Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling and Analyzing Information Flow in Development Teams as a Pipe System

Teamwork is essential for developing valuable software. Working in a team requires an appropriate information exchange among team members in order to avoid loss of information. In order to analyze and improve information flows, it is recommended to observe the information exchange in a team. We propose an approach for modeling the information flow of teams as a pipe system. Different pipe diameters represent the amount of information passing through the pipe. In order to show the applicability of our approach, we conducted a case study in a globally distributed software engineering company. The study consists of the elicitation of information flows inside the company and the automated analysis by our approach. We are able to visualize the information flows, find critical paths such as bottlenecks, and improve information flow structures. This enables project leaders to customize the communication structure to the needs of their team and to prevent loss of information.
PET-driven respiratory phase tracking and self-gating of PET data: clinical demonstration of enhanced lesion detectability in cardiovascular PET/MRI

The advent of cardiovascular PET/MR in clinic may offer superior motion compensation capabilities by exploiting the non-ionizing nature of MR to sufficiently track and model respiratory and cardiac motion at high spatial resolution. However, the estimated motion models need to be continuously driven by the respiratory and cardiac motion phase for the accurate motion correction of the PET and MR data, thereby demonstrating the need for constant cardio-respiratory phase tracking throughout the entire scan period. Although MR-based continuous monitoring of cardio-respiratory phase is possible, it could reserve valuable time from other diagnostic MR sequences, thus diminishing PET/MR clinical potential. In this study, we validate a readily applicable in clinic PET list-mode (LM) datadriven respiratory phase extraction method to enable robust respiratory self-gating of PET data. The method relies on the hypothesis that for certain tracers the total LM PET counts can be sensitive to the periodic movement of hot or cold activity regions in and out of the PET field of view during breathing. The respiratory phase is tracked by continuously monitoring the total LM counts temporal profile, after smoothing with moving average filters (MAFs) to automatically correct for deep breath hold and drifting patterns. Subsequently the phase is used to drive the self-gating of the PET data into five respiratory gates and a special breath-hold gate. The period of the respiratory phase extracted with our proposed method matched well with the expected period of normal human breathing. Moreover, the automatically identified irregular LM PET count patterns corresponded in time to breath-hold MR acquisitions. The clinical application of the proposed method on our cardiovascular PET/MR studies demonstrated feasibility, while quantitative assessment of 18F-NaF coronary lesions detectability suggested a 10% improvement in lesion contrast and contrast-tonoise scores for the self-gated PET images.
Contraction-Based Identification of a Neuron Model with Nonlinear Parameterization via Synchronization

In this work, a scheme for the identification of a nonlinearly parameterized neural system described by the Hindmarsh-Rose model, using synchronization and contraction for stability, is proposed. The given algorithm is based on the construction of an adaptive law which helps to render contractive, in a generalized sense, certain virtual system. This virtual dynamics is obtained as an abstract model for which the ideal identification goals and the identification error of the system under study are particular solutions. Contraction ensures that ideal and real trajectories tend to each other whenever they are initialized within the contraction region.The algorithm was successfully applied to identify the scalar nonlinear parameter of the Hindmarsh-Rose model and numerical results are shown in order to demonstrate the effectiveness of the method.
Investigation on Performance of Large Area Low Loss Fiber in High Capacity Multichannel Systems

In this paper, performance comparision between standard single mode fiber (SMF) and large area low loss fiber (LA-LLF) is done which reveals the advantages of using LA-LLF in closely spaced, nonlinearitv prone high power DWDM systems. The effects of high launched power, number of channels, channel spacing and transmission distance on the quality of transmission Q factor are investigated through numerical simulations. In single channel 128 Gbps PM-QPSK system, LA-LLF shows about 1.5 dB more tolerance than SMF while operating with high powers. In the nyquist rate spaced multichannel system, LA-LLF shows about 2 dB superior performance over SMF when maximum number of channels are transmitted and 0.8 dB better performance when transmission distances are varied.
Six-minute walk test and incremental shuttle walk test in the evaluation of functional capacity in Chagas heart disease

Chagas heart disease (CHD) leads to a progressive functional impairment. Field tests, as the 6-min walk test (6MWT) and the incremental shuttle walk test (ISWT), may be inexpensive approaches in the evaluation of functional capacity of these patients. The present study was addressed to compare the 6MWT and the ISWT measures, and to determine the accuracy of these tests in the identification of functional impairment in patients with CHD. Thirty-five patients with CHD (47.1±8.2 years, NYHA I–III) were evaluated by echocardiography, cardiopulmonary exercise test (CPET), 6MWT, and ISWT. Correlations between the CPET (peak oxygen uptake [peak VO2] and the ratio between ventilation and the carbon dioxide production [VE/VCO2 slope]) and the field tests (walking distances) were also performed. The receiver operating characteristic (ROC) curve was selected to identify the best distances related to identify those patients with functional impairment. There was no difference between distances walked during the 6MWT and ISWT (P=0.694). The Bland-Altman analysis showed good agreement between the field tests. Both 6MWT and ISWT correlated with peak VO2 (r=0.577, P<0.001 and r=0.587, P<0.001, respectively) and ISWT correlated with VE/VCO2 slope (r=−0.339, P=0.003). The cutoff distances of 6MWT and ISWT to identify patients with peak VO2 less than 20 mL/kg/min were 520 m and 400 m, respectively, with no difference between the areas under ROC curves (P=0.276). Both the 6MWT and the ISWT demonstrated accuracy in identify functional impairment in patients with CHD, being useful tools for the risk stratification of these patients.
Beyond concept analysis: Uses of mind mapping software for visual representation, management, and analysis of diverse digital data

Mind mapping is a visual-spatial method of representing information using nodes (information segments) to show ideas and connecting lines to define relationships between content. As a critical thinking tool, it is applicable to a range of research activities, including information management, project development, and data analysis. The purposes of this manuscript are to describe the use of mapping for qualitative data analysis, provide step-by-step instructions of how to construct mind maps, and present examples specific to qualitative data analysis. An example from a recent study of patient and provider perceptions of virtual visits demonstrates the use of Xmind in conjunction with Atlas.ti for qualitative content analysis of open-ended survey data. While coding in Atlas.ti, we used Xmind to develop dynamic memos, code networks, and themes. The memo map served to identify common coding patterns and informed subsequent coding stages. After coding in Atlas.ti, the entire code list was imported into a new map in Xmind and iteratively organized to identify conceptual groupings, similarities/differences, and key ideas. Themes were identified through pattern coding and refining code networks within the Xmind map. Map iterations formed part of the analytic trail and facilitated peer-to-peer discussions. The final map served as the model for publication. The use of mind mapping enhanced the rigor, credibility, and transparency of analyses and facilitated peer-to-peer communication. This technique can be used to manage diverse content (documents, audio/video file, image, web links, and personal notes) and thus has great potential to contribute to a variety of data management tasks.
A Compact Design of Reconfigurable Dual Band-Notched UWB Antenna

This paper presents a compact design of UWB antenna with reconfigurable dual notch bands is proposed. The UWB antenna with a notch filter consists of a circular antenna and two-pairs of L-shaped resonators. To realize the notch characteristics in WLAN at 5.2 GHz and 5.8 GHz bands, a half wavelength of L-resonator is introduced in the radiating patch. A small T-shaped notch is etched in the partial ground plane to enhance the UWB bandwidth up to 7.513 GHz, which covers the frequency range from 3.048 - 10.561 GHz. An experimental proposed structure shows a good agreement with the simulated results. Furthermore, the proposed UWB antenna with notch filter has a compact size of $\mathbf{37.6, x, 28, mm}^{\mathbf{2}}$. This proposed design can give an alternative solution for eliminating WLAN interferes in the UWB bands by designing the notch filter with a good tuning capability.
Sliding mode three-dimension SLAM with application to quadrotor helicopter

Unmanned Aerial Vehicles (UAV) systems have increased their applications, however, in different environments, it is not possible to obtain the location with devices such as the Global Positioning System (GPS). Also, in exploration applications, it is required to build maps with these systems. In this paper, the navigation of a quadcopter is carried out where an algorithm is proposed to solve the Simultaneous Localization And Mapping (SLAM) problem. Therefore, the Extended Kalman Filter (EKF) is one of the most used techniques to perform SLAM in different robots. However, one of the restrictions of the EKF asks that the uncertainties must be of the Gaussian type wirh zero-mean. For this reason, we propose the SM-SLAM algorithm to relax this restriction, in such a way, the algorithm is robust against bounded perturbations. The results obtained from the proposed algorithm are compared with the EKF-SLAM.
Fault Identification Based on PD Ultrasonic Signal Using RNN, DNN and CNN

Traditional fault identification algorithms have low recognition accuracy in practical engineering applications. In this paper, new fault identification methods are proposed and proved to be more excellent. The new methods are based on: 1) Downsample the partial discharge (PD) ultrasonic signal to obtain sound signal that human can hear; 2) Extract features from sound data based on methods including Mel Frequencies Cepstral Coefficient (MFCC) to extract expanding signal characteristics; 3) Use Recurrent Neural Network (RNN), Deep Neural Network (DNN) and Convolutional Neural Network (CNN) classifiers on each feature extraction method and compare the effects and performances.
Orbital Navigation Using Resident Space Object Observations

With the population of Resident Space Objects (RSOs) in low earth orbit growing steadily year by year, there is an increasing challenge to track and map this population. While dedicated space and ground-based RSO detectors have done well, there has been an increasing amount of space-based detectors that assist in maintaining the RSO catalog. With continual RSO knowledge improvements, it may be possible to one day use RSO observations as a means of space-based navigation. This paper explores how this RSO information could one day be used in the attitude and orbit determination of the satellite. By leveraging the measurement parallax of nearby RSOs on the star tracker detector, the star tracker can be used to provide both orbit and attitude information to the navigation filter on-board the spacecraft, providing a useful backup to a standard GPS receiver. This paper presents preliminary work on a combined orbit / attitude Kalman filter that includes RSO observations from standard star trackers.
Teaching intersectionality: Pedagogical approaches for lasting impact

Recently there have been calls to study and apply critical theory and tools around social justice, and intersectional approaches of race, anti-racism, gender, sexuality, disability and accessibility, and class in Library and Information Studies (LIS). But applying lasting techniques in the LIS classroom require pedagogies that are intersectional, assessable, and apply lasting change for the student. This article argues for impactful approaches to intersectionality- the inclusion of multiple identities and subjectivities such as race, gender, sexuality, and class- to LIS in three parts: (1) Teaching critical theories alongside traditional LIS texts, (2) using systems of assessment for cultural competencies and analysis, and (3) classroom activities that implement metacognitive change. These approaches in the LIS classroom can demonstrably move LIS students into a deeper critical analysis of power in libraries that will be applied throughout their careers.
Multi-Task Learning in Deep Neural Network for Sentiment Polarity and Irony classification

We study the impact of a new multi-task learning approach in deep neural network for polarity and irony detection in Italian Twitter posts. We compare this approach with traditional single-task learning models. The different behavior of the two approaches shows the effectiveness of the proposed method that is able to combine the information from the two tasks improving the accuracy in both tasks. This is particularly true on edge cases in which knowledge about the two tasks is needed to classify a tweet, this is the case, for example, when the literal polarity of a tweet is inverted by irony.
Populations of the Beet Cyst Nematode Heterodera schachtii Exhibit Strong Differences in Their Life-History Traits Across Changing Thermal Conditions

It is widely accepted that climate has an essential influence on the distribution of species and that temperature is the major abiotic factor that affects their life-history traits. Species with very restricted active dispersal abilities and a wide geographical distribution are thus expected to encompass distinct populations adapted to contrasted local conditions. The beet cyst nematode Heterodera schachtii is a good biological model to study temperature adaptation in populations collected from different environments. Here, we tested the effect of temperature on H. schachtii life-history traits using seven field populations from Morocco, Spain, France, Germany, Austria, Poland and Ukraine. We tested hatching and multiplication rates of each population at different temperatures, as well as hatching rates of each population after storage at different temperatures – simulating survival conditions during the inter-cropping period. Results showed a strong temperature effect on the life-history traits explored. Temperature impact on hatching (at different temperatures and after storage at different temperatures) depended on the origin of populations, separating southern from northern ones. Surprisingly, low temperatures influenced hatching less in southern populations. However, for these populations, a storage period at low temperatures strongly reduce subsequent hatching. Conversely, nematode multiplication was not differentially affected by temperatures, as favorable conditions for the host are also favorable for the parasite. Finally, a significant correlation between the genetic diversity and the level of specialization showed that the less diverse populations were more specialized than the more diverse ones.
Internet of Medical Things: A Review of Recent Contributions Dealing With Cyber-Physical Systems in Medicine

The Internet of Medical Things (IoMT) designates the interconnection of communication-enabled medical-grade devices and their integration to wider-scale health networks in order to improve patients’ health. However, because of the critical nature of health-related systems, the IoMT still faces numerous challenges, more particularly in terms of reliability, safety, and security. In this paper, we present a comprehensive literature review of recent contributions focused on improving the IoMT through the use of formal methodologies provided by the cyber-physical systems community. We describe the practical application of the democratization of medical devices for both patients and health-care providers. We also identify unexplored research directions and potential trends to solve uncharted research problems.
Finite Element Analysis of Electric Field Distribution in the Dielectric Gas R410A as an Alternative to SF6for High Voltage Applications

This paper examines the electric field distribution in the gap of dielectric gas R410A for the sphere-sphere electrodes. FEMM (ver. 4.2) open dedicated simulation software for implementing Finite Element Analysis (FEA) is used for this study. Analysis has been done on the electric field intensity along the gap axis of the sphere-sphere electrodes. The electric field distribution in the gap is strongly affected by the distance between the electrodes. Simulation results of R410A were compared with the results of SF6and at the same conditions the electric field intensity for R410A is 0.92 times of SF6. Beside other properties, R410A has comparable dielectric strength 0.92 that of SF6 and is good alternative to SF6.
Adapt Cases 4 BPM - A Modeling Framework for Process Flexibility in IIoT

The digital transformation of manufacturing systems has been prominently discussed by academia and industry in recent years. In this context, software systems can be treated as special kind of self-adaptive systems with an enhanced process flexibility, since interconnected resources have the ability to access data to fulfill non-functional requirements. This enhanced flexibility introduces new issues in the domain of BPM, since processes have to orchestrate business logic as well as adaptation logic that ensure the desired flexibility. This leads to a high complexity, which cannot be handled by classical BPM approaches adequately. In this paper, we present a modeling language based approach that supports modeling flexible and adaptive processes and managing the increased complexity. Additionally, we introduce a corresponding software engineering process that can be used to design flexible and adaptive processes. Since our approach is based on existing concepts of the languages UML and BPMN2.0, it is easy to adopt in new and existent projects that are based on them.
3D nuclide imaging method using neutron and X-ray synergy imaging

Nuclide distributions in a object can be obtained using pulsed neutron imaging. However, the real space images obtained by the method have a low spatial resolution because of the performance limitations of the detector. In this study, we combined between X-ray and neutron radiography measurements to improve the spatial resolution of the nuclide three dimensional distribution in a bulk object.
Implementation of Qualitative and Mixed Methods Researches

The objective of the qualitative and quantitative integration in research designs is the reconciliation between paradigms and methods in research in social science. The objective to specify the general epistemological formulations on which qualitative methods are based in more precise and current methodological proposals, since we are in an exciting moment in the qualitative research in which it is appreciated a clear tendency in the use of a mixed methods research. During the Twentieth-First Century that have favoured the rise of mixed methods researches that enhance the mutual invigoration of the two types of methods, and facilitate the triangulation through operations. The aim of this track is to provide a space for reflection and put into practice the foundation, operationalization, and fields of application of qualitative and mixed methods researches.
Extrapolation Method of On-Orbit Soft Error Rates of EDAC SRAM Devices From Accelerator-Based Tests

Single-event upset sensitivity of 55- and 180-nm SRAM devices with error detection and correction (EDAC) exhibits obvious ion flux and scrubbing time dependence. On-orbit soft error rates (SERs) of EDAC SRAM devices are extrapolated from accelerator heavy-ion data and compared with rectangular parallelepiped-predicted SER, based on an experimentally verified formula. It is found that on-orbit SER of EDAC SRAM is contributed by both the memory array and the EDAC circuitry. This method can guide the optimization of EDAC SRAM hardening strategy and also the on-orbit hardness assurance.
Goal-driven elaboration of OCL enriched UML class diagrams

UML class diagrams (or equivalent) are used to build a structural model of the system under design, including constraints captured using OCL. Being more focused on design, UML lacks support to make sure the model systematically captures the relevant domain concepts and properties in a traceable way, which is crucial for the subsequent design or testing steps. This paper shows how to apply goal-oriented requirements engineering techniques (GORE) to build UML class diagrams that are as complete as possible and consistent w.r. t. system goals and requirements captured using OCL. A mapping between both representations is defined and implemented based on the KAOS meta-model and USE textual syntax. In addition, the GORE process also enables to consider different alternatives before selecting a specific one and deriving specialised strengthenings of pre and post-conditions operations to enforce the system properties. The proposed approach is illustrated on excerpts of a railway system.
SIMPACK - Anwendungen eines Multidisziplinären Entwurfswerkzeugs für die Luft- und Raumfahrt in Industrie und Forschung

Das Programmpaket SIMPACK hat seinen Ursprung in Arbeiten der Organisationseinheit Fahrzeug-Systemdynamik im DLR und hat sich vom reinen Mehrkorpersimulations-Programm zum multidisziplinaren Entwurfswerkzeug entwickelt. Es ist in zahlreichen Luft- und Raumfahrt-Anwendungen in der Industrie und in der Forschung, sowohl an Instituten des DLR als auch an zahlreichen Universitaten im Einsatz. Das Anwendungsspektrum reicht dabei von Lastberechnungen von Flugzeugfahrwerken uber Stromungs-Struktur-Kopplung von Flugzeugen und Hubschraubern bis hin zu Docking Manovern von Satelliten und Bahnoptimierung von Weltraumrobotern. Fur die Anwendungen werden neben de Integration modernster mathematischer Methoden in SIMPACK die Entwicklung von intelligenten, bi-direktionalen Schnittstellen zu Standard-Entwurfswerkzeugen notwendig. Dazu gehoren Interfaces zu CAD-Systemen, Finite-Elemente-Programmen, zur Regler-Entwurfs-Software sowie zu Optimierungsumgebungen. Zunehmende Bedeutung hat ausderdem die Kopplung zu Computational Fluid Dynamics - Losern. Der Artikel soll reprasentative multidisziplinare Anwendungen von SIMPACK im Bereich der Luft- und Raumfahrt vorstellen, zentrale Problemstellungen dieser Anwendungen beleuchten und zeigen, welche Losungsansatze mit Hilfe der Mehrkorpersimulation gewahlt wurden.
Fluid Switch for Radiation Pattern Reconfigurable Antenna

This work presents a conductive fluid switch design, which is applied to a 3-element Yagi-Uda antenna operating at 433MHz industrial scientific medical (ISM) band. The directivity of the antenna is re-configurable by controlling the conduction state of the fluid switchs. 3D printing technology is used to fabricate the two parasitic elements. A microcontroller and a pump system are used to control the fluid level in the switch.