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COVID‐19 pandemic has impacted many nations, causing physical as well as mental health concerns globally. In most countries, governments enforced strict lockdowns and social distancing, thus affecting people's daily lives. People usually tweet their views on online platforms that is unstructured text with implicit meaning. With the evolution of artificial intelligence in the natural language processing domain, the prediction of sentiments accurately has become a challenge. To contribute as a solution to this, a hybrid approach is proposed for sentiment prediction with the use of an evolutionary‐based approach, transfer‐based learning and machine learning. The proposed approach uses bidirectional encoder representations from transformers (BERT) with genetic algorithm (GA) and support vector machine (SVM), namely, hybrid evolutionary intelligent model (GA‐BERT‐SVM). These approaches aid in extracting important features considering semantics and context present in the text. To avoid the limitations of the backpropagation approach, such as trapping in local minima and overfitting the data, the initial parameters (weights and biases) of the dense layers has been optimized using GA. Additionally, the pretrained BERT layers are utilized without any modification, following a standard transfer learning approach. The BERT embeddings are concatenated with the SVM for training and classification. GridSearchCV and GeneticSearchCV is used for obtaining optimal parameters of SVM. A multi‐classification problem is tackled using a benchmark COVID‐19 dataset, which comprises of Twitter data and is categorized into COVIDSENTI‐A, COVIDSENTI‐B, COVIDSENTI‐C and a combined dataset called COVIDSENTI. Experimental evaluation demonstrates promising results of the proposed model in terms of accuracy, F1‐score, precision and recall, surpassing state‐of‐the‐art approaches. [ABSTRACT FROM AUTHOR]

Context: Schiff base-containing metal complexes have been the subject of extensive research. In this work, a coordination polymer-derived complex called [Cu(L)] that is solution-stable (L = 2-(2-hydroxybenzylidene-amino)phenol) has been explored theoretically with five different pyridyl-based ligands using DFT/TDDFT in order to understand the structural–functional and electronic transitions of these five complexes. Frontier molecular orbital (FMO) analysis was carried out to assess the reactivity behavior of all five complexes. For the purpose of studying the charge energy distribution over complexes, electrostatic potential maps were also drawn. Furthermore, in order to identify any stabilizing interactions that may be present in the given complexes, an NBO analysis was studied. To learn more about any potential correlations between the properties of these five complexes, a comparative analysis was explored. Our calculations demonstrate that complex 3 having pyridine-4-carboxamide as a ligand has a lower energy gap and a higher negative electrostatic potential which may indicate its higher reactivity and this may be due to the electron withdrawing group (carboxamide). TDDFT results show that the highest light harvesting efficiency (LHE) of all the studied complexes is found in the range of 440–448 nm. Complexes 1, 2, and 4 show the higher light harvesting efficiency as compared to complexes 3 and 5. Our findings are in good accordance with the available experimental data. Methods: All DFT computations were performed using the Gaussian16 with unrestricted B3LYP-D2 functional with the basis sets 6-31G(d,p) for O, N, C, and H while LanL2DZ for Cu. The polarized continuum model (PCM) was used for the solvation. The software GaussView6.1 was utilized for the modeling of initial geometries and the plotting of MEP maps. The NBO6.0 program which is incorporated in Gaussian16 was utilized to investigate the bonding nature and stabilization energies of the complexes. The ORCA program was used to simulate the absorption spectra. [ABSTRACT FROM AUTHOR]

Brain Computer Interface is an emerging technology for assisting patients having long term disability. Electroencephalography is the best technique for recording neural activities, however, recording bio signal data from patients is a hectic task. Therefore, Data augmentation using generative adversarial networks is expected to solve this problem. In this paper, we present temporal generative adversarial network with conditional input labels to learn the spatio-temporal features of electroencephalograph and generate realistic data. In order to evaluate the performance of proposed model, we introduce qualitative, quantitative and feature visualization techniques on motor imagery electroencephalograph dataset. Further, we used 1-dimensional temporal convolutional neural network to investigate whether augmented data can replace real data or not for training models. The presented data augmentation framework was compared to three more data augmentation techniques like: copula generative adversarial network, conditional tabular generative adversarial network and tabular variational autoencoder. Our presented technique showed significantly better results to other data augmentation techniques for Electroencephalograph data. The experimental results show that the value of Kullback–Leibler Divergence (KL Divergence) and Inverted Kolmogorov Smirnov D static test (KS test) of data generated by proposed model is the lowest i.e., 0.8940 and 0.7674 respectively. Further, we have tested exhaustively our new data and used a new testing strategy achieving an accuracy of 94.1%. Finally, it is concluded that a time series-based data augmentation technique for Electroencephalograph can reduce long calibration process and thus improve the overall performance of motor imagery user action classification. [ABSTRACT FROM AUTHOR]

Background: Feed intolerance during early postnatal period is common in newborns with meconium-stained liquor (MSL). Prophylactic gastric lavage in neonates delivered with MSL and its recommendation by some pediatric textbooks, despite negligible scientific evidence and evidencebased recommendations. Aims and Objectives: This study was designed with the objective of determining if gastric lavage in all babies with MSL led to the development of less feed intolerance as compared to those who were not subject to the procedure. Materials and Methods: The present study was a randomized control trial, conducted at National Medical College and Teaching Hospital, Birgunj, from December 01, 2021, to November 30, 2022. The study populations were 280 vigorous neonates with ≥34 weeks of gestation and ≥1800 g delivered with MSL. Among them, 140 neonates were kept in the lavage and non-lavage group. Data were analyzed using the Chi-square test, odds ratio, and level of significance at P<0.05. Results: Thirty-two (22.85%) and 54 (38.57%) neonate in the lavage and no lavage group developed the first episode of vomiting with a significant P=0.005. No significant difference in the incidence of feed intolerance was found (8.57% vs. 15%, P=0.099). None of the neonates in either group developed any complications during the procedure. Conclusion: Gastric lavage seems to reduce the first episode of vomiting but not overall feed intolerance in vigorous infants born through meconium-stained amniotic fluid. Hence, concluded that gastric lavage should be reserved for treating the rather rare feed intolerance than routine prophylactic in vigorous neonates delivered with MSL. [ABSTRACT FROM AUTHOR]

Density functional theory is applied to account the ligand effect on modification in the redox potential of coordination of three NN bidentate ligands (bpy/phen) to the metal ion (Fe2+/3+/Co2+/3+). Also, the role of the ligand framework for the stabilization of [M(bpy/phen)3]2+/3+ species is discussed in detail. In this work, we have found that the M2+ ions are more stabilized with the bpy ligands while the M3+ ions are more stable with the phen ligands. The electronic structure and geometrical study disclosed the electronic configurations of the metal ions in both the possible spin states of a species. Furthermore, the HOMO–LUMO analysis demonstrates that the M3+ ion coordinated species have more energy gap as compared to the M2+ ion coordinated species. Among all the species, HOMO–LUMO energy gap has been found highest (4.62 eV) in the [Fe(bpy)3]3+ whereas lowest (3.28 eV) in the [Co(phen)3]2+ species. Additionally, we have also found that the bpy coordinated species have relatively higher redox potential value as compared to phen ligated species. Here we have noticed a close relationship between the redox potential and the optimized structural parameters of the studied species. Also, all the computed structural parameters of the studied species are in good agreement with the experimental data. [ABSTRACT FROM AUTHOR]

Background: The present study was conducted to estimate the prevalence and distribution of MSDs in different anatomical regions among Doctors and NO and to determine their ergonomic risk factors and predictors. Methods: This cross-sectional study was conducted in an apex institution in Western India. The socio-demographic information, medical and occupational history, and other personal and work-related attributes were captured using a semi-structured questionnaire, which was developed and finalized by piloting on 32 participants (who were not part of the study). Nordic Musculoskeletal and International Physical Activity Questionnaires were used to assess MSDs and Physical activity. Data were analyzed using SPSS v.23. Prevalence of Musculoskeletal Symptoms (M.S.), Multisite Musculoskeletal Symptoms (MMS), and Widespread Musculoskeletal Symptoms (WMS) were calculated. A comparison was made to estimate the burden and distribution of MSD among Doctors and Nursing officers. Logistic regression was applied to identify the predictors of MSDs and pinpoint the risk factors associated with MSDs. Results: A total of 310 participants, of which 38.7% were doctors, and 61.3% were Nursing Officers (NOs) were included in the study. The mean age of the respondents was 31.63 ± 4.9 years. Almost 73% (95%CI: 67.9–78.1) of participants had MSD in the last 12 months, with approximately 41.6% (95%CI: 36.1–47.3) suffering from MSDs in the previous seven days of the survey. The lower back (49.7%) and the neck (36.5%) were the most affected sites. Working in the same position for a long time (43.5%) and not taking adequate breaks (31.3%) were the highest self-reported risk factors. Females had significantly higher odds of having pain in the upper back [aOR:2.49(1.27–4.85)], neck [aOR:2.15(1.22–3.77)], shoulder [aOR:2.8 (1.54–5.11)], hips [aOR:9.46 (3.95–22.68)] and knee [aOR:3.8(1.99–7.26)]. Conclusions: Females, who are NOs, work for > 48 h per week, and fall in the obese category were significantly at more risk of developing MSDs. Working in an awkward position, treating an excessive number of patients in a day, working in the same position for a long period, performing repeated tasks, and not having enough rest breaks were significant risk factors for MSDs. [ABSTRACT FROM AUTHOR]

Background. Meningiomas are the most frequent tumors of the brain and spinal cord with a potency to recur in around one third of the cases and and invade surrounding tissue. Hypoxia driven factors like HIFs (Hypoxia inducible factors) are implicated in tumor cell growth and proliferation. Aim. This study aims at determining the association of HIF 1 α with different histopathological grades and types of meningiomas. Methods. This prospective study was conducted on 35 patients. The patients presented with headache (65.71%), seizures (22.86%) and neurological deficits (11.43%). They underwent surgical excision and surgical tissue samples of these patients were histopathologically processed and microscopically graded and typed. Immunohistochemistry was performed using anti-HIF 1α monoclonal antibody. The nuclear expression of HIF 1 α was graded as <10%: negative, 11-50%: mild to moderate positive, >50%: strong positive. Results. Of the 35 cases so examined 20% were recurrent; 74.29% were WHO grade I with meningothelial type (22.86%), being the commonest; 57.14 % revealed mild to moderate positivity for HIF 1α, while strong positivity was noted in 28.57%. Significant association was found between WHO grade and HIF 1α (p=0.0015) and between histopathological types and HIF 1α (p=0.0433). Furthermore, HIF 1α was also significantly associated with the recurrent cases (p=0.0172). Conclusion. HIF 1α appears to be a marker and a promising target for effective therapeutics in meningiomas. [ABSTRACT FROM AUTHOR]

Background: Indian Diabetic Risk Score (IDRS) and Community Based Assessment Checklist (CBAC) are easy, inexpensive, and non-invasive tools that can be used to screen people for Metabolic Syndrome (Met S). The study aimed to explore the prediction abilities of IDRS and CBAC tools for Met S. Methods: All the people of age ≥30 years attending the selected rural health centers were screened for Met S. We used the International Diabetes Federation (IDF) criteria to diagnose the Met S. ROC curves were plotted by taking Met S as dependent variables, and IDRS and CBAC scores as independent/prediction variables. Sensitivity (SN), specificity (SP), Positive and Negative Predictive Value (PPV and NPV), Likelihood Ratio for positive and negative tests (LR+ and LR-), Accuracy, and Youden's index were calculated for different IDRS and CBAC scores cut-offs. Data were analyzed using SPSS v.23 and MedCalc v.20.111. Results: A total of 942 participants underwent the screening process. Out of them, 59 (6.4%, 95% CI: 4.90–8.12) were found to have Met S. Area Under the Curve (AUC) for IDRS in predicting Met S was 0.73 (95%CI: 0.67–0.79), with 76.3% (64.0%-85.3%) sensitivity and 54.6% (51.2%-57.8%) specificity at the cut-off of ≥60. For the CBAC score, AUC was 0.73 (95%CI: 0.66–0.79), with 84.7% (73.5%-91.7%) sensitivity and 48.8% (45.5%-52.1%) specificity at the cut-off of ≥4 (Youden's Index, 2.1). The AUCs of both parameters (IDRS and CBAC scores) were statistically significant. There was no significant difference (p = 0.833) in the AUCs of IDRS and CBAC [Difference between AUC = 0.00571]. Conclusion: The current study provides scientific evidence that both IDRS and CBAC have almost 73% prediction ability for Met S. Though CBAC holds relatively greater sensitivity (84.7%) than IDRS (76.3%), the difference in prediction abilities is not statistically significant. The prediction abilities of IDRS and CBAC found in this study are inadequate to qualify as Met S screening tools. [ABSTRACT FROM AUTHOR]

Background: This study aimed to explore the perception of doctors regarding telemedicine consultations and the level of patient satisfaction with the services received through teleconsultations. Methods: This cross-sectional study was conducted on clinicians who provided teleconsultations and patients who received teleconsultations in an Apex healthcare institution in Western India. Semi-structured interview schedules were used to record the quantitative and qualitative information. Clinicians' perceptions and patients' satisfaction were assessed using two different 5-point Likert scales. Data were analyzed using SPSS v.23 using non-parametric tests (Kruskal Wallis and Mann-Whitney U). Results: A total of 52 clinicians who delivered teleconsultations and 134 patients who received teleconsultations from those doctors were interviewed in this study. For 69% of doctors, telemedicine was feasible to implement, and for the rest, it was challenging. Doctors believe telemedicine is convenient for patients (77%) and prevents the transmission of infection (94.2%). Difficulty in clinical evaluation (73%), communication (55.7%), network connectivity (34%), diagnosis and investigations (32%), and patients' e-illiteracy (32%) were the most common challenges faced by clinicians. Patients' experiences were positive in terms of ease of registration (82.1%), audio quality (100%), freedom to discuss medicine (94.8%), and comprehension of the diagnoses (88.1%). Patients expressed satisfaction with the length of the teleconsultation (81.4%), the advice and care they received (78.4%), and the manner and communication of the clinicians (78.4%). Conclusions: Though there were some challenges in the implementation of telemedicine, the clinicians perceived it quite helpful. The majority of the patients were satisfied with teleconsultation services. Difficulty in registration, lack of communication, and a deep-rooted mindset of physical consultations were the primary concerns from the patient side. [ABSTRACT FROM AUTHOR]

Mesothelioma is an aggressive lung cancer, harms the linings of the lungs. It is one of the deadliest cancers diagnosed in those exposed to fibrous silicate minerals (asbestos). Millions of people face severe consequences as they are diagnosed at late stages. This study presents a comparison of several machine learning approaches with distinct feature sets and addresses the issue of class imbalance. The dataset used in this study is available publicly on the University of California Irvine (UCI) machine learning repository. This study used the resampling technique, synthetic minority oversampling technique (SMOTE) , and adaptive synthetic sampling (ADASYN) to handle the class imbalance. Most of the machine learning strategies performed well with the resampling technique. The best accuracy using the resampling strategy was achieved by artificial neural networks (ANN). The highest accuracy was recorded on the feature set selected by principal component analysis (PCA) is 96%. Overall, ensemble techniques performed well. The proposed stacking-based classifier achieved the highest accuracy (89%) on data balanced using SMOTE and ADASYN. [ABSTRACT FROM AUTHOR]

Production systems have been growing exponentially in size in recent decades. One of the problems in the manufacturing system is that a need of effective and efficient materials transportation between the workstations. Auto-mated guided vehicles (AGV's) can provide a satisfactory solution to this issue. Because of this, AGV's is a one of the most important material handling tool used in flexible manufacturing system (FMS). The designing, scheduling and routing of the AGV's are the key issues for the reason that performance of AVG's in flexible manufacturing system depends on these parameters. The failure of AGVs may significantly impact the operation and efficiency of the entire system, and it is a critical issue. In this paper the aims to answer How the reliability of individual AGVs in the system assessed?, and How AGVs affects the performance of the whole FMS system?. It was also discussed that optimizing techniques to improve the performance of AGV in FMS. This paper discussed the details studies of approaches and optimization techniques used for optimizing AGV's in FMS including design and their control. [ABSTRACT FROM AUTHOR]

Cancer is a complex worldwide health concern that resulted in 10 million cancer deaths in 2018; hence, early cancer detection is crucial. Early detection involves developing more precise technology that offers information about the patient's cancer, allowing clinicians to make better-informed treatment options. This study provides an in-depth analysis of multiple cancers. This study also exhibits a good survey of the machine or deep learning techniques used in cancer research. Also, the study proposed a stacking-based multi-neural ensemble learning method's prediction performance on eight datasets, including the benchmark datasets like Wisconsin Breast cancer dataset, mesothelioma, cervical cancer, non-small cell lung cancer survival dataset, and prostate cancer dataset. This study also analyzes the three real-time cancer datasets (Lung, Ovarian & Leukemia) of the Jammu and Kashmir region. The simulation findings indicate that the methodology described in our study attained the highest level of prediction accuracy across all types of cancer data sets. Additionally, the proposed approach has been statistically validated. The purpose of this investigation was to develop and evaluate a prediction model that might be used as a biomarker for malignancy based on anthropometric, clinical, imaging, and gene data. [ABSTRACT FROM AUTHOR]

Friction stir welding is a novel technique for joining ferrous and non-ferrous materials in a solid state. The groove fill techniques are most popular and generally used by researchers to dope reinforcement in the FSWed zone to improve the properties of joints. The main drawback of this technique is that a few amounts of reinforcement material come out from the groove during the fabrication of the joint. In the present work, the adhesive-assisted reinforcement technique was used to overcome this problem for the fabrication of particulates reinforced friction stirred weld joint. In the present work, the aluminum alloy plate edges were coated with a thin layer of TiB2. The coated and non-coated edge plates were joined using friction stir welding at the rotational speed of 1400 and 2240 rpm, and welding speed of 32 mm/min using a taper threaded pin tool. The tensile strength of coated edge plate welded joints was found highest in comparison to non-coated joints which was 39.74% superior. The percentage elongation of coated edge joint was observed about 1.5 times lower than the non-coated edge plate joint. The flexure strength of TiB2 reinforced coated edge joint was found about 1.5 times higher. However, the impact strength of coated edge plate was found nearly three times lower than the uncoated edge joints. The TiB2 coated edge joints reveal 22.75% higher hardness than the non-coated edge plate joints welded at the rotational speed of 2240. [ABSTRACT FROM AUTHOR]

Background: There is a paucity of research to demonstrate the quantification of adolescents' risk behavior toward Non-Communicable Diseases (NCD) in India. This study aims to explain the knowledge of schoolaged adolescents about NCD and whether their knowledge is truly translating into lifestyle changes and if not, what are the potential underlying factors responsible for that. Methodology: A school-based cross-sectional study was conducted on adolescents in Jodhpur district, India, in grades 6 to 12. The data was gathered via a semi-structured questionnaire. The participant's weight and height were assessed using a digital weighing machine and a stadiometer, respectively. SPSS v.23 was used to analyze the data. Univariate (chi-square) and multivariate (logistic regression) analysis were used to quantify knowledge and risk factors, and inferences were derived. Results: A total of 1010 students participated in the study. The mean scores of knowledge and risk behavior were 32.82+6.43 (out of 40) and 9.23+2.63 (out of 30), respectively.Adolescent risk behavior and knowledge were not found to be significantly related. Physical activity, spending fewer hours sitting, not skipping breakfast, and habit of fruit and vegetable consumption were significant factors for a healthy lifestyle among them. Conclusion: Due to differences in underlying predictors, adolescents' understanding of NCDs did not translate into healthy lifestyle modifications. These findings highlight the importance of developing tailored interventions for adolescents that target identified risk domains. [ABSTRACT FROM AUTHOR]

This study investigated the effects of fly ash and wood flour fillers on mechanical and dynamic mechanical properties (DMP) of Acacia arabica fiber (AAF) reinforced polyester hybrid composites. Mechanical properties such as hardness, tensile, flexural and impact strengths were studied. The experimental data of mechanical tests show that wood flour marginally enhanced the bending strength and modulus while fly ash filler performed 17% and 39% increase in hardness and interfacial shear strength of AAF/polyester hybrid composite. Scanning electron microscope (SEM) analysis proves that good adhesion present between the fibers and matrix. Dynamic mechanical properties such as storage modulus (E′), loss modulus (E″), Damping (Tanδ) and glass transition temperature (Tg) of prepared composite samples were investigated using the dynamic mechanical analyzer. The fly ash filler composite has reported 5% increase in the maximum value of Tg while the wood flour showed 17% increase in peak height of Tanδ curve. The experimental results indicated that the AAF with wood flour filler composite has the highest thermal stability and load bearing capacity due to strong adhesion between the fiber, filler and matrix which leads to the formation of superior performing hybrid composites for potential applications in various manufacturing industries. [ABSTRACT FROM AUTHOR]

DNA:bm-PNA duplexes endowed with all-C on either the t-amide or triazole face and mixed base sequence on the other face can be welded with silver ions through C:Ag+:C connects to give triple duplexes in one complex. The interplay of WC and Ag+-mediated duplexes leads to synergistic stability effects on both duplexes and the complex. [ABSTRACT FROM AUTHOR]

Background: The aim of the present study was to recalibrate the effectiveness of Indian Diabetes Risk Score (IDRS) and Community-Based Assessment Checklist (CBAC) by opportunistic screening of Diabetes Mellitus (DM) and Hypertension (HT) among the people attending health centres, and estimating the risk of fatal and non-fatal Cardio-Vascular Diseases (CVDs) among them using WHO/ISH charts.Methods: All the people aged ≥ 30 years attending the health centers were screened for DM and HT. Weight, height, waist circumference, and hip circumferences were measured, and BMI and Waist-Hip Ratio (WHR) were calculated. Risk categorization of all participants was done using IDRS, CBAC, and WHO/ISH risk prediction charts. Individuals diagnosed with DM or HT were started on treatment. The data was recorded using Epicollect5 and was analyzed using SPSS v.23 and MedCalc v.19.8. ROC curves were plotted for DM and HT with the IDRS, CBAC score, and anthropometric parameters. Sensitivity (SN), specificity (SP), Positive Predictive Value (PPV), Negative Predictive Value (NPV), Accuracy and Youden's index were calculated for different cut-offs of IDRS and CBAC scores.Results: A total of 942 participants were included for the screening, out of them, 9.2% (95% CI: 7.45-11.31) were diagnosed with DM for the first time. Hypertension was detected among 25.7% (95% CI: 22.9-28.5) of the participants. A total of 447 (47.3%) participants were found with IDRS score ≥ 60, and 276 (29.3%) with CBAC score > 4. As much as 26.1% were at moderate to higher risk (≥ 10%) of developing CVDs. Area Under the Curve (AUC) for IDRS in predicting DM was 0.64 (0.58-0.70), with 67.1% SN and 55.2% SP (Youden's Index 0.22). While the AUC for CBAC was 0.59 (0.53-0.65). For hypertension both the AUCs were 0.66 (0.62-0.71) and 0.63 (0.59-0.67), respectively.Conclusions: IDRS was found to have the maximum AUC and sensitivity thereby demonstrating its usefulness as compared to other tools for screening of both diabetes and hypertension. It thus has the potential to expose the hidden NCD iceberg. Hence, we propose IDRS as a useful tool in screening of Diabetes and Hypertension in rural India. [ABSTRACT FROM AUTHOR]

Background: The aim of the present study was to recalibrate the effectiveness of Indian Diabetes Risk Score (IDRS) and Community-Based Assessment Checklist (CBAC) by opportunistic screening of Diabetes Mellitus (DM) and Hypertension (HT) among the people attending health centres, and estimating the risk of fatal and non-fatal Cardio-Vascular Diseases (CVDs) among them using WHO/ISH charts. Methods: All the people aged ≥ 30 years attending the health centers were screened for DM and HT. Weight, height, waist circumference, and hip circumferences were measured, and BMI and Waist-Hip Ratio (WHR) were calculated. Risk categorization of all participants was done using IDRS, CBAC, and WHO/ISH risk prediction charts. Individuals diagnosed with DM or HT were started on treatment. The data was recorded using Epicollect5 and was analyzed using SPSS v.23 and MedCalc v.19.8. ROC curves were plotted for DM and HT with the IDRS, CBAC score, and anthropometric parameters. Sensitivity (SN), specificity (SP), Positive Predictive Value (PPV), Negative Predictive Value (NPV), Accuracy and Youden's index were calculated for different cut-offs of IDRS and CBAC scores. Results: A total of 942 participants were included for the screening, out of them, 9.2% (95% CI: 7.45–11.31) were diagnosed with DM for the first time. Hypertension was detected among 25.7% (95% CI: 22.9–28.5) of the participants. A total of 447 (47.3%) participants were found with IDRS score ≥ 60, and 276 (29.3%) with CBAC score > 4. As much as 26.1% were at moderate to higher risk (≥ 10%) of developing CVDs. Area Under the Curve (AUC) for IDRS in predicting DM was 0.64 (0.58–0.70), with 67.1% SN and 55.2% SP (Youden's Index 0.22). While the AUC for CBAC was 0.59 (0.53–0.65). For hypertension both the AUCs were 0.66 (0.62–0.71) and 0.63 (0.59–0.67), respectively. Conclusions: IDRS was found to have the maximum AUC and sensitivity thereby demonstrating its usefulness as compared to other tools for screening of both diabetes and hypertension. It thus has the potential to expose the hidden NCD iceberg. Hence, we propose IDRS as a useful tool in screening of Diabetes and Hypertension in rural India. [ABSTRACT FROM AUTHOR]

Cancer is one of the leading causes of death in the world. Cancer research is vital as the prognosis of cancer enables clinical applications for patients. In this study, we have proposed the Stacked Ensemble Model (Stacking of bagged and boosted learners) for the automatic disease diagnosis. The experimental results prove the superiority of the proposed method to conventional machine learning techniques. In the empirical study, the performance of eight data handling methods and 14 classification methods is compared to obtain prediction results. The performance of the model has been evaluated on five benchmark datasets. The appreciable Area under the Curve scores achieved by the proposed methodology on Cervical Cancer (0.98), Mesothelioma (0.93), Breast Cancer (0.99), Prostate Cancer (0.97), and Hepatitis‐C Virus (0.998) datasets make this work more significant than the previously published works. The experimental results show that our proposed method is superior to conventional machine learning techniques and the proposed model contributes in the form of an efficient computational model. [ABSTRACT FROM AUTHOR]

A class imbalance problem plays a vital role while dealing with classes with rare number of instances. Noisy class imbalanced datasets create considerable effect on the machine learning classification of classes. Data resampling techniques commonly used for handling class imbalance problem show insignificant behavior in noisy imbalanced datasets. To cure curse of data resampling technique in noisy class imbalanced data, we have proposed improved hybrid bag-boost with proposed resampling technique model. This model contains proposed resampling technique used for handling noisy imbalanced datasets. Proposed resampling technique comprises K-Means SMOTE (Synthetic Minority Oversampling TEchnique) as an oversampling technique and edited nearest neighbor (ENN) undersampling technique used as noise removal. This resampling technique is used to mitigate noise in imbalanced datasets at three levels, i.e. first clusters datasets using K-Means clustering technique, SMOTE inside clusters for handling imbalance by inducing synthetic instances of class in minority and lastly, using ENN technique to remove instances that create noise afterwards. Experiments were performed using 11 binary imbalanced datasets by varying attribute noise percentages, and by using area under receiver operating curve as performance metrics. Experimental results confirmed that proposed model shows better results than the rest. Moreover, it is also confirmed that proposed technique performs better with an increased noise percentage in binary imbalanced datasets. [ABSTRACT FROM AUTHOR]

• The rise of the rotating target holder rise in temperature due to impact of deuterium ion beam. • The effectiveness of cooling of rotating target holder with changing water parameters like mass flow rate and changing the rotational speed of the rotating target holder to limit its temperature rise within 100 ºC. • Study the various results with change of speed of rotating target holder and flow parameters, to optimize the parameters to finalise the best parameters for system. An accelerator based 14-MeV neutron generator is installed at Institute for Plasma Research, Gandhinagar to generate high energy neutrons by using a water-cooled rotating tritium target. In this device, neutrons would be generated from the nuclear reaction 3H(D, n)4He by bombarding accelerated deuterium ions on a solid tritium target. The rotating target holder mainly consists of a rotating copper disc water-cooled case mounted on the rotating shaft. The high-energy deuterium ion beam impacted on solid TiT target fitted on the copper case imparting its energy to the case. This energy is taken away from the system through the water passing through the annulus cavity of the shaft. This paper presents details of the engineering CFD (computed fluid dynamics) analysis carried out for optimizing two important parameters of the rotating target. Firstly optimization of the location of flow parameters of the water as mass flow rate and Secondly optimization of speed of the rotating target and the design of fins inside the copper case. [ABSTRACT FROM AUTHOR]

Introduction. MGMT (O-6-methylguanine-DNA methyl transferase) is a DNA repair enzyme with implications on chemoresistance and subsequent patient prognosis. This study investigated the association of MGMT with the various grades and subtypes of gliomas and evaluated the associated clinical outcome of these patients. Methods. This observational longitudinal follow up study spun over a period of 36 months and included 33 patients with primary glioma who underwent surgical interventions and chemoradiotherapy at a tertiary care center in Kolkata. The surgical samples were processed and histopathologically typed. Immunohistochemical analysis was done using anti-MGMT antibody and MGMT status was determined. Patients were followed up for 3 years. Results. Males were 1.3 times more commonly affected by gliomas. Mean age was 42.9 years for females and 47.2 years for males. Frontal lobe was the most commonly involved site whereas focal neurological deficit was the most common symptom. Karnofsky performance score was higher for low grade gliomas and lower for high grade gliomas (p=0.04). Significant association was found between histopathological grade and MGMT immunoexpression (p=0.0001) as well as histopathological subtype and MGMT status (p=0.0036). On follow up, mean survival of the patients was 25.4 months. Significant association was found between MGMT status and survival of the patients (p=0.0437). Conclusion. MGMT immunoexpression is significantly associated with different grades and subtypes of gliomas. In addition, MGMT has significant implications on chemoresistance and patient survival. Hence, MGMT expression should be mandatorily checked before starting the chemotherapy. [ABSTRACT FROM AUTHOR]

Aims: The indigenously developed Indian Council of Medical Research (ICMR)-NIV COVID Kavach IgG enzyme linked immunosorbent assay (ELISA) has been recommended for seroprevalence among vulnerable populations in India, which provided essential services throughout the lockdown. The staff working in the High Court was one such group. We compared anti-SARS-CoV-2 IgG seropositivity among the staff of Jodhpur and Jaipur High Courts, Rajasthan, India. Methods: Asymptomatic judiciary staff of Jodhpur and Jaipur benches of High Courts were enrolled after informed written consent. A questionnaire was filled and 3--5 ml venous blood was collected from participants. The ICMR-NIV COVID Kavach IgG ELISA and EUROIMMUN IgG ELISA were used for detection of Anti-SARS-CoV-2 IgG antibodies. Results: A total of 63 samples (41 from Jodhpur and 22 from Jaipur) were collected between 28th July to 4th August 2020. The overall anti-SARS-CoV-2 IgG seroprevalence was found to be 6.35%. Seropositivity was higher among the staff from Jaipur (13.64%) as compared to Jodhpur (2.44%). The Kavach ELISA results were in complete agreement with EUROIMMUN ELISA. The infection control measures were deemed effective. Conclusion: Seroprevalence among the staff of Jodhpur High Court was found to be lower than Jaipur, reflecting higher susceptibility to COVID-19 in the former. Many offices worldwide are closed till mid 2020 but need to come up with pre-emptive policies eventually. This study may help to anticipate the possible challenges when other government/private offices start functioning. The infection control practices of one workplace may help formulate guidelines for other offices. [ABSTRACT FROM AUTHOR]

A radial turbine is one of the vital components of a helium liquefaction plant. The design of a turbine becomes critical due to its compact size and high‐speed configuration. In this study, numerical optimization has been performed for the three‐dimensional steady flow of helium gas in the radial inflow turbine of a helium liquefaction plant at a nominal condition. The mean line design is an appropriate method to obtain the approximate results. The computational fluid dynamics simulation algorithm is adopted in this study to reach the final results and Ansys CFX is used for the simulation. From the analysis, it has been reported that the number of rotor blades was overestimated in the mean line design. Performance parameters like total‐ to‐static efficiency and velocity ratio were also found to be optimum numerically under a preliminary design condition. Finally, power of 1.7 kW was achieved at total‐to‐static efficiency of 71.4%. The deviation in analytical and numerical results is within ±10% for performance as well as geometric parameters. [ABSTRACT FROM AUTHOR]

19 in India. Methodology: This was a descriptive analysis of the COVID-19 cases and their outcomes between 1st March to 31st May 2020 in India. Unpaired t-test and ANOVA were used to determine the statistical differences. Linear regression models were prepared to estimate the effect of testing on the fatalities. The Infection Fatality Rate (IFR)/Case Fatality Rate (CFR), doubling time, and Basic Reproduction Number (R0) per week were calculated. Results: Two-thirds of the cases were between 21-50 years of age, while three-fourth of deaths were among people above 50-years of age. The mean age of people infected with COVID-19 was declining throughout the study period. The mean age of infected males and females was significantly different. The male-female ratio of both infection and deaths due to COVID-19 was near about 2:1. IFR/CFR was 3.31 (95% CI = 3.13-3.50) in April, which reduced to 2.84 (95% CI = 2.77-2.92) in May. An incremental trend was observed in the recovery rates (9.42% to 48.18%), tests conducted / million population (12 / million to 2708 / million) and doubling time (3.59 to 17.71 days). The number of tests was significantly influencing the fatalities (ß = 0.016, 95% CI = 0.012-0.020). The overall R0 was found to be 1.72. Conclusions: Public health interventions were likely effective in containing the spread of COVID-19. There is a need to further improve the testing capacity. The high-risk category of individuals being prioritized for hospital admission should be redefined to include individuals older than 50 years. [ABSTRACT FROM AUTHOR]

The Pine Leaf tree is a high altitude plant that is mostly found in the Himalayan region. The pine leaf ash contains the hard compound of Si, Ca, K, Mg, and Fe which make it an alternative cost-effective reinforcement material for composites. In this paper, the surface composite of aluminum alloy reinforced with Pine Leaf Ash was developed by friction stir process (FSP) with varying tool feed rate using different profile pin tool at constant 1400 rpm. The effects of tool pin profile and feed rate on hardness and tribological properties of the fabricated surface composite were reported. It was found that composite fabricated at 56 mm/min feed rate with threaded taper pin tool exhibited highest hardness and lowest wear rate amongst all fabricated composites. The hardness and wear properties of composite fabricated with threaded pin tool improved 15.81 and 18.13%, respectively. [ABSTRACT FROM AUTHOR]

Epigenetics functions as a bridge between host genetic & environmental factors, aiding in human health and diseases. Many immune-related diseases, including infectious and allergic diseases, have been linked to epigenetic mechanisms, particularly DNA methylation. In this review, we summarized an updated overview of DNA methylation and its importance in personalized medicine, and demonstrated that DNA methylation has excellent potential for disease prevention, diagnosis, and treatment in a personalized manner. The future implications and limitations of the DNA methylation study have also been well-discussed. [ABSTRACT FROM AUTHOR]

Drug–target interaction is the intercommunication between chemical drugs and target proteins to produce any kind of change in the human body. The laboratory experiments conducted to recognize these potential intercommunications are costly and tedious. Various computational methods have been established recently, including the chemogenomic approach for identifying drug–target intercommunication, that integrates the chemical data of the drugs and the genomic properties of the proteins for identifying the interactions between them. This paper proposes a novel technique based on hybrid ensemble to predict drug target interactions. Hybrid ensembles introduce diversity in classification that helps to improve the performance of prediction. The proposed method has been evaluated by comparing the technique with state–of‐the‐art methods on two different databases under three cross‐validation settings. The comparison clearly shows that the technique produced significant improvement in the interaction prediction. [ABSTRACT FROM AUTHOR]

Friction stir welding is a novel solid-state welding process for joining aluminum alloy components. The heat generation, proper mixing of joint line material and properties of welds depends on the profiles of friction stir tools. Aluminum alloy Al 1120 plates were welded via friction stir welding using deferent friction stir tools. The effects of tool pin profile on mechanical properties were reported in this paper. The result reveals that weld joints formed with a taper threaded pin tool exhibited better tensile and flexure strength. However, welds formed with a cylindrical threaded pin tool showed higher hardness and impact strength. [ABSTRACT FROM AUTHOR]

Rice serves as one of the essential staple food for half of the global human population. However, due to rapid human population growth, there is an increase in food demand across the globe. Thus, to lessen the gap between food demand and supply, there is an urgent requirement for grain yield enhancement in various important cereals crops, including rice. In the present study, the authors attempted to characterize haplotypes and single nucleotide polymorphisms associated with Gn1a for high grain number formation in rice plants. Result obtained reveals that high grain number gene sequences are under balancing selection and four high grain number specific missense SNPs decreases the stability of Gn1a. Earlier studies have also suggested that decreases Gn1a expression causes cytokinin accretion in inflorescence meristems, which in turn led to increase in grain yield. Hence, these four SNPs may be utilized for increasing grain yield in rice plants. • Strong association between panicle number & tiller number and panicle length & grain number. • High grain number gene sequences are under balancing selection. • Four high grain number specific missense SNPs decreases the stability of Gn1a. • Decreases Gn1a expression led to increase in grain yield. [ABSTRACT FROM AUTHOR]

Estrogen increases bone formation by promoting mineralization and prolonging the lifespan of osteoblasts. To understand the underlying molecular mechanism/s, we identified estrogen-regulated proteins at different stages of human osteoblast differentiation using differential proteomics approach. Among the identified proteins, we observed that estrogen upregulated RAB3GAP1 on day 1 and 5 of differentiation. RAB3GAP1 is critically involved in the process of autophagy, a eukaryotic degradative pathway essential for cell survival. We, therefore, investigated the effect of estrogen on autophagy in differentiating human osteoblasts and their precursors, the mesenchymal stem cells (MSCs). MSCs exhibited high autophagic flux which declined during osteoblast differentiation, resulting in high basal apoptosis in osteoblasts. Estrogen reduced apoptosis in differentiating osteoblasts by promoting autophagy, thus contributing towards their longer lifespan. Further, MSCs were resistant against starvation-induced apoptosis, whereas, differentiating osteoblasts showed significant susceptibility towards it. Estrogen, in addition to promoting mineralization, protected differentiating osteoblasts from starvation-induced apoptosis by increasing autophagic flux. Autophagic flux in RAB3GAP1 knockdown osteoblasts appeared diminished, and showed increased apoptosis even in nutrient-rich conditions, and exhibited significantly impaired mineralization. However, irrespective of the presence of estrogen, starvation further enhanced apoptosis in these cells. Furthermore, estrogen failed to promote mineralization in these osteoblasts. Our study illustrates that autophagy is essential for human osteoblast survival and mineralization, and osteoblasts are susceptible to apoptosis due to reduced autophagy during differentiation. Estrogen, via upregulation of RAB3GAP1, promotes autophagy in osteoblasts during differentiation thereby increasing their survival and mineralization capacity. Our study demonstrates the positive role of autophagy in bone homeostasis. • Autophagy reduces during human osteoblast differentiation. • Osteoblasts are therefore susceptible to basal and starvation-induced apoptosis. • Estrogen upregulates RAB3GAP1 and promotes autophagy in differentiating osteoblasts. • Estrogen prolongs lifespan of osteoblasts by averting their apoptosis. • Estrogen fails to protect autophagy-impaired/RAB3GAP1-silenced cells from apoptosis. [ABSTRACT FROM AUTHOR]

Rice serves as the major food for almost half of the world population. Because of its origin in the tropical and subtropical area, rice is more sensitive towards cold stress. Three homologs of DREB1, namely DREB1A, DREB1B and DREB1C are induced Queryduring cold stress and after binding with GCC-box in the promoter region of the target gene, they enhance cold tolerance in rice plants. Though the majority of DREBs bind GCC-box, the degree of activation varies among DREBs. The protein encoded via these three transcription factors contains a common domain, namely AP2/ERF. In silico method was utilised to predict 3D structure of each AP2/ERF domain. The molecular dynamic analysis suggests, under the normal environmental condition, in each AP2/ERF domain, a positive correlation exists between β-strands and the movement of C-α is constrained. However, during cold stress, when AP2/ERF domain binds with GCC-box present in the promoter region of the target gene, mean pressure of each three AP2/ERF domain gets lowered and final potential energy increases. A positive correlation between β-strands gets disrupted and C-α experiences random movement suggesting enhanced activity of DREB1A, DREB1B and DREB1C during cold stress and enhancement of cold tolerance in plants. Further, MM/PBSA calculations for protein–DNA affinities reveal that, due to lack of α2 in DREB1C, the binding affinity of GCC-box with AP2/ERF domain of DREB1A > DREB1B > DREB1C. Thus, due to a better binding affinity with GCC-box, DREB1A and DREB1B can be utilised in near future for increasing cold tolerance of rice plant and increasing yield. [ABSTRACT FROM AUTHOR]

Abstract In silico approach was utilised to identify differentially expressed key hub genes during BPH infestation on Bt rice plant, under laboratory conditions. Re-analysis of GSE74745 data with in-house R scripts and STRING database reveals that only 5 key hub genes, namely Os05g0176100, Os06g0683200, Os07g0208500, Os07g0252400 and Os07g0424400, belonging to cellulose synthase family, are differentially expressed and have confidence score ≥0.9 among themselves. Conserve domain analysis of all proteins encoded via these 5 key hub genes reveals that they have a common cellulose synthase domain, in which "Plant-Conserved Region" (PCR) is highly conserved. After binding with other domains of cellulose synthase proteins or other accessory proteins, like sucrose synthase, PCR serves as a metabolic channel to deliver UDP-Glucose, which is the main substrate for cellulose synthesis, into the active site of cellulose synthase and initiate cellulose synthesis. Simulation study of recently solved topological model of PCR [PDB ID: 5JNP] and molecular docking studies of PCR with UDP-glucose reveals that, during BPH infestation, in nearby phloem tissue where BPH suck sap, there is an increase interaction of UDP-glucose with PCR and other accessory proteins which in turn increases both the stability of PCR and the production of cellulose, finally causing callose deposition at that site and hence causing longer nymphal developmental period and lower fertility of BPH infested on Bt rice. In near future, these differentially identified 5 hub genes could be possible targets for controlling BPH infestation in rice plant under field conditions and increasing rice yield globally. Graphical abstract Image 1 Highlights • Re-analysis of GSE74745 reveals 5 key hub genes. • All 5 key hub genes have cellulose synthase domain. • PCR of cellulose synthase when bind UDP-glucose initiate cellulose synthesis. • High cellulose synthesis at BPH infestation site form causing callose deposition. [ABSTRACT FROM AUTHOR]

Highlights • T2D related 115 DEGs from GEO dataset & 233 from GWAS catalog were identified. • Protein-protein interaction of 348 DEGs identified 99 key hub genes. • Five genes (CCL2, ELMO1, VEGFA, FOS, & TCF7L2) playing major role in T2D. • Target miRNA, TFs and potential drugs identified for T2D hub genes. Abstract Diabetes mellitus is clinically characterized by hyperglycemia. Though many studies have been done to understand the mechanism of Type 2 Diabetes (T2D), however, the complete network of diabetes and its associated disorders through polygenic involvement is still under debate. The present study designed to re-analyze publicly available T2D related microarray raw datasets present in GEO database and T2D genes information present in GWAS catalog for screening out differentially expressed genes (DEGs) and identify key hub genes associated with T2D. T2D related microarray data downloaded from Gene Expression Omnibus (GEO) database and re-analysis performed with in house R packages scripts for background correction, normalization and identification of DEGs in T2D. Also retrieved T2D related DEGs information from GWAS catalog. Both DEGs lists were grouped after removal of overlapping genes. These screened DEGs were utilized further for identification and characterization of key hub genes in T2D and its associated diseases using STRING, WebGestalt and Panther databases. Computational analysis reveal that out of 99 identified key hub gene candidates from 348 DEGs, only four genes (CCL2, ELMO1, VEGFA and TCF7L2) along with FOS playing key role in causing T2D and its associated disorders, like nephropathy, neuropathy, rheumatoid arthritis and cancer via p53 or Wnt signaling pathways. MIR-29, and MAZ_Q6 are identified potential target microRNA and TF along with probable drugs alprostadil, collagenase and dinoprostone for the key hub gene candidates. The results suggest that identified key DEGs may play promising roles in prevention of diabetes. [ABSTRACT FROM AUTHOR]

Abstract Estrogen insufficiency at menopause cause accelerated bone loss due to unwarranted differentiation and function of osteoclasts. Unraveling the underlying mechanism/s may identify mediators of estrogen action which can be targeted for improved management of osteoporosis. Towards this, we analyzed the effect of 17β-estradiol on the proteomes of differentiating human osteoclasts. The major proteomic changes observed included upregulation of LYN by estrogen. We, therefore, investigated the effect of estrogen on osteoclast differentiation, survival, and function in control and LYN knockdown conditions. In control condition, estrogen treatment increased the apoptosis rate and suppressed the calcium signaling by reducing the intracellular Ca2+ levels as well as expression and activation of NFATc1 and c-Src during differentiation, resulting in reduced osteoclastogenesis. These osteoclasts were smaller in size with reduced extent of multinuclearity and produced significantly low levels of bone resorbing enzymes. They also exhibited disrupted sealing zone formation with low podosome density, impaired cell polarization and reduced resorption of dentine slices. Interestingly, in LYN knockdown condition, estrogen failed to induce apoptosis and inhibit activation of NFATc1 and c-Src. Compared to effect of estrogen on osteoclast in control condition, LYN knockdown osteoclasts did not show reduction in production of bone resorbing enzymes and had defined sealing zone formation with high podosome density with no impairment in cell polarization. They resorbed significant area on dentine slices. Thus, the inhibitory action of estrogen on osteoclast was severely restrained in LYN knockdown condition, demonstrating the importance of LYN as a key mediator of the effect of estrogen on osteoclastogenesis. Highlights • Differentiation, survival and activity of osteoclasts is inhibited by estrogen. • This inhibitory effect on osteoclasts is restrained in LYN knockdown condition. • Estrogen upregulates LYN expression and activation during osteoclastogenesis. [ABSTRACT FROM AUTHOR]

This research work was focussed on investigating the influence of size of hexagonal boron nitride (hBN) on the tribological performance of oils. Hexagonal boron nitride–added oils were developed using polyisobutylene succinimide as a dispersant (1 wt%) for hBN (4 wt%) particles in base oil. Dynamic light scattering–based studies were conducted to evaluate the stability of oils quantitatively. Physical properties evaluation was done for density, kinematic viscosity, and flashpoint. Tribo‐investigations were performed for anti‐wear and extreme‐pressure performance on 4‐ball tester. Anti‐wear and extreme‐pressure performance increased by ≈60% and ≈30%, respectively, for nano‐hBN–added oil, while 5 micron particles proved least performers among the selected sizes of hBN. Worn surfaces examination was done through scanning electron microscopy, energy‐dispersive X‐ray analysis, and atomic force microscopy. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Highly crystalline Zn 2 SiO 4 nanorods have been synthesized by low-temperature hydrothermal route. • A decrease in the optical band gap (5.05 eV) was observed. • Zn 2 SiO 4 nanorods exhibited very high dielectric constant of about 212. Abstract Highly crystalline zinc silicate (Zn 2 SiO 4 ) nanorods have been synthesized by a cost-effective low-temperature hydrothermal route. X-ray diffraction analysis confirmed the crystalline willemite Zn 2 SiO 4 phase of nanorods. The average diameter and length of nanorods were found to be 50 nm and 1–2.5 μm, respectively in electron microscopy studies. An absorption band in the range of 200–300 nm and a significant reduction in the optical band (5.05 eV) gap was observed in UV–Vis studies. Zn 2 SiO 4 nanorods exhibited a very high dielectric constant of about 270 which is almost ten fold higher than that of bulk Zn 2 SiO 4. Observation of high dielectric constant and band gap reduction makes Zn 2 SiO 4 nanorods suitable for optoelectronics, phosphors and various nano-electronics devices applications. [ABSTRACT FROM AUTHOR]

This paper reports about comparative performance evaluation of oils with and without graphite particles (nanometre, sub-micrometre and micrometre), in order to understand the influence of size of particles on anti-wear (AW) and extreme pressure (EP) properties as well as the physical properties of oils. The results indicated that the nano-particles (NPs) exhibited highest improvement as AWA (50%) and EPA (80%). The scanning electron microscopy on worn surfaces, however, proved to be least effective to correlate the wear performance with the surface topography and size of particles in oil. AFM, proved to be very effective in correlating the tribo-performance with sizes of particles and understand the wear mechanisms. Surface characterization was also carried out by XPS to understand the film compositions. [ABSTRACT FROM AUTHOR]

Solid lubricants (SLs) are known to enhance the tribo-performance of oils significantly. Current work focusses on issue of exploration of combination of SLs in different amounts along with dispersant (Polyisobutylene succinimide −1 wt% const.) for possible synergism. Hexagonal boron nitride (hBN) and polytetrafluoroethylene (PTFE) are known as anti-friction, Anti-wear additives. PTFE is also known as an effective extreme-pressure (EP) additive. A series of oils based on Group III (Gr III) as base oil containing PIBSI (1%) along with increasing amount of hBN (0–4%) and simultaneous decrease in PTFE (4–0%) were prepared. The tribo-performance of oils was evaluated on 4 ball tester for EP (weld load) and anti-wear performance. Formulations were characterized for physical properties density, viscosity, flash point. Also the stability of oils was observed using Dynamic Light Scattering studies. Results revealed the inclusion of these two SLs showed better tribo-performance (43% in Weld Load) than with presence of PTFE in oil. The characterization of wear and a possible wear mechanism was given by observing the worn surface under a scanning electron microscope and energy dispersive X-ray analysis. [ABSTRACT FROM AUTHOR]

• Radiation analysis of SMARTEX-C to estimate the maximum temperature on different parts. • Detailed thermal hydraulic analysis of cooling and baking scheme attached externally around the vessel and over the flanges of SMARTEX-C. • A possible cooling scheme has been designed to resolve the high temperature of different parts of vessel with limited external surface area. • Pressure drop, heat transfer coefficient and temperature have been evaluated for the designed cooling and baking scheme. In this paper, a unified cooling and baking scheme has been designed and analyzed, which aids in maintaining the vacuum levels of an experimental system SMARTEX-C. It is a SM all A spect R atio T oroidal Ex periment in a 'C' (SMARTEX-C) shaped geometry. It is a trap meant for confining electron plasma i.e. non-neutral plasma. A vacuum ∼ (1.5 ± 0.5) x 10−10 mbar is maintained inside the vessel. Electrons are emitted from a heated tungsten filament, which eventually deteriorates the vacuum of the vessel with time. To perform reproducible electron plasma experiments it is essential to maintain vacuum levels constant. The designed cooling scheme helps in maintaining it. Additionally, flow of hot Nitrogen has been incorporated in this scheme which serves baking of the vacuum vessel making the dedicated baking system redundant and makes the operation of the system hassle-free. The scheme is modeled in CATIA© and analyzed in ANSYS CFX©. The thermal-hydraulic performance has been analyzed and parametric results in terms of temperature, heat transfer coefficient and pressure drop have been provided for the cooling and baking of the vessel. [ABSTRACT FROM AUTHOR]

The human upper airway is comprised of many anatomical volumes. The obstructions in the upper airway volumes are needed to be diagnosed which requires volumetric segmentation. Manual segmentation is time-consuming and requires expertise in the field. Automatic segmentation provides reliable results and also saves time and effort for the expert. The objective of this study is to systematically review the literature to study various techniques used for the automatic segmentation of the human upper airway regions in volumetric images. PRISMA guidelines were followed to conduct the systematic review. Four online databases Scopus, Google Scholar, PubMed, and JURN were used for the searching of the relevant papers. The relevant papers were shortlisted using inclusion and exclusion eligibility criteria. Three review questions were made and explored to find their answers. The best technique among all the literature studies based on the Dice coefficient and precision was identified and justified through the analysis. This systematic review provides insight to the researchers so that they shall be able to overcome the prominent issues in the field identified from the literature. The outcome of the review is based on several parameters, e.g., accuracy, techniques, challenges, datasets, and segmentation of different sub-regions. Flowchart of the search process as per PRISMA guidelines along with inclusion and exclusion criteria. [ABSTRACT FROM AUTHOR]

Introduction: Breast cancer remains a leading cause of unintended death among Indian women. Cancer treatment-induced pain, fatigue, nausea/vomiting, body image, and sexual problems could affect the patient psychosocial well-being and quality of life (QOL). The study aims to determine the QOL and psychosocial well-being among women with breast cancer. Materials and Methods: A cross-sectional survey completed by 244 women with breast cancer at a tertiary level teaching hospital. The European Organisation for Research and Treatment of Cancer QOL Questionnaire C30, the Breast Module (QLQ-BR23), and the Hospital Anxiety and Depression Scale (HADS) is used to measure the QOL, and psychological well-being, respectively. Appropriate descriptive and inferential statistics are applied to compute the results. Results: The total number of women with breast cancer interviewed was 244, with a mean age of 45.06 (standard deviation ± 11.17) years. The mean global health score was 70.97 ± 15.63. As per the QLQ-C30 scale, "physical functioning" scored the highest (70.54 ± 22.00), and "role functioning" reported the lowest (49.45 ± 36.15) mean score. Further, on the QLQ-C30 symptoms scale, "appetite loss" (45.09 ± 35.09) was the worst reported symptom, followed by "nausea and vomiting" (34.97 ± 38.39). On the BR-23 scale, body image said (68.42 ± 22.28) higher score than other domains and experience of arm-related problems (43.80 ± 26.06) were more frequently reported symptom in women. As per the HADS scale, 24.6% and 36.1% of women were in moderate anxiety and depression, respectively. The mean HADS score was 14.39 ± 5.82. Findings on predictors for the individual patient remained the same as that earlier published literature. Conclusions and Recommendations: Women with breast cancer have an overall good QOL and poor psychosocial well-being. However, using a holistic approach, including identifying psychological problems and their time management, signifies the need for the studied population. [ABSTRACT FROM AUTHOR]

In-silico attempt was made to identify the key hub genes which get differentially expressed in biliary stricture and hepatic carcinoma. Gene expression data, GSE34166, was downloaded from the GEO database, which contains 10 biliary stricture samples (4 benign control and 6 malignant carcinoma), for screening of key hub genes associated with the disease. R packages scripts were identified 85 differentially expressed genes. Further these genes were uploaded in WebGestalt database and identified nine key genes. Using STRING database and Gephi software, the protein-protein interaction networks were constructed and also studied gene ontology through WebGestalt. Finally, we identified four key genes ( CXCR4 , ADH1C , ABCB1 and ADH1A ) are associated with liver carcinoma and further cross-validated with Liverome, Protein Atlas database and bibliography. In addition, transcription factors and their binding sites also studied. These identified hub genes and their transcription factors are the probable potential targets for possible future drug design. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM) is one of the most lethal brain tumors with an inadequately understood pathophysiology. Biomarkers that guide accurate diagnosis and treatment decisions would greatly support precision medicine for GBM. Previous studies of GBM have focused on signaling pathways such as epidermal growth factor receptor (EGFR), platelet-derived growth factor receptors (PDGFRs), notch, wnt, and others, identified with single omics technology platforms (genomics, transcriptomics, or proteomics), but not with their integrated use. In this context, we report here a multi-omics pathway view, expanded through integration of the expression data at transcriptomic and proteomic levels, followed by selection of a functionally related group of proteins such as kinases deregulated in GBM. By using this strategy, we observed a highly significant enrichment of the gonadotropin-releasing hormone (GnRH) signaling pathway that was not deciphered with single omics datasets. The curation of the GnRH pathway with extensive literature analysis brought about a comprehensive annotation of the pathway, which included several additional pathway members that were not previously annotated. A targeted search resulted in identification of additional nonkinase members of the pathway in the GBM multi-omics datasets. We found evidence of GnRH receptor expression in GBM and other cancers. We offer here an updated generic pathway map of GnRH signaling, show its enrichment in the context of GBM, and discuss its plausible cross-connectivity with EGFR, wnt, calcium, and focal adhesion kinase signaling pathways that were earlier shown to be the top deregulated pathways in GBM. In conclusion, this study demonstrates the promise of multi-omics research and analyses to better understand complex cancers and suggests continued efforts and research in this direction in the field of integrative biology. [ABSTRACT FROM AUTHOR]

Background: Lack of access to information and education makes women more susceptible to acquire HIV/AIDS. Self-help groups (SHGs) are seen as instruments for empowering women in the community. Realizing this, it was hypothesized that if the strategy to train SHG women brings significant improvement in the knowledge of study population about HIV/AIDS; then this strategy may be a financially sustainable and practicable method in rural India. Objective: Empower and engage the SHG women against HIV/AIDS by creating awareness and sustaining interest through lesson plans in the IEC material. Methods: This was a 'Multi-centric Action Research Demonstration Study'. As an intervention, series of workshops were conducted with the help of pre-developed IEC material. 400 households (200 from each intervention and control sites) of SHG women were interviewed for baseline and end line each. Results: The planned intervention could make significant changes in level of awareness of the respondents about HIV/AIDS in terms of mode of spread, prevention and control measures and places to get tested for HIV/AIDS. This was also found effective to reduce the misconceptions regarding transmission of HIV/AIDS in the study area, thus in turn reducing the stigma attached with the disease. Conclusion: The awareness level about HIV/AIDS in rural areas among SHG women was very low and there is an urgent need and scope for development and implementation of effective interventions strategy to train local community worker which in turn can bring improvement in the knowledge of community by providing the information in culturally acceptable manner. [ABSTRACT FROM AUTHOR]

Bubble-induced vibration has become vital during recent investigation and advancement in the area of multiphase boiling. The induced vibration phenomenon can be understood with the help of proper and detailed understanding of vapor bubble formation, growth, collapse, and interaction with the surface. The growth mechanism for the formation of bubbles under nucleate boiling conditions is theoretically investigated. This paper also discusses the dynamics of vapor bubbles during flow in subcooled boiling conditions. In the part of the vapor bubble formation, the characteristics of a bubble emerged from the heated surface at a single nucleation site along with the flow boiling phenomena have been considered for analysis. The bubble is considered to be of spherical shape and detached from a heated surface due to the formation of a microlayer of liquid. The fluid is supposed to be static far away from a vapor bubble. Using well-known models of bubble formation and detachment, equations considering various forces acting over a single bubble have been derived. These equations monitor bubble characteristics in a definite manner according to the derived differential equation for energy conservation developed for the two-phase flow system. To illustrate this phenomenon, two bubble formation mechanisms, inertia-controlled and heat transfer-controlled growth have been considered. The present investigation discusses the governing equations for the bubble growth rate, bubble size and frequency, forces, and the well-known Rayleigh's equation. Also, the vibration characteristic has been reviewed, and the two phenomena, i.e., subcooled boiling induced vibration (SBIV) and flow-induced vibration (FIV) have been discussed in brief. The present review paper aims to reveal the latest evaluation done in the area of bubble-induced vibration and to ascertain the contributions made until now as well as the solution to the upcoming issues. [ABSTRACT FROM AUTHOR]

Polybenzimidazole (PBI) is a specialty polymer with highest thermal stability. However, its potential to develop composites has not yet been explored because of problems associated with processing. To overcome this problem, blend of Polyetherketone (PEK) and PBI was developed for the first time, and its mechanical and tribological properties were investigated. Further, a systematic series of composites containing solid lubricants (SLs), short fibers of glass and carbon was developed and its physical, mechanical, thermal and tribological properties were investigated. The composites with either SLs or fibers did not show good tribo-potential. However, when these were used together, performance was significantly better. When compared to the commercial composite based on PBI–PEEK blend and with similar composition, the new composites demonstrated excellent tribo-potential with very low friction coefficient ( µ )≈0.05 and specific wear rate ( K 0 )≈1×10 −16 m 3 /N m along with very high PV safe-limit value≈63 MPa m/s. [ABSTRACT FROM AUTHOR]

Proteins present in human saliva offer an immense potential for clinical applications. However, exploring salivary proteome is technically challenged due to the presence of amylase and albumin in high abundance. In this study, we used four workflows to analyze human saliva from healthy individuals which involved depletion of abundant proteins using affinity-based separation methods followed by protein or peptide fractionation and high resolution mass spectrometry analysis. We identified a total of 1256 human salivary proteins, 292 of them being reported for the first time. All identifications were verified for any shared proteins/peptides from the salivary microbiome that may conflict with the human protein identifications. On integration of our results with the analyses reported earlier, we arrived at an updated human salivary proteome containing 3449 proteins, 808 of them have been reported as differentially expressed proteins in oral cancer tissues. The secretory nature of 598 of the 808 proteins has also been supported on the basis of the presence of signal sequence, transmembrane domain or association with exosomes. From this subset, we provide a priority list of 139 proteins along with their proteotypic peptides, which may serve as a reference for targeted investigations as secretory markers for clinical applications in oral malignancies. This article is part of a Special Issue entitled: Proteomics in India. [ABSTRACT FROM AUTHOR]