Miracle-dz/UniFAR-FTUs huggingface dataset:
Building A Thesaurus Using LDA-Frames

In this paper we present a new method for measuring semantic relatedness of lexical units, which can be used to generate a thesaurus automatically. The method is based on a comparison of probability distributions of semantic frames generated using the LDA-frames algorithm. The idea is evaluated by measuring the overlap of WordNet synsets and generated semantic clusters. The results show that the method outperforms another automatic approach used in the Sketch Engine project.
Initial in vitro studies on tissues and cells from GTKO/CD46/NeuGcKO pigs

The impact that the absence of expression of NeuGc in pigs might have on pig organ or cell transplantation in humans has been studied in vitro, but only using red blood cells (pRBCs) and peripheral blood mononuclear cells (pPBMCs) as the target cells for immune assays. We have extended this work in various in vitro models and now report our initial results.
Development of a desk-type tactile interface using force sensors

This paper describes a technique to provide tactile sense to a desk by a simple mechanism. The tactile sense is provided to the whole body of the desk by fixing a force sensor on each leg. One of the advantages of this technique is that the contact point can be estimated without any sensor device on the surface of the desk. The desk can be used as a kind of a tactile interface by utilizing the advantage. Some examples of application using the desk with computer graphics are introduced.
Quality of reporting in abstracts of randomized controlled trials published in leading journals of periodontology and implant dentistry: a survey.

BACKGROUND Most readers, reviewers, and editors rely on abstracts to decide whether to assess the full text of an article. A research abstract should, therefore, be as informative as possible. The standard of reporting in abstracts of randomized controlled trials (RCTs) in periodontology and implant dentistry has not yet been assessed. The objectives of this review are: 1) to assess the quality of reporting in abstracts of RCTs in periodontology and implant dentistry, and 2) to investigate changes in the quality of reporting by comparing samples from different periods. METHODS The authors searched the PubMed electronic database, independently and in duplicate, for abstracts of RCTs published in seven leading journals of periodontology and implant dentistry from 2005 to 2007 and from 2009 to 2011. The quality of reporting in selected abstracts with reference to the CONSORT (Consolidated Standards of Reporting Trials) for Abstracts checklist published in January 2008 was assessed independently and in duplicate. Cohen κ statistic was used to determine the extent of agreement of the reviewers. Pearson χ(2) test and/or Fisher exact test were used to assess differences in reporting in the two samples. Level of significance was set at P <0.05. RESULTS Three hundred ninety-two abstracts are included in this review. Three items (intervention, objective, and conclusions) were almost fully reported in both samples. In contrast, other items (randomization, trial registration, and funding) were never reported. There were significant changes in reporting for only two items, trial design and title (items better reported in the pre- and post-CONSORT samples, respectively). Most topics, however, were similarly poorly reported in both samples of abstracts. CONCLUSIONS The quality of reporting in abstracts of RCTs in periodontology and implant dentistry can be improved. Authors should follow the CONSORT for Abstracts guidelines, and journal editors should promote clear rules to improve authors' adherence to these guidelines.
AVIoT: web-based interactive authoring and visualization of indoor internet of things

Internet of things recently emerges as a common platform and service for consumer electronics. This paper presents an interactive framework of visualizing and authoring IoT in indoor environments such as home or small office. Building blocks of the framework are virtual sensors and actuators that abstract physical things and their virtual behaviors on top of their physical networks. Their behaviors are abstracted and programmed through visual authoring tools on the web, which allows a casual consumer to easily monitor and define their behaviors even without knowing the underlying physical connections. The user study performed to assess the usability of the visual authoring showed that the visual authoring is easy to use, understandable, and also preferred to typical text-based script programming.
Comparative analysis of the beneficial effects of treadmill training and electroacupuncture in a rat model of neonatal hypoxia-ischemia

In the present study, we investigated whether treadmill training and electroacupuncture (EA) have autonomous or synergistic beneficial effects on deficits caused by neonatal hypoxia-ischemia in Sprague-Dawley rats. For this purpose, rats subjected to hypoxia-ischemia underwent treadmill training and EA stimulation from 4 to 8 weeks of age. Conventional EA (CEA) and scalp EA (SEA) were delivered by electrical stimulation (2 Hz, 1 mA) at traditional acupoints and at the scalp to the primary motor area, respectively. In the behavioral examination, markedly improved performances in the rotarod test were observed in the rats that underwent treadmill exercise, and in the rats that underwent treadmill exercise and CEA compared to the untreated rats subjected to hypoxia-ischemia. An improvement was also observed in the passive avoidance test in the rats that underwent treadmill training and EA. As shown by western blot analysis, the expression levels of neuronal nuclei (NeuN), 2′,3′-cyclic-nucleotide 3′-phosphodiesterase and myelin basic protein (MBP) exhibited a significant decrease in the contralateral subventricular zone (SVZ) of the rats subjected to hypoxia-ischemia compared to the controls; however, these expression levels increased following treadmill exercise and EA stimulation. As shown by immunohistochemical analyses, the thickness of the corpus callosum and the integrated optical density (IOD) of MBP were significantly increased in the rats subjected to treadmill exercise and EA compared to the untreated rats subjected to hypoxiaa-ischemia. The synergistic effects of treadmill training and EA were also observed in the protein levels and IOD of MBP. A marked increase in the number of bromodeoxyuridine (BrdU)- and BrdU/NeuN-positive cells in the contralateral SVZ was also observed in the rats that underwent treadmill training and EA; the number of BrdU-positive cells was synergistically affected by treadmill training and EA. These results suggest that treadmill training and EA stimulation contribute to the enhancement of behavioral recovery following hypoxia-ischemia via the upregulation of myelin components and neurogenesis. Thus, treatment with EA stimulation, as well as treadmill training offers another treatment option to promote functional recovery in cerebral palsy.
The LZIP: A Bayesian latent factor model for correlated zero‐inflated counts

Motivated by a study of molecular differences among breast cancer patients, we develop a Bayesian latent factor zero‐inflated Poisson (LZIP) model for the analysis of correlated zero‐inflated counts. The responses are modeled as independent zero‐inflated Poisson distributions conditional on a set of subject‐specific latent factors. For each outcome, we express the LZIP model as a function of two discrete random variables: the first captures the propensity to be in an underlying “at‐risk” state, while the second represents the count response conditional on being at risk. The latent factors and loadings are assigned conditionally conjugate gamma priors that accommodate overdispersion and dependence among the outcomes. For posterior computation, we propose an efficient data‐augmentation algorithm that relies primarily on easily sampled Gibbs steps. We conduct simulation studies to investigate both the inferential properties of the model and the computational capabilities of the proposed sampling algorithm. We apply the method to an analysis of breast cancer genomics data from The Cancer Genome Atlas.
Acute Effects of Exercise Mode on Arterial Stiffness and Wave Reflection in Healthy Young Adults: A Systematic Review and Meta-Analysis

Background: This systematic review and meta-analysis quantified the effect of acute exercise mode on arterial stiffness and wave reflection measures including carotid-femoral pulse wave velocity (cf-PWV), augmentation index (AIx), and heart rate corrected AIx (AIx75). Methods: Using standardized terms, database searches from inception until 2017 identified 45 studies. Eligible studies included acute aerobic and/or resistance exercise in healthy adults, pre- and post-intervention measurements or change values, and described their study design. Data from included studies were analyzed and reported in accordance with the Cochrane Handbook for Systematic Reviews of Interventions and PRISMA guidelines. Meta-analytical data were reported via forest plots using absolute differences with 95% confidence intervals with the random effects model accounting for between-study heterogeneity. Reporting bias was assessed via funnel plots and, individual studies were evaluated for bias using the Cochrane Collaboration's tool for assessing risk of bias. A modified PEDro Scale was applied to appraise methodological concerns inherent to included studies. Results: Acute aerobic exercise failed to change cf-PWV (mean difference: 0.00 ms−1 [95% confidence interval: −0.11, 0.11], p = 0.96), significantly reduced AIx (−4.54% [−7.05, −2.04], p = 0.0004) and significantly increased AIx75 (3.58% [0.56, 6.61], p = 0.02). Contrastingly, acute resistance exercise significantly increased cf-PWV (0.42 ms−1 [0.17, 0.66], p = 0.0008), did not change AIx (1.63% [−3.83, 7.09], p = 0.56), and significantly increased AIx75 (15.02% [8.71, 21.33], p < 0.00001). Significant heterogeneity was evident within all comparisons except cf-PWV following resistance exercise, and several methodological concerns including low applicability of exercise protocols and lack of control intervention were identified. Conclusions: Distinct arterial stiffness and wave reflection responses were identified following acute exercise with overall increases in both cf-PWV and AIx75 following resistance exercise potentially arising fromcardiovascular and non-cardiovascular factors that likely differ from those following aerobic exercise. Future studies should address identified methodological limitations to enhance interpretation and applicability of arterial stiffness and wave reflection indices to exercise and health.
Assessing quantile prediction with censored quantile regression models

An important goal of censored quantile regression is to provide reliable predictions of survival quantiles, which are often reported in practice to offer robust and comprehensive biomedical summaries. However, formal methods for evaluating and comparing working quantile regression models in terms of their performance in predicting survival quantiles have been lacking, especially when the working models are subject to model mis‐specification. In this article, we proposes a sensible and rigorous framework to fill in this gap. We introduce and justify a predictive performance measure defined based on the check loss function. We derive estimators of the proposed predictive performance measure and study their distributional properties and the corresponding inference procedures. More importantly, we develop model comparison procedures that enable thorough evaluations of model predictive performance among nested or non‐nested models. Our proposals properly accommodate random censoring to the survival outcome and the realistic complication of model mis‐specification, and thus are generally applicable. Extensive simulations and a real data example demonstrate satisfactory performances of the proposed methods in real life settings.
Balance Control Using Both ZMP and COM Height Variations: A Convex Boundedness Approach

Developments for 3D control of the center of mass (CoM) of biped robots are currently located in two local minima: on the one hand, methods that allow CoM height variations but only work in the 2D sagittal plane; on the other hand, nonconvex direct transcriptions of centroidal dynamics that are delicate to handle. This paper presents an alternative that controls the CoM in 3D via an indirect transcription that is both low-dimensional and solvable fast enough for real-time control. The key to this development is the notion of boundedness condition, which quantifies the capturability of 3D CoM trajectories.
Some Observations on the Recycling of Superalloys by the EBCHM Process

The casting of DS and single crystal superalloy components generates a considerable proportion of scrap in alloys which are extremely expensive. Most specifications forbid the extensive re-use of recycled materials on the grounds that they are contaminated in such a manner as to affect the castings which might be made from them. The effect of impurities (principally oxygen and nitrogen) is not well defined but may appear as increased microporosity, rejectable non-metallic inclusion clusters or an enhanced propensity for the formation of freckles and random grains. The purpose of this work is to analyse the defect formation in recycled alloys and also the necessary refining to eliminate it in the cases of two specific alloys, IN100 and MAR M247. It is concluded that the required refining can be achieved for a 100% recycled charge by the use of the electron-beam cold-hearth refining process.
Reproducing Czech Syntactic Parsing Results Published in CoNLL Tasks

In this paper, I describe the approach on reproducing MST Parser and MaltParser results for Czech dependency parsing which were published in several tasks of Conference on Computational Natural Language Learning. Firstly, I brieﬂy describe basic principles of parsers. Then, I include features and options that need to be optimized while using the parsers to get the desired results on testing ﬁles as well as evaluation methodology used in my research. I also shortly mention hardware requirements for those, who would like to train their own model for Czech language parsing. Finally, I include the practical application of trained models for our approach.
Intracellular trafficking of begomoviruses in the midgut cells of their insect vector

Begomoviruses are exclusively transmitted by whiteflies in a persistent circulative manner and cause considerable economic losses to crop production worldwide. Previous studies have shown that begomoviruses accumulate in vesicle-like structures in whitefly midgut cells and that clathrin-mediated endocytosis is responsible for their internalization. However, the process by which begomoviruses are trafficked within whitefly midgut cells remains largely unknown. In this study, we investigated the roles of vesicle trafficking in the transport of Tomato yellow leaf curl virus (TYLCV), a begomovirus that has spread to over 50 countries and caused extensive damage to a range of important crops, within midgut cells of whitefly (Bemisia tabaci). By disrupting vesicle trafficking using RNA silencing and inhibitors, we demonstrated that the early steps of endosomal trafficking are important for the intracellular transport of TYLCV in the whitefly midgut. In addition, our data show that, unlike many animal viruses, TYCLV is trafficked within cells in a manner independent of recycling endosomes, late endosomes, lysosomes, the Golgi apparatus and the endoplasmic reticulum. Instead, our results suggest that TYLCV might be transported directly from early endosomes to the basal plasma membrane and released into the hemolymph. Silencing of the sorting nexin Snx12, which may be involved in membrane tubulation, resulted in fewer viral particles in hemolymph; this suggests that the tubular endosomal network may be involved in the transport of TYLCV. Our results also support a role for the endo-lysosomal system in viral degradation. We further showed that the functions of vector early endosomes and sorting nexin Snx12 are conserved in the transmission of several other begomoviruses. Overall, our data indicate the importance of early endosomes and the tubular endosomal network in begomovirus transmission.
Support for symmetric shadow memory in multiprocessors

Runtime monitoring support serves as a foundation for the important tasks of providing security [15, 14, 2], performing debugging [13, 11, 8], and improving performance of applications [1]. Runtime monitoring, typically, requires the maintenance of meta data associated with each of the application's original memory location, which are held in corresponding shadow memory locations. Each original memory instruction (OMI) is then accompanied by additional shadow memory instructions (SMIs) that manipulate the meta data associated with the memory location. Often the SMIs associated with OMIs are symmetric, in that, original stores (loads) are accompanied by shadow stores (loads). Unfortunately, existing shadow memory implementations need thread serialization to ensure that OMIs and SMIs are executed atomically [12]. Naturally this is not an efficient approach, especially in the now ubiquitous multiprocessors. In this paper, we present an efficient shadow memory implementation that handles symmetric shadow instructions. By coupling the coherency of shadow memory with the coherency of the main memory, we ensure that the SMIs execute atomically with their corresponding OMIs. We also couple the allocation of application memory pages with its associated shadow pages, for enabling fast translation of original addresses into corresponding shadow memory addresses. Our experiments show that the overheads of run-time monitoring tasks are significantly reduced in comparison to previous software implementations.
Single-View Food Portion Estimation: Learning Image-to-Energy Mappings Using Generative Adversarial Networks

Due to the growing concern of chronic diseases and other health problems related to diet, there is a need to develop accurate methods to estimate an individual's food and energy intake. Measuring accurate dietary intake is an open research problem. In particular, accurate food portion estimation is challenging since the process of food preparation and consumption impose large variations on food shapes and appearances. In this paper, we present a food portion estimation method to estimate food energy (kilocalories) from food images using Generative Adversarial Networks (GAN). We introduce the concept of an “energy distribution” for each food image. To train the GAN, we design a food image dataset based on ground truth food labels and segmentation masks for each food image as well as energy information associated with the food image. Our goal is to learn the mapping of the food image to the food energy. We can then estimate food energy based on the energy distribution. We show that an average energy estimation error rate of 10.89% can be obtained by learning the image-to-energy mapping.
Community-based Outlier Detection for Edge-attributed Graphs

The study of networks has emerged in diverse disciplines as a means of analyzing complex relationship data. Beyond graph analysis tasks like graph query processing, link analysis, influence propagation, there has recently been some work in the area of outlier detection for information network data. Although various kinds of outliers have been studied for graph data, there is not much work on anomaly detection from edge-attributed graphs. In this paper, we introduce a method that detects novel outlier graph nodes by taking into account the node data and edge data simultaneously to detect anomalies. We model the problem as a community detection task, where outliers form a separate community. We propose a method that uses a probabilistic graph model (Hidden Markov Random Field) for joint modeling of nodes and edges in the network to compute Holistic Community Outliers (HCOutliers). Thus, our model presents a natural setting for heterogeneous graphs that have multiple edges/relationships between two nodes. EM (Expectation Maximization) is used to learn model parameters, and infer hidden community labels. Experimental results on synthetic datasets and the DBLP dataset show the effectiveness of our approach for finding novel outliers from networks.
Minority Carrier Lifetime Improvement of Multicrystalline Silicon Using Combined Saw Damage Gettering and Emitter Formation

In this work we use Saw Damage Gettering (SDG) in combination with emitter formation to improve the minority carrier lifetime of highly contaminated multi-crystalline silicon wafers. This process is applied to wafers from the bottom of ingots, commonly referred to as the “red zone”, which are currently discarded since their high concentration of impurities limits the efficiency of solar cells produced therefrom. SDG is a potentially simple technique designed to upgrade these wafers. In this technique, bulk impurities are dissolved via annealing. The wafers are then cooled which generates a super-saturation of impurities in solution. The system then relaxes through the formation of precipitates in the saw damaged region. SDG is shown to be enhanced when using a temperature dependent cooling rate which maximizes the flux of impurities to the saw damaged regions. In addition, these benefits were observed even after an additional gettering process occurring during an emitter formation procedure. The SDG annealing conditions required to achieve the maximum lifetime were altered by the introduction of the emitter formation process. The enhancement generated by the SDG process may be sufficient to enable red-zone wafers to be processed is the same manner as higher quality no-red zone wafer wafers without adversely affecting the resultant cell efficiency. Due to its simplicity, it is expected that SDG can easily be incorporated into current production methods.
Introducing shadows: Flexible document representation and annotation on the Web

The Web is witnessing an exponential growth of increasingly complex, distributed and heterogeneous documents. This hampers document exchange, as well as their annotation and retrieval. While information retrieval mechanisms concentrate on textual features (corpus analysis), annotation approaches either target specific formats or require that a document follows interoperable standards. This work presents our effort to handle these problems, providing a more flexible solution. Rather than trying to modify or convert the document itself, or to target only textual characteristics, the strategy described in this work is based on an intermediate descriptor - the document shadow. A shadow represents domain-relevant aspects and elements of both structure and content of a given document, as defined by a user group. Rather than annotating documents themselves, it is the shadows that are annotated, thereby providing independence between annotations and document formats. Our annotations take advantage of the LOD initiative. Via annotations users can derive correlations across shadows, in a flexible way. Moreover, shadows and annotations are stored in databases, therefore allowing uniform database treatments of heterogeneous documents.