Miracle-dz/UniFAR-FTUs huggingface dataset:
A new single‐phase multilevel converter topology with reduced power electronic devices, voltage rating on switches, and power losses

In this paper, a new extended single‐phase structure for multilevel converter is presented which consists of several bidirectional and unidirectional switches along with dc voltage sources. To generate all possible levels at output voltage waveform, 2 methods are presented for determination of the amplitudes of dc voltage sources. The proposed structure is compared with traditional cascade H‐bridge multilevel converter and other recently proposed structures in terms of the number of power electronic components, voltage rating on switches, and power losses. Based on the comparison results, it is demonstrated that the proposed structure needs minimum number of IGBTs, gate drivers, and anti‐parallel diodes. Moreover, the voltage rating on bidirectional and unidirectional switches in the proposed structure is less than other similar topologies. Also, power losses analysis on the proposed topology is investigated. It is shown that the power loss of proposed topology is less than H‐bridge multilevel converter topology. The number of on‐state switches in the current path of proposed topology is much lower than other topologies which lead to the reduction of voltage drop on the switches and power losses. Both experimental and simulation works are provided to verify the performance of the presented structure.
Multi-Viewpoints Ontological Knowledge Representation: A Fuzzy Description Logics Based Approach

Description Logics (DLs) play a key role in the design of ontologies. An ontology is a formal description of important concepts in a particular domain. In practice, a set of a specific-domain applications use different representations of the same real world entity due to various viewpoints, context, and specific interest. In this paper, we are interested in the problem of representing an ontology in a heterogeneous domain by taking into consideration different viewpoints and different terminologies of various users, groups or even communities in the organisation. This type of ontology, called multi-viewpoints ontology, confers to the same universe of discourse, several partial descriptions, where each one is relative to a particular viewpoint. Moreover, these partial descriptions share at global level, fuzzy ontological elements allowing the representation of vague/imprecise knowledge between the various viewpoints. So, our goal is to propose a fuzzy multi-viewpoints ontology Web language, which is an extension of OWL-DL language, to allow the multi-viewpoints ontologies representation.
How Do Victims of Sexual Violence Benefit From Mutual Disclosure? An Exploratory Study of Women in South Korea

Sexual violence victims in the Republic of Korea (henceforth, South Korea) have mutual support groups that provide a variety of programs promoting mutual disclosure between them. These programs are based upon the premise that responses within those groups are more supportive than conventional responses; however, there is no empirical evidence of mutual disclosure. The aim of the current study is to answer two research questions: (a) How do responses and outcomes of mutual disclosure compare with those of traditional disclosure? and (b) What themes describe mutual disclosure as distinguishable from a traditional one? A sample of 25 Korean sexual violence victims reported their disclosure experiences by responding to a survey and/or an in person interview. This study found that responses and outcomes of mutual disclosure were overall positive based on their similar victimized experience. The finding emphasizes a balance between a victim’s dual role as help-seeker and support provider for the benefits of mutual disclosure. Existing mutual support groups and relevant institutions should consider the aspects and effects of mutual disclosure to provide more opportunities for victims to speak out as well as to foster greater access to support.
Phenotypic and Genomic Properties of Brachybacterium vulturis sp. nov. and Brachybacterium avium sp. nov.

Two strains, VM2412T and VR2415T, were isolated from the feces of an Andean condor (Vultur gryphus) living in Seoul Grand Park, Gyeonggi-do, South Korea. Cells of both strains were observed to be Gram-stain positive, non-motile, aerobic, catalase positive and oxidase negative. Growth was found to occur at 10-30°C, showing optimum growth at 30°C. The strains could tolerate up to 15% (w/v) NaCl concentration and grow at pH 6-9. The strains shared 99.3% 16S rRNA gene sequence similarity to each other but were identified as two distinct species based on 89.0-89.2% ANIb, 90.3% ANIm, 89.7% OrthoANI and 38.0% dDDH values calculated using whole genome sequences. Among species with validly published names, Brachybacterium ginsengisoli DCY80T shared high 16S rRNA gene sequence similarities with strains VM2412T (98.7%) and VR2415T (98.4%) and close genetic relatedness with strains VM2412T (83.3–83.5% ANIb, 87.0% ANIm, 84.3% OrthoANI and 27.8% dDDH) and VR2415T (82.8–83.2% ANIb, 86.7% ANIm, 83.9% OrthoANI and 27.2% dDDH). The major fatty acid of the two strains was identified as anteiso-C15:0 and the polar lipids consisted of phosphatidylglycerol, diphosphatidylglycerol, presumptively phosphatidylethanolamine and three unidentified glycolipids. Strain VR2415T also produced an unidentified phospholipid. The cell walls of the two strains contained meso-diaminopimelic acid as diagnostic diamino acid and the whole cell sugars were ribose, glucose, and galactose. The strains contained MK-7 as their predominant menaquinone. The genomes of strains VM2412T, VR2415T, and B. ginsengisoli DCY80T were sequenced in this study. The genomic G+C contents of strains VM2412T and VR2415T were determined to be 70.8 and 70.4 mol%, respectively. A genome-based phylogenetic tree constructed using an up-to-date bacterial core gene set (UBCG) showed that the strains formed a clade with members of the genus Brachybacterium, supporting their taxonomic classification into the genus Brachybacterium. Based on phenotypic and genotypic analyses in this study, strains VM2412T and VR2415T are considered to represent two novel species of the genus Brachybacterium and the names Brachybacterium vulturis sp. nov. and Brachybacterium avium sp. nov. are proposed for strains VM2412T (=KCTC 39996T = JCM 32142T) and VR2415T (=KCTC 39997T = JCM 32143T), respectively.
Towards a Rigorous Methodology for Measuring Adoption of RPKI Route Validation and Filtering

In this talk, we will report on our recent article "Towards a Rigorous Methodology for Measuring Adoption of RPKI Route Validation and Filtering", published in ACM Computer Communication Review, January 2018. We will also present new results that arise from ongoing deployment of RPKI route origin validation (\eg default filtering at IXP route servers), and introduce a publicly available measurement platform for daily monitoring of the state of deployment.
Daytime driving decreases amphibian roadkill

Roadkill has gradually become a common factor that has contributed to the decline of amphibians, and traffic volume is an important parameter that can be used to determine the impacts of roads. However, few researchers have studied the effects of either daily or nightly traffic volume on amphibian roadkill in China. Hence, as an essential step for implementing mitigation measures, we conducted 77 road surveys along 10 km of road in the Wanglang National Nature Reserve (NNR) to determine the temporal and spatial distribution patterns of amphibian road mortality. In total, 298 dead individuals (Bufo andrewsi and Rana chensinensis) were observed on the road from April to October in 2017 and during June and August in 2015 and 2016. B. andrewsi had the highest number of records (85.2%) and was more vulnerable to road mortality than R. chensinensis. Amphibian fatalities mainly occurred during the breeding season in April, but there was an additional concentration of B. andrewsi roadkill in June and July. There was a significantly positive correlation between amphibian road mortality and mean night-time traffic volume. Roadkill hotspots were non-randomly distributed throughout the study area and were mainly concentrated in the road sections near the breeding pools. Therefore, to effectively mitigate the effects of road mortality in the Wanglang NNR, measures should be implemented both during hot moments and at hotspots. First, based on roadkill hot moments, during the breeding season (in April) and in June and July, the Wanglang NNR should establish temporary traffic restraints at night. Second, based on roadkill hotspots, culverts should be established in areas near breeding pools adjacent to roads, and barrier walls should be installed to guide amphibians into the culverts.
A Review on Image- and Network-based Brain Data Analysis Techniques for Alzheimer's Disease Diagnosis Reveals a Gap in Developing Predictive Methods for Prognosis

Unveiling pathological brain changes associated with Alzheimer's disease (AD) is a challenging task especially that people do not show symptoms of dementia until it is late. Over the past years, neuroimaging techniques paved the way for computer-based diagnosis and prognosis to facilitate the automation of medical decision support and help clinicians identify cognitively intact subjects that are at high-risk of developing AD. As a progressive neurodegenerative disorder, researchers investigated how AD affects the brain using different approaches: 1) image-based methods where mainly neuroimaging modalities are used to provide early AD biomarkers, and 2) network-based methods which focus on functional and structural brain connectivities to give insights into how AD alters brain wiring. In this study, we reviewed neuroimaging-based technical methods developed for AD and mild-cognitive impairment (MCI) classification and prediction tasks, selected by screening all MICCAI proceedings published between 2010 and 2016. We included papers that fit into image-based or network-based categories. The majority of papers focused on classifying MCI vs. AD brain states, which has enabled the discovery of discriminative or altered brain regions and connections. However, very few works aimed to predict MCI progression based on early neuroimaging-based observations. Despite the high importance of reliably identifying which early MCI patient will convert to AD, remain stable or reverse to normal over months/years, predictive models are still lagging behind.
The presence of amniotic fluid sludge in pregnant women with a short cervix: an independent risk of preterm delivery

Abstract Objective: To examine whether the presence of amniotic fluid sludge (AFS) could increase the risk of preterm delivery in women with a cervical length (CL) of less than 25 mm. Materials and methods: This is a retrospective cohort study of 110 women who were 14–30 weeks pregnant with a singleton gestation and a CL of less than 25 mm. The primary outcomes were defined as preterm delivery before 34 weeks and preterm delivery before 37 weeks. The secondary outcome was defined as preterm premature rupture of membranes (PPROM) prior to preterm delivery. Risk factors for preterm delivery were defined as AFS, subchorionic hematoma (SCH), history of preterm delivery, CL of less than 20 mm, and CL of less than 15 mm. A univariate analysis was performed to assess the primary and secondary outcomes according to the presence or absence of each risk factor. A multiple logistic regression analysis was performed to evaluate the parameters, using a significance of p < . 05 on the univariate analysis to examine whether they were independent risk factors. Results: A significantly increased risk of preterm delivery was found in the group of women with AFS who actually did deliver prior to 34 weeks (p < .001; odds ratio [OR] 6.44; 95% confidence interval [CI] 2.51–16.5), prior to 37 weeks (p = .001; OR 4.46; 95% CI 1.76–11.3), and who had PPROM (p < .001; OR 4.96; 95% CI 2.00–12.3). A multivariate logistic regression analysis was performed in the women with AFS who experienced preterm delivery before 34 weeks, in the women with a CL less than 20 mm, and in the women with a CL less than 15 mm. The results showed that AFS was an independent risk factor for preterm delivery before 34 weeks (p = .001; OR 5.86; 95% CI 2.11–16.3). Conclusion: The presence of AFS was an independent risk factor for preterm delivery before 34 weeks in women with a CL less than 25 mm.
Final Report of a Phase I Trial of Olaparib with Cetuximab and Radiation for Heavy Smoker Patients with Locally Advanced Head and Neck Cancer

Purpose: Our goal was to evaluate the safety and toxicity of combining a PARP inhibitor, olaparib, with cetuximab and fractionated intensity-modulated radiotherapy for patients with locally advanced head and neck cancer and heavy smoking histories. Patients and Methods: Patients with ≥10 packs/year history of smoking were treated with olaparib at doses ranging from 25–200 mg orally twice daily beginning approximately 10 days prior to initiation of and with concurrent radiation (69.3 Gy in 33 fractions) using a time-to-event continual reassessment method model. Cetuximab was administered starting approximately 5 days prior to radiation per standard of care. Results: A total of 16 patients were entered onto the study, with 15 evaluable for acute toxicity. The most common treatment-related grade 3–4 side effects were radiation dermatitis and mucositis (38% and 69%, respectively). The MTD was determined to be 50 mg orally twice daily, but the recommended phase II dose was deemed to be 25 mg orally twice daily. At a median follow-up of 26 months, the actuarial median overall survival was 37 months, but was not reached for other endpoints. Two-year overall survival, progression-free survival, local control, and distant control rates were 72%, 63%, 72%, and 79%, respectively. Patients who continued to smoke during therapy experienced higher recurrence rates. MYC and KMT2A were identified as potential correlatives of response on gene amplification and mutational analysis. Conclusions: Olaparib at 25 mg orally twice daily with concurrent cetuximab and radiation was well tolerated with reduced dermatitis within the radiation field. Response rates were promising for this high-risk population. Clin Cancer Res; 24(20); 4949–59. ©2018 AACR.
Robust nanoscopy of a synaptic protein in living mice by organic-fluorophore labeling

Significance In vivo fluorescence microscopy with resolution well beyond the diffraction limit entails complexities that challenge the attainment of sufficient image brightness and contrast. These challenges have so far hampered investigations of the nanoscale distributions of synaptic proteins in the living mouse. Here, we describe a combination of stimulated emission depletion microscopy and endogenous protein labeling, providing high-quality in vivo data of the key scaffolding protein PSD95 at the postsynaptic membrane, which frequently appeared in extended distributions rather than as isolated nanoclusters. Operating in the far-red to near-IR wavelength range, this combination promises reduced photostress compared with prior in vivo nanoscopy at much shorter wavelengths. Extending superresolution fluorescence microscopy to living animals has remained a challenging frontier ever since the first demonstration of STED (stimulated emission depletion) nanoscopy in the mouse visual cortex. The use of fluorescent proteins (FPs) in in vivo STED analyses has been limiting available fluorescence photon budgets and attainable image contrasts, in particular for far-red FPs. This has so far precluded the definition of subtle details in protein arrangements at sufficient signal-to-noise ratio. Furthermore, imaging with longer wavelengths holds promise for reducing photostress. Here, we demonstrate that a strategy based on enzymatic self-labeling of the HaloTag fusion protein by high-performance synthetic fluorophore labels provides a robust avenue to superior in vivo analysis with STED nanoscopy in the far-red spectral range. We illustrate our approach by mapping the nanoscale distributions of the abundant scaffolding protein PSD95 at the postsynaptic membrane of excitatory synapses in living mice. With silicon-rhodamine as the reporter fluorophore, we present imaging with high contrast and low background down to ∼70-nm lateral resolution in the visual cortex at ≤25-µm depth. This approach allowed us to identify and characterize the diversity of PSD95 scaffolds in vivo. Besides small round/ovoid shapes, a substantial fraction of scaffolds exhibited a much more complex spatial organization. This highly inhomogeneous, spatially extended PSD95 distribution within the disk-like postsynaptic density, featuring intricate perforations, has not been highlighted in cell- or tissue-culture experiments. Importantly, covisualization of the corresponding spine morphologies enabled us to contextualize the diverse PSD95 patterns within synapses of different orientations and sizes.
How Media Reports Trigger Copycats: An Analysis of the Brewing of the Largest Packet Storm to Date

In late February 2018, news spread through the mainstream media about a massive distributed denial-of-service attack on the popular software collaboration website github.com. Estimated at a rate of 1.3 Terrabit per second, this massive packet flood was the largest DDoS attack by volume to date, surpassing previous records set by the first IoT-based DDoS attacks in 2017. In this paper, we analyze the behavior of the actors scanning and probing the Internet for presence of exploitable memcached servers that were the root cause of this attack, both before and after the media coverage. We find that the attacks of late February were preceeded by a large scale reconnaissance action a month before, and that the attacks were the result of an extended evolution of methods to find a suitable attack strategy. Furthermore, we see that the coverage about the massive DDoS attack actually triggered another wave of DDoS attacks, resulting in the large influx of new, previously unseen users who seem to be leveraging ready-made tools.
RF-based 3D skeletons

This paper introduces RF-Pose3D, the first system that infers 3D human skeletons from RF signals. It requires no sensors on the body, and works with multiple people and across walls and occlusions. Further, it generates dynamic skeletons that follow the people as they move, walk or sit. As such, RF-Pose3D provides a significant leap in RF-based sensing and enables new applications in gaming, healthcare, and smart homes. RF-Pose3D is based on a novel convolutional neural network (CNN) architecture that performs high-dimensional convolutions by decomposing them into low-dimensional operations. This property allows the network to efficiently condense the spatio-temporal information in RF signals. The network first zooms in on the individuals in the scene, and crops the RF signals reflected off each person. For each individual, it localizes and tracks their body parts - head, shoulders, arms, wrists, hip, knees, and feet. Our evaluation results show that RF-Pose3D tracks each keypoint on the human body with an average error of 4.2 cm, 4.0 cm, and 4.9 cm along the X, Y, and Z axes respectively. It maintains this accuracy even in the presence of multiple people, and in new environments that it has not seen in the training set. Demo videos are available at our website: http://rfpose3d.csail. mit.edu.
DELIMIT PyTorch - An extension for Deep Learning in Diffusion Imaging

DELIMIT is a framework extension for deep learning in diffusion imaging, which extends the basic framework PyTorch towards spherical signals. Based on several novel layers, deep learning can be applied to spherical diffusion imaging data in a very convenient way. First, two spherical harmonic interpolation layers are added to the extension, which allow to transform the signal from spherical surface space into the spherical harmonic space, and vice versa. In addition, a local spherical convolution layer is introduced that adds the possibility to include gradient neighborhood information within the network. Furthermore, these extensions can also be utilized for the preprocessing of diffusion signals.
Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL

CPU has insufficient resources to satisfy the efficient computation of the convolution neural network (CNN), especially for embedded applications. Therefore, heterogeneous computing platforms are widely used to accelerate CNN tasks, such as GPU, FPGA, and ASIC. Among these, FPGA can accelerate the computation by mapping the algorithm to the parallel hardware instead of CPU, which cannot fully exploit the parallelism. By fully using the parallelism of the neural network’s structure, FPGA can reduce the computing costs and increase the computing speed. However, the development of FPGA requires great design skills. As a heterogeneous development platform, OpenCL has some advantages such as high abstraction level, short development cycle, and strong portability, which can make up for the lack of skilled designers. This paper uses Xilinx SDAccel to realize the parallel acceleration of CNN task, and it also proposes an optimizing strategy of single convolutional layer to accelerate CNN. Simulation results show that the calculation speed could be improved by adopting the proposed optimizing strategy. Compared with the baseline design, the strategy of single convolutional layer could increase the computing speed 14 times. Performance of the whole CNN task could be improved 2 times more than before, and the speed of image classification could attain more than 48 fps.
Dispositional Optimism and Cardiovascular Reactivity Accompanying Anger and Sadness in Young Adults.

BACKGROUND Dispositional optimism, a generalized expectation for positive outcomes, appears to promote physical health and well-being, including positive effects on cardiovascular disease outcomes. Mechanisms may involve adaptive responses to psychological stressors that dampen their physiological impact. PURPOSE This study investigated (i) whether individual differences in optimism are associated with attenuated cardiovascular reactivity (CVR); (ii) whether the CVR moderating effect of optimism differs for two stress emotions, anger and sadness; and (iii) whether separate measures of optimism and pessimism, and the more commonly used measure that combines them, differ in their relationships with CVR. METHODS The Life Orientation Test-Revised (LOT-R) was used to provide an overall dispositional optimism score and subscale scores separately assessing optimism and pessimism. These predictors were examined in relation to cardiovascular responses evoked by a stressful autobiographical recall task. Task instructions were manipulated within subjects to produce anger and sadness. CVR measures were systolic and diastolic blood pressure (SBP and DBP) and heart rate (HR). RESULTS Dispositional optimism was inversely associated with SBP and HR (but not DBP) elevations while participants related both anger- and sadness-inducing events. There was some indication that these associations were stronger for sadness than for anger, and that the LOT-R optimism subscale was a better predictor of CVR than its pessimism subscale. CONCLUSIONS These findings add to the understanding of health-promoting effects of dispositional optimism by addressing relationships of optimism and pessimism with cardiovascular concomitants of anger and sadness that are thought to contribute to heart disease.