Modular Interface Research Articles

Augmented Reality Interface for Adverse-Visibility Conditions Validated by First Responders in Rescue Training Scenarios

Updating the equipment of the first responder (FR) by providing them with new capabilities and useful information will inevitably lead to better mission success rates and, therefore, more lives saved. This paper describes the design and implementation of a modular interface for augmented reality displays integrated into standard FR equipment that will provide support during the adverse-visibility situations that the rescuers find during their missions. This interface includes assistance based on the machine learning module denoted as Robust Vision Module, which detects relevant objects in a rescue scenario, particularly victims, using the feed from a thermal camera. This feed can be displayed directly alongside the detected objects, helping FRs to avoid missing anything during their operations. Additionally, the information exposition in the interface is organized according to the biometrical parameters of FRs during the operations. The main novelty of the project is its orientation towards useful solutions for FRs focusing on something occasionally ignored during research projects: the point of view of the final user. The functionalities have been designed after multiple iterations between researchers and FRs, involving testing and evaluation through realistic situations in training scenarios. Thanks to this feedback, the overall satisfaction according to the evaluations of 18 FRs is 3.84 out of 5 for the Robust Vision Module and 3.99 out of 5 for the complete AR interface. These functionalities and the different display modes available for the FRs to adapt to each situation are detailed in this paper.

Defining hybrid hierarchical models in πHYFLOW

Defining hybrid hierarchical models in <i>π</i>H<scp>Y</scp>F<scp>LOW</scp>

Pathway analysis for functional characterization of microRNAs

DIANA-miRPath webserver enables the exploration of combined miRNA effects using predicted or experimentally supported miRNA interactions. Its latest version (DIANA-miRPath v4.0, http://www.microrna.gr/miRPathv4 ), introduces the capacity to tailor its target-based miRNA functional analysis engine towards specific biological/experimental contexts. Via a modular interface with rich interaction, annotation and parameterization options, users can perform enrichment analysis on Gene Ontology (GO) terms, KEGG and REACTOME pathways, gene sets from Molecular Signatures Database (MSigDB) and PFAM. Included miRNA interaction sets are derived from state-of-the-art resources of experimentally supported (DIANA-TarBase v8.0, miRTarBase and microCLIP cell-type-specific interactions) or from in silico miRNA-target interactions (DIANA-microT-2023 and TargetScan predictions). Bulk and single-cell expression datasets from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression project (GTEx), as well as single-cell expression atlases can be used to assess expression change of targeted genes within terms, across a wide range of states. A discrete module to perform miRNA-tailored CRISPR knock-out screen analyses deems possible the investigation of selected miRNAs within conditions under study. Hellenic Foundation for Research and Innovation (HFRI) under the 1 st Call for HFRI Research Projects to Support Faculty Members &amp; Researchers and Procure High-Value Research Equipment grant (Project Number 2563). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Predicting the linear response of self-gravitating stellar spheres and discs with LinearResponse.jl

ABSTRACT We present LinearResponse.jl, an efficient, versatile public library written in julia to compute the linear response of self-gravitating (three-dimensional spherically symmetric) stellar spheres and (two-dimensional axisymmetric razor-thin) discs. LinearResponse.jl can scan the whole complex frequency plane, probing unstable, neutral and (weakly) damped modes. Given a potential model and a distribution function, this numerical toolbox estimates the modal frequencies as well as the shapes of individual modes. The libraries are validated against a combination of previous results for the spherical isochrone model and Mestel discs, and new simulations for the spherical Plummer model. Beyond linear response theory, the realm of applications of LinearResponse.jl also extends to the kinetic theory of self-gravitating systems through a modular interface.

Influence of protein migration on the fretting-corrosion behavior of 316 L stainless steel with artificial crevices

Fretting-crevice-corrosion at the modular interface of artificial joints can cause failure of the joint replacement. In this study, long-term fretting crevice corrosion tests of 316 L stainless steel were carried out at the center of an artificial crevice in a saline solution with and without proteins. The results showed that fretting initiated significant crevice corrosion without proteins and corrosion of large areas was observed in the non-contact area inside the crevice. In the presence of proteins, proteins can migrate into the crevice and block the crevice mouth. The enriched proteins had a lubricating effect and inhibited the occurrence of crevice corrosion.

Modular Framework for the Solution of Boundary-coupled Multiphysics Problems

This paper presents a modular multiphysics framework developed for OpenFOAM. The framework is built around an iterative implicit coupling scheme based on a multi-region partitioned approach. This scheme allows the implementation of formal implicit time-marching schemes, which improves the stability of strongly interacting coupled problems. This methodology allows physical interactions to be handled through specifically designed interface boundary conditions. It also allows region-specific solvers to be implemented as modular class solvers. The coupling methodology is handled with a main program that manages solver-specific actions. The aim of this framework is to facilitate the implementation and testing of new multiphysics coupling problems in an integrated code structure. To show the capabilities of the framework to integrate new physics, solvers and boundary conditions requirements are discussed. Also, three validated examples involving fluid-structure interactions, conjugate heat transfer, and fluid-structure-thermal interactions are presented. Although all these problems are boundary-coupled multiphysics problems, the framework is conceptually not limited to this kind of problems. The benefit of this work to the OpenFOAM community is a general and modular framework that facilitates the setup and solution of diversified multiphysics problems, and that illustrates the implementation of modular interface boundary conditions between physics regions.

Occams: A Text Summarization Package

Extractive text summarization selects asmall subset of sentences from a document, which gives good “coverage” of a document. When given a set of term weights indicating the importance of the terms, the concept of coverage may be formalized into a combinatorial optimization problem known as the budgeted maximum coverage problem. Extractive methods in this class are known to beamong the best of classic extractive summarization systems. This paper gives a synopsis of thesoftware package occams, which is a multilingual extractive single and multi-document summarization package based on an algorithm giving an optimal approximation to the budgeted maximum coverage problem. The occams package is written in Python and provides an easy-to-use modular interface, allowing it to work in conjunction with popular Python NLP packages, such as nltk, stanza or spacy.

DIANA-miRPath v4.0: expanding target-based miRNA functional analysis in cell-type and tissue contexts.

DIANA-miRPath is an online miRNA analysis platform harnessing predicted or experimentally supported miRNA interactions towards the exploration of combined miRNA effects. In its latest version (v4.0, http://www.microrna.gr/miRPathv4), DIANA-miRPath breaks new ground by introducing the capacity to tailor its target-based miRNA functional analysis engine to specific biological and/or experimental contexts. Via a redesigned modular interface with rich interaction, annotation and parameterization options, users can now perform enrichment analysis on Gene Ontology (GO) terms, KEGG and REACTOME pathways, sets from Molecular Signatures Database (MSigDB) and PFAM. Included miRNA interaction sets are derived from state-of-the-art resources of experimentally supported (DIANA-TarBase v8.0, miRTarBase and microCLIP cell-type-specific interactions) or from in silico miRNA-target interactions (updated DIANA-microT-CDS and TargetScan predictions). Bulk and single-cell expression datasets from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression project (GTEx) and adult/fetal single-cell atlases are integrated and can be used to assess the expression of enriched term components across a wide range of states. A discrete module enabling enrichment analyses using CRISPR knock-out screen datasets enables the detection of selected miRNAs with potentially crucial roles within conditions under study. Notably, the option to upload custom interaction, term, expressionand screen sets further expands the versatility of miRPath webserver.

PyComplexHeatmap: a Python package to visualize multimodal genomics data.

Python has emerged as a robust programming language increasingly employed in genomics data analysis, largely due to its comprehensive deep learning libraries and proficiency in handling large-scale data, such as single-cell multi-omics datasets. Although Python has become a prominent data science ecosystem for bioinformatics, there remains a growing demand for advanced heatmap visualization and assembly tools, which are not sufficiently addressed by existing Python-based data visualization libraries. We present PyComplexHeatmap, an all-inclusive Python library for heatmap visualization, inspired by the ComplexHeatmap package currently available in R. PyComplexHeatmap is built upon the matplotlib library and features a versatile, modular interface that seamlessly integrates with other Python-based data science tools, such as Pandas, NumPy, and genomics tools, such as Scanpy, in a standard-compliant manner. This library caters to the requirements of exquisite rendering of multimodal matrix data, incorporating both textual and graphical annotations, thereby enabling efficient integrative analysis of multimodal data and associated metadata.

Sliding Corrosion Fatigue of Metallic Joint Implants: A Comparative Study of CoCrMo and Ti6Al4V in Simulated Synovial Environments

Mechanical contact in a corrosive synovial environment leads to progressive surface damage at the modular interface of the joint implants. The wear debris and corrosion products degrade the synovial fluids and change the lubrication mechanisms at the joints. Consequently, the unstable joint lubrication and corrosion products will further induce the undesirable performance of the joint implants. In this study, the two major joint materials, CoCrMo and Ti6Al4V, were tested during the course of reciprocal sliding contact in simulated synovial liquids. Open circuit potential and coefficient of friction were monitored to describe electrochemical and mechanical responses. Potentiostatic test results illustrated electrochemical damage on both surfaces that modified oxidation chemistry on both surfaces. However, more significant modification of the CoCrMo surface was detected during wear in the simulated joint liquid. Even with a reduced coefficient of friction on the CoCrMo surface in sodium lactate environments, fretting current density drastically increased in corrosive sodium lactate with pH 2. However, the test results from the Ti6Al4V surface presented less coefficient of friction values, and moderate change in fretting current. Therefore, the experimental study concluded that the biocompatibility of Ti6Al4V is superior to that of CoCrMo in the combined effect of mechanical loadings and an electrochemical environment.

Low plasticity burnishing improves fretting fatigue resistance in bone-anchored implants for amputation prostheses

Fretting fatigue is a common problem for modular orthopedic implants which may lead to mechanical failure of the implant or inflammatory tissue responses due to excessive release of wear debris. Compressive residual stresses at the contacting surfaces may alleviate the problem. Here we investigate the potential of a surface enhancement method known as low plasticity burnishing (LPB) to increase the fretting fatigue resistance of bone-anchored implants for skeletal attachment of limb prostheses. Rotation bending fatigue tests performed on LPB treated and untreated test specimens demonstrate that the LPB treatment leads to statistically significantly increased resistance to fretting fatigue (LPB treated test specimens withstood on average 108,780 load cycles as compared with 37,845 load cycles for untreated test specimens, p = 0.004). LPB treated test specimens exhibited less wear at the modular interface as compared with untreated test specimens. This surface treatment may lead to reduced risk of fretting induced component failure and a reduced need for revision of implant system componentry.

The challenge of long-term stability for nucleic acid-based electrochemical sensors.

Nucleic acid-based electrochemical sensors are a versatile technology enabling affinity-based detection of a great variety of molecular targets, regardless of inherent electrochemical activity or enzymatic reactivity. Additionally, their modular interface and ease of fabrication enable rapid prototyping and sensor development. However, the technology has inhibiting limitations in terms of long-term stability that have precluded translation into clinically valuable platforms like continuous molecular monitors. In this opinion, we discuss published methods to address various aspects of sensor stability, including thiol-based monolayers and anti-biofouling capabilities. We hope the highlighted works will motivate the field to develop innovative strategies for extending the long-term operational life of nucleic acid-based electrochemical sensors.

Droplet Transportation through an Orifice on Electrode for Digital Microfluidics Modulations.

A digital microfluidic modular interface (chip-to-chip interface) which possesses an electrode with an orifice to vertically transport core–shell droplets is presented. The electrodes were geometrically designed to promote droplet deformation and suspension. The droplets were then applied with an electrical potential for insertion into and passage through the orifice. The concepts were tested with three types of droplets at the volume of 0.75~1.5 μL, which is usually difficult to transfer through an orifice. The integration of electrowetting on dielectric (EWOD) with paper-based microfluidics was demonstrated: the droplet could be transported within 10 s. More importantly, most of the core droplet (~97%) was extracted and passed through with only minimal shell droplets accompanying it.

PymoNNto: A Flexible Modular Toolbox for Designing Brain-Inspired Neural Networks.

The Python Modular Neural Network Toolbox (PymoNNto) provides a versatile and adaptable Python-based framework to develop and investigate brain-inspired neural networks. In contrast to other commonly used simulators such as Brian2 and NEST, PymoNNto imposes only minimal restrictions for implementation and execution. The basic structure of PymoNNto consists of one network class with several neuron- and synapse-groups. The behaviour of each group can be flexibly defined by exchangeable modules. The implementation of these modules is up to the user and only limited by Python itself. Behaviours can be implemented in Python, Numpy, Tensorflow, and other libraries to perform computations on CPUs and GPUs. PymoNNto comes with convenient high level behaviour modules, allowing differential equation-based implementations similar to Brian2, and an adaptable modular Graphical User Interface for real-time observation and modification of the simulated network and its parameters.

CORR Insights®: A Modeling Study of a Patient-specific Safe Zone for THA: Calculation, Validation, and Key Factors Based on Standing and Sitting Sagittal Pelvic Tilt.

CORR Insights®: A Modeling Study of a Patient-specific Safe Zone for THA: Calculation, Validation, and Key Factors Based on Standing and Sitting Sagittal Pelvic Tilt.

High-energy resummation in Lambda _c baryon production

We present a study on inclusive emissions of a double Lambda _c or of a Lambda _c plus a light-flavored jet system as probe channels in the semi-hard regime of QCD. Our formalism relies on the so-called hybrid high-energy/collinear factorization, where the standard collinear description is supplemented by the t-channel resummation à la BFKL of energy logarithms up to the next-to-leading accuracy. We make use of the JETHAD modular interface, suited to the analysis of different semi-hard reactions, employing the novel KKSS19 parameterization for the description of parton fragmentation into Lambda _c baryons. We provide predictions for rapidity distributions and azimuthal correlations, that can be studied at current and forthcoming LHC configurations, hunting for possible stabilizing effects of the high-energy series.

Connecting Free Improvisation Performance and Drumming Gestures Through Digital Wearables.

High-level improvising musicians master idiosyncratic gesture vocabularies that allow them to express themselves in unique ways. The full use of such vocabularies is nevertheless challenged when improvisers incorporate electronics in their performances. To control electronic sounds and effects, they typically use commercial interfaces whose physicality is likely to limit their freedom of movement. Based on Jim Black's descriptions of his ideal digital musical instrument, embodied improvisation gestures, and stage performance constraints, we develop the concept of a modular wearable MIDI interface to closely meet the needs of professional improvisers, rather than proposing a new generic instrument that would require substantial practice to adapt improvisational techniques already acquired. Our research draws upon different bodies of knowledge, from theoretical principles on collaboration and embodiment to wearable interface design, in order to create a digital vest called Track It, Zip It (TIZI) that features two innovative on-body sensors. Allowing for sound control, these sensors are seamlessly integrated with Black's improvisational gesture vocabulary. We then detail the design process of three TIZI prototypes structured by the outcomes of a performance test with Black, a public performance by a novice improviser during the 2017 International Guthman Musical Instrument Competition, and measurements of sensor responses. After commenting on the strengths and weaknesses of the final TIZI prototype, we discuss how our interdisciplinary and collective process involving a world-class improviser at the very center of the design process can provide recommendations to designers who wish to create interfaces better adapted to high-level performers. Finally, we present our goals for the future creation of a wireless version of the vest for a female body based on Diana Policarpo's artistic vision.

Research on Integrated Interface Design of Small Modular Spacecraf

Modularity in space provides a solution to the scale-constrained problem of space systems, while providing other benefits in terms of flexibility, sustainability and affordability. In the system, modules are added and removed through interconnect interfaces, which transfer mechanical load, data, electrical power, and heat from one module to another. The current research tends to integrate multiple functions into a single device or equipment to reduce costs and improve standardization. This article will explore the design requirements and constraints that need to be satisfied in the design of this standardized, extensible, multifunctional (mechanical, electrical, data, thermal), modular interface, and compare the realization of each function to provide a design consideration.

Development of a modular interface of the computer support system for aircraft design

The article summarizes the experience in the field of education of the designer’s aircraft with the support of modern information systems, programming languages, databases and knowledge. We consider the problem of interface design assistant job designer based on thesaurus of subject area. We present the existing type of the interface work of the designer and its possibilities. Further ways of development of the program, communication and interaction with the thesaurus of the subject area are considered. The conceptual description of the model of ontological support of the intelligent assistant of the robot designer is shown.

SPISEA: A Python-based Simple Stellar Population Synthesis Code for Star Clusters

Abstract We present Stellar Population Interface for Stellar Evolution and Atmospheres (SPISEA), an open-source Python package that simulates simple stellar populations. The strength of SPISEA is its modular interface which offers the user control of 13 input properties including (but not limited to) the initial mass function, stellar multiplicity, extinction law, and the metallicity-dependent stellar evolution and atmosphere model grids used. The user also has control over the initial–final mass relation in order to produce compact stellar remnants (black holes, neutron stars, and white dwarfs). We demonstrate several outputs produced by the code, including color–magnitude diagrams, HR-diagrams, luminosity functions, and mass functions. SPISEA is object-oriented and extensible, and we welcome contributions from the community. The code and documentation are available on GitHub (https://github.com/astropy/SPISEA) and ReadtheDocs (https://spisea.readthedocs.io/en/latest/), respectively.