Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Magnetic Scalar Hysteresis Lump Model Based on Jiles–Atherton Quasi-Static Hysteresis Model Extended With Dynamic Fractional Derivative Contribution

Accurate and simple magnetic material law is necessary to correctly model the complete electromagnetic systems. In this paper, a new formulation based on the scalar quasi-static hysteresis Jiles–Atherton model extended to dynamic behavior using fractional derivative dynamic contribution is proposed. The fractional contribution is solved using convolution which highly reduces the numerical issues. The order of the fractional derivation provides a new degree of freedom and allows obtaining correct simulation results on a very large frequency bandwidth. By using such a formulation, high-memory and time-consuming space discretization techniques (finite differences and finite elements) are avoided while keeping the global accurate simulation results.
Spatio-Temporal Distribution of Negative Emotions in New York City After a Natural Disaster as Seen in Social Media

Disasters have substantial consequences for population mental health. We used Twitter to (1) extract negative emotions indicating discomfort in New York City (NYC) before, during, and after Superstorm Sandy in 2012. We further aimed to (2) identify whether pre- or peri-disaster discomfort were associated with peri- or post-disaster discomfort, respectively, and to (3) assess geographic variation in discomfort across NYC census tracts over time. Our sample consisted of 1,018,140 geo-located tweets that were analyzed with an advanced sentiment analysis called ”Extracting the Meaning Of Terse Information in a Visualization of Emotion” (EMOTIVE). We calculated discomfort rates for 2137 NYC census tracts, applied spatial regimes regression to find associations of discomfort, and used Moran’s I for spatial cluster detection across NYC boroughs over time. We found increased discomfort, that is, bundled negative emotions after the storm as compared to during the storm. Furthermore, pre- and peri-disaster discomfort was positively associated with post-disaster discomfort; however, this association was different across boroughs, with significant associations only in Manhattan, the Bronx, and Queens. In addition, rates were most prominently spatially clustered in Staten Island lasting pre- to post-disaster. This is the first study that determined significant associations of negative emotional responses found in social media posts over space and time in the context of a natural disaster, which may guide us in identifying those areas and populations mostly in need for care.
Breathing and Coughing: The Extraordinarily High Degassing of Popocatépetl Volcano Investigated With an SO2 Camera

How do lava domes release volcanic gases? Studying this problem is crucial to understand, and potentially anticipate, the generation of the sudden and dangerous explosive eruptions that frequently accompany dome extrusions. Since its awakening in 1994, Popocatepetl volcano has produced more than fifty lava domes and has been consistently among the strongest permanent emitters of volcanic gases. In this work, we have characterized the passive and explosive degassing between 2013 and 2016 at a high time resolution using an SO2 camera, to achieve a better understanding of the conduit processes. Our 4-year average SO2 flux is 45 kg/s, in line with the long-term average of the whole current eruptive period. We show that Popocatepetl volcano is essentially an open system and that passive degassing, i.e. degassing with no associated emission of lava or ash, dominates >95% of the time. This passive degassing is continuous and sustained, whether the crater contains a lava dome or not. It shows most of the time a strong periodic component, with a pseudo-period of ~5 minutes, and amplitudes of 30 to 60% of the average value. We could distinguish two types of explosions based on their SO2 flux patterns. The first type (E1) occurs in the middle of the normal passive degassing and is followed by a rapid return of the SO2 flux down to its pre-explosive level. The second type (E2), which corresponds to the strongest events, is anticipated by a rapid decrease of the SO2 flux to abnormally low values and is followed by a return to its normal values. The E2 explosions are probably caused by the accumulation of gas below a rapidly compacting permeable dome. We suggest that transient episodes of gravitational compaction of the usually permeable dome and the upper conduit is the only mechanism that is fast enough to explain the sharp decrease of the SO2 flux that anticipates the E2 explosions. Our model is potentially applicable to a large number of andesitic volcanoes that undergo passive degassing interspersed with short-lived explosions.
Deriving YouTube Playout Phases from Encrypted Packet Level Traffic

From the point of view of telecommunication providers, video streaming is one of the most demanding applications in today's Internet. Over 73% of the total global network traffic has been attributed to video streaming applications in 2017. In this work, we provide a first step towards a better understanding of the packet level behavior of video streaming traffic to enable more efficient traffic engineering in the future. We perform a measurement study with the popular video streaming platform YouTube and show that the different playout phases of a video streaming session can not only be observed by evaluating application layer metrics, but also from raw and encrypted packet level traces.
Clues to recognition of fumarate hydratase‐deficient renal cell carcinoma: Findings from cytologic and limited biopsy samples

Fumarate hydratase (FH)‐deficient renal cell carcinoma (RCC) is rare and highly aggressive and is believed to arise mostly in the setting of hereditary leiomyomatosis‐RCC syndrome with a germline mutation of FH. Because of the aggressiveness of these tumors and a frequent lack of ascertainable family history, these tumors may first present as metastases and be sampled by cytology. The cytologic findings of FH‐deficient RCC have not previously been reported.
Factors associated with unsuccessful treatment outcome in tuberculosis patients among refugees and their surrounding communities in Gambella Regional State, Ethiopia

Background Tuberculosis (TB) is a leading cause of public health challenges among immigrant refugees and their surrounding communities in developing countries. Evaluating the treatment outcome of TB patients is one of the key indicators to understand the performance of TB control program. Hence, this study aims to assess profile, treatment outcome and factors associated with unsuccessful outcome of TB patients treated under the TB control program among refugees and their surrounding communities (SCs) in Gambella Regional State, Ethiopia. Methodology Retrospective study was conducted in the health facilities of refugee and their SCs in Gambella Regional State from March 1 to May 30, 2017. Demographic and related data of all TB patients registered in TB Control Program between September, 2008 and October, 2017 in health facilities of refugee and the SCs was extracted using data extraction format. Eight years trend of TB, treatment outcome and factors associated with unsuccessful outcome among refugees and the SCs were computed using SPSS version 20.0 software. Result A total of 886 refugees and 3284 SCs TB patients, registered for anti TB treatment in the last eight years, were evaluated in the study. The trend of all forms of TB is progressively increasing among refugees contrary to the SCs in the course of the study period (X2 trend = 207.7; P<0.0001). Smear positive pulmonary TB (PTB+) was found to be predominant (57.6%) TB form in refugees while smear negative pulmonary TB (PTB-) (44.8%) is in the SCs (X2 = 185.834; P<0.0001). There was also significant difference in the treatment outcome (X2 = 170.915; P<0.0001). Mean treatment success rate was 74.2% and 88.1% for refugees and the SCs, respectively (X2 = 92.887; P<0.0001). The study also revealed that the risk of unsuccessful TB treatment outcome was significantly higher among refugee (AOR = 2.17; 95% CI: 1.69–2.77), retreated cases (AOR = 1.53; 95% CI: 1.07–2.17), patients aged between 35–44 years (AOR = 1.38; 95% CI: 1.0–1.91), and greater than 44 years old (AOR = 1.77; 95% CI: 1.28–2.44), and patients with extra pulmonary TB (EPTB) form (AOR = 1.34; 95% CI: 1.04–1.73) compared to their counterparts. Patient coming from rural area (AOR = 0.77; 95% CI: 0.62–0.97), who are female (AOR = 0.76; 95% CI: 0.63–0.91) and TB/HIV non-infected (AOR = 0.63; 95% CI: 0.51–0.77) were more likely to be successfully treated. Conclusion The study confirmed that there was low treatment success rate among refugees compared to the SCs. Being refugee, retreated case, patient’s age ≥35 years old, EPTB form, gender, rural patient address and HIV status were predictor factors for unsuccessful treatment outcome. Hence, the study urges the need for strengthened TB prevention program among refugees with due consideration of identified predictor factors to prevent the potential effect of hosting refugee to the SCs and the nations at large.
UAV-Aided Secure Communications With Cooperative Jamming

This paper investigates unmanned aerial vehicle (UAV) enabled secure communication systems where a mobile UAV wishes to send confidential messages to multiple ground users. To improve the security performance, a cooperative UAV is additionally considered that transmits the jamming signal. In this system, we maximize the minimum secrecy rate among the ground users by jointly optimizing the trajectory and the transmit power of the UAVs as well as the user scheduling. To efficiently solve this nonconvex problem, we adopt block successive upper bound minimization techniques, which address a sequence of approximated convex problems for each block of variables. Numerical results verify that the proposed algorithm outperforms baseline methods.
Video Segmentation using Teacher-Student Adaptation in a Human Robot Interaction (HRI) Setting

—Video segmentation is a challenging task that has many applications in robotics. Learning segmentation from few examples on-line is important for robotics in unstructured environments. The total number of objects and their variation in the real world is intractable, but for a speciﬁc task the robot deals with a small subset. Our network is taught, by a human moving a hand-held object through different poses. A novel two-stream motion and appearance ”teacher” network provides pseudo-labels. These labels are used to adapt an appearance ”student” network. Segmentation can be used to support a variety of robot vision functionality, such as grasping or affordance segmentation. We propose different variants of motion adaptation training and extensively compare against the state-of-the-art methods. We collected a carefully designed dataset in the human robot interaction (HRI) setting. We denote our dataset as (L)ow-shot (O)bject (R)ecognition, (D)etection and (S)egmentation using HRI. Our dataset contains teaching videos of different hand-held objects moving in translation, scale and rotation. It contains kitchen manipulation tasks as well, performed by humans and robots. Our proposed method outperforms the state-of-the-art on DAVIS and FBMS with 7% and 1.2% in F-measure respectively. In our more challenging LORDS-HRI dataset, our approach achieves signiﬁcantly better performance with 46.7% and 24.2% relative improvement in mIoU over the baseline.
Frequency Analysis of Disturbance Torque Exerted on a Carriage Arm in Hard Disk Drives Using Hilbert–Huang Transform

In this paper, we applied the Hilbert–Huang transform (HHT) to the time series of the torque exerted on the carriage arm of a hard disk drive, which was calculated using the finite-element analysis. Then, a Fourier transform (FT) was implemented to perform frequency analysis; the results were subsequently compared with the HHT results. A comparison of both spectra revealed the superior ability of HHT to perform frequency analysis of flow phenomena via disturbance torque analysis. Furthermore, the HHT results confirmed that to achieve more precise head positioning, it is necessary to decrease torque fluctuations induced by the non-stationary phenomena that are not always observed in the power spectrum obtained via the FT analysis, such as vortex shedding around an arm.
Nuclear Integrity but Not Topology of Mouse Sperm Chromosome is Affected by Oxidative DNA Damage

Recent studies have revealed a well-defined higher order of chromosome architecture, named chromosome territories, in the human sperm nuclei. The purpose of this work was, first, to investigate the topology of a selected number of chromosomes in murine sperm; second, to evaluate whether sperm DNA damage has any consequence on chromosome architecture. Using fluorescence in situ hybridization, confocal microscopy, and 3D-reconstruction approaches we demonstrate that chromosome positioning in the mouse sperm nucleus is not random. Some chromosomes tend to occupy preferentially discrete positions, while others, such as chromosome 2 in the mouse sperm nucleus are less defined. Using a mouse transgenic model (Gpx5−/−) of sperm nuclear oxidation, we show that oxidative DNA damage does not disrupt chromosome organization. However, when looking at specific nuclear 3D-parameters, we observed that they were significantly affected in the transgenic sperm, compared to the wild-type. Mild reductive DNA challenge confirmed the fragility of the organization of the oxidized sperm nucleus, which may have unforeseen consequences during post-fertilization events. These data suggest that in addition to the sperm DNA fragmentation, which is already known to modify sperm nucleus organization, the more frequent and, to date, the less highly-regarded phenomenon of sperm DNA oxidation also affects sperm chromatin packaging.
Dual-Hop Mixed RF-UOW Communication System: A PHY Security Analysis

In this paper, the secrecy performance of a dual-hop mixed radio-frequency/underwater optical wireless communication (RF-UOWC) system is investigated. The considered system consists of one single antenna source node (<inline-formula> <tex-math notation="LaTeX">$S$ </tex-math></inline-formula>) communicating with one destination node (<inline-formula> <tex-math notation="LaTeX">$D$ </tex-math></inline-formula>), considered as the legitimate receiver, through an amplify-and-forward relay node equipped with multiple antennas for reception. Specifically, the relay receives the incoming signal from <inline-formula> <tex-math notation="LaTeX">$S$ </tex-math></inline-formula> via an RF link, applies maximal-ratio combining technique, amplifies the output combined signal with either a fixed gain or variable gain, and then forwards it to the destination via an UOWC link. The transmission protocol is performed under the eavesdropper’s attempt to overhear the RF link (i.e., <inline-formula> <tex-math notation="LaTeX">$S$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$R$ </tex-math></inline-formula>). We derive exact closed-form expressions for the system’s average secrecy capacity and the intercept probability in terms of Meijer’s <inline-formula> <tex-math notation="LaTeX">$G$ </tex-math></inline-formula>-function as well as the univariate and bivariate Fox’s <inline-formula> <tex-math notation="LaTeX">$H $ </tex-math></inline-formula>-functions. A complexity analysis is also performed to analyze the evaluation time of the derived analytical formulas as well as Monte Carlo simulation method complexity. Our derived analytical formulas present an efficient tool to depict the impact of some system and channel parameters on the secrecy performance, namely, the number of relay antennas, the number of eavesdropping nodes, relay gain, fading severity of RF links, and water turbulence severity of the UOWC link.
Prevalence of childhood asthma in US military and non-military families: Comparisons by rural–urban residence and geographic region

Objective We sought to determine variables associated with asthma among children from military and non-military families. Methods We performed secondary data analysis on the 2016 Behavioral Risk Factor Surveillance System. Parents with and without military experience (n = 61,079) were asked whether a child ever had asthma and currently has asthma. We used two multiple logistic regression models to determine the influence of rurality and geographic region on “ever” and “current” asthma in children of military and non-military families, while controlling for socio-demographic and behavioral variables. Results Overall childhood asthma prevalence for children in military families was lower than non-military families (ever, 9.7% vs. 12.9%; currently, 6.2% vs. 8.2%) in 2016. However, multiple logistic regression showed variation in “ever” and “current” asthma among children of military and non-military families by rurality and race. Discussion Developers of public health asthma interventions should consider targeting African-American children of military families living in urban areas. This population is approximately twice as likely to have asthma as Caucasian children of non-military families.
LadderNet: Multi-path networks based on U-Net for medical image segmentation

U-Net has been providing state-of-the-art performance in many medical image segmentation problems. Many modifications have been proposed for U-Net, such as attention U-Net, recurrent residual convolutional U-Net (R2-UNet), and U-Net with residual blocks or blocks with dense connections. However, all these modifications have an encoder-decoder structure with skip connections, and the number of paths for information flow is limited. We propose LadderNet in this paper, which can be viewed as a chain of multiple U-Nets. Instead of only one pair of encoder branch and decoder branch in U-Net, a LadderNet has multiple pairs of encoder-decoder branches, and has skip connections between every pair of adjacent decoder and decoder branches in each level. Inspired by the success of ResNet and R2-UNet, we use modified residual blocks where two convolutional layers in one block share the same weights. A LadderNet has more paths for information flow because of skip connections and residual blocks, and can be viewed as an ensemble of Fully Convolutional Networks (FCN). The equivalence to an ensemble of FCNs improves segmentation accuracy, while the shared weights within each residual block reduce parameter number. Semantic segmentation is essential for retinal disease detection. We tested LadderNet on two benchmark datasets for blood vessel segmentation in retinal images, and achieved superior performance over methods in the literature. The implementation is provided \url{this https URL}
Ectoparasitism and infections in the exoskeletons of large fossil cingulates

Studies on paleopathological alterations in fossil vertebrates, including damages caused by infections and ectoparasites, are important because they are potential sources of paleoecological information. Analyzing exoskeleton material (isolated osteoderms, carapace and caudal tube fragments) from fossil cingulates of the Brazilian Quaternary Megafauna, we identified damages that were attributed to attacks by fleas and dermic infections. The former were compatible with alterations produced by one species of flea of the genus Tunga, which generates well-delimited circular perforations with a patterned distribution along the carapace; the latter were attributable to pathogenic microorganisms, likely bacteria or fungi that removed the ornamentation of osteoderms and, in certain cases, generated craters or pittings. Certain bone alterations observed in this study represent the first record of flea attack and pitting in two species of large glyptodonts (Panochthus and Glyptotherium) and in a non-glyptodontid large cingulate (Pachyarmatherium) from the Quaternary of the Brazilian Intertropical Region. These new occurrences widen the geographic distribution of those diseases during the Cenozoic and provide more evidence for the co-evolutionary interaction between cingulates and parasites registered to date only for a small number of other extinct and extant species.
Optimal Fairness and Quality in Video Streaming with Multiple Users

With the majority of video distribution services relying on the HTTP adaptive streaming paradigm, a great deal of research is geared towards developing algorithms and solutions for improving user perceived quality while making efficient use of available resources. Our goal is to provide the means for benchmarking such solutions in the context of multiple users accessing Video on Demand content while sharing a bottleneck link. For that purpose, we propose a quadratic problem formulation to compute the theoretical optimum in terms of adaptation strategies and corresponding segment downloads across multiple users under given bandwidth constraints. By aiming to maximize both service quality and fairness, we quantify and compare the impact of different fairness objectives (bandwidth fairness, pattern fairness, and session fairness) on resulting quality and achieved QoE fairness. Based on conducted simulations and parameter studies, our results demonstrate the benefits of optimizing for session fairness as compared to other approaches.
Finite sample expressive power of small-width ReLU networks

We study universal finite sample expressivity of neural networks, defined as the capability to perfectly memorize arbitrary datasets. For scalar outputs, existing results require a hidden layer as wide as $N$ to memorize $N$ data points. In contrast, we prove that a 3-layer (2-hidden-layer) ReLU network with $4 \sqrt {N}$ hidden nodes can perfectly fit any arbitrary dataset. For $K$-class classification, we prove that a 4-layer ReLU network with $4 \sqrt{N} + 4K$ hidden neurons can memorize arbitrary datasets. For example, a 4-layer ReLU network with only 8,000 hidden nodes can memorize datasets with $N$ = 1M and $K$ = 1k (e.g., ImageNet). Our results show that even small networks already have tremendous overfitting capability, admitting zero empirical risk for any dataset. We also extend our results to deeper and narrower networks, and prove converse results showing necessity of $\Omega(N)$ parameters for shallow networks.
Increased Coronary Artery Plaque Volume Among Male Marathon Runners.

Background Long-term marathon running improves many cardiovascular risk factors, and is presumed to protect against coronary artery plaque formation. This hypothesis, that long-term marathon running is protective against coronary atherosclerosis, was tested by quantitatively assessing coronary artery plaque using high resolution coronary computed tomographic angiography (CCTA) in veteran marathon runners compared to sedentary control subjects. Methods Men in the study completed at least one marathon yearly for 25 consecutive years. All study subjects underwent CCTA, 12-lead electrocardiogram, measurement of blood pressure, heart rate, and lipid panel. A sedentary matched group was derived from a contemporaneous CCTA database of asymptomatic healthy individuals. CCTAs were analyzed using validated plaque characterization software. Results Male marathon runners (n = 50) as compared with sedentary male controls (n = 23) had increased total plaque volume (200 vs. 126 mm3, p < 0.01), calcified plaque volume (84 vs. 44 mm3, p < 0.0001), and non-calcified plaque volume (116 vs. 82 mm3, p = 0.04). Lesion area and length, number of lesions per subject, and diameter stenosis did not reach statistical significance. Conclusion Long-term male marathon runners may have paradoxically increased coronary artery plaque volume.