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Abstract Low oxygen stress (hypoxia) induced by submergence significantly impairs respiration in fruit trees, leading to reduced yield and, in extreme cases, tree mortality. While extensive research has focused on the root responses of peach trees to waterlogging, the mechanisms underlying leaf responses to complete submergence remain poorly understood. In this study, both transcriptomic and metabolic approaches were employed to explore the differential submergence tolerance between two peach cultivars: 'Dongxi Xiaoxian' (DX), which exhibits tolerance, and 'Hujing Milu' (HM), which is sensitive. Compared to HM, DX leaves experienced less decline in leaf verdancy, chlorophyll, and carotenoid content under submergence. DX leaves also showed enhanced antioxidant activities of ROS scavengers and reduced levels of H2O2 and MDA, correlating with improved tolerance. Transcriptomic analysis revealed significant alterations in the expression of genes involved in photosynthesis, glycan biosynthesis, and α-linolenic acid metabolism between the two cultivars. Key metabolites, including sugars (sorbitol and sucrose), amino acids (phenylalanine and L-norvaline), cell wall polysaccharides (lignin and pectin), and plant hormones (jasmonic acid and salicylic acid), were identified as critical for DX's superior submergence tolerance. These findings elucidate the mechanisms of peach leaf tolerance to submergence, providing insights into potential strategies for genetic improvement aimed at enhancing hypoxia resistance in fruit trees.

ABSTRACT Background The relentless integration of Artificial Intelligence (AI) into neurosurgery necessitates a meticulous exploration of the associated ethical concerns. This systematic review focuses on synthesizing empirical studies, reviews, and opinion pieces from the past decade, offering a nuanced understanding of the evolving intersection between AI and neurosurgical ethics. Materials and Methods Following PRISMA guidelines, a systematic review was conducted to identify studies addressing AI in neurosurgery, emphasizing ethical dimensions. The search strategy employed keywords related to AI, neurosurgery, and ethics. Inclusion criteria encompassed empirical studies, reviews, and ethical analyses published in the last decade, with English language restriction. Quality assessment using Joanna Briggs Institute tools ensured methodological rigor. Results Eight key studies were identified, each contributing unique insights to the ethical considerations associated with AI in neurosurgery. Findings highlighted limitations of AI technologies, challenges in data bias, transparency, and legal responsibilities. The studies emphasized the need for responsible AI systems, regulatory oversight, and transparent decision‐making in neurosurgical practices. Conclusions The synthesis of findings underscores the complexity of ethical considerations in the integration of AI in neurosurgery. Transparent and responsible AI use, regulatory oversight, and mitigation of biases emerged as recurring themes. The review calls for the establishment of comprehensive ethical guidelines to ensure safe and equitable AI integration into neurosurgical practices. Ongoing research, educational initiatives, and a culture of responsible innovation are crucial for navigating the evolving landscape of AI‐driven advancements in neurosurgery.

Abstract Background and Objectives: Medication safety is critical for pediatric cardiac care, especially in low- and middle-income countries (LMICs), where limited resources contribute to high rates of medication errors. Studies in LMICs have shown that pharmacist interventions can reduce medication errors by up to 57% and proved that clinical pharmacists are essential for ensuring accurate and optimized medication use. This study aims to evaluate the role of clinical pharmacist interventions to rectify prescription errors in a pediatric cardiac care setting in Pakistan. Methods: This single-center retrospective study was conducted from January to August 2022 in a pediatric cardiac ward at the National Institute of Cardiovascular Diseases. Pediatric patients of all age groups and genders diagnosed with acquired, inherited, or congenital heart diseases were included. We reviewed patient files for any prescription changes made by the clinical pharmacist, based on a comprehensive review of the patient profile, treatment regimens, and laboratory results, to ensure safe and effective pharmacotherapy. Results: 260 pharmacist interventions were observed among 2754 patients over eight months, demonstrating a significant role in mitigating medication errors. The interventions addressed wrong doses (126), incorrect frequencies (101), redundant coverage (23), and therapy duration errors (8). Antibiotics were the most frequent source of prescription errors, accounting for 81% of the interventions. Conclusion: Clinical pharmacists’ involvement in pediatric cardiac care significantly reduces medication errors in LMICs, as demonstrated by this study. These findings underscore the need to integrate clinical pharmacists into multidisciplinary teams to enhance medication safety and improve patient outcomes.

Background: Inguinal hernia repair is a common surgical operation being performed worldwide, and the primary objective of hernia repair is to reduce recurrence, minimize complications, and robust recovery. This systematic review and meta-analysis reviewed and compared two widely used surgical techniques: the Trans-abdominal Pre-peritoneal (TAPP) repair, a minimally invasive laparoscopic surgical technique, and the Lichtenstein operation, which is an open repair. Methods: A thorough search was conducted across several databases, including PubMed, Cochrane Library, Google Scholar, and Web of Science, from 2004 to August 2024. We searched a combination of keywords and medical subject-related headings related to "trans abdominal Pre-peritoneal," "TAPP Surgical Technique," "Lichtenstein open repair operation," "primary inguinal hernia," and "randomized controlled trials (RCTs)." Studies included in the meta-analysis were grouped based on the primary outcomes of interest to elaborate a comprehensive analysis. In addition to the surgical operation and hospital stay duration, acute post-operative pain, return to work time, hematoma, wound infection, and seroma incidence were also measured. The Randomized controlled trials (RCTs) comparing TAPP and Lichtenstein operations for primary inguinal hernia repair and studies reporting on at least one of the above-mentioned outcomes were included. The studies with patients having incarcerated hernia, femoral or bilateral hernias were excluded. The risk of bias for included studies was assessed using the Cochrane Risk of Bias tool and sed on odds ratios (ORs), standardized mean differences (SMDs) and confidence intervals (CIs), a quantitative meta-analysis study was conducted. Results: Nine Randomized Controlled Trials (RCTs) comparing the TAPP and Lichtenstein technique for primary inguinal hernia repair were included in the meta-analysis. The duration of the surgical procedure was longer in the TAPP group (46.3 to 96.12 minutes), compared to the Lichtenstein group (27.8 to 54.2 min). In terms of acute post-operative pain, the TAPP group reported lower pain scores (mean: 5.66) compared to the Lichtenstein group (mean: 8.53). The overall complication rate was lower for the TAPP group (Odds Ratio = 0.461) as compared to Lichtenstein repair. Conclusion: The meta-analysis concluded that TAPP tops out with benefits like less post-operative pain and a robust recovery period. However, the Lichtenstein technique remains a widely used option, especially in settings where access to advanced Laparoscopic facilities and expertise might not be available.

Spiders contribute significantly to natural pest control in agriculture. Here, we investigated the biodiversity, population dynamics and predatory activities of spiders in the maize-growing districts (Kasur and Lahore) of Punjab, Pakistan during 2018–2019. Various collecting methods including pitfall and yellow pan traps, manual hand-picking, beat sheet, and sweep nets were used to collect spiders on a biweekly basis. The collected 12,894 individuals represented 45 different species, 27 genera, and 13 families. The major families recorded were Araneidae (32.92%), Lycosidae (20.43%) and Salticidae (11.12%) comprising >64% of the overall abundance. Neoscona theisi (Araneidae) was found to be most dominant species (11.61%). Moreover, the species Macracantha hasselti (Araneidae) and Atypena formosana are reported for the first time from Pakistan. Besides, the estimated species diversity from both districts was 97%. The Margalef's index was highest in Kasur (D = 5.08) and lowest in Lahore (D = 4.95). The values of the Shannon-Wiener and species evenness indices were similar in Kasur and Lahore suggesting similar diversity levels and an even distribution. Spider abundance was highest in April and lowest in June and July. These findings will help to develop effective Integrated Pest Management strategies in maize growing areas across the world.

The emergence of tick resistance against synthetic and eco-toxic chemical acaricides has stressed the need to find target-specific, non-toxic, and more potent alternatives such as botanicals. The current study was designed to investigate the acaricidal and repellent potential of ethyl acetate extract of Moringa oleifera seeds against Rhipicephalus microplus cattle ticks. Adult immersion test, larval immersion test, and tick climbing repellent assay were carried out to evaluate the acaricidal and repellent potential of M. oleifera extract. Five different concentrations (20, 10, 5, 2.5, and 1.25 %) of the ethyl acetate extract of M. oleifera were prepared to evaluate the acaricidal and repellent potential. Different parameters like adult tick mortality, larval mortality, egg hatchability, inhibition of egg hatchability, oviposition reduction, reproductive index, reproductive efficiency index, tick repellency, and product effectiveness were determined. Ethyl acetate extract of M. oleifera showed 70% adult mortality after 24 h treatment when 20% concentration was used. Similarly, 73% larval tick mortality was observed at 20% concentration. The results also showed the dose-dependent response of ethyl acetate extract of M. oleifera seeds against egg hatchability, inhibition of egg hatchability, oviposition reduction, reproductive index, reproductive efficiency index, and tick repellency, confirming that 20% concentration is effective as an acaricide and repellent against R. microplus. Therefore, the tested extract can be considered a possible candidate for controlling R. microplus in cattle.

In data-scarce regions, prudent planning and precise decision-making for sustainable development, especially in agriculture, remain challenging due to the lack of correct information. Remotely sensed satellite images provide a powerful source for assessing land use and land cover (LULC) classes and crop identification. Applying remote sensing (RS) in conjunction with the Geographical Information System (GIS) and modern tools/algorithms of artificial intelligence (AI) and deep learning has been proven effective for strategic planning and integrated resource management. The study was conducted in the canal command area of the Lower Chenab Canal system in Punjab, Pakistan. Crop features/classes were assessed using the Normalized Difference Vegetation Index (NDVI) algorithm. The Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m and Landsat 5 TM (thematic mapper) images were deployed for NDVI time-series analysis with an unsupervised classification technique to obtain LULC classes that helped to discern cropping pattern, crop rotation, and the area of specific crops, which were then used as key inputs for agricultural mechanization planning and resource management. The accuracy of the LULC map was 78%, as assessed by the error matrix approach. Limitations of high-resolution RS data availability and the accuracy of the results are the concerns observed in this study that could be managed by the availability of good quality local sources and advanced processing techniques, that would make it more useful and applicable for regional agriculture and environmental management.

With the global population surpassing 7.9 billion, sustaining food production poses a formidable challenge, heavily reliant on groundwater for irrigation, particularly in regions with limited surface water. Concerns over groundwater sustainability are mounting as agricultural dependence grows, highlighting the need for robust management strategies to ensure long-term viability. The unchecked extraction of groundwater poses a threat to agricultural productivity, as excessive withdrawal leads to aquifer depletion and reduced water availability for irrigation. Numerous studies, including those conducted by organizations like the Food and Agriculture Organization (FAO) and the World Bank, underscore the detrimental effects of over-extraction on crop yields, food security, and agricultural expansion efforts. Furthermore, the depletion of groundwater exacerbates water scarcity, driving up food prices and jeopardizing dietary diversity and nutritional intake. Despite these challenges, groundwater remains indispensable for global food security, supporting approximately 60% of irrigated agriculture worldwide. In regions susceptible to climate variations and water scarcity, groundwater serves as a reliable irrigation source, enabling year-round crop cultivation and sustaining livelihoods. However, sustainable groundwater management is imperative to mitigate the risks of over-extraction, aquifer depletion, and environmental degradation. Pakistan exemplifies the intricate relationship between groundwater and agricultural sustainability. The nation’s irrigation system heavily relies on diverse water resources, including the Indus River System and groundwater extracted through tube wells. While these resources bolster agricultural productivity and contribute significantly to the economy, challenges such as water scarcity and inefficient usage threaten their sustainability. Addressing these challenges requires a concerted effort to implement sustainable water management practices, enhance infrastructure, and mitigate the impacts of climate change. Amidst these challenges, the development of the Groundwater Irrigation Advisory Application (GIAA) emerges as a potential solution. By providing real-time groundwater monitoring, tailored irrigation schedules, and educational support, GIAA empowers farmers to make informed decisions regarding water usage, ultimately contributing to sustainable groundwater management and global food security. However, the successful implementation of GIAA necessitates collaboration among stakeholders, continuous updates, and a commitment to integrating new features and technological advancements. In this context, this paper explores the development, functionality, and potential impact of GIAA on sustainable groundwater management, agricultural productivity, and food security. Through a comprehensive analysis of its features, benefits, and limitations, this study aims to elucidate the role of GIAA in safeguarding groundwater resources and ensuring the resilience of agricultural systems in an era of increasing water scarcity and climate uncertainty.

Background: Although Dengue fever is affecting various tropical and sub-tropical regions but it is common disease in Pakistan at time of floods. It can be easily managed with appropriate knowledge of disease and preventive measures only.Objective: To estimate knowledge perception and prevention awareness of individuals with respect to sociodemographic characteristics towards Dengue fever. Study type, settings & duration: This cross-sectionalstudy was conducted at Shaheed Zulfiqar Ali Bhutto Medical University, IslamabadfromFebruary to April 2023. Methodology: Close-Ended structured questionnaire with non-probability convenience sampling was used, where 384 participants belonged to age groups between 15–60 years. Total 25 questions were employed to calculate disease knowledge whereas 11 Questions to investigate prevention awareness. Chi-Square Test was used to evaluate categorical values and their association was estimated with p-value

The ever-growing volume of global electronic waste (e-waste) poses significant environmental and health challenges. Printed circuit boards (PCBs), which form the core of most electronic devices, contain valuable metals as well as hazardous materials. The efficient disassembly and recycling of e-waste is critical for both economic and environmental sustainability. The traditional manual disassembly methods are time-consuming, labor-intensive, and often hazardous. The integration of edge computing and the Internet of Things (IoT) provides a novel approach to automating the disassembly process, potentially transforming the way e-waste is managed. Automated disassembly of WPCBs involves the use of advanced technologies, specifically edge computing and the IoT, to streamline the recycling process. This strategy aims to improve the efficiency and sustainability of e-waste management by leveraging real-time data analytics and intelligent decision-making at the edge of the network. This paper explores the application of edge computing and the IoT in the automated disassembly of WPCBs, discussing the technological framework, benefits, challenges, and future prospects. The experimental results show that the YOLOv10 model achieves 99.9% average precision (AP), enabling accurate real-time detection of electronic components, which greatly facilitates the automated disassembly process.

Wheat Stripe Rust Disease (WRD) poses a significant threat to wheat crops, causing substantial yield losses and can result in total crop damage if not detected early. The localization of WRD-infected areas is a labor-intensive and time-consuming task due to the intricate and varied nature of the disease spread, especially for large plantations. Hence, segmentation of wheat crops is vital for early identification of the WRD-affected area, which allows for the implementation of targeted intervention measures. The state-of-the-art segmentation technique for WRD using the real-world semantic segmentation NWRD dataset is based on a UNet model with the Adaptive Patching with Feedback (APF) technique. However, this implementation is complex and requires significant resources and time for training due to the processing of each patch of the dataset. Our work in this paper improves the state-of-the-art by using a two-stage model: a Vision Transformer (ViT) classifier to distinguish between the rust and non-rust patches and a less complex co-salient object detection (Co-SOD) model for segmentation of the classified images. The Co-SOD model uses multiple rust patches to extract contextual features from a group of images. By analyzing multiple patches of wheat rust disease simultaneously, we can segment disease regions more accurately. Our results show that the proposed approach achieves a higher F1 score (0.638), precision (0.621), and recall (0.675) for the rust class with 5× less training time as compared to the previous works.

Cassava is the sixth most important food crop worldwide and the third most important source of calories in the tropics. More than 800 million people depend on this plant’s tubers and sometimes leaves. To protect cassava crops and the livelihoods depending on them, we developed a stochastic fractional delayed model based on stochastic fractional delay differential equations (SFDDEs) to analyze the dynamics of cassava mosaic disease, focusing on two equilibrium states, the state of being absent from cassava mosaic disease and the state of being present with cassava mosaic disease. The basic reproduction number and sensitivity of parameters were estimated to characterize the level beyond which cassava mosaic disease prevails or declines in the plants. We analyzed the stability locally and globally to determine the environment that would ensure extinction and its persistence. To support the theoretical analysis, as well as the reliable results of the model, the present study used a nonstandard finite difference (NSFD) method. This numerical method not only improves the model’s accuracy but also guarantees that cassava mosaic probabilities are positive and bounded, which is essential for the accurate modeling of the cassava mosaic processes. The NSFD method was applied in all the scenarios, and it was determined that it yields adequate performance in modeling cassava mosaic disease. The ideas of the model are crucial for exploring key variables, which affect the scale of cassava mosaic and the moments of intervention. The present work is useful for discerning the mechanism of cassava mosaic disease as it presents a solid mathematical model capable of determining the stage of cassava mosaic disease.

Global literature highlights risks in the seafood trade and suggests mitigation methods, but these issues are often overlooked in developing countries, particularly in Pakistan, due to ineffective policy implementation. This underlines the urgent need for a thorough investigation into Pakistan’s seafood trade to address its multifaceted risks and revive this agricultural sector. This study is notable for being the first to explore these uncharted risks in Pakistan’s seafood trade, which can help achieve the sustainable development goals (SDGs) of the United Nations, particularly SDG 14 (life underwater) and SDG 2 (zero hunger). Primary data were gathered from 626 respondents using snowball sampling and structured questionnaires from July 13, 2023, to December 27, 2023. The study used multi-criteria decision analysis, including fuzzy Analytic Hierarchy Process (AHP) and Importance Performance Analysis (IPA), and multivariate analysis, comprising Analysis of Moment Structures (AMOS), to analyze the data. The findings revealed that ‘environmental risks’ were the most significant, followed by ‘infrastructure and logistic risks’. The biggest sub-risk identified for managerial focus includes overfishing. Controlling overfishing is critical for ensuring marine conservation and reviving the seafood trade. Several sub-risks, like seafood prices, marketing strategies, consumer preferences, and tastes, are critical but never addressed in the regulations. Furthermore, risk perception mediates the relationship between risk management and risk performance. The survey respondents reported low-risk perception and inadequate management measures. Besides, this study expounds on ramifications, shortcomings, and areas for further research.

Introduction. Cranioplasty is a standard neurosurgical procedure these days where surgeons repair a defect or deformity of a skull. This procedure can lead to fatal experiences after surgery. We encounter a similar experience we want to share. Case report. we present a case of 37 years 37-year-old patient who developed epidural fluid collection after cranioplasty. The patient deteriorated after surgery which we managed carefully and recovered later. Conclusion. Post-cranioplasty patients should be under observation and neurological deterioration should be kept in mind. Surgical intervention is not always needed and can be managed conservatively.

This research evaluates the impact of investing in cleaner bonds on funding clean energy initiatives, pivotal for sustainable economic recovery. The study seeks to assess the efficacy of cleaner bonds in fostering environmentally friendly projects and propelling economic growth and applies fuzzy analytical hierarchy process to examine the findings. Findings suggest that cleaner bonds potentially increase clean energy expenditures by an average growth rate of 4.9 % per year, significantly enhancing economic resilience. Additionally, these bonds are shown to accelerate the revitalization of green economies by approximately 17 % annually. The research underscores the role of energy performance contracts as viable alternatives to conventional project financing, through the application of various modelling tools and fuzzy analyses. It also discusses the strategic allocation of public and private funds into cleaner bond investments to accelrate economic sustainability and energy conservation. This study highlights the essential nature of cleaner bonds for entities and environmental groups aiming to secure funding for long-term projects, stressing the importance of expanding the sustainable economy through green bond issuances for eco-friendly and energy-efficient developments. Furthermore, the research recommends implications for stakeholders to diligently consider the legal aspects associated with these investments.

Rice farming in developing countries contributes significantly to economic growth, yet it confronts diverse risks. Strengthening its resilience necessitates systematically identifying and prioritizing these risks, allowing for optimized resource allocation. The majority of published literature, however, focuses primarily on individual risks rather than comparing or ranking them according to their importance. This regime needs to be more helpful for managers and policy-makers in achieving effective management. As a result, frequent management failures are causing substantial economic losses and threatening food security in the most populous regions of the world. This study addresses these existing research gaps by systematically identifying and prioritizing these risks, aligning with the United Nations Sustainable Development Goal (SDG) 2, viz., Zero Hunger, ultimately contributing to enhanced risk management and developing countries’ rice farming sector resilience. Data was obtained from Pakistan through a purposefully designed questionnaire and sourced from a pool of 412 respondents representing a spectrum of stakeholders selected by the snowball technique. Multi-criteria decision analysis (MCDA) was employed to deconstruct and comprehend the data statistically. A key observation is the recognition of the main risks within rice farming, notably revolving around resource-related and external environmental risks. These risks emphasize the critical management of sub-risks of water management and pest and disease. This study also identified several risk sub-factors that are critical but have yet to be extensively discussed in the literature. Furthermore, survey respondents expressed low levels of risk perception and suggested strengthening the management system through policy reforms. To enhance the resilience of rice farming, stakeholders must engage in effective risk communication, capacity building, and policy implementation. Therefore, more comprehensive integrated risk management interventions are urgently needed to address rice farming risks for achieving SDG 2.

Objective: To compare the antiemetic effects of Metoclopramide and Ondansetron in female patients undergoing laparoscopic cholecystectomy. Study Design: Quasi-experimental study. Place and Duration of Study: Department of Anesthesia, Combined Military Hospital Rawalpindi, Pakistan, Feb to Jul 2022. Methodology: Female patients aged between 15-80 years, American Society of Anesthesiologists Grade I or II planned for laparoscopic cholecystectomy were included in the study. Using non-probability consecutive sampling technique 66 patients were assigned to two Groups with 33 participants in each Group i.e., Group-A (Metoclopramide) and Group-B (Ondansetron) Group. Patients from Group-A received 10mg Metoclopramide while patients from Group-B received Ondansetron 4mg as a part of premedication. Recorded variables were nausea, vomiting and requirement of antiemetic medication at recovery, during the first 06 hours and during 06-24 hours post-operatively. Results: Mean age of the patients was 44.61±12.74 years. ASA distribution of the patients in our study revealed 28(84.8%) patients from Group-A and 26(78.8%) patients from Group-B belonged to ASA I while 05(15.2%) and 07(21.2%) were from ASA II in Group-A and Group-B respectively. Both Metoclopramide and Ondansetron were effective, however results were significant only for nausea and the requirement of antiemetic medication in post-anesthesia care unit. Conclusion: Metoclopramide and Ondansetron both are effective in reducing nausea and vomiting after laparoscopic cholecystectomy in female patients. Ondansetron is superior to Metoclopramide in the reduction of nausea postoperatively however in case of vomiting there is no significant relationship between the two drugs.

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.

Background: Accidental parathyroidectomy during thyroid surgery can lead to temporary or permanent hypocalcemia and serious morbidity. Proper identification of parathyroid glands during surgery can be an effective way to prevent this complication. Methods: The keywords “parathyroid gland,” “preserve,” “protect,” “inadvertent or accidental parathyroidectomy,” “surgery,” and “dissection” were used to search Medline and Embase databases. A total of 133 articles were selected after preliminary review, of which 80 indexed papers were reviewed for subject relevance. Results: Imaging techniques, such as the use of carbon nanoparticles or indocyanine green angiography, and operative techniques, such as meticulous capsular dissection of the thyroid gland, were associated with significantly improved rates of avoidance of inadvertent parathyroidectomy. Conclusion: During thyroid surgery, the use of imaging and careful operative techniques can prevent parathyroid injury. This, in turn, can prevent complications resulting from hypoparathyroidism such as tetany, ECG changes, and neurological sequelae.

Abstract Purpose The present study sought to comprehend the impact of human capital on radical and incremental innovation, with a focus on examining the mediating effects of entrepreneurial passion and entrepreneurial alertness. Design/methodology/approach The study employed a purposive sampling technique for collecting data from entrepreneurs in from different sectors of Pakistan. A sample of 382 entrepreneurs completed the survey. Data were analyzed using SPSS and AMOS. Reliability, discriminant, and convergent validity tests were conducted, and structural equation modeling was used to test the hypotheses. Findings It was revealed that human capital has a significant impact on radical and incremental innovation. Furthermore, entrepreneurial passion and alertness significantly mediates the relationship between human capital and innovation. Originality/value The study contributes to the emerging research on innovation in entrepreneurship. There is limited research on types of innovation and entrepreneurial alertness in Pakistan; therefore, the study adds value to the scarce empirical research on innovation and entrepreneurial alertness and passion.

Abstract Background Prostate cancer is the second most common malignancy in men, and its incidence is increasing which is attributed to increased screening programs. The treatment options of intermediate and high risk prostate cancer include radical prostatectomy, radiotherapy and androgen deprivation therapy. Hypofractionated radiotherapy is becoming more popular lately due to better understanding of the radiobiology of prostate cancer and favorable logistics. Objective To compare the toxicity and efficacy of hypofractionated versus conventional fractionation external beam radiotherapy in patients with intermediate and high risk localized prostate cancer treated in Shaukat Khanum Memorial Hospital and Research Center, Lahore (SKMCH & RC). Methodology We retrospectively conducted this study on histopathologically confirmed 114 patients with prostate adenocarcinoma who underwent treatment from January 2013 till December 2018. These patients were treated with radical radiotherapy along with hormonal therapy as per indication. Data was collected from electronic hospital system and analyzed by SPSS version 23. Results 114 patients were selected according to the inclusion criteria. Mean age was 68 years (61–75). 88% of patients had stage III-IVA disease at the time of diagnosis. Mean PSA and GS was 33 ± 39 SD and 7 ± 0.9 SD respectively. 89% (n = 102) received radiotherapy with 69% of patients receiving dose of 60 Gy in 20 fractions. Among patients who received hypofractionated dose, 86% (n = 61) of them were categorized as high risk and 14% (n = 10) were intermediate risk, whereas among conventional group 90% (n = 28) were high risk patients and 10% (n = 3) were of intermediate risk. In hypofractionated dose group, 14% (n = 10) developed grade 2 proctitis and 8% (n = 6) developed grade 2 cystitis, in contrast to conventional dose group in which only 3 patients (5%) developed grade 2 GI toxicity and 2 patients (2.9%) had grade 2 GU toxicity. However, these toxicities and their grade were clinically insignificant when compared with the dose groups (p = 0.11). 5 year overall survival for hypofractionated radiotherapy versus conventional dose was 100% and 90% respectively with 95% Cl and p value of 0.3 (clinically insignificant), whereas 5 year disease free survival was 100% and 75% for hypofractionation versus conventional EBRT respectively with 95% CI and p value of 0.04 (clinically significant). Conclusion Hypofractionated radiotherapy in patients with intermediate and high risk localized prostate cancer has better disease free survival at the expense of higher risk for proctitis and cystitis but no difference in overall survival as compared to conventional dose of radiation.

Speech is a powerful means to expressing thoughts, emotions, and perspectives. However, accurately determining the emotions conveyed through speech remains a challenging task. Existing manual methods for analyzing speech to recognize emotions are prone to errors, limiting our understanding and response to individuals’ emotional states. To address diverse accents, an automated system capable of real-time emotion prediction from human speech is needed. This paper introduces a speech emotion recognition (SER) system that leverages supervised learning techniques to tackle cross-accent diversity. Distinctively, the system extracts a comprehensive set of nine speech features—Zero Crossing Rate, Mel Spectrum, Pitch, Root Mean Square values, Mel Frequency Cepstral Coefficients, chroma-stft, and three spectral features (Centroid, Contrast, and Roll-off) for refined speech signal processing and recognition. Seven machine learning models are employed, encompassing Random Forest, Logistic Regression, Decision Tree, Support Vector Machines, Gaussian Naive Bayes, K-Nearest Neighbors, ensemble learning, and four individual, hybrid deep learning models including Long short-term memory (LSTM) and 1-Dimensional Convolutional Neural Network (1D-CNN) with stratified cross-validation. Audio samples from diverse English regions are combined to train the models. The performance evaluation results of conventional machine learning and deep learning models indicate that the Random Forest-based feature selection model achieves the highest accuracy of up to 76% among the conventional machine learning models. Simultaneously, the 1D-CNN model with stratified cross-validation reaches up to 99% accuracy. The proposed framework enhances the cross-accent emotion recognition accuracy up to 86.3%, 89.87%, 90.27%, and 84.96% by margins of 14.71%, 10.15%, 9.6%, and 16.52% respectively.

Electrosurgical generators (ESGs) are vital during medical operations, providing high-frequency electrical currents for cutting tissue and coagulation in surgery. Maintaining precise control over output power is challenging due to variable tissue loads. Inconsistent regulation can lead to undesirable surgical outcomes. This paper addresses this challenge through a novel Variable band hybrid current mode control (VBHCMC) technique. The study explores the limitations of existing approaches, such as peak current mode control (PCMC), emphasizing the need for improving control methodologies. The proposed VBHCMC method ensures stable output power, addressing issues associated with PCMC. It dynamically adapts the hysteresis band for variable load impedances, enhancing stability. The significance of this approach lies in its ability to combine the benefits of peak and valley current mode controls while maintaining a nearly constant switching frequency, significantly reducing steady-state errors. Results demonstrate significant reduction in steady-state errors compared to conventional PCMC. The proposed controller provides an effective solution to challenges faced in regulating output power during surgical procedures, enhancing safety and precision. The results have been verified in the MATLAB/Simulink environment, Processor-in-Loop (PIL) simulation in PSIM and using hardware validation.

The ever-expanding Internet of Things (IoT) landscape presents a double-edged sword. While it fosters interconnectedness, the vast amount of data generated by IoT devices creates a larger attack surface for cybercriminals. Intrusions in these environments can have severe consequences. To combat this growing threat, robust intrusion detection systems (IDS) are crucial. The data comprised by this attack is multivariate, highly complex, non-stationary, and nonlinear. To extract the complex patterns from this complex data, we require the most robust, optimized tools. Machine learning (ML) and deep learning (DL) have emerged as powerful tools for IDSs, offering high accuracy in detecting and preventing security breaches. This research delves into anomaly detection, a technique that identifies deviations from normal system behavior, potentially indicating attacks. Given the complexity of anomaly data, we explore methods to improve detection performance. This research investigates the design and evaluation of a novel IDS. We leverage and optimize supervised ML methods like tree-based Support Vector Machines (SVM), ensemble methods, and neural networks (NN) alongside the cutting-edge DL approach of long short-term memory (LSTM) and vision transformers (ViT). We optimized the hyperparameters of these algorithms using a robust Bayesian optimization approach. The implemented ML models achieved impressive training accuracy, with Random Forest and Ensemble Bagged Tree surpassing 99.90% of accuracy, an AUC of 1.00, an F1-score, and a balanced Matthews Correlation Coefficient (MCC) of 99.78%. While the initial deep learning LSTM model yielded an accuracy of 99.97%, the proposed ViT architecture significantly boosted performance with 100% of all metrics, along with a validation accuracy of 78.70% and perfect training accuracy. This study demonstrates the power of our new methods for detecting and stopping attacks on Internet of Things (IoT) networks. This improved detection offers a three-pronged approach to security: increased system reliability through attack prevention, enhanced security by swiftly identifying and mitigating fraudulent activity, and optimized network performance by preventing malicious attacks. Consequently, these methods offer significant potential for fortifying the security of IoT networks.

This study presents an AI-enhanced peak current mode controller developed for electrosurgical generators (ESG). A regression neural network (RNN) is used by the controller to minimize peak current errors. This makes the generator more accurate and stable when there are non-idealities and varying tissue impedances. The controller’s efficacy is evaluated through rigorous MATLAB Simulink, processor-in-the-loop (PIL), and hardware results. The ESG is based on a buck converter and full bridge inverter. The MATLAB simulation results show good consistent output power, voltage, and current across several reference powers (30W, 40W, and 50W) and impedance values (i.e., 80 ohms, 100 ohms, and 120 ohms). The proposed controller has shown improved mean squared error (MSE) and root mean squared error (RMSE) values of 6.76 and 2.60 times, respectively, compared to previous control schemes. The proposed scheme is also verified by the real-time response of PIL simulations using a C2000 Launchpad. The prototype has validated the ESG performance on the C2000 Launchpad. This AI-powered control system has shown good performance in terms of accuracy, safety, and reliability, as verified through simulation and hardware results.

Abstract Bamboo and coffee, which are abundant and inexpensive, have been used as green adsorbents for the adsorption of industrial dye rhodamine B (RB). Bamboo and coffee are natural sources of cellulose, hemicellulose, and lignin, making them promising green materials for industrial dye removal. The effects of various adsorption conditions, such as contact time, temperature, dose of bamboo powder (BP), coffee ground (CG), initial concentration of RB, and pH values of RB solution, were measured. Consequently, the kinetics of RB adsorption onto bamboo and coffee was in accordance with the pseudo-second-order model, with an activation energy of 29.51 kJ mol−1 for bamboo and 27.46 kJ mol−1 for coffee. The Langmuir model is well fitted to the whole adsorption period at different temperatures, in which the increase in the tested temperature has improved the adsorption capacity (i.e., BP: 6.76 mg g−1/30 °C, 6.96 mg g−1/40 °C, 7.64 mg g−1/50 °C and CG: 6.53 mg g−1/30 °C, 6.80 mg g−1/40 °C, 7.51 mg g−1/50 °C). Moreover, the spontaneous nature of the adsorption was based on the negative Gibbs free energy values obtained (i.e., from − 11.09 to − 14.30 kJ mol−1 [BP] and from − 10.34 to − 13.07 kJ mol−1 [CG]). These revealed that RB adsorption occurred at physical and chemical adsorption states. In addition, the recycling capability of adsorbents was determined in five cycles. Therefore, these materials are promising candidates for low-cost adsorbents.

Abstract The online recommendation system has benefited the traditional restaurant business economically. However, finding the best restaurant during rush time and visiting new places is tough. This objective is addressed through a restaurant recommendation approach, which impacts the human decision‐making method. With the help of collaborative filtering, some user‐based recommendation systems were designed to generate the best recommendation based on user choices. Thus, a user preferences‐based method is presented using A Lite Bidirectional Encoder Representations from Transformers and Simple Recurrent Unit to suggest restaurants based on user preferences. Here, a publicly available dataset from Kaggle called Kzomato is used with 9552 samples and 21 features. And the system obtained an F1‐score, precision, and recall of 86%, which will save time and provide the best recommendation based on user preferences easily.

Abstract Floating treatment wetlands (FTWs) are a sustainable solution to treat polluted water, but their role in chromium (Cr(III)) removal under neutral pH conditions remains poorly understood. This study evaluated the potential of FTWs planted with two perennial emergent macrophytes, Phragmites australis and Iris pseudacorus, to remove Cr(III) and nutrients (N and PO4-P) from water containing 7.5 mg/L TN, 1.8 mg/L PO4-P, and Cr(III) (500, 1000, and 2000 µg/L). Within 1 h of exposure, up to 96–99% of Cr was removed from the solution, indicating rapid precipitation. After 50 days, Phragmites bound 9–19% of added Cr, while Iris bound 5–22%. Both species accumulated Cr primarily in the roots (BCF > 1). Biomass production and growth development were inhibited in Cr treatments, but microscopic examination of plant roots revealed no histological changes at 500 and 1000 µg/L Cr, suggesting high resistance of the tested species. At 2000 µg/L Cr, both species exhibited disruptions in the arrangement of vessel elements in the stele and increased aerenchyma spaces in Phragmites. At the end of the experiment, 70–86% of TN and 54–90% of PO4-P were removed.

ABSTRACTThis study analyses the knowledge-sharing process and its outcomes among stakeholders (i.e., academia, industry, government and civil society) in the context of a regional sustainability-oriented project held in Ena City, central Japan, by using the Quadruple Helix (QH) framework. We collected data through interviews with the stakeholders and related documents and employed qualitative content analysis to analyse the data. Our findings imply that there is a gap between the theoretical understanding and practical application of sustainability practices at the initial stage of interaction. However, the project facilitated inter-exchanges of knowledge among stakeholders in the respective helices that could address this gap. Our research suggested the roles of stakeholders in a sustainability-driven collaboration as bridging academics, resource-providing industry, observant government and boundary-spanning civil society which represent the balanced QH model. The current study contributes to the existing literature three-fold. First, few existing studies have employed the QH model in the context of sustainability. Second, most previous studies on the QH model have focused on macro-perspectives. Third, the study clarifies the roles of the stakeholders, which extends the understanding of the QH model. This study suggests a regional sustainability policy that encourages more bottom-up initiatives, in line with the balanced helix model.

Introduction. Stroke is a leading cause of disability and mortality globally, with a significant impact on healthcare systems. Various factors, including age, gender, comorbidities, and the type of stroke, influence the burden of stroke and its outcomes. The study was conducted with an objective to determine the impact of baseline characteristics on the long-term functional outcome of stroke patients. Methods. This prospective observational study was conducted between April 6, 2022 - December 31, 2023, at a tertiary hospital. The study included patients with radiologically confirmed stroke, selected through convenience sampling. Stroke patients of any gender and all age groups, with any comorbidity, were included. The Modified Rankin Scale (mRS) assessed disability on admission and three months post-stroke. Results. Of the 213 patients, 122 (57.3%) were males and the majority, 199 (93.4%) individuals, had acute ischemic stroke. The median age of the participants was 60 years (range: 13-97 years; IQR=18 years). The mRS score on admission was poor (5.0; IQR=1.0) for patients ≥ 60 years. In 74 (34.74%) participants, the left middle cerebral artery was a frequently involved site. Age of ≥ 60 years (mRS=4.0; IQR=4.0; p=0.001) and the presence of ≥ 3 comorbidities (mRS=5.0; IQR=1.0; p=0.001) were significantly associated with poor outcomes three months post-stroke. Ordinal logistic regression revealed that a mRS score of 4 (OR=14.20; 95% CI=1.70-145.25; p=0.02) and a mRS score of 5 (OR=78.84; 95% CI=9.35-820.25; p < 0.001) on admission were associated with poor outcomes. In addition, the presence of ≥ 3 comorbidities (OR=4.59; 95% CI=14.65; p < 0.01) and increasing age (OR=1.04; 95% CI=1.01-1.07; p=0.02) were predictors of poor outcomes three months post-stroke. Conclusions. The study underscores the importance of early intervention and effective management of comorbidities to improve functional outcomes in stroke patients. It highlights the need for targeted stroke care and rehabilitation strategies.

Background Bronchial artery embolization (BAE) is the established first-line treatment for patients presenting with massive haemoptysis, a life-threatening condition that can occur because of numerous underlying diseases. BAE is a relatively safe procedure with control of haemorrhage achieved in 77%–90% of cases and rare occurrence of complications. Spinal cord infarction is one such rare complication, which can have severe implications in terms of morbidity.Case presentations We present a case of a 70-year-old man who developed paraplegia with loss of pain and temperature sensation as well as sphincteric involvement following BAE for hemoptysis. MRI of the spine was suggestive of an ischaemic event involving anterolateral spinal cord segment T4–T6, so a diagnosis of anterior spinal artery syndrome post BAE was made. The patient was given corticosteroids, dual antiplatelet medications, pregabalin, supportive management and regular physiotherapy. Follow-up of the patient at 3 and 6 months failed to show any significant improvement in neurological function, although the patient did not report problem of significant hemoptysis afterward.Conclusion Spinal cord infarct is a rare and disabling complication of BAE despite it being a safe procedure with good long-term outcomes. Detailed knowledge about the anatomy of bronchial arteries and spinal arteries with detailed preprocedure investigations may lower the risk of this disabling complication.

Key Clinical Message Successful management of cervical tuberculosis and severe kyphosis was achieved using a PEEK expandable cage and titanium plate, demonstrating favorable outcomes in restoring cervical alignment and stability. This approach represents a promising alternative for addressing complex cervical pathologies, highlighting the potential of PEEK‐based interventions in surgical management. Abstract Cervical tuberculosis can lead to severe vertebral destruction and kyphosis, posing challenges in surgical management. Recent advancements, including the use of polyetheretherketone (PEEK) expandable cages and titanium plates, show promise in addressing multilevel cervical pathologies. This report details the successful treatment of a 27‐year‐old male with cervical tuberculosis and severe kyphosis. Surgical intervention involved prevertebral abscess evacuation, C5‐C7 corpectomy, and insertion of a PEEK expandable cage with an anterior titanium plate. Postoperative care included a Philadelphia collar, and follow‐up demonstrated restored cervical alignment and stability. The use of PEEK‐based surgical interventions, as demonstrated in this case, represents a significant evolution in managing complex cervical conditions. The successful outcome highlights the potential benefits of PEEK expandable cages in addressing cervical tuberculosis and kyphosis. Further research is needed to validate these findings and establish PEEK‐based interventions as a viable alternative in such cases.

Objective: To compare the efficacy of intravenous phenylephrine infusion versus boluses for blood pressure management in elective caesarean sections. Study Design: Quasi-experimental study. Place and Duration of Study: Anaesthesia Department, Combined Military Hospital, Rawalpindi Pakistan, from Feb to Jul 2022. Methodology: Three hundred ninety patients requiring elective caesarean section were divided into an Infusion Group (n=195) and a Bolus Group (n=195). The Infusion Group received phenylephrine with 100 mcg/ml titration immediately after spinal anaesthesia as per weight and height at a 1 ml/minute rate and continued for 5 minutes. Infusion stopped if MAP at 5 minutes was above baseline and restarted if dropped below baseline in subsequent readings. In the case of bradycardia, 600mcg of Glycopyrrolate was administered. Parameters recorded at 1, 5, 10 and 15-minute intervals. In the bolus group, total numbers of 100mcg boluses at the end of fifteen minutes were recorded. Protocol for bradycardia and data record intervals was the same. The primary variables were mean arterial pressure (MAP), heart rate(HR), the total dose of phenylephrine used, and nausea and vomiting. Results: Primary outcome variables showed consistent improvement in maintaining MAP in the Infusion Group versus the Bolus Group (p

Plums are the ubiquitous fruit belonging to genus Prunus, subgenus Prunus, consumed as food and have many health benefits and medicinal effect in the treatment of many diseases. Pulp from plums is also used in different beverages. Plums are the potential source of polyphenolic compounds and bioactive compounds such as phenolic, anthocyanins, and carotenoids and many organic acids such as citric acid and malic acid. Plums are also the abundant sources of many minerals such as calcium, magnesium, phosphorus, potassium, and vitamins A, B, K, and C. Plums are the abundant sources of predominant antioxidants and phenolic compounds such as caffeic acid, chlorogenic acid, crypto-chlorogenic acid, and neo-chlorogenic acid. These antioxidants and bioactive compounds are effective in the treatment and prevention of gastrointestinal diseases, bone heath, and cardiovascular diseases and in maintaining the blood glucose level. Plums helps in the heart diseases prevention, as it is low in fat content and high in dietary fiber. It is also effective in the treatment of lung and oral cancer. The consumption of plums boosts human health and prevents many diseases. The review discusses the importance, production, different varieties of plums along with its nutritional profile, availability of bioactive compounds, phytochemical composition, and antioxidants mainly phenolic and flavonoid compounds. It also introduces the beneficial effect of the bioactive compounds in heart, lungs, and cardiovascular diseases, followed by its in vivo human and animal studies.

This study investigates the nexus between CO2 emission, trade, Gross domestic product (GDP), and tourism in Pakistan during 1990-2019. We examined the asymmetric relationship between CO2 emission, international trade, Gross domestic product (GDP), and international tourism number of arrivals in Pakistan. Data Stationarity has been tested using the Augmented Dicky Fuller (ADF), Kwiatkowski-Phillips-Schmidt-Shin (KPSS), and Phillips-Perron (PP) tests for unit roots. We used the NARDL technique. Then a Granger Causality helped estimate the relationship between these environmental variables. If there is an asymmetric association between these variables, we estimate the non-linear auto-regressive distributed lag, which is the most applicable econometric estimate. The ARDL technique can potentially explore the dynamic nexus between CO2 emission, tourism, GDP, and trade. Our findings suggest a dynamic relationship between tourism, trade, CO2 emission, and GDP from Pakistan's perspective. The outcomes reveal that negative and positive shocks to trade, GDP, and tourism affect CO2 emissions in the short and long term. The Granger Causality findings also determined that causality is directed from Tourism toward CO2 emission, while unidirectional causality was found between CO2 emission and tourism. In this study, the graphs of the CUSUM and CUSUMQ determined the functional stability of the established relationship. This indicates that this model is a suitable and valuable strategy tool. Therefore, an increase or decrease in the macroeconomic series will cause variation in carbon emissions in Pakistan in the long -term. The finding benefits macro-level policymakers and will provide important insight for the relevant stakeholders.

Solar photovoltaic (PV) panels generate optimal electricity when operating at the maximum power point (MPP). This study introduces a novel MPP tracking algorithm that leverages the numerical prowess of the predictor-corrector method, tailored to accommodate voltage and current fluctuations in PV panels resulting from variable environmental factors like solar irradiation and temperature. This paper delves into the intricate dynamics of solar panels, presenting a comprehensive mathematical model capturing the interdependencies between current, voltage, power, solar irradiation, and temperature. Existing numerical MPPT techniques are explored to provide their advantages and disadvantages. The proposed algorithm, formulated in MATLAB, encapsulates essential solar panel variables and undergoes rigorous dynamic testing in the Simulink® environment under diverse solar irradiation and temperature scenarios. These results are visually represented through graphs and tabulations. A subsequent section offers a simulation-driven comparative review of the proposed algorithm against established methodologies. The article culminates with conclusions drawn from the empirical findings and outlines promising avenues for future research.

Aim . This study aimed to assess the effectiveness of 3 interventions—skit video, pictorial, and sign language—in improving the oral hygiene of children with hearing impairment. Materials and Methods . Sixty children randomly divided into 3 groups: Skit video, Pictorial, and Sign language. The mean gingival and Oral Hygiene Index scores were recorded before and after interventions. A 1-way ANOVA was used for statistically significant difference between pre and post intervention scores. Results . A significant difference in mean oral hygiene and gingival index scores before and after interventions was found in Group A ( P

Anthropogenic environmental pollution has become a global concern due to its profound impact on Earth's ecosystems. This study examines the interrelation between energy resources (both renewable and non-renewable), economic growth, and CO2 emissions across G-20 countries, using historical data from 1990 to 2020. The study employs a robustness analysis to confirm the stability and consistency of the data acquired from the primary approaches. The study utilizes FMOLS (Fully Modified Ordinary Least Squares) and DOLS (Dynamic Ordinary Least Squares) methodologies to investigate endogeneity issues and examine the dynamic linkages in long-term and short-term contexts. The analysis is bifurcated based on two distinct dependent variables: CO2 emissions from gas and oil. Results indicate that gas and oil energies directly augment CO2 emissions. While hydro and renewable energies typically diminish CO2 emissions, specific quantiles suggest a slight increase, indicating an indirect contribution. GDP's quantile transition from positive to negative implies that economic growth can curtail CO2 emissions, suggesting a shift in developed economies from non-renewable to renewable energy dependencies. This study offers insightful policy implications, emphasizing the need to transition from harmful conventional energy sources to renewables to align with the Sustainable Development Goals (SDGs) for 2030.

The cultivation of summer vegetables in open-air nutrient film technique (NFT) hydroponics is limited due to the elevated nutrient solution temperature (NST). In this regard, non-electric evaporative-cooling techniques were explored to maintain NST in open-air NFT hydroponics. Four cooling setups were employed by wrapping polyvinyl chloride (PVC) grow pipes with one and two layers of either wet or dry jute fabrics and attaching them with coiled aluminum pipe buried inside a) wet sand-filled brick tunnels (Cooling Setup I), b) two inverted and vertically stacked earthen pots (Cooling Setup II), c) two inverted and vertically stacked earthen pots externally wrapped with wet jute fabric (Wrapped Cooling Setup II), and d) an earthen pitcher wrapped with wet jute fabric (Cooling Setup III). Wrapping grow pipes with two layers of wet jute fabric reduced NST by 5°C as compared to exposed (naked) grow pipes. The double-layer jute fabric-wrapped grow pipes produced 182% more reduction in NST in comparison to single layer-wrapped grow pipes. Additionally, the installation of Wrapped Cooling Setup II and Cooling Setup III outperformed Cooling Setup I and Cooling Setup II through NST reduction of approximately 4°C in comparison to control. Interestingly, Cooling Setup III showed its effectiveness through NST reductions of 193%, 88%, and 23% during 11 a.m.–12 p.m. as compared to Cooling Setup I, Cooling Setup II, and Wrapped Cooling Setup II, respectively. In contrast, Wrapped Cooling Setup II caused NST reductions of 168%, 191%, and 18% during 2–3 p.m. in comparison to Cooling Setup I, Cooling Setup II, and Cooling Setup III, respectively. Thus, the double-layer jute fabric-wrapped grow pipes linked with Wrapped Cooling Setup II can ensure summer vegetable cultivation in open-air NFT hydroponics as indicated by the survival of five out of 12 vegetable plants till harvest by maintaining NST between 26°C and 28°C.

Background and Objective: The contagious and invasive nature has made coronavirus disease-19 (COVID-19) a critical health issue for the community. The lower respiratory tract is the major site of inflammation seen in COVID-19-positive individuals. Vitamin D (Vit D) has been proposed to have a positive role in immunomodulation, hence, this study aimed to determine the association between Vit D levels and the severity of COVID-19 in infected pediatric patients presenting at a secondary healthcare hospital in Pakistan. Methods: This cross-sectional analytical study was conducted on 100 pediatric patients of the age range 1-18 years from March to December 2021. These patients were hospitalized and diagnosed with coronavirus disease with confirmed results on a real‐time reverse transcription-polymerase chain reaction. Blood samples of the patients were taken to monitor the baseline levels of markers of acute infection and Vit D levels. Patients with serum Vit D levels ≤ 20ng/ml were labeled with deficiency, those with levels 21-29ng/ml were presumed to have Vit D insufficiency whereas levels ≥30 ng/ml were considered normal. Results: There were 57 (57%) males and 43 (43%) female pediatric patients. The mean age of the patients was 10.46 ± 4.25 years (1-18 years). The deficient Vit D level group had a greater frequency of pyrexia, weakness, cough, anosmia, headache, myalgia, and diarrhea. The levels of Vit D and severity of the disease were significantly associated (p-value = 0.027). Conclusion: Pediatric patients with COVID-19 having optimum levels of Vit D were less likely to develop complications associated with the severity of the disease.

World scenario after pandemic COVID-19 has been drastically changing and researchers more focusing on, to minimize the post-pandemic effects on economy, energy sustainability and food security. Agriculture sector is playing pivotal role in world food security and energy sustainability. There is high need to optimize the mechanization technologies to increase the yield in limited energy inputs and operation time to fulfill the world growing food demand. This research is mainly focused on the design development and structural analysis aiding with Finite Element Analysis (FEA) approach for Cotton Stalk Puller and Shredder machine (CSPS) to cut the crop leftovers, soil conditioning (shredding the plant waste into soil) and sowing of next crop in single run by conserving input resources. The experimental trials revealed that there is high pressure on cutting blades, chocking of shredder section and excessive pulling load on tractor hitches, which affected the machine’s performance. To mitigate deficiencies and design optimization to improve the machine safety/reliability, the structure analysis carried out. Six core components of machine including baseplate, blade, gear system, root digger, pulley and shaft has investigated as per field conditions. The results revealed that the material of blade, root digger and teeth of gear system receiving the high stress under the operational conditions which results the edge wear and damage. The carbonization up to one-millimeter thickness can provide the extra strength to bear the excessive load on edge layers.

Background: Gout is one of the most prevalent inflammatory arthritis in the world. It is associated with non-modifiable factors like age gender and genetics and modifiable risk factors like life style changes. Objective: To determine the co-morbidities of gout in patients presenting at tertiary care hospital Peshawar. Study type, settings & duration: A descriptive cross sectional study was conducted at Department of Rheumatology, Lady Reading Hospital, Peshawar from January 2021 to August 2021. Methodology: In this study a total of 323 patients fulfilling the inclusion and exclusion criteria of Gout were observed. All the patients in age between 16-80 years, either gender presenting with gout were included in the study. Gout was diagnosed as per American College of Rheumatology (ACR) Gout Classification Criteria.All the information i.e. age, gender and comorbidities were recorded and were analyzed in statistical software SPSS version 23. Results: A total of 323 patients were enrolled in the study, mean age was 42 with SD ±12.49,female predominance was noted with percentage of 71.8%.The most common comorbidities associated with gout were hypertension(61.6%) and obesity (68.1%). We had patients with other co-existing inflammatory and non-inflammatory Rheumatological diseases. These included seropositive and seronegative Rheumatoid arthritis, Polymyalgia Rheumatica PMR, connective tissue disorder CTD and psoriasis were rarely reported. Among non-inflammatory RMDs, vitamin D deficiency was found to be highly prevalent, followed by Osteoarthritis, Spondylitis and Radiculopathies. Conclusion: Our study concludes that the most common co-morbidities of gout were hypertension and obesity followed by other Rheumatologic diseases (RMDs) and vitamin D deficiency.

In this work a new thresholding function referred to as ’mixture model shrinkage’ (MMS) based on the minimization of a convex cost function is proposed. Normally, thresholding functions underestimate larger signal amplitudes during the de-noising process. The proposed model is a more flexible shrinkage function as it solves the underestimation problem to a greater extent and thus efficiently de-noises the signal without affecting signal amplitudes. The Expectation minimization (EM) algorithm is used to find the model parameters along with the majorization-minimization (MM) algorithm that minimize the monotonic cost function. The proposed model is then applied for de-noising group sparse signals and Shepp Logan phantom images. Our experimental study shows that MMS outclasses current thresholding functions and overlapping group shrinkage algorithm without results suffering from underestimation. Furthermore, the proposed model has the smallest Root Mean Square Error (RMSE) for de-noising group sparse signals.

Objective: This descriptive case series aimed to determine the frequency of feto-maternal outcomes in pregnant women with iron deficiency anaemia at the Mardan Medical Complex, Mardan. The study was conducted between December 2020 and May 2021 in the Department of Obstetrics and Gynecology. Methods: A total of 125 pregnant women diagnosed with anaemia were included in the study. Participants were followed up until delivery, and fetomaternal outcomes, including gestational hypertension, preeclampsia, postpartum haemorrhage, prolonged labour, low Apgar score, low birth weight, preterm delivery, and early neonatal death, were recorded based on predefined operational definitions. Results: The study participants ranged from 18 to 40 years, with a mean age of 27.784±3.13 years. The mean gestational age was 30.112±2.89 weeks. Among the participants, gestational hypertension was observed in 47.2% of patients, preeclampsia in 60.8%, postpartum haemorrhage in 33.6%, prolonged labour in 40%, low Apgar score in 50.4%, low birth weight in 30.4%, preterm delivery in 28.8%, and early neonatal death in 8%. Conclusions: The study findings suggest that maternal anaemia, specifically iron deficiency anaemia, increases the risk of adverse maternal and neonatal outcomes. It is crucial to closely monitor and promptly treat pregnant women with iron anaemia to reduce the risk of feto-maternal complications. Keywords: Pregnancy, Iron deficiency anemia, Feto-maternal outcomes.

Introduction: Massive traumatic subarachnoid hemorrhage (tSAH) is a rare but potentially life-threatening condition that can mimic the clinical presentation of aneurysmal subarachnoid hemorrhage (aSAH). The accurate differentiation between these two entities is crucial, as their management and prognoses significantly differ. Case presentation: We present a case of a 64-year-old male patient who presented to our emergency department after being involved in a motor vehicle collision. His radiological findings on a computed tomography (CT) scan were suggestive of aSAH based on its location, which showed massive SAH in bilateral sylvian fissures and the basal cisterns. There was no evidence of vasospasm. The patient later developed a stroke despite the use of Nimodipine. Conclusion: While traumatic subarachnoid hemorrhage mimicking aneurysmal subarachnoid hemorrhage is a recognized phenomenon, it is relatively uncommon. We present a case of massive tSAH complicated by a stroke with no evidence of aneurysm on cerebral angiogram, shedding light on the diagnostic challenges in differentiating tSAH from aSAH and emphasizing the importance of accurate diagnosis for appropriate management, in addition, we aim to remind the readers that trauma may be a cause for massive SAH and should prompt a medical SAH management plan.

Women’s empowerment is a procedure that provides control of intensity and assets to women, and completely changes them after sometime through their dynamic support in that procedure. The main objective of this study was to evaluate the impact of Information Communication Technology (ICT) on the social and economic empowerment of women in three selected districts of Southern Punjab, Pakistan viz. Multan, Vehari and Khanewal. For this purpose, cross-sectional data of 384 women (100 from Multan, 100 from Khanewal and 184 women from Vehari district) were obtained through random stratified sampling from both rural and urban areas. Women empowerment index (WEI), ANOVA, t-test and ordinary least square (OLS) methods were used for analysis. The findings concluded that the practice of ICT significantly affected the social and economic empowerment of the women. It is recommended that women should be given free access to use ICT for creating new opportunities and more empowerment in the society.