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Aims: The aim of this study was to evaluate the effects of yoga-based cardiac rehabilitation (Yoga-CaRe) on the endothelial system, oxidative stress, and inflammatory markers in patients with acute myocardial infarction (MI). Methods: A sub-study was conducted in two clinical sites of the Yoga-CaRe trial (a multicenter randomized controlled trial). Participants with acute MI were randomized and allocated to either the Yoga-CaRe program (13 sessions with encouragement to home practice) or enhanced standard care (three educational sessions). Endothelial function, oxidative stress, and inflammatory biomarkers were assessed using biomarkers such as asymmetric dimethylarginine (ADMA), endothelial nitric oxide synthase (eNOS), endothelin-1 (ET-1), E-selectin, P-selectin, vascular cell adhesion molecule (VCAM), intercellular cell-adhesion molecule-1, total nitric oxide concentration (NOx), oxidized low-density lipoprotein (Oxd-LDL), superoxide dismutase, total antioxidant capacity (TAOC), tumor necrosis factor-alpha (TNFα), and C-reactive protein (CRP) at baseline and 12 weeks. Laboratory and statistical analysis were done by staff blinded to group allocation. Results: Eighty-two patients (of the 110 patients recruited) completed the study. The mean age was 53.1 ± 10.6 and 51.9 ± 10.7 years in enhanced standard care and Yoga-CaRe group, respectively. At 12 weeks, Yoga-CaRe significantly reduced ADMA, ET-1, and ICMA-1 than the enhanced standard care group. Although E-selectin and VCAM at 12 weeks were reduced in both groups, enhanced standard care had a significantly higher reduction than the Yoga-CaRe group. Among markers of oxidative stress, TAOC increased in the Yoga-CaRe group. We found no difference in eNOS, NOx, P-selectin, TNFα, CRP, and Oxd-LDL between the two groups. Conclusion: Yoga-CaRe improved the endothelial function (through a reduction in ET-1 and modulating adhesion molecules) and enhanced antioxidant capacity.

In this investigation, we employed a cost-efficient co-precipitation technique to synthesize nanostructures of Indium-doped ZnO, incorporating varying percentages of Indium (0.25 %, 0.5 %, 1 %, 2 %, and 4 %) into the ZnO lattice. These Indium atoms were introduced either by replacing oxygen (O2) or occupying tetrahedral interstitial spaces within the structure. The resultant materials exhibited an average crystal size ranging from approximately 5 to 10 nm and displayed a highly crystalline nature. The UV–visible spectroscopy of these synthesized materials, revealing an excitation spectrum spanning 380 nm–395 nm. Photoluminescence measurements showed two distinct emission peaks at 390 nm and 471 nm, originates from the recombination of the free excitons through an exciton-exciton collision process and the presence of defects or impurities in the In–ZnO nanostructures. Defects in the crystal lattice, such as oxygen vacancies or interstitial defects, can create energy levels within the bandgap. Subsequently, we evaluated the suitability of these Indium-doped ZnO nanostructures for light sensor applications. Response and recovery times to infrared (IR), visible, and ultraviolet (UV) light was recorded. Remarkably, the nanostructures exhibited exceptional response and recovery times, in UV light compared to their performance with IR and visible light. This significant performance of synthesized materials in UV light shows the cost-effective co-precipitation method in fabricating Indium-doped ZnO nanostructures for UV light sensing applications.

Parking spots have become a prevalent concern in urban growth. The number of automobiles is increasing faster than accessible parking spaces. This problem is addressed by implementing an Internet of Things (IoT)-based Parking Surveillance Scheme (IoT-PSS) for the smart campus. The system aims to efficiently match vehicles with available parking spaces, resulting in time savings, improved parking space usage, reduced management expenses, and decreased traffic congestion. Edge computing provides a new answer to data processing in monitoring systems by using advancements in IoT, artificial intelligence, and transmission technologies to analyze data regionally at the edge. This research explores the viability of using edge computing for smart parking monitoring, focusing on detecting parking occupancy via a real-time video stream. The structure operating pipeline to prioritize adaptability, online surveillance, data transfer, detection precision, and system dependability. The experimental findings show that the final detection approach achieves more than 95% accuracy in real-world situations with outstanding effectiveness and reliability. The IoT-PSS system is essential for smart cities and is a strong basis for future use in smart transportation networks.

In many industries, hydrodynamic journal bearings support the rotor in rotating machineries like large turbines, generators, compressors, gearboxes, etc. where load acts in both axial as well as radial direction. Conical journal bearings are more suitable in such applications where both radial and axial load acts on rotating parts. In conical hydrodynamic journal bearings, wear occurs due to continuous use of rotating parts and frequent start-stop activity. The objective of this work is to analyze the wear influence on conical hydrodynamic journal bearing. To achieve this, both experimental and analytical methods are used in this work. Analytically, Reynold’s equation with spherical coordinate system is solved using Finite Element Analysis (FEA) method. In experimental method, Hydraulic oil of Viscosity Grade ISO VG46 is used in Conical Hydrodynamic Journal Bearing (CHJB) test rig along with 10°, 20° and 30° semi-cone angle bearings. The experimental outcomes are in good compliance with that of analytical. The result shows that unworn bearing performance is better compared to worn bearing. The results will be helpful to anticipate the actual behavior of worn conical hydrodynamic journal bearing wherever it is used like in case of blood flow pump, large turbine, etc.

The current study focuses on the impact of firecrackers emission on particulate matter (PM2.5 and PM10), carbon monoxide (CO), carbon dioxide (CO2), and total volatile organic compounds (TVOC) and the noise was analyzed on pre, during, and post-Diwali 2022 period (5 days) in a residential area of Tamil Nadu state of India. The findings demonstrated that, for 24-hour mean values of PM2.5 and PM10 concentrations over the study period were consistently higher than the NAAQS (National Ambient Air Quality Standard) permitted limit. On the day of Diwali, the mean CO concentration reaches 2.5 mg/m3, exceeding the NAAQSrecommended allowable limit of 2 mg/m3. The CO2 concentration during Diwali day is 1.8 times higher than the pre-Diwali day. In addition, the 24-hour mean concentration of TVOC during pre-Diwali, Diwali, and post-Diwali was found to be 915.21 µg/m³, 1513.52 µg/m³ and 1617.12 µg/m³ respectively which is quite higher than normal days. Furthermore, the average noise level in the study site during pre, during, and post-Diwali was found to be 57.71 dB (A), 75.5 dB (A), and 63.66 dB (A) respectively which were higher than the safer limit on the residential zone. As a result of the widespread usage of firecrackers during Diwali festivities, these pollutants are significantly increased, which may have a negative influence on the general public’s health.

The primary goal of this paper is to develop a robot capable of efficiently climbing teak wood trees and performing bud pruning tasks, thereby addressing the challenges posed by labor scarcity in farming. Teak wood cultivation has been significantly affected by the lack of skilled labor, necessitating a minimum of five tree climbs per year for successful cultivation. The proposed robot design features an ‘X’ frame structure with conical-shaped rollers positioned at the bottom, connected to two DC motors. These motors can be controlled remotely to enable vertical movement along the tree. To ensure secure attachment, springs are utilized to fasten the robot model to the tree. At the top of the robot, an appropriately arranged motor-driven chainsaw is installed to execute high-speed bud pruning. Overall, this robot will be helpful to automate the pruning process through sustainable development.The bud pruning robot described consists of an ‘X’ frame design with two conical-shaped rollers at the bottom.These rollers are connected to two DC motors, which are controlled by a remote, allowing the robot to move up and down the tree.To ensure stability and secure attachment to the tree, springs are utilized to firmly fasten the robot in place. The top of the frame is equipped with a high-speed DC motor to which a chainsaw is attached for the purpose of pruning buds.

The Automatic UPS Battery Maintenance System is an innovative and technologically advanced solution developed to optimize the upkeep of Uninterruptible Power Supply (UPS) battery cells. Utilizing precision sensors and real-time data analysis, the system intelligently assesses the electrolyte levels and triggers automated distilled water replenishment when necessary. By eliminating the need for manual water level checks and refilling, the system minimizes the risk of under filled batteries, which can lead to decreased battery lifespan and compromised performance. User-friendliness is a cornerstone of the system’s design. It features an intuitive interface that provides users with a comprehensive view of battery health, water levels, and system status. In the event of anomalies, the system promptly issues notifications and alerts, ensuring timely response and minimizing potential disruptions during power outages. Key advantages of the Automatic UPS Battery Maintenance System include prolonged battery lifespan through reduced plate corrosion and sulfation, consistent and uninterrupted power supply, reduced labor and time overhead, datadriven insights for informed decision-making, and environmentally responsible water usage.In conclusion, this project introduces an intelligent and efficient solution to enhance UPS battery maintenance practices. By automating the critical process of water level management, the Automatic UPS Battery Maintenance System contributes to the overall reliability and longevity of UPS batteries, making it a valuable asset for businesses and individuals reliant on continuous and dependable power supply.

Rescue operations for people trapped in deep borewells provide a serious problem needing both advanced robotic technology and human expertise. This abstract focuses on the creation of a revolutionary machine-human rescuing robot that is specifically designed to respond to emergencies in deep borewells. the complicated nature of deep borewell rescues, which includes technical challenges, time-sensitive situations, and the requirement for swift and accurate action. It draws attention to the drawbacks of conventional rescue techniques and promotes the creation of a flexible robotic system that can work in tandem with human rescuers. The suggested robot is built as a hybrid system that combines human control with autonomous functionality. To deliver real-time data and visual feedback from the borewell inside, it integrates specialized sensors, cameras, and communication tools. The borewell rescue robot’s, structural frame work consists of two cylindrical pipes fastened vertically with the help of T shaped square rod, these cylindrical pipes acts as a holding platform for children hands. Lower end of the pipes are provided with mechanical straps which in turn are actuated by BLCD motors with human rescuers is a crucial component of its functionality. Skilled operators can control the robot’s movements in real time thanks to remote operating interfaces and haptic feedback systems. The significance of the robot-human rescue team in deep borewell crises is emphasized in the abstract.

In a wireless communication system, due to the presence of the surrounding objects, the amplitude of the received signal rapidly changes by reflection, diffraction, and scattering and noise is added to the received signal. This prompts multipath fading and interference, which affects the quality of communication. The proposed Adaptive Routing Scheme (ARS) considers the algorithm Reliable Routing (RR) using Average Bit Error Rate expressed in Nakagami-m fading channel (ABERN-m) to predict the quality of the link, the Energy Efficient Routing (EER) calculates Remaining Battery Energy (RBE) to extend the network lifetime. The Canberra Distance Measure (CDM) is used instead of Euclidean Distance Measure (EDM) to improve the accuracy of distance measurement in mobile nodes. The aim of the proposed scheme is to predict the best optimal path and maintain the consistent path to enhance the Quality of Service (QoS) in real-time communication to improve efficient traffic on the road. First published online 5 June 2020

Objective: To address the architectural distortion (AD) which is an irregularity in the parenchymal pattern of breast. The nature of AD is extremely complex; still, the study is very much essential because AD is viewed as a primitive sign of breast cancer. In this study, a new convolutional neural network (CNN) based system is developed that performs classification of AD distorted mammograms and other mammograms. Methods: In the first part, mammograms undergo pre-processing and image augmentation techniques. In the other half, learned and handcrafted features are retrieved. The AlexNet Pretrained CNN is utilized for extraction of learned features. The support vector machine (SVM) validates the existence of AD. For improved classification, the scheme is tested for various conditions. Results: A sophisticated CNN based system is developed for stepwise analysis of AD. The maximum accuracy, sensitivity and specificity yielded as 92%, 81.50% and 90.83% respectively. The results outperform the conventional methods. Conclusion: Based on the overall study, it is recommended that a combination of CNN pre-trained network and support vector machine is a good option for identification of AD. The study will motivate researchers to find improved methods of high performance. Further, it will also help the radiologists. Significance: The AD can develop up to two years before the growth of any anomaly. The proposed system will play an essential role in the detection of early manifestations of breast cancer. The system will aid society to go for better treatment options for women all over the world and curtail the mortality rate.

Traumatic brain injury (TBI) is one of the major health problems worldwide that causes death or permanent disability through primary and secondary damages in the brain. TBI causes primary brain damage and activates glial cells and immune and inflammatory cells, including mast cells in the brain associated with neuroinflammatory responses that cause secondary brain damage. Though the survival rate and the neurological deficiencies have shown significant improvement in many TBI patients with newer therapeutic options, the underlying pathophysiology of TBI-mediated neuroinflammation, neurodegeneration, and cognitive dysfunctions is understudied. In this study, we analyzed mast cells and neuroinflammation in weight drop-induced TBI. We analyzed mast cell activation by toluidine blue staining, serum chemokine C-C motif ligand 2 (CCL2) level by enzyme-linked immunosorbent assay (ELISA), and proteinase-activated receptor-2 (PAR-2), a mast cell and inflammation-associated protein, vascular endothelial growth factor receptor 2 (VEGFR2), and blood-brain barrier tight junction-associated claudin 5 and Zonula occludens-1 (ZO-1) protein expression in the brains of TBI mice. Mast cell activation and its numbers increased in the brains of 24 h and 72 h TBI when compared with sham control brains without TBI. Mouse brains after TBI show increased CCL2, PAR-2, and VEGFR2 expression and derangement of claudin 5 and ZO-1 expression as compared with sham control brains. TBI can cause mast cell activation, neuroinflammation, and derangement of tight junction proteins associated with increased BBB permeability. We suggest that inhibition of mast cell activation can suppress neuroimmune responses and glial cell activation-associated neuroinflammation and neurodegeneration in TBI.

The construction and maintenance of pavement over the weak subgrade soil become the challenging task to the pavement engineering. One of the major reasons of subgrade failure of pavement is weak subgrade. The weak subgrade soil noticed a Black Cotton (BC) soil. The BC soil subgrade poses several serious problems to the pavement such as rutting, fatigue, reflecting crack and undulation of the pavement. To minimize this problem of pavement, there are many conventional stabilization techniques were adopted and reported. But these techniques are not applied effectively into the pavement to stabilize the weak subgrade. To address this problem, to give the additional strength to the pavement geosynthetics are taken as alternate material for stabilization of pavement. In the present study, an attempt is made in the laboratory with four types of coir mats by using the fabricated mould. The study is conducted in the form of two-layer pavement system. The pavement model layer is prepared as subgrade and sub-base with BC soil and sandy gravel soil respectively. The prepared fabricated mould is tested by using the Wheel Tracking Test (WTT) under moving traffic loading condition. This study concluded that the suitable placement position and the types of coir mats can be affect the performance of the LVRs. It’s also noticed that the suitable coir mats can effectively reduce the deformation, so that it can be used over the weak subgrade to improve the performance of the LVRs.

This paper presents a numerical modelling and optimization of a new ‘star-like’ geometric texture shape with an aim to improve tribological performance. Initial studies showed that the triangle effect is the most dominant in reducing the friction. Motivated with this, a ‘star-like’ texture shape consisting of a series of triangular spikes around the centre of the texture is proposed. It is hypothesised that by increasing the triangular effect on a texture shape, the converging micro-wedge effect is expected to increase, hence increasing the film pressure and reducing the friction. Using the well-known Reynolds boundary conditions, numerical modelling of surface texturing is implemented via finite difference method. Simulation results showed that the number of apex points of the new ‘star-like’ texture has a significant effect on the film pressure and the friction coefficient. A 6-pointed texture at a texture density of 0.4 is shown to be the optimum shape. The new optimum star-like texture reduces the friction coefficient by 80%, 64.39%, 19.32% and 16.14%, as compared to ellipse, chevron, triangle and circle, respectively. This indicates the potential benefit of the proposed new shape in further enhancing the hydrodynamic lubrication performance of slider bearing contacts.

Abstract In the context of the scope, time, cost, and quality constraints, failure is not uncommon in project management. While small projects have 70% chances of success, large projects virtually have no chance of meeting the quadruple constraints. While there is no dearth of research on project risk management, the manifestation of barriers to project risk management is a less dwelt topic. The success of project management is oftentimes based on the understanding of barriers to effective risk management, application of appropriate risk management methodology, proactive leadership to avoid barriers, workers’ attitude, adequate resources, organizational culture, and involvement of top management. This paper represents various risk categories and barriers to risk management in domestic and international projects through literature survey and feedback from project professionals. After analysing the various modelling methods used in project risk management literature, interpretive structural modelling (ISM) and MICMAC analysis have been used to analyse interactions among the barriers and prioritize them. The analysis indicates that lack of top management support, lack of formal training, and lack of addressing cultural differences are the high priority barriers, among many others.

In this study, Taguchi method is used to investigate the effect of critical process parameters of investment casting on dimensional variations of thin walled, complex geometrical stainless steel component. A set of experiments have been conducted to calculate shrinkages which is a measure of dimensional variation. The process parameters considered here are number of ceramic coats, pouring time, pouring temperature, and casting cooling rate. The signal-to-noise ratio and analysis of variance are used to study the influence of these parameters on shrinkage. Optimized condition for reduced shrinkage deviation can be obtained by selecting lower number of ceramic coats, faster and laminar metal pouring, lower superheated metal temperature, and faster cooling rate. Analysis of variance reports that the number of ceramic coats is the most significant parameter with more than 80% contribution whereas other parameters are insignificant. Investigation results also indicate that constraint dimension (width) has 25%–27% higher dimensional variability than non-constraint dimensions (height) for the selected component.

Mast cell activation plays an important role in stress-mediated disease pathogenesis. Chronic stress cause or exacerbate aging and age-dependent neurodegenerative diseases. The severity of inflammatory diseases is worsened by the stress. Mast cell activation-dependent inflammatory mediators augment stress associated pain and neuroinflammation. Stress is the second most common trigger of headache due to mast cell activation. Alzheimer’s disease (AD) is a progressive irreversible neurodegenerative disease that affects more women than men and woman’s increased susceptibility to chronic stress could increase the risk for AD. Modern life-related stress, social stress, isolation stress, restraint stress, early life stress are associated with an increased level of neurotoxic beta amyloid (Aβ) peptide. Stress increases cognitive dysfunction, generates amyloid precursor protein (APP), hyperphosphorylated tau, neurofibrillary tangles (NFTs), and amyloid plaques (APs) in the brain. Stress-induced Aβ persists for years and generates APs even several years after the stress exposure. Stress activates hypothalamic-pituitary adrenal (HPA) axis and releases corticotropin-releasing hormone (CRH) from hypothalamus and in peripheral system, which increases the formation of Aβ, tau hyperphosphorylation, and blood-brain barrier (BBB) disruption in the brain. Mast cells are implicated in nociception and pain. Mast cells are the source and target of CRH and other neuropeptides that mediate neuroinflammation. Microglia express receptor for CRH that mediate neurodegeneration in AD. However, the exact mechanisms of how stress-mediated mast cell activation contribute to the pathogenesis of AD remains elusive. This mini-review highlights the possible role of stress and mast cell activation in neuroinflammation, BBB, and tight junction disruption and AD pathogenesis.

Mast cells are localized throughout the body and mediate allergic, immune, and inflammatory reactions. They are heterogeneous, tissue-resident, long-lived, and granulated cells. Mast cells increase their numbers in specific site in the body by proliferation, increased recruitment, increased survival, and increased rate of maturation from its progenitors. Mast cells are implicated in brain injuries, neuropsychiatric disorders, stress, neuroinflammation, and neurodegeneration. Brain mast cells are the first responders before microglia in the brain injuries since mast cells can release prestored mediators. Mast cells also can detect amyloid plaque formation during Alzheimer's disease (AD) pathogenesis. Stress conditions activate mast cells to release prestored and newly synthesized inflammatory mediators and induce increased blood-brain barrier permeability, recruitment of immune and inflammatory cells into the brain and neuroinflammation. Stress induces the release of corticotropin-releasing hormone (CRH) from paraventricular nucleus of hypothalamus and mast cells. CRH activates glial cells and mast cells through CRH receptors and releases neuroinflammatory mediators. Stress also increases proinflammatory mediator release in the peripheral systems that can induce and augment neuroinflammation. Post-traumatic stress disorder (PTSD) is a traumatic-chronic stress related mental dysfunction. Currently there is no specific therapy to treat PTSD since its disease mechanisms are not yet clearly understood. Moreover, recent reports indicate that PTSD could induce and augment neuroinflammation and neurodegeneration in the pathogenesis of neurodegenerative diseases. Mast cells play a crucial role in the peripheral inflammation as well as in neuroinflammation due to brain injuries, stress, depression, and PTSD. Therefore, mast cells activation in brain injury, stress, and PTSD may accelerate the pathogenesis of neuroinflammatory and neurodegenerative diseases including AD. This review focusses on how mast cells in brain injuries, stress, and PTSD may promote the pathogenesis of AD. We suggest that inhibition of mast cells activation and brain cells associated inflammatory pathways in the brain injuries, stress, and PTSD can be explored as a new therapeutic target to delay or prevent the pathogenesis and severity of AD.

Alzheimer’s disease (AD) is characterized by the presence of neuropathological lesions containing amyloid plaques (APs) and neurofibrillary tangles (NFTs). AD is associated with mitochondrial dysfunctions, neuroinflammation and neurodegeneration in the brain. We have previously demonstrated enhanced expression of the proinflammatory protein glia maturation factor (GMF) in glial cells near APs and NFTs in the AD brains. Parahippocampal gyrus consisting of entorhinal and perirhinal subdivisions of temporal cortex is the first brain region affected during AD pathogenesis. Current paradigm implicates oxidative stress-mediated neuronal damage contributing to the early pathology in AD with mitochondrial membrane potential regulating reactive oxygen species (ROS) production. The inner mitochondrial membrane anion transporters called the uncoupling proteins (UCPs), function as regulators of cellular homeostasis by mitigating oxidative stress. In the present study, we have analyzed the expression of GMF and mitochondrial UCP2 and UCP4 in the parahippocampal gyrus of AD and non-AD brains by immunostaining techniques. APs were detected by thioflavin-S fluorescence staining or immunohistochemistry (IHC) with 6E10 antibody. Our current results suggest that upregulation of GMF expression is associated with down-regulation of UCP2 as well as UCP4 in the parahippocampal gyrus of AD brains as compared to non-AD brains. Further, GMF expression is associated with up-regulation of inducible nitric oxide synthase (iNOS), the enzyme that induces the production of nitric oxide (NO), as well as nuclear factor kB p65 (NF-κB p65) expression. Also, GMF appeared to localize to the mitochondria in AD brains. Based on our current observations, we propose that enhanced expression of GMF down-regulates mitochondrial UCP2 and UCP4 thereby exacerbating AD pathophysiology and this effect is potentially mediated by iNOS and NF-κB. Thus, GMF functions as an activator protein that interferes with the cytoprotective mechanisms in AD brains.