Traffic Simulation with Open-Source and Commercial Traffic Microsimulators: A Case Study

The analysis of traffic problems in large urban centers often requires the use of computational tools, which give the possibility to make a more detailed analysis of the issue, suggest solutions, predict behaviors and, above all, support efficient decision-making. Transport microsimulation software programs are a handy set of tools for this type of analysis. This research paper shows a case study where functions and limitations of Aimsun version 8.2.0, a commercial-like European software and Sumo version 1.3.1, a European open-source software, are presented. The input and output data are similar in both software and the interpretation of results is quite intuitive for both, as well. However, Aimsun's graphical interface interprets results more user-friendly, because Sumo is an open-access software presented as an effective alternative tool for transport modeling.

GeCoAgent: A Conversational Agent for Empowering Genomic Data Extraction and Analysis

With the availability of reliable and low-cost DNA sequencing, human genomics is relevant to a growing number of end-users, including biologists and clinicians. Typical interactions require applying comparative data analysis to huge repositories of genomic information for building new knowledge, taking advantage of the latest findings in applied genomics for healthcare. Powerful technology for data extraction and analysis is available, but broad use of the technology is hampered by the complexity of accessing such methods and tools. This work presents GeCoAgent, a big-data service for clinicians and biologists. GeCoAgent uses a dialogic interface, animated by a chatbot, for supporting the end-users’ interaction with computational tools accompanied by multi-modal support. While the dialogue progresses, the user is accompanied in extracting the relevant data from repositories and then performing data analysis, which often requires the use of statistical methods or machine learning. Results are returned using simple representations (spreadsheets and graphics), while at the end of a session the dialogue is summarized in textual format. The innovation presented in this article is concerned with not only the delivery of a new tool but also our novel approach to conversational technologies, potentially extensible to other healthcare domains or to general data science.

Status and Challenges in Homogenization Methods for Lattice Materials

Lattice structures have shown great potential in that mechanical properties are customizable without changing the material itself. Lattice materials could be light and highly stiff as well. With this flexibility of designing structures without raw material processing, lattice structures have been widely used in various applications such as smart and functional structures in aerospace and computational mechanics. Conventional methodologies for understanding behaviors of lattice materials take numerical approaches such as FEA (finite element analysis) and high-fidelity computational tools including ANSYS and ABAQUS. However, they demand a high computational load in each geometry run. Among many other methodologies, homogenization is another numerical approach but that enables to model behaviors of bulk lattice materials by analyzing either a small portion of them using numerical regression for rapid processing. In this paper, we provide a comprehensive survey of representative homogenization methodologies and their status and challenges in lattice materials with their fundamentals.

Immunoprofiling Identifies Functional B and T Cell Subsets Induced by an Attenuated Whole Parasite Malaria Vaccine as Correlates of Sterile Immunity

Immune correlates of protection remain elusive for most vaccines. An identified immune correlate would accelerate the down-selection of vaccine formulations by reducing the need for human pathogen challenge studies that are currently required to determine vaccine efficacy. Immunization via mosquito-delivered, radiation-attenuated P. falciparum sporozoites (IMRAS) is a well-established model for efficacious malaria vaccines, inducing greater than 90% sterile immunity. The current immunoprofiling study utilized samples from a clinical trial in which vaccine dosing was adjusted to achieve only 50% protection, thus enabling a comparison between protective and non-protective immune signatures. In-depth immunoprofiling was conducted by assessing a wide range of antigen-specific serological and cellular parameters and applying our newly developed computational tools, including machine learning. The computational component of the study pinpointed previously un-identified cellular T cell subsets (namely, TNFα-secreting CD8+CXCR3−CCR6− T cells, IFNγ-secreting CD8+CCR6+ T cells and TNFα/FNγ-secreting CD4+CXCR3−CCR6− T cells) and B cell subsets (i.e., CD19+CD24hiCD38hiCD69+ transitional B cells) as important factors predictive of protection (92% accuracy). Our study emphasizes the need for in-depth immunoprofiling and subsequent data integration with computational tools to identify immune correlates of protection. The described process of computational data analysis is applicable to other disease and vaccine models.

Methodology of Teaching Methods of FEM Analysis Using Software ANSYS

This paper presents the authors' experience of teaching the finite element method (FEM) at university. With the development of computational tools in the second half of the twentieth century, there was also the development of computational methods focused on the algorithmization of engineering tasks based on FEM. From the solution of individual problems of the state of stress and deformation from the influence of the external environment, a complex solution of the mutual interaction of the system of deformable bodies (elements) has been performed while improving the physical and geometric characteristics of modern materials and structures. Many processes in the automatic design system take place as if in a "black box" and the process of verifying the achieved results becomes the most important stage in the design activity. Without knowledge of the theoretical basis of FEM, physical and mathematical modeling, verification procedures and methods, the design of a structure cannot be safe and reliable. In this paper we present one of the possibilities how the student can get acquainted with the theoretical foundations of FEM and with computational procedures using ANSYS software.

The Neuroscience Experiments System (NES)–A Software Tool to Manage Experimental Data and Its Provenance

Computational tools can transform the manner by which neuroscientists perform their experiments. More than helping researchers to manage the complexity of experimental data, these tools can increase the value of experiments by enabling reproducibility and supporting the sharing and reuse of data. Despite the remarkable advances made in the Neuroinformatics field in recent years, there is still a lack of open-source computational tools to cope with the heterogeneity and volume of neuroscientific data and the related metadata that needs to be collected during an experiment and stored for posterior analysis. In this work, we present the Neuroscience Experiments System (NES), a free software to assist researchers in data collecting routines of clinical, electrophysiological, and behavioral experiments. NES enables researchers to efficiently perform the management of their experimental data in a secure and user-friendly environment, providing a unified repository for the experimental data of an entire research group. Furthermore, its modular software architecture is aligned with several initiatives of the neuroscience community and promotes standardized data formats for experiments and analysis reporting.