Low-cost evaluation techniques for information retrieval systems: A review

For a system-based information retrieval evaluation, test collection model still remains as a costly task. Producing relevance judgments is an expensive, time consuming task which has to be performed by human assessors. It is not viable to assess the relevancy of every single document in a corpus against each topic for a large collection. In an experimental-based environment, partial judgment on the basis of a pooling method is created to substitute a complete assessment of documents for relevancy. Due to the increasing number of documents, topics, and retrieval systems, the need to perform low-cost evaluations while obtaining reliable results is essential. Researchers are seeking techniques to reduce the costs of experimental IR evaluation process by the means of reducing the number of relevance judgments to be performed or even eliminating them while still obtaining reliable results. In this paper, various state-of-the-art approaches in performing low-cost retrieval evaluation are discussed under each of the following categories; selecting the best sets of documents to be judged; calculating evaluation measures, both, robust to incomplete judgments; statistical inference of evaluation metrics; inference of judgments on relevance, query selection; techniques to test the reliability of the evaluation and reusability of the constructed collections; and other alternative methods to pooling. This paper is intended to link the reader to the corpus of ‘must read’ papers in the area of low-cost evaluation of IR systems.     

Review on COVID-19 Etiopathogenesis,Clinical Presentation and Treatment Available with Emphasis on ACE2

In December 2019, Wuhan city in the Hubei province of China reported for the first time a cluster of patients infected with a novel coronavirus, since then there has been an outburst of this disease across the globe affecting millions of human inhabitants. Severe acute respiratory syndrome coronavirus type-2 (SARS-CoV-2), is a member of beta coronavirus family which upon exposure caused a highly infectious disease called novel coronavirus disease-2019 (COVID-19). COVID-19, a probably bat originated disease was declared by World Health Organization (WHO) as a global pandemic in March 2020. Since then, despite rigorous global containment and quarantine efforts, the disease has affected nearly 56,261,952 laboratory confirmed human population and caused deaths of over 1,349,506 lives worldwide. Virus passes in majority through respiratory droplets and then enters lung epithelial cells by binding to angiotensin converting enzyme 2 (ACE2) receptor and there it undergoes replication and targeting host cells causing severe pathogenesis. Majority of human population exposed to SARS-CoV-2 having fully functional immune system undergo asymptomatic infection while 5–10% are symptomatic and only 1–2% are critically affected and requires ventilation support. Older people or people with co-morbidities are severely affected by COVID-19. These categories of patients also display cytokine storm due to dysfunctional immune response which brutally destroys the affected organs and may lead to death in some. Real time PCR is still considered as standard method of diagnosis along with other serology, radiological and biochemical investigations. Till date, no specific validated medication is available for the treatment of COVID-19 patients. Thus, this review provides detailed knowledge about the different landscapes of disease incidence, etiopathogenesis, involvement of various organs, diagnostic criteria’s and treatment guidelines followed for management of COVID-19 infection since its inception. In conclusion, extensive research to recognize novel pathways and their cross talk to combat this virus in precarious settings is our future positive hope.     

A new approach to personalization: integrating e-learning and m-learning

Most personalized learning systems are designed for either personal computers (e-learning) or mobile devices (m-learning). Our research has resulted in a cloud-based adaptive learning system that incorporates mobile devices into a classroom setting. This system is fully integrated into the formative assessment process and, most importantly, coexists with the present e-learning environment. Unlike many mobile learning systems, this system provides teachers with real-time feedback about individual and group learners. Its scalable and extendable architectural framework includes the server-side pedagogical recommendation of content adaptation based on the users?? knowledge-levels and preferences. Content is also automatically adapted to the end device that is being used. This context-aware delivery allows users to switch between e-learning and m-learning, and between devices, without any loss in personalized content. Our work builds on a web-based Adaptive Learning and Assessment System (ALAS) that is built on the Knowledge Space Theory model. At present, this system is used at school computer labs and our goal was to widen this user-base by enhancing this system to support personalized learning on mobile devices. This study describes our process of developing this technology, and contains an empirical analysis of students?? performance, perceptions, and achievements when using ALAS on both personal computers and mobile devices.     

Analysis of Modification of Liver Proteome in Diabetic Rats by 2D Electrophoresis and MALDI-TOF-MS

The uncontrolled hyperglycemia can lead to disturbances in the cell structure and functions of organs. This study was performed to analyze the “differential proteome” change in rat liver associated with diabetes mellitus in relation to effects of an anti-diabetic herb, Cynodon dactylon leaf extracts. Rats were intraperitoneally injected with alloxan (150 mg/kg/bw) and treated with C. dactylon leaf extracts (450 mg/kg/bw/day/orally). The liver proteins were subjected to proteome analysis using the advanced technologies i.e., 2D electrophoresis (2-DE) and mass spectrometry. Comparison of 2-DE protein distribution profiles among the livers from normal, alloxan-induced diabetic rats and alloxan-induced diabetic rats treated with C. dactylon leaves identified three proteins that were up-regulated in alloxan-induced diabetic rats i.e., nucleophosmin, l-xylulose reductase and carbonic anhydrase III which are known to be mainly involved in ribosome biogenesis, centrosome duplication, cell proliferation, tumor suppression, glucose metabolism, osmo-regulation, water–CO₂ balance and acid–base balance. These results help us to understand the elucidation of molecular mechanism connected to liver function and insulin associated with diabetes mellitus. These identified proteins were primarily involved in cell proliferation and homoeostasis of liver tissues upon the treatment with C. dactylon leaf extracts.