Performance Analysis of Strained Monolayer MoS2_{2} MOSFET

We present a computational study on the impact of tensile/compressive uniaxial ($\varepsilon_{xx}$) and biaxial ($\varepsilon_{xx}=\varepsilon_{yy}$) strain on monolayer MoS$_{2}$ NMOS and PMOS FETs. The material properties like band structure, carrier effective mass and the multi-band Hamiltonian of the channel, are evaluated using the Density Functional Theory (DFT). Using these parameters, self-consistent Poisson-Schr\"{o}dinger solution under the Non-Equilibrium Green's Function (NEGF) formalism is carried out to simulate the MOS device characteristics. 1.75$$ uniaxial tensile strain is found to provide a minor (6$$) ON current improvement for the NMOSFET, whereas same amount of biaxial tensile strain is found to considerably improve the PMOSFET ON currents by 2-3 times. Compressive strain however degrades both NMOS and PMOS device performance. It is also observed that the improvement in PMOSFET can be attained only when the channel material becomes indirect-gap in nature. We further study the performance degradation in the quasi-ballistic long channel regime using a projected current method

ADVANCEMENTS IN NON-INVASIVE VENTILATION TECHNIQUES FOR MANAGING ACUTE RESPIRATORY DISTRESS: A NARRATIVE REVIEW.

Acute respiratory failure (ARF) presents a significant clinical challenge, often necessitating invasive mechanical ventilation (IMV). Non-invasive ventilation (NIV) has emerged as a valuable alternative, but recent innovations and advancements in NIV strategies warrant exploration to optimize its clinical utility. The review aims to synthesize recent innovations in NIV strategies for the management of ARF, assess their clinical applications and efficacy, discuss challenges, and outline future directions for research and clinical practice. Recent advancements in NIV devices, interfaces, and ventilation modes have enhanced patient comfort, improved outcomes, and expanded the applicability of NIV across various clinical settings. Smart ventilation systems driven by artificial intelligence (AI) and machine learning algorithms, portable and wearable NIV devices, and the integration of telemedicine have revolutionized the delivery of respiratory support. Clinical studies have demonstrated the efficacy of NIV in specific populations, such as COPD exacerbations, cardiogenic pulmonary edema, and COVID-19 pneumonia, further solidifying its role in respiratory care. Future research in NIV is focused on refining personalized ventilation strategies, integrating NIV with other therapeutic modalities, and developing next-generation ventilators capable of real-time adaptation to patient needs. These advancements hold promise for improving outcomes, enhancing the quality of care, and reducing the burden of respiratory failure. The outcomes of this review have implications for clinical policy and development, highlighting the importance of incorporating recent innovations in NIV into clinical practice guidelines and protocols. Healthcare providers should remain abreast of technological advancements and evidence-based practices to optimize the management of ARF and improve patient outcomes

Machine Learning for Soil Fertility and Plant Nutrient Management using Back Propagation Neural Networks

The objective of this paper is to analysis of main soil properties such as organic matter, essential plant nutrients , micronutrient that affects the growth of crop s and find out the suitable relationship percentage among those properties usi ng Supervised Learning , Back Propagation Neural N etwork. Although these parameters can be measured directly, their measurement is difficult and expensive. Back Propagation N etworks (BPN) are trained with re ference crops growth properties available nutrient status and its ability to provide nutrients out of its own reserves and through external applications for crop production in both cases , BPN will find and suggest the correct correlation percentage among those properties. This machine learning system is divided into three steps, first s ampling (Different soil with same number of properties with different p arameters) second Back Propa gation Algorithm and third Weight updating . The performance of the Back Propagation N eural network model will be evaluated using a test data set. Results will show that ar tificial neural network with certain number of neurons in hidden layer had better pe rformance in predicting soil properties than multivariate regression. In conclusion, the result of this study showed that training is very important in increasing the model accuracy of one region and result in the form of a guide to recognizing soil proper ties relevant to plant growth and protection

Corporate governance attributes, firm characteristics and the level of corporate disclosure: Evidence from the Indian listed firms

This study investigates the association between firm characteristics, corporate governance attributes and the level of corporate disclosure of listed firms in India. The research paper has been based on a sample of 60 firms listed in the Bombay Stock Exchange (BSE) / National Stock Exchange (NSE) during the study period from 2000-01 to 2009-10. The study has used the Standard & Poor (2008) model for measuring the level of corporate disclosure. To examine the association between explanatory variables and the level of corporate disclosure, multiple regression model has been used. The results suggest a positive relationship between board size, ratio of audit committee members to total board members, family control, CEO duality, firm size, profitability, liquidity and the extent of corporate disclosure. However, the degree of corporate disclosure is negatively related to board composition, leverage and age of the firm

Isolation of a cdc28 mutation that abrogates the dependence of S phase on completion of M phase of the budding yeast cell cycle

We have isolated a mutation in the budding yeast Saccharomyces cerevisisae CDC28 gene that allows cdc13 cells, carrying damaged DNA, to continue with the cell division cycle. While cdc13 mutant cells are arrested as largebudded cells at the nonpermissive temperature 37°C, the cdc13 cdc28 double mutant culture showed cells with one or more buds, most of which showed apical growth. The additional buds emerged without the intervening steps of nuclear division and cell separation. We suggest that the cdc28 mutation abrogates a checkpoint function and allows cells with damaged or incompletely replicated DNA an entry to another round of cell cycle and bypasses the mitotic phase of the cell cycle

Patterns of Alcohol Consumption among Male Adults at a Slum in Kolkata, India

Globally, alcohol-abuse is a major cause of mortality and morbidity. Consumption of alcohol has increased in India in the recent decades. It is imperative to know the patterns of alcohol consumption among different types of consumers to launch a well-planned nationwide programme for the prevention and control of this devastating social pathology. This community-based, cross-sectional study was undertaken to identify the patterns of alcohol intake among different types of alcohol consumers and to assess the clinical signs of chronic harmful alcohol-use. A predesigned, pretested, semi-structured alcohol-use disorders identification test (AUDIT) questionnaire was used for interviewing males, aged >18 years, selected by random sampling from an updated household list of a randomly-selected sector of the service area of the Urban Health Centre in Chetla, Kolkata, West Bengal, India. Written informed consents were obtained from all the respondents. Relevant clinical examination for chronic harmful alcohol-use was done according to the AUDIT clinical screening procedures. The results revealed that 65.8% (150/228) were current consumers of alcohol; 14% were alcohol-dependents; 8% were hazardous or harmful consumers, and 78% were non-hazardous non-harmful consumers. The mean age of the respondents at the initiation of drinking alcohol was 20.8+5.9 years. Eighty-six percent of dependents (n=21) took both Indian-made foreign liquor and locally-made alcoholic beverages. The proportions of alcohol consumers who drank alone among alcohol-dependents, hazardous or harmful consumers, and non-hazardous non-harmful consumers were 71.4%, 50%, and 7.7% respectively, and the difference was significant (p<0.01). Forty-one percent of the consumers drank at public places and workplaces, which may be socially harmful. About 38% of the dependents purchased alcohol from unlicensed liquor shops. Only 16% expressed concerns for their drinking habit mainly to the past illness. The proportion of the concerned respondents was higher in the hazardous and harmful drinking patterns than in the non-hazardous non-harmful drinking pattern, and the difference was significant (p<0.05). About 62% of the dependents had clinical signs of chronic alcohol consumption. The presence of a considerable proportion of alcohol-dependents, the low mean age at initiation of drinking alcohol, and the habit of drinking in public places and workplaces are the main areas that need special emphasis by intervention programmes

Modelling of Impact of Detritus on Detritivorous Food Chain of Sundarban Mangrove Ecosystem, India

AbstractDecomposition and subsequent remineralization of mangrove detritus is important in nutrient dynamics within the forest as well as in offshore system. In order to study the impact of detritivorous fish on the mangrove estuarine detritus food web, a five compartment model of detritus food web dynamics has been developed for mangrove estuarine creeks of Hooghly- Matla Estuarine complex, Sundarban. The model simulates concentration of nutrient, biomass of phytoplankton, zooplankton, detritus and detritivorous fishes. Almost 70% of the detritus formed in the soil was being washed in the estuarine water to act as source or sink of nutrient for the primary producers of aquatic food chain. A significant amount of detritus in the estuarine water is readily consumed by a group of detritivorous fishes before it is being rematerialized completely in to inorganic nutrient form. The model has been calibrated and validated using field data accordingly. Increased detrital nitrogen values in the late monsoon and post monsoon months, assists the growth and high yield of detritivorous fishes as found in simulated and field observations. Comparison of simulated and observed results demonstrates the dependence of phytoplankton growth is a function of nutrient concentration and zooplankton grazing. Model results also show the dependence of detritivorous fishes on detritus which is a function of detritus biomass. In turn, detritus biomass is dependent upon several factors like mortality of phytoplankton, zooplankton, and detritivorous fishes; and chiefly on litter biomass and litter decomposition