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Graph labeling is an increasingly popular problem in graph theory. A mapping converts a collection of graph components into a set of integers known as labels. Graph labeling techniques typically label edges with positive integers, vertices with even numbers, and edge weights with consecutive numbers, known as edge irregular reflexive total labeling. This is achieved by utilizing the reflexive edge irregularity strength of the graphical structure. The edge calculates the exact values of the reflexive edge irregularity strength irregular reflexive labeling for the $ m^t $-graph of cycle graph $ mC_n $ on $ t = 1 $ with $ n \geq 3 $ and $ m \geq 4 $. The maximum number of assignments assigned to each individual in a communication network, as well as providing a secure communication channel to ensure the unique identification of each employee, are potential applications for this problem.

Background and Purpose: Emergence of fungi as a pathogenic threat presents a significant challenge to public health, notably in intensive care units (ICUs) and among immunocompromised patients. Various factors, including sepsis-induced barrier disruptions, immune system dysfunction, and extremes of age, contribute to increased susceptibility to fungal infections. Hospital practices, such as prolonged surgeries, broad-spectrum antibiotic use, and invasive procedures, further exacerbate the risk. Fungal bloodstream infections, particularly those caused by Candida albicans, rank among the most common hospital-acquired infections, leading to substantial morbidity and mortality. The global rise in invasive candidiasis, particularly due to non-albicans Candida species, presents challenges in the diagnosis and treatment due to nonspecific symptoms and emerging antifungal resistance. Nanotechnology interventions particularly by utilizing green synthesized copper nanoparticles could possibly provide a novel solution to combat microbial colonization, biofilm formation, and drug resistance. This study aimed to assess the prevalence of candidemia, identify the distribution of causative Candida species, and understand their susceptibility patterns to commonly used antifungal agents for effective management in ICU settings. Additionally, the study sought to explore the in vitro anti-Candida activity of green copper nanoparticles synthesized using Euphorbia milii des moul extract.Materials and Methods: This study was conducted at Microbiology Laboratory of Maharishi Markandeshwar Institute of Medical Sciences and Research from January to December 2022, focused on ICU patients suspected of bloodstream infections. Blood samples were collected aseptically and processed using BD BACTECTM culture vials. Identification of organisms was performed via the Vitek-2 system by confirming candidemia with positivity in both blood samples. After that antifungal susceptibility testing was also performed against Clinical and Laboratory Standards Institute recommended antifungal drug using Vitek 2 system. G-CuNPs were synthesized using E. milii Des moul extract and possessed for physiochemical characterization. The anti-Candida activity of GCuNPs was evaluated through the MTT assay and time kill assay. After that generation of intracellular reactive oxygen species and DNA degradation were evaluated to understand its mechanism.Results: This study identified a candidemia rate of 7.3% (58/789). Age and gender analysis revealed higher Candida colonization rates in individuals above 60 years old and females. Antifungal sensitivity profiling indicated notable resistance to fluconazole (27.59%) and voriconazole (25.86%). Synthesizing G-CuNPs using E. milii des moul extract represents a novel approach exhibiting significant fungicidal potency against clinically isolated C. albicans, supporting potential therapeutic applications.Conclusion: the findings concluded that synthesized G-CuNPs have tremendous potential to battle against medical device-borne infections by surface coating.

Abstract This article introduces a novel integrated nearest level controller (NLC) combined with selective harmonic mitigation (SHM) control approach aimed at efficiently suppressing lower‐order harmonics has been introduced. The proposed methodology is implemented on the PUC‐7 inverter topology, leveraging the combined benefits offered by both NLC and SHM controllers through a hybrid model. The proposed method demonstrates the capability to reduce lower‐order harmonics up to the 49th harmonic from the load voltage. The particle swarm optimization algorithm is employed to determine optimal switching angles and their corresponding nearest levels, thereby reducing implementation time, computational complexity, and overall system intricacy. The performance analysis of the proposed control strategy across various scenarios, including fluctuations in modulation index and monitoring diverse parameters such as load dynamics has been performed. This approach yields a significant reduction in total harmonic distortion in both load voltage and current. A comparative analysis between NLC, selective harmonic mitigation (SHM), and the integrated NLC‐SHM approach is carried out on the PUC‐7 inverter. The integrated SHM‐NLC control is implemented and validated using the MATLAB Simulink environment, complemented by hardware‐based experimentation, to ascertain its effectiveness.

Background & objectives: Chronic obstructive pulmonary disease (COPD) is a notable worldwide public health issue and a major cause of morbidity and mortality in Pakistan. The objective of this study was to assess the health-related Quality of Life (HRQoL) among patients diagnosed with COPD and to explore the determinants that impact it. Methods: This cross-sectional study comprised 400 individuals diagnosed with COPD who were aged 30–75. The St. George's Respiratory Questionnaire (SGRQ), which is specific to COPD, was employed to assess the patient's quality of life. The overall score of all three domains, namely activity, impact, and symptoms, was calculated. The chi-square test was used to find out the association between the SGRQ scores and the respondent's characteristics. Results: The mean score of SGRS was 59.04 ± 1.03, indicating worse health. About 60 % (n = 240) of the participants had phlegm most of the day. Additionally, most of them 62 % (248) suffered from cough most days a week, with a p-value of 0.010, and the shortness of breath (p

As load-bearing components, metallic implants are frequently used for orthopedic prostheses due to their superiority over conventional ceramic and polymeric biomaterials. Metal-based orthopedic implants have been subjected to various fabrication and treatment methods to enhance their biological activities at the host site. Modifying the structure, improving the hydrophilicity, and developing controlled-release drug delivery systems can improve cellular adhesion, proliferation, osseointegration, and differentiation. Ultrafast lasers have recently attracted interest in surface engineering. Laser surface structuring permits the alteration of sample topography, the chemical makeup of the surface, and the material physical properties. This study presents the surface modification of a TiNbZrSn shape memory alloy using a femtosecond laser to produce laser-induced periodic structures with better drug release than that of a pristine sample. We also present the in vitro cell viability and biocompatibility of the alloy system. All samples structured with femtosecond laser exhibited superhydrophilic nature with 0° contact angle. In addition, the laser structured surfaces showed cell viability above 80 % and minimal cytotoxicity towards human keratinocytes. Moreover, a well-defined hydroxyapatite layer developed on the laser structured surface. In general, the laser structuring process and the induced changes on the surface in terms of roughness and oxide formation result in slower drug release (up to 10 %) compared to pristine specimens.

Abstract A new area of applied chemistry called chemical graph theory uses combinatorial techniques to explain the complex interactions between atoms and bonds in chemical systems. This work investigates the use of edge partitions to decipher molecular connection patterns. The main goal is to use topological indices that capture important topological features to create a connection between the thermodynamic properties and structural characteristics of chemical molecules. We specifically examine the complex web of atoms and links that make up the Fe phthalocyanine chemical graph. Moreover, our study demonstrates a relationship between the calculated topological indices and the thermodynamic properties of Fe phthalocyanine (Phthalocyanine Iron (II)). This work offers insight into the thermodynamic consequences of molecule structures. It advances the subject of chemical graph theory, providing a useful perspective for future applications in catalysis and materials science.

Abstract Background Intellectual disability (ID) is a neurodevelopmental condition affecting around 2% of children and young adults worldwide, characterized by deficits in intellectual functioning and adaptive behavior. Genetic factors contribute to the development of ID phenotypes, including mutations and structural changes in chromosomes. Pathogenic variants in the HCFC1 gene cause X-linked mental retardation syndrome, also known as Siderius type X-linked mental retardation. The MN1 gene is necessary for palate development, and mutations in this gene result in a genetic condition called CEBALID syndrome. Methods Exome sequencing was used to identify the disease-causing variants in two affected families, A and B, from various regions of Pakistan. Affected individuals in these two families presented ID, developmental delay, and behavioral abnormalities. The validation and co-segregation analysis of the filtered variant was carried out using Sanger sequencing. Results In an X-linked family A, a novel hemizygous missense variant (c.5705G > A; p.Ser1902Asn) in the HCFC1 gene (NM_005334.3) was identified, while in family B exome sequencing revealed a heterozygous nonsense variant (c.3680 G > A; p. Trp1227Ter) in exon-1 of the MN1 gene (NM_032581.4). Sanger sequencing confirmed the segregation of these variants with ID in each family. Conclusions The investigation of two Pakistani families revealed pathogenic genetic variants in the HCFC1 and MN1 genes, which cause ID and expand the mutational spectrum of these genes.

Abstract In this research, the star gold structure with beta graphene is thoroughly examined. We mainly focus on computing degree-based topological indices, which provide information about the network’s connectivity and complexity as well as structural features. In addition, we compute an entropy measure to represent the uncertainty, information richness, and degree of unpredictability in the network. Furthermore, this study explores the relationships between topological descriptors and entropy using regression models that are logarithmic, linear, and quadratic. By merging these regression models, we uncover hidden patterns and understand the underlying ideas governing the network’s behaviour. Our findings shed light on the connection between topological indices and entropy. This work improves our understanding of star gold structure dynamics and provides a visual framework for interpreting their behaviour.

Background: Terminal ‘hotshot’ (THS) cardioplegia is a technique that might contribute into myocardial protection in patients undergoing cardiac surgery. Objective: To determine the effect of THS cardioplegia administration in patients undergoing coronary artery bypass grafting (CABG). Methods: A randomized control trial (ACTRN12624001225505) was conducted from 20th December 2023 to 10th February 2024 involving 60 patients admitted from the outpatient department for elective CABG at Faisalabad Institute of Cardiology, Faisalabad, Pakistan. It was a single-blinded study and the patients were randomized into two equal groups, group A (control group) and group B (experiment group). During the surgery performed utilizing a Cardiopulmonary Bypass (CPB) machine, both groups received cold blood cardioplegia to arrest the heart, providing a quiescent field at the start of the grafting process in CABG. In group B patients, 100 ml of THS volume was given to each of the grafted territories via saphenous vein grafts and the rest of the volume from the total of 500 mL was given in the aortic root via the antegrade cardioplegia cannula for maximum myocardial distribution. The levels of Troponin I (TnI) and Creatinine Kinase MB (CK MB) were measured in the blood one hour after regaining sinus rhythm and on 5th postoperative day (POD). Durations of postoperative Inotrope use, intubation, aortic cross-clamp, CPB time, time to regain sinus rhythm, and ICU stay were recorded in both the groups. Data was entered and analyzed using SPSS version 25. A p-value ≤ 0.05 was considered statistically significant. Results: Mean age of the participants was 58.9±7.36 years. The levels of TnI were lower in group B than in group A one hour after regaining sinus rhythm (0.20±0.076 ng/ml and 0.31±0.058 ng/ml respectively, p-value 0.05). Conclusion: ‘Hot shot’ cardioplegia decreases the release of TnI from the myocardial cells post-cardiac surgery. The inotropic support time is also shortened when THS cardioplegia is used.

The article provides a detailed look at the fabrication of a high-performance structure for FASnI3-based perovskite solar cells (PSCs). The FTO/CeO2/FASnI3/CuI/Au structure is designed using the Solar Cell Capacitance Simulator in One Dimension (SCAPS-1D) to investigate the fabricated PSC's performance. This investigation's main objective is to improve PSCs performance by using non-traditional Hole transport layer (HTL) and Electron transport layer (ETL) materials, such as CeO2 and CuI, which have both been the subject of limited research. Moreover, the investigation seeks to determine the impact of several perovskite layer characteristics, including bandgap (Eg), electron affinity (χ), acceptor density (NA), thickness (t), and defect density (Nt). Additionally, this study also investigates the effect of various back contact work functions. Significant improvements in solar cell parameters, such as power conversion efficiency (PCE) from 22.06% to 24.87% and current density (Jsc) from 26.0274 to 30.675 mA/cm2, were observed by optimizing the device's parameters. In contrast, the fill factor (FF) and open circuit voltage (Voc) decreased their values from 86.13% to 87.10% and 0.9843 to 0.9308 V, respectively. These findings show that our designed solar cell structure performs better than those with conventionally used HTLs and ETLs. Consequently, this study highlights the potential benefits of lead-free PSCs and presents fresh opportunities for their development and use in various solar applications.

This work presents the concept of controlled dislocated metric spaces, and the Banach contraction principle in these spaces is examined. Next, we provide extensive examples of numerical convergence of fixed points to demonstrate the practical implications of such spaces. Along with specific instances, it presents the idea of a rational contraction of the [Formula: see text]type to determine common fixed points in such spaces. Moreover, numerical analysis and graphical comparisons are used to further assess the existence of common fixed points based on the provided notions. Lastly, using these ideas to solve a Volterra integral equation shows how useful they are for finding common solutions, improving our comprehension of fixed point theory in these spaces, and creating new avenues for applications.

This study examines the role of Islamic finance in advancing the United Nations' Sustainable Development Goals (SDGs), focusing on often-overlooked conflicts among these goals, such as the tension between poverty alleviation (SDG 1), hunger eradication (SDG 2), and environmental sustainability. It emphasizes the need for balanced progress across SDGs, particularly in Muslim societies where welfare aligns with religious principles. The study advocates for a Green Economic Transition (GET) aimed at achieving high human development while respecting Maqasid Shariah and ecological limits. GET, it suggests, should be the core of climate-conscious policies and business strategies. Recognizing shifts in the global financial system to reconcile economic and social development with environmental goals, the study underscores the need for policies aligning these aspects. It also explores the contribution of Islamic economics and finance-including commercial finance (banking, takaful, Sukuk, Shariah-compliant equity markets) and social finance (Zakah, Waqf, charities, Qard)-in fostering sustainable green finance. Noting the gap where these tools are still tied to conventional finance, the study proposes a framework for developing coherent climate policies within Islamic finance and identifies opportunities for Islamic sustainable green finance.

After successfully performing Agrobacterium-mediated CRISPR-Cas9-based gene editing in plants, isolation of the Cas9 T-DNA is essential for the stable inheritance of induced mutations. Here, we report a simple technique that allows the isolation of Cas9-free mutants, eliminating the need for outcrossing or other intricate methods. This method is based on the ability of Basta-sensitive Arabidopsis thaliana seedlings, which generally perish, to recover and grow once transplanted to Basta-free growth media. By growing gene-edited heterozygous populations of single-locus insertion Basta-resistant plants on Basta selection media, plants lacking the Cas9 T-DNA can be identified. These pale-looking plants lacking Cas9 are then rescued on media lacking the Basta to recover Cas9-free plants. The ability of seedlings to recover from Basta selection was also studied in camelina, canola, and wheat. All three crops showed different recovery rates, with wheat demonstrating the highest recovery once transplanted from Basta to normal growth media. In summary, our findings demonstrate that by harnessing the recovery capability of Basta-sensitive seedlings, we can effectively identify and rescue plants lacking the Cas9 T-DNA, enabling the isolation of Cas9-free mutants in Arabidopsis and potentially extending to other crops.

The performance of power networks is enhanced by the penetration of solar energy, which helps to equate continuously the generation and demand power imbalance. However, the time margin that grids must adapt to unforeseen frequency fluctuations and restore generation-demand equivalency is reduced by these linkages. Consequently, it exerts the stability and performance of the power grid at risk. Thus, it becomes vital to assess real-time system data and to recognize and implement suitable remedies to maintain a healthy system performance. In order to improve grid stability in power networks that have solar energy penetration, this manuscript suggests a data driven integrated framework. The proposed approach is a two-step framework wherein the first stage assesses impending transient instability in the system through novel Instability Evaluation (IE). Step two involves creating and deploying a Decision Boundary based Control (DBC) to stabilize an unstable system following an emergency control strategy. An IE module employing short-synchronized movement data is presented for evaluating post-disturbance transient stability (TS). In the initial cycles following the fault initiation, the IE projects the impending transient instability. Next, an innovative DBC creates an emergency remedial system for unstable processes that determines the nature, magnitude and location of the remedial action. The DBC assesses pertinent action sets that it implements to sustain system stability using a proposed Decision Assisted Inference (DAI) technique. The simulation investigations validate the aptness of suggested analysis on the performance of power system with and without PV and topological variations.

Effective microgrid control for system recovery and restoring normal operation necessitates fast event detection and implementation of remedial action (if need arises). However, fast and reliable event detection in microgrids is challenging because of low observability and inconsistencies in measurements. A novel technique is proposed in the present work for the real-time event detection and to identify the various emerging abnormalities in the microgrid. The continuous energy signature using TKEO (Teager-Kaiser Energy Operator) of the continuous varying voltage and frequency signal are extracted through μPMU. REII (Robust Event Identification Index) is constructed from these energy signatures and based on its abrupt post-event deviation from the nominal values an event is flagged in the proposed method. The proposed method is data–driven and only depends on the real-time inputs through μPMUs thus it automatically adapts the uncertainties associated with the intermittent sources of energy in the microgrid under different operating conditions. The traditional event detection techniques fail in identification of abnormalities for a microgrid connected to the transmission systems and equipped with multiple DERs such as PVDG, WG etc. To address this challenge, an integrated microgrid with multiple DERs viz. PVDG, WG and a SG (Synchronous Generator) is first developed in this work. The complexity of simultaneous operation of a static generator i.e. PVDG along with a rotor-based generator such as WG and SG is handled by the modeling the dynamic controllers of PVDG and WG for their frequency and voltage control. The simulation results depict the efficiency, accuracy and robustness of the proposed technique in terms of estimation time, event accuracy and applicability in all types of events. Moreover, the presented methodology is also compared with the four AI/ML based methods to highlight the superiority of the method.

Muhammadiyah as a part of the civilization has a responsibility to spread the mercy. The organization that founded by KH Ahmad Dahlan is not carrying the theme "Efforts to Save the Universe" for its 111th anniversary in 2023 without reason. This is because the universe is not fine. Especially the natural environment. The proof is the waste emergency, the prolonged impact of El Niño, forest fires, and the never-ending haze. These are the problems of this research. Collective efforts as the solutions are needed to resolve these problems. Muhammadiyah as a preaching movement of amar ma'ruf nahi munkar takes a role in caring for the environment. This research has some contributions. They are as a lesson learnt for another communities and the implementation of Fikih Biah. The purpose of this article is to analyze the realization of efforts to save the universe. The method used is literature research. Some literatures are used to reveal the role of Muhammadiyah to reach the good society (khairu ummah). Water jurisprudence, disaster jurisprudence, Global Forum for Climate Change, and a lot of communities empowering are the evidences of Muhammadiyah commitment to save this universe. The conclusion of this research that include in Muhammadiyah efforts is felt in adding environmental awareness, switching consumption behavior, and developing the quality of life of local socities.

Abstract Carotenoid cleavage oxygenases (CCOs) enzymes play a vital role in plant growth and development through the synthesis of apocarotenoids and their derivative. These chemicals are necessary for flower and fruit coloration, as well as the manufacture of plant hormones such as abscisic acid (ABA) and strigolactones, which control a variety of physiological processes. The CCOs gene family has not been characterized in Arachis hypogaea. Genome mining of A. hypogaea identifies 24 AhCCO gene members. The AhCCO gene family was divided into two subgroups based on the recent study of the Arabidopsis thaliana CCO gene family classification system. Twenty-three AhCCO genes, constituting 95.8% of the total, were regulated by 29 miRNAs, underscoring the significance of microRNAs (miRNAs) in governing gene expression in peanuts. AhCCD19 is the only gene that lacks a miRNA target site. The physicochemical characteristics of CCO genes and their molecular weights and isoelectric points were studied further. The genes were then characterized regarding chromosomal distribution, structure, and promoter cis-elements. Light, stress development, drought stress, and hormone responsiveness were discovered to be associated with AhCCO genes, which can be utilized in developing more resilient crops. The investigation also showed the cellular location of the encoded proteins and discovered that the peanut carotenoid oxygenase gene family’s expansion was most likely the result of tandem, segmental, and whole-genome duplication events. The localization expresses the abundance of genes mostly in the cytoplasm and chloroplast. Expression analysis shows that AhCCD7 and AhCCD14 genes show the maximum expression in the apical meristem, lateral leaf, and pentafoliate leaf development, while AhNCED9 and AhNCED13 express in response to Aspergillus flavus resistance. This knowledge throws light on the evolutionary history of the AhCCO gene family and may help researchers better understand the molecular processes behind gene duplication occurrences in plants. An integrated synteny study was used to find orthologous carotenoid oxygenase genes in A. hypogaea, whereas Arabidopsis thaliana and Beta vulgaris were used as references for the functional characterization of peanut CCO genes. These studies provide a foundation for future research on the regulation and functions of this gene family. This information provides valuable insights into the genetic regulation of AhCCO genes. This technology could create molecular markers for breeding programs to develop new peanut lines.

Abstract Background Dentin hypersensitivity (DH) is one of the most challenging and persistent dental complaints characterized by transient, intense pain triggered by various stimuli. It affects a significant portion of the global population, predominantly those aged 20–40. This study aims to evaluate the desensitizing efficacy of seventh-generation dentin bonding agents (Single Bond Universal by 3 M ESPE and Xeno-V + by Dentsply) against a control group using Bifluorid 12 by Voco in mitigating DH within a month of the follow-up period. Methods This was a single-center, parallel-group, double-blind, controlled randomized clinical trial conducted at Dow University of Health Sciences, Karachi, Pakistan. A total of 105 patients with DH were allocated into three groups for this study. The patients were divided into three groups (Single Bond Universal by 3 M ESPE and Xeno-V + by Dentsply) and the control group containing fluoride varnish (Bifluorid 12 by Voco). Discomfort Interval Scale scores and Schiff Cold Air Sensitivity Scale scores were recorded at baseline, immediately after the intervention, after 01 weeks, and after 01 month. Results All the materials demonstrated a statistically significant reduction in discomfort and sensitivity (DIS scores p-value 0.01) immediately after 01 week and over a period of 01 month after treatment compared with the baseline scores before application, with no single material proving superior over the one-month observation period. The study also provided insights into dental hygiene practices, with a significant majority using a toothbrush and sensitivity patterns, with cold stimuli being the most common cause of sensitivity. Conclusion The study demonstrates that Single Bond Universal, Xeno V+, and Bifluorid 12 are equally effective in reducing dentin hypersensitivity, with no distinct superiority observed over a one-month period. The findings highlight the potential of fluoride varnishes as a less technique-sensitive and cost-effective option for treating DH, offering valuable insights for future research and clinical practice. Trial registration NCT04225247 ( https://clinicaltrials.gov/study/NCT04225247 ), Date of Registration: 13/01/2020. (Retrospectively registered).

Objective: Delay in the diagnosis of tuberculosis (TB) is a significant problem at both individual and community levels. Delayed diagnosis of TB contributes to more severe disease manifestations, higher risk of death, and higher disease transmission in the community. We conducted this study to assess the extent and associated reasons for delay in diagnosis of pulmonary TB. Methods: This study was conducted in the Department of TB and Respiratory Diseases, J. N. Medical College, Aligarh, from June 2020 to May 2022. A total of 2053 new pulmonary TB patients, who first consulted any private healthcare provider (HCP) for treatment, were enrolled in the study. The required information was collected by interview technique using a predesigned questionnaire. Results: A total of 2053 patients were enrolled in the study. There was a significant delay of more than 2 weeks in the diagnosis of pulmonary TB after the onset of symptoms in 94% of patients. The extent of delay ranged from 8 days to 240 days with a mean of 36.33 days. The delay in visiting the HCPs by the patient was not significant. Only 5.85% of patients had a significant delay of more than 2 weeks in seeking any health care after the appearance of symptoms. A delay by HCP contributed to a greater portion of the total delay, with a mean of 31.77 days. The main reason for the delay by HCPs was not investigating TB. The hospital delay was not significant. The mean hospital delay was 5.82 days. Conclusion: The delay in the diagnosis of TB in India is very high. A delay by HCPs contributes to a greater portion of the total delay. Information, Education and Communication (IEC) activities will play an important role in reducing the delay. All HCPs should be actively involved in subjecting the suspects to TB diagnosis at the earliest possible as per National Tuberculosis Elimination Programme (NTEP) guidelines.

This study investigates how plants protect themselves, specifically looking at a group of genes called Xyloglucan Endotransglucosylase/Hydrolase (XTH) in cucumber plants. A detailed investigation of CsXTH genes, uncover their evolutionary background, structural motifs, regulatory networks, and functional responsibilities. The investigation utilized various bioinformatics tools and databases to highlight the dynamic interplay between CsXTH genes and abiotic stress responses. The investigation begins with a phylogenetic analysis that reveals the cladding of CsXTH genes into four categories. Further unraveling the conserved motif and domain analyses expose the coordination of xyloglucan modification, highlighting essential motifs and domains shared among these genes. Analyzing cis-regulatory elements helps us understand the complex networks that control the defense mechanisms of cucumber plants. Among these elements, CGTCA-motif and TGACG-motif stand out as key players in interpreting environmental signals and coordinating stress responses. The microRNA Csa-miR169 is becoming a key player in regulating the expression of CsXTH genes, and controlling the biological responses of cucumber plants. Chromosome mapping, Ka/Ks calculations, and protein-protein interaction analysis offer insights into the structural and evolutionary dynamics of CsXTH genes. Additionally, the study explores sub-cellular localization, uncovering the diverse cellular compartments where CsXTH genes are active. Finally, through chrysophanol and physcion, we unveil the adaptable functions of specific CsXTH genes in response to distinct treatments, underscoring their role in orchestrating cucumber's adaptive strategies.

Image deblurring (ID) plays a vital role in various applications, including photography, medical imaging, and surveillance. Traditional ID methods often face challenges in preserving fine details and handling complex blurring scenarios due to expensive calculations. In this paper, a novel approach utilizing conformable fractional derivative (CFD) to address these challenges and improve the effectiveness of ID is presented. CFD offer a flexible framework for capturing and exploiting the non-local and non-linear properties inherent in images. Additionally, we propose a new circulant preconditioned matrix that ensures a fast convergence rate. The proven analytical property of the new preconditioner ensures fast convergence rates. The efficiency and efficacy of our algorithm is demonstrated by numerical experiments.

Objectives The current study aimed to find the distribution and factors associated with undernutrition among children aged 6–36 months in Kabul.Design Cross-sectional study.Setting Public Ataturk Children’s Hospital, Kabul.Participants 385.Methods A structured questionnaire was used to collect data on sociodemographic conditions and anthropometry of children. Logistic regression was used to find determinants of undernutrition.Results The distribution of stunting, wasting and underweight was 38.7%, 11.9% and 30.6%, respectively. Among the children studied, 54% did not receive breast milk within the first hour of birth, 53.2% were not exclusively breastfed, 21% received complementary feeding before the age of 6 months, 22.1% lacked access to safe water and 44.7% did not practise hand washing with soap. The odds of stunting were lower (p

Objective To assess the level of bioethics awareness among healthcare professionals in Pakistan, focusing on the associations with sociodemographic characteristics, training and teaching of ethics, medical ethics practice and specific ethical issues.Design Cross-sectional study.Setting Public and private hospitals in Haripur, Pakistan.Participants A total of 647 healthcare professionals participated in this study.Methods This study was conducted between March and May 2023, following Strengthening the Reporting of Observational Studies in Epidemiology checklist criterion, involving healthcare professionals with at least 6 months of experience in patient care practice. Providers under close supervision are advised not to respond to the bioethics knowledge, attitudes and practices survey form due to potential ethical dilemmas.Results Both physicians and non-physicians need to know more about bioethics. There was a significant difference (p

Pakistan has limited natural gas reserves, and most are found onshore. This article reports on the problems of an onshore gas gathering network (GGN) analysed through steady-state simulation modelling using PIPESIM software. The research methodology incorporates a comprehensive steady-state hydraulic analysis considering fluid flowing velocity limitations, liquid holdup and slugging along with other issues faced by gas gathering networks. The steady-state hydraulic analysis has led us to pinpoint specific GGN pipelines facing critically low gas velocities and consequent liquid holdup. Addressing these issues involved application of PIPESIM software for modelling, considering various operating schemes of gas-producing wells and their associated pipelines. To select an optimal operating scheme, the study utilized the Analytic Hierarchy Process (AHP) for operational optimization, to identify the most effective solution for reduced liquid holdup, improving production, and ensuring the safe operation among available alternatives. Findings from our hydraulic analysis highlight the importance of reducing GGN outlet pressure to mitigate challenges associated with liquid holdup which causes slugging and back pressure effect at source leading to low production and poor performance of the GGN. Study of three alternative cases reveals that decreasing outlet pressure lowers the liquid holdup, improve gas flowing velocities, and enhanced overall production. These findings validate our hypothesis that reducing GGN outlet pressure is a viable strategy to lower the liquid holdup in pipelines. This research offers significant value by providing a comprehensive solution to GGN liquid holdup, low flowing velocities, back pressure and low production challenges. The integration of steady-state hydraulic analysis, simulation modelling with PIPESIM, and the application of AHP for optimization contributes novel insights into the optimization of operation of gas gathering networks. Emphasizing the reduction of liquid holdup and enhancing production through outlet pressure adjustments offers a practical framework for optimizing the functionality of gas gathering networks.

Ion implantation of laser induced graphite plasma has been performed for modifications in surface, optical, electrical and structural properties of CR-39. KrF Excimer laser (248 nm, 18 ns, 120 mJ), at an irradiance of 2.5 × 108 W cm−2 is utilized for the production of graphite plasma. The energy and fluence of graphite ions are estimated by Thomson parabola technique. The targets are implanted with energy of 710 KeV graphite ions for four fluences ranging from 26 × 1012 to 92 × 1015 ions/cm2, in presence of magnetic field of strength 90 mT. The digital optical analysis reveals well-arranged dendritic and island like structure formation on irradiated polymer surface. Confocal microscopic investigation illustrates the growth of nano/micro sized craters and hillocks for various ion fluences. Dissociation of bonds along with formation of new bonds is confirmed from Raman analysis. UV–Vis spectral analysis reveals that the optical transmittance values for visible regions of CR-39 are drastically reduced from 90 % to 68 % for maximum laser fluence of 92 × 1015 ions.cm−2. Significant improvement in electrical conductivity is achieved from 10−9 to 10−7 Scm−1 for lowest fluence value of graphite ions. SRIM software is utilized for the measurement of stopping power or Linear Energy Transfer (LTE) of 710 Kev graphite ions, is about, 55.53 eV/Ǻ, in the CR-39 targets.

In the growing field of biotechnology, artificial intelligence (AI) has emerged as a pivotal force of innovation, unveiling a new era of discovery and advancement. The convergence of AI with biotechnology has revolutionized the landscape of scientific research and development. The dynamic interplay between AI and biotechnology highlights the transformative power of AI techniques in accelerating advancements in drug discovery, development, personalized medicine, biomolecular engineering, bioprocessing, CRISPR technology, genome editing, genomics, proteomics, metabolomics, transcriptomic, and AI-enabled robotics in biotechnology. This integration of AI with biotechnology helps us combat global challenges and offers environmentally friendly and sustainable solutions like bioremediation, bioplastics, biodiesel, and biofiltration. Current examples of these problems include waste management, air pollution, healthcare, clean water, energy access, sustainable practices, conservation of biodiversity, and ecosystems. This review article provides a comprehensive analysis, drawing on current literature, case studies, and emerging trends, to highlight the transformative potential of AI in reshaping the biotechnological landscape. It also addresses the challenges and opportunities associated with this AI-powered transformation, discussing future directions, ethical considerations, and the need for human-AI collaboration to ensure responsible and sustainable progress for a brighter future.

In the quest to mitigate excessive CO2 emissions, the electrochemical reduction of CO2 (eCO2R) into multi-carbon fuels and vital chemical precursors emerges as a compelling strategy. Meticulous control of the C–C coupling on a catalyst surface is a grand challenge in the selective production of desired C2+ products. Ethane and propanol are among the most desirable C2+ products in the gas and liquid phase, respectively. Herein, we demonstrate facile femtosecond laser-enabled tuning of Cu selectivity towards ethane and propanol. The laser-enabled tailoring of the Cu surface induces a shift from C1 products to ethane and propanol. This shift in product composition is attributed to the concurrent creation of hierarchical porous structures, the stabilization of {111}, {200}, and {220} Cu2O facets, and the promotion of the Cu1+ oxidation state. These alterations collectively enhance the adsorption strength, leading to an increased propensity for C-C coupling and, consequently, an elevated selectivity toward C2+ products.

IoT devices or sensor nodes are essential components of the machine learning (ML) application workflow because they gather abundant information for building models with sensors. Uncontrollable factors may impact this process and add inaccuracies to the data, raising the cost of computational resources for data preparation. Choosing the best method for this data pre-processing stage can lessen the complexity of ML models and wasteful bandwidth use for cloud processing. Devices in the IoT ecosystem with limited resources provide an easy target for attackers, who can make use of these devices to create botnets and spread malware. To repel attacks directed towards IoT, robust and lightweight intrusion detection systems are the need of an hour. Furthermore, data preprocessing remains the first step for modish machine learning models, ensemble techniques, and hybrid methods in developing anti-intrusion applications for lightweight IoT. This article proposes a novel data preprocessing model as a core structure using an Extra Tree classifier for feature selection and two classifiers LSTM and 1D-CNN for classification. The dataset used in this research is CIC IoT 2023 with 34 attack classes and SMOTE (Synthetic Memory Oversampling Technique) has been used for class balancing. The article evaluates the performance of 1D-CNN and LSTM on the CIC IoT 23 dataset using classification metrics. The proposed ensemble approach using LSTM has obtained 92% accuracy and with 1D-CNN the model obtained 99.87% accuracy.

A particularly useful assessment tool for evaluating uncertainty and dealing with fuzziness is the Fermatean fuzzy set (FFS), which expands the membership and non-membership degree requirements. Distance measurement has been extensively employed in several fields as an essential approach that may successfully disclose the differences between fuzzy sets. In this article, we discuss various novel distance measures in Fermatean hesitant fuzzy environments as research on distance measures for FFS is in its early stages. These new distance measures include weighted distance measures and ordered weighted distance measures. This justification serves as the foundation for the construction of the generalized Fermatean hesitation fuzzy hybrid weighted distance (DGFHFHWD) scale, as well as the discussion of its weight determination mechanism, associated attributes and special forms. Subsequently, we present a new decision-making approach based on DGFHFHWD and TOPSIS, where the weights are processed by exponential entropy and normal distribution weighting, for the multi-attribute decision-making (MADM) issue with unknown attribute weights. Finally, a numerical example of choosing a logistics transfer station and a comparative study with other approaches based on current operators and FFS distance measurements are used to demonstrate the viability and logic of the suggested method. The findings illustrate the ability of the suggested MADM technique to completely present the decision data, enhance the accuracy of decision outcomes and prevent information loss.

Availability of smooth power supply for the industrial and residential consumption is a major resource that assists the economic and social development of a nation. Automation and intelligent systems are energy intensive and the adequate electricity is required in order to operate such systems. However, there are electricity generation and distribution challenges in most of the developing countries as a result of disparity in the energy supply & demand and the absence of improved infrastructure. Pakistan being the 5th most populated developing country has the substantial demand of energy, accounting for 56% of total generation whereas thermal energy accounts for 61% of all electricity generated in Pakistan. Therefore, it is required to look for the feasible alternate solutions to address these challenges by incorporating renewable energy and the net metering. In first phase of this study, a survey was conducted to collect the feedback from the photovoltaic (PV) consumers and in second phase, market assessment was performed and the electricity systems were designed & analyzed using cost benefit analysis to measure the financial performance as well as carbon credits. Analysis was performed using Meteonorm, Google Maps and Helioscope Simulation software. Following the objective of this study, a self-sustaining power distribution system for a housing society using net metering is proposed to balance the energy production and consumption, combating greenhouse gases emissions from the energy produced by fossil fuels and to upgrade the existing electricity distribution system. The results indicate a remarkable performance of the centralized power distribution system. Till date, no specific study has proposed a sustainable centralized model for addressing energy issues as a self-sustaining power distribution system in a housing society. The proposed integrated model can aid in maximizing the use of PV system.

This paper proposes a new multi-objective stochastic market settlement model for a coupled energy and reactive power ancillary service, named as MOSMS-CERP model, for a prospective grid integration of wind energy. It is a comprehensive two-stage scenario-based stochastic optimization model to incorporate the system uncertainties associated with wind power generations along with load demands. In this multi-objective framework, two competing objective functions as the expected total payment functions for energy and reactive power ancillary services are simultaneously minimized while satisfying all the system operating constraints including technical as well as market driven constraints. An efficient hybrid payment strategy is designed for energy market as well as reactive power ancillary service market for creating a competitive and fair market auction. A pay-as-bid payment mechanism is adopted for all thermal generating units whereas a pay-at-MCP (Market Clearing Price) is adopted for all hydro-powered generating units and wind farms for the energy market settlement. However, the ancillary service market of reactive power is settled using uniform price payment mechanism. It is a unique market settlement model, which combines three significant complexities such as stochastic nature, multi-objective constrained optimization, and meta-heuristics. The proposed MOSMS-CERP model is examined by applying five well-known, recent, and advanced meta-heuristic methods such as Non-dominated Sorting Genetic Algorithms (NSGA-II & I-NSGA-III), Multi-Objective Keshtel Algorithm (MOKA), Hybrid Fuzzy Multi-Objective Evolutionary Algorithm (HFMOEA), and Multi-Objective Particle Swarm Optimization (MOPSO) for producing the sets of Pareto-optimal solutions. A fair statistical comparison is carryout for these five meta-heuristic methods based on No Free Launch Theorem. All simulations are conducted on a standard IEEE 24-bus RTS with a doubly fed induction generator (DFIG) based wind farm on a DIgSILENT Power Factory software platform. The obtained simulation results ensure the robustness and effectiveness of the proposed MOSMS-CERP model.

Increasing food production is crucial for attaining the Sustainable Development Goal (SDG#2) by 2030 through supplying agricultural credit and improved inputs. Thus, the present study examined the roles of agricultural credit, applications of fertilizer, usage of pesticides, farming area, and agricultural employment in enhancing wheat production in the developing economy (Pakistan) from 1990 to 2020. This study applied the autoregressive distributed lag (ARDL) regression method for the empirical analysis. The empirical findings from the ARDL regression technique revealed that agricultural credit can significantly enhance wheat production, while improved inputs, including fertilizer and pesticide usage, also positively contribute to wheat production. Notably, agriculture credit plays a vital role in assisting farmers to purchase advanced farm inputs and indirectly increases the wheat yield. Consequently, this study suggests that the banking sector should supply agricultural credit to farmers under flexible lending conditions; therefore, farmers can easily access credit and adopt modern technologies to enhance food production and ensure food security.

Introduction: Flow dynamics due to the peristaltic pumping has been the topic of great interest for the researchers. But numerical and analytical analyses for the peristaltic motion are limited where flow domain is deformed real-time. Research on peristalsis has a limitation where theoretical aspects of walls motion are considered, neglecting the real time deformation of the walls.Objectives: This paper aims to propose a more reliable and accurate numerical methodology for peristaltic motions to address the above-mentioned challenge. Stream traces, velocities, and pressure drops along the tube is to be visualized more accurately.Methods: In present study a finite volume based dynamic mesh motion method is adopted to analyze the peristaltic motion of a non-Newtonian Quemada fluid in an axisymmetric channel. The walls and interior domain of the channel is dynamically deformed for a sinusoidal wave traveling on boundary.Results: Simulation of unsteady flow behavior for time t=0s to 2s and amplitude ratio Φ=0.2,0.4,and0.6. predicts fluid trapping phenomenon. Rotation of fluid particles is more prominent for higher amplitude ratios. Pressure gradient increases with increasing amplitude ratios.Conclusion: A novel dynamic mesh method is proposed for peristaltic pumping. It provides more accurate and more physical results for stream traces; pressure drops and velocities along the tube. A limited case of the study validates the theoretical and analytical results already presented in literature; hence the method is reliable.

Morphology is broader field of linguistics that studies the structure of words, forms of words and word-formation processes (Zeller, 2001; Zahid, A., 2016). Morphology studies morphemes (the smallest meaningful units of words) and how these morphemes shape words into different grammatical categories and meanings. The current study aims to explore the properties of Balochi verbs in Makrani dialect, and it also tries to find how these morphemes change the form and meaning of the verbs. The current study’s main concern is to analyse and investigate the properties of Balochi morphemes and to find out how these morphemes change the meaning and form of the verbs. For this study, the data have been collected through unstructured interviews from the native participants of Balochi (speaking the Makrani dialect). The data have been analyzed through Radford’s (2009) “theory of agreement”. The study finds that Balochi, being a pro-drop language, works like English and other languages of the world where subject agrees with verb and verb with its subject. It is also found that verbs in Balochi have various properties and these properties are generalized by tense, number, mood, voice, and person.

Abstract Public health emergency management systems encountered difficulties in developing countries, especially in Pakistan. The COVID-19 pandemic was extremely challenging for different agencies/departments in Pakistan. Health emergency management depends on a well-established public health emergency operations center that could generate a coordinated response to emergencies. We conducted an assessment of public health emergency response coordination implemented during the COVID-19 at strategic level. This was mix-method qualitative study. Primary data was collected by using a structured questionnaire, and secondary data was collected by desk review. The agencies engaged in pandemic response at the national level in Pakistan were included in the assessment. The overall score of the emergency response coordination system during COVID-19 was 49% for all agencies. We found that agencies faced challenges in leadership, legislation, and financing issues during the pandemic response (44%). None of the agencies had a fully developed framework for joint planning and response system for health emergencies. Roles and responsibilities attached to designated agencies in response were relatively clear (55%) for most of the agencies. Effective public health emergency response is based on multi-departmental coordination, resource mobilization, and clear roles for each agency. Pakistan must proactively address these challenges for pandemic response in future.

Despite development, the present and prospects of olive cultivation in Pakistan are progressive in every aspect; people use olive oil and olive-based products not only for their food and nutritional values but also for their religious importance. With an annual expenditure of approximately 4.5 billion dollars on edible oil imports, Pakistan initiated olive production ventures in collaboration with Italy, Spain, and China to curtail import costs and attain self-sufficiency. The olive farming potential of Pakistan has been recognized due to more than 8 million wild olive plants and suitable land and climate conditions in various regions of KPK, Balochistan, and Punjab. Along with grafting millions of wild olive trees, about 5 million new plants have grown in the past few years, and still, more than 10 million acres of suitable land are available. The establishment of new olive processing mills, the “50 Million Olive Tree Tsunami” project, and the “Promotion of Olive Cultivation for Economic Development and Poverty Alleviation' project have been instrumental in expanding olive cultivation, augmenting production capacity, generating employment opportunities, and addressing poverty. However, there is still a dire need to mitigate the challenges and needs within the olive sector, which include awareness and training among farmers, infrastructure improvement, adequate storage and packaging facilities, standardized quality testing, and competitive pricing. The lack of interest from local vendors and food processing companies, along with financial constraints faced by farmers, poses additional hurdles. Recommendations to address these challenges include prioritizing training programs, conducting surveys for data collection, increasing awareness of the health benefits of olive oil, and establishing loan schemes and private-sector investments. Encouraging the local production of olive oil extraction machinery and upgrading technology can help reduce reliance on imports. These measures collectively aim to propel Pakistan toward becoming a significant player in the global olive production landscape.

The mandatory carbon reduction guidelines and regulations in Indonesia encourage all industrial sectors particularly the petroleum industry to implement decarbonization programs by systematically reducing carbon emissions as part of climate action. Unlike existing carbon emission studies in the petroleum industry, the literature lacks studies on the decarbonization patterns. In addition, the effectiveness of carbon mitigation in the upstream oil and gas field has not been studied so far. This study developed short panel data models to understand the current decarbonization efforts and patterns during 2015–2018. The results indicate that the considered variables are significantly impactful in carbon reduction with different coefficient patterns. It is suggested to associate decarbonization with oil and gas production and highlight energy efficiency optimization to stabilize production. The impact of financial, human, and administrative resources on the supporting facility is critical for executing sustainable carbon mitigation projects.

Study region: Beijing Region Study focus: Limited studies have yet been done on regionalization of multi-performances of rainwater harvesting systems (RHS). In this study, the daily rainfall records from 77 stations are used, and a hydro-economic model is adopted to examine regional water saving, stormwater control and economic performances of RHS by proposing a regionalization approach. New hydrological insights for the region: Higher water saving efficiency (WSE) and reliability (R) of RHS are linked with lower water demand, larger tank size and greater rainfall conditions. Differently, higher stormwater capture efficiency (SCE) is related to higher water demand, larger tank size and lower rainfall. The WSE and R of RHS demonstrate substantial regional differences; their maximized obtainable values closely depend on water demand scenarios and range from 9% to 99%, with smaller values in western mountain area but larger values in northeast suburban and central urban areas. The maximum obtainable values of SCE range from 61% to 100%, with higher values in western mountain area, but lower values in northeast suburban and central urban areas. A 10 m3 tank size can provide the highest benefit-cost ratio of RHS across the Beijing region. The regionalization approach proposed is a useful guidance for the implementation of RHS and sustainable urban water management, and thus it has the potential for wide uses in other regions with high rainfall gradients.

Artificial neural networks, deep learning and machine learning are versatile data-driven tools widely applied in different disciplines such as finance, image and voice recognition, and earth science. For scientists and enthusiasts (including those not very experienced with programming), there is a need for easy-to-use and fast-to-setup tools that enable users to prototype and focus on the research part quickly rather than spending time on data preparation, on extracting features and setup multiple experiments for training and validating models. In this paper, we introduce Kit4DL, which is a Python package to speed up the experimentation process of machine- and deep-learning by using just a single TOML configuration file, allowing a user to set up all aspects involved in training and validation. Though simple to use in its default mode, the proposed package enables high customisation possibilities for more experienced users. Kit4DL streamlines the deep learning development process by simplifying the creation of the entire training, validation, and testing loop. Users only need to implement a few core methods outlined in a provided configuration file, significantly reducing development time compared to traditional approaches requiring from a user to implement all procedures him/herself. Additionally, Kit4DL facilitates code reusability by allowing researchers to leverage the same codebase across multiple experiments, reducing redundancy and streamlining the experimentation process.

Blood flow analysis plays an essential role in understanding cardiovascular health and disease. An accurate mathematical modeling is necessary in context of representation of arterial domains and blood flow to learn about the intricate blood dynamics. In this paper we concentrate on the mathematical representation of the geometry of the blood artery and find numerical solutions with mild to severe degree of stenosis. Blood dynamics has steady state, in-compressible and laminar nature. The shear thinning non-viscous effects of blood are assumed to obey Carreau model. Fluid flow is based on coupled Navier-Stokes equation in three dimensions and is simulated with finite volume approach over hexahedral elements. Application of a constant mass flow rate at the inlet of the artery results in a number of observations to analyze. It is found that with increasing the severity of stenosis, blood velocity becomes higher in stenotic region, pressure drop along the arterial domain is increased and shear stresses exerted by blood on walls of artery are increased.

Introduction: The coagulation profile of cardiac surgery patients is impacted by pro-inflammatory effects caused by procedures involving cardiopulmonary bypass. In order to counteract these effects, pharmacological therapies and allogeneic blood transfusions are required. The strategy of Acute normovolemic hemodilution also known as “intraoperative autologous donation” is also a viable option to address these negative effects. The theoretical basis for ANH is that the removed blood of a patient’s own self is shielded from the inflammatory response of blood cells to the bypass circuit. ANH is an infrequently practiced strategy at various cardiac surgery institutes within Pakistan to enhance coagulation profile, decrease the need for blood transfusions despite being an established approach abroad. Aims and Objectives: The objective of our study is to compare the effect of ANH on patients undergoing adult cardiac surgery in a sample group versus a control group with the primary endpoint of postoperative drain output as a measure of effectiveness of blood coagulation profile. Blood coagulation profiles were also compared between the two groups as secondary variables. Place and Duration of study: The study was conducted at the Faisalabad Institute of Cardiology from December 21st, 2023 to February 13th, 2024. Material and Methods: A randomized controlled trial involving 60 patients over the age of 12 years who were to undergo adult cardiac surgery was conducted. An online research randomizer software randomly selected them into two equal groups, sample and control (n=30). The ANH volume retrieved from the patient's central vein in the sample group was used to fill the CPD blood transfusion bags after administering anesthesia. After the patients in both groups were weaned off CPB and protamine administered to neutralize heparin, ANH blood was infused back into the patients in the sample group whereas the control group received allogenic blood only. Chi square test was applied to all qualitative variables and Independent Samples t-test for all quantitative variables. The results were analyzed using SPSS version 25, and a p-value ? 0.05 was considered statistically significant. Results: Hemoglobin (12.9±0.90 g/dL in ANH and 11.8±1.00 g/dL in non-ANH) and aPTT levels (34.2±6.06 seconds in ANH and 54.2±10.95 seconds in non-ANH) were statistically significant (p-value

This study conducted a bibliometric analysis of the literature on sustainable project management in crisis management, particularly in humanitarian disasters, using the Scopus database. After filtration and abstract screening of 115,737 (1980–2022), only 544 related articles were identified and analyzed graphically using VoSviewer (visualization of similarities) to create maps of co-occurrence, co-authorship, and citations. The analysis provided an understanding of the most frequent keywords, key authors, journals, affiliations, and contributing countries in the literature on project management and crisis management. The trends observed in this study’s results highlight the significance of sustainable project management within the realm of disaster management. This study examines the bibliometric parameters and indices as measures of research success and their potential implications for grant funding sources, universities, governments, and organizations. The findings suggest that bibliometric parameters and indices could be increasingly utilized by grant funding sources as metrics to evaluate research success. Universities and research institutions may consider incorporating benchmarking standards based on bibliometric data into promotion and tenure guidelines to determine academic achievement. Furthermore, governments and organizations may also benefit from establishing benchmark standards to enhance sustainability in disaster management projects. Although Scopus has limitations that prefer certain fields, this study provides avenues for future research, including using other databases and conducting a comparative study between Scopus and WoS (Web of Science) to determine their strengths and weaknesses.

Natural gas and condensate are exposed to hydrates formation at high pressure and low temperature in the presence of traces of water. Hydrates formation results in blockage of pipelines and equipment leading to plant shutdown and production losses. This study intends to find a novel hydrate prevention process for high pressure refrigerated condensate (HPRC) lines. HPRC is utilised as lean oil for enhanced liquified petroleum gas recovery in absorption process. This research was conducted by performing fifteen tests in which various processed natural gas (PNG) samples were injected into different HPRC samples using Aspen HYSYS software. The results showed lowering of the hydrates formation temperature in the HPRC at constant pressure. By capitalizing on in-house resources and reducing dependence on traditional hydrate inhibitors, this innovative approach offers cost-effectiveness and readily available hydrate inhibitor for HPRC lines in gas processing facilities. Moreover, it has been found that PNG samples with a relatively higher percentage of methane are more effective in lowering the hydrate formation temperature when injected into the HPRC lines. This study will enable hydrates researchers in reducing hydrates management costs in HPRC lines and invite hydrates prevention research in all areas capitalizing on in-house resources and reducing external dependence.

Evaluating the potential impacts of land use and land cover change (LULCC) and climate change on air pollution is crucial to unravel the driving forces and mechanisms behind changes in air quality. A multi-faceted approach was adopted, including a land change model (LCM) and Mann–Kendall (MK) test, to evaluate the transition of land cover type, changes in climate, and atmospheric pollutants during 2004–2021 in Pakistan. Moreover, a multiscale geographically weighted regression (MGWR) model and a mathematical model were used to assess the potential contribution of LULCC and climate dynamics to atmospheric pollution. It was revealed that during 2004, croplands covered an area of 9.72 × 104 mile2, accounting for 38% of the total area. However, the area of the croplands increased to 10.1 × 104 mile2, accounting for 40% of the total area in 2021. The MK test showed that the north and west–south regions significantly experienced air pollution, with the increasing trend for nitrogen dioxide (NO2) and sulfur dioxide (SO2) being 0.89× 1015 molecules/cm2 per year and 0.54 DU/year, respectively. For climate variability, mean precipitation (Precp) and mean surface pressure (SP) showed a prominent increasing trend, with a maximum value of 1 mm/year and 0.01 Kpa/year, respectively. The mean temperature maximum (Tmax) showed an increasing and decreasing trend, with the highest value of 0.28°C/year and 0.08°C/year, respectively. In the context of contribution, the conversion of cropland to grasslands increased the trend for SO2 concentrations. The highest increasing trend of 1.5 DU for ozone (O3) was found due to conversion of grasslands to shrublands. Additionally, regional climate played a significant role in making air pollution stagnant across the country. Precp and wind speed (WS) contributed significantly in escalating NO2 concentrations in Pakistan, while Precp contributed most (0.004 DU) to increasing SO2 concentrations. For O3, the most influential climate factor was Precp. These results on a long-term temporal scale demonstrated how maintaining climate variability through comprehensive land use management can help improve ambient air quality in Pakistan.

Green synthesis of metal nanoparticles (NPs) has received extensive attention over other conventional approaches due to their non-toxic nature and more biocompatibility. Herein we report gold and silver NPs (AuNPs@AV and AgNPs@AV) prepared by employing a green approach using crude extract of Aconitum violaceum Jacquem. ex Stapf. The synthesized NPs were characterized using Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Energy Dispersive X-ray (EDX), X-ray Diffraction (XRD), UV/Visible spectroscopy, Fourier Transform Infrared (FTIR), X-ray Photoelectron Spectroscopy (XPS), and Zeta Potential. Morphological analysis showed spherical and triangular shapes of the NPs with average size of

Different from conventional educational paradigms, online education lacks the direct interplay between instructors and learners, particularly in the sphere of virtual physical education. Regrettably, extant research seldom directs its focus toward the intricacies of emotional arousal within the teacher-student course dynamic. The formulation of an emotion generation model exhibits constraints necessitating refinement tailored to distinct educational cohorts, disciplines, and instructional contexts. This study proffers an emotion generation model rooted in data mining of teacher-student course interactions to refine emotional discourse and enhance learning outcomes in the realm of online physical education. This model includes techniques for data preprocessing and augmentation, a multimodal dialogue text emotion recognition model, and a topic-expanding emotional dialogue generation model based on joint decoding. The encoder assimilates the input sentence into a fixed-length vector, culminating in the final state, wherein the vector produced by the context recurrent neural network is conjoined with the preceding word’s vector and employed as the decoder’s input. Leveraging the long-short-term memory neural network facilitates the modeling of emotional fluctuations across multiple rounds of dialogue, thus fulfilling the mandate of emotion prediction. The evaluation of the model against the DailyDialog dataset demonstrates its superiority over the conventional end-to-end model in terms of loss and confusion values. Achieving an accuracy rate of 84.4%, the model substantiates that embedding emotional cues within dialogues augments response generation. The proposed emotion generation model augments emotional discourse and learning efficacy within online physical education, offering fresh avenues for refining and advancing emotion generation models.

In text applications, pre-processing is deemed as a significant parameter to enhance the outcomes of natural language processing (NLP) chores. Text normalization and tokenization are two pivotal procedures of text pre-processing that cannot be overstated. Text normalization refers to transforming raw text into scriptural standardized text, while word tokenization splits the text into tokens or words. Well defined normalization and tokenization approaches exist for most spoken languages in world. However, the world’s 10th most widely spoken language has been overlooked by the research community. This research presents improved text normalization and tokenization techniques for the Urdu language. For Urdu text normalization, multiple regular expressions and rules are proposed, including removing diuretics, normalizing single characters, separating digits, etc. While for word tokenization, core features are defined and extracted against each character of text. Machine learning model is considered with specified handcrafted rules to predict the space and to tokenize the text. This experiment is performed, while creating the largest human-annotated dataset composed in Urdu script covering five different domains. The results have been evaluated using precision, recall, F-measure, and accuracy. Further, the results are compared with state-of-the-art. The normalization approach produced 20% and tokenization approach achieved 6% improvement.

BackgroundDiabetes mellitus (DM) is well known for related micro and macrovascular complications. Uncontrolled hyperglycemia in diabetes mellitus leads to endothelial dysfunction, inflammation, microvascular impairment, myocardial dysfunction, and skeletal muscle changes which affect multiple organ systems. This study was designed to take an extensive view of cardiorespiratory dynamics in patients with type 2 DM.MethodsOne hundred healthy controls (HC) and 100 DM patients were enrolled. We measured and compared the breathing patterns (spirometry), VO2 max levels (heart rate ratio method) and self-reported fitness level (international fitness scale) of individuals with and without diabetes. Data was analyzed in SPSS v.22 and GraphPad Prism v8.0.ResultsWe observed restrictive spirometry patterns (FVC ConclusionThis study shows decreased pulmonary functions, decreased cardiorespiratory fitness (VO2 max) and IFiS scale variables in diabetic population as compared to healthy controls which are also associated with glycemic levels and long-standing DM. Screening for pulmonary functions can aid optimum management in this population.