Miracle-dz/UniFAR-FTUs huggingface dataset:
Comprehensive Characterization of the 4H-SiC Planar and Trench Gate MOSFETs From Cryogenic to High Temperature

In this article, the static, dynamic, and short-circuit properties of 1.2-kV commercial 4H-SiC planar and trench gate metal–oxide–semiconductor field-effect transistors (MOSFETs) are compared and analyzed in a wide temperature range from 90 to 493 K. The temperature-dependent specific ON-resistance (<inline-formula> <tex-math notation="LaTeX">${R}_{\text {sp}- \mathrm{\scriptscriptstyle ON}}$ </tex-math></inline-formula>) and threshold voltage (<inline-formula> <tex-math notation="LaTeX">${V}_{\text {th}}$ </tex-math></inline-formula>) are analyzed in relation to the density of the interface state. The turn-on rise and turn-off fall times (<inline-formula> <tex-math notation="LaTeX">${T}_{r}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${T}_{f}$ </tex-math></inline-formula>) and the corresponding energy loss (<inline-formula> <tex-math notation="LaTeX">${E}_{r}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${E}_{f}$ </tex-math></inline-formula>) are extracted from a double-pulse test from cryogenic to high temperature and analyzed. The short-circuit capability of the two structures is studied at low temperature for the first time. The comprehensive comparison and analysis of the planar and trench gate MOSFET versus temperature in this work show the importance to study applications with SiC MOSFETs in a wide temperature range, especially for the cryogenic temperatures.
Urban Impervious Surface Detection From Remote Sensing Images: A review of the methods and challenges

Urban impervious surface (UIS) offers potentially valuable information for the development of sustainable urban management strategies and environmental change monitoring actions. In this article, we focus on UIS-detection-related issues, identify and analyze systematic challenges, construct a general processing scheme for UIS detection, provide four categories of major methods, and propose a deep compressive-based convolutional deep belief network (dc-CDBN) method and a novel classification strategy for multisource data fusion models.
Improving Elliptic/Hyperbolic Localization Under Multipath Environment Using Neural Network for Outlier Detection

The presence of measurement outliers can significantly reduce the performance of a localization algorithm. Detection and removal of the outliers are crucial to improve the positioning accuracy. This paper proposes new features together with an Artificial Neural Network (ANN) for outlier detection, where the outlier statistics and the number of outliers are not known a priori. The features reflect the quality of a location estimate using a subset of the measurements and are effective for use with an ANN of two hidden layers for outlier detection. Simulations demonstrate the ability of the proposed method in handling various number of outliers and providing the Cramèr-Rao lower bound (CRLB) localization accuracy under Gaussian noise, and show that it maintains 100% correct detection of outliers while keeping the false detection at a minimum level. The proposed method can work with elliptic and hyperbolic positioning in 2-D and 3-D.
Development and Analysis of a Hybrid Inverse Kinematic Solution for Anthropomorphic In-Hand Manipulations

The evolutionary success of humans is a result of many biological factors; however, one predominant advantage is from the capabilities of the human hand. The dexterity of this mechanical system provides the capabilities to perform a wide variety of tasks. This performance is the motivation to design robotic systems with similar characteristics. Anthropomorphic robotic hands are designed to be the robotic counterpart of human hands. These human-like systems attempt to achieve the same dexterity as human hands to allow flexibility in the applications that require robotic assistance. Controlling these complex systems serves as a challenge in the robotic community and currently limits the capabilities of these advanced robot hands. This paper proposes a solution for controlling objects during in-hand manipulations with inspiration from parallel manipulators. This solution shows promising results that offer the basis for further research into more complex tasks.
Exploiting Spatial-Wideband Effect for Fast AoA Estimation at Lens Antenna Array

Energy-efficient, highly integrated lens antenna arrays (LAAs) have found widespread applications in wideband millimeter wave or terahertz communications, localization and tracking, and wireless power transfer. Accurate estimation of angle-of-arrival (AoA) is key to those applications, but has been hindered by a spatial-wideband effect in wideband systems. This paper proposes to exploit (rather than circumventing) the spatial-wideband effect to develop a fast and accurate AoA estimation approach for LAAs. Specifically, we unveil new spatial-frequency patterns based on the spatial-wideband effect, and establish one-to-one mappings between the patterns and the strongest discrete Fourier transform (DFT) beam containing the AoA. With the strongest DFT beam identified, we propose a method to estimate the AoA uniquely and accurately, using only a few training symbols. This is achieved by deriving a new one-to-one mapping between the AoA and the set of DFT beams judiciously selected based on the strongest. In the case that an impinging path is uniformly distributed in <inline-formula><tex-math notation="LaTeX">$ [\text{0,2}\pi ]$</tex-math></inline-formula>, simulations show that the proposed algorithm is able to reduce the mean squared error of the AoA estimation by as much as <inline-formula><tex-math notation="LaTeX">$\text{ 82.1}$</tex-math></inline-formula>% while reducing the number of required symbols by <inline-formula><tex-math notation="LaTeX">$\text{ 93.2}$</tex-math></inline-formula>%, as compared to existing techniques. The algorithm can also increase the spectral efficiency by <inline-formula><tex-math notation="LaTeX">$\text{ 89}$</tex-math></inline-formula>% when the average SNR is <inline-formula><tex-math notation="LaTeX">$ -\text{20}$</tex-math></inline-formula> dB at each antenna of the receiver.
Symmetry of Gating in Double-Gate MoS2 FETs

In this article, we correlate various double-gate (DG) molybdenum disulfide (MoS<sub>2</sub>) FET architectures with the contact resistance (<inline-formula> <tex-math notation="LaTeX">${R}_{{\text {C}}}$ </tex-math></inline-formula>) and performance. We show that the MoS<sub>2</sub> DGFETs can achieve near-ideal subthreshold slope and threshold voltage modulation. We demonstrate how these DGFETs enable extraction of the gate-dependent contact resistance using only two-point probe (2PP) measurements. We show that when MoS<sub>2</sub> is either only above or below source/drain (S/D) metal contacts, only one of the two gates can modulate the contact resistance through electrostatic doping, even when both gates overlap the contacts with the associated overlap capacitance. Finally, we fabricate and characterize a new MoS<sub>2</sub> DGFET structure in which MoS<sub>2</sub> is both above and below the S/D contacts, to enable both gates to modulate <inline-formula> <tex-math notation="LaTeX">${R}_{{\text {C}}}$ </tex-math></inline-formula> and the channel resistance (<inline-formula> <tex-math notation="LaTeX">${R}_{{\text {CHANNEL}}}$ </tex-math></inline-formula>). We show that both gates of the new DGFET can reduce <inline-formula> <tex-math notation="LaTeX">${R}_{\text {C}}$ </tex-math></inline-formula> leading to higher drive current and more symmetrical gating for design flexibility. This new architecture will be useful in applications of DGFETs in signal processing including mixing and low-noise amplification.
The Qualitative and Quantitative Structure of the Causes of Occupational Accidents on Construction Scaffolding

Abstract The article presents the results of research, the aim of which was to determine the qualitative and quantitative structure of the causes of accidents that were a result of falling from scaffolding. An original methodology for the classification of accidents with regards to their causes was developed and was based on cluster analysis. An example of using the proposed methodology is provided. 187 post-accident protocols of occupational accidents involving construction scaffolding, which occurred between 2010 and 2017 in selected Polish voivodeships, were analyzed. Afterwards, the matrix of accident causes, for which the calculations were made, was created. Five subsets of accidents were obtained and the accidents were classified to a subset with similar causes.
Deindustrialization and Implementation of Industry 4.0 - Case of The Republic of Croatia

Abstract The industrial sector of the Republic of Croatia is subject to deindustrialization, which was globally recognized as early as in the 1960s. Such a situation is a challenge in terms of implementing new sources of economic growth and industrial production, with a particular emphasis on investing in research and development, education and their products. Since 2011, special emphasis has been placed on the need to implement the concept of Industry 4.0. The problem surveyed in this research derives from insufficient readiness of the Republic of Croatia to implement Industry 4.0, mainly resulting from its major orientation towards traditional industrial sectors and a low share of high value added activities, which is particularly visible through the share of high technology products in total exports. However, the Republic of Croatia is characterized by low levels of scientific research and innovative activities, which greatly slows down this process. The aim of the conducted research is to present the theoretical aspects of the process of deindustrialization and Industry 4.0, to make projections of the key indicators of deindustrialization and Industry 4.0 until 2025, and to propose scientifically based measures to be taken in the direction of securing digital transformation of the Croatian industry. The purpose of the conducted research is to analyse trends in the industrial sector in the Republic of Croatia and to determine the current state of the (de)industrialization process and the level of implementation of Industry 4.0. The research has showed that the process of deindustrialization in the Republic of Croatia is characterized by a reduction in the share of employment in the primary sector, by a growing employment in the secondary sector, and by a relative increase in industrial production and labour productivity. However, since 2015 there has been an increase in employment in the secondary sector, which is in contrast to the theoretical concepts of deindustrialization and indicates a new trend in the industrial sector. This situation is a challenge concerning the implementation of Industry 4.0, which requires increased investment in research and development and the improvement of knowledge and the ability of the population and their implementation in the economic sector. By analysing this segment of the Croatian economy, some progress has been made. Also, it has also been found that in some segments it significantly lags behind the EU levels.
Impact of selected lean management tools on work safety

Abstract The ongoing processes in production enterprises must be constantly monitored and improved in order to meet the requirements of growing competition in the technical, technological and organizational aspects. Also, customer expectations regarding the quality of products are constantly increasing, while maintaining the lowest manufacturing costs. The analysis of the course of operations, exploited resources, materials, recharges, as well as the identification of risk and losses are the basis for improvement and optimization, leading to increase in process efficiency, as well as optimisation of organization and working conditions. There are many management methods and tools used to streamline processes. Currently, Lean Management (LM) is one of the most popular and effective concepts in this field. The primary goal of LM is to eliminate activities that do not bring added value in processes, while saving resources and meeting customer requirements. The Lean concept offers many useful methods and tools that, when properly selected in the organization, implemented and used, can bring the intended results. The aim of the article is to present the results of the analysis of potentially accidental events in a production enterprise based on the identification of key threats occurring in the plant. Based on Lean Management methods and tools implemented in the company, their impact on work safety was determined.
Heart Rate Variability Analysis During Lower Body Negative Pressure Test Induced Central Hypovolemia

Abstract In clinical patient monitoring scenarios, the detection of hemorrhage is still a major problem. Traditional vital signs like heart rate and blood pressure are insensitive to blood loss due to compensatory mechanisms in the body that can sustain these parameters until shortly before cardiovascular collapse. These compensatory mechanisms during blood loss are primarily driven by the autonomic nervous system. Heart rate variability analysis is a viable tool in the quantitative analysis of the autonomic nervous system and shows promising results in the context of hypovolemia detection. In order to investigate if HRV parameters suitably reflect a mild to moderate blood volume reduction, we conducted a lower body negative pressure test study with 30 volunteering participants thereby simulating progressive central hypovolemia. Here, HRV parameters from the time domain (mean HR, SDNN, RMSSD, rSDRM, pNN50), the frequency domain (VLF, LF, HF, LF/HF), non-linear HRV parameters (SD1, SD2, SD1/SD2, SampEn, ApEn) and the respiratory rate (RR) were collected. The changes of the evaluated parameters as a consequence of the reduced blood volume were statistically evaluated. A statistically significant deviation from their baseline values could be found for RMSSD, rSDRM, pNN50, HF, LF/HF, SD1 and SD1/SD2 at a chamber pressures starting at −30 mmHg. Therefore, we support the proposition that heart rate variability analysis can help in detecting otherwise occult hypovolemia.
The CAC 40 Index’s Reaction to Terrorist Attacks: The Case of Charlie Hebdo

Abstract Over the last decades, terrorism has become a global phenomenon to which every society is exposed from time to time. Terrorist attacks can have many economic consequences that may affect a number of sectors, including the capital market. The main goal of this paper is to examine the reaction of the CAC40 index to one terrorist attack, mainly “Charlie Hebdo” using an event study methodology. By calculating the abnormal returns and the cumulative abnormal returns in the event period, the results obtained show no significant abnormal returns on the day of the terrorist attack suggesting that the market had directly absorbed the effect of the attack. Thus, the findings suggest that the French market is semi-strong efficient. Investors can rely neither on past information nor on publicly available information to make abnormal profits.
Secular and catastrophic processes reflected in sediments of the Suchedniów water reservoir, Holy Cross Mountains (Poland)

Abstract The Suchedniów water reservoir is located in the central section of the River Kamionka in the northern part of the Holy Cross Mountains of central Poland. This area once belonged to the Old Polish Industrial District that, during the Middle Ages, was very intensively developed by iron metallurgy. Many forges and mills along the rivers used water power, which led to the construction of an anthropogenic, small-scale water retention system. At the beginning of the twentieth century many of these reservoirs were drained after the collapse of metallurgical activities. The present-day reservoir was built in 1974 and drained in 2017. Research into the drained basin has documented various forms and sediments, some of which record present-day depositional processes (fire proof clay layer, inland fan delta), while others represent the historical period (lacustrine sediments of older reservoirs). Traces of catastrophic events have been preserved as well; an assemblage of megaripples marks the sudden drainage caused by a dam break in 1974.
A step towards enzyme-free tissue dissociation

Abstract The future of personalized diagnostics commences on the single cell level. Even high-end technologies like Next Generation Sequencing can be improved if applied on pure single cell populations (e.g., tumor cells without contaminating stromal cells) or on a single cell level (DNA/RNA sequencing). The vast majority of these technologies need individual and preferably undistorted cells for the analytical process. Thus, decisive prerequisite for high-end analytics is to remove cells from their tissue matrix as gently as possible. This can be accomplished by an enzyme-free, fast and reproducible approach of generating pure and individual single cells from tissue samples. In this study we demonstrate the utility of a semi-automated Tissue Grinder that is compatible with standard 50 ml centrifuge tubes and standard cell strainer for mechanically, nonenzymatic and parallel processing of tissue samples. We show that without enzymatic treatment viable single-cell yields match or exceed reference enzymatic methods, while reducing processing time by at least 80%.
Integrating Label Uncertainty in Ultrasound Image Classification using Weighted Support Vector Machines

Abstract Inference from medical image data using machine learning still suffers from the disregard of label uncertainty. Usually, medical images are labeled by multiple experts. However, the uncertainty of this training data, assessible as the unity of opinions of observers, is neglected as training is commonly performed on binary decision labels. In this work, we present a novel method to incorporate this label uncertainty into the learning problem using weighted Support Vector Machines (wSVM). The idea is to assign an uncertainty score to each data point. The score is between 0 and 1 and is calculated based on the unity of opinions of all observers, where u = 1 if all observers have the same opinion and u = 0 if the observers opinions are exactly 50/50, with linear interpolation in between. This score is integrated in the Support Vector Machine (SVM) optimization as a weighting of errors made for the corresponding data point. For evaluation, we asked 15 observers to label 48 2D ultrasound images of aortic roots addressing whether the images show a healthy or a pathologically dilated anatomy, where the ground truth was known. As the observers were not trained experts, a high diversity of opinions was present in the data set. We performed image classification using both approaches, i.e. classical SVM and wSVM with integrated uncertainty weighting, utilizing 10-fold Cross Validation, respectively (linear kernel, C = 7). By incorporating the observer uncertainty, the classification accuracy could be improved by 3.1 percentage points (SVM: 83.5%, wSVM: 86.6%). This indicates that integrating information on the observers’ unity of opinions increases the generalization performance of the classifier and that uncertainty weighted wSVM could present a promising method for machine learning in the medical domain.
Biodegradable magnetic microspheres for drug targeting, temperature controlled drug release, and hyperthermia

Abstract Magnetic microspheres (MMS) used for magnetic drug targeting consist of magnetic nanoparticles (MNP) and a pharmaceutical agent embedded in a polymeric matrix material. The application of MNP for drug targeting enables guiding the MMS to a target area, imaging the position of the MMS with magnetic particle imaging, and finally inducing drug release. As latter takes place by degradation of the MMS or diffusion through the matrix, an increase in temperature, e.g. through magnetic hyperthermia, leads to an accelerated drug release. Here, MMS consisting of poly(lactic-coglycolic) acid (PLGA) with different monomer ratios were prepared by an oil-in-water emulsion evaporation method. The model drug Camptothecin (CPT) and magnetic multicore nanoparticles (MCNP) with a high specific heating rate were embedded into the microspheres. We obtained MMS in the preferred size range of 1 to 2 μm with a concentration of MCNP of 16wt%, a drug load of about 0.5wt% and an excellent heating performance of 161 W/gMMS. Investigations of the drug release behaviour showed an accelerated drug release when increasing the temperature from 20 °C to 37 °C or 43 °C by using a water bath. In addition, an increase in drug release of about 50% through magnetic heating of the MMS up to 44 °C compared to 37 °C was observed. By this, a magnetic hyperthermia induced CPT release from PLGA MMS is demonstrated for the very first time.
Construction of a novel microfluidic experimental setup for testing recent glaucoma drainage devices

Abstract Glaucoma is an eye disorder in which the optic nerve is damaged over time due to a sustained elevation of the intraocular pressure (IOP). Being the second leading cause of blindness according to the reports of the World Health Organization, glaucoma is not only a serious ocular disease that threatens individuals, but also a community health problem. In recent years, great improvement has been achieved in the technology of implants used in the treatment of the disease. Despite the great effort dedicated to the design and implementation of the glaucoma drainage devices (GDD), they still have unsolved problems and weaknesses. Most of the currently employed GDDs are very simple and have major problems such as reversed flow, choking and a coarse interval of pressure control. Experiments must be devised to investigate the flow behavior inside these devices. In this study, an accurate microfluidics experimental setup is constructed to analyze and characterize the in-vitro performance of actively employed GDDs on the glaucoma treatment. Proposed setup includes a pressurized fluid reservoir, ELVEFLOW microfluidics flow rate measurement/control unit, microfluidics flow/pressure sensors, and data analysis system. In the setup, more precise measurements than experimental setups in literature is planned to be provided. It is estimated that the results showing consistency with in-vivo measurements will be obtained, behavior of the fluid passing through the GDDs will be observed and issues with design flaws will be addressed.
The feasibility of using a low-cost depth camera for 3D scanning in mass customization

Abstract By combining additive manufacturing with 3D measurement techniques, tailored production work-flows that include the digitizing of existing components, computer-aided design, and tool-free manufacturing of the customized parts can be envisioned, potentially reducing the costs of mass customization. The introduction of affordable depth cameras has greatly increased the consumer availability of 3D measuring. We present the application of an affordable depth camera for the 3D digitizing of existing components, the utilization of the produced data in the design process, and finally, the production of the designed component with additive manufacturing. The capabilities of the affordable depth camera system are evaluated by comparing it with photogrammetric 3D reconstruction, revealing issues in smaller geometric details and sharp edges.