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Composite materials are identified to be an alternate solution for the present-day problems pertaining to the reduction of the weight of the components without compromising on their strength and stiffness. The application of the different reinforcements improves the mechanical or thermal properties of the base matrix material related to the application and the heterogeneous nature of the composite material adds flexibility in the design. The manufacturing methods of the composites have also improved in the recent past to ensure that the Reinforcements are properly distributed in the base matrix. Machining a hard composite using conventional techniques is tedious, time-consuming, and will lead to higher tool wear. Therefore, non-conventional machining processes were adopted for the machining of the composite material which can be carried out using inexpensive tooling, The present work aims at optimization of the machining parameters and helps in providing better productivity and cost-effectiveness. The material identified for the optimization was AA6351-SiC-B4C hybrid composites which have widespread application in the nuclear industry. This work aimed at the optimization of the parameters by employing Analysis of Variance (ANOVA) and Response Surface Methodology (RSM) for the identification of the optimum parameters. The current was identified to be the major contributing parameter for the machining of the composite for the output parameters considered. The optimum values for all the composites were identified to be at 12A current.100 µs Pulse on time and feed rate of wire at 8m/min irrespective of the percentage variation of B4C. It can be identified that the optimum values identified are independent of the reinforcement percentage and therefore, can be adopted for all the percentages of B4C in the composite.

Background: Oral ulcers are frequent ulcerative conditions in the oral cavity that cause pain, recur often, and negatively impact quality of life. Aim and Objective: This study aims to assess the effectiveness of herbal extracts containing saffron, Withania somnifera, dry ginger, and tulsi as anti-inflammatory and cytotoxic agents for treating oral ulcers. Materials and Methods: A blend of 1 g each of tulsi, Withania somnifera, and dry ginger powders was mixed with 100 ml of distilled water and heated at 50 to 60 degrees Celsius for 15 minutes. The anti-inflammatory and cytotoxic activities were tested by adding 5 ml of the extract to a gel composed of 5 g of carboxylate methyl cellulose and carbopol. The anti-inflammatory properties of the herbs were assessed using the Membrane Stabilization Assay, BSA Assay, and EA Assay, while the cytotoxic effect was evaluated using the Brine Shrimp Lethality Assay. Results: The Membrane Stabilization Assay at concentrations of 10, 20, 30, 40, and 50 micrograms/ml showed values of 53, 64, 77, 79, and 85, respectively. The BSA Assay results were 42, 56, 67, 75, and 77, and the EA Assay results were 54, 61, 65, 69, and 78. The P values were 0.658 for the Membrane Stabilization Assay, 0.281 for the BSA Assay, and 0.647 for the EA Assay. These values indicate that the herbal ingredients’ cytotoxic activity is comparable to the standard. Conclusion: This study demonstrates that the natural components of medicinal herbs can effectively treat oral ulcers, improving patients’ quality of life. Thus, herbal medicines can be used alongside commercially available allopathic drugs.

Abstract Rice metabolomics is widely used for biomarker research in the fields of pharmacology. As a consequence, characterization of the variations of the pigmented and non-pigmented traditional rice varieties of Tamil Nadu is crucial. These varieties possess fatty acids, sugars, terpenoids, plant sterols, phenols, carotenoids and other compounds that plays a major role in achieving sustainable development goal 2 (SDG 2). Gas-chromatography coupled with mass spectrometry was used to profile complete untargeted metabolomics of Kullkar (red colour) and Milagu Samba (white colour) for the first time and a total of 168 metabolites were identified. The metabolite profiles were subjected to data mining processes, including principal component analysis (PCA), Orthogonal Partial Least Square Discrimination Analysis (OPLS-DA) and Heat map analysis. OPLS-DA identified 144 differential metabolites between the 2 rice groups, variable importance in projection (VIP) ≥ 1 and fold change (FC) ≥ 2 or FC ≤ 0.5. Volcano plot (64 down regulated, 80 up regulated) was used to illustrate the differential metabolites. OPLS-DA predictive model showed good fit (R2X = 0.687) and predictability (Q2 = 0.977). The pathway enrichment analysis revealed the presence of three distinct pathways that were enriched. These findings serve as a foundation for further investigation into the function and nutritional significance of both pigmented and non-pigmented rice grains thereby can achieve the SDG 2.

BackgroundBy 2023, COVID-19 had caused 6.8 million deaths in the United States. COVID-19 presents more severely in leukemia compared to solid tumors (OR 1.6, p

Advanced industrialization requires an enormous amount of water, dyes, and chemicals, and it continuously releases toxic effluents into the environment and water bodies. In textile, paper, leather, and other industries, dyes are the compounds being used to provide color to the substances. Among all of the dyes utilized in the dyeing sector, azo dyes contribute about 60 % of all dyestuffs used globally. Synthetic dyes harm the aesthetic qualities of water resources by elevating COD (Chemical oxygen demand) and BOD (Biological oxygen demand), toxic substances, turbidity, hindering photosynthesis, stifling plant development, contaminating the food chain, inducing recalcitrance, and accumulation, and effectively stimulating toxicity, carcinogenicity, as well as mutagenicity. To minimize negative impacts on the surroundings, people, and natural water bodies, wastewater comprising dye pollutants must be removed effectively through eco-friendly technology. As a result, treatment of these textile effluents is required before they are eliminated into the surroundings. Physical, chemical, physio-chemical, and biological methods are among those used for treating textile wastewater. Biological methods, such as treatment with bacteria, bacterial enzymes, fungi, and plants, were used due to their environment-friendly and cost-effective method. The classification of dyes and their degradation mechanism by bacteria are addressed in this paper.

Despite extensive preclinical research over the years, a significant gap remains in our understanding of the specific effects of methamphetamine (METH) and amphetamine (AMPH) withdrawal. Understanding these differences could be pivotal to unveiling the unique pathophysiology underlying each stimulant. This may facilitate the development of targeted and effective treatment strategies tailored to the specific characteristics of each substance. Following PRISMA guidelines, this systematic review was conducted to examine alterations in spontaneous locomotor activity, specifically horizontal activity, in animals experiencing withdrawal from extended and repeated administration of AMPH or METH. Original articles were retrieved from four electronic databases, supplemented by a review of the references cited in the published papers. A total of thirty-one full-length articles (n = 31) were incorporated in the analysis. The results indicated that six studies documented a significant increase in horizontal activity among animals, seven studies reported decreased locomotion, and eighteen studies (8 AMPH; 10 METH) reported no significant alterations in the animals’ locomotor activity. Studies reporting heightened locomotion mainly employed mice undergoing withdrawal from METH, studies reporting diminished locomotion predominantly involved rats undergoing withdrawal from AMPH, and studies reporting no significant changes in horizontal activity employed both rats and mice (12 rats; 6 mice). Drug characteristics, routes of administration, animal models, dosage regimens, duration, and assessment timing seem to influence the observed outcomes. Despite more than 50% of papers enlisted in this review indicate no significant changes in the locomotion during the stimulant withdrawal, the unique reactions of animals to withdrawal from METH and AMPH reported by some underscore the need for a more nuanced understanding of stimulant withdrawal.

This study explores the novel design of geometric rubbing profiles on rotary friction welding for enhanced mechanical clamping in joining dissimilar alloys such as copper and stainless steel 316L. The clamping behavior of rubbing profiles could hold the yielding of the weld joint to a maximum level. An innovative approach to effective mixing of the weldment zone could be achieved through the definition of rubbing profiles. The effective dispersion of dissimilar metallic phases could be governed by the geometrical profile in achieving the intermetallic SS-Cu phase. Variations were made in welding parameters like tool rotational speed, upset pressure, upset time, friction pressure, and friction time to find the appropriate process for the four different rubbing profiles, namely helical fluke, plus, cylindrical, and flat to achieve a reduction in micro and macro-structural defects with strong weld nugget. Results show that helical fluke rubbing profiles were seen to have explicit values like ultimate tensile strength of 217 MPa (upset pressure), elongation of 9.8 % (upset pressure), and average hardness of 125 HV (friction pressure) at the weld nugget. Microstructural characteristics prove that the formation of IMCs through grain size reduction such as cementite increases the Vickers hardness of the weldment.

The impact of climate change on methane (CH4) emissions from rice production systems in the Coimbatore region (Tamil Nadu, India) was studied by leveraging field experiments across two main treatments and four sub-treatments in a split-plot design. Utilizing the closed-chamber method for gas collection and gas chromatography analysis, this study identified significant differences in CH4 emissions between conventional cultivation methods and the system of rice intensification (henceforth SRI). Over two growing seasons, conventional cultivation methods reported higher CH4 emissions (range: from 36.9 to 59.3 kg CH4 ha−1 season−1) compared with SRI (range: from 2.2 to 12.8 kg CH4 ha−1 season−1). Experimental data were subsequently used to guide parametrization and validation of the DeNitrification–DeComposition (DNDC) model. The validation of the model showed good agreement between the measured and modeled data, as denoted by the statistical tests performed, which included CRM (0.09), D-index (0.99), RMSE (7.16), EF (0.96), and R2 (0.92). The validated model was then used to develop future CH4 emissions projections under various shared socio-economic pathways (henceforth SSPs) for the mid- (2021–2050) and late (2051–2080) century. The analysis revealed a potential increase in CH4 emissions for the simulated scenarios, which was dependent on specific soil and irrigation management practices. Conventional cultivation produced the highest CH4 emissions, but it was shown that they could be reduced if the current practice was replaced by minimal flooding or through irrigation with alternating wetting and drying cycles. Emissions were predicted to rise until SSP 370, with a marginal increase in SSP 585 thereafter. The findings of this work underscored an urgency to develop climate-smart location-specific mitigation strategies focused on simultaneously improving current water and nutrient management practices. The use of methanotrophs to reduce CH4 production from rice systems should be considered in future work. This research also highlighted the critical interaction that exists between agricultural practices and climate change, and emphasized the need to implement adaptive crop management strategies that can sustain productivity and mitigate the environmental impacts of rice-based systems in southern India.

The manufacturing of copper oxide (CuO) nanoparticles has been accomplished utilizing a green technique that relies on biologically reliable mechanisms. Aqueous solutions of copper nitrate and Ixora Coccinea leaf extract are used in an environmentally safe process for creating CuO nanoparticles. The characterization of the synthesized CuO nanoparticles involves the utilization of techniques such as X-ray diffractometry (XRD), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and thermogravimetricanalysis (TGA). CuO nanoparticles are confirmed by XRD and FTIR peak results. When the particles are measured, they range between 93.75 nm and 98.16 nm, respectively. The produced CuO nanoparticles are used to prepare the nanofluid. While conventional water exhibits a 3 °C temperature difference, nanofluid achieves a considerable temperature differenceof 7 °C. As a result, it is clear that the nanofluid performs better at dispersing heat into the environment. The experiment’s overall findings support the possibility of ecologically friendly, green-synthesized CuO nanoparticle-induced nanofluid as an effective heattransfer fluid that can be applied to heattransfer systems.

The present study is focused on numerical analysis of magnetic roller (Mr) using finite element method magnetics (FEMM) software for different magnet disc-to-steel disc (MD-to-SD) width ratios. The numerical (FEMM) results reveal that, the optimized Mr with the MD-to-SD width ratio of 5 mm: 2.5 mm was proved advantageous because of the effective magnetic field (Mf) value of 0.89–2.59 T. The artificial neural network (ANN) modelling technique was used for the prediction analysis of obtained numerical results. Furthermore, by using optimized Mr, the lab-scale permanent magnet roller separator (PMRS) was developed and parametric optimization has been carried out using Taguchi-based L27 orthogonal array design. The significance of parameters on the overall quality of the product has also been evaluated quantitatively by the analysis of variance (ANOVA) method. It was found that the belt thickness was the most influential factor in the product of desired Fe grade and recovery %. The obtained regression coefficient (i.e., R2 = 87.13 and 91.69% for Fe grade and Fe recovery %, respectively) and normal probability plot show the highest correlation between the experimented and predicted data. The results suggested that the numerical approach was suitable for designing optimized Mr for the processing of paramagnetic minerals.

In India, research on the development of new composite materials is extensively increased. In the present study, composites are developed with the renewable materials of plant and animal-based natural fibers. The present study will lead to the experimental and statistical investigation of the composite produced with a combination of plant-based natural fibers, i.e., jute and coco peat powder with the animal-based natural fibers, i.e., silk. In the present study, jute and silk were utilized as reinforcement material, cocopeat powder as a filler material (5%), and epoxy resin as matrix material (35%). The composites were prepared with the varying composition of reinforcement material, and also the filler and matrix material were kept constant. Furthermore, mechanical properties such as tensile, flexural, and impact tests were performed on the developed composites. Further, a comparative study was drawn on the mechanical test results of tensile and flexural strength of the composite using power and polynomial regression model. The regression coefficient (R2) was used to study the correlation between the experimental and predicted values. The results showed that the polynomial regression is the best suitable mathematical model than the power regression model for predicting the composites’ tensile and flexural test performance.

In India, the utilization of natural fibers for developing new composites with desirable properties has been increasing from the last decade. Bio-waste such as fish scale and coconut shell (CS) powder was utilized to develop natural fiber-based composites in the present work. Three composite specimens, i.e., 30 wt% fish scale (FS), 30 wt% CS powder (CS), and 5 wt% fish scale (FS)+ 5 wt% CS powder specimen, were developed. The tensile, flexural, and impact strength testing was carried out on each specimen. A comparative study was drawn between the test results of the specimen. The experimental results showed that the CS powder-based composites yield improved mechanical properties compared to the fish scale-based composites. Furthermore, a quadratic and cubic mathematical model was developed on the experimental results of tensile and flexural testing for each specimen. The regression results show that the cubic regression model yields better prediction results than the quadratic regression model for all the composite specimens. The experimental results showed that the largely available fish scale and CS powder could be used to produce biowaste-based value-added material that provides a sustainable and eco-friendly approach.

Since financial institutions have provided almost similar products and services, thus financial firms have been highly competitive in the industry. The results of this competition are based on service quality. Apart from that, the development of technology has caused Fintech products and services to be introduced in Malaysia. This research aims to investigate the customer experiences with Fintech products and services. This study also identifies sources of customer satisfaction and dissatisfaction associated with the several factors that impact the use of Fintech products and services in Sungai Petani, Kedah. The main factors of this research are security, convenience, and service quality. Besides that, the result of this study was derived from 200 respondents who are young adults aged between 20 and 39 in Sungai Petani through the online questionnaire survey. Lastly, the study indicated that all of these three independent variables: security, convenience, and service quality have affected customer satisfaction with Fintech.

Additive Manufacturing (AM) empowers the creation of high‐performance cellular materials, underscoring the increasing need for programmable and predictable energy absorption capabilities. This study evaluates the impact of a precisely tuned fused filament fabrication (FFF) process on the energy absorption and failure characteristics of 2D‐thermoplastic lattice materials through multiscale experiments and predictive modeling. Macroscale in‐plane compression testing of both thick‐ and thin‐walled lattices, along with their µ‐CT imaging, reveal relative density‐dependent damage mechanisms and failure modes, prompting the development of a robust predictive modeling framework to capture process‐induced performance variation and damage. For lower relative density lattices, an FE model based on the extended Drucker–Prager material model, incorporating Bridgman's correction with crazing failure criteria, accurately captures the crushing response. As lattice density increases, interfacial damage along bead‐bead interfaces becomes predominant, necessitating the enrichment of the model with a microscale cohesive zone model to capture interfacial debonding. The predictive modeling introduces an enhancement factor, offering a straightforward method to assess the impact of the AM process on energy absorption performance, thereby facilitating the inverse design of FFF‐printed lattices. This approach provides a critical evaluation of how FFF processes can be optimized to achieve the highest attainable performance and mitigate failures in architected materials. [ABSTRACT FROM AUTHOR]

Background: By 2023, COVID-19 had caused 6.8 million deaths in the United States. COVID-19 presents more severely in leukemia compared to solid tumors (OR 1.6, p<0.05). However, data on Acute Myeloid Leukemia (AML) and Myelodysplastic Syndrome (MDS) are limited. We investigated the mortality in AML and MDS patients with COVID-19. Methods: Data from the 2020-2021 National Inpatient Sample was used to conduct a cross-sectional analysis. We identified AML and MDS patients with COVID-19 hospitalizations through ICD-10 codes. Analysis was done by propensity matching and multivariate regression with a p-value of ≤0.05. Results: Of 28,028 AML admissions, 336 (1.2%) were admitted for COVID-19. AML-COVID-19 cohort had a lower hospitalization risk (aOR 0.3, p=0.000) and higher mortality (21.7% vs 8.7%; aOR 1.6, p=0.023) than AML patients admitted for other causes. AML patients post-HSCT (Hematopoietic Stem Cell Transplantation) had a higher risk of COVID-19 (20.2% vs 9.8%; aOR 2.6, p=0.000) and increased mortality (19.1% vs 6.7%; aOR 4.1, p=0.000) compared to other causes. Similarly, of 28,148 MDS patients, 769 (2.7%) were admitted for COVID-19. The MDS-COVID-19 cohort had a lower hospitalization risk (aOR 0.59, p=0.000) and higher mortality (19.6% vs 6.6%; aOR 2.2, p=0.000) compared to other causes. In MDS, HSCT did not alter the risk of COVID-19 hospitalizations (3% vs 3.9%; aOR 0.9, p=0.662), but these patients had higher mortality (17.4% vs 5.1%; aOR 4.0, p=0.032). Conclusion: COVID-19 hospitalization was low in AML and MDS but carried a high mortality risk. Post-HSCT, the mortality is high, warranting research into understanding the underlying factors. [ABSTRACT FROM AUTHOR]

Background: India relies primarily on direct smear microscopy for tuberculosis (TB) diagnosis. However, the low sensitivity of smear microscopy emphasizes the need to improve its performance. We recently described the development of 'TBDetect' kit which showed improved performance over direct smear microscopy at National Reference Laboratories (NRLs) in India. Methods: The present study was aimed to assess the operational feasibility of 'TBDetect' microscopy in field settings. This was evaluated by (i) assessing the performance of 'TBDetect' microscopy vs. LED-fluorescence microscopy (LED-FM) on consecutive presumptive pulmonary TB patients (n = 5300) who attended Designated Microscopy Centres (DMCs, n = 13) under 4 NRLs at Bhubaneswar, Bhopal, Chennai, and New Delhi, and (ii) obtaining feedback from Scientists (n = 10) and laboratory technicians (n = 42) using semi-structured questionnaires under the following parameters: feasibility of initiation of 'TBDetect' microscopy in DMCs, sample preparation and testing, training, time-to-result, logistics, and troubleshooting. A scoring questionnaire was also used to assess 'TBDetect' microscopy vs. LED-FM and statistical significance of the scores was calculated using paired t-test. Results: The overall positivity of 'TBDetect' microscopy was 10.32% (547/5300) vs. 8.96% (475/5300) of LED-FM at all sites and the increment in positivity was significant (p = 0.019). In addition, 'TBDetect' microscopy yielded an increment in smear grade status over LED-FM (p = 0.043). The feedback from the study-in-charge and kit users indicated that 'TBDetect' microscopy was easily adapted in point-of-care settings. An analysis of scoring feedback suggested that it was easy to perform and observe in comparison to LED-FM (p < 0.005). Conclusions: This study established the feasibility of 'TBDetect' microscopy in field settings. [ABSTRACT FROM AUTHOR]

This study demonstrates the piezoresistive behaviour of hyperelastic silicone/CNT nanocomposites for large strain sensing applications. Four different 2D lattices, namely the Hexagonal, Re-entrant, I-shape and S-shape are employed to explore the effect of unit cell architecture on gauge factor. The lattices are produced at three different relative densities (30%, 40%, 50%) to determine the effect of such on piezoresistive sensitivity. Piezoresistive gauge factors of 2.66, 0.61, 4.91 and 0.20 at 125% strain were recorded respectively for each lattice geometry: Hexagonal, Re-entrant, I-shaped, and S-shaped. The results showed the effective sensitivity of the elastomeric nanocomposite auxetic lattices up to 400% tensile strain, far beyond that achieved by extant studies.

This research is about to explore factors that impact employee turnover intention in the banking sector in Penang. A few factors anticipate influencing the employee's turnover intention. Questionnaires disseminated to respondents chose a sum of 150 bank employees from various banks. The outcomes indicate that there is a positive connection between all factors and employee's turnover intention. All variables have an impact on employee's turnover intention. This investigation will help the bank management recognize the potential factors that impact their staff to resign from the present place of employment and few recommendations for further research proposed toward the end of this research.

Background: Psoriasis is a chronic inflammatory disease which can be associated with metabolic syndrome and cardiovascular abnormalities. Objectives: The aim and objective of the study are to demonstrate interleukin-17 (IL-7) positivity in histopathological sections of psoriatic plaques and to correlate with metabolic syndrome and cardiovascular changes. Materials and Methods: Forty-seven patients with chronic plaque psoriasis with body surface area >10% and psoriasis area and severity index (PASI) score >12, in whom skin biopsy showed munro's microabscesses, were evaluated for IL-17 positivity (intensity and proportion) with associated metabolic syndrome according to the National Cholesterol Education Program adult treatment panel III criteria and cardiovascular comorbidities. A co-relation with PASI score was made. IL-17 intensity and proportion were graded with a score ranging from 0 to 3. IBM SPSS version 16.0 was used for statistical analysis and independent t-test and Chi-square test were used for proportion. Results: The mean age of patients was 43 years. A total of 15 (31.9%) female and 32 (68.1%) male patients were enrolled. The mean PASI score was 21.6. Metabolic syndrome was seen in 31 (65.96%) patients. There was statistically significant association with raised diastolic blood pressure in patients with metabolic syndrome (P = 0.042). The total number of patients with IL-17 positivity with metabolic syndrome was 21 (63.6%). Of these, 9 (42.9%) cases showed IL-17 positivity in the munro's microabscess, 14 (66.7%) cases in the rest of the epidermis, and 18 (85.7%) cases in the dermis. Conclusion: In our study, there was no significant difference in IL-7 positivity between patients with or without metabolic syndrome. Further studies need to be done with large sample size to confirm the significance.

The fabrication of the Al2219 + Si3N4 composites was done by means of stir casting process. The specimen was subjected to microstructural studies. The density of Si3N4 employed in the fabrication of the composites has been evaluated. Generally, the density of the composites increases as the weight percent of Si3N4 increases. TGA and DTA were performed at temperatures ranging from 30°C to 800°C, with some mass loss noted as well as the thermal stability of an AA2219 matrix improved. Under various parameters of applied load, operating duration, and speed, the wear behaviour of the produced aluminium matrix composite (AMC) was examined. Corrosion behaviour was examined using potentiodynamic polarization curve data, and it was discovered that the rate of corrosion decreases with increasing Si3N4 content, adding to the AA2219 matrix. The research work is intended to produce a totally new composite material with various compositions of reinforcement and to investigate their mechanical properties and a result of simulation.