BatchBMD as an Efficient and Accurate Dual-Energy X-ray Absorptiometry Report Generator

Dual-energy X-ray absorptiometry is the gold standard for evaluating Bone Mineral Density (BMD); however, a typical BMD report is generated in a time-inefficient manner and is prone to error. We developed a rule-based automated reporting system, BatchBMD, that accelerates DXA reporting while improving its accuracy over current systems. BatchBMD generates a structured report, customized to the specific clinical purpose. To compare BatchBMD to a Web-based Reporting (WBR) system for efficiency and accuracy, 500 examinations were randomly chosen from those performed at the Taipei Municipal Wanfang Hospital from January to March 2021. The final assessment included all 2326 examinations conducted from September 2020 to March 2021. The average reporting times were 6.7 and 10.8 minutes for BatchBMD and the WBR system, respectively, while accuracy was 99.4% and 98.2%, respectively. Most of the errors made by BatchBMD were digit errors in the appendicular skeletal muscle index. After correcting this, 100% accuracy across all 2326 examinations was validated. This automated and accurate BMD reporting system significantly reduces report production workload for radiologists and technicians while increasing productivity and quality. Additionally, the portable software, which employs a simple framework, can reduce deployment costs in clinical practice.

MICROCONTROLLER SYSTEM FOR MONITORING THE HUMAN PHYSIOLOGICAL STATE

The paper presents a study of a device for measuring physiological human parameters by photometry. The purpose of this paper is to design a portable software and hardware complex for monitoring the human physiological condition based on the integrated heart rate sensor and microcontroller. In a process of the mathematical modeling of pulse signals, spectral analysis and filtering of the photoplethysmogram signal model with an additional pulse wave signal have been performed, which made it possible to determine both the range of values of pulse signal parameters and peak pulse signal detector parameters, that, in turn, provides avoiding calculation errors. Based on the obtained results of mathematical modeling, the computational algorithms of the physiological monitoring system have been optimized that have been implemented on the basis of a modern energy efficient and inexpensive microcontroller STM32F103C8. The development of a prototype system for the study of physiological parameters has been performed using a bread-board that allows fast testing and provides the ability to quickly replace/add the necessary components of the system. The implemented monitoring system has an additional function of connection to a PC on which it is possible to display data from the pulse oximeter in terminal mode, as well as further process them in the MATLAB environment for a detailed study of the human physiological condition. Thus, the need to create a portable software and hardware complex for monitoring the human condition, based on an integrated heart rate sensor and microcontroller, is relevant, and the designed system can be used in everyday conditions to monitor human physiological parameters such as heart rate, oxygen saturation and temperature.

Exascale models of stellar explosions: Quintessential multi-physics simulation

The ExaStar project aims to deliver an efficient, versatile, and portable software ecosystem for multi-physics astrophysics simulations run on exascale machines. The code suite is a component-based multi-physics toolkit, built on the capabilities of current simulation codes (in particular Flash-X and Castro), and based on the massively parallel adaptive mesh refinement framework AMReX. It includes modules for hydrodynamics, advanced radiation transport, thermonuclear kinetics, and nuclear microphysics. The code will reach exascale efficiency by building upon current multi- and many-core packages integrated into an orchestration system that uses a combination of configuration tools, code translators, and a domain-specific asynchronous runtime to manage performance across a range of platform architectures. The target science includes multi-physics simulations of astrophysical explosions (such as supernovae and neutron star mergers) to understand the cosmic origin of the elements and the fundamental physics of matter and neutrinos under extreme conditions.

A Wireless Hand Grip Device for Motion and Force Analysis

A prototype portable device that allows for simultaneous hand and fingers motion and precise force measurements has been. Wireless microelectromechanical systems based on inertial and force sensors are suitable for tracking bodily measurements. In particular, they can be used for hand interaction with computer applications. Our interest is to design a multimodal wireless hand grip device that measures and evaluates this activity for ludic or medical rehabilitation purposes. The accuracy and reliability of the proposed device has been evaluated against two different commercial dynamometers (Takei model 5101 TKK, Constant 14192-709E). We introduce a testing application to provide visual feedback of all device signals. The combination of interaction forces and movements makes it possible to simulate the dynamic characteristics of the handling of a virtual object by fingers and palm in rehabilitation applications or some serious games. The combination of these above mentioned technologies and open and portable software are very useful in the design of applications for assistance and rehabilitation purposes that is the main objective of the device.

HeteroGGM: an R package for Gaussian graphical model-based heterogeneity analysis

Summary Heterogeneity is a hallmark of many complex human diseases, and unsupervised heterogeneity analysis has been extensively conducted using high-throughput molecular measurements and histopathological imaging features. ‘Classic’ heterogeneity analysis has been based on simple statistics such as mean, variance and correlation. Network-based analysis takes interconnections as well as individual variable properties into consideration and can be more informative. Several Gaussian graphical model (GGM)-based heterogeneity analysis techniques have been developed, but friendly and portable software is still lacking. To facilitate more extensive usage, we develop the R package HeteroGGM, which conducts GGM-based heterogeneity analysis using the advanced penaliztaion techniques, can provide informative summary and graphical presentation, and is efficient and friendly. Availabilityand implementation The package is available at https://CRAN.R-project.org/package=HeteroGGM. Supplementary information Supplementary data are available at Bioinformatics online.

First experiences with a portable analysis infrastructure for LHC at INFN

The challenges proposed by the HL-LHC era are not limited to the sheer amount of data to be processed: the capability of optimizing the analyser's experience will also bring important benefits for the LHC communities, in terms of total resource needs, user satisfaction and in the reduction of end time to publication. At the Italian National Institute for Nuclear Physics (INFN) a portable software stack for analysis has been proposed, based on cloud-native tools and capable of providing users with a fully integrated analysis environment for the CMS experiment. The main characterizing traits of the solution consist in the user-driven design and the portability to any cloud resource provider. All this is made possible via an evolution towards a “python-based” framework, that enables the usage of a set of open-source technologies largely adopted in both cloud-native and data-science environments. In addition, a “single sign on”-like experience is available thanks to the standards-based integration of INDIGO-IAM with all the tools. The integration of compute resources is done through the customization of a JupyterHUB solution, able to spawn identity-aware user instances ready to access data with no further setup actions. The integration with GPU resources is also available, designed to sustain more and more widespread ML based workflow. Seamless connections between the user UI and batch/big data processing framework (Spark, HTCondor) are possible. Eventually, the experiment data access latency is reduced thanks to the integrated deployment of a scalable set of caches, as developed in the context of ESCAPE project, and as such compatible with the future scenarios where a data-lake will be available for the research community. The outcome of the evaluation of such a solution in action is presented, showing how a real CMS analysis workflow can make use of the infrastructure to achieve its results.

STUDY THE ALGORITHM OF PATHS CALCULATION PARALLELIZATION IN THE PROBLEM OF GROUP CONTROL OF ROBOTS

The work is about development and study of the implementation of a multithreaded flow manager in computing systems for the transport problem of controlling a heterogeneous group of robots. The aim of the work is to study the parameters of the thread manager in order to find a suboptimal configuration for solving the task of managing compu-tation resources and formulating practical recommendations for configuration the developed software as well. In the work, a series of experiments were carried out on the thread manager, experimental dependences of the computing system performance on the manager's configuration parameters were established. In the course of the experiments was established that it is possible to find the suboptimal configuration of the thread manager on the basis of the pa-rameters, such as: the number of logical threads, the size of the batch of subtasks for computation, the number of the subtasks. The results will be used in when the creating of a subsystem for managing computational threads of the general problem, and can be used in other applied problems together with a portable software in the software of the routes computation threads manager.

An Embedded, Low-Power, Wireless NO2 Gas-Sensing Platform Based on a Single-Walled Carbon Nanotube Transducer

This work proposes a portable, software-defined NO2-sensing platform, which is able to acquire currents ranging from nA to µA from a Single-Walled Carbon Nanotube (SWCNT) gas sensor. It includes an embedded software that steers the system allowing dynamical adjustments of the SWCNT bias levels, measurement range, sampling rate and of measurement time intervals. Further, the embedded functions can post-process the measurement results, log data on an SD card or send data via a wireless connection.