathers the common practices of WOs. This research has implications for researchers and communities in the adoption of the WO concept. The article highlights the challenges of WOs, such as data crawling, privacy and security. It also provides future research and development directions. The article provides a comparative analysis of existing WOs. It discusses the architecture of WOs. It presents components of a WO in a coherent manner and finally provides insights into challenges and limitations of WOs.

Industrial sector is the backbone of the development of a country; however, its untreated effluents are damaging various ecological phenomena. Every day huge amounts of municipal, industrial and agricultural wastes are being released into the environment, causing serious ecological problems. Pakistan is currently experiencing profound demographic, economic changes and energy crisis that pose serious limitations on spending capital on water treatment. However, no serious effort has been put forth by any agency in Pakistan to characterize the exact nature and concentrations of contaminants found in wastewaters originating from various industrial zones. The current study aimed to characterize the industrial effluent quality of Hattar Industrial Estate, Hattar, Pakistan. The effluent samples were collected from five different drains, each having the combined effluent of many industries. All the samples were characterized for pH, temperature, TS, TDS, TSS, EC, DO, BOD, COD, turbidity, nitrates (NO3–N), phosphates (PO4), ammonia (NH4–N) and different heavy metals according to the standard methods. Majority of the water quality parameters exceeded the National Environmental Quality Standards in the country. These pollutants may have serious impacts on the soil profile, groundwater quality and freshwater ecosystems and thus need attention of policy makers to install a centralized wastewater treatment plant.

An effective numerical method is proposed for the three-dimensional nonlinear analysis of mooring cables using catenary theory. In this method, the mooring line is divided into finite number of catenary elements. In addition to self-weight, each catenary element is subjected to drag force due to steady ocean currents. The proposed procedure is validated by comparing the results with those of the shooting optimization and the finite element methods. Finally, a parametric study is conducted to study the effect of extensibility on the static response of mooring cables. The effects of fluid drag forces and cable extensibility on mooring cable tension, equilibrium configurations, and stressed lengths are illustrated for two- and three-dimensional mooring cable problems. From the numerical results, the method is found to be numerically stable, and it provides a more rational static response for mooring cables.

All the compositions in the (1−x)Mg0.95Ni0.05Ti0.98Zr0.02O3–xCa0.6La0.8/3TiO3(0 ≤ x≤ 0.2) series were fabricated using solid state sintering route. Mg0.95Ni0.05Ti0.98Zr0.02O3possessed excellent microwave dielectric properties with εr≈ 17.1, Quf0≈ 195855 GHz, and τf≈ -46 ppm/°C. τfwas tuned through zero by mixing with Ca0.6La0.8/3TiO3. In the present study, τf≈ -2 ppm/°C with εr≈ 23.9 and high Quf0≈ 115870 GHz was achieved for x= 0.15, i.e., for a mixture of 85% Mg0.95Ni0.05Ti0.98Zr0.02O3and 15% Ca0.6La0.8/3TiO3.

AbstractScalability in hardware and/or software is an important factor for enhancing the performance of running processes as well as the throughput of the system of business organizations. This paper explores the need for scalability and issues related to extending the resources in order to ensure an improved and scaled-up Customer Relationship Management (CRM) architecture. The main contribution discussed in this paper is the proposal of a conceptual framework for measuring the process performance and throughput of the system beyond the selection of the type of scalability. Furthermore, this paper concerns the CRM system, as customer requests, their online transactions, and responses need a fast and efficient system. Taking into consideration all these factors, ultimately this paper proposed a customer-friendly framework for measuring the process performance and throughput of the system. Finally, the proposed framework’s steps are shown in an algorithm calculating process performance and throughput of the system.

In this paper, a contactless charging system for an electric vehicle (EV) battery is proposed. The system consists of three parts: 1) a high-frequency power supply from a full-bridge inverter with frequency modulation; 2) a loosely coupled transformer that utilizes series resonant capacitors for both the primary and secondary windings; and 3) a rectification output circuit that uses a full-bridge diode rectifier. With carefully selected compensation network parameters, zero-voltage switching can be ensured for all the primary switches within the full range of an EV battery charging procedure, which allows the use of low ON-state resistance power MOSFETs to achieve high-frequency operation and system efficiency. The design of loosely coupled transformer is simulated and verified by finite element analysis software. For a 4-kW hardware prototype, the peak dc-dc efficiency reaches 98% and 96.6% under 4- and 8-cm air gap conditions, respectively. The prototype was tested with an electronic load and a home-modified EV to verify the performance of constant current and constant voltage control and their transitions.

Untreated wastewater discharges may have significant short term and long term effects on the quality of a river system. Present study was undertaken to assess the present status of the water quality of the River Kabul near Peshawar in Pakistan. Seven sites were sampled upstream and downstream in the River Kabul in 2009. Samples were also taken from waste water channel (Budni Drain) that carries waste-water of Peshawar Industrial Estate as well as the domestic sewers to assess the pollution contribution of these sources to the River Kabul. Physico-chemical and microbiological parameters of the samples were analyzed during the study, as well as possible sources of contamination were investigated. The study showed that the pollution level in river is rising from upstream (at city entrance) to downstream (at city exit) due to discharge of domestic waste water effluents, agricultural activities, and solid waste dumping directly into the river.