Metallurgical and Materials Engineering (E-Journal)
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Sustainable Hydrogen Peroxide Synthesis Using Bismuth-Modified Biochar
Get PDFIn this work a novel biochar based renewable electrode material has been developed for the sustainable electrochemical synthesis of hydrogen peroxide via oxygen reduction. Biochar was derived from waste, Himalayan poplar wood (Populus ciliata) through pyrolysis at (600-1000oC). The obtained biochar was characterized by using techniques, like scanning electron microscopy (SEM) to investigate morphology, X-ray diffraction (XRD) to analyze crystal structure and degree of graphitization and Raman spectroscopy to probe internal structure. The results affirmed that the biochar obtained from poplar wood was highly porous and containing both ordered and disordered carbon framework. This biochar was further ball milled with bismuth carbonate and annealed at 600oC to get bismuth doped biochar. The XRD spectra revealed the successful incorporation of bismuth in the carbon framework of biochar. The results of electrochemical impedance spectroscopy (EIS) showed that the bismuth doped biochar has less equivalent series resistance compared to pristine biochar. Incorporating bismuth into biochar resulted in a current density of 1.1 mA/cm², exceeding the 0.5 mA/cm² achieved by undoped biochar. Moreover, the bismuth-doped biochar exhibited greater selectivity of 71.25% compared to 49.6% for the pristine biochar. These findings hold good promise for bio waste utilization to develop ecofriendly electrode material for onsite, on demand synthesis of hydrogen peroxide
The Impact Of Digital Finance And Fintech On Enhancing Financial Inclusion
Get PDFThis research paper attempts to assess the effect of digital money on financial inclusion to ensure everyone has access to financial services. It analyses how digital money offers better cost-effectiveness and convenience to marginalised communities to empower them in help of financial inclusion. Challenges relating to the digital divide and risks of data security may restrict that progress. Fintech companies help go digital and offer services through application-driven designs on smartphone. It also focuses as to how Fintech companies (especially mobile payments, AI fraud detection) are making a difference in financial inclusion because of the ease of use. It explores as to how after the ATM boom, new technology developments started happening to finally get to blockchain and crypto. This research is very for decision-makers, to understand how Fintech, digital money and financial inclusion are related to each other it may help in building a safer and inclusive financial system
One-Pot MCR of 3,4-dihydropyrimidine-2-(1H)-one Derivatives by Silica Supported Cu-Zn Nanoparticle
Get PDFA rapid and environmentally sustainable one-pot MCR for the formation of 3,4-dihydropyrimidine-2-(1H)-one analogues, utilizing a silica-supported Cu-Zn nanocomposite as an efficient catalyst under 40 kHz ultrasound conditions with ethanol as the solvent. This one-pot multicomponent reaction, which integrates aromatic aldehydes, urea, and ethyl acetoacetate, yields remarkable results in a very short time, demonstrating high selectivity. The synthesized silica-supported nano catalyst was thoroughly characterized using SEM-EDX. Various spectroscopic techniques, including 1H NMR, 13C NMR, and mass spectrometry has been to confirm the structural information of formed molecules. This method additional advantages like as operational simplicity and environmentally viable, a nano-stable catalyst with excellent reusability (up to 8-10 cycles), rapid reaction times (<10 min), and the elimination of high-cost purification. Because of these attributes, the used method plays dual role sustainable and cost-effective
Predicting Student Mental Health with A Data-Driven Approach to Early Intervention and Artificial Intelligence
Get PDFThe mental health of students has become a fast-developing area of research, given its impact on academic performance, interpersonal relationships, and overall health. This study utilizes machine learning techniques, specifically Random Forest for classification and K-Means clustering with Principal Component Analysis (PCA), to analyze key factors influencing student mental health, including self-esteem, sleep quality, study load, social support and anxiety levels. A mental health analyzer was developed to sort and analyze student data, identifying distinct groups, including those with high stress and severe anxiety and depression due to academic pressure, those with moderate stress but with some coping capacity, those with stable mental health and minor issues, and those with high well-being, good academic performance, and good social support. The findings emphasize the importance of early intervention, personalized support strategies, and mental health support in educational settings. By integrating machine learning for mental health assessment, this research yields valuable insights to educators and policymakers in designing evidence-based, individualized interventions to improve student well-being and academic performance
Ulam Stability Of Finite Dimensional Quadratic /Functional Equation In Banach Space And Banach Algebra
Get PDFIn this work, we examine the Ulam stability of finite-dimensional quadratic functional equation (briefly Fun. Equation) in Banach spaces and Banach algebra by utilizing fixed point and direct approaches. Within the context of this quadratic functional equation, as an illustration of the stability of the equation will be regulated by products and sums of powers of norms, we present several instances
Experimental Evaluation Of Compressive Strength Of Fiber-Reinforced Concrete Using Destructive And Non-Destructive Testing Methods
Get PDFThis study investigates the impact of integrating several types of fibers—glass, carbon, polypropylene, and crimped steel—into standard concrete to create Fiber Reinforced Concrete (FRC) with improved mechanical qualities and durability. This study examines both destructive (compressive strength) and non-destructive (rebound hammer, core strength) test to determine the impact of each fiber type on conventional concrete at various curing times (7, 28, 90, and 360 days). The testing findings demonstrate that crimped steel fibers improved compressive strength the most, reaching 44.00 MPa after 360 days, followed by polypropylene, carbon, and glass fibers. Rebound Hammer tests indicate the better density and surface hardness of FRC made with steel and polypropylene fibers.The study emphasizes the importance of optimizing fiber type and dosage, revealing that a 1.5% content for steel and polypropylene fibers, and 1% for glass and carbon fibers, provides the best performance. This research supports the application of Non-Destructive methods in predicting the long-term strength, quality, and structural integrity of concrete in diverse construction environments
Awareness of Organic Food on Athletic Performance in India
Get PDFThere is a growing interest in organic food in India as many individuals have become concerned about environmental and health issues. This research focused on the production and significance of organic foods in India, particularly for athletic performance. This research is based on previous reports, studies, and official data. The research found that small and marginal farmers who use traditional cultivation methods primarily do organic farming in India. Only a few states in India produce organic food; Sikkim was the first to declare that it was organic. India's main organic agricultural categories are cereals, pulses, fruits, and vegetables. Consumption of organic food in India is still low compared to conventional food. Yet, there has been a significant increase in demand for organic food in urban areas due to rising health enterprises and awareness about the harmful effects of pesticides and chemicals. People were unaware of organic food, especially in athletic performance, but now people are aware because organic food is essential for overall health, especially for Athletes. The Indian government has also introduced several initiatives to support organic farming and give farmers incentives. The Indian market for organic foods is still in its nascent age, but it is expanding quickly. The major players in the market are small and medium-sized companies that concentrate on original and indigenous markets. The market could be more organized, and organic product certification and standardisation are needed to increase consumer confidence. Overall, the study sheds light on the situation of organic food in India and why it is essential for athletic performance and identifies the sector's prospects and limitations. The research indicated that collaboration between the government, producers, and the commercial sector is necessary to improve organic farming, raise public awareness of organic food, and increase the demand for organic products in India, especially for Indian athletics, as it affects their performance
Impact of Digital HRM on Academicians' Performance in Higher Educational Institutions of Sindh: Exploring the Mediating Role of Organizational Empowerment and Moderating Role of Digital Innovation
Get PDFThe digitalization of HRM has significantly influenced organizational performance across various sectors, such as higher education. This study examines the influence of Digital HRM on the performance of Pakistan's Sindh region HEIs' academicians and its mediating and moderating influence through organizational empowerment, and digital innovation. Although corporate settings have been experiencing the growing adoption of digital HRM practices, limited empirical studies have explored their adoption and effectiveness in HEIs, particularly in the developing world. This study employed a quantitative approach, using structural equation modeling completed through structured questionnaires from 356 Sindh's HEIs academicians. Findings indicate a strong positive correlation between Digital HRM and academicians' performance, where organizational empowerment mediates this relationship. Digital innovation also moderates the Digital HRM and academic performance relationship, such that its effects are magnified when institutions effectively utilize innovative digital solutions. This study contributes to theoretical knowledge on Digital HRM in academic settings via offering evidence of its influence on enhancing academic performance through empowerment and innovation. From a pragmatic point of view, the study provides insights to policymakers, education leaders, and HR practitioners in HEIs of Sindh, Pakistan on how to utilize digital HRM strategies to create a more empowered and high-performing academic faculty. The study emphasizes the pivotal role of digital infrastructure and innovative HRM practices in increasing research productivity, pedagogical effectiveness, and institutional success
Enhancing Remote Patient Monitoring through IoT: A Wearable Sensor Fusion Approach for Cardiovascular Health Management
Get PDFRemote Case monitoring (RPM) via the Internet of Effects (IoT) bias has surfaced as a promising approach for managing cardiovascular health. This study presents a new methodology using wearable detector emulsion to enhance RPM effectiveness in cardiovascular health operation. Our approach integrates data from multiple wearable detectors, such as ECG, PPG, and accelerometer, to give comprehensive real-time monitoring of vital signs and physical exertion. Using machine literacy algorithms, the fused detector data is anatomized to descry anomalies, prognosticate cardiovascular events, and epitomize intervention strategies. Likewise, the IoT structure enables flawless communication between cases, healthcare providers, and pall-grounded PPG (Photoplethysm analytics platforms, easing timely intervention and remote discussion. The proposed frame aims to ameliorate patient issues by enabling early discovery of cardiovascular issues, optimizing treatment plans, and promoting visionary healthcare operation. Through simulation studies and confirmation with clinical data, we demonstrate the feasibility and efficacy of our wearable detector emulsion approach in enhancing RPM for cardiovascular health operation
Deep Learning based Feature Fusion Network for Long Range Attack Detection on Blockchain Consensus Layer
Get PDFA blockchain is recognized as a revolutionary and advanced technology, primarily due to its features of privacy, security, immutability, and data integrity. The consensus layer serves as the foundation and it is the most critical component of blockchain architecture. Identifying Long-Range Attacks (LRA) within a block chain presents significant challenges. Existing studies face various difficulties in detecting these long-range attacks and monitoring the behaviour of validator nodes within the blockchain network. Consequently, this paper introduces a novel deep learning approach designed to accurately detect the nodes as either normal or attack, thereby effectively reducing the risk of long-range attacks. Initially, data are collected, and pre-processing is done to improve the quality of input using Upgraded Min-Max Normalization. Next, high level features are extracted using Improved Non-negative Matrix Factorization (INMF) and Sparse Variational Auto encoder (SVAE) methods. The INMF based features are given as input to the Depth wise Separable Convolutional Resnet (DSC-ResNet) to learn the latent features. The Stacked Bidirectional Gated Recurrent Dropout Network (SBi-GRDN) is trained using the SVAE features to identify complex relationships and interactions among features for capturing attack patterns efficiently. Then, the attention layer is used to fuse features from the DSC-ResNet and SBi-GRDN models. Finally, a fully connected layer with a sigmoid is employed for classifying the attack. The experimental results illustrate that the proposed approach attains an accuracy of 99.1%, Precision of 99.5%, Recall of 99.4%, and F1-score of 99.5%, which provides effective results in detecting long range attacks