Miracle-dz/UniFAR-FTUs huggingface dataset:
Voltage Control of a Stand-Alone Cascaded Doubly Fed Induction Generator

This paper studies the cascaded doubly fed induction machine, operating as a brushless variable speed constant frequency generator supplying an isolated load. In isolated electric supply, the amplitude and frequency of the output voltage of the generator should be stabilized during the speed and/or load changing. Despite the complexity of the generator model, a simple indirect field-oriented vector control is elaborated to meet the output voltage requirements. Experimental results validate the proposed control approach. The study is extended to reveal the behavior of the controlled system under unbalanced load.
Dependency-Aware Data Locality for MapReduce

MapReduce effectively partitions and distributes computation workloads to a cluster of servers, facilitating today’s big data processing. Given the massive data to be dispatched, and the intermediate results to be collected and aggregated, there have been a significant studies on data locality that seeks to co-locate computation with data, so as to reduce cross-server traffic in MapReduce. They generally assume that the input data have little dependency with each other, which however is not necessarily true for that of many real-world applications, and we show strong evidence that the finishing time of MapReduce tasks can be greatly prolonged with such data dependency. In this paper, we present Dependency-Aware Locality for MapReduce (DALM) for processing the real-world input data that can be highly skewed and dependent. DALM accommodates data-dependency in a data-locality framework, organically synthesizing the key components from data reorganization, replication, placement. Beside algorithmic design within the framework, we have also closely examined the deployment challenges, particularly in public virtualized cloud environments, and have implemented DALM on Hadoop 1.2. 1 with Giraph 1.0. 0. Its performance has been evaluated through both simulations and real-world experiments, and compared with that of state-of-the-art solutions.
C2R Net: The Coarse to Refined Network for Image Forgery Detection

Image splicing forgery means to extract a portion from one image and then place it to another image for merging a new image. Distinguishing a splicing forgery image is a challenging task. In this paper, we propose a deep learning based method to detect splicing image. The proposed network includes two convolutional neural networks (CNNs): the coarse CNN and the refined CNN, which extracts the differences between image itself and splicing regions from patch descriptors of different scales. Unlike previous detection methods that always rely on one property difference detection between the splicing image and the original image, the proposed detection method learns various intrinsic property differences between the splicing images and the original images by CNNs with different scales. For decreasing the complexity of computational time, we further propose image-level CNN to replace the previous patch-level CNN for fast computation. Experimental results show that the proposed detection method is better than the previous detection methods, especially the testing dataset is the real-world dataset.
Displacement improvement from variable pre-stretch diaphragm type Dielectric Elastomer Actuator

Dielectric Elastomer Actuator (DEA) is a promising technology for artificial muscle applications based on its large voltage-induced displacement and the ability to generate a large variety of motion. This paper presents a DEA based on a modified diaphragm configuration that improves electrically-induced displacement. Existing diaphragm DEAs are equal-biaxially pre-stretched before being constrained by rigid inner and outer rings. In this paper, we first apply equal-biaxial pre-stretch, and then relax its radial pre-stretch before securing it on the outer ring. By doing this, we allow the actuation space in a radial direction to be increased. Both analysis and experiment show significant improvement in actuation as compared to an equal-biaxially-secured one. Our analysis predicted a 53% more electrically-induced displacement as compared to that of equal-biaxially pre-stretched DEAs. Our experiments further showed that when actuated near electrical breakdown, a variable pre-stretched DEA can actuate more than 50% in its out-of-plane displacement with dead load. At large displacement, the output force of our modified DEA is also higher, thus increasing the stored mechanical energy. We hope to expand the applications of diaphragm DEAs with a variable pre-stretched diaphragm in robotic applications.
Mindfulness-based cognitive therapy for psycho-oncology patients: an exploratory study

Objectives Mindfulness-based cognitive therapy (MBCT) is a group-based intervention similar to mindfulness-based stress reduction, but which includes cognitive therapy techniques. This study investigates its usefulness in the treatment of depressive, anxiety and stress/distress symptoms in cancer patients referred to a psycho-oncology service. It also examines whether effect on depression is mediated by self-compassion. Method In phase 1 of this study, 16 cancer patients with mild/moderate psychological distress were randomised to MBCT (n=8) or treatment as usual (TAU; n=8), and assessed pre- and post-treatment. Analysis of variance was performed to examine the effect of treatment on anxiety and depression. In phase 2, the TAU group received the intervention, and results of pre- and post-MBCT assessments were combined with those receiving MBCT in phase 1. Finally, both groups were followed up at 3 months. Results In phase 1, the MBCT group had a significant improvement in mindfulness and a decrease in anxiety. Statistically significant improvements in both depression and anxiety were found at 3 month follow-up. Self-compassion appeared to mediate the effect on anxiety/depression. Conclusion This small pilot study suggests that MBCT may have a beneficial effect on psychological variables often adversely affected in cancer in a heterogeneous cancer population.
Through-Glass Vias for Glass Interposers and MEMS Packaging Applications Fabricated Using Magnetic Assembly of Microscale Metal Wires

A through-glass via (TGV) provides a vertical electrical connection through a glass substrate. TGVs are used in advanced packaging solutions, such as glass interposers and wafer-level packaging of microelectromechanical systems (MEMS). However, TGVs are challenging to realize because via holes in glass typically do not have a sufficiently high-quality sidewall profile for super-conformal electroplating of metal into the via holes. To overcome this problem, we demonstrate here that the via holes can instead be filled by magnetically assembling metal wires into them. This method was used to produce TGVs with a typical resistance of $64~ \text {m} \Omega$ , which is comparable with other metal TGV types reported in the literature. In contrast to many TGV designs with a hollow center, the proposed TGVs can be more area efficient by allowing solder bump placement directly on top of the TGVs, which was demonstrated here using solder-paste jetting. The magnetic assembly process can be parallelized using an assembly robot, which was found to provide an opportunity for increased wafer-scale assembly speed. The aforementioned qualities of the magnetically assembled TGVs allow the realization of glass interposers and MEMS packages in different thicknesses without the drawbacks associated with the current TGV fabrication methods.
Insights into the nature of female sexuality from the perspective of female stroke survivors

Abstract Aim: The purpose of this study was to provide insights into the nature of female sexuality from the perspective of one group of women following a stroke. Method: Nine female stroke survivors from metropolitan and surrounding districts of Sydney, Australia participated in face to face semi-structured interviews about sexuality after stroke. The age of stroke survivors ranged from 31 to 70 years. The majority of females identified as heterosexual (n = 8). Length of time between stroke and interview ranged from 1 year, 2 months to 15 years, 9 months. The interviews were digitally recorded and transcribed. Braun and Clarke’s 6 steps of thematic analysis were used to answer the question: what is the nature of female sexuality? Results: The women in this study saw themselves as sexual beings and communicated a tacit knowledge of the nature of female sexuality. Female sexuality was described as having two distinct, but related aspects, that captured “the being” and “the doing” of female sexuality. These encompassed a woman’s way of being female and expressions of that way of being through engagement in specific activities. Conclusions: The findings of this study underline the importance of addressing sexuality as part of rehabilitation and provide some guidance about what might be important to address. Implications for Rehabilitation Sexuality should be addressed by clinicians as part of person-centred rehabilitation. Understanding “the being” and “the doing” of female sexuality is a pre-requisite for understanding female sexuality post-stroke. Idealised constructions of being female formulated pre-stroke may continue to be points of reference for self-assessment post-stroke, hence need to be understood when seeking to support a positive sense of self. The influence of significant others on the self-esteem of females may be important to consider for some individuals post-stroke.
Fast Wideband Scattering Analysis Based on IE-ODDM and Cubic Polynomial Inter/Extrapolation

A fast wideband electromagnetic scattering analysis method based on the overlapped domain decomposition method for integral equation (IE-ODDM) and cubic polynomial inter/extrapolation is proposed. During the frequency sweeping process, the impedance matrix is fast generated by a cubic polynomial inter/extrapolation method. In order to reduce the memory requirement, IE-ODDM is implemented for the analysis of electrically large problems. Numerical example is provided to demonstrate the validity and efficiency of the proposed method.
Effects of Circuit Training According to the Feedback Type on Psychological and Physical Health of Workers with Social Anxiety Disorder

Background: The effects of circuit training was investigated according to the feedback type on the psychological (social anxiety, anxiety, positive emotion) health and physical (body composition, physical fitness) health of social anxiety disorder workers. Methods: Sixty male workers in H Company in Seoul, South Korea with social anxiety disorder were divided into four groups (positive, negative, mixed, no feedback) by conducting a circuit training program in sport center of H company during 3 times per week, total 8 weeks from Feb 1st to Mar 31st, 2017. The results of the pre-test and post-test were analyzed as follows. Results: 1) In effect of social anxiety, there were significant differences in the positive, negative, and mixed feedback groups. 2) In the effect of anxiety, there were significant differences in the positive, negative, and mixed feedback groups. 3) In the effect of positive emotion, there were significant differences in the positive, negative, mixed, and no feedback groups. 4) In the effect of body composition, body fat mass and body fat percentage have significant differences in the positive, negative, mixed, and no feedback groups. And fat free mass has significant differences in the positive and mixed feedback groups. 5) In the effect of physical fitness, grip strength, wall squat, bending forward have significant differences in positive, negative, mixed, and no feedback groups. Conclusion: The circuit training program improves the social anxiety disorder and positively affects the psychological health and physical health of participants. To participate in continuous exercise, personal training should be accompanied by the correct feedback of the leader.
Performance Analysis of LP Residual and Correlation Coefficients based Speech Seperation Front End

Performance of modern automatic speech recognition systems can be enhanced either at the front end by, speech separation system or by a set of efficient features or by a powerful classifier at the backend. A speech separation front end is built using average zero crossing rate, log energy, correlation coefficient of LP residual for separating the speech frames from AWGN samples. The experimental results on TIMIT database demonstrates that the proposed speech separation system performs well over the AWGN of various SNR levels.
Molecular identification of clinical isolates of Fusarium in Colombia.

OBJECTIVE Identifying Fusarium isolates from mycosis symptomatic patients through molecular techniques as PCR and sequencing. METHODS In this study, samples were taken from 101 mycosis symptomatic patients in-between 2004-2006. To determine isolates belonging to the Fusarium genus, the DNAr 28S region was amplified through PCR and specific PCR primers further confirmed their identity to the species level. Additionally, in order to confirm the identity of the species of the isolates, 75 isolates of these were analyzed by partial sequencing of the 28S rDNA and the TEF1-α gene. RESULTS The 28S rDNA portion detected all 101 isolates as belonging to Fusarium and the PCR specific primers detected 52 and 29 isolates as F. oxysporum and F. solani, respectively; 34 and 41 of these, afterwards studied by partial sequencing of the 28S rDNA and TEF1- α genes respectively, were effectively identified by the technique. CONCLUSION From all the molecular markers used to identify Fusarium isolates, the sequence of the TEF1-α gene provided the best resolution in the identification of species level; however it is possible to discriminate between F. oxysporum and F. solani isolates by PCR, in most of the cases, what is important considering the simplicity of the technique and a faster diagnosis.
Single-Phase Multicell AC–DC Converter With Optimized Controller and Passive Filter Parameters

This paper presents a novel single-phase multicell converter for ac–dc power conversion, which is formed by a series connection of several full-bridge converter stages through passive components. The proposed topology employs a simple control scheme based on the carrier-based sinusoidal pulsewidth modulation technique. Detailed design procedure of the passive filter components are analyzed and discussed. An efficient optimization method based on a differential evolution algorithm is utilized to optimize the filter parameters. Considering the filter structure, active damping is introduced in the control scheme to improve the stability of the overall system, which is later verified by experiments. The systematic design approach of the controller parameter is also highlighted, focusing a specific set of goals. Experimental results for a 1-kW prototype are presented to further validate the concept.
Modeling and Control of a Tailsitter UAV

Unconventional UAVs are being proposed to combine the benefits of fixed-wing and rotary-wing aircraft. Among these are tailsitter aircraft, which are fixed-wing aircraft with vertical landing capability. In this work, we present the development of a real-time simulation of a commercial radio-controlled tailsitter aircraft, along with a single controller that is capable of executing vertical takeoff, level flight, and vertical landing. The model accounts for progressive stall, the effect of large control surface deflections, as well as the drag generated by the aircraft's structural components. The thruster model accounts for changes in battery voltage, inflow velocity, and predicts slipstream effects. A ground contact model is also implemented to allow simulation of the takeoff and landing phases. A cascaded quaternion-based controller is then implemented in this simulated environment to control the tailsitter in a typical flight mission, with promising results. The transition from level flight to hover proves to be the most challenging aspect in the control of this aircraft.
The Curtius Rearrangement: Applications in Modern Drug Discovery and Medicinal Chemistry

The Curtius rearrangement is the thermal decomposition of an acyl azide derived from carboxylic acid to produce an isocyanate as the initial product. The isocyanate can undergo further reactions to provide amines and their derivatives. Due to its tolerance for a large variety of functional groups and complete retention of stereochemistry during rearrangement, the Curtius rearrangement has been used in the synthesis of a wide variety of medicinal agents with amines and amine‐derived functional groups such as ureas and urethanes. The current review outlines various applications of the Curtius rearrangement in drug discovery and medicinal chemistry. In particular, the review highlights some widely used rearrangement methods, syntheses of some key agents for popular drug targets and FDA‐approved drugs. In addition, the review highlights applications of the Curtius rearrangement in continuous‐flow protocols for the scale‐up of active pharmaceutical ingredients.
The effect of outdoor air pollution on the risk of hospitalisation for bronchiolitis in infants: a systematic review

Objective To systematically review the evidence around the effect of ambient levels of particulate and gaseous pollutants, and the risk of hospitalisation with bronchiolitis for infants under two years of age. Design Systematic review of observational epidemiological studies including cohort, time series, case crossover and case control study designs. Data sources Medline, Scopus, and Web of Science searched to November 2017 with no language restrictions. Eligibility criteria Studies investigating impact of air pollution levels on particulate pollutants (diameter <2.5 μm (PM2.5) or <10 μm (PM10) and gaseous pollutants (nitrogen dioxide (NO2), sulphur dioxide (SO2), carbon monoxide (CO), ozone (O3)) on hospital admission for bronchiolitis. Main outcome measure Risk of hospitalisation from bronchiolitis. Results Eight studies were eligible for review. Long term exposure to PM2.5 may be associated with increased risk of hospitalisation for bronchiolitis. SO2 may also be associated with hospitalisation, but results for other pollutants are inconsistent between studies. In three of the five studies that showed a positive association between air pollutants and hospitalisation, measured concentrations were below World Health Organization (WHO) recommended levels. Conclusions Certain particulate and gaseous pollutants may have a clinically relevant effect on hospital admissions for bronchiolitis in children below age two years old. Large cohort or time series studies are needed to examine this possible association. Protocol The protocol can be found at PROSPERO (CRD42017080643).
A general channel model for visible light communications in underground mines

In underground mines, visible light communication (VLC) system is a promising method to realize effective communication, which supports communication and illumination at the same time. Therefore, adequate research of underlying physical propagation phenomenon should be carried out to realize VLC system in underground mines. To design VLC system and evaluate its performance, accurate and efficient channel models, including large-scale fading and scattering characteristics, are needed to be established. However, the characteristics of the underlying VLC channels about fading and scattering have not been sufficiently investigated yet. In this paper, a path loss channel model, based on the recursive model, is proposed precisely. Its path loss exponent is determined by three different trajectories, which is studied in the mining roadway and working face environment. Besides, the shadowing effect for VLC has been modelled by a Bimodal Gaussian distribution in underground mines. Considering the number of transmitters in line-of-sight (LoS) as well as non-line-of-sight (NLoS) scenarios, our simulation illustrates the fact that, as the curve fitting technique is employed, the path loss displays a linear behavior in log-domain. The path loss expression is derived, it is related to the distance. Finally, root mean square (RMS) delay spread and Mie scattering in underground mines are analyzed.
Joint Optimization of Rate, Distortion, and Maximum Absolute Error for Compression of Medical Volumes Using HEVC Intra

Many visual quality metrics are used to measure the quality of lossy compressed images and videos, and are integrated in the rate-distortion optimization of hybrid video codecs. However, most of the metrics focus on the average objective quality in a picture. In certain applications, like medical image processing, the maximum absolute error should be more weighted. In this paper, the rate-distortion optimization of HEVC is extended by integrating this error metric. Thus, rate, average error, and maximum absolute error are jointly optimized. Furthermore, a weighting factor α is included into the calculation of the optimization for balancing the ratio between average and maximum absolute error. For HEVC intra with $\alpha =0.25$ an average maximum absolute error reduction of −25.63 can be achieved, while the bitrate increases slightly by 0.59%. Furthermore, the visual quality of the medical volumes improves and the data fidelity increases, i.e. less block artifacts appear and less structure disappear.
A Risk-aware Path Planning Method for Unmanned Aerial Vehicles

This paper proposes a risk-aware path planning method for Unmanned Aerial Vehicles, with the aim to generate safe flight paths minimizing the risk to the population. The proposed approach consists of two phases: first, an off-line path planning computes the optimal global path in a static environment considering the risk; then, taking into account a dynamic risk-map, an on-line path planning adjusts and adapts the off-line path. The risk-map is a location-based map, in which each cell represents a specific location with an associated risk-cost.The off-line path planning is performed by the riskA* algorithm. It is based on the well-known A* algorithm, enhanced considering the minimization of the risk-cost. The off-line path planning is executed in a static environment and it has no time constraints. On the contrary, the on-line path planning needs to adapt the path in a short time, thus a fast response constitutes a critical design parameter. The on-line path planning is performed by a novel algorithm, called Borderland. Borderland uses a check and repair routine, then it identifies and adjusts only the portions of path involved by changes in the dynamic risk-map. Simulation results corroborate the validity of our approach.
Parkinson's Disease Diagnosis via Joint Learning From Multiple Modalities and Relations

Parkinson's disease (PD) is a neurodegenerative progressive disease that mainly affects the motor systems of patients. To slow this disease deterioration, early and accurate diagnosis of PD is an effective way, which alleviates mental and physical sufferings by clinical intervention. In this paper, we propose a joint regression and classification framework for PD diagnosis via magnetic resonance and diffusion tensor imaging data. Specifically, we devise a unified multitask feature selection model to explore multiple relationships among features, samples, and clinical scores. We regress four clinical variables of depression, sleep, olfaction, cognition scores, as well as perform the classification of PD disease from the multimodal data. The multitask model explores the relationships at the level of clinical scores, image features, and subjects, to select the most informative and diseased-related features for diagnosis. The proposed method is evaluated on the public Parkinson's progression markers initiative dataset. The extensive experimental results show that the multitask framework can effectively boost the performance of regression and classification and outperforms other state-of-the-art methods. The computerized predictions of clinical scores and label for PD diagnosis may offer quantitative reference for decision support as well.