Miracle-dz/UniFAR-FTUs huggingface dataset:
Multilevel Inverter based Battery System Operation using a Decentralized Controller

Intensive research is currently being carried out on multilevel inverter based battery systems because of their wide range of possible applications and their promising results in efficiency. Since the communication within such a system is increasingly difficult with a rising number of modules, a new concept of module operation is necessary. This paper introduces the operation of an electric vehicle’s battery pack based on a multilevel inverter using a decentralized controller. Thereby, the necessary information transmitted within the system can be minimized. By using an individual current controller on each of the system’s modules, the distinct switching states for each module do not need to be transmitted via the data connection. A simulation model describing the system is implemented in Matlab/Simulink. It is used for parameter estimation of the individual controllers. Additionally, the decentralized controller’s functionality can be verified. The results show that the operation is fast enough for charging via the AC power grid and for the control of an electric motor. Furthermore, the regulations for grid-parallel operation can be complied with. It can also be shown that the system is enabled for battery balancing, defect monitoring and troubleshooting during operation.
High‐frequency asymptotic solutions benchmarking skew incidence diffraction by anisotropic impedance half and full planes

The diffraction of plane waves obliquely incident on the edge of anisotropic impedance half and full planes is investigated. Homogeneous anisotropic impedance boundary conditions are defined on both faces of the canonical structures under study, the principal anisotropy axes being parallel and perpendicular to the edge. Rigorous integral representations for the longitudinal field components are derived by applying the Sommerfeld‐Maliuzhinets method for a set of specific electrical configurations. Explicit uniform asymptotic expressions for the fields are given in the format of the Uniform Geometrical Theory of Diffraction (UTD). Although obtained for a specific class of geometrical and electrical configurations, these high‐frequency solutions provide a contribution for investigating the effects of material anisotropy on edge diffraction, as they represent a new set of reference cases for either developing perturbative solutions or testing numerical and approximate analytical methods of more general validity. Furthermore, these solutions extend the applicability of the Sommerfeld‐Maliuzhinets technique and represent a step forward to the solution of more general wedge canonical problems.
Evaluation of advanced reserve sizing methods based on RE variability and uncertainty

The large-scale integration of variable renewable energy (RE) into the electricity mix imposes to deal with the uncertainty and variability associated with such generation. As a result, the power system reserve management, which aims to ensure real-time balancing between production and load, has to evolve in order to guarantee the reliable operation of the electrical grid. This paper focuses on the evaluation of advanced reserve sizing methods identified in the literature, based on real operation data, from RE plants under operation. More precisely, the paper details a field-data oriented analysis, where fine time-resolution (few minutes time step) data is analyzed (1) to characterize RE variability and uncertainty, and (2) to evaluate the benefits from taking into account such variability and uncertainty for advanced reserve sizing.
Evaluation of Sustainable SF6 Alternative Gas Mixtures Used in Electric Power Equipment

Sulfur hexafluoride, SF6, has been the preferred dielectric medium in electrical power applications for decades. However, due to its extremely long atmospheric lifetime and very high global warming potential the industry is designing SF6-free technologies for many applications, including switchgear, circuit breakers and gas-insulated lines or bus bars. Alternative gas mixtures incorporating a fluoronitrile or a fluoroketone have low climate impact and are being successfully used in gas-insulated equipment currently operating on the grid in Europe.This paper reviews the toxicological studies conducted on these gases and the parameters required to perform a risk assessment for their use in electric power applications. The toxicological studies demonstrate that the alternative gases are low in acute inhalation toxicity which is the primary mode of potential exposure to an insulating gas. The occupational exposure limits established for these SF6-alternatives are well above the typical concentrations of insulating gas found near electric power equipment. In the event of accidental release of insulating gas, the alternative gas mixtures present potential exposure risks similar to those exhibited with SF6-filled equipment. Thus, these alternative gases and their mixtures provide a wide margin of safety required for these applications.
Determination of spin-dependent Seebeck coefficients of CoFeB/MgO/CoFeB magnetic tunnel junction nanopillars

We investigate the spin-dependent Seebeck coefficient and the tunneling magneto thermopower (TMTP) of CoFeB/MgO/CoFeB magnetic tunnel junctions (MTJ) in the presence of thermal gradients across the MTJ. The thermo power voltage VTP across the MTJ is found to scale linearly with the heating power and reveals similar field dependence as the tunnel magnetoresistance (TMR). Based on calibration measurements and finite element simulations of the heat flux, the thermal gradient and large spin-dependent Seebeck coefficients of the order of (240 ± 110) μV/K are derived. From additional measurements on MTJs after dielectric breakdown, a TMR up to 90% and Seebeck coefficients up to 650 μV/K can be derived.
Semantic Segmentation of SAR Images Through Fully Convolutional Networks and Hierarchical Probabilistic Graphical Models

This paper addresses the semantic segmentation of synthetic aperture radar (SAR) images through the combination of ful-ly convolutional networks (FCN s), hierarchical probabilistic graphical models (PGMs), and decision tree ensembles. The idea is to incorporate long-range spatial information together with the multiresolution information extracted by FCN s, through the multiresolution graph topology on which hierar-chical PGMs can be efficiently formulated. The objective is to obtain accurate classification results with small datasets and reduce problems of spatial inconsistency. The experimental validation is conducted with several COSMO-SkyMed satel-lite images over Northern Italy. The results are significant, as the proposed method obtains more accurate classification results than the standard FCN s considered.
Recent improvements in efficiency, accuracy, and convergence for implicit approximate factorization algorithms. [computational fluid dynamics

In 1977 and 1978, general purpose centrally space differenced implicit finite difference codes in two and three dimensions have been introduced. These codes, now called ARC2D and ARC3D, can run either in inviscid or viscous mode for steady or unsteady flow. Since the introduction of the ARC2D and ARC3D codes, overall computational efficiency could be improved by making use of a number of algorithmic changes. These changes are related to the use of a spatially varying time step, the use of a sequence of mesh refinements to establish approximate solutions, implementation of various ways to reduce inversion work, improved numerical dissipation terms, and more implicit treatment of terms. The present investigation has the objective to describe the considered improvements and to quantify advantages and disadvantages. It is found that using established and simple procedures, a computer code can be maintained which is competitive with specialized codes.
Why Are AGN and Host Galaxies Misaligned

It is well-established observationally that the characteristic angular momentum axis on small scales around AGN, traced by radio jets and the putative torus, is not well-correlated with the large-scale angular momentum axis of the host galaxy. In this paper, we show that such misalignments arise naturally in high-resolution simulations in which we follow angular momentum transport and inflows from galaxy to sub-pc scales near AGN, triggered either during galaxy mergers or by instabilities in isolated disks. Sudden misalignments can sometimes be caused by single massive clumps falling into the center slightly off-axis, but more generally, they arise even when the gas inflows are smooth and trace only global gravitational instabilities. When several nested, self-gravitating modes are present, the inner ones can precess and tumble in the potential of the outer modes. Resonant angular momentum exchange can flip or re-align the spin of an inner mode on a short timescale, even without the presence of massive clumps. We therefore do not expect that AGN and their host galaxies will be preferentially aligned, nor should the relative alignment be an indicator of the AGN fueling mechanism. We discuss implications of this conclusion for AGN feedback and BH spin evolution. The misalignments may mean that even BHs accreting from smooth large-scale disks will not be spun up to maximal rotation, and so have more modest radiative efficiencies and inefficient jet formation. Even more random orientations/lower spins are possible if there is further, un-resolved clumpiness in the gas, and more ordered accretion may occur if the inflow is slower and not self-gravitating.
An Analysis of Intention Detection Strategies to Control Advanced Assistive Technologies at the CYBATHLON

With the increasing range of functionalities of advanced assistive technologies (AAT), reliable control and initiation of the desired actions become increasingly challenging for users. In this work, we present an analysis of current practices, user preferences, and usability of AAT intention detection strategies based on a survey among participants with disabilities at the CYBATHLON 2020 Global Edition. We collected data from 35 respondents, using devices in various disciplines and levels of technology maturity. We found that conventional, direct inputs such as buttons and joysticks are used by the majority of AAT (71.4%) due to their simplicity and learnability. However, 22 respondents (62.8%) reported a desire for more natural control using muscle or non-invasive brain signals, and 37.1% even reported an openness to invasive strategies for potentially improved control. The usability of the used strategies in terms of the explored attributes (reliability, mental effort, required learning) was mainly perceived positively, whereas no significant difference was observed across intention detection strategies and device types. It can be assumed that the strategies used during the CYBATHLON realistically represent options to control an AAT in a dynamic, physically and mentally demanding environment. Thus, this work underlines the need for carefully considering user needs and preferences for the selection of intention detection strategies in a context of use outside the laboratory.
Effect on Hand Function After Six-week Use of a Wearable Soft-Robotic Glove Assisting ADL: Interim Results of an Ongoing Clinical Study

In an ongoing study, an assistive wearable soft-robotic glove is tested at home for 6 weeks by subjects with decreased handgrip strength, due to different hand injuries or diseases, to assess whether use of this assistive grip-supporting glove will result in improved hand strength/ function. An interim analysis of the available dataset of 46 participants showed that (unsupported) grip strength and hand function improved after using the soft-robotic glove as assistive aid during activities of daily living (ADLs) during 6 weeks at home. After glove use is ended, this is maintained for at least 4 weeks. Considering that in the current situation the analysis is underpowered, these interim results are promising for finding a clinical (therapeutic) effect of using a soft-robotic glove as assistance during ADLs. If this is the case, this might open up entirely new opportunities for extending rehabilitation into people’s homes, while also providing them with assistance to directly support performance of daily activities. Such a combination is becoming available with the development of mature and user-friendly wearable soft-robotic devices. This would enable very high doses of training throughout the day, in the most functional, task-specific way possible, and possibly prevention of learned non-use.
Preliminary Validation of Proportional Myoelectric Control of A Commercially Available Robotic Ankle Exoskeleton

Proportional myoelectric control of robotic lower limb exoskeletons can increase the variability and adaptability of biomechanical behaviors for assisting human movement compared to traditional state-based control. Previous exoskeletons using proportional myoelectric control have relied on pneumatic actuators and been limited to laboratory use. We applied proportional myoelectric control to a robotic ankle exoskeleton using a brushless DC motor (Dephy) and enabled it to work in community settings. Benchtop testing verified electromechanical responses similar to biological values (electromechanical delay of 22 ms and time to peak activation of 123 ms). Four healthy participants trained for thirty minutes each using bilateral ankle exoskeletons. From minute one of powered walking to minute 30 of powered walking, peak soleus EMG reduced by 17.9% as they learned to walk with exoskeleton assistance. Our future work will extend the powered walking period, measure metabolic cost, and measure gait variability between participants using proportional myoelectric control on fully portable, electromechanical ankle exoskeletons.
Helium enhanced stars and multiple populations along the horizontal branch of NGC 2808: direct spectroscopic measurements

We present an abundance analysis of 96 horizontal branch (HB) stars in NGC 2808, a globular cluster exhibiting a complex multiple stellar population p attern. These stars are distributed in different portions of the HB and cover a wide range of temperature. By studying the chemical abundances of this sample, we explore the connection between HB morphology and the chemical enrichment history of multiple stellar populatio ns. For stars lying on the red HB, we use GIRAFFE and UVES spectra to determine Na, Mg, Si, Ca, Sc, Ti, Cr, Mn, Fe, Ni, Zn, Y, Ba, and Nd abundances. For colder, blue HB stars, we derive abundances for Na, primarily from GIRAFFE spectra. We were also able to measure direct NLTE He abundances for a subset of these blue HB stars with temperature higher than∼9000 K. Our results show that: (i) HB stars in NGC 2808 show different content in Na depending on their position in the color-magnitude diagram, with blue HB stars having higher Na than red HB stars; (ii) the red HB is not consistent with an uniform chemical abundance, with slightly warmer stars exhibiting a statistically significant higher Na content; and (iii) our subsample of blue HB stars with He abundances shows evidence of enhancement with respect to the predicted primordial He ‐ ‐ ‐ ‐
Learning Dynamic Patient-Robot Task Assignment and Scheduling for A Robotic Rehabilitation Gym

A robotic rehabilitation gym is a setup that allows multiple patients to exercise together using multiple robots. The effectiveness of training in such a group setting could be increased by dynamically assigning patients to specific robots. In this simulation study, we develop an automated system that dynamically makes patient-robot assignments based on measured patient performance to achieve optimal group rehabilitation outcome. To solve the dynamic assignment problem, we propose an approach that uses a neural network classifier to predict the assignment priority between two patients for a specific robot given their task success rate on that robot. The priority classifier is trained using assignment demonstrations provided by a domain expert. In the absence of real human data from a robotic gym, we develop a robotic gym simulator and create a synthetic dataset for training the classifier. The simulation results show that our approach makes effective assignments that yield comparable patient training outcomes to those obtained by the domain expert.
The WBM Reconfiguration to Prevent the Instability on DC Shipboard Microgrids

Most innovative DC shipboard microgrids are designed to feed high-performance loads with advanced flexibility feature. The onboard loads not only require great amounts of power, but also their management results dynamically demanding. To this aim, tightly controlled power converters are employed to supply the loads by the filtered DC distribution. In such an islanded system, high-bandwidth converters and LC filters can negatively interact thus finally jeopardizing the ship operation. Smart procedures are to be conceived to preserve the system stability by reconfiguring the online shipboard loads. As the system stability depends on power/bandwidth of each load, the Weighted Bandwidth Method (WBM) is adopted to aggregate the effect of the several controlled loads. Once the WBM identifies two controlled loads as representative of the total dynamics demand, a 3D map results consequent. It reveals the loads combination to be fed without impairing the stability. If the Power Management System (PMS) exploits the outcomes from the 3D map to perform planned reconfigurations, the onboard stable operation is certainly ensured.
Correlating Vibration Patterns to Perception of Tactile Information for Long-Term Prosthetic Limb Use and Continued Rehabilitation of Neuropathic Pain

Prosthetic limbs (and orthotic devices) have been used as a paradigm for the treatment and rehabilitation of neuropathic pain, such as phantom limb pain. Long-term adoption of the devices for the continued use in rehabilitation remains low in part due to reduced embodiment and the high cognitive load associated with controlling the device. Previous research has shown that incorporating sensory feedback in prostheses can provide proprioceptive information, increase control and manipulation of objects, and improve embodiment. However, feedback experienced by the user varies daily and requires constant parameter adjustments to maintain accurate and intuitive sensory perception, further preventing long term adoption. Work therefore needs to be explored that correlate feedback modalities to perception of tactile information, such as texture and pressure. The work presented in this paper begins to explore this by utilizing a deep-learning algorithm to classify the dissipation of vibration artefacts found in the EMG signals of able-bodied individuals to specific texture patterns. Four texture patterns were applied to 7 participants using two vibration motors and repeated 3 times. In post processing, a RNN network identified the artefact features along equidistantly spaced EMG electrodes and correctly classified unseen data from each participant.
Observational constraints on Tachyon and DBI inflation

We present a systematic method for evaluation of perturbation observables in non-canonical single-field inflation models within the slow-roll approximation, which allied with field redefinitions enables predictions to be established for a wide range of models. We use this to investigate various non-canonical inflation models, including Tachyon inflation and DBI inflation. The Lambert 𝒲 function will be used extensively in our method for the evaluation of observables. In the Tachyon case, in the slow-roll approximation the model can be approximated by a canonical field with a redefined potential, which yields predictions in better agreement with observations than the canonical equivalents. For DBI inflation models we consider contributions from both the scalar potential and the warp geometry. In the case of a quartic potential, we find a formula for the observables under both non-relativistic (sound speed cs2 ∼ 1) and relativistic behaviour (cs2 ≪ 1) of the scalar DBI inflaton. For a quadratic potential we find two branches in the non-relativistic cs2 ∼ 1 case, determined by the competition of model parameters, while for the relativistic case cs2 → 0, we find consistency with results already in the literature. We present a comparison to the latest Planck satellite observations. Most of the non-canonical models we investigate, including the Tachyon, are better fits to data than canonical models with the same potential, but we find that DBI models in the slow-roll regime have difficulty in matching the data.
UNDERSTANDING AGN–HOST CONNECTION IN PARTIALLY OBSCURED ACTIVE GALACTIC NUCLEI. III. PROPERTIES OF ROSAT-SELECTED SDSS ACTIVE GALACTIC NUCLEI

As the third paper of our series of studies that aim at examining the AGN–host co-evolution by using partially obscured active galactic nuclei (AGNs), we extend the broad-line composite galaxies (composite AGNs) into ROSAT-selected Seyfert 1.8/1.9 galaxies based upon the ROSAT All Sky Survey/Sloan Digital Sky Survey Data Release 5 (SDSS-DR5) catalog given by Anderson et al. The SDSS spectra of a total of 92 objects are analyzed by the same method used in our previous studies, after requiring the signal-to-noise ratio in the SDSS r′ band to be larger than 20. Combining the ROSAT-selected Seyfert galaxies with the composite AGNs reinforces the tight correlation between the line ratio [O i]/Hα versus Dn(4000), and establishes a new tight correlation between [S ii]/Hα versus Dn(4000). Both correlations suggest that the two line ratios are plausible age indicators of the circumnuclear stellar population for typical Type I AGNs in which the stellar populations are difficult to derive from their optical spectra. The ROSAT-selected Seyfert galaxies show that the two correlations depend on the soft X-ray spectral slope αX, which is roughly estimated from the hardness ratios by requiring that the X-ray count rates within 0.1–2.4 keV be larger than 0.02 counts s-1. However, we fail to establish a relationship between αX and Dn(4000), which is likely caused by the relatively large uncertainties of both the parameters (especially for αX because of the AGN intrinsic obscuration). The previously established L/LEdd–Dn(4000) evolutionary sequence is reinforced again by the extension to the ROSAT-selected Seyfert galaxies. These X-ray-selected Seyfert galaxies are, however, biased against the two ends of the sequence, which implies that the X-ray Seyfert galaxies present a population at a middle evolutionary stage.
Extended O VI haloes of star-forming galaxies

We consider evolution of metal-enriched gas exposed to a superposition of timedependent radiation field of a nearby starburst galaxy and nearly invariant (on timescales 100 Myr) extragalactic ionization background. We study the evolution of ionic species (particularly those commonly observed in galactic circumference) depending on the galactic mass and star formation rate, and derive conditions for the highly ionized oxygen OVI to appear in extended galactic haloes in absorption or emission spectra. We have found that the maximum OVI fraction can reach � 0.4 0.6 under the action of both the ionizing radiation field from the galaxy, and the extragalactic background, and remains high in a wide temperature range. This circumstance can explain high column densities of OVI (N(OVI) � 10 14.5−15.3 cm −2 ) observed in the haloes of staforming galaxies by Tumlinson et al. (2011) even for a relatively low (� 0.1Z⊙) metallicity. As a result, the requirements to the sources of oxygen in the extended haloes relax to a reasonably conservative level.