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Coronavirus disease 2019 (COVID-19) is a highly infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of April 17, 2020, the total number of cases all over the world read as 2,182,823 positive cases with 145,551 deaths and 547,679 recovered cases. In India, the total number of affected cases has alarmingly increased up to 13,430, crossing the 10 thousand mark with 11,214 active cases and 1768 recovered cases. There have been multiple studies and reviews published regarding the nature of the disease, its clinical symptoms and their progression, as well as findings on chest radiography, computed tomography, and positron emission computed tomography. A systematic literature search of the PubMed database was performed on April 8, 2020, using the suitable keywords and publications on novel coronavirus infection were also searched for in the WHO database. Only those articles published in the year 2020 were included. Data were collected, extracted, and tabulated for systematic reviewing from 26 original articles and 4 case series. The typical radiological findings on computed tomography for COVD 19 were ground-glass opacity with and without consolidation, isolated consolidation, air bronchogram, crazy paving, and interlobular septal thickening with subpleural lines. With the progression of the disease, other atypical radiological findings are noted, such as pulmonary atelectasis, peribronchial thickening, pleural effusion, pericardial effusion, mediastinal lymphadenopathy, reverse halo or atoll sign, and tree in bud appearance with bronchiectasis. Computed tomography proved as a useful tool for screening COVID 19 cases to delineate the status and severity of lung pathology.

Finetuning language models on a collection of datasets phrased as instructions has been shown to improve model performance and generalization to unseen tasks. In this paper we explore instruction finetuning with a particular focus on (1) scaling the number of tasks, (2) scaling the model size, and (3) finetuning on chain-of-thought data. We find that instruction finetuning with the above aspects dramatically improves performance on a variety of model classes (PaLM, T5, U-PaLM), prompting setups (zero-shot, few-shot, CoT), and evaluation benchmarks (MMLU, BBH, TyDiQA, MGSM, open-ended generation). For instance, Flan-PaLM 540B instruction-finetuned on 1.8K tasks outperforms PALM 540B by a large margin (+9.4% on average). Flan-PaLM 540B achieves state-of-the-art performance on several benchmarks, such as 75.2% on five-shot MMLU. We also publicly release Flan-T5 checkpoints, which achieve strong few-shot performance even compared to much larger models, such as PaLM 62B. Overall, instruction finetuning is a general method for improving the performance and usability of pretrained language models., Comment: Public checkpoints: https://huggingface.co/docs/transformers/model_doc/flan-t5

Introduction: Laboratory physicians confront with ethical issues in routine practice, but still ethics does notdraw the importance it deserves. A critical appraisal of the existing postgraduate curriculum of Pathology,Microbiology and Biochemistry with reference to its Bioethical inclusions to their conformity with referenceto Bioethical principles applicable to profession as included in UNESCO Declaration is needed.Aim: To critically analyse the inclusions of “Bioethics in Laboratory Medicine” into the ExistingPostgraduate Curriculum of Pathology, Microbiology and Biochemistry with reference to Bioethicalprinciples incorporated in UNESCO DeclarationMaterial and Methods: It was a descriptive study for rapid review of literature for the purposes ofidentification and critical appraisal of bioethical considerations in Laboratory Medicine in existingGuidelines for Competency Based Postgraduate Training Programme for MD in Pathology, Microbiology,Biochemistry with reference to Bioethical principles included in UNESCO declaration specially thoseapplicable to profession and not propagation or advocacy.Observations and Results: Upon critical analysis and mapping of the competencies in the Guidelines forCompetency Based Postgraduate Training Programme for MD in Pathology, Microbiology, Biochemistrywith the principles in the UNESCO universal declaration, 16 competencies were identified as professionalethical inclusions. 19 Competencies suggested in regards to “Bioethics in Laboratory Medicine” forGuidelines for Competency Based Postgraduate Training Programme for MD In these subjects to makethem commensurate with UNESCO universal declarationConclusion: This has brought out subsequent omissions which need to be managed in order to makecompetencies in Existing PG curriculum of Pathology, Microbiology and Biochemistry comparable with theUNESCO universal declaration and therefore, make it better and standardised on global and internationallevel.

­Decomposition of litter is a function of various interrelated variables; both biotic factors and abiotic factors. Litter decomposition acts like a natural fertilizer, plays a prime role in maintaining the productivity and nutrient cycling in forest ecosystem. So, it is necessary to be aware of the machinery operation behind this significant ecological process. This review is based on the published work carried out in recent years and critically examines the role of different factors involved in litter decomposition, their limitations and gaps to be investigated. Numerous methods are there, litter bag technique is quite simple and handy in investigating and explaining the variations in decomposition rate constant 'k'. It is not surprising that the environment and decomposers are the key players; but role of litter quality cannot be underestimated. Changing climate can alter the microbial diversity and its consequences can be drastic in nature. Under soil aspect, nutrients (N and P), whether endogenous or exogenous, have the ability to modify the process but results are diverse and conflicting. Most of the studies and related information is based on the single species litter decomposition. However, forest ecosystems are mixer of understory herbaceous plants and woody trees and interaction between all the variables and mixed litter surely modify the litter dynamics. Future studies should be focused on how qualitative and quantitative characters of mixed litter, interact with others factors of this promising ecological process. It is necessary to divert the interest towards the mechanism and modeling of decomposition rates 'k' and rate of nutrient released by mixed litter decomposition with special reference to with global environment change.

A three dimensional molecular dynamic code is used to study the generation of fusion neutrons from Coulomb explosion of Deuterium clusters driven by intense near infra-red (NIR) laser ($\lambda=800nm$) of femtosecond pulse duration ($\tau=50 fs$) under beam-target interaction scheme. We have considered various clusters of average sizes ($\langle R_0\rangle$=80,140,200\AA) which are irradiated by a laser of peak spatial-temporal intensity of 1$\times10^{18} W/cm^{2}$. The effects of cluster size and spatial laser intensity distribution on ion energies due to the Coulomb explosion of the cluster are included by convolution of single cluster single intensity ion energy distribution function (IEDF) over a range of cluster sizes and laser intensities. The final convoluted IEDF gets broadened on both lower and higher energy sides due to this procedure. Furthermore, the neutron yield which takes into account the convoluted IEDF, also gets modified by a factor of $\sim$2 compared to the case when convolution effects are ignored.

Communications over social media, telephone, email, text etc have emerged as an integral part of modern society and they are popularly used for the expression of anger, anxiety, fear, agitation and opinion by the people. People's social interaction tend to increase dramatically during periods of epidemics, protest and calamities. Therefore, above mentioned communication channels plays an important role in the spread of infectious phenomenon, like rumors, fads and effects. These infectious phenomena alters people's behavior during disease epidemic [1][2]. Social contact networks and epidemics co-evolve [1][2]. The spread of a disease influences people's behavior which in turn changes their social contact network, thereby altering the disease spread itself. As a result, there is a need for modeling the spread of these infectious phenomena that lead to changes in behavior. Their propagation among population primarily depends on the social contact network. The nature of social contagion spread is very similar to the spread of any infectious disease as they are contagious in nature. To spread contagious disease requires direct exposure to an infectious agent, whereas social contagions can be spread using various communications media like social networking forums, phones, emails and tweets. EpiSimdemics is an individual-based modeling environment. It uses a people-location bipartite graph as the underlying network [3]. In its current form, EpiSimdemics requires two people to interact at a location to model simulations. Thus, it cannot simulate the spread of social contagions that do not necessarily require the meeting of two agents at a location. We enhance EpiSimdemics by incorporating Person-Person network, which can model communications between people that are not contact based such as communications over email, phone, text and tweet. This Person-Person network is used to model effects (social contagion) which induce behavioral changes in population and thus impacting the disease spread. The disease spread is modeled on Person-Location network. This leads to the scenario of two interacting networks: Person-Person network modeling social contagion and Person-Location modeling disease. Theoretically, there can be multiple such networks modeling various interacting phenomena. We demonstrate the usefulness of this network by modeling and simulating two interacting PTTSs (probabilistic timed transition systems). To model disease epidemics, we have defined Disease Model and to model effects (social contagion), we have defined Fear Model. We show how these models influence each other by performing simulations on EpiSimdemics with interacting Disease and Fear Model. Therefore a model that does not include the affect adaptations on disease epidemics and vice-versa, fails to reflect the actual behavior of a society during disease epidemic spread. The addition of Person-Person network to EpiSimdemics will allow for a better understanding of the affect adaptions, which can include behavior changes in society during an epidemic outbreak. This would lead to effective interventions and help to better understand the dynamics of disease epidemic. Master of Science

To analyze the relationship between the management of three forest stand plantations and soil quality in the Dimapur district of the Northeastern Himalayan region, India, three forest soil profiles, covered by different species stands, at three depths were tested for 13 physical and chemical variables. Only four of these variables (electric conductivity, bulk density exchangeable Mg and available P) were included in a minimum data set, after using a varimax rotation algorithm in a principal component analysis, and subsequently used to calculate a soil quality index (SQI). Results showed higher SQIs in the surface layers (0–20 cm depth) than in the deeper ones. Average weighed SQI varied significantly (P