Search

Introduction: Although diarrheal diseases are highly preventable, they remain one of the leading causes of mortality and morbidity in the pediatric population in developing countries. Knowledge of etiological agents is essential to implement public health programs. Viral infections are the most common cause of acute infectious diarrhea among children. There is a paucity of information regarding viral enteropathogens responsible for diarrhea in India, as many hospitals do not routinely carry out diagnostic tests for viral detection. Aim and Objectives: To estimate the prevalence of viral enteropathogens in children under five years of age presenting with acute diarrhea using real-time multiplex polymerase chain reaction (PCR) and its correlation with clinico-demographic features. Methodology: A cross-sectional study was carried out in a tertiary care center in Maharashtra from January 2016 to June 2019. Our study included 300 children who were under five years old with acute diarrhea. Standard protocols were advocated for the collection and transportation of stool samples. All samples were subjected to real-time multiplex PCR (Light cycler 480 Roche) using Fast Track Diagnostic kits for viral gastroenteritis. Data analysis was done using descriptive and analytical methods. Results: In our study, 57% of samples were positive for viral enteropathogens. Rotavirus (32%) was the most common isolate, followed by Norovirus Genogroup II (GII) (17%). The majority of pathogens were isolated from children less than 2 years of age. Conclusion: There is a need to test stool specimens of clinically confirmed diarrheal patients for enteric virus. This will avoid blind antibiotic treatment.

Background: Rheumatoid arthritis (RA) is a chronic inflammatory disorder involving the joints along with various other extra-articular manifestations. Mortality due to coronary artery disease is higher in patients with RA when compared to the general population. Hence, this study is undertaken to assess the predictors of sub-clinical atherosclerosis in patients with RA, so that early prompt management can prevent cardiovascular complications. Methods: A case–control study with 42 patients of RA and 42 healthy age- and sex-matched controls was undertaken. Relevant investigations were done. Disease Activity Score (DAS)-28 was calculated. Carotid artery doppler was performed on both sides to examine the common carotid artery. Results: The mean carotid intima–media thickness (CIMT) (mm) was significantly higher in RA patients compared to controls on the right side (0.57 ± 0.11 Vs 0.40 ± 0.03; P < 0.001) as well as left side (0.56 ± 0.11 Vs 0.39 ± 0.06; P < 0.001). Only age (P = 0.006) and DAS-28 (P = 0.002) showed a positive correlation with CIMT. Conclusions: CIMT can be used as a marker for the detection of subclinical atherosclerosis and the risk of atherosclerosis increases with the increasing age and increasing disease severity.

The current work examines the significant impact of Carreau hybrid nanofluid, particularly in enhancing thermal conductivity and heat transfer efficiency, which is discussed through the integration of aluminium oxide (Al2O3) and titanium dioxide (TiO2) nanoparticles into a base fluid made of 50 % water and 50 % ethylene glycol solution. The study is concentrated on thermal radiation, chemical reactions, thermophoresis, Brownian motion, and viscous dissipation over an exponentially curved Riga surface. The governing partial differential equations are formulated in light of all of these factors. Subsequently, the original partial differential equations are transformed using boundary layer approximations and similarity variables to produce a dimensionless ordinary differential equation. The above equations are solved numerically using the shooting method and the MATLAB function bvp4c. The behaviour of heat and mass transfer in both shear thinning (pseudoplastic) fluids and shear thickening (dilatant) fluids is discussed in detail, and efforts are made to highlight some important parameters such as the Weissenberg number, the curvature radius, the modified Hartmann number, Thermophoresis, Brownian motion, and chemical reaction. The fundamental observation is that a rise in the Weissenberg number results in a reduction of skin friction and Nusselt number in shear thickening scenarios, whereas it leads to an increase in shear thinning scenarios. Increasing the modified Hartmann number results in elevated skin friction and a reduction in the Nusselt number for both shear thickening and shear thinning scenarios. These findings are advantageous for developing strategies applicable to heat control across many industries and biological sectors to enhance energy efficiency and system performance.

Corrosion significantly threatens the structural integrity of steel-based constructions like buildings and industrial units. Traditional corrosion inhibitors, such as chromates, are associated with environmental and health risks. This has led to a growing interest in environmentally sustainable alternatives, with plant extracts emerging as promising candidates. These extracts are widely available, sustainable, and eco-friendly. This review aims to explore the potential of plant extracts as corrosion inhibitors for various types of steel. After examining current scientific literature, over 40 plant extracts have been identified that exhibit corrosion inhibition properties. These extracts have been thoroughly analyzed to understand their effectiveness in preventing corrosion. The review elucidates the mechanisms by which these extracts interact with metal surfaces to form protective layers, effectively hindering the corrosion process. In this review, we focus on the challenges associated with utilizing plant extracts as inhibitors, including optimal extract concentration and temperature considerations.

Plant compounds such as flavonoids, terpenoids, polyphenols, enzymes, and alkaloids are used as reducing agents in eco-friendly titanium dioxide nanoparticle manufacturing. In the current investigation, titanium oxide was converted into titanium dioxide nanoparticles with the application of a lemon extract. Amazingly, the process was also cheap, eco-friendly, and easy to implement. Seeing the white fluid change to a pale yellowish white allowed us to visually confirm that the nanoparticles had been successfully created. Transmission electron microscopy (TEM) and ultraviolet-visible spectroscopy were employed for further characterization. Nanoparticles of titanium dioxide were measured to be between 30 and 45 nm in size. In the DPPH assay, a titanium dioxide nanoparticle concentration of 50 L was shown to be optimal for antioxidant activity. The results of the bovine serum albumin denaturation experiment validated the green produced nanoparticles' dose-dependent anti-inflammatory effect. Consequently, the green synthetic titanium dioxide nanoparticles have great potential as an anti-inflammatory and antioxidant in future medicinal applications.

The investigation is carried to observe the impact of radiation on the MHD couple stress hybrid nanofluid over porous sheet with dissipation. The water based MHD couple stress hybrid nanofluid flow due to porous shrinking sheet with thermal radiation and viscous dissipation has range of engineering applications dealing with energy distribution, solar energy storage, chemical reactors and polymer production. The flow problem is mathematically modelled into nonlinear partial differential equations, which are transformed into set of ordinary differential equations via similarity variable. The analytical solutions are derived in the form of hypergeometric functions. These results are in line with the existing classical results. The physical insights on the impact of MHD, mass transpiration, Eckert number, Couple stress, porosity and thermal radiation on velocity and temperature profiles are provided by means of graphs.

Abstract Background The urinary stone formation is a very common health problem due to the prolonged medication. Calcium Hydrogen Phosphate Dihydrate (CaHPO4.2H2O, CHPD and Brushite) is one of the major constituent of urinary stone crystals. The formation and deposition of brushite crystals is the central cause of recurrent kidney stone disease among the global population. The present study aims to investigate the effect of Aegle marmelos leaves on the growth of brushite crystals to explicate the inhibitory effect of urinary stones from a different point of view. Methods The CHPD crystals were grown by the Single Diffusion Gel growth technique. In order to inhibit the formation of urinary stones, CHPD crystals are grown in the laboratory in the pure form and by adding the prolonged medicine A. marmelos taken especially by diabetic patients. A comparative study of the pure and A. marmelos leaves added crystals has been carried out using the Growth factor, Powder X-ray diffraction, Microstructural parameters, FTIR and SEM-EDAX. Results Total mass of the grown crystals is found to decrease with increasing concentrations of leaf extract of the A. marmelos. On comparing with undoped, crystalline size of the A. marmelos doped samples is reduced. Disappearance of absorption band and peak shift in the FTIR shows the incorporation of functional groups of A. marmelos. The morphology changes of the treated crystals are assessed in SEM. Conclusions The result shows that herbal extracts prepared from A. marmelos have good inhibitory effect on the growth of the brushite urinary stone crystals considered.

In this study, Antioxidant activity of Cyperus rotundus rhizomes extract (CRRE) was evaluveted in a series of in vitro assay involving free radicals and reactive oxygen species and IC50 values were determined. CRRE exhibited its scavenging effect in concentration dependent manner on superoxide anion radicals, hydroxyl radicals, nitric oxide radical, hydrogen peroxide, and property of metal chelating and reducing power. The extract was also studied for lipid peroxidation assay by thiobarbituric acid–reactive substances (TBARS) using young and aged rat brain mitochondria. The extract was also effective in preventing mitochondrial lipid peroxidation induced by FeSO4/ ascorbate in concentration dependent manner. The results obtained in the present study indicate that C. rotundus rhizomes extract can be a potential source of natural antioxidant.

The importance of predicting crop yields has increased due to growing concerns of surrounding food security. Early forecasting of crop yields holds a pivotal role in avoiding starvations by estimating the food supply available for the expanding global population. Several Deep Learning (DL) and Machine Learning (ML) techniques are involved to develop effective and accurate crop yield prediction model. Nevertheless, existing models faces some limitations such as less accuracy, high error rate because of noisy data, high training time and extracted less effective features for prediction. To overcome these issues, the novel DL methodology is introduced for attaining high accurate crop yield prediction. Initially, the soil, weather and other resources big data are collected from the various agriculture field. In data collection phase, the input data of larger size are stored in the Hadoop platform for the purpose of storing as well as processing the entire data in a distributed manner. The data are pre-processed through the utilization of Missing value imputation and z-score based data normalization. From the pre-processed data, the optimal features are considered using Integrated Correlation Random recursive elimination (InCorRe) approach. Based on the previous soil and weather information, the suitable yield of crops can be predicted using Multi head Residual dilated convolution assisted gated unit (MResGat) model. Finally, the losses of the network model can be optimized using African vulture optimization algorithm (AVO). The proposed method is evaluated using the several performance metrics, which achieved 0.023% of MSE value and 0.036% of MAE values. [ABSTRACT FROM AUTHOR]

Background of the Study: Low back pain is one of the most common health problem and 80% of people experiences low back pain in their lifetime. Majority of low back pain is due to the muscle imbalance. Muscle imbalance occurs due to shortened or lengthened in structure and it leads to injury which causes changes in motor programming. Objectives: To compare the effects of Muscle Energy Technique, Positional Release Technique and Conventional Therapy on improving pain, range of motion and functional ability in patients with mechanical low back pain. Subjects and Methods: Twenty four patients of complaining of mechanical low back pain participated in the study. Patients were randomly allocated using computer generator software into three groups: group A which received Muscle Energy Technique, group B which received Positional Release Technique and group C which received Conventional Therapy. Treatment sessions were given three times per week for three weeks. Patients were assessed before and after treatment using Numerical Pain Rating Scale(NPRS),Modified Oswestry Disability Index (MODI), and Modified Schobers Test to assess pain severity, functional ability, and range of motion of lumbar spine respectively. Results: Based on this statistical analysis, Group A showed better statistically significance in NPRS,MODI and ROM mean values as compared to Group B and C. Hence alternate hypothesis is accepted and null hypothesis is rejected. This we conclude that Muscle Energy Technique is more beneficial compared to Positional Release Technique and Conventional Therapy group. Conclusion: Muscle Energy Technique and Conventional therapy group shows significant improvement on Pain and Lumbar Extension Range of Motion compared to Positional Release Technique, whereas there was no significant difference in MODI on Muscle Energy Technique, Positional Release Technique and Conventional therapy. [ABSTRACT FROM AUTHOR]

Introduction: Although diarrheal diseases are highly preventable, they remain one of the leading causes of mortality and morbidity in the pediatric population in developing countries. Knowledge of etiological agents is essential to implement public health programs. Viral infections are the most common cause of acute infectious diarrhea among children. There is a paucity of information regarding viral enteropathogens responsible for diarrhea in India, as many hospitals do not routinely carry out diagnostic tests for viral detection. Aim and Objectives: To estimate the prevalence of viral enteropathogens in children under five years of age presenting with acute diarrhea using real-time multiplex polymerase chain reaction (PCR) and its correlation with clinico-demographic features. Methodology: A cross-sectional study was carried out in a tertiary care center in Maharashtra from January 2016 to June 2019. Our study included 300 children who were under five years old with acute diarrhea. Standard protocols were advocated for the collection and transportation of stool samples. All samples were subjected to real-time multiplex PCR (Light cycler 480 Roche) using Fast Track Diagnostic kits for viral gastroenteritis. Data analysis was done using descriptive and analytical methods. Results: In our study, 57% of samples were positive for viral enteropathogens. Rotavirus (32%) was the most common isolate, followed by Norovirus Genogroup II (GII) (17%). The majority of pathogens were isolated from children less than 2 years of age. Conclusion: There is a need to test stool specimens of clinically confirmed diarrheal patients for enteric virus. This will avoid blind antibiotic treatment. [ABSTRACT FROM AUTHOR]

The exponential growth of the Internet of Things (IoT) usage for real-time applications has made it necessary to implement stringent security measures to protect sensitive data that is communicated and stored by IoT devices. These procedures are designed to prevent unauthorized access. In this research work, we investigate how the Internet of Things (IoT) could benefit from the implementation of a revolutionary lightweight Cipher-Text Attribute-Based Encryption (CP-ABE) system that is rooted in lattice cryptography. We dive into the complexities of lattice-based cryptography and evaluate its viability in contexts where there is limited access to resources related to the Internet of Things (IoT). In addition, we carry out a thorough analysis of the ABE methods that are currently in use, paying particular attention to how effective they are and how easily they may be scaled. Our contribution consists of the development of a novel lightweight lattice-based CP-ABE system that is specifically optimized for Internet of Things installations. According to the findings of our research, it has the potential to considerably bolster the security of the Internet of Things. We provide empirical data that is drawn from applications that take place in the actual world to back up these arguments. Our major purpose is to present a revolutionary CP-ABE approach that was designed to improve the security of the Internet of Things, and this objective will be supported by compelling experimental data in terms of encipherment and decipherment times, key generation times of existing models with the proposed model. According to the results, we have concluded that the computational overhead of the proposed model is roughly 30% lower than that of the existing models, and that the efficiency of providing security is 20% higher in the proposed model than in the existing models. [ABSTRACT FROM AUTHOR]

These days, diabetes is an incurable disease, with millions of people suffering from it worldwide. Several variables namely lack of education, crowded living conditions, obesity and improper diet are among the causes of this recent upsurge in diabetes cases. They are identified by the name of infections induced by bacteria or viruses, harmful compounds in food, autoimmune reactions, obesity, unhealthy lifestyles, and pollution in the environment. Excessive and sight-threatening diabetic retinopathy (DR) is the most common retinal micro-vascular dysfunction that is characterized by the occurrence of a disorder of retinal blood vessels resulting in impaired vision. The IoT-based work is conducted in this work on the machine learning (ML) techniques, K-Nearest Neighbor (KNN) and Support Vector Machine (SVM). The classification of diabetic retinopathy is a topic that is under research. The range of activities of the processes of downsampling, labelling, image flattening, and format conversion is all within the dataset preparation process. An advanced prognosis model is designed which follows a combination of two machine learning techniques such as SVM and KNN. This approach classifies the images of diabetic retinopathy into five segments (subclasses), thus facilitating in-depth analysis. Our solution proposal in this case is a superior one because of its higher classification accuracy and faster processing speed as the findings showed. The robustness and accuracy that the SVM is known for are ensured by the convergence of the KNN to the SVM. The paper also proves a close linkage of clinical symptoms and blood sugar readings to an algorithmic DM prediction system that is based on IoT and ML approaches. This is another advantage of this method that it outperforms the existing classification methods. Amongst all the classifiers that we used in this project, the KNN ML classifier turned out to be the most accurate one with an accuracy rate of 93%. It was found that the algorithm performed with a 79% accuracy rate after tough testing and training and it was consistently providing number one quality DM predictions. [ABSTRACT FROM AUTHOR]

This research paper explores the implications of technology in promoting wellness tourism in Thrissur, Kerala. Thrissur, renowned for its cultural heritage and natural beauty, has emerged as a significant destination for wellness tourism, offering Ayurvedic retreats, yoga centers, and holistic healing practices. In recent years, technological advancements have reshaped the tourism industry, presenting opportunities for enhanced marketing strategies, personalized experiences, and improved accessibility. Through a mixed-methods approach combining quantitative analysis of online marketing data and qualitative insights from tourists, wellness practitioners, and local stakeholders, this study aims to assess the effectiveness of technology-driven promotional strategies in attracting wellness tourists to Thrissur. It also analyzes the impact of digital platforms on visitor experiences, identifies challenges and opportunities for leveraging technology in wellness tourism promotion, and provides recommendations for stakeholders. The findings contribute to the understanding of the role of technology in shaping wellness tourism destinations and offer practical insights for destination marketers, policymakers, and businesses in Thrissur. [ABSTRACT FROM AUTHOR]

Background: Rheumatoid arthritis (RA) is a chronic inflammatory disorder involving the joints along with various other extra-articular manifestations. Mortality due to coronary artery disease is higher in patients with RA when compared to the general population. Hence, this study is undertaken to assess the predictors of sub-clinical atherosclerosis in patients with RA, so that early prompt management can prevent cardiovascular complications. Methods: A case-control study with 42 patients of RA and 42 healthy age- and sex-matched controls was undertaken. Relevant investigations were done. Disease Activity Score (DAS)-28 was calculated. Carotid artery doppler was performed on both sides to examine the common carotid artery. Results: The mean carotid intima-media thickness (CIMT) (mm) was significantly higher in RA patients compared to controls on the right side (0.57 ± 0.11 Vs 0.40 ± 0.03; P < 0.001) as well as left side (0.56 ± 0.11 Vs 0.39 ± 0.06; P < 0.001). Only age (P = 0.006) and DAS-28 (P = 0.002) showed a positive correlation with CIMT. Conclusions: CIMT can be used as a marker for the detection of subclinical atherosclerosis and the risk of atherosclerosis increases with the increasing age and increasing disease severity. [ABSTRACT FROM AUTHOR]