Development of an evidence-based medicine mobile application for the use in medical education

BACKGROUND: Evidence-based medicine (EBM) is a methodology that is being incorporated into more medical school curricula. Boston University School of Medicine was one of early adopters of Evidence Based Medicine in the United States. A growing concern in the medical community was that the complexities of applying EBM might be lost when students enter into their clinical rotations, thus there is a need for development of a tool to help reinforce the EBM principles. METHODS: The research team in collaboration with the designers of the Finding Information Framework, a custom-made EBM finding information tool, worked to develop a mobile application to help reinforce the framework for medical students. The app was designed with both Apple and PC operating systems in mind. Key features that were identified from current literature to provide the most user-friendly mobile application. Thus, the research team specifically utilized iOS and Android platforms as both platforms have a centralized app store, possess the highest volume of medical apps available, and are most widely used in the United States by medical students. RESULTS: The Finding Information Framework was a custom-made tool developed to guide new users of EBM, and help them to apply the principles in practice. The mobile application served an added convenience by allowing easy access and fast utilization of the EBM tools. The app was designed on an Android platform first due to its open-source OS and ease in app development to new programmers. Initially, the user-friendly web-based tool, App Inventor (AI), powered by Massachusetts Institute of Technology was evaluated to program the pilot Android app. Using both the AI Component Designer and the Block Editor, several problems were encountered in AI, such as the simplicity of the program and the lack of freedom in design. This moved the project to create the app natively and with a collaborative effort with the BU's Global App Initiative club. Initially, a wireframe was built using Balsamiq. Subsequently, the Android app was built using Android SDK and the iOS app was built in XCode with Objective C; both platforms had design sections prepared in Sketch, Adobe Photoshop and Illustrator. The last and final step was to obtain Boston University branding privileges for the app. CONCLUSION: The research team identified necessary features based on research to build a user-friendly, professional mobile application of an information mastery framework that can be used off-line. The app is called FIF as it is the title of the information mastery tool designed by BUSM EBM-VIG. With a clear mobile interface, it will be beneficial to the learning and training of medical students in EBM

Bayesian Approach for Identification of Multiple Events in an Early Warning System

The 2011 Tohoku earthquake (M_w 9.0) was followed by a large number of aftershocks that resulted in 70 early warning messages in the first month after the mainshock. Of these warnings, a non‐negligible fraction (63%) were false warnings in which the largest expected seismic intensities were overestimated by at least two intensities or larger. These errors can be largely attributed to multiple concurrent aftershocks from distant origins that occur within a short period of time. Based on a Bayesian formulation that considers the possibility of having more than one event present at any given time, we propose a novel likelihood function suitable for classifying multiple concurrent earthquakes, which uses amplitude information. We use a sequential Monte Carlo heuristic whose complexity grows linearly with the number of events. We further provide a particle filter implementation and empirically verify its performance with the aftershock records after the Tohoku earthquake. The initial case studies suggest promising performance of this method in classifying multiple seismic events that occur closely in time

Communicating Uncertainty and Risk in Air Quality Maps

Environmental sensors provide crucial data for understanding our surroundings. For example, air quality maps based on sensor readings help users make decisions to mitigate the effects of pollution on their health. Standard maps show readings from individual sensors or colored contours indicating estimated pollution levels. However, showing a single estimate may conceal uncertainty and lead to underestimation of risk, while showing sensor data yields varied interpretations. We present several visualizations of uncertainty in air quality maps, including a frequency-framing "dotmap" and small multiples, and we compare them with standard contour and sensor-based maps. In a user study, we find that including uncertainty in maps has a significant effect on how much users would choose to reduce physical activity, and that people make more cautious decisions when using uncertainty-aware maps. Additionally, we analyze think-aloud transcriptions from the experiment to understand more about how the representation of uncertainty influences people's decision-making. Our results suggest ways to design maps of sensor data that can encourage certain types of reasoning, yield more consistent responses, and convey risk better than standard maps

Asian American Studies

Asian Americans have faced a long heritage of exclusion and injustice in relation to race, class, gender, sexuality, colonialism, immigration, labor, and a myriad of other problems throughout their history, particularly during times of shifting demographics, economic crisis, or war. In today\u27s society, these inequities go largely unnoticed and are not addressed as often as they should be. This zine is meant to bring those inequities to light and discuss the history of Asians in America. We cover a wide range of topics, from the Vietnam war, to Japanese concentration camps, to the “model minority” myth. Understanding the history of Asian Americans is crucial to understanding the history of the United States as a whole. The United States is a land of immigrants and people of diverse backgrounds and identities. The United States is also a land with deep roots in inequality, prejudice, and violence towards minorities, including Asians. Many of the inequities that Asian Americans had to face years ago are still not solved. For example, in our zine we included some brief discussion about COVID-19 and how its existence has, unfortunately, perpetuated stereotypes about Asians that have existed since the 1850s. As students, we read and analyzed the material we wrote about in our zine, all while drawing parallels from history to modern day life. It opened our eyes to the history of Asian Americans and why their stories are critical to understanding not just the history of the United States, but as well as the present-day United States. We encourage you, as the reader, to do the same and draw parallels from Asian American history to the present day as you read our zine. Thank you.https://digital.sandiego.edu/ethn-zines/1011/thumbnail.jp

Active inductor shunt peaking in high-speed VCSEL driver design

An all transistor active inductor shunt peaking structure has been used in a prototype of 8-Gbps high-speed VCSEL driver which is designed for the optical link in ATLAS liquid Argon calorimeter upgrade. The VCSEL driver is fabricated in a commercial 0.25-um Silicon-on-Sapphire (SoS) CMOS process for radiation tolerant purpose. The all transistor active inductor shunt peaking is used to overcome the bandwidth limitation from the CMOS process. The peaking structure has the same peaking effect as the passive one, but takes a small area, does not need linear resistors and can overcome the process variation by adjust the peaking strength via an external control. The design has been tapped out, and the prototype has been proofed by the preliminary electrical test results and bit error ratio test results. The driver achieves 8-Gbps data rate as simulated with the peaking. We present the all transistor active inductor shunt peaking structure, simulation and test results in this paper.Comment: 4 pages, 6 figures and 1 table, Submitted to 'Chinese Physics C

High-mass Starless Clumps in the inner Galactic Plane: the Sample and Dust Properties

We report a sample of 463 high-mass starless clump (HMSC) candidates within $-60\deg<l<60\deg$ and $-1\deg<b<1\deg$. This sample has been singled out from 10861 ATLASGAL clumps. All of these sources are not associated with any known star-forming activities collected in SIMBAD and young stellar objects identified using color-based criteria. We also make sure that the HMSC candidates have neither point sources at 24 and 70 \micron~nor strong extended emission at 24 $\mu$m. Most of the identified HMSCs are infrared ($\le24$ $\mu$m) dark and some are even dark at 70 $\mu$m. Their distribution shows crowding in Galactic spiral arms and toward the Galactic center and some well-known star-forming complexes. Many HMSCs are associated with large-scale filaments. Some basic parameters were attained from column density and dust temperature maps constructed via fitting far-infrared and submillimeter continuum data to modified blackbodies. The HMSC candidates have sizes, masses, and densities similar to clumps associated with Class II methanol masers and HII regions, suggesting they will evolve into star-forming clumps. More than 90% of the HMSC candidates have densities above some proposed thresholds for forming high-mass stars. With dust temperatures and luminosity-to-mass ratios significantly lower than that for star-forming sources, the HMSC candidates are externally heated and genuinely at very early stages of high-mass star formation. Twenty sources with equivalent radius $r_\mathrm{eq}<0.15$ pc and mass surface density $\Sigma>0.08$ g cm$^{-2}$ could be possible high-mass starless cores. Further investigations toward these HMSCs would undoubtedly shed light on comprehensively understanding the birth of high-mass stars.Comment: 16 pages, 15 figures, and 5 tables. Accepted for publication in ApJS. FITS images for the far-IR to sub-mm data, H2 column density and dust temperature maps of all the HMSC candidates are available at https: //yuanjinghua.github.io/hmscs.html. Codes used for this work are publicly available from https://github.com/yuanjinghua/HMSCs_ca

Applying positive psychology to selling behaviors: A moderated–mediation analysis integrating subjective well-being, coping and organizational identity

Subjective well-being (SWB) has been widely found to have a profound impact on the individual, yet its application in the sales field remains unexplored. Applying Broaden and Build theory, this study examines SWB and its influence on the selling behaviors, specifically adaptive selling and sales creativity. Using salesperson coping as a mediator and organizational identity (OI) as a moderator, the relationship between SWB and selling behaviors was further explored. Survey results from 334 sales professionals from multiple industries in India showed that SWB enhances adaptive selling and sales creativity directly and via the mediating effect of salesperson coping. Our results helps us to better understand this potential strategic synergy between salespeople's internal qualities and skills and their organizational identity, our research highlights on what we believe are three key contributors to salesperson creativity and adaptive selling: subjective wellbeing (SWB), positive coping, and organizational identity (OI)