Web-accessible application for identifying pathogenic transcripts with RNA-seq: Increased sensitivity in diagnosis of neurodevelopmental disorders.

For neurodevelopmental disorders (NDDs), a molecular diagnosis is key for management, predicting outcome, and counseling. Often, routine DNA-based tests fail to establish a genetic diagnosis in NDDs. Transcriptome analysis (RNA sequencing [RNA-seq]) promises to improve the diagnostic yield but has not been applied to NDDs in routine diagnostics. Here, we explored the diagnostic potential of RNA-seq in 96 individuals including 67 undiagnosed subjects with NDDs. We performed RNA-seq on single individuals' cultured skin fibroblasts, with and without cycloheximide treatment, and used modified OUTRIDER Z scores to detect gene expression outliers and mis-splicing by exonic and intronic outliers. Analysis was performed by a user-friendly web application, and candidate pathogenic transcriptional events were confirmed by secondary assays. We identified intragenic deletions, monoallelic expression, and pseudoexonic insertions but also synonymous and non-synonymous variants with deleterious effects on transcription, increasing the diagnostic yield for NDDs by 13%. We found that cycloheximide treatment and exonic/intronic Z score analysis increased detection and resolution of aberrant splicing. Importantly, in one individual mis-splicing was found in a candidate gene nearly matching the individual's specific phenotype. However, pathogenic splicing occurred in another neuronal-expressed gene and provided a molecular diagnosis, stressing the need to customize RNA-seq. Lastly, our web browser application allowed custom analysis settings that facilitate diagnostic application and ranked pathogenic transcripts as top candidates. Our results demonstrate that RNA-seq is a complementary method in the genomic diagnosis of NDDs and, by providing accessible analysis with improved sensitivity, our transcriptome analysis approach facilitates wider implementation of RNA-seq in routine genome diagnostics.

Alveolus analysis: a web browser-based tool to analyze lung intravital microscopy.

BACKGROUND: Acute lung injury and the acute respiratory distress syndrome are characterized by pulmonary inflammation, reduced endothelial barrier integrity and filling of the alveolar space with protein rich edema fluid and infiltrating leukocytes. Animal models are critical to uncovering the pathologic mechanisms of this devastating syndrome. Intravital imaging of the intact lung via two-photon intravital microscopy has proven a valuable method to investigate lung injury in small rodent models through characterization of inflammatory cells and vascular changes in real time. However, respiratory motion complicates the analysis of these time series images and requires selective data extraction to stabilize the image. Consequently, analysis of individual alveoli may not provide a complete picture of the integrated mechanical, vascular and inflammatory processes occurring simultaneously in the intact lung. To address these challenges, we developed a web browser-based visualization application named Alveolus Analysis to process, analyze and graphically display intravital lung microscopy data. RESULTS: The designed tool takes raw temporal image data as input, performs image preprocessing and feature extraction offline, and visualizes the extracted information in a web browser-based interface. The interface allows users to explore multiple experiments in three panels corresponding to different levels of detail: summary statistics of alveolar/neutrophil behavior, characterization of alveolar dynamics including lung edema and inflammatory cells at specific time points, and cross-experiment analysis. We performed a case study on the utility of the visualization with two members or our research team and they found the tool useful because of its ability to preprocess data consistently and visualize information in a digestible and informative format. CONCLUSIONS: Application of our software tool, Alveolus Analysis, to intravital lung microscopy data has the potential to enhance the information gained from these experiments and provide new insights into the pathologic mechanisms of inflammatory lung injury.

Development of In-Browser Simulators for Medical Education: Introduction of a Novel Software Toolchain.

BACKGROUND: Simulators used in teaching are interactive applications comprising a mathematical model of the system under study and a graphical user interface (GUI) that allows the user to control the model inputs and visualize the model results in an intuitive and educational way. Well-designed simulators promote active learning, enhance problem-solving skills, and encourage collaboration and small group discussion. However, creating simulators for teaching purposes is a challenging process that requires many contributors including educators, modelers, graphic designers, and programmers. The availability of a toolchain of user-friendly software tools for building simulators can facilitate this complex task. OBJECTIVE: This paper aimed to describe an open-source software toolchain termed Bodylight.js that facilitates the creation of browser-based client-side simulators for teaching purposes, which are platform independent, do not require any installation, and can work offline. The toolchain interconnects state-of-the-art modeling tools with current Web technologies and is designed to be resilient to future changes in the software ecosystem. METHODS: We used several open-source Web technologies, namely, WebAssembly and JavaScript, combined with the power of the Modelica modeling language and deployed them on the internet with interactive animations built using Adobe Animate. RESULTS: Models are implemented in the Modelica language using either OpenModelica or Dassault Systèmes Dymola and exported to a standardized Functional Mock-up Unit (FMU) to ensure future compatibility. The C code from the FMU is further compiled to WebAssembly using Emscripten. Industry-standard Adobe Animate is used to create interactive animations. A new tool called Bodylight.js Composer was developed for the toolchain that enables one to create the final simulator by composing the GUI using animations, plots, and control elements in a drag-and-drop style and binding them to the model variables. The resulting simulators are stand-alone HyperText Markup Language files including JavaScript and WebAssembly. Several simulators for physiology education were created using the Bodylight.js toolchain and have been received with general acclaim by teachers and students alike, thus validating our approach. The Nephron, Circulation, and Pressure-Volume Loop simulators are presented in this paper. Bodylight.js is licensed under General Public License 3.0 and is free for anyone to use. CONCLUSIONS: Bodylight.js enables us to effectively develop teaching simulators. Armed with this technology, we intend to focus on the development of new simulators and interactive textbooks for medical education. Bodylight.js usage is not limited to developing simulators for medical education and can facilitate the development of simulators for teaching complex topics in a variety of different fields.

A New Integrated System for Assistance in Communicating with and Telemonitoring Severely Disabled Patients.

In this paper, we present a new complex electronic system for facilitating communication with severely disabled patients and telemonitoring their physiological parameters. The proposed assistive system includes three subsystems (Patient, Server, and Caretaker) connected to each other via the Internet. The two-way communication function is based on keywords technology using a WEB application implemented at the server level, and the application is accessed remotely from the patient's laptop/tablet PC. The patient's needs can be detected by using different switch-type sensors that are adapted to the patient's physical condition or by using eye-tracking interfaces. The telemonitoring function is based on a wearable wireless sensor network, organized around the Internet of Things concept, and the sensors acquire different physiological parameters of the patients according to their needs. The mobile Caretaker device is represented by a Smartphone, which uses an Android application for communicating with patients and performing real-time monitoring of their physiological parameters. The prototype of the proposed assistive system was tested in "Dr. C.I. Parhon" Clinical Hospital of Iasi, Romania, on hospitalized patients from the Clinic of Geriatrics and Gerontology. The system contributes to an increase in the level of care and treatment for disabled patients, and this ultimately lowers costs in the healthcare system.

Investigating the Efficacy of Web-Based Transfer Training on Independent Wheelchair Transfers Through Randomized Controlled Trials.

OBJECTIVES: To determine the efficacy of a web-based transfer training module at improving transfer technique across 3 groups: web-based training, in-person training (current standard of practice), and a waitlist control group (WLCG); and secondarily, to determine subject factors that can be used to predict improvements in transfer ability after training. DESIGN: Randomized controlled trials. SETTING: Summer and winter sporting events for disabled veterans. PARTICIPANTS: A convenience sample (N=71) of manual and power wheelchair users who could transfer independently. INTERVENTIONS: An individualized, in-person transfer training session or a web-based transfer training module. The WLCG received the web training at their follow-up visit. MAIN OUTCOME MEASURE: Transfer Assessment Instrument (TAI) part 1 score was used to assess transfers at baseline, skill acquisition immediately posttraining, and skill retention after a 1- to 2-day follow-up period. RESULTS: The in-person and web-based training groups improved their median (interquartile range) TAI scores from 7.98 (7.18-8.46) to 9.13 (8.57-9.58; P<.01), and from 7.14 (6.15-7.86) to 9.23 (8.46-9.82; P<.01), respectively, compared with the WLCG that had a median score of 7.69 for both assessments (baseline, 6.15-8.46; follow-up control, 5.83-8.46). Participants retained improvements at follow-up (P>.05). A lower initial TAI score was found to be the only significant predictor of a larger percent change in TAI score after receiving training. CONCLUSIONS: Transfer training can improve technique with changes retained within a short follow-up window, even among experienced wheelchair users. Web-based transfer training demonstrated comparable improvements to in-person training. With almost half of the United States population consulting online resources before a health care professional, web-based training may be an effective method to increase knowledge translation.

Seasonality of Ankle Swelling: Population Symptom Reporting Using Google Trends.

In our experience, complaints of ankle swelling are more common in summer, typically from patients with no obvious cardiovascular disease. Surprisingly, this observation has never been reported. To objectively establish this phenomenon, we sought evidence of seasonality in the public's Internet searches for ankle swelling. Our data, obtained from Google Trends, consisted of all related Google searches in the United States from January 4, 2004, to January 26, 2016. Consistent with our expectations and confirmed by similar data for Australia, Internet searches for information on ankle swelling are highly seasonal (highest in midsummer), with seasonality explaining 86% of search volume variability.

Evaluation Methods for Assessing Users' Psychological Experiences of Web-Based Psychosocial Interventions: A Systematic Review.

BACKGROUND: The use of Web-based interventions to deliver mental health and behavior change programs is increasingly popular. They are cost-effective, accessible, and generally effective. Often these interventions concern psychologically sensitive and challenging issues, such as depression or anxiety. The process by which a person receives and experiences therapy is important to understanding therapeutic process and outcomes. While the experience of the patient or client in traditional face-to-face therapy has been evaluated in a number of ways, there appeared to be a gap in the evaluation of patient experiences of therapeutic interventions delivered online. Evaluation of Web-based artifacts has focused either on evaluation of experience from a computer Web-design perspective through usability testing or on evaluation of treatment effectiveness. Neither of these methods focuses on the psychological experience of the person while engaged in the therapeutic process. OBJECTIVE: This study aimed to investigate what methods, if any, have been used to evaluate the in situ psychological experience of users of Web-based self-help psychosocial interventions. METHODS: A systematic literature review was undertaken of interdisciplinary databases with a focus on health and computer sciences. Studies that met a predetermined search protocol were included. RESULTS: Among 21 studies identified that examined psychological experience of the user, only 1 study collected user experience in situ. The most common method of understanding users' experience was through semistructured interviews conducted posttreatment or questionnaires administrated at the end of an intervention session. The questionnaires were usually based on standardized tools used to assess user experience with traditional face-to-face treatment. CONCLUSIONS: There is a lack of methods specified in the literature to evaluate the interface between Web-based mental health or behavior change artifacts and users. Main limitations in the research were the nascency of the topic and cross-disciplinary nature of the field. There is a need to develop and deliver methods of understanding users' psychological experiences while using an intervention.

A framework for understanding an open scientific community using automated harvesting of public artifacts.

Background: The Observational Health Data Sciences and Informatics (OHDSI) community has emerged as a leader in observational research on real-world clinical data for promoting evidence for healthcare and decision-making. The community has seen rapid growth in publications, citations, and the number of authors. Components of its successful uptake have been attributed to an open science and collaborative culture for research and development. Investigating the adoption of OHDSI as a field of study provides an opportunity to understand how communities embrace new ideas, onboard new members, and enhance their impact. Objective: To track, study, and evaluate an open scientific community's growth and impact. Method: We present a modern architecture leveraging open application programming interfaces to capture publicly available data (PubMed, YouTube, and EHDEN) on open science activities (publication, teaching, and engagement). Results: Three interactive dashboard were implemented for each publicly available artifact (PubMed, YouTube, and EHDEN). Each dashboard provides longitudinal summary analysis and has a searchable table, which differs in the available features related to each public artifact. Conclusion: We discuss the insights enabled by our approach to monitor the growth and impact of the OHDSI community by capturing artifacts of learning, teaching, and creation. We share the implications for different users based on their functional needs. As other scientific networks adopt open-source frameworks, our framework serves as a model for tracking the growth of their community, driving the perception of their development, engaging their members, and attaining higher impact.

Implementation of a web-based partnership support program for improving the quality of life of male patients undergoing infertility treatment: a pilot feasibility study.

OBJECTIVES: In this study, we aimed to implement and evaluate a Web-based partnership support program to enhance the QoL of male patients undergoing infertility treatment. We conducted a pilot study involving 41 infertile couples from September to October of 2021. We used a quasi-experimental design (pre-test and post-test with comparison) involving purposive sampling. A subgroup analysis was conducted to determine which demographics of the participants would benefit from the program. RESULTS: Thirty-four participants (mean age 37.3 years; duration of infertility treatment 14.5 months) were included in the final analysis (follow-up rate 82.9%). Although there was no significant increase in the participants' QoL under the Web-based partnership support program, the assisted reproductive technology group (P = 0.03), the no medical history group (P = 0.032), and the with experience of changing hospital group (P = 0.027) showed a significant increase in the relational subscale scores of the QoL before and after the program. The majority of the participants (n = 29; 85.3%) expressed satisfaction with the support program. Participation in the Web-based partnership support program may improve the QoL of some men undergoing infertility treatment. Trial registration Retrospectively registered at the University Hospital Medical Information Network on 26 January 2023 (ID: UMIN0000 000050153).

Effectiveness of a web-based partnership support program for preventing decline in the quality of life of male patients undergoing infertility treatment: A quasi-experimental study.

AIM: During infertility treatment, distress increases and the quality of life declines in both men and women over time. Thus, both men and women need equal support and care. In this study, we aimed to explore the effectiveness of a web-based partnership support program in preventing quality of life deterioration and reducing emotional distress in men undergoing infertility treatment. METHODS: We conducted a non-randomized controlled trial involving 151 infertile couples in Japan from January to April of 2022. The program consisted of couple discussion, information provision for couple cooperation, and communication techniques. We used a quasi-experimental design (non-equivalence two groups pre-test and post-test with comparison) involving purposive sampling. Data were collected using the FertiQoL tool and Distress scales. Analyses were conducted by a two-way factorial analysis of variance using SPSS software. RESULTS: Data for the analysis were included for the intervention group (n = 58) and the control group (n = 62) (valid response rate 79.5%). There were no significant interaction effects between program and time in the FertiQoL and Distress scales. However, there were significant interaction effects between program and time in the Relational (p < .001) and Social (p = .044) subscales. Subgroup analysis showed that in the non-assisted reproductive technologies group, deterioration in the quality of life was more effectively prevented in the intervention group than in the control group. CONCLUSIONS: The web-based partnership support program appeared to be effective in preventing the deterioration of the quality of life of only men undergoing non-assisted reproductive technology treatment.

Is Web-Based Program Effective on Self-Care Behaviors and Glycated Hemoglobin in Patients with Type 2 Diabetes: A Randomized Controlled Trial.

Background: Diabetes Self-Management Education and Support (DSMES) as a framework focuses on seven self-care behaviors. Moreover, technology-assisted self-care education is increasingly suggested for patients with Type 2 Diabetes Mellitus (T2DM). Therefore, we examined the effect of a web-based program on self-care behaviors and glycated hemoglobin values in patients with diabetes mellitus. Materials and Methods: This randomized controlled clinical trial was conducted at Alzahra Hospital in Isfahan, Iran, between April and November 2020 and included 70 patients with T2DM. Data were collected using a questionnaire that included a demographic information section and a diabetes self-management section with 21 questions on a Likert scale. Fasting blood samples (2.50 ml) were collected before and after the interventions to measure HbA1c levels. The study intervention involved a web-based program that included multimedia educational content (such as videos, lectures, educational motion graphics, text files, posters, and podcasts) presented in seven sections based on DSMES over a 21-day period with monitoring by an instructor. Results: The mean scores for healthy eating (F = 3.48, p = 0.034) and medication adherence (F = 6.70, p < 0.001) significantly increased in the interventional group, while the mean scores for being active, monitoring, reducing risks, problem-solving, and healthy coping did not significantly change. Additionally, the mean differences in HbA1c values significantly improved in the interventional group compared to the control (F = 5,1, p = 0.026). Conclusions: A web-based program in accordance with DSMES improved HbA1c levels and increased scores for healthy eating and medication adherence in patients with T2DM. However, further research with larger sample sizes and qualitative interviews is needed.

CWcollab: Presenting multimedia with web-based context-aware collaboration.

Remote collaboration tools for conferencing and presentation are gaining significant popularity during the COVID-19 pandemic period. Most prior work has drawbacks, such as a) limited support for media types, b) lack of interactivity, for example, an efficient replay mechanism, c) large bandwidth consumption for screen sharing tools. In this paper, we propose a general-purpose multimedia collaboration platform-CWcollab. It supports collaboration on general multimedia by using simple messages to represent media controls with an object-prioritized synchronization approach. Thus, CWcollab can not only support fine-grained accurate collaboration, but also rich functionalities such as replay of these collaboration events. The evaluation shows hundreds of kilobytes can be enough to store the events in a collaboration session for accurate replays, compared with hundreds of megabytes of Google Meet.

Remote Moderator and Observer Experiences and Decision-making During Usability Testing of a Web-Based Empathy Training Portal: Content Analysis.

BACKGROUND: COVID-19 restrictions severely curtailed empirical endeavors that involved in-person interaction, such as usability testing sessions for technology development. Researchers and developers found themselves using web-based moderation for usability testing. Skilled remote moderators and observers are fundamental in this approach. However, to date, more empirical work is needed that captures the perceptions and support needs of moderators and observers in testing situations. OBJECTIVE: The aim of this paper was to identify remote moderator and observer participant experiences and their use of certain tools to capture feedback of users as they interact with the web browser application. METHODS: This research is part of a broader study on an educational web browser application for nursing students to learn perspective taking and enhance their perceptual understanding of a dialogue partner's thoughts and feelings. The broader study used a quantitative and think-aloud qualitative problem-discovery usability study design. This case study explored written accounts of the remote moderator and observer participants regarding their roles, experiences, and reactions to the testing protocol and their suggestions for improved techniques and strategies for conducting remote usability testing. Content analysis was used to analyze participants' experiences in the usability testing sessions. RESULTS: We collected data from 1 remote moderator and 2 remote observers. Five themes were identified: dealing with personal stressors, dealing with user anxiety, maintaining social presence, ethical response to the study protocol, and communication during sessions. The participants offered recommendations for the design of future remote testing activities as well as evidence-informed training materials for usability project personnel. CONCLUSIONS: This study's findings contribute to a growing body of endeavors to understand human-computer interaction and its impact on remote moderator and observer roles. As technology rapidly advances, more remote usability testing will occur where the knowledge gleaned in this study can have an impact. Recommendations based on moderator and observer participant perspectives identify the need for more evidence-informed training materials for their roles that focus on web-based interpersonal communication skills, execution of user testing protocols, troubleshooting technology and test user issues, proficiency in web conferencing platforms, behavior analysis and feedback technologies, and time management.

A Reusable Multiplayer Game for Promoting Active School Transport: Development Study.

BACKGROUND: Most children and adolescents in Sweden do not meet the recommended daily physical activity levels of the World Health Organization. Active school transport (AST) and gamification are potential methods for increasing children's daily physical activity. We previously developed a game named Tic-Tac-Training for promoting active transport at workplaces; however, the game has not been applied to AST. OBJECTIVE: The objectives of this study are to investigate how Tic-Tac-Training functions to promote AST among schoolchildren in northern Sweden, improve the game to be more suitable for schoolchildren, and construct a road map for future development based on children's ideas. METHODS: First, we developed Tic-Tac-Training using the Scrum agile software development method. Second, we conducted a questionnaire-based formative evaluation of the game with schoolchildren (n=16; 9/16, 56% male; 6/16, 38% female; and 1/16, 6% other aged 11-12 years) in Luleå, Sweden. Third, we conducted focus group interviews with 33 children (13/33, 39% male and 20/33, 61% female aged 12-13 years) to gather ideas for gamifying AST. We mapped the interview results to the Octalysis gamification framework and established a road map for future development. RESULTS: The formative evaluation revealed several issues, including a lack of interesting game features, lack of support for continuous engagement, disliked competitive features, and lack of incentives for discourse and participation. New features such as rewards, collectibles, and levels were implemented based on the results. The focus group interviews revealed additional ideas for gamifying AST, such as using avatars, in-game currency and trading, and context-sensitive tasks. CONCLUSIONS: The results have several potential impacts on how reusable, gamified AST interventions can be developed and what kind of gamification elements schoolchildren in northern Sweden wish to see. These results can interest game researchers and teachers who wish to apply gamification in school contexts. Finally, we aim to continue developing the game based on the road map.

[COVID19-Tracker: a shiny app to analise data on SARS-CoV-2 epidemic in Spain]. / COVID19-Tracker: una aplicación Shiny para analizar datos de la epidemia de SARS-CoV-2 en España.

Data visualization is an important tool for exploring and communicating findings in medical research, and specially in epidemiological surveillance. The COVID19-Tracker web application systematically produces daily updated data visualization and analysis of SARS-CoV-2 epidemic in Spain. It collects automatically daily data on COVID-19 diagnosed cases and mortality, from February 24th, 2020 onwards. Three applications have already been developed: 1) to analyze data trends and estimating short-term projections; 2) to estimate the case fatality rate; and 3) to assess the effect of the lockdowns on the data trends. The application may help for a better understanding of the SARS-CoV-2 epidemic data in Spain.

Predicting tick-borne encephalitis using Google Trends.

Data generated through public Internet searching offers a promising alternative source of information for monitoring and forecasting of infectious disease. Here future cases of tick-borne encephalitis (TBE) were predicted using traditional weekly case reports, both with and without Google Trends data (GTD). Data on the weekly number of acute, confirmed TBE cases in Germany were obtained from the Robert Koch Institute. Data relating to the volume of Internet searching on TBE was downloaded from the Google Trends website. Data were split into training and validation parts. A SARIMA (0,1,1) (1,1,1) [52] model was used to describe the weekly TBE case number time series. Google Trends Data was used as an external regressor in a second, as optimal identified SARIMA (4,1,1) (1,1,1) [52] model. Predictions for the number of future cases were made with both models and compared with the validation dataset. GTD showed a significant correlation with reported weekly case numbers of TBE (p < 0.0001). A comparison of forecasted values with reported ones resulted in an RMSE (residual mean squared error) of 0.71 for the model without Google search values, and an RMSE of 0.70 for the Google Trends values enhanced model. However, difference between predictive performances was not significant (Diebold Mariano test, p-value = 0.14).

Web Browsing Habits of Healthcare Professions Students in Gross Anatomy Laboratory.

Personal computer use for educational purposes by the healthcare professions students has become ubiquitous. Although the effect of computer-based dissection instructions has been studied, there is a paucity of information regarding student browsing habits of information available on the Internet. Although current students have favorable attitudes toward accessing anatomical information online, web browsing habits have not yet been investigated specifically in the dissection laboratory setting. The purpose of this study was to describe the browsing habits of the healthcare professions students in the gross anatomy setting using a retrospective analysis. Files containing web browser history were retrieved from desktop computers in the gross anatomy laboratory and custom code was written to parse them into comma separated value files. Each web address was categorized and descriptive statistics was calculated. Browser history for 24 computers was analyzed from June 2013 to January 2015. During this period, students accumulated 100,857 webpage visits. Most often, students performed a Google search for anatomy (22.0% of all visits) and non-anatomy related (20.6% of all visits) information. Students also used the web browser to access various entertainment (16.4% of all visits) and productivity related services (15.9% of all visits). This analysis revealed a large volume of webpage visits by the healthcare professions students in the gross anatomy laboratory. A wide diversity of anatomy and non-anatomy related webpages were visited. Future analyses could be directed at examination of when in relation to class time students accessed the information, how browsing habits change over time, and what anatomical structures were most commonly searched for.

Can Google Trends data improve forecasting of Lyme disease incidence?

BACKGROUND: Online activity-based epidemiological surveillance and forecasting is getting more and more attention. To date, Google search volumes have not been assessed for forecasting of tick-borne diseases. Thus, we performed an analysis of forecasting of the Lyme disease incidence based on the traditional data extended with Google Trends. METHODS: Data on the weekly incidence of Lyme disease in Germany from 16 June 2013 to 27 May 2018 were obtained from the database of the Robert Koch Institute. Data of Internet searches were obtained from Google Trends searching "Borreliose" in Germany for the "last 5 years" as a timespan category. Data were split into the training (from 16 June 2013 to 11 June 2017) and validation (from 12 June 2017, to 27 May 2018) data sets. A seasonal autoregressive moving average model, SARIMA (0,1,1) (0,1,1) [52] model was selected to describe the time series of the weekly Lyme incidence. After this, we added the Google Trends data as an external regressor and identified the SARIMA (0,1,1) (0,1,1) [52] model as optimal. We made predictions for the validation interval using these two models and compared predictions with the values of the validation data set. RESULTS: Forecasting for the validation timespan resulted in similar values for the models. Comparing the forecasted values with the reported ones resulted in an residual mean squared error (RMSE) of 0.3763; the mean absolute percentage error (MAPE) was 8.233 for the model without Google searches with an RMSE of 0.3732; and the MAPE was 8.17495 for the Google Trends values-expanded model. The difference between the predictive performances was insignificant (Diebold-Mariano Test, p-value = 0.4152). CONCLUSION: Google Trends data are a good correlate of the reported incidence of Lyme disease in Germany, but it failed to significantly improve the forecasting accuracy in models based on traditional data.

Forensic Analysis of Tor Browser: A Case Study for Privacy and Anonymity on the Web.

Web browsers are among the most commonly used applications to access the web from any platform nowadays. With recent digital incidents involving breach of data, users are becoming more cognizant of the threat posed by malicious actors having access to personal data as well as vulnerable applications which may compromise their data. For this very reason, users are being offered privacy preserving solutions for trust maturity. The onion router (Tor) browser is one such application which not only ensures the privacy preservation goals but also provides promising anonymity. Due to this feature, majority of the users use Tor browser for normal use as well as malign activities. In order to validate the claims of Tor browser and help digital forensic investigators and researchers, we created different scenarios to forensically analyze the Tor browser privacy and anonymity. As a result of the findings, it can be concluded that the Tor browser leaves plethora of sensitive digital artifacts on host machine, which can be further used to compromise user data.

From the Wet Lab to the Web Lab: A Paradigm Shift in Brain Imaging Research.

Web technology has transformed our lives, and has led to a paradigm shift in the computational sciences. As the neuroimaging informatics research community amasses large datasets to answer complex neuroscience questions, we find that the web is the best medium to facilitate novel insights by way of improved collaboration and communication. Here, we review the landscape of web technologies used in neuroimaging research, and discuss future applications, areas for improvement, and the limitations of using web technology in research. Fully incorporating web technology in our research lifecycle requires not only technical skill, but a widespread culture change; a shift from the small, focused "wet lab" to a multidisciplinary and largely collaborative "web lab."