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Ball bearing is used to provide free rotation around a fixed axis. Various kinds of faults exist in the bearing such as inner race fault, outer race fault and ball race fault. One very effective method to diagnose the bearing fault is vibration signal analysis. Empirical mode decomposition (EMD) has been used for ball-bearing fault diagnosis in mechanical systems using vibration signal analysis. Classification of the ball-bearing fault has always been a challenging task. Various classification schemes such as Extreme learning machine (ELM), K-means Clustering, and Support vector machine (SVM), have been reported in the literature for ball-bearing fault classification. SVM is restricted by multiclass classification efficiency, and ELM is restricted by the longer training. In this paper, the entropy analysis of the wavelet coefficient obtained from the third level decomposition of the residue signal (obtained after subtracting the highest frequency component from the raw signal) has been done for ball-bearing fault classification. A comparative analysis of the wavelet coefficient based on entropy measurement has been presented here. High fault classification accuracy has been achieved using the proposed method for the detection of ball-bearing fault. Shannon entropy, Average Shannon entropy, and Renyi's entropy are parameters for the justification of the proposed approach. The result shows the best wavelet to be chosen among the available discrete wavelet based on various entropy measurements. [ABSTRACT FROM AUTHOR]

Background: Diabetes poses a global threat, leading to hospitalizations and premature death if not managed properly. It involves tumor necrosis factor-α (TNF-α), an inflammatory cytokine, which binds to TNF-α receptor-1, triggering sphingomyelinase, and ceramide production. Vitamin D acts as an anti-inflammatory agent, reducing inflammatory cytokines and proinflammatory cell growth, and benefiting diabetes mellitus (DM). Aims and Objectives: The primary objective was to compare serum Vitamin D and TNF-α levels in diabetics and nondiabetics. The secondary objective was to explore Vitamin D and TNF-α correlation in newly diagnosed type 2 diabetes. Materials and Methods: A case-control study involved 92 subjects in each group. Data included demographics, clinical assessments, glycemic parameters, Vitamin D, and TNF-α. Statistical analysis used student's t-test and Pearson correlation (P<0.05). Results: The cohort comprised 34 females (36.96%) and 58 males (63.04%). Cases had significantly higher glycemic levels: FBG (247.2±53.92 mg/dL vs. 91.45±16.64 mg/dL), postprandial plasma glucose (319.7±72.08 mg/dL vs. 111.3±21.76 mg/dL), and glycated hemoglobin (HbA1c) (10.39±2.41% vs. 5.43±0.48%). Mean serum Vitamin D in cases (22.63 ng/mL) was significantly lower than controls (58.15 ng/mL), and mean TNF-α in cases (5.01 pg/mL) was higher than controls (4.63 pg/mL, P<0.0001). HbA1c negatively correlated with serum Vitamin D (r=-0.7461) and positively with TNF-α (r=0.7831). Vitamin D correlated negatively with TNF-α (r=-0.6481). Conclusion: The study revealed lower serum Vitamin D and higher TNF-α levels in cases, with a significant inverse association. It also found an inverse link between Vitamin D and HbA1c and a strong positive correlation between HbA1c and TNF-α. Recognizing Vitamin D and TNF-α's diagnostic significance promises innovative strategies for managing type 2 DM. [ABSTRACT FROM AUTHOR]

Background: Vitiligo is a chronic, common disease of still unknown etiology characterized by circumscribed ivory or chalky white macules of different size and shape. The pathogenesis of vitiligo is complex and still not well understood. According to autocytotoxic hypothesis, oxidative stress has been suggested to be the initial pathogenic event in melanocyte degeneration. Objective: The present study was conducted with an objective to evaluate the role of oxidative stress and antioxidant status in the pathogenesis of vitiligo. Materials and Methods: A total of sixty (60) subjects (age group 14-50 years) of both sexes were enrolled in this study. Of 60, 30 were clinically diagnosed cases of vitiligo of all types and remaining 30 were normal healthy controls. The indicator of oxidative stress was determined by measuring serum level of MDA. The role of antioxidant was determined by measuring serum levels of SOD and Vitamin C. Results: The mean serum level of MDA was significantly increased in vitiligo patients compared to controls while the mean serum level of SOD was significantly decreased in patients of vitiligo than controls. Also, Vitamin C was decreased in vitiligo compared to controls but was insignificant. Conclusion: The result of the present study demonstrates imbalance between oxidant-antioxidant system and support the associations between oxidative stress and free radical-mediated damage in the pathogenesis of vitiligo. [ABSTRACT FROM AUTHOR]

Apis mellifera, a priceless bee species is known to produce various nutritional products. Royal Jelly (RJ) is one such bee product which has high nutritive value, functional and biological qualities. However factors such as bee species, environment, season, collection technique and larval age affect the composition of RJ at macro and micro levels thus there is a need to evaluate Indian Royal Jelly (IRJ) for its chemical properties. So in the present work IRJ samples collected from Southern, Central and Northern regions of India were evaluated for physicochemical parameters (nature, color, appearance, odor, and solubility,) residual content (moisture content, ash value and pesticide content), chemical attributes (total polyphenol content, total flavonoid content,), nutraceutical potential (total fat, protein, carbohydrate content, and energy), and antioxidant activity (DPPH assay, ABTS assay and reducing power,). The total flavonoid content and total phenolic content were in the range of 0.119-0.321 mg quercetin/g of IRJ and 25.2844-68.203 mg Gallic acid/g, respectively. High energy, protein and low fat value suggested IRJ as a suitable nutraceutical agent. Antioxidant activity (IC50) of IRJ samples was found to be in the order of IRJ II > IRJ IV > IRJ I > IRJ III. Overall, it was observed that the IRJ-II showed better nutritional efficacy, polyphenolic content, and antioxidant properties. [ABSTRACT FROM AUTHOR]

Advancements in UAVs have enabled them to act as flying access points that can be positioned to create an interconnected wireless network in complex environments. The primary aim of such networks is to provide bandwidth coverage to users on the ground in case of an emergency or natural disaster when existing network infrastructure is unavailable. However, optimal UAV placement for creating an ad hoc wireless network is an NP-hard and challenging problem because of the UAV's communication range, unknown users' distribution, and differing user bandwidth requirements. Many techniques have been presented in the literature for wireless mesh network deployment, but they lack either generalizability (with different users' distributions) or real-time adaptability as per users' requirements. This paper addresses the UAV placement and control problem, where a set of genetic-algorithm-optimized potential fields guide UAVs for creating long-lived ad hoc wireless networks that find all users in a given area of interest (AOI) and serve their bandwidth requirements. The performance of networks deployed using the proposed algorithm was compared with the current state of the art on several experimental simulation scenarios with different levels of communication among UAVs, and the results show that, on average, the proposed algorithm outperforms the state of the art by 5.62 % to 121.73 % . [ABSTRACT FROM AUTHOR]

The potential of Indian propolis as a suitable therapeutic agent is still to be explored to the fullest. As variation in the chemical composition across different geographical regions has been a major concern, it is, therefore, worthwhile to systematically investigate, and assess the quality of Indian propolis and set nationalized standards. The propolis collected from three different regions were authenticated for the major plant source, followed by the evaluation of physicochemical properties. Different extraction methods were compared, with their influence on balsam content, polyphenol, and flavonoid content. The sample coded HAR using ultrasonication gave the highest extraction yield of 71.87%. Further, the process variables in the ultrasonication method (i.e. Amplitude, extraction time, the concentration of ethanol) at three levels were optimized using the Box-Behnken response design. The model was found significant with the concentration of ethanol having a maximum influence on the responses. The model was successfully verified by setting the amplitude at 48%, extraction time to 5.6 mins, and ethanol concentration to 87% v/v. The extraction efficiency of 83.86±1.17% was achieved with a substantial diminution of extraction time. The total phenolic, total flavonol, and total flavanone content of the optimized batch were 28.74±0.13 mgGAE/g, 4.66±0.78 mgQE/g, and 3.16±0.14 mgPE/g of propolis respectively. Further HPTLC fingerprint image of the optimized extract revealed the presence of quercetin, p-coumaric acid, kaempferol, chrysin, pinocembrin, and galangin. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) cell line MDA-MB-231 is known for Warburg metabolism and defects in mitochondria. On the other hand, dipeptidyl peptidase-IV (DPP-IV) inhibitors such as sitagliptin and vildagliptin and GLP-1 agonist exendin-4 are known to improve mitochondrial functions as well as biogenesis, but no study has evaluated the influence of these drugs on mitochondrial biogenesis on metastatic breast cancer cell line. We have recently reported anticancer effects of 5-aminoimidazole-4-carboxamide riboside on MDA-MB-231 cells via activation of AMP-dependent kinase (AMPK), which activates the downstream transcription factors PGC-1α,PGC-1β, or FOXO1 for mitochondrial biogenesis; above-mentioned incretin-based therapies are also known to activate AMPK. This study evaluated the effects of sitagliptin, vildagliptin, and exendin-4 on MDA-MB-231 cells and the underlying changes in mitochondrial biogenesis, were examined. Treatment with sitagliptin (100 µM), vildagliptin (100 µM), and exendin-4 (10 nM) for 72 h to MDA-MB-231 cells led to a decrease in viability indicated by MTT assay, cell migration by scratch, and transwell migration assays, accompanied with marginal reduction in cell numbers along with the apoptotic appearance, the rate of apoptosis, and decreased lactate content in conditioned medium. These changes in the cancer phenotype were accompanied by an increase in the mitochondrial DNA to nuclear DNA ratio, increased MitoTracker green and red staining, and increased expression of transcription factors PGC-1α, NRF-1, NRF-2, TFAM, and HO-1. Pre-treatment of cells with these incretin-based drugs followed by 48 h treatment with 1 µM doxorubicin increased doxorubicin sensitivity as observed by a decrease in viability by MTT assay. Thus, sitagliptin, vildagliptin, and exendin-4 exert their beneficial effects on TNBC cells via an increase in mitochondrial biogenesis that helps to switch Warburg metabolism into anti-Warburg effect. Therapeutic response was in the order of: sitagliptin > vildagliptin > exendin-4. [ABSTRACT FROM AUTHOR]

Traffic violation monitoring and control is a major concern in India due to excess crowd, increasing commuters, bad traffic signal management, and rider mentality. It is obvious that physical traffic police-based monitoring alone is insufficient to monitor such large traffic volumes and simultaneously track violations. This has led to many violators going unnoticed. The violators, in turn, cause more serious mishaps on the road resulting in danger to their own life as well as to other’s life. Thus, there is a need for incorporating Artificial Intelligence (AI)-based techniques to eliminate manual intervention for the detection and catching of violators. In this paper, we propose a system to automatically detect two-wheeler violations like not wearing a helmet, usage of a phone while riding, triple riding, wheeling, and illegal parking for Indian road scenarios and eventually automating the ticketing process by capturing the violations and corresponding vehicle number in a database. We propose using a custom trained Yolo-v4 + DeepSORT for violation detection and tracking and Yolo-v4 + Tesseract for number plate detection and extraction. This implementation obtained a mean average precision (mAP) of 98.09% for violation detection and an accuracy of 99.41% for number plate detection on the test data. Further, the system detected 77 out of 93 violations with zero false positives in real-life scenarios. Thus,showing that the traffic violation system developed can be used to automate traffic violation ticketing. The developed system would be particularly useful in deriving various safety-related policies and will help to enforce strong regulation of traffic rules and build towards a smart city ecosystem via the automated AI-based traffic violation and ticketing system. [ABSTRACT FROM AUTHOR]

Background and aim: Insulin resistance has been linked to both triglyceride-glucose index (TyG) and hypertension, and it is a major risk factor for cardiovascular disease. The present study aimed to determine the TyG index and atherogenic indices in essential hypertensive subjects and find out the association between them. Materials and Methods: In this case-control study, 250 patients with essential hypertension and 250 healthy controls were recruited and their serum lipids were analyzed using a Biosystem BA-400 chemistry analyzer. TyG index and atherogenic indices were calculated. Results: Triglyceride-glucose index was increased significantly in essential hypertension subjects compared to controls. All the atherogenic indices i.e. atherogenic index of plasma (AIP), cardiac risk ratio (CRR), and atherogenic coefficient (AC) were significantly increased in essential hypertensive subjects compared to controls. Additionally, the TyG index demonstrated a statistically significant positive association with the atherogenic index of plasma, cardiac risk ratio, and atherogenic coefficient in participants with essential hypertension. Conclusion: In conclusion, the TyG index was found to be positively associated with atherogenic indices in essential hypertension, suggesting essential hypertensive subjects are at increased risk for cardiovascular disease. [ABSTRACT FROM AUTHOR]

A running machine generates multi-frequency vibration signals which can be captured by accelerometers. Empirical mode decomposition, wavelet decomposition, and wavelet packet decomposition are the commonly used methods to decompose the multi-frequency signal. Quick fault classification, accurate signal decomposition, and fault size detection are still a problem in machines with rotary components. In the proposed work, fault diameter in rotary part of machine is detected and classified using the machine learning methods. In the first stage, we have employed empirical mode decomposition (EMD) for high-frequency noise removal. Residue signal is obtained by removing first IMF from base signal considering first IMF as a high-frequency noisy signal, followed by wavelet decomposition. Entropy of the wavelet coefficient obtained from 3rd level decomposition of residue signal is calculated which acts as an input parameter to the machine learning techniques to determine the diameter for fault. Three different sets have been taken for inner race, outer race, and ball race correspondingly. The proposed method classifies and detects the fault diameter up to 99.5%. The proposed method can be used for different types of continuous as well as discrete wavelets. [ABSTRACT FROM AUTHOR]

Extracting the features from an image is a cumbersome task. Initially, this task was performed by domain experts through a process known as hand-crafted feature design. A deep embedding technique known as convolutional neural networks (CNNs) later solved this problem by introducing the feature learning concept, through which the CNN is directly provided with images. This CNN then learns the features of the image, which are subsequently given as input to the further layers for an intended task like classification. CNNs have demonstrated astonishing performance in several practicable applications in the last few years. Nevertheless, the pursuance of CNNs primarily depends upon their architecture, which is handcrafted by domain expertise and type of investigated problem. On the other hand, for researchers who do not have proficiency in using CNNs, it has been very difficult to explore this topic in their problem statements. In this paper, we have come up with a rank and gradient descent-based optimized genetic algorithm to automatically find the architecture design of CNNs that is vigorously competent in exploring the best CNN architecture for maneuvering the tasks of image classification. In the proposed algorithm, there is no requirement for handcrafted pre- and post-processing, which implies that the algorithm is fully mechanized. The validation of the proposed algorithm on conventional benchmarked datasets has been done by comparing the run time of a graphics processing unit (GPU) throughout the training process and assessing the accuracy of various measures. The experimental results show that the proposed algorithm accomplishes better and more persistent 'classification accuracy' than the original genetic algorithm on the CIFAR datasets by using fifty percent less intensive computing resources for training the individual CNN and the entire population. [ABSTRACT FROM AUTHOR]

Programmable logic devices (PLDs) are increasing their presence in power electronics and motion control applications. With rising gate densities of PLDs, larger functionality is being incorporated. This paper looks at certain areas of motion control that are making use of PLD for faster control and in taking the processing load off the system microprocessor. Index Terms--Application-specific integrated circuits (ASICs), digital control, field-programmable gate arrays (FPGAs), hardware description languages (HDLs), motor drives.