Journal of Scientific & Industrial Research (JSIR)

A Study on Occupational Health in the Marble Industry in Mexico: The Case of Tepexi de Rodríguez-Puebla

Teodoro Alarcón-Ruíz — 2024-12-09

The existing literature lacks a unified perspective on the impact of occupational health in the marble industry, especially in developing countries. This study aims to enhance current knowledge by exploring how operational conditions and work activities affect workers' health. In the municipality of Tepexi de Rodríguez, Puebla, Mexico, two marble companies and 27 workers participated. In 2021, lighting, noise, and operational conditions were measured, and in 2024, sleep disorders and occupational fatigue were evaluated. The three-year gap between study periods resulted from accessibility and logistical issues. The study used the LEST method, NOM-011-STPS-2001 and NOM-025-STPS-2008 standards, and the Pittsburgh and Yoshitake instruments; data were processed using Ergoniza® software. Results show a physical workload of 7.7, mental workload of 3.0, psychosocial aspects of 4.3, and work time of 6.9 (on a scale of 0 to 10). Noise levels reached 92.26 dB, natural lighting was 899.6 lx, and artificial lighting was 269.4 lx. The sleep disorder index was 7.0, and occupational fatigue showed 2.3 out of 5 for physical fatigue, 1.9 for mental fatigue, and 2.1 for mixed fatigue. These findings reveal a severe physical workload in the cutting, polishing, and packaging areas, correlating sleep disorders to work areas. Increasing the sample size and randomly selecting workers for dynamic system modelling is recommended to explain the correlation between working conditions and productivity. This study underscores the need to improve working conditions to mitigate health impacts, offering practical insights for marble companies and health organizations.

GCN based Bio-Inspired Classifier for Autism Spectrum Disorder

Christina J — 2024-12-09

Autism spectrum disorder is a diverse neurological state with long-lasting and in most instances lifetime implications for individuals. The early identification and intervention are crucial in mitigating the impact of this disorder, necessitating the development of an objective diagnostic method. This study proposes a novel diagnostic approach that utilizes the data extracted from resting state Functional Magnetic Resonance Imaging (rs-fMRI) and critical phenotypic data of each individual. Recursive feature elimination with Grey Wolf Optimization (GWO) is employed for identifying the optimal attributes from the fMRI data. The selected attributes are then inputted into a Graph Convolution Network (GCN) along with the demographic and basic clinical information for categorization purposes. By utilizing a bioinspired optimization algorithm, the likelihood of identifying the optimal feature subset is enhanced. The study compares the performance of the GCN obtained from the GWO feature selection using both the wrapper and filter approaches. The feature set selected through the GWO wrapper approach demonstrates improved accuracy, achieving 73.86%, along with an AUC of 0.817 when inputted into the Graph Convolution Network. These detections emphasise the significance of an objective and accurate ASD diagnosis method with a limited feature set.

A Two-Phase Fault Tolerant System to Reduce the Service Level Agreement Violations

Archana Pandita — 2024-12-09

Fault-tolerant systems are crucial in environments where uninterrupted service is mandatory and also in environments where continuous service is critical, such as in cloud computing and high-availability systems. The main goal of this research is to introduce a fault-tolerant framework that can effectively manage faults without leading to system failures, ensuring seamless service delivery. The proposed system follows a two-phase approach, incorporating fault detection and correction mechanisms that are designed to maintain system integrity and minimize performance degradation. Upon identifying a fault, the system deploys a correction technique aimed at preventing Service Level Violations (SLV), which could otherwise disrupt the service and breach Service Level Agreements (SLA). This fault-handling process is designed to mitigate interruptions while enhancing overall system performance. The proposed solution demonstrates a significant improvement in reducing SLA violations, achieving a reduction to 98.76%. Additionally, the efficiency of the system is enhanced through an increase in the task success rate, further ensuring the reliability of service. To validate its effectiveness, the performance of this fault-tolerant system has been benchmarked against other contemporary algorithms such as First Come First Serve (FCFS), Priority-based, and CD algorithms. The results reveal that the proposed approach offers notable improvements in response times, reducing them by 23%, 16%, and 33.1% respectively, in comparison to the FCFS, Priority-based, and CD algorithms. These results demonstrate the system's superior capability in handling faults and maintaining service quality, making it an ideal choice for environments where uninterrupted service is mandatory.

Developing Sustainable Consumer Practices: A Framework for Managing Refurbished Electronic Goods in India

Mangesh Joshi — 2024-12-09

This study delves into sustainable buying behaviour for refurbished electronic goods in India, driven by the increasing importance of sustainable consumption. It aims to identify key factors influencing consumer decisions, providing insights for businesses and policymakers. The research employs Interpretive Structural Modelling (ISM) and Spherical Fuzzy Analytic Hierarchy Process (SF-AHP). Eight participants from varied backgrounds contribute diverse perspectives, and a strategic methodology includes expert briefings, literature distribution, and collaborative decision–making. Fourteen sustainability drivers are identified and ranked using SF-AHP. Noteworthy factors include "Personal Financial Situation," highlighting economic influence, and ISM analysis reveals societal impact, product quality, and cost savings as central themes. Analysis such as MICMAC (Matrice d' Impacts Croisés Multiplication Appliqués à un Classement i.e., cross‑impact matrix multiplication applied to classification) underscores the interconnectedness of factors, emphasizing driving forces like customer support and product upgradability. Such analysis adds complexity, highlighting driving and dependent factors, offering a holistic view of refurbished product adoption dynamics in India. The novelty lies in integrating ISM and SF-AHP methodologies, unveiling fourteen sustainability drivers, and providing insights into factors influencing consumer choices. This study offers a nuanced understanding of sustainable consumer behaviour, emphasizing economic considerations, trust–building measures, and awareness campaigns. The findings contribute actionable insights for businesses and policymakers aiming to promote the adoption of refurbished goods in the Indian market.

Performance of Rectangular Micro-Strip Notch Antenna for RF Energy Harvesting Applications

Niketan Kumar Mishra — 2024-12-09

An enhanced bandwidth and performance for Wi-Fi applications was achieved through the design and optimization of a notched rectangle microstrip patch antenna in this work. A transmission line model was used in the CST STUDIO SUITE to develop an inset-fed microstrip rectangle patch antenna that would guarantee correct matching of impedance with the microstrip communication line. One of the crucial elements determining the antenna's physical properties, which in turn affected its ideal performance, was the substrate material. Radiation efficiency and impedance matching were the main objectives of this design, which was completed with careful consideration for the patch's size and feed placement. An extensive analysis was conducted on the antenna's key performance parameters, including efficiency, Voltage Standing Wave Ratio (VSWR), far-field radiation patterns, and return loss. The results for return loss demonstrated very good impedance matching, and the far-field radiation pattern demonstrated extremely good directivity with an effective proportion of energy. The return loss study showed a significant reduction at 2.275 GHz, while the VSWR data confirmed a nearly perfect match at the target frequency of 2.45 GHz. With a main lobe gain of 11.1 dB and a peak radiation efficiency of 90% at the design frequency, it is an excellent choice for applications involving the harvesting of radio frequency energy from ambient sources such as Wi-Fi, GSM, UMTS, and LTE signals. The chosen frequencies of 2.275 GHz and 2.45 GHz were selected to optimize impedance matching and enhance the antenna's performance for Wi-Fi and other RF energy harvesting applications, ensuring efficient energy capture and utilization. This work emphasizes the antenna's increased capabilities and provides a workable solution, as well as new applications for contemporary wireless communication systems.

Prediction based Multiobjective Solution of Economic Emission and Load Dispatch for Solar Integrated Power Systems

Sarat Kumar Mishra — 2024-12-09

In present day power systems, the conventional thermal generating stations are being interconnected with solar photovoltaic sources to reduce the running cost along with environmental emission. For proper load dispatch, short term forecasting of electric load is essential to avoid overloads, surges and instability because of varying demand. In this work, Improved Multi-Objective Teaching Learning-Based Optimization (IMOTLBO) algorithm has been developed for effective Economic Emission and Load Dispatch (EELD). Here, the predicted load of a real time load center on a test Solar Integrated System (SIS) has been utilized to obtain Pareto solution, considering cost and emission as two objectives. The performance of the proposed IMOTLBO algorithm is compared with four other MOEAs, namely, Non-dominated Sorting Genetic Algorithm-II (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO), Modified Multiobjective Cat Swarm Optimization (MMOCSO) and Multi-Objective Differential Evolution with Recursive Distributed Constraint Handling (MODE-RDC). For efficient prediction of the expected electrical load demand, an efficient single layer low complexity neural network i.e. Functional Link Artificial Neural Network (FLANN) model is considered. The weights of FLANN model are optimized by utilizing four different algorithms; one derivative based i.e. Least Mean Squares (LMS), and three others heuristic algorithms, namely Particle Swarm Optimization (PSO), Jaya and TLBO. To compare the performance of the proposed TLBO based FLANN models with the other three models, the Root Mean Square Error (RMSE) has been considered as the performance index. The dominance of the proposed FLANN-TLBO models over others is investigated by conducting non-parametric statistical testing.

Spectroscopic Investigations, Quantum Chemical, Molecular Docking and Drug Likeness Studies of 3-Fluorobenzamide

S. Sumathi — 2024-12-09

A significant class of pharmaceuticals due to their biological properties and anti-tumor properties are benzamide derivatives. Density Functional Theory (DFT) calculations involving basis sets, 6-31++G(d,p) and 6-311++G(d,p), have been employed to understand the molecular characteristics of 3-fluorobenzamide. The FTIR and FT-Raman spectroscopies have been used to characterize the vibrational spectra of the molecule. The estimated structural parameters and vibrational frequencies have been analyzed and compared with the experimental findings. The frontier orbital energy gap of the molecule is determined to be 5.521 eV. According to UV-Vis study, the π→π* transition occurs because the ring's C-C bonds function as a leading electron acceptor, while the oxygen (O13) and nitrogen (N14) atoms can act as electron donors. The density of states (DOS) spectrum has 84 electrons, 42α and 42β electrons combined. The Natural Bond Orbital (NBO) results showed that the lone pair transition of F8 and N14 atoms to π*(C3-C4) and π*(C12-O13) indicated a significant stabilizing energy of 17.84 and 43.56 Kcal∙mol⁻¹. The region around the oxygen atom (electrophilic) and amino group hydrogen atoms (nucleophilic) have been analyzed. For ¹H and ¹³C NMR, the predicted chemical shifts were 1.55 to 8.95 ppm and 127.04 to 193.09 ppm, respectively. The binding energies of human matrix metalloproteinase-2, an inhibitor of ovarian cancer, were found to be −6.5 Kcal∙mol⁻¹, those of human progesterone and allosteric inhibitor, inhibitors of breast cancer, to be −6.6 and −5.4 Kcal∙mol⁻¹, and those of histone deacetylases, an inhibitor of leukemia cancer, to be −6.5 Kcal∙mol⁻¹, These are comparable to the binding energies of standard drugs (cytarabine, anastrozole, and carboplatin). ADMET predictions have been employed and the chemical can effectively cure cancers of the ovaries, breast and leukemia while reducing the adverse effects of medical procedures.

Industrial Designs and FDI: India and its Economic Partners

Saurav — 2024-12-09

India’s trade agreements and policies related to Intellectual Property Rights (IPR) have played catalytic role in attracting huge Foreign Direct Investment (FDI) since early 2000s. FDI plays an important role in facilitating technological support, financial capital, and the creation of technological products through R&D. Under IPR, Industrial Designs (IDs) is an important indicator about the manufacturing and industrial base in an economy. After 2005, India signed the trade agreements like Comprehensive Economic Partnership Agreement (CEPA) and the Comprehensive Economic Cooperation Agreements (CECA) to facilitate technology transfer, investment and further strengthening of the IPR regime. This study analyses the relationship between FDI inflows from selective ten economic partners and its interlinkages with the filings of industrial design applications by them on yearly basis in Indian offices. The time line for impact analysis is between 2005 and 2022. The countries are divided in 2 groups, those under CEPA & CECA and those which are not. The Year Fixed Estimation methodology is used for the study. The independent variables such as GDP per capita, annual inflation rate and labour force participation rate have been included to demonstrate the macro effect. The findings show a positive correlation for those countries which are part of trade agreements. This study is unique in case of India as not many studies are available which highlights the effectiveness of CECA & CEPA in stimulating FDI inflows for strengthening of IPR structure in India. Overall the study also provide a huge scope for India to move from labour-driven manufacturing competitiveness towards the intellectual property driven knowledge competitiveness economy thus encouraging more industrial design applications in India.

Standardization of Frying Condition for Preparation of Chhena Jhilli: A Traditional Cheese-based Sweet of Odisha

Krishnananda Nayak — 2024-12-09

Study aimed to standardize the frying conditions and ingredient selection for preparing Chhena jhilli, a cheese-based deep-fried sweet. The research compared the quality parameters (colour, texture, sensory evaluation, and functional characteristics) of samples prepared with either semolina or refined wheat flour mixed with cottage cheese, fried under different temperature (160, 170 and 180℃) and time (3, 4, and 5 minutes) combinations. Results showed that as frying temperature and time increased, the hardness of the samples consistently increased, while moisture content decreased. An improvement in total colour change and overall acceptability was observed when the frying temperature increased from 160℃ to 170℃ but declined at 180℃. Functional properties, such as volume expansion ratio and oil absorption capacity, also increased with higher temperatures, though the increase was not significant between samples fried at 170℃ and 180℃. The analysis concluded that the optimal Chhena jhilli sample was prepared using a 5:1 cheese-to-semolina ratio, fried at 170℃ for 5 minutes, and dipped in 40°Brix sugar syrup. This sample achieved the highest sensory score (8.42) and closely resembled market samples in terms of colour, hardness, volume expansion, and moisture content. The study's insights are highly valuable for the food processing industry, providing a foundation for efficient, scalable, and high-quality Chhena jhilli production that meets both domestic and global demand.

Effects of Drying Methods on Different Characteristics of Chokeberry

Cigdem Mustu Ceylan — 2024-12-09

This research was aimed to determine effect of four different drying techniques, namely Hot Air Drying (HAD), Vacuum Drying (VD), Ultrasound-Assisted Vacuum Drying (USVD), and Freeze Drying (FD) on drying time, total bioactive content, phenolic and anthocyanin profile, surface characteristic and color change of chokeberries. The novelty of this study is the first application of USVD in chokeberry drying. The drying times were recorded as 2100, 1380, and 1200 minutes for HAD, VD, and USVD, respectively, indicating that the application of ultrasound significantly reduced the drying time. Total Phenolic Content (TPC) value of the dried samples varied between 53.15 and 81.18 GAE/g. The individual phenolic and anthocyanin content were determined by HPLC methods. The phenolic profile of the chokeberries showed that protocatechuic acid, catechin, and chlorogenic acid were the major phenolic compounds. The protocatechuic acid value changed between 707.04 and 1126.49 mg/100 and FD showed highest protocatechuic acid value. The anthocyanin profile test showed that the cyanidin-3-O-galactoside was the most prevalent anthocyanin and its value was found as 27725–198674 mcg/100g. DE value was used to determine effect of drying techniques on color change of the dried samples. DE value was found as 8.07–11.98. SEM analysis was used to determine effect of drying on surface characteristic of chokeberries. The samples dried by FD and USVD showed more porous structure. This study concluded that USVD emerged as a promising alternative to VD and HAD due to its shorter drying time, higher retention of bioactive compounds, and better color preservation.