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Background: Delirium is a reversible state that, if ignored, can result in increased morbidity and mortality. Studies from across the world have shown that nurses’ knowledge regarding delirium is inadequate. This study is one of the very few Indian studies addressing this issue. The study aims to infer an intensive care unit (ICU) nurse’s knowledge regarding delirium.Materials and Methods: This is a descriptive study carried out in the ICUs of a multispecialty general hospital. A convenient sample of 220 nurses was recruited after obtaining written informed consent. Knowledge regarding delirium was ascertained using the Delirium Knowledge Questionnaire; this, along with the sociodemographic variables, was circulated as Google Forms through WhatsApp groups. Data were analyzed using Statistical Package for the Social Sciences (SPSS) version 26, and results were presented as means and percentages.Results: The present study reveals that out of 211 nurses 130 (61.6%) had an average knowledge about delirium. Out of the 211 nurses 108 (51.2%) had average knowledge about clinical features of delirium and 105(49.8%) had average knowledge about etiology of delirium. More than half of the nurses (53.1%) had awareness regarding the medical management of delirium. In the domain of knowledge regarding non-medical management, 81 (38.4%) had excellent knowledge and 114 (54%) respondents had average knowledge regarding the prevention of delirium.Conclusion: The study calls for the need to provide educational interventions to the nursing staff for prevention, prompt recognition, and treatment of delirium.

ABSTRACTSoil pollution is one of the serious global threats causing risk to environment and humans. The major cause of accumulation of pollutants in soil are anthropogenic activities and some natural processes. There are several types of soil pollutants which deteriorate the quality of human life and animal health. They are recalcitrant hydrocarbon compounds, metals, antibiotics, persistent organic compounds, pesticides and different kinds of plastics. Due to the detrimental properties of pollutants present in soil on human life and ecosystem such as carcinogenic, genotoxic and mutagenic effects, alternate and effective methods to degrade the pollutants are recommended. Bioremediation is an effective and inexpensive method of biological degradation of pollutants using plants, microorganisms and fungi. With the advent of new detection methods, the identification and degradation of soil pollutants in different ecosystems were made easy. Metagenomic approaches are a boon for the identification of unculturable microorganisms and to explore the vast bioremediation potential for different pollutants. Metagenomics is a power tool to study the microbial load in polluted or contaminated land and its role in bioremediation. In addition, the negative ecosystem and health effect of pathogens, antibiotic and metal resistant genes found in the polluted area can be studied. Also, the identification of novel compounds/genes/proteins involved in the biotechnology and sustainable agriculture practices can be performed with the integration of metagenomics.

The future development of wireless mobile networks (5G and beyond) aims to create a service-aware network using the network slicing technique. These networks are anticipated to handle substantial amounts of traffic and offer a wide range of services tailored to meet consumer needs. The use cases, such as Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communication (uRLLC), and Massive Machine Type Communication (mMTC), have diverse service needs that depend on the applications they support. Based on this premise, the study suggests formulating a multi-objective problem to precisely forecast traffic using the Deep Convolution Neural Network and Long Short-term Memory Networks predictive models. The efficacy of this Deep Reinforcement Learning model is evaluated using learning algorithms such as Adaptive Moment Estimation (ADAM), Stochastic Gradient Descent Momentum, and Root Mean Squared Propagation (RMSProp). The findings display the comparison of evaluation measures such as precision, recall, F1-score, and accuracy. Additionally, this projected data is utilized as the traffic for the subsequent resource allocation model. The second model employs the advanced Tasmanian Devil Optimization-Elite (TDO-E) method to allocate resources effectively. This study presents the initial application of the TDO algorithm in the 5G slicing technique for resource allocation. The TDO-E is an advanced version that utilizes a revolutionary way to achieve optimized results by implementing a strategy of sharing information. This resource allocation technique focuses on two main issues: (i) Creating and assigning slices to new devices. (ii) Implementing slice reconfiguration to optimize resource use. We have shown that the predictive model utilizing the ADAM algorithm has achieved superior outcomes compared to other algorithms, with a corresponding output value of 99.785% in the evaluation metrics. The resource allocation for devices with TDO-E shows a 6.79% improvement compared to TDO. The TDO-E evaluates the techniques in terms of resource efficiency and adaptability. The proposed approach is also evaluated using different numbers of devices. The results demonstrate the efficacy of the planned approach by comparing graphs depicting the percentage of resources provided in relation to the number of devices. The implementation of predictive models with slice reconfiguration will significantly advantage network operators by optimizing resource allocation and enhancing service quality for customers.

The rapid growth of urban areas and population as well as associated development over recent decades have been a major factor controlling ambient air quality of the urban environment in Kerala (India). Being located at the southwestern fringe of the Indian peninsula, Kerala is one of the regions that has been significantly influenced by the activities in the Indian Ocean. The present study focuses on the effect of the COVID-19 lockdown (in 2021) on ambient air quality in the selected coastal metropolitan areas of Kerala. Although previous research studies reported improvement in ambient air quality in Kerala during the lockdown period, this study demonstrates the potential of onshore transport of air pollutants in controlling the air quality of coastal urban regions during the lockdown period. Data from the ambient air quality monitoring stations of the Kerala State Pollution Control Board in the urban areas of Thiruvananthapuram (TM), Kollam (KL), Kozhikode (KZ), and Kannur (KN) are used for the analysis. Temporal variation in the concentration of air pollutants during the pre-lockdown (PRLD), lockdown (LD), and post-lockdown (PTLD) periods (i.e., 1 March to 31 July) of 2021 is examined to assess the effect of lockdown measures on the National Air Quality Index (AQI). Results indicate a significant decline in the levels of air pollutants and subsequent improvement in air quality in the coastal urban areas. All the effect of lockdown measures has been evident in the AQI, an increase in the concentration of different pollutants including CO, SO2, and NH3during the LD period suggests contributions from multiple sources including onshore transport due to marine traffic and transboundary transport.

Deterioration of ambient air quality associated with urbanisation is a serious concern in many parts of the world. In India, air pollution, primarily due to particulate matter, has increased exponentially in the last few decades due to rapid urbanization, industrialization and population growth. This study investigates the non-uniform influence of COVID-19 lockdown on the ambient air quality of three distinct local climate zones (LCZs) within the urban region of Kochi (Kerala, India). The analysis of the air pollutant data of the ambient air quality monitoring stations during the pre-lockdown (PRLD), lockdown (LD) and post-lockdown (PTLD) periods of 2021 implies the significance of lockdown measures in the improvement of urban air quality. The air quality index (AQI) exhibits characteristic variability in different LCZs and contrasting behaviour between the LD period of 2020 and 2021, primarily due to the differences in the lockdown restrictions and strategies as well as the influence of local climatic factors. This study highlights the need for multiple monitoring stations in the urban regions with respect to different LCZs to identify the urban air quality hot spots.

Background: Euphorbia species are known for the diversity of terpenes, and the presence of toxic diterpenoids in Euphorbia species have raised occupational and eco-toxicological concerns. The present study reports the terpene profile of Euphorbia tortilis Rottler ex Ainslie, along with cytotoxicity assay. Method: Triterpenes were isolated from the hexane extract of E. tortilis through column chromatography and were characterized by various spectroscopic techniques. Phorbol esters were detected from the methanol extract of the latex through high performance liquid chromatography-electrospray ionizationquadrupole time of flight tandem mass spectrometry (HPLC-QTOF- MS/MS). Cytotoxicity of the extract was tested against human cervical cancer cell line HeLa and normal cardiac myoblasts cell line H9C2 using MTT assay. Results: The pentacyclic triterpenoids 3β-friedelinol, 3α-friedelinol, friedelin, epi-friedelinyl acetate and taraxerol were isolated and characterized from E. tortilis. Ten phorbol esters belonging to the tigliane family of diterpenoids were detected through HPLC-ESI-QTOF-MS/MS method. The major tumor promoting phorbol ester TPA (phorbol-12-myristate-13-acetate) reported from Euphorbiaceae family could not be detected in E. tortilis, whereas the potential anti HIV and cytotoxic phorbol ester prostratin has been detected. Latex extract was inactive on the normal cell line H9C2 within the concentration range of 10-100μg/ml, while the cell growth inhibition of the extract at 100μg/ml on Hela cell line was negligible (3.06%). Conclusion: Pentacyclic triterpenes were the major compounds isolated and characterized from E. tortilis. HPLC-ESI-QTOF-MS/MS method has been found as an ideal tool for the detection of minor phorbol esters. The terpenoid profile revealed the absence of toxic TPA. Furthermore, the latex extract was non toxic towards normal cell line H9C2. The findings are relevant in the context of toxicological concerns related to Euphorbia members.

ABSTRACTActive efflux of drugs mediated by efflux pumps that confer drug resistance is one of the mechanisms developed by bacteria to counter the adverse effects of antibiotics and chemicals. To understand these efflux mechanisms in Mycobacterium tuberculosis, we generated knockout (KO) mutants of four efflux pumps of the pathogen belonging to different classes. We measured the MICs and kill values of two different compound classes on the wild type (WT) and the efflux pump (EP) KO mutants in the presence and absence of the efflux inhibitors verapamil and l-phenylalanyl-l-arginyl-β-naphthylamide (PAβN). Among the pumps studied, the efflux pumps belonging to the ABC (ATP-binding cassette) class, encoded by Rv1218c, and the SMR (small multidrug resistance) class, encoded by Rv3065, appear to play important roles in mediating the efflux of different chemical classes and antibiotics. Efflux pumps encoded by Rv0849and Rv1258calso mediate the efflux of these compounds, but to a lesser extent. Increased killing is observed in WT M. tuberculosiscells by these compounds in the presence of either verapamil or PAβN. The efflux pump KO mutants were more susceptible to these compounds in the presence of efflux inhibitors. We have shown that these four efflux pumps of M. tuberculosisplay a vital role in mediating efflux of different chemical scaffolds. Inhibitors of one or several of these efflux pumps could have a significant impact in the treatment of tuberculosis. The identification and characterization of Rv0849, a new efflux pump belonging to the MFS (major facilitator superfamily) class, are reported.

Active efflux of drugs mediated by efflux pumps that confer drug resistance is one of the mechanisms developed by bacteria to counter the adverse effects of antibiotics and chemicals. To understand these efflux mechanisms in Mycobacterium tuberculosis, we generated knockout (KO) mutants of four efflux pumps of the pathogen belonging to different classes. We measured the MICs and kill values of two different compound classes on the wild type (WT) and the efflux pump (EP) KO mutants in the presence and absence of the efflux inhibitors verapamil and L-phenylalanyl-L-arginyl-β-naphthylamide (PAβN). Among the pumps studied, the efflux pumps belonging to the ABC (ATP-binding cassette) class, encoded by Rv1218c, and the SMR (small multidrug resistance) class, encoded by Rv3065, appear to play important roles in mediating the efflux of different chemical classes and antibiotics. Efflux pumps encoded by Rv0849 and Rv1258c also mediate the efflux of these compounds, but to a lesser extent. Increased killing is observed in WT M. tuberculosis cells by these compounds in the presence of either verapamil or PAβN. The efflux pump KO mutants were more susceptible to these compounds in the presence of efflux inhibitors. We have shown that these four efflux pumps of M. tuberculosis play a vital role in mediating efflux of different chemical scaffolds. Inhibitors of one or several of these efflux pumps could have a significant impact in the treatment of tuberculosis. The identification and characterization of Rv0849, a new efflux pump belonging to the MFS (major facilitator superfamily) class, are reported.

Materials/metals, polymers, reinforced plastics, composites, functionally graded materials, ceramics and nano materials find significant place in many engineering and scientific applications. The material structural members such as plates and beams are subjected to structural deformation owing to several external and internal factors such as temperature, hysteresis and so on. Therefore, to analyze the structural deformation of these material structures, its nonlinear behavior modeling is relevant. The rapid progress in high speed computing devices resolve research problems involving material non-linearity behavior such as post-buckling behavior in varied structures. The post-buckling behavior of commonly used structural elements especially plates under thermal and mechanical loads are of great practically important research topic. Therefore, a comparative study on the thermal post buckling behavior of plates by various numerical methods such as finite element formulation, shear deformation theory, Rayleigh - Ritz method, iteration methods and so on will be helpful to obtain a cutting edge on numerical solutions and their applications in varied engineering applications. This paper reports a novel mathematical formulation involving substitution method to evaluate and compare the thermal post buckling load carrying capacity of circular plates with minimal errors.

A mathematical formulation to obtain the non-dimensionalized added virtual mass incremental factor for uniform circular plate in contact with fluid is presented. Based on Rayleigh's quotient, the natural frequencies can be evaluated using the added virtual mass incremental factors. A suitable approximation is used to describe the effect of non-dimensionalized added virtual mass incremental factors in the vibration analysis of circular plates. The numerical results obtained from the present formulation are compared with the known results reported in the literature and a good agreement was found. The maximum error percentage has been predicted from the present formulation is 0.005%.