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Lifestyle is well known to be a player in the health of society, increasing the number of concerns on lifestyle diseases accounting to increase in the mortality to the coronavirus pandemic make it more evident. The COVID-19 pandemic is a dreadful disease caused by the recently discovered coronavirus, still at large affecting the lives of millions across the globe. The lockdown and social distancing are known key factors that can slow down the spread apart from host immunity. The objective of this study is to find the effect of many lifestyle components in influencing host immunity and health. Methods: COVID lifestyle questionnaire was designed by experts and digitally circulated. The aim of the study is to determine the importance of the various lifestyle components in health, during the Covid 19 pandemic. The questionnaire was related to pandemic lockdown work style, stress, sleep, food habit, physical activity, social connectivity, personal habits, perception of health factors and healthy practices. Results: The 94 valid responses in total, and the data showed that the lifestyle component of (i) work duration was high in (n=37, 35.6%), (ii) physical stress at work was high and above in (n=49, 46.6%), mental stress at work (n=65, 61.9%), (iii) sleep -bedtime beyond 11: 00 PM (n=71.68.3%), sleep duration below 6 hours (n=54, 51.4%), (iv) change of food habit (n= 61, 58%), (v) low physical activity (n=42, 40.4%), low exercise (n=56, 53.3%), (vi) social interaction, decrease in peer (n=60, 57.1%), decline in friends (n=55, 52.4%), increase in a family circle (n=64, 61%), increase socializing activities (n= 74, 71.1%). Chi-square test to determine the association between categorical variables showed an association between Lockdown, Food, Social habits, and personal time with a significance of p

Rapidly expanding industrial areas ensues a negative impact on the soil chemistry, it delivers certain stubborn heavy metals in the soil. Inefficient emission management and pollution alleviation contributes discharge of heavy metals in the surroundings causing a threat to mankind. To subside the effect of heavy metal; most effective, cost free, solardriven, green technology phytoremediation has been adopted which indulges exploitation of hyper-accumulator plants. Heavy metal toxicity leads to production of reactive oxygen species causing oxidative stress to the plant cell. To mitigate the oxidative stress plant cell initiates production of antioxidative enzymes. The present experiment was setup for analysis and assessment of comparative study of physical (electrokinetic remediation) and chemical (chelators) amendments in enhancing antioxidative enzymes in response to the metal phytoxicity in Vetiveria zizanioides.

In this paper, we have proposed a fuzzy based decision making component for high volume traffic MPLS networks, by implementing Traffic Engineering, Quality of Service and Multipath routing. The approach explicitly proves to be successful in solving the issues and challenges pertaining to stability, scalability in high volume and dynamic traffic. Furthermore, it will work to handle congestion by higher link utilization and provides efficient rerouting of traffic along with fault tolerance in the network. In this research work, fuzzy calculations are done for fixing the attributes of the MPLS label(s), which is put on particular packet representing the Forwarding Equivalence Class. Fuzzy controller consists of two sub fuzzy systems- Label Switched Path setup System (LsS) and Traffic Splitting System (TSS). The computation of dynamic status of Load and Delay is utilized by LsS to arrange the paths in preference order. The attained Link Capacity and Utilization Rate are employing by TSS for maintaining congestion free path. The impact of this is to facilitate, we have better decision making for splitting the traffic for different promising paths. This was apparent from the series of traffic scenarios. Observations are obtained using this realization.

A field experiment was conducted during the rabi season of 2019-2020 at research farm, J.N.K.V.V., College of Agriculture, Tikamgarh (Madhya Pradesh) to study the “Effect of different levels of sulphur on growth and yield of onion (Allium cepa L.)”. The treatments consisted of four levels of sulphur, viz.( S0 - 0kg S/ha, S1 - 20 kg S/ha, S2 - 40 kg S/ha and S3 - 60 kg S/ha) were laid out in Randomized Block Design with three replications. Result showed significant influence on growth and yield attribute for different sulphur levels. Maximum plant height (62.62 cm), number of leaves per plant (10.25), leaf length (55.45 cm), leaf diameter(0.95 cm), neck thickness (1.88 cm), bulb length (5.73 cm), polar diameter (5.99cm), equatorial diameter (6.11 cm), bulb weight (91.32 g) bulb yield (20.30 kg/plot) and bulb yield (282.00 q/ha) were recorded with application of sulphur 60 kg/ha. Which justify its superiority over rest of the treatment while minimum Growth and Yield parameters were recorded 0kg S/ha.

Background: Drought and moisture stress is the most limiting factor affecting growth and productivity of crop plants. The genotypes may differ in their ability to withstand drought or moisture stress. Therefore, the research was carried out to identify suitable genotypes in moisture stress environments. Methods: The forty eight genotypes of fenugreek were planted in randomized block design with three replications under two environmental conditions namely, (i) normal irrigation (E1) and (ii) staggered irrigation (E2) during rabi 2016-2017. Eight stress tolerance indices viz., stress tolerance (TOL), stress susceptibility index (SSI), stress tolerance index (STI), mean production (MP), geometric mean production (GMP), yield index (YI), stress susceptibility percentage index (SSPI) and modified stress tolerance index (MSTI) were calculated based on seed yield under moisture stress (Ys) and non-stress condition (Yp). The correlation coefficient and mean rank of stress indices were calculated to identify the moisture stress tolerant genotypes. Result: The seed yield under non-stress condition (Yp) had significant positive association with TOL, SSI, STI, MP, GMP, SSPI and K1STI. The seed yield under stress condition (Ys) had significant positive association with STI, MP, GMP, YI and K2STI, while significant negative association with TOL, SSI and SSPI. The results showed that MP, GMP and STI indices were more effective in identifying high yielding genotypes in both stress and non-stress conditions while TOL, SSI, YI and SSPI under moisture stress condition. Based upon the mean seed yield and stress tolerance indices, the genotypes UM-124, UM-60, UM-55, UM-28 and UM-4 were found tolerant to staggered irrigation conditions. Hence, these genotypes may be used further in breeding programmes for moisture stress tolerance.

Polymer matrix composites are being widely used in various applications area like as aerospace, construction, shipbuilding, automobile industry etc, due to excellent Mechanical properties and rich hydroxyl group used in surface modification the application area of nanocellulose is increasing day by day. Nanocellulose can be extracted from agricultural waste such as sugarcane bagasse, cotton linter, rice husks, and can be used as a reinforcing material for composites which gives very high Specific stiffness and strength, Elastic modulus of nanocellulose is predicted more than the Kevlar fiber and specific strength is approximately 7–8 times higher than stainless steel as reported in several literature. In this paper extraction technique of nanocellulose and fabrication of polymer matrix composites has been explained, Elastic modulus of composites can be obtained and verified by rule of mixture. Due to its low toxicity, renewable nature, nanoscale dimension and good biocompatibility the future scope of nanocellulose is very wide. Nanocellulose have rich hydroxyl groups which is used for surface treatment of materials, mechanical properties of nanocellulose such as high stiffness and strength are attractive to use it as a filler for composites which gives better mechanical and thermal properties. Nanocellullose composites are used in various application such as in biomedical for tissue repair, drug delivery and implants of some body parts, in paper and packaging industry, in electronic industry such as time- temperature integrator, gas and leak detector etc.

Predicting the groundwater level of karst aquifers in North China Coalfield is essential for early warning of mine water hazards and regional water resources management. However, the dynamic changes of strata structure and hydrogeological parameters driven by coal mining activity cause challenges to the process-oriented groundwater model. In order to achieve accurate prediction of groundwater level in large mining areas, this study was the first to use the data-driven Nonlinear Autoregressive with External Input (NARX) model to predict the groundwater level of six karst aquifer observation wells in Pingshuo Mining Area. Three variable input scenarios were set up, solely considering meteorological factors, anthropogenic disturbance factors, and considering both meteorological and anthropogenic disturbance factors. The novel partial mutual information (PMI) screening algorithm was adopted to determine optimized input variables in each scenario. The input and feedback delay coefficients of NARX model were determined by using Seasonal-trend Decomposition Procedure Based on Loess (STL) algorithm and auto- and cross-correlation functions. The results showed that PMI algorithm can effectively screen out the optimal input variables for predicting groundwater level, the NSE coefficients of the PMI-NARX models under the three scenarios were 38.81%, 4.26% and 41.46% higher than those of the corresponding control experiments, respectively. In addition, the prediction performance of the PMI-NARX built on the basis of meteorological factors is poor (NSE0.63). However, in scenarios which solely use anthropogenic disturbance factors and both use meteorological and anthropogenic disturbance factors, the PMI-NARX coupling models exhibit good prediction performance (NSE and R

Background: Weeds are the major threat to direct seeded rice and a single strategy of weed control may not be effective for season-long weed control. Intending to accomplish the long-term and sustainable weed management of direct seeded rice, the integration approach of weed management strategies seems a better alternative. The current field study was aimed to evaluate the impact of integration of different weed control methods on direct seeded rice under irrigated ecosystem on weed growth and rice yield. Methods: The experiment was laid out in randomized block design with three replications and twelve treatments during 2017 at G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India. The twelve treatments included the combination of cultural, mechanical, physical and chemical weed management methods. Result: Combination of stale seedbed technique integrated with pre-emergence application of pendimethalin with mechanical weeding at 25 DAS followed by 1 hand weeding at 45 DAS, Sesbania (line sowing) fb application of pendimethalin (PE) fb 1 mechanical weeding at 25 DAS fb 1 hand weeding at 45 DAS, stale seedbed with application of pendimethalin (PE) with Sesbania brown manuring supplemented with mechanical weeding (25 DAS) fb hand weeding at 45 DAS, mulching with wheat straw mulch along with post-emergence application of penoxsulam (20 DAS) fb 1 hand weeding at 45 DAS and application of pendimethalin (PE) fb penoxsulum (PoE) at 20 DAS fb 1 hand weeding at 45 DAS with a row spacing of 25 cm found to be similar in the suppression of weed population and weed density at 40 and 60 DAS and crop yields (4.3, 4.1, 4.2, 4.0 and 4.2 t/ha, respectively) were on par with weed free plot i.e. 4.4t/ha. Application of pendimethalin (PE) fb penoxsulum (PoE) at 20 DAS fb 1 hand weeding at 45 DAS with row spacing of 25cm recorded 93.7%, 90.6% and 4.5% weed control efficiency, weed control index and weed index respectively, which was similar with above integrated weed management treatments. A negative correlation of the weed density and dry matter with the yield of rice was recorded.

This paper presents and evaluates design improvements to the Visual Data Acquisition (ViDAQ) system for reading multi-dial gauges. ViDAQ in general, is targeted to occupy a niche application for a cost effective and readily deployable solution for non-intrusive and remote acquisition of data from legacy human machine interface (HMI) indicators. Legacy HMI indicators that pose numerous technological hurdles in being digitally monitored, include analogue rotary multi-dial gauges, alarm lamps, switches etc, much like those common to industrial process monitoring systems can benefit from ViDAQ. Furthermore, ViDAQ is poised to assist in realizing an overarching design goal of a generic EYE-on-HMI (Expert supervisorY systEm) framework. As a framework, EYE-on-HMI stands to integrate the burgeoning field of machine learning and computer vision for real-time detection of human-in-the-loop operator errors and gather human performance data in any commercial and/or industrial process control domain for improving operational safety. Operator interaction with HMI is vital to the operational safety of any process control such as in nuclear power plant operation, aviation, public transit vehicles, driverless vehicles, etc. and thus should be monitored actively.

The material intends to make available the readymade information to students and make them more critical in various subjects. The path is created in form of examples and multiple questions so that students can understand the subjects and can think about the patterns of various competitive examinations. I hope this compendium may be beneficial for the students willing to appear in various competitive examinations like Junior Research Fellowships, Senior Research Fellowships, UPSC, ASRB etc.

In this study, it was focused on the research of new materials with high attenuation efficiency that can be used as radiation shielding material due to the incapability of conventional materials. In accordance with this purpose, the radiation shielding capabilities of four different precipitation-hardening stainless steels (PH-SSs), which are symbolized 15-5PH, 15-7PH, 17-4PH and 17-7PH, were determined both experimentally and theoretically in a wide range of radiation energy. For experimental measurements, two different detectors (Si(Li) and Na(Tl)) and twenty-three different photon energies (from 22.1 to 1332.5 keV) emitted from seven different radionuclides were used in narrow-beam transmission geometry. Phy-X/PSD software were used for theoretical calculations. The theoretically calculated parameters were determined both in the photon energies emitted by the radionuclides used in the experiment and in the continuous energy range of 0.015-15 MeV. Furthermore, in order to make a remarkable assessment of the integration of PH-SSs to nuclear energy applications, the all results obtained have been compared with the corresponding values of Fe-based steel concretes (steel-scrap (SS) and steel magnetite (SM)), which are widely used as conventional shield materials in nuclear power plants. Moreover, in order to choose the best material to be used in nuclear applications among the PH-SSs, the results were evaluated comparatively in terms of both the characteristics of the materials and the magnitude of the radiation shielding parameters. Consequently, it was concluded that the material with the best radiation shielding performance among the examined PH-SSs was 15-7PH and the radiation shielding performance ranking was generally in the form of 15-7PH >= 15-5PH > 17-4PH > 17-7PH > SM > SS. Due to both high attenuation efficiency and superior properties for radiation shielding, it was determined that the PH-SSs can be used as new shielding materials in nuclear applications.

Electrokinetic remediation is an innovative technique to clean spiked soils, in the experiment undertaken effect of current and chemical chelators have been studied and discussed on marigold in potted plants, 15 d(days) old plant were transferred to pots followed up by discrete treatment with 3 milimolar(mM) ethylenediaminetetra acetic acid (EDTA) and electric current. Increasing voltage of DC current (i.e. 1V, 2V, 3V and 4V) was applied for 15 min (minute) for 30 days (d). The findings unveiled that the shoot of physically amended plant was capable of accumulating higher values of metal on 30thd initially, however on 45thd the accumulation was almost same for chemically and physically amended plants. The faster accumulation of heavy metal was aided by the intermediate values of current which helped the plant to withdraw maximum heavy metal on 30th(d) day which proves electrokinetic remediation to be a rapid and better alternative compared to EDTA which shows retarded remediation initially because of damage caused by it to the root hair and has potential threat to contaminate the underground water due to leaching of heavy metals.

Situational Awareness (SA) is paramount to ensuring operational safety in Nuclear Power Plant (NPP) and Commercial aviation industry. An increase in Human-in-the-loop (HITL) error rate may be indicative of reduced operator SA while undermining safety. In this paper, natural language processing (NLP) is applied for modelling industrial Human Machine Interface (HMI) state transitions as a means to detect operator HITL error precursors in real-time. A custom seq2seq encode-decoder deep-learning model design is implemented and evaluated using real-plant scenario dataset obtained from a NPP Operator training simulator. Results support NLP HMI state model may be employed to detect HITL error precursor within the desired N time-steps prior to an accident event.

A novel approach presented herein transforms the Human Machine Interface (HMI) states, as a pattern of visual feedback states that encompass both operator actions and process states, from a multi-variate time-series to a natural language processing (NLP) modeling domain. The goal of this approach is to predict operator response patterns for n &minus, a h e a d time-step window given k &minus, l a g g e d past HMI state patterns. The NLP approach offers the possibility of encoding (semantic) contextual relations within HMI state patterns. Towards which, a technique for framing raw HMI data for supervised training using sequence-to-sequence (seq2seq) deep-learning machine translation algorithms is presented. In addition, a custom Seq2Seq convolutional neural network (CNN) NLP model based on current state-of-the-art design elements such as attention, is compared against a standard recurrent neural network (RNN) based NLP model. Results demonstrate comparable effectiveness of both the designs of NLP models evaluated for modeling HMI states. RNN NLP models showed higher ( &asymp, 26 % ) forecast accuracy, in general for both in-sample and out-of-sample test datasets. However, custom CNN NLP model showed higher ( &asymp, 53 % ) validation accuracy indicative of less over-fitting with the same amount of available training data. The real-world application of the proposed NLP modeling of industrial HMIs, such as in power generating stations control rooms, aviation (cockpits), and so forth, is towards the realization of a non-intrusive operator situational awareness monitoring framework through prediction of HMI states.

Coefficients of thermal expansion of some uniaxially fiber-reinforced composites have been evaluated using three-phase unit-cell model. Results have been compared with the values predicted by two other models based on composite cylinders assembly (CCA), and also with some earlier reported experimental values. An extension of the two-phase unit-cell model has also been presented for the evaluation of thermal expansion coefficients of three-phase composites. The formulation has been used to evaluate the overall coefficients of thermal expansion of AS-graphite/epoxy system with a low modulus coating on the fibers. The results have been compared with the results obtained from the Sutcu's recursive concentric cylinders model for composites containing coated fibers. From the comparison of results of the unit-cell models (both, two-phase and three-phase) with the results obtained from some other models available in the literature, it is concluded that the overall thermal properties of fiber-reinforced composites evaluated by the unit-cell model can be used as effectively as by any other model.

Central neurocytomas (CNCs) are benign intraventricular neoplasms seen in children and young adults. Rarely, neoplasms that are similar in histopathological appearance arise in the brain parenchyma and are termed as extra-ventricular neurocytoma (EVNC). These EVNCs commonly present as epilepsy and behave more aggressively than CNCs with poorer long-term outcome. Here, we present a case of EVNCs in a male child with multiple recurrences, aggressive behavior and extensive craniospinal dissemination. Keywords: Central neurocytoma, Extra-ventricular neurocytoma, Craniospinal dissemination

SrO-Bi2O3-B2O3 (SBBO) transparent glass ceramics are fabricated via conventional melt-quenching technique. Simply via surface fluorination of these glass ceramics, by using HF solution, we obtained the coating of cubic BiO0.51F1.98over SBBO glass ceramic. Further, with successive fluorination by using concentrated HF solutions the crystal structure of coating tends towards the cubic α-BiF3 structurefrom the cubic BiO0.51F1.98. Both the structures of cubic BiO0.51F1.98 and cubic α-BiF3possess totally different morphologies; first having compact spheres and the other shows densely packed cubes, respectively. Along with fluorination, besides the structural and microstructure transformations, we have attained the improved transparency. Synergy effects of structural transformation on the contact angle and the photocatalytic properties are studied. The fluorinated SBBO transparent glass ceramics can be used as self-cleaning structural application.

Mass attenuation coefficients and exposure buildup factors (EBF) for some ceramic hosts such as Hollandite (BaAl 2 Ti 6 O 16 ), Perovskite (CaTiO 3 ), Zirconolite (CaZrTi 2 O 7 ), Apatite (Pb 10 (VO 4 ) 4.8 (PO 4 ) 1.2 I 2 ), and Zircon (ZrSiO 4 ) for high level radioactive waste have been computed in the present paper. The mass attenuation coefficients for the Apatite were found to be the highest. The EBF for the Apatite were found the smallest in low-to-intermediate energy (

The present article deals with 2Bi2O3-B2O3 (BBO) glass whose photocatalytic activity has been enhanced by the method of wet etching using an aqueous solution of hydrofluoric acid (HF). X-ray diffraction of the samples reveals that etching with an aqueous solution of HF leads to the formation of BiF3 and BiO0.1F2.8 phases. Surface morphology obtained from scanning electron microscopy show granular and plate-like morphology on the etched glass samples. Rhodamine 6G (Rh 6G) has been used to investigate the photocatalytic activity of the as-quenched and etched glasses. Enhanced visible light-driven photocatalytic activity was observed in HF etched glass-ceramics compared to the as-quenched BBO glass. Contact angle of the as-quenched glass was 90.2°, which decreases up to 20.02° with an increase in concentration of HF in the etching solution. Enhanced photocatalytic activity and increase in the hydrophilic nature suggests the efficient treatment of water pollutants by using the prepared surface crystallized glass–ceramics.

SrO-Bi2O3-B2O3 transparent glass ceramic was fabricated via conventional melt-quenching technique. Structural analysis like X-ray diffraction, Raman and Fourier transform infrared spectroscopies were performed to confirm SBBO glass ceramic formation. As-quenched glass samples exhibited X-ray diffraction peaks corresponding to SrBi2B2O7 which were further confirmed through Field Emission Scanning Electron Microscope. UV–vis transmission spectra revealed 60%–80% transparency in 500–800 nm spectral range. Absorption study revealed direct bandgap of 2.58 eV. Resazurin (Rz) ink was used as an indicator to monitor photocatalytic activity for self-cleaning purposes. Digital photographic method was performed to examine photoreduction of Rz ink. Further, the pseudo-first order kinetics was istimated for Methylene blue (MB) degradation. Nucleation of nanoparticles of SrBi2B2O7 over glass surface were found responsible for photocatalytic activity. Contact angle with water droplet for SBBO glass ceramic was 63.43°. Reduced Young’s modulus (Er) and Vickers hardness (Hv) were found 59.9 GPa and 5.01 GPa, respectively.