Box-Girder Bridges - Modelling and Analysis

The box-girder bridge has become very popular lately due to its serviceability, stability, and structural efficiency. The study of such a bridge requires analytical, experimental, or numerical methods. The structural behavior of the box-girder bridge is very complex and is quite cumbersome to be investigated by conventional methods. This paper presents a modelling process for the analysis of simply supported reinforced concrete (RC) box-girder bridges (straight, skew, curve, and skew-curved) using the finite element method under Indian loading conditions. This modelling process is developed on the basis of the Codal provisions of Indian Road Congress (IRC) 6:2017 and IRC 21:2000, and its implementation is quite simple as it avoids the cumbersome calculations and requires less time. Different values of the span, span-depth ratio, and the number of cells are considered to suit the requirements, and limiting criteria for stresses and deflection are checked. The static and free vibration analyses are carried out, and the results are compared to control the applicability of the proposed modelling process. The present modelling process is applied to analyse the RC box-girder bridges up to 50 m spans, and no erection procedure is included. However, one may follow the proposed modelling procedure for any box-girder bridge for its analysis

EVALUATION OF THE EFFECT OF YOGIC PRACTICES ON RAKTAGATA VATA (ESSENTIAL HYPERTENSION)

Objective: Essential hypertension is the most frequent kind of hypertension and also known as primary hypertension or idiopathic, affecting 95% of hypertensive patients. This study was conducted to see the effect of Yogic practices as Nadi Shodhana Pranayama (NSP = cleaning of subtle energy channel along with regulation of rhythm of breathing) and Dhyana (meditation) on the symptoms of Raktagata Vata (essential hypertension), blood pressure, and Hamilton's anxiety rating scale.Methods: This clinical study was conducted on 50 cases of Raktagata Vata, and these were randomly divided into two subgroups: (1) Control and (2) intervention consisting of 25 cases in each subgroup. Yogic practices were done regularly for 3 months by the registered cases in both subgroups. Light medication of first order initially was also prescribed to intervention subgroup.Result: In both subgroups, significant results (p<0.001) were observed and most of the symptoms of Raktagata Vata improved better in the intervention than control subgroup. Significant results (p<0.001) were also observed in blood pressure along with Hamilton's anxiety scale scoring.Conclusion: Yogic practices impact positive effects on Agya Chakra (hypothalamus-cerebral system), control autonomic nervous system and improve the quality of life of Raktagata Vata patients by improving symptoms and regulating the blood pressure

Utilizing Alike Neighbor Influenced Similarity Metric for Efficient Prediction in Collaborative Filter-Approach-Based Recommendation System

The most popular method collaborative filter approach is primarily used to handle the information overloading problem in E-Commerce. Traditionally, collaborative filtering uses ratings of similar users for predicting the target item. Similarity calculation in the sparse dataset greatly influences the predicted rating, as less count of co-rated items may degrade the performance of the collaborative filtering. However, consideration of item features to find the nearest neighbor can be a more judicious approach to increase the proportion of similar users. In this study, we offer a new paradigm for raising the rating prediction accuracy in collaborative filtering. The proposed framework uses rated items of the similar feature of the ’most’ similar individuals, instead of using the wisdom of the crowd. The reliability of the proposed framework is evaluated on the static MovieLens datasets and the experimental results corroborate our anticipations

Luminescent quantum clusters of gold in transferrin family protein, lactoferrin exhibiting FRET

We report the synthesis of highly luminescent, water soluble quantum clusters (QCs) of gold, which are stabilized by an iron binding transferrin family protein, lactoferrin (Lf). The synthesized AuQC@Lf clusters were characterized using UV-Visible spectroscopy, X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), photoluminescence (PL), matrix assisted laser desorption ionization mass spectrometry (MALDI-MS), FTIR spectroscopy and circular dichroism (CD) spectroscopy along with picosecond-resolved lifetime measurements. Detailed investigations with FTIR and CD spectroscopy have revealed changes in the secondary structure of the protein in the cluster. We have also studied Forster resonance energy transfer (FRET) occurring between the protein and the cluster. The ability of the clusters to sense cupric ions selectively at ppm concentrations was tested. The stability of clusters in widely varying pH conditions and their continued luminescence make it feasible for them to be used for intracellular imaging and molecular delivery, particularly in view of Lf protection

FILLER LOADING IN THE LUMEN OR/AND CELL WALL OF FIBERS – A LITERATURE REVIEW

A review of the literature reveals potential advantages that papermakers can achieve by placing minerals in the lumens or cell walls of fibers before the pulp is formed into paper. Loading of filler into the fiber lumen by mechanical deposition or within the cell wall by in-situ precipitation has been reported to generally result in a moderate reduction in light scattering coefficient and increased strength properties of laboratory handsheets, as well as in paper manufactured with pilot plant equipment, when compared to conventional addition of filler. However, there are some exceptions to this general observation, where the fiber loading is reported to decrease the tensile strength of paper. Some related effects can be achieved by either precipitating mineral onto fiber surfaces or co-flocculating mineral particles with cellulosic fines. Challenges remain with respect to the implementation of fiber-loading concepts at a commercial scale. Also, there is a need for further research aimed at establishing high-end applications in which it may be an advantage to load cellulosic fiber cell walls or lumens with minerals or other substances

Identification of Surface Defects on Solar PV Panels and Wind Turbine Blades using Attention based Deep Learning Model

According to Global Electricity Review 2022, electricity generation from renewable energy sources has increased by 20% worldwide primarily due to more installation of large green power plants. Monitoring the renewable energy assets in those large power plants is still challenging as the assets are highly impacted by several environmental factors, resulting in issues like less power generation, malfunctioning, and degradation of asset life. Therefore, detecting the surface defects on the renewable energy assets would facilitate the process to maintain the safety and efficiency of the green power plants. An innovative detection framework is proposed to achieve an economical renewable energy asset surface monitoring system. First capture the asset's high-resolution images on a regular basis and inspect them to detect the damages. For inspection this paper presents a unified deep learning-based image inspection model which analyzes the captured images to identify the surface or structural damages on the various renewable energy assets in large power plants. We use the Vision Transformer (ViT), the latest developed deep-learning model in computer vision, to detect the damages on solar panels and wind turbine blades and classify the type of defect to suggest the preventive measures. With the ViT model, we have achieved above 97% accuracy for both the assets, which outperforms the benchmark classification models for the input images of varied modalities taken from publicly available sources

A Resilient Power Distribution System using P2P Energy Sharing

The adoption of distributed energy resources (DERs) such as solar panels and wind turbines is transforming the traditional energy grid into a more decentralized system, where microgrids are emerging as a key concept. Peer-to-Peer (P2P) energy sharing in microgrids enhances the efficiency and flexibility of the overall system by allowing the exchange of surplus energy and better management of energy resources. This work analyzes the impact of P2P energy sharing for three cases - within a microgrid, with neighboring microgrids, and all microgrids combined together in a distribution system. A standard IEEE 123 node test feeder integrated with renewable energy sources is partitioned into microgrids. For P2P energy sharing between microgrids, the results show significant benefits in cost, reduced energy dependence on the grid, and a significant improvement in the system's resilience. We also predicted the energy requirement for a microgrid to evaluate energy resilience for the control and operation of the microgrid. Overall, the analysis provides valuable insights into the performance and sustainability of microgrids with P2P energy sharing.Comment: arXiv admin note: text overlap with arXiv:2212.0231

Two distinct fluorescent quantum clusters of gold starting from metallic nanoparticles by pH-dependent ligand etching

Two fluorescent quantum clusters of gold, namely Au25 and Au8, have been synthesized from mercaptosuccinic acid-protected gold nanoparticles of 4-5 nm core diameter by etching with excess glutathione. While etching at pH ~3 yielded Au25, that at pH 7-8 yielded Au8. This is the first report of the synthesis of two quantum clusters starting from a single precursor. This simple method makes it possible to synthesize well-defined clusters in gram quantities. Since these clusters are highly fluorescent and are highly biocompatible due to their low metallic content, they can be used for diagnostic applications

Study of coronary artery disease in young population of Central India

Background: Coronary heart disease is the most common indication among cardiovascular diseases (CVD) and a major cause of mortality and morbidity. According to global burden of disease study estimates, nearly 24.8% of all deaths in India are attributable to CVD. Objectives of the current research study were to establish a correlation between varied risk factors and coronary artery disease (CAD), to determine angiographic characteristics individually in patients with multiple risk factors and to evaluate number of vessels involved in CAD.Methods: Present study was a prospective study conducted on 50 patients with acute coronary syndrome below 40 yrs of age admitted at the department of cardiology, Superspeciality hospital, NSCB medical college, Jabalpur. All patients included in the study were subjected to coronary angiography. The angiographic characteristics such as extent of CAD (characterized by the number of vessels with angiographic lesions) were determined.Results: Current study findings depicted that most of CAD patients were in age group of 36-40 years. Proportion of males was higher than females. One-fifth of patients were diabetics and 34.0% were hypertensive. It was observed that 54.0% CAD patients had history of smoking and 32.0% had history of premature CAD. Most of patients exhibited single vessel disease in CAG and left anterior descending (LAD) was the most commonly involved artery.Conclusions: Smoking was concluded as one of the major risk factor associated with CAD and most of patients exhibited single vessel disease, LAD being the most commonly involved artery. Significant number of patients with family history depicted high risk for CAD. Males were concluded to be more prone to CAD at younger age

Preparation and Evaluation of Sodium Alginate Microparticles using Pepsin

Aim: The main aim of this article is to prepare and evaluate sodium alginate microparticles and evaluate on the basis of their characterization. The drug is dissolved, encapsulated or attached to a microparticles matrix. Depending upon method of preparation microparticles were obtained. Microparticles were developed as a carrier for vaccines and other disease like rheumatoid arthritis, cancer etc. Microparticles were developed to increase the efficacy of active pharmaceutical ingredient to a specific targeted site. Material and Method: Microparticles of Sodium Alginate, Pepsin and Calcium Chloride were prepared in six batches (A-F) with different ratio of sodium alginate and calcium chloride respectively i.e. (0.25:2.5), (0.25:5), (0.25:7.5), (0.5:2.5), (0.5:5), (0.5:7.5) by using a homogenizing method. Microparticles were evaluated for particle size distribution, zeta potential and morphology. Result and Discussion:  The normal particle size of each of the six batches were analyzed by Zeta Sizer (Delsa C Particle Analyzer) and it was found that the Batch B (0.25:5) delivered the best microparticles with size distribution of 1.2731 (µm). All batches were seen under Motic magnifying microscope by using the Sulforhodamine B (M.W. 479.02) color as staining dye. Microparticles was found to be semi spherical in shape. Conclusion: Results of all the six batches was contrasted based on particle size investigation, zeta potential and morphology. Batch B (0.25:5) was considered as the best formulation. Key words:  Micro Particle, Pepsin, Sodium Alginate and Calcium Chloride, Sulforhodamine B, Zeta Sizer