Transition in pharmacology: From theoretical knowledge of medicines to practice-oriented approach. Do role-plays help?

Background: Pharmacology, a subject criticized by medicos as ‘dry and volatile’ is in a stage of constant reformation. Traditional teaching-learning in pharmacology has focused more on theoretical knowledge of medicines with little emphasis on the art and science of communicating the same to patients in actual practice. Role-play is one novel method which attracts learners to gain knowledge through concrete experience, there-by bringing in a behavioural change that persists eventually. The objective of this study was to evaluate the effectiveness of role-play as an educational tool in teaching patient education and counseling skills regarding medications prescription for ischemic heart disease (IHD).Methods: A quantitative, randomized, interventional study with pre & post-OSPE using a pre-validated checklist (modified-Calgary-Cambridge) was conducted in 84, II-MBBS students. The scores obtained in intervention group (Lecture-IHD counseling + Role-play) were compared with the control group (Lecture) using Wilcoxon test for paired-data and Mann-Whitney test for inter-group comparisons.Results: Paired-data analysis showed an increase in post-test mean scores in both control and intervention groups following training. However, inter-group comparisons revealed statistically significant improvement in 8 of the 13 parameters in intervention group. Students in intervention group stressed more on pharmacological aspects of medications, along with emergency measures and need for follow-up. Hence it can be said that role-plays played a significant role in improving communication skills regarding medications prescription.Conclusions: Medical communication skills course for II-MBBS students may enable them to demonstrate better patient-doctor interactions. Role-plays are an effective tool to acquire technical and behavioural skills to deal with real-life situations through simulation

Slim U-Net: Efficient Anatomical Feature Preserving U-net Architecture for Ultrasound Image Segmentation

We investigate the applicability of U-Net based models for segmenting Urinary Bladder (UB) in male pelvic view UltraSound (US) images. The segmentation of UB in the US image aids radiologists in diagnosing the UB. However, UB in US images has arbitrary shapes, indistinct boundaries and considerably large inter- and intra-subject variability, making segmentation a quite challenging task. Our study of the state-of-the-art (SOTA) segmentation network, U-Net, for the problem reveals that it often fails to capture the salient characteristics of UB due to the varying shape and scales of anatomy in the noisy US image. Also, U-net has an excessive number of trainable parameters, reporting poor computational efficiency during training. We propose a Slim U-Net to address the challenges of UB segmentation. Slim U-Net proposes to efficiently preserve the salient features of UB by reshaping the structure of U-Net using a less number of 2D convolution layers in the contracting path, in order to preserve and impose them on expanding path. To effectively distinguish the blurred boundaries, we propose a novel annotation methodology, which includes the background area of the image at the boundary of a marked region of interest (RoI), thereby steering the model's attention towards boundaries. In addition, we suggested a combination of loss functions for network training in the complex segmentation of UB. The experimental results demonstrate that Slim U-net is statistically superior to U-net for UB segmentation. The Slim U-net further decreases the number of trainable parameters and training time by 54% and 57.7%, respectively, compared to the standard U-Net, without compromising the segmentation accuracy.Comment: Accepted in 9th ACM International Conference on Biomedical and Bioinformatics Engineering (ICBBE) 2022 http://www.icbbe.com

Template-Stripped Multifunctional Wedge and Pyramid Arrays for Magnetic Nanofocusing and Optical Sensing

We present large-scale reproducible fabrication of multifunctional ultrasharp metallic structures on planar substrates with capabilities including magnetic field nanofocusing and plasmonic sensing. Objects with sharp tips such as wedges and pyramids made with noble metals have been extensively used for enhancing local electric fields via the lightning-rod effect or plasmonic nanofocusing. However, analogous nanofocusing of magnetic fields using sharp tips made with magnetic materials has not been widely realized. Reproducible fabrication of sharp tips with magnetic as well as noble metal layers on planar substrates can enable straightforward application of their material and shape-derived functionalities. We use a template-stripping method to produce plasmonic-shell-coated nickel wedge and pyramid arrays at the wafer-scale with tip radius of curvature close to 10 nm. We further explore the magnetic nanofocusing capabilities of these ultrasharp substrates, deriving analytical formulas and comparing the results with computer simulations. These structures exhibit nanoscale spatial control over the trapping of magnetic microbeads and nanoparticles in solution. Additionally, enhanced optical sensing of analytes by these plasmonic-shell-coated substrates is demonstrated using surface-enhanced Raman spectroscopy. These methods can guide the design and fabrication of novel devices with applications including nanoparticle manipulation, biosensing, and magnetoplasmonics

Impact of emission mitigation on ozone-induced wheat and rice damage in India

In this study, we evaluate the potential impact of ground level ozone (O3) on rice and wheat yield in top 10 states in India during 2005. This study is based on simulated hourly O3 concentration from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), district-wise seasonal crop production datasets and accumulated daytime hourly O3 concentration over a threshold of 40 ppbv (AOT40) indices to estimate crop yield damage resulting from ambient O3 exposure. The response of nitrogen oxides (NOx) and volatile organic compounds (VOC) mitigation action is evaluated based on ground level O3 simulations with individual reduction in anthropogenic NOx and VOC emissions over the Indian domain. The total loss of wheat and rice from top 10 producing states in India is estimated to be 2.2 million tonnes (3.3%) and 2.05 million tonnes (2.5%) respectively. Sensitivity model study reveals relatively 93% decrease in O3-induced crop yield losses in response to anthropogenic NOx emission mitigation. The response of VOC mitigation action results in relatively small changes of about 24% decrease in O3-induced crop yield losses, suggesting NOx as a key pollutant for mitigation. VOC also contribute to crop yield reduction but their effects are a distant second compared to NOx effects

Fatal Dog Bite Injury – A Case Report

Background: Dog bite is one of the most common childhood accidents causing significant morbidity and mortality in pediatrics age group (1). The exposed position compounded by the short stature of children makes the face very vulnerable to dog bite or animal bite injuries. Unlike wounds inflicted by assaults and accidents, animal bite wounds are distinctive as they are puncture type deep wounds which are injected by the bite force, with inoculums of pathogenic bacteria from the saliva of the attacking dog.Case Report: A case of a 2 month-old child who had succumbed to multiple facial and head bite injuries is presented. At autopsy, multiple bite wounds were noted on the upper part of body like face, head, chest and abdomen. Distinctive bite marks diagnostic of canine dentition were present, most prominently on the head, face and chest. Death was due to cranio-cerebral damage.Conclusion: Public health notification should occur for all dog bites. This would facilitate the development of regional dog bite registries with information on incidence and dogs at risk, which in turn could guide policies such as leash laws and licensing

Effect of screening on shot noise in diffusive mesoscopic conductors

Shot noise in diffusive mesoscopic conductors, at finite observation frequencies $\omega$ (comparable to the reciprocal Thouless time $\tau_T^{-1}$), is analyzed with an account of screening. At low frequencies, the well-known result $S_I(\omega)=2eI/3$ is recovered. This result is valid at arbitrary $\omega \tau_T$ for wide conductors longer than the screening length. However, at least for two very different systems, namely, wide and short conductors, and thin conductors over a close ground plane, noise approaches a different fundamental level, $S_I(\omega) = eI$, at $\omega \tau _T\gg 1$.Comment: 5 pages, 3 figures. Published version. Also available in the journal's format at http://hana.physics.sunysb.edu/~yehuda/cv/papers/shotnoise.pd

Mapping 6D N = 1 supergravities to F-theory

We develop a systematic framework for realizing general anomaly-free chiral 6D supergravity theories in F-theory. We focus on 6D (1, 0) models with one tensor multiplet whose gauge group is a product of simple factors (modulo a finite abelian group) with matter in arbitrary representations. Such theories can be decomposed into blocks associated with the simple factors in the gauge group; each block depends only on the group factor and the matter charged under it. All 6D chiral supergravity models can be constructed by gluing such blocks together in accordance with constraints from anomalies. Associating a geometric structure to each block gives a dictionary for translating a supergravity model into a set of topological data for an F-theory construction. We construct the dictionary of F-theory divisors explicitly for some simple gauge group factors and associated matter representations. Using these building blocks we analyze a variety of models. We identify some 6D supergravity models which do not map to integral F-theory divisors, possibly indicating quantum inconsistency of these 6D theories.Comment: 37 pages, no figures; v2: references added, minor typos corrected; v3: minor corrections to DOF counting in section

Expert-Agnostic Ultrasound Image Quality Assessment using Deep Variational Clustering

Ultrasound imaging is a commonly used modality for several diagnostic and therapeutic procedures. However, the diagnosis by ultrasound relies heavily on the quality of images assessed manually by sonographers, which diminishes the objectivity of the diagnosis and makes it operator-dependent. The supervised learning-based methods for automated quality assessment require manually annotated datasets, which are highly labour-intensive to acquire. These ultrasound images are low in quality and suffer from noisy annotations caused by inter-observer perceptual variations, which hampers learning efficiency. We propose an UnSupervised UltraSound image Quality assessment Network, US2QNet, that eliminates the burden and uncertainty of manual annotations. US2QNet uses the variational autoencoder embedded with the three modules, pre-processing, clustering and post-processing, to jointly enhance, extract, cluster and visualize the quality feature representation of ultrasound images. The pre-processing module uses filtering of images to point the network's attention towards salient quality features, rather than getting distracted by noise. Post-processing is proposed for visualizing the clusters of feature representations in 2D space. We validated the proposed framework for quality assessment of the urinary bladder ultrasound images. The proposed framework achieved 78% accuracy and superior performance to state-of-the-art clustering methods.Comment: Accepted in IEEE International Conference on Robotics and Automation (ICRA) 202

Enhancement strategies for hydrogen production from wastewater: A review

© 2016 Bentham Science Publishers. This mini review focuses on the current developments in the field of dark fermentation technologies using wastewater as carbon and nutrient source in batch reactors. Besides, the major microbiota (pure, enriched mixed, co and mixed cultures) involved in the process have been emphasized. Additionally, problems associated with the lower production performances and the overcoming strategies applied to enhance the production rate (HPR) and yield (HY) bybio-augmentation, immobilization, enrichment technique and nano particles (NP) addition were also discussed. This mini review provides more insights about the recent developments in the dark fermentative hydrogen production (DHFP) process and their advantages in a brief manner. The perspective towards the development of sustainable society by using bioH2 technology is enlightened