Teaching Programming to the Post-Millennial Generation: Pedagogic Considerations for an IS Course

Teaching introductory programming to IS students is challenging. The educational, technological, demographic, and cultural landscape has changed dramatically in recent years. The post-millennial generation has different needs and expectations in an era of open resources. Learning to program is perceived as difficult, teaching approaches are diverse, and there is little research on what works best. In this paper, we share our experiences in developing, testing, and implementing a new design for teaching introductory IS programming at the undergraduate level. We describe pedagogic considerations and present teaching tips for a blended course that combines best practices with experimentation. Our approach recognizes the changing nature of the student body, the needs of an IS major in the current environment, and the worldwide shift in education from instructor-centered to student-centered learning

Ask-the-expert: Active Learning Based Knowledge Discovery Using the Expert

Often the manual review of large data sets, either for purposes of labeling unlabeled instances or for classifying meaningful results from uninteresting (but statistically significant) ones is extremely resource intensive, especially in terms of subject matter expert (SME) time. Use of active learning has been shown to diminish this review time significantly. However, since active learning is an iterative process of learning a classifier based on a small number of SME-provided labels at each iteration, the lack of an enabling tool can hinder the process of adoption of these technologies in real-life, in spite of their labor-saving potential. In this demo we present ASK-the-Expert, an interactive tool that allows SMEs to review instances from a data set and provide labels within a single framework. ASK-the-Expert is powered by an active learning algorithm for training a classifier in the backend. We demonstrate this system in the context of an aviation safety application, but the tool can be adopted to work as a simple review and labeling tool as well, without the use of active learning

Apical targeting of syntaxin 3 is essential for epithelial cell polarity

In polarized epithelial cells, syntaxin 3 localizes to the apical plasma membrane and is involved in membrane fusion of apical trafficking pathways. We show that syntaxin 3 contains a necessary and sufficient apical targeting signal centered around a conserved FMDE motif. Mutation of any of three critical residues within this motif leads to loss of specific apical targeting. Modeling based on the known structure of syntaxin 1 revealed that these residues are exposed on the surface of a three-helix bundle. Syntaxin 3 targeting does not require binding to Munc18b. Instead, syntaxin 3 recruits Munc18b to the plasma membrane. Expression of mislocalized mutant syntaxin 3 in Madin-Darby canine kidney cells leads to basolateral mistargeting of apical membrane proteins, disturbance of tight junction formation, and loss of ability to form an organized polarized epithelium. These results indicate that SNARE proteins contribute to the overall specificity of membrane trafficking in vivo, and that the polarity of syntaxin 3 is essential for epithelial cell polarization

The SNARE Protein Syntaxin 3 Confers Specificity for Polarized Axonal Trafficking in Neurons.

Cell polarity and precise subcellular protein localization are pivotal to neuronal function. The SNARE machinery underlies intracellular membrane fusion events, but its role in neuronal polarity and selective protein targeting remain unclear. Here we report that syntaxin 3 is involved in orchestrating polarized trafficking in cultured rat hippocampal neurons. We show that syntaxin 3 localizes to the axonal plasma membrane, particularly to axonal tips, whereas syntaxin 4 localizes to the somatodendritic plasma membrane. Disruption of a conserved N-terminal targeting motif, which causes mislocalization of syntaxin 3, results in coincident mistargeting of the axonal cargos neuron-glia cell adhesion molecule (NgCAM) and neurexin, but not transferrin receptor, a somatodendritic cargo. Similarly, RNAi-mediated knockdown of endogenous syntaxin 3 leads to partial mistargeting of NgCAM, demonstrating that syntaxin 3 plays an important role in its targeting. Additionally, overexpression of syntaxin 3 results in increased axonal growth. Our findings suggest an important role for syntaxin 3 in maintaining neuronal polarity and in the critical task of selective trafficking of membrane protein to axons

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation

A major focus of the commercial aviation community is discovery of unknown safety events in flight operations data. Data-driven unsupervised anomaly detection methods are better at capturing unknown safety events compared to rule-based methods which only look for known violations. However, not all statistical anomalies that are discovered by these unsupervised anomaly detection methods are operationally significant (e.g., represent a safety concern). Subject Matter Experts (SMEs) have to spend significant time reviewing these statistical anomalies individually to identify a few operationally significant ones. In this paper we propose an active learning algorithm that incorporates SME feedback in the form of rationales to build a classifier that can distinguish between uninteresting and operationally significant anomalies. Experimental evaluation on real aviation data shows that our approach improves detection of operationally significant events by as much as 75% compared to the state-of-the-art. The learnt classifier also generalizes well to additional validation data sets

Vaccination Status and Outcome of Patients at a Dedicated COVID-19 Centre, Delhi, India: A Retrospective Study

Introduction: Coronavirus Disease-2019 (COVID-19) vaccine provides strong protection against transmission, serious illness, hospitalisation, and death. As India carried out robust vaccination drive covering more than two third of its population, the study was aimed to highlight the effects of vaccination status of patient on the outcome of COVID-19 infection. Aim: To describe the relation of vaccination with disease severity and its outcome during the third wave of COVID-19. Materials and Methods: It was a single-centre retrospective, cross-sectional study conducted in a dedicated COVID-19 Hospital (Guru Tegh Bahadur Hospital) in Delhi, India. A total of 257 patients were admitted between 10th January 2022 to 9th February 2022, and 246 were included in the study. For each individual, demographic, and clinical data was collected. Vaccination data was extracted via the CoWin platform which included vaccine type, as well as date of administration. The profile of patients was established based on clinical examination, laboratory data, nursing record and radiological record during the course of hospitalisation. The clinical outcome was described as discharge, length of hospital stays, and in-hospital death in relation to the vaccination status. Statistical analysis was done using Statistical Package for the Social Sciences (SPSS), version 22.0. Results: Total of 246 patients were divided into three groups- 97 were fully vaccinated, 46 were partially vaccinated and 103 were unvaccinated. Both vaccinated and unvaccinated groups had similar percentage of co-morbidities i.e. 61.3% vs 63.5%. Those who were fully vaccinated were more likely to maintain saturation at room air 30.9% vs 26.1% vs 3.9%, had lesser requirements of mechanical ventilation (6.2% vs 15.2% vs 21.4%), shorter duration of hospital stay (4.2 vs 5.3 vs 7.2 days), and lesser mortality (9.3% vs 21.7% vs 33%) as compared to the partially vaccinated and unvaccinated patients respectively. Conclusion: The beneficial effect of the vaccination was observed in severity, mortality, morbidity, and lesser number of hospitalisations. Hence, vaccination coverage was critical in reducing the severity in reducing the and the hospitalisation in third wave of COVID-19

Red light variation an effective alternative to regulate biomass and lipid profiles in Phaeodactylum tricornutum

Abstract: Marine water diatom Phaeodactylum tricornutum is a photosynthetic organism that is known to respond to the changing light environment and adapt to different temperatures to prevent photoinhibition and maintain its metabolic functions. The objective of the present study was to test whether light shift variations in different growth phases impact the growth and lipid metabolism of P. tricornutum. Thus, we investigated R exposure in different growth phases to find the most effective light shift condition. The results showed that substituting white light (W) by red light (R) under autotrophic conditions, a condition called red shift (RS), increased biomass and lipid content compared to levels found under continuous W or R exposure alone. We observed an increase by 2-fold biomass and 2.3-fold lipid content in RS as compared to W. No significant change was observed in the morphology of lipid droplets, but the fatty acid (FA) composition was altered. Specifically, polyunsaturated FAs were increased, whereas monounsaturated FAs decreased in P. tricornutum grown in RS compared to W control. Therefore, we propose that a light shift during the beginning of the stationary phase is a low-cost cultivation strategy to boost the total biomass and lipids in P. tricornutum