Adenovirus Death Protein: The Switch Between Lytic and Persistent Infections in Lymphocytes?

ABSTRACT Adenovirus Death Protein (ADP) expression during late stages of a lytic infection releases mature virions to promote viral spread, thus leading to death of the host cell. We sought to investigate ADP expression patterns in persistently infected human lymphocytes cells. We hypothesized that low expression of ADP allows the virus to persist while high expression would promote lytic infection in lymphocytes. Accordingly, we found ADP expressed in low amount in BJAB and KE37 cells, while lytically infected Jurkat cells demonstrated higher ADP expression in both protein and transcript levels. ADP overexpression in persistently infected lymphocytes did not alter the viability of these cells, or their level of ADP expression. In contrast, Jurkat cells infected with an ADP-deleted virus had increased survival and maintained viral DNA for greater than 1-month, suggesting conversion to a persistent infection. Also manipulating ADP expression had minimal impact on the total virus yield from infected lymphocytes

ML based approach for covid-19 future forecasting

ML based forecast systems have demonstrated their significance in expecting the preoperative result in to further develop independent direction in regards to the future course of action.ML models have for some time been utilized in numerous application regions requiring the ID and prioritization of troublesome variables for a danger. Understanding and characterizing chest x-beam (CXR) and figured tomography (CT) pictures are critical for the finding of COVID19. To resolve these issues, we utilized the CNN Vggnet19 engineering to analyse Coronavirus in light of CXR lung pictures. Such a device can save time in deciphering chest x-beams and increment exactness and consequently work on our clinical capacity to identify and analyse COVID19. Research is that arrangement of clinical x-beam lung pictures (which incorporate typical pictures, contaminated with microorganisms, and tainted infections including COVID19) were utilized to frame a profound CNN that could make the differentiation among clamour and helpful data then utilize this preparation to decipher new pictures by perceiving designs that show specific sicknesses, for example, Covid disease in individual pictures

INFLUENCE OF ACHIEVEMENT MOTIVATION AND PSYCHOLOGICAL ADJUSTMENT ON ACADEMIC ACHIEVEMENT: A CROSS-SECTIONAL STUDY OF SCHOOL STUDENTS

Purpose: The aim of the current research was to understand the role of achievement motivation and psychological adjustment on the academic performance of the school students. Methodology: A cross-sectional research design was employed for the study. A sample of 283 urban adolescent school students participated in the study. The students were administered measures of achievement motivation and psychological adjustment. The total percentage of marks secured in the tenth standard was used as the measure of academic performance. Pearson’s correlation coefficient and multiple hierarchical regression analysis were performed to analyze the obtained data. SPSS version 21 was used for data analysis. Main Findings: The results revealed a significant association of achievement motivation and educational adjustment with the academic performance of the students. However, there was no significant association between emotional and social adjustment with academic performance. Applications: The observations shed light on how cultivating enhanced student engagement and nurturing aspirations both within and outside classrooms may enhance the academic achievement of school students. Thus, the findings can provide greater insight to teachers, psychologists, and educational institutions to better plan the academic environment around the students. Novelty/Originality: The study gives a contemporary model to enhance the academic performance of students. Contrary to the popular perception, the results of the current study indicate no significant association of emotional and social adjustment with academic performance. However, educational adjustment and achievement motivation are associated with academic performance

System-Engineered Miniaturized Robots: From Structure to Intelligence

The development of small machines, once envisioned by Feynman decades ago, has stimulated significant research in materials science, robotics, and computer science. Over the past years, the field of miniaturized robotics has rapidly expanded with many research groups contributing to the numerous challenges inherent to this field. Smart materials have played a particularly important role as they have imparted miniaturized robots with new functionalities and distinct capabilities. However, despite all efforts and many available soft materials and innovative technologies, a fully autonomous system-engineered miniaturized robot (SEMR) of any practical relevance has not been developed yet. In this review, the foundation of SEMRs is discussed and six main areas (structure, motion, sensing, actuation, energy, and intelligence) which require particular efforts to push the frontiers of SEMRs further are identified. During the past decade, miniaturized robotic research has mainly relied on simplicity in design, and fabrication. A careful examination of current SEMRs that are physically, mechanically, and electrically engineered shows that they fall short in many ways concerning miniaturization, full-scale integration, and self-sufficiency. Some of these issues have been identified in this review. Some are inevitably yet to be explored, thus, allowing to set the stage for the next generation of intelligent, and autonomously operating SEMRs

Probability of Semantic Similarity and N-grams Pattern Learning for Data Classification

Semantic learning is an important mechanism for the document classification, but most classification approaches are only considered the content and words distribution. Traditional classification algorithms cannot accurately represent the meaning of a document because it does not take into account semantic relations between words. In this paper, we present an approach for classification of documents by incorporating two similarity computing score method. First, a semantic similarity method which computes the probable similarity based on the Bayes' method and second, n-grams pairs based on the frequent terms probability similarity score. Since, both semantic and N-grams pairs can play important roles in a separated views for the classification of the document, we design a semantic similarity learning (SSL) algorithm to improves the performance of document classification for a huge quantity of unclassified documents. The experiment evaluation shows an improvisation in accuracy and effectiveness of the proposal for the unclassified documents

Reflections on Sustaining Morale and Combat Motivation in Soldiers

Military morale and motivation formulate the signature strength of a fighting force. However, sustenance of these faculties is a bigger challenge than generating them. The exponential development in the neo-cortex and emerging social structure has made human beings hardcore individualistic. The sense of ‘self’ has become much stronger than the sense of the whole. This results in the recurrent violation of collective identity, as evidenced by the rise in numbers of misconduct behaviors, mutinies, estranged leader-led relations, desertion, fragging, and suicides. Utilizing the lessons from various ecological systems and derived scientific principles, the present paper takes note of significant researches in the area to arrive at a reflective model of Morale and Combat Motivation in soldiers. Firstly, it attempts to understand ‘why and why not the soldiers shall fight’ and subsequently give suggestive guidelines to ‘how they will continue to fight’ with particular reference to the Indian military setup. The model can be utilised by military leaders and policymakers alike who are entrusted with the herculean task of upkeeping battle-mind state of soldiers in military organisations

Equatorial counter electrojets and polar stratospheric sudden warmings - a classical example of high latitude-low latitude coupling

Favored occurrences of Equatorial Counter Electrojets (CEJs) with a quasi 16-day periodicity over Trivandrum (8.5° N, 76.5° E, 0.5° N diplat.) in association with the polar Stratospheric Sudden Warming (SSW) events are presented. It is observed that, the stratospheric temperature at ˜30 km over Trivandrum shows a sudden cooling prior to the SSWs and the CEJs of maximum intensity which occurs around this time. In general stronger CEJs are associated with more intense SSW events. The stratospheric zonal mean zonal wind over Trivandrum also exhibits a distinctly different pattern during the SSW period. These circulation changes are proposed to be conducive for the upward propagation of the lower atmospheric waves over the equatorial latitudes. The interaction of such waves with the tidal components at the upper mesosphere and its subsequent modification are suggested to be responsible for the occurrence of CEJs having planetary wave periods

Detection of Covid-19 from X-ray Images using Deep Learning Techniques

Machine Learning (ML) based forecast systems have demonstrated their significance results in detecting several diseases. ML models have for some time been utilized in numerous application regions requiring the ID and prioritization of troublesome variables for a danger. Understanding and characterizing chest x-beam (CXR) and figured tomography (CT) pictures are critical for the finding of COVID19. To resolve these issues, the CNN Vggnet19 has been utilized to analyze Corona virus in light of CXR lung pictures. Such a device can save time in deciphering chest x-beams and increment exactness and consequently work on our clinical capacity to identify and analyze COVID19. In this work, arrangement of clinical x-beam lung pictures (which incorporate typical pictures, contaminated with microorganisms, and tainted infections including COVID19) were utilized to frame a profound CNN that could make the differentiation among clamour and helpful data, then utilize this preparation to decipher new pictures by perceiving designs that show specific sicknesses, for example, Covid disease in individual pictures

First report of Lividin and Spinulosain peptides from the skin secretion of an Indian frog

Here, we report two novel peptides identified from the skin secretion, having homologies to Lividin and Spinulosain, of an endemic frog, Hydrophylax bahuvistara, of Western Ghats. This is the first report of these peptides from Indian frogs and first identification of Lividin from the Hydrophylax genus. Both peptides exhibited weak antimicrobial activity but very low haemolytic activity. The problems of naming amphibian host defense peptides (HDPs) are also discussed