COVID-19 Epidemic Peer Support and Crisis Intervention Via Social Media

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.This article describes a peer support project developed and carried out by a group of experienced mental health professionals, organized to offer peer psychological support from overseas to healthcare professionals on the frontline of the COVID-19 outbreak in Wuhan, China. This pandemic extremely challenged the existing health care systems and caused severe mental distress to frontline healthcare workers. The authors describe the infrastructure of the team and a novel model of peer support and crisis intervention that utilized a popular social media application on smartphone. Such a model for intervention that can be used elsewhere in the face of current global pandemic, or future disaster response

High-Throughput Construction of Intron-Containing Hairpin RNA Vectors for RNAi in Plants

With the wide use of double-stranded RNA interference (RNAi) for the analysis of gene function in plants, a high-throughput system for making hairpin RNA (hpRNA) constructs is in great demand. Here, we describe a novel restriction-ligation approach that provides a simple but efficient construction of intron-containing hpRNA (ihpRNA) vectors. The system takes advantage of the type IIs restriction enzyme BsaI and our new plant RNAi vector pRNAi-GG based on the Golden Gate (GG) cloning. This method requires only a single PCR product of the gene of interest flanked with BsaI recognition sequence, which can then be cloned into pRNAi-GG at both sense and antisense orientations simultaneously to form ihpRNA construct. The process, completed in one tube with one restriction-ligation step, produced a recombinant ihpRNA with high efficiency and zero background. We demonstrate the utility of the ihpRNA constructs generated with pRNAi-GG vector for the effective silencing of various individual endogenous and exogenous marker genes as well as two genes simultaneously. This method provides a novel and high-throughput platform for large-scale analysis of plant functional genomics

Integrating Visualization Grammars With the Task Language of Data Analysts

Creating visualizations is an integral part of data analysts' work. Often based on the Grammar of Graphics, visualization grammars, such as ggplot2 and Vega-Lite, provide elegant abstractions for visualization specification. Even though visualization grammars have consistent syntax and promote the exploration of visualization design space, we have a limited understanding of how data analysts interact with visualization grammars. There is a semantic distance between analysts' task language and visualization grammars. Data analysts may have friction in executing their task language, e.g., probability distributions, and data operations, using visualization grammars. Alternatively, analysts may have trouble evaluating whether visualization outputs achieved their analytic goals. In this thesis, I explore integrating visualization grammars with analysts' task language to understand and reduce the semantic distance between them. As an example of executing visualizations, data analysts need to inspect and communicate uncertainty. However, visualizing probability distribution, such as P(A|B), remains convoluted and error-prone in visualization grammars. I designed a Probabilistic Grammar of Graphics (PGoG), an extension to ggplot2. By making expressions such as P(A|B) data objects in the grammar, PGoG enables analysts to systematically create and iterate on a variety of probabilistic visualizations, including icon arrays, product plots, and stacked density plots. PGoG reduced the edit distance between plot designs and avoids creating plots with misleading proportions. Overall, PGoG helps analysts execute visualizations by introducing probability distributions into a visualization grammar. In the direction of evaluation, I designed Datamations, a framework that helps people understand data analysis pipelines. A pipeline consists of a sequence of data operation functions (verbs) such as group_by() and summarize(), with the results of one verb piped to the next. Pipeline outputs (i.e. plots and tables) are not straightforward to interpret because the semantic concepts of data and analysis verbs are not directly visible. Datamations turn these semantic concepts into an animated explanation by leveraging the state-transition abstraction in analysis pipelines. It translates data operation verbs into animated transitions, and intermediate data states into static keyframes. I showed that Datamations helped laypeople understand Simpson's paradox better in a crowd-sourced experiment, which suggested the potential for analysts to use Datamation. PGoG and Datamations are solutions that reduce the semantic distance. As retrospection, I investigated the semantic distance itself---how do real-life analysts adapt to a visualization grammar during analysis? I conducted a qualitative study where I recruited participants (N=6) from TidyTuesday, a data science community. Through reflexive thematic analysis, I described how participants executed plots centered on analysis tasks and how plots looked, in addition to concepts in the visualization grammar. Participants had trouble evaluating their analyses due to the tight coupling between visualization and analysis specifications. By understanding how analysts have adapted to visualization grammars, we can identify more ways to reduce the semantic distance between them. Based on my three projects, I discuss ways visualization grammars can be more practical for data analysts. We can center analysts' language, the need for customization, and visual templates. Analysts can evaluate their analysis better by having visualization-analysis integration that maintains consistency and increases transparency. Computational notebooks can be a productive environment to promote this integration. Integrating visualization grammars and analysts' task language has more potential to shape and support analysts' work.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/174265/1/xpu_1.pd

Feasibility of Using Freshwater Mussels to Monitor BA and SR Contaminations in Pennsylvania Streams

With the extensive Marcellus Shale natural gas development, horizontal drilling, combined with hydraulic fracturing, produces a large quantity of saline flowback water high in Ba and Sr contents, raising health and ecological concerns in case of spills or leaks. Freshwater mussels, as sedentary filter feeders, could potentially take up Ba and Sr in the growth rings of their shells, reflecting the chemistry of the aquatic environment over time. The experimental site mussels (E. complanata and L. cariosa) were obtained from the West Branch Susquehanna River near Williamsport PA; the control site is on Buffalo Creek, Union County. From 2010 to 2014, PA Department of Environmental Protection data, at two monitoring points near West Branch sample sites, showed that the river water Ba concentrations (± 1$) were 30 (5) and 34 (13) %g/L, Sr 100 (44) and 98 (50) %g/L. In two tributaries, Ba concentrations were 19 (6) and 26 (6) %g/L, Sr 23 (8) and 32 (8) %g/L. X-ray diffraction confirmed that the mineralogy of the shell is mostly aragonite (CaCO3). Cross-sectional thin sections (0.5 mm) were observed under transmitted light microscope and environmental scanning electron microscope back-scattered electron mode to identify possible growth rings. Major (Ca) and trace elements (Ba, Sr) were analyzed along transects in shell layers using electron probe micro-analysis (EPMA). Results were reported as molar ratios of [X/Ca]shell (X Ba, Sr). Correlating [X/Ca]shell and historical [X/Ca] in the water was challenging, because of the uncertainty in the shell layer ages and the scarcity of data. If shell and water chemistry data had sufficiently high spatial and temporal resolutions, freshwater mussel shell layers could potentially be interpreted as water chemistry records

SPy: Car Steering Reveals Your Trip Route!

Vehicular data-collection platforms as part of Original Equipment Manufacturers’ (OEMs’) connected telematics services are on the rise in order to provide diverse connected services to the users. They also allow the collected data to be shared with third-parties upon users’ permission. Under the current suggested permission model, we find these platforms leaking users’ location information without explicitly obtaining users’ permission. We analyze the accuracy of inferring a vehicle’s location from seemingly benign steering wheel angle (SWA) traces, and show its impact on the driver’s location privacy. By collecting and processing real-life SWA traces, we can infer the users’ exact traveled routes with up to 71% accuracy, which is much higher than the state-of-the-art

High Prevalence of Plasmid-Mediated Quinolone Resistance and IncQ Plasmids Carrying qnrS2 Gene in Bacteria from Rivers near Hospitals and Aquaculture in China.

Effluents from hospital and aquaculture are considered important sources of quinolone resistance. However, little information is available on the impact of this effluent on nearby rivers. In this study, 188 ciprofloxacin-resistant bacterial isolates obtained from rivers near hospitals and aquaculture were screened for plasmid-mediated quinolone resistance (PMQR) genes. Species identification, antibiotic susceptibility testing, and PMQR gene transferability assessment were conducted for PMQR-positive bacteria. Representative qnrS2-encoding plasmids were subsequently sequenced using a primer-walking approach. In total, 44 isolates (23.4%) were positive for qnr genes (16 qnrB2, 3 qnrS1, and 25 qnrS2) and 32 isolates (17.0%) were positive for aac(6')-Ib-cr. Other PMQR genes were not detected. The qnrB2 and aac(6')-Ib-cr genes had a higher prevalence in aquaculture samples than in hospital samples, and were significantly associated with Enterobacteriaceae (p < 0.05). In contrast, the prevalence of qnrS2 was not site-related, but was significantly associated with Aeromonas spp. (p < 0.05). All PMQR isolates were resistant to three or more classes of antibiotics. Eleven qnrS2-harboring plasmids from Aeromonas spp., including a novel conjugative plasmid pHP18, were selected for sequencing. These plasmids were small in size (6,388-16,197 bp) and belonged to the IncQ or IncU plasmid family, with qnrS2 being part of a mobile insertion cassette. Taken together, our findings suggest that aquaculture is a possible source for aac(6')-Ib-cr and qnrB2 dissemination, and demonstrate the ubiquity of qnrS2 in aquatic environments. Finally, Aeromonas spp. served as vectors for qnrS2 with the help of IncQ-type plasmids