Miracle-dz/UniFAR-FTUs huggingface dataset:
Impedance Network Modeling and Quantitative Stability Analysis of Sub-/Super-Synchronous Oscillations for Large-Scale Wind Power Systems

Recently, emerging sub-/super-synchronous oscillation (SSO) issues occurred in large-scale wind power systems, which are caused by the interactions between the power electronic converter based-wind turbine generators (WTGs) and the ac/dc grids. In previous studies, the practical system is usually simplified to equivalent system models, which consist of a (several) large-capacity WTGs connected to a radial equivalent line. However, such equivalent models can hardly represent the dynamics of the practical large-scale wind systems. Besides, the impacts on SSO characteristics from such important factors as network topology, steam turbine generators, and high-voltage direct currents have not been clarified yet. To deal with these challenges, this paper proposes a systematic impedance network modeling and quantitative stability analysis method. All system components of the large-scale wind systems are represented with impedance models (IMs) in a unified reference frame, and then, they are interconnected based on the system topology to form the impedance network model (INM) of the whole system. With the INM reduced to an aggregated IM, a stability criterion is developed to assess SSO stability just by analyzing the frequency characteristics of the determinant of the aggregated IM, and a quantitative analysis method is proposed to quantify the damping, frequency, and sensitivity of the SSO mode. The electromagnetic transient simulations on a practical wind system, which suffered actual SSO issues, have validated the effectiveness and accuracy of the proposed method. This paper also conducts comparative analysis on four types of popular stability analysis methods to show the advantages of the proposed method.
Inverted E-Shaped Wearable Textile Antenna for Medical Applications

A miniaturized textile antenna is designed and demonstrated for ISM band applications at 2.4 GHz. The proposed antenna uses appropriate loading of a rectangular slot/notch with a strip line inserted to form an inverted E-shaped antenna. The structure is simple, compact, and easy to manufacture using only fabric material. The antenna size is 75% smaller than a conventional antenna. When the antenna is subjected to bending, its performance proves sustainable under deformation. Each slot/notch and strip line is translated to its equivalent circuit and then integrated to form the whole equivalent circuit of the proposed antenna. The results from the equivalent circuits and simulation show acceptable agreement. The antenna shows an improvement of size miniaturization of $30 \times 20 \times 0.7$ mm3 and demonstrates an impedance bandwidth of 15% and efficiency of 79%, showing that it is a promising candidate for incorporation into wearable systems.
Comparison of the Absorb bioresorbable vascular scaffold to the Xience durable polymer everolimus-eluting metallic stent in routine clinical practice: a propensity score-matched analysis from a multicenter registry

Introduction Most clinical trials related to bioresorbable vascular scaffold (BVS) technology are limited to a highly selected patient population. Aim To evaluate early and long-term clinical outcomes of the Absorb everolimus-eluting BVS compared to the everolimus-eluting metallic XIENCE V stent in routine clinical practice. Material and methods This is a multicenter, retrospective propensity score-matched comparative study, comprising 76 patients treated with a bare metal stents (BMS) and 501 with a XIENCE stent. Patients included in the study had stable and unstable angina and both types of myocardial infarction (STEMI and NSTEMI) as an indication for intervention and at least one significant de novo lesion in native coronary arteries. The primary endpoint was major adverse cardiovascular event (MACE), defined as death, myocardial infarction (MI), or target vessel revascularization (TVR). Results Median follow-up was 400 days in both groups. After propensity score matching for patient baseline characteristics, only higher rate of predilatation, predominantly treated left anterior descending artery (LAD) and lower number of used stents in the BVS group remained statistically significant. After adjustment there was no difference in type of treated lesions. The MACE rate did not differ between BVS and drug-eluting stents (DES) groups (7.2% vs. 11.15%, respectively; p = 0.17). The TVR was 2.9% in both groups. Except in the periprocedural period, there were no deaths or MI in the BVS group. There was no stent thrombosis in either studied group. Conclusions In routine clinical practice throughout long-term follow-up, clinical outcomes of patients who successfully received the Absorb BVS did not differ from those of patients who received the Xience stent. Longer follow-up data are required to determine whether these findings will persist beyond one year.
Mapping-Varied Spatial Modulation for Physical Layer Security: Transmission Strategy and Secrecy Rate

In this paper, a novel transmission strategy, referred to as mapping-varied spatial modulation, is proposed for physical layer security, where the transmitter varies mapping patterns for the radiated information and the antenna information of spatial modulation, based on the instantaneous pattern of legitimate channel quality information that is unknown to eavesdroppers. Therefore, eavesdroppers cannot successfully decode the confidential information and the transmission over the legitimate link is secured from the wire-tap of eavesdroppers, without relying on higher-layer encryption. An important virtue of the proposed transmission strategy is that the transmitter does not need to know eavesdroppers’ channels states at all. To further demonstrate the advantage of this scheme, its secrecy rate was formulated for the purpose of facilitating the performance evaluation. Moreover, illustrative numerical results pertaining to the metrics of ergodic secrecy rate and secrecy outage probability not only substantiate the validity of the proposed transmission strategy, but also provide useful references for the system design with the mapping-varied spatial modulation, from the view of physical layer security.
Contractions in the Isolated Uterus of a Rat Model of Polycystic Ovary Syndrome Compared to Controls in Adulthood

Background Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women during the reproductive age. Considering disorders reported in women with PCOS, e.g. infertility, pregnancy complications (premature delivery, caesarean section and spontaneous miscarriages), and hormonal disorders, we hypothesized that uterine contractions in PCOS rats may be different from controls. We aimed to compare uterine contractions in PCOS rats with controls. Methods Rats in the experimental group were subcutaneously injected with 5 mg of free testosterone on gestational day 20, while controls received solvent. The contractions of isolated uterus in offspring of both groups were recorded by the power lab system, after exposure to carbachol and oxytocin. Two-way analysis of variance was used to compare results between 2 groups. Results PCOS rats showed more irregular uterine contractions compared to controls. After exposure to carbachol, frequency, and resting tone in the PCOS rats were significantly increased compared to controls (P = 0.004, P = 0.02, respectively). After exposure to oxytocin, the frequency, resting tone and amplitude of rhythmic contractions did not differ between the 2 groups. Conclusions Our study indicates irregular uterine contractions and different mechanical responses of isolated uterus in PCOS rats compared to controls.
The Role of Autobiographical Story-Telling During Rehabilitation Among Hip-Fracture Geriatric Patients

Hip fracture is one of the most common health care problems among elderly people. Literature shows that high self-efficacy expectations and positive affect are some of the key issues in functional recovery after hip fracture. The present investigation tested whether self-narration of such life-breaking event influences self-efficacy and depression during the process of rehabilitation. We designed a Self-Narration Journey (SNJ) to be administered during the in-hospital rehabilitation. In Study 1, we investigated the influence of SNJ on depression and perceived self-efficacy. Study 2 aimed to explore the effect of SNJ, depression, and self-efficacy on functional recovery of independence to perform daily activities during the rehabilitation process. The data showed that the Self-Narration Journey proved effective in increasing the perceived self-efficacy and in lowering the level of depression. The present work highlights a significant effect of the SNJ on the functional recovery process.
Comparison of Two Hyperparameter-Free Sparse Signal Processing Methods for Direction-of-Arrival Tracking in the HF97 Ocean Acoustic Experiment

In this paper, we review and compare the performance of two recently introduced hyperparameter-free sparse signal processing methods namely, the sparse iterative covariance-based estimation method and the sparse Bayesian learning-based relevance vector machine method, for direction-of-arrival (DOA) tracking of multiple signals using an array of sensors. The methods are presented to the readers, in a tutorial style for easy understanding. Hyperparameter-free sparsity-based methods are attractive in practice since tuning of regularization parameters (hyperparameters) is not necessary as they are automatically estimated from the data. The DOA tracking problem is formulated as a snapshot-by-snapshot estimation problem and the implementation of the methods are discussed in detail. A simulation study using a uniform-linear-array is carried out to evaluate the performance of the methods in terms of the root-mean-squared error of the DOA estimates and the probability of resolution with the goal of determining when one is to be preferred over the other. The algorithms are also applied on passive sonar data from the 1997 High-Frequency (HF$\mathbf {97}$) ocean acoustic experiment to demonstrate their usability in a real underwater scenario, as well as their robustness to the modeling assumptions made. We draw new conclusions about the main features of these methods that are important to the underwater acoustic practitioners.
Inclination sensor based on FBG with enhanced sensitivity

The Brazilian mining disaster, which occurred in 2015 in the city of Mariana, released millions of tons of toxic mud and has caused destruction across a vast area from the mountains of Minas Gerais to the Atlantic Ocean. Preventing such accidents demands a real-time, continuous monitoring sensor system capable of detecting dangerous soil displacement. In this paper, we present a temperature-independent, modular inclinometer based on a fiber Bragg grating (FBG) array for the detection of soil displacement. The proposed sensor array is based on a modular topology, in which each module is composed of a pair of FBG sensors bonded to the opposite sides of a steel cantilever holding a known weight. When the system is inclined, the gravitational force acts on the weight, pushing the cantilever to a bending position. Furthermore, since the measurements are wavelength-encoded, the proposed sensor does not suffer from light source intensity fluctuations. Our prototype was tested in laboratory with inclinations ranging from 0 ° to 40 ° with a resolution of ± 0.025 ° and very good repeatability, indicating that the proposed system is feasible and can be applied to the precise and fast detection of soil displacements.
An easy solution to use external sensors in Android: Experimental characterization

Nowadays smartphones and tablets are pervasive in our lives, and are used to fulfil several of our daily tasks. One approach is their usage as sensory systems; by exploiting their embedded sensors, it is possible to get data about users. Typically, such sensors are high end, and it is relatively easy to use them by means of Applications. Data access is handled by Android, which decreases sensor performance, as sampling rate, but greatly eases fruition of such information. On the other hand, many useful sensors are available, today, only externally from the smartphone; typically, they can be connected by Bluetooth Low Energy, a widespread standard for Internet of Things. However, this task is cumbersome for a lot of reasons, e.g. the fact that external sensors can be manufactured by different producers with their own proprietary software approach and solutions. The SAndroidE framework allows an easy connection to external sensors/development kits, managing them and their data as if they were embedded in the smartdevice. This work proposes an experimental characterization of measurements by external sensors, highlighting possibilities and limits of the proposed solution, even in complex scenarios.
Tuning Fiber Bragg Gratings by Deformable Slides

Fiber gratings are key photonic elements having broad applications. Development of tunable fiber grating devices can provide a tunable “all-fiber” platform with extended applications. In this paper, we describe a novel deformable slide tuning technique that can achieve a large tuning range and a reliable tuning process. Fiber Bragg gratings at wavelength band of 1550, 1060, and 2000 nm have been tested, and shown to achieve around 50-nm tuning range of the center wavelength. Long-term stability is evaluated at better than 0.08 nm for a 1550-nm fiber Bragg grating tuned at 30-nm position. The tuning mechanism can also be configured for tuning the refractive index perturbation profile of the fiber grating, demonstrating that a regular fiber Bragg grating can be tuned to a purely phase-sampled fiber Bragg grating. By employing tunable fiber Bragg gratings, tunable fiber lasers can be built in a very compact and robust “all-fiber” configuration without a free-space optical path in the laser cavity, which is experimentally demonstrated in Er, Yb, and Tm doped fiber lasers.
Defect detection in plain weave fabrics by yarn tracking and fully convolutional networks

Weaving is a highly automated industrial process. Due to small inaccuracies during the production process, different types of weave defects can occur, by which the quality of the produced fabric is heavily impaired. The defects can diminish the selling price by up to 50%. Current automated visual defect detection systems need to be adjusted by a trained operator to every new fabric, making them impractical for industrial use. We present a novel automated visual defect detection framework which localizes and tracks yarns in new and unseen fabrics without the need for tedious settings, and which consecutively detects anomalies. The detection of weave defects is based on three consecutive steps, (1) the identification of single weft and warp float-points with fully convolutional networks, (2) the tracking of single yarns based on a set of rules, and finally (3) the recognition of defects using statistical analysis.
Association of PTPN22 gene polymorphism with non-segmental vitiligo in South Indian Tamils

Introduction Non-segmental vitiligo (NSV) is a depigmentation skin disease with loss of melanocytes in the skin. Aim To evaluate whether the protein tyrosine phosphatase non-receptor type (PTPN22) single nucleotide polymorphism at +1858C/T had any association with non-segmental vitiligo in South Indian Tamils. Material and methods Genomic DNA was extracted using the phenol-chloroform method, and PTPN22 +1858C/T polymorphism was assayed by Taqman 5’allele discrimination assay. Protein levels were quantified by ELISA. Results We found that the allelic frequency of variants of PTPN22 (rs2476601) were significantly different between controls and cases showing a vitiligo risk in the South Indian Tamil population. PTPN22 levels were higher in the heterozygous CT genotype in NSV, when compared with that of the major variant CC genotype of rs2476601. Conclusions This study suggests that the heterozygous CT genotype, of the PTPN22 SNP rs2476601, has a strong risk association with non-segmental vitiligo in South Indian Tamils.
3DmFV: Three-Dimensional Point Cloud Classification in Real-Time Using Convolutional Neural Networks

Modern robotic systems are often equipped with a direct three-dimensional (3-D) data acquisition device, e.g., LiDAR, which provides a rich 3-D point cloud representation of the surroundings. This representation is commonly used for obstacle avoidance and mapping. Here, we propose a new approach for using point clouds for another critical robotic capability, semantic understanding of the environment (i.e., object classification). Convolutional neural networks (CNNs), that perform extremely well for object classification in 2-D images, are not easily extendible to 3-D point clouds analysis. It is not straightforward due to point clouds’ irregular format and a varying number of points. The common solution of transforming the point cloud data into a 3-D voxel grid needs to address severe accuracy versus memory size tradeoffs. In this letter, we propose a novel, intuitively interpretable, 3-D point cloud representation called 3-D modified Fisher vectors. Our representation is hybrid as it combines a coarse discrete grid structure with continuous generalized Fisher vectors. Using the grid enables us to design a new CNN architecture for real-time point cloud classification. In a series of performance analysis experiments, we demonstrate competitive results or even better than state of the art on challenging benchmark datasets while maintaining robustness to various data corruptions.
Optimization or Alignment: Secure Primary Transmission Assisted by Secondary Networks

Security is a challenging issue for cognitive radio (CR) to be used in future 5G mobile systems. Conventionally, interference will degrade the performance of a primary user (PU) when the spectrum is shared with secondary users (SUs). However, when properly designed, SUs can serve as friendly jammers to guarantee the secure transmission of PU. Thus, in this paper, we propose two schemes to improve the sum rate of SUs while guaranteeing the secrecy rate of PU. In the first scheme, the secondary transceivers are jointly designed to maximize their sum rate while satisfying a threshold on the PU’s secrecy rate. Due to the non-convex nature, it is first converted into a convex one and then, an alternating optimization algorithm based on the second-order cone programming is proposed to solve it. In the second scheme, the principle of interference alignment is employed to eliminate interference from PU and other SUs at each secondary receiver, and the interference from SUs is zero-forced at the primary receiver. Thus, interference-free transmission can be performed by the legitimate CR network, with eavesdropping towards PU disrupted by SUs. The key features and performances of the two proposed schemes are also compared. Finally, simulation results are presented to verify the effectiveness of the two proposed schemes for secure CR networks.
Robust Long-Term Registration of UAV Images of Crop Fields for Precision Agriculture

Continuous crop monitoring is an important aspect of precision agriculture and requires the registration of sensor data over longer periods of time. Often, fields are monitored using cameras mounted on unmanned aerial vehicles (UAVs) but strong changes in the visual appearance of the growing crops and the field itself poses serious challenges to conventional image registration methods. In this letter, we present a method for registering images of agricultural fields taken by an UAV over the crop season and present a complete pipeline for computing temporally aligned three-dimensional (3-D) point clouds of the field. Our approach exploits the inherent geometry of the crop arrangement in the field, which remains mostly static over time. This allows us to register the images even in the presence of strong visual changes. To this end, we propose a scale invariant, geometric feature descriptor that encodes the local plant arrangement geometry. The experiments suggest that we are able to register images taken over the crop season, including situations where matching with an off-the-shelf visual descriptor fails. We evaluate the accuracy of our matching system with respect to manually labeled ground truth. We furthermore illustrate that the reconstructed 3-D models are qualitatively correct and the registration results allow for monitoring growth parameters at a per plant level.
Demographic and medical factors affecting short-term changes in subjective evaluation of asthma control in adolescents

Introduction Asthma control is an important measure of disease stabilization, which is linked to the treatment and lifestyle recommendations. Aim To assess the impact of selected factors on asthma control in adolescents, as assessed using the Asthma Control Test (ACT™). Material and methods The prospective study included 100 asthma patients aged between 12 and 19. Asthma was assessed in three consecutive follow-up visits spaced 3 months apart, using the standardized ACT™ questionnaire. Results Asthma was fully controlled (ACT score = 25 points) in more than half of the patients in all follow-up visits (53.0%, 54.0%, and 56.0%, respectively). More than one third of the participants scored between 20 and 24 points (37.0% vs. 39.0% vs. 40.0%). A minority of patients had uncontrolled asthma (scores below 20), and the group consistently diminished in subsequent visits (10% vs. 7% vs. 4%). Uncontrolled asthma was found significantly more often in female patients (33.33%; p < 0.001) and those living in rural areas (20.59%; p < 0.01). Treatment with a combination of inhaled corticosteroids (ICS) and LABAs was associated with worse asthma control (14.81%; p < 0.05). Better asthma control was found in patients with a family history of allergies (73.85% vs. 75.38% vs. 78.46%; p < 0.001) and in those with concurrent allergies (66.67% vs. 68.00% vs. 70.67%; p < 0.001). Conclusions Asthma control in adolescents differs by sex and residence. Concurrent allergies and family history of allergies improve asthma self-control in adolescents.
A Non-Stationary Geometry-Based Scattering Vehicle-to-Vehicle MIMO Channel Model

In this study, a non-wide-sense stationary geometry-based model that includes both static and mobile scatterers for vehicle-to-vehicle multiple-input multiple-output Ricean fading channels is presented. The proposed channel introduces a two-circle model to describe static vehicles (i.e., around the mobile transmitter (MT) and mobile receiver (MR)) and an ellipse model to depict stationary roadside environments. The relative movement between the MT and MR results in time-variant geometric statistics that make our model non-stationary. Furthermore, the impacts of moving properties of mobile scatterers on the channel statistics are first investigated in the proposed model. Finally, numerical results show that the proposed channel statistics are very close to the prior results, thereby demonstrating the utility of our channel model.