Insights from the IronTract challenge: optimal methods for mapping brain pathways from multi-shell diffusion MRI

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset. Macaque brains that have received both tracer injections and ex vivo dMRI at high spatial and angular resolution allow a comprehensive, quantitative assessment of tractography accuracy on state-of-the-art dMRI acquisition schemes. We find that, when analysis methods are carefully optimized, the HCP scheme can achieve similar accuracy as a more time-consuming, Cartesian-grid scheme. Importantly, we show that simple pre- and post-processing strategies can improve the accuracy and robustness of many tractography methods. Finally, we find that fiber configurations that go beyond crossing (e.g., fanning, branching) are the most challenging for tractography. The IronTract Challenge remains open and we hope that it can serve as a valuable validation tool for both users and developers of dMRI analysis methods.

Considering Eye-tracking as a Validation Tool in Cinema Research

The use of eye-tracking in data collection, when accompanied by the proper research questions and methodology, is a powerful tool that may provide invaluable insights into the way viewers perceive and experience movies. Film theory can use eye-tracking to test and verify research hypotheses not only with unprecedented accuracy, but also with the ability to address a significant variety of theoretical questions. Eye-tracking can help build contemporary film theory by supporting its various fields of research, and also even assist the production of films themselves by helping filmmakers make more informed creative decisions. The present article is an overview of eye-tracking and its gradual implementation in cinema research; in the context of discussing some recent examples of academic work based on eye-tracking, it considers the technology of eye-trackers and the way in which human vision handles visual information on screen. By testing the attentional behaviour of viewers, eye-tracking can produce more solid answers to questions regarding the way films are experienced; therefore, it may very well prove to be the spearhead of a more robust body of film theory in the near future.

TT-Mars: Structural Variants Assessment Based on Haplotype-resolved Assemblies

Variant benchmarking is a critical component of method development and evaluating the accuracy of studies of genetic variation. Currently, the best approach to evaluate the accuracy of a callset is the comparison against a well curated gold standard. In repetitive regions of the genome it may be difficult to establish what is the truth for a call, for example when different alignment scoring metrics provide equally supported but different variant calls in on the same data. Here we provide an alternative approach, TT-Mars, that takes advantage of the recent production of high-quality haplotype-resolved genome assemblies by evaluating variant calls based on how well their call reflects the content of the assembly, rather than comparing calls themselves. We used TT-Mars to assess callsets from different SV discovery methods on multiple human genome samples and demonstrated that it is capable at accurately classifying true positive and false positive SVs. On the HG002 personal genome, TT-Mars recapitulates 96.0%-99.6% of the validations made using the Genome in a Bottle gold standard callset evaluated by truvari, and evaluates an additional 121-10,966 variants across different callsets. Furthermore, with a group of high-quality assemblies, TT-Mars can evaluate performance of SV calling algorithms as a distribution rather than a point estimate. We also compare TT-Mars against the long-read based validation tool, VaPoR, and when assembly-based variant calls produced by dipcall are used as a gold standard. Compared with VaPoR, TT-Mars analyzes more calls on a long read callset by assessing more short variant calls (< 100 bases), while requiring smaller input. Compared with validation using dipcall variants, TT-Mars analyzes 1,497-2,229 more calls on long read callsets and has favorable results when candidate calls are fragmented into multiple calls in alignments. TT-Mars is available at https://github.com/ChaissonLab/TT-Mars.git with accompanying assembly data and corresponding liftover files.

Flick Flack Training Tool for Beginner Athletes PERSANI Medan

Gymnastics is a body exercise on the floor or on a device designed to increase endurance, strength, flexibility, agility, coordination and self-control. One of them is floor exercise, this exercise also has various kinds of movements that are not easy to do, for example, the movement flick flack. Beginner athletes in PERSANI, Medan City have not mastered the movement properly flick flack due to limited tools and costs from PERSANI so that the coach has to innovate with existing tools. The population in this study were 9 Siahaanathletes Gymnastic Club, 5 Windy's Gymnastic Clubathletes, 2athletesathlete Star Kids Gymnastic Club and 1 QA Gymnastic Club in 2020. The Training tool was flick flack validated first by 9 experts, 3 experts in in sports, 3 experts in the field of equipment / media, 3 experts in the field of coaches, where the average percentage value of validity is 81.8%, thus according to the experts they get the "Good / Feasible" category. The method used is the method of development research (Research and Development / R & D). The results of the small group trial involved 14 athletes, 9 Siahaanathletes Gymnastic Club and 5athletes Wendy's Gymnastic Club that the development of the training tool flick flack in this study can be concluded that it meets the criteria to be continued in large group trials. The results of the large group trial involved 17 athletes, 9 Siahaan Gymnastic Clubathletes, 5 Windy's Gymnastic Club, 2 athletes. Star Kids Gymnastic Club and 1athlete QA Gymnastic Club concluded that they met the criteria to be used in helping training flick flack. From the results of the validation tool, test a small group and large group trial can be concluded that the tools exercise flick flack is needed in practice flick.

A Comparison between Agent-Based and GIS-Based Tsunami Evacuation Simulations: A Case Study for Tofino, BC

Soft measures such as evacuation planning are recommended to mitigate the loss of life during tsunamis. Two types of evacuation models are widely used: (1) Agent-based modelling (ABM) defines sets of rules that individual agents in a simulation follow during a simulated evacuation. (2) Geographical information systems (GIS) are more accessible to city planners, but cannot incorporate the dynamic behaviours found in ABMs. The two evacuation modelling methodologies were compared through a case study by assessing the state of evacuation preparedness and investigating potential mitigation options. The two models showed different magnitudes for mortality rates and facility demand but had similar trends. Both models agreed on the best solution to reduce the loss of life for the community. GIS may serve as a useful tool for initial investigation or as a validation tool for ABMs. ABMs are recommended for use when modelling evacuation until GIS methodologies are further developed.

Attitudes to fake news verification: Youth orientations to ‘right click’ authenticate

This article examines the phenomenon of fake news through a survey of university students in the United Kingdom. The survey, composed through a selection of factual and non-factual content/news and complemented through a validation tool, sought to assess the attitudes of these respondents to items of factual misinformation before and after these were verified with the tool. The findings from the survey present online misinformation as a very complex and unfolding phenomenon in terms of user behaviour, particularly when presented with an authentication tool. The majority of respondents failed in identifying factual from fake news posts. While respondents indicated mistrust in using third-party validation tools, the majority indicated a critical need for a verification tool that would support their quest and increase their trust in what they read online.

Alpha-XIC: a deep neural network for scoring the coelution of peak groups improves peptide identification by data-independent acquisition mass spectrometry

ABSTRACTMotivationThe peptide-centric identification methodologies of data-independent acquisition (DIA) data mainly rely on scores for the mass spectrometric signals of targeted peptides. Among these scores, the coelution scores of peak groups constructed by the chromatograms of peptide fragment ions have a significant influence on the identification. Most of the existing coelution scores are achieved by artificially designing some functions in terms of the shape similarity, retention time shift of peak groups. However, these scores cannot characterize the coelution robustly when the peak group is in the circumstance of interference.ResultsOn the basis that the neural network is more powerful to learn the implicit features of data robustly from a large number of samples, and thus minimizing the influence of data noise, in this work, we propose Alpha-XIC, a neural network-based model to score the coelution. By learning the characteristics of the coelution of peak groups derived from identified peptides, Alpha-XIC is capable of reporting robust coelution scores even for peak groups with interference. With this score appending to initial scores generated by the accompanying identification engine, the ensuing statistical validation tool can update the identification result and recover the misidentified peptides. In our evaluation of the HeLa dataset with gradient lengths ranging from 0.5h to 2h, Alpha-XIC delivered 16.7% ~ 49.1% improvements in the number of identified precursors at 1% FDR. Furthermore, Alpha-XIC was tested on LFQbench, a mixed-species dataset with known ratios, and increased the number of peptides and proteins fell within valid ratios by up to 16.6% and 13.8%, respectively, compared to the initial identification.Availability and ImplementationSource code are available at www.github.com/YuAirLab/Alpha-XIC.