LT-ViT: A Vision Transformer for multi-label Chest X-ray classification

Vision Transformers (ViTs) are widely adopted in medical imaging tasks, and some existing efforts have been directed towards vision-language training for Chest X-rays (CXRs). However, we envision that there still exists a potential for improvement in vision-only training for CXRs using ViTs, by aggregating information from multiple scales, which has been proven beneficial for non-transformer networks. Hence, we have developed LT-ViT, a transformer that utilizes combined attention between image tokens and randomly initialized auxiliary tokens that represent labels. Our experiments demonstrate that LT-ViT (1) surpasses the state-of-the-art performance using pure ViTs on two publicly available CXR datasets, (2) is generalizable to other pre-training methods and therefore is agnostic to model initialization, and (3) enables model interpretability without grad-cam and its variants.Comment: 5 pages, 2 figure

Role of heat stress in migration decisions : a case study of Faisalabad

This study explores the relation between migration decisions and heat stress, its impact on livelihoods and thermal comfort levels both at home and at work. Many developing countries face declining worker productivity due to heat stress. Migration provides an opportunity to reduce risk and diversify livelihoods. Extreme heat stress is associated with migration because it affects livelihood and reduces farm and non-farm income. The paper is based on a household survey using a structured questionnaire to compare two study sites 1) Rural areas of Faisalabad district 2) Peri-urban areas of Faisalabad city.UK Government’s Department for International Development (DfID)International Development Research Centre (IDRC

Application of Treated and Untreated Cucumis Sativus Peels for Elimination of Congo Red Dye from Aqueous Solutions: An Adsorption Study

Chief objective of present study was to examine the eliminative potential of congo red dye from aqueous solutions by using adsorption process with the help of untreated Cucumis sativus peels (UCSP) and treated Cucumis sativus peels (TCSP) in the form of comparison. An adsorptive elimination of congo red dye was attain first time by using Cucumis sativus peels from aqueous solutions. The effects of different parameters in adsorption process like effect of pH, dose of adsorbent, initial concentration and agitation time were also investigated. Maximum percentage elimination of congo red dye by using untreated Cucumis sativus peels was occurred at pH of 7, adsorbent dose of 300 mg, initial concentration of 150 ppm and agitation time of 250 minutes, which was 95.31% and using treated Cucumis sativus peels, it was occurred at pH of 7, adsorbent dose of 500 mg, agitation time 250 minutes and initial concentration of 120 ppm, which was 98.48%. Adsorption kinetics study indicated that adsorption of congo red dye was best followed by pseudo second order kinetics model as compared to pseudo first order kinetics model. Treated Cucumis sativus peels was found to be performed well for elimination of congo red dye from aqueous solutions as compared to untreated Cucumis sativus peels

Machine Learning and Internet of Things Enabled Monitoring of Post-Surgery Patients: A Pilot Study

Artificial Intelligence (AI) and Internet of Things (IoT) offer immense potential to transform conventional healthcare systems. The IoT and AI enabled smart systems can play a key role in driving the future of smart healthcare. Remote monitoring of critical and non-critical patients is one such field which can leverage the benefits of IoT and machine learning techniques. While some work has been done in developing paradigms to establish effective and reliable communications, there is still great potential to utilize optimized IoT network and machine learning technique to improve the overall performance of the communication systems, thus enabling fool-proof systems. This study develops a novel IoT framework to offer ultra-reliable low latency communications to monitor post-surgery patients. The work considers both critical and non-critical patients and is balanced between these to offer optimal performance for the desired outcomes. In addition, machine learning based regression analysis of patients’ sensory data is performed to obtain highly accurate predictions of the patients’ sensory data (patients’ vitals), which enables highly accurate virtual observers to predict the data in case of communication failures. The performance analysis of the proposed IoT based vital signs monitoring system for the post-surgery patients offers reduced delay and packet loss in comparison to IEEE low latency deterministic networks. The gradient boosting regression analysis also gives a highly accurate prediction for slow as well as rapidly varying sensors for vital sign monitoring

Impact of diabetes mellitus on nerves

Background: Involvement of the peripheral and autonomic nervous systems is probably the most common complication of diabetes. The main symptoms of diabetic polyneuropathy include negative symptoms (those related to nerve fiber loss or dysfunction) such as numbness and weakness, and positive symptoms (those related to abnormal function of surviving nerve fibers) such as tingling and pain.Methods: This was a cross-sectional study held in diabetic clinic of Nishter hospital, Multan, Pakistan. The study included any diabetic patients showing symptoms of neuropathy.Results: There were total of 140 in this study. This study included 85% of male and 15% of female. Most common symptoms of diabetic neuropathy were pain (70%) and tingling (70%) followed by numbness in 65% of patients. There were 28 patients in 5 years duration of diabetes, 35 people in 6-10 years duration, 21 patients in 11-15 years duration, and 14 patients in 20+ years duration.Conclusions: Neuropathy due to diabetes is crippling especially when pain is the prominent symptoms. Autonomic symptoms like constipation and lightheadedness are discomforting for the patients. The most commonly used screening test is vibrating tuning fork test which is east to perform is clinical setting and is not time consuming. Diabetic patients need to take special care of

A review of spatial variations of multiple natural hazards and risk management strategies in Pakistan

Natural hazards are dynamic and unpredictable events that are a continuous threat to global socio-economic development. Humans’ reactions to these catastrophes are influenced by their proximity to the hazards and their ability to anticipate, resist, cope with, and recover from their consequences. Due to climatic changes, the risk of multiple natural hazards is expected to increase in several regions of Pakistan. There is a pressing need to understand the spatial discrepancies of natural hazards due to climate change and identifying the regions that require special measures to increase resilience, achieve adaptation, and sustainable development goals. This paper synthesizes the related literature to understand spatial variations of natural hazards due to climate changes across Pakistan. The Emergency Events Database (EM-DAT), National Aeronautics and Space Administration Global Landslide Catalog (NASA-GLC), National Disaster Management Authority (NDMA), and Pakistan Meteorological Department (PMD) are utilized to analyze spatial discrepancies and vulnerabilities to natural hazards. This study unveils that Pakistan’s current risk analysis and management strategies seem to be obsolete compared to global trends. Because of spatial variations of hazards, most research work on hazard risk assessments and risk management focuses on a single hazard, neglecting the co-occurrence impact of different natural hazards. Very limited studies are included in comprehensive multi-hazard risk strategies. Therefore, in Pakistan, risk management would require integrated multi-hazard risk assessment approaches to detect, analyze, measure, and evaluate various natural hazards, their effects, and interconnections. Moreover, the Pakistan governmental institutes dealing with natural hazards should focus on pre-disaster mitigation and resilience techniques instead of investing only in post-disaster relief activities

Migration futures in Asia and Africa : economic opportunities and distributional effects : the case of Pakistan

Declining agricultural yields and diminishing livelihood prospects due to climate change may motivate people to move households in search of better opportunities. This study applies two types of analyses: (i) a livelihood resilience approach: by constructing a resilience index for migrant and non-migrant households, and (ii) a case study approach for each study site, towards better understanding of factors that drive out-migration from rural areas; the social impacts of male out-migration on left-behind families; and the profile of current and potential migrants among households. This report is part of a long-term research agenda that guides Pathways to Resilience in Semi-arid Economies (PRISE).UK Government’s Department for International Development (DfID)International Development Research Centre (IDRC

What defines livelihood vulnerability in rural semi‑arid areas? : evidence from Pakistan

In view of the enhanced vulnerability of semi-arid regions to climate change (IPCC AR5 Climate Change 2014: Mitigation of Climate Change) this paper attempts to identify the key determinants of vulnerability in three semi-arid districts of Pakistan using an indicator-based approach. Semi-arid lands in Pakistan predominantly feature irrigated agriculture. Results of IPCC–LVI show varying levels of vulnerability experienced by farmers in the three study sites. This paper uses the IPCC-Livelihood Vulnerability Index for developing site-specific vulnerability scores that portray the unique aspects that determine districts’ vulnerability to climate change such as water supply, access to information, rural poverty, health, education and genderUK's Department for International Development (DFID

Awareness to Handle Research and Healthcare Waste (RHCW) in teaching and research institutes; a comprehensive review

Environmental pollution has become the major challenge not only for developing countries but also for developed ones Worldwide. The major goal of this comprehensive review is to compile the reference data regarding the different types of waste generated in teaching, research, and healthcare institutes and specific strategy to manage such wastes. In addition to the pharmaceutical, leather, chemicals, food, and paper industries, teaching, research, and healthcare institutions are also significant sources of different types of Non-hazardous as well as hazardous wastes. Therefore, a simple and implementable guideline for cleaning and waste disposal services in such institutions requires strict adherence to applicable policies and procedures. Research and healthcare waste (RHCW) management is a joint effort among Research Laboratory Personnel, Healthcare facilitators, Building Services Personnel, and Local Environmental Health and Safety Personnel. As Pakistan is among the developing countries situated in South Asia, most of the institutes, including teaching, research, and healthcare, try to follow the WHO guidance or manage hazardous and non-hazardous wastes with self-planned strategies. Although most of the local Governing bodies and Institutional bodies are trying to handle the wastes at their levels by following different protocols, introducing a protocol at the National level is the need of the current era to fight against environmental pollutants.