Miracle-dz/UniFAR-FTUs huggingface dataset:
The Association of Brachial-Ankle Pulse Wave Velocity with Coronary Artery Disease Evaluated by Coronary Computed Tomography Angiography

The aim of this study was to investigate whether brachial-ankle pulse wave velocity (baPWV) is associated with the severity of coronary artery disease (CAD) assessed by coronary computed tomography angiography (CCTA), and to evaluate baPWV as a predictor of obstructive CAD on CCTA. A total of 470 patients who underwent both baPWV and CCTA were included. We evaluated stenosis degree and plaque characteristics on CCTA. To estimate the severity of CAD, we calculated the number of segment with plaque (segment involvement score; SIS), stenosis degree-weighted plaque score (segment stenosis score; SSS), and coronary artery calcium score (CACS). The mean baPWV was 1,485 ± 315 cm/s (range, 935-3,175 cm/s). Non-obstructive (stenosis < 50%) and obstructive (stenosis ≥ 50%) CAD was found in 129 patients (27.4%) and 144 (30.6%), respectively. baPWV in patients with obstructive CAD was higher than that of patients with non-obstructive (1,680 ± 396 cm/s versus 1,477 ± 244 cm/s, P < 0.001) or no CAD (1,680 ± 396 cm/s versus ± 196 1,389 cm/s, P < 0.001). baPWV showed significant correlation with SSS (r = 0.429, P < 0.001), SIS (r = 0.395, P < 0.001), CACS (r 0.346, P < 0.001), and the number of segment with non-calcified plaque (r 0.092, P = 0.047), mixed plaque (r = 0.267, P < 0.001), and calcified plaque (r = 0.348, P < 0.001), respectively. The optimal baPWV cut-off value for the detection of obstructive CAD was 1,547 cm/s. baPWV ≥ 1,547 cm/s was independent predictor for the obstructive CAD. In conclusion, baPWV is well correlated with the severity of CAD evaluated by CCTA. baPWV has the potential to predict severity of coronary artery atherosclerosis.
A German Sign Language Corpus of the Domain Weather Report

All systems for automatic sign language translation and recognition, in particular statistical systems, rely on adequately sized corpora. For this purpose, we created the Phoenix corpus that is based on German television weather reports translated into German Sign Language. It comes with a rich annotation of the video data, a bilingual text-based sentence corpus and a monolingual German corpus. All systems for automatic sign language translation and recognition, in particular statistical systems, rely on adequately sized corpora. For this purpose, we created the Phoenix corpus that is based on German television weather reports translated into German Sign Language. It comes with a rich annotation of the video data, a bilingual text-based sentence corpus and a monolingual German corpus.
Is the serum ferritin level a considerable predictor for hemorrhagic transformation of ischemic stroke?

Background: Hemorrhagic Transformation (HT) of Ischemic Stroke (IS) is a detrimental complication. This study investigated the association between serum ferritin level and HT in patients with massive IS of middle cerebral artery. Methods: Thirty patients with massive IS of middle cerebral artery were enrolled in this prospective cohort study. They were divided into two groups based on the serum ferritin level, lower or greater than 164.1ng/ml at the first 24 hours after admission. To investigate the incidence of HT in the two groups, we observed them for two weeks. Results: During the two- week observation, the incidence of HT was two persons (13.3%) in the group with the serum ferritin level of lower than 164.1ng/ml, and eight persons (53.3%) in the other group. This difference was statistically significant between the two groups (p=0.02). The relative risk of HT was 4 (95% CI: 1.012- 15.8) in the patients with massive IS of middle cerebral artery and the serum ferritin level greater than 164.1ng/ml. Conclusion: This study revealed that the serum ferritin level greater than 164.1ng/ml in the first 24 hours after admission is a reasonably important predictor for HT of IS. Conducting studies on factors affecting the serum ferritin level are suggested.
High-Quality Assembly of an Individual of Yoruban Descent

De novo assembly of human genomes is now a tractable effort due in part to advances in sequencing and mapping technologies. We use PacBio single-molecule, real-time (SMRT) sequencing and BioNano genomic maps to construct the first de novo assembly of NA19240, a Yoruban individual from Africa. This chromosome-scaffolded assembly of 3.08 Gb with a contig N50 of 7.25 Mb and a scaffold N50 of 78.6 Mb represents one of the most contiguous high-quality human genomes. We utilize a BAC library derived from NA19240 DNA and novel haplotype-resolving sequencing technologies and algorithms to characterize regions of complex genomic architecture that are normally lost due to compression to a linear haploid assembly. Our results demonstrate that multiple technologies are still necessary for complete genomic representation, particularly in regions of highly identical segmental duplications. Additionally, we show that diploid assembly has utility in improving the quality of de novo human genome assemblies.
An assessment of the relationship between organizational culture and continuous knowledge management initiatives

The purpose of this research study was to assess the relationship between e-business organizational culture types and continuous knowledge management initiatives in an e-business organization in the transportation industry. This research study provided the foundations and conceptualizations of technologies, people, and knowledge within the context of a single case study of 31 sales professionals. The two-part sequential phase of grounded theory included triangulation through the collection and analysis of quantitative data from a questionnaire followed by the collection and analysis of qualitative data from interviews, observations, and documents. The quantitative design entailed three survey instrument components: a Demographic Respondent Profile, an Organizational Culture Assessment Instrument (OCAI), and a Knowledge Management Assessment Instrument (KMAI). The Competing Values Framework (Quinn & Rohrbaugh, 1983) provided discussion to understand how an e-business organization may improve value creation. The results of conducting this case study may help in determining if knowledge management initiatives will be beneficial and advantageous to an e-business organization determining a specific organizational culture type(s) and implementing knowledge management initiatives. In the right organizational culture, knowledge management may be an effective strategic initiative that enables long-term success, enhances value, and helps to increase an organizations competitive advantage.
MICA at ImageClef 2013 Plant Identification Task

In the framework of ImageClef 2013 [1], plant identification task [2], we have submitted three runs. For the first run named Mica Run 1, we employ GIST descriptor with k-nearest neighbor (kNN) for all sub-categories. Concerning Mica Run 2, we observe that global descriptors such as color histogram and texture are able to distinguish classes of two sub-categories that are flower and entire. For the others sub-categories, we still employ GIST descriptor and kNN. Based on our work for leaf identification, for the third run (named MICA run 3), we have proposed to apply our method for leaf images for both SheetasBackground and Natural background. For the remaining subcategories, we used the same method as the two first runs. Concerning our method for leaf images, we firstly apply Un-sharp Masking (USM) on SheetAsBackground images. Then, we extract Speeded-Up Robust Features (SURF). Finally, we used Bag-of-Words (BoW) for calculating feature vector of each image and Support Vector Machine (SVM) for training the model of each class in training dataset and for predicting class id of new images. In this paper, we describe in detail the algorithms used in our runs.
A robust pedestrian detector based on heterogeneous feature fusion

Pedestrian detection exhibits important application value in driver assistance systems, The detection performance often suffers from the various appearances of pedestrians, the illumination changes and complex background. Aiming at solving these challenges, in this paper, first, a new color moments feature is presented to describe the local similarity structure of pedestrians, which reduces the influence of complicated background. A combination coefficient method is introduced to effectively fuse three heterogeneous features, COLOR, HOG, and LBP, which makes better use of each feature. Then, pedestrians of various poses and views are divided into subclasses with S-Isomap and K-means algorithm. A classifier is trained for each subclass. Finally, with respect to the output values of different subclass classifiers, an equally weighted sum based multi-pose-view ensemble detector is proposed. Experiment results on public datasets demonstrate that the proposed feature combination method significantly improves the description capabilities of pedestrian features. Compared with the existing methods, the proposed detector combining the feature and multi-pose-view ensemble detector boosts the detection accuracy effectively.
Using Affiliation Networks to Study the Determinants of Multilateral Research Cooperation: Some Empirical Evidence from EU Framework Programs in Biotechnology

This paper studies multilateral cooperation networks among organizations and work on a two-mode representation to study the decision to participate in a consortium. Our objective is to explain the underlying processes that give rise to multilateral collaboration networks. Particularly, we are interested in how heterogeneity in organizations' attributes plays a part and in the geographical dimension of this formation process. We use the data on project proposals submitted to the 7th Framework Program (FP) in the area of Life sciences, Biotechnology and Biochemistry for Sustainable Non-Food. We employ exponential random graph models (p* models) (Frank and Strauss, 1986 ; Wasserman and Pattison, 1996) with node attributes (Agneessens et al., 2004), and we make use of extensions for affiliation networks (Wang et al., 2009). These models do not only enable handling variability in consortium sizes but also relax the assumption on tie/triad independence. We obtained some preliminary results indicating institutional types as a source of heterogeneity affecting participation decisions. Also, these initial results point out that organizations take their potential partners' participations in other projects into account in giving their decision ; organizations located in the core European countries tend to participate in the same project ; the tendency to preserve the composition of a consortium across projects and the tendency of organizations with the same institutional type to co-participate are not significant.
AdS vacua, attractor mechanism and generalized geometries

We consider flux vacua attractor equations in type IIA string theory compactified on generalized geometries with orientifold projections. The four-dimensional = 1 superpotential in this compactification can be written as the sum of the Ramond-Ramond superpotential and a term described by (non)geometric flux charges. We exhibit a simple model in which supersymmetric AdS and Minkowski solutions are classified by means of discriminants of the two superpotentials. We further study various configurations without Ramond-Ramond flux charges. In this case we find supersymmetric AdS vacua both in the case of compactifications on generalized geometries with SU(3) × SU(3) structures and on manifolds with an SU(3)-structure without nongeometric flux charges. In the latter case, we have to introduce correction terms into the prepotential in order to realize consistent vacua.
Efficient Electrolytes for Lithium–Sulfur Batteries

This review article mainly encompasses on the state-of-the-art electrolytes for lithium–sulfur batteries. Different strategies have been employed to address the issues of lithium-sulfur batteries across the world. One among them is identification of electrolytes and optimization of their properties for the applications in lithium-sulfur batteries. The electrolytes for lithium-sulfur batteries are broadly classified as (i) non-aqueous liquid electrolytes, (ii) ionic liquids, (iii) solid polymer and (iv) glass-ceramic electrolytes. This article presents the properties, advantages and limitations of each type of electrolytes. Also the importance of electrolyte additives on the electrochemical performance of Li-S cells is discussed.
Antiangiogenesis Targeting Tumor Microenvironment Synergizes Glucuronide Prodrug Antitumor Activity

Purpose: This study is aimed at investigating the in vivo antitumor activity of a novel cell-impermeable glucuronide prodrug, 9-aminocamptothecin glucuronide (9ACG), and elucidating the synergistically antitumor effects of antiangiogenesis therapy by targeting the tumor microenvironment. Experimental Design: We analyzed the antitumor effects of 9ACG alone or combined with antiangiogenic monoclonal antibody DC101 on human tumor xenografts by measuring tumor growth and mouse survival in BALB/c nu/nu nude and NOD/SCID mice. The drug delivery, immune response, and angiogenesis status in treated tumors were assessed by high performance liquid chromatography, immunohistochemistry, and immunofluorescence assays. Results: We developed a nontoxic and cell-impermeable glucuronide prodrug, 9ACG, which can only be activated by extracellular β-glucuronidase to become severely toxic. 9ACG possesses potent antitumor activity against human tumor xenografts in BALB/c nu/nu nude mice but not for tumors implanted in NOD/SCID mice deficient in macrophages and neutrophils, suggesting that these cells play an important role in activating 9ACG in the tumor microenvironment. Most importantly, antiangiogenic monoclonal antibody DC101 potentiated single-dose 9ACG antitumor activity and prolonged survival of mice bearing resistant human colon tumor xenografts by providing strong β-glucuronidase activity and prodrug delivery through enhancing inflammatory cell infiltration and normalizing tumor vessels in the tumor microenvironment. We also show that inflammatory cells (neutrophils) were highly infiltrated in advanced human colon cancer tissues compared with normal counterparts. Conclusions: Our study provides in vivo evidence that 9ACG has potential for prodrug monotherapy or in combination with antiangiognesis treatment for tumors with infiltration of macrophage or neutrophil inflammatory cells.
Utilization of a Porous Cu Interlayer for the Enhancement of Pb-Free Sn-3.0Ag-0.5Cu Solder Joint

The joining of lead-free Sn-3.0Ag-0.5Cu (SAC305) solder alloy to metal substrate with the addition of a porous Cu interlayer was investigated. Two types of porous Cu interlayers, namely 15 ppi—pore per inch (P15) and 25 ppi (P25) were sandwiched in between SAC305/Cu substrate. The soldering process was carried out at soldering time of 60, 180, and 300 s at three temperature levels of 267, 287, and 307 °C. The joint strength was evaluated by tensile testing. The highest strength for solder joints with addition of P25 and P15 porous Cu was 51 MPa (at 180 s and 307 °C) and 54 MPa (at 300 s and 307 °C ), respectively. The fractography of the solder joint was analyzed by optical microscope (OM) and scanning electron microscopy (SEM). The results showed that the propagation of fracture during tensile tests for solder with a porous Cu interlayer occurred in three regions: (i) SAC305/Cu interface; (ii) inside SAC305 solder alloy; and (iii) inside porous Cu. Energy dispersive X-ray spectroscopy (EDX) was used to identify intermetallic phases. Cu6Sn5 phase with scallop-liked morphology was observed at the interface of the SAC305/Cu substrate. In contrast, the scallop-liked intermetallic phase together with more uniform but a less defined scallop-liked phase was observed at the interface of porous Cu and solder alloy.
A Distributed Information Extraction System Integrating Ontological Knowledge and Probabilistic Classifiers

In this work we consider the problem of extracting concepts and relations between them from documents, aiming at constructing an index for a more semantically oriented search engine. While assessment is performed on a biomedical application, the proposed solutions can be also applied to different domains. With the distributed architecture proposed, we obtain an approach that can be applied also on large data sets. Experimental assessment has been performed on a standard data set, BioNLP 2013.
Neural Network Ensemble Based Ant Colony Classification Rule Mining

Generalization ability and comprehensibility are very important for classification rule mining. This paper proposes an improved ant colony classification rule mining method named ant-classifier with strong comprehensibility. Neural network ensemble is with good generalization ability. A novel algorithm NeAnt is also proposed which integrates neural network ensemble and ant-classifier's merit. In the NeAnt, neural network ensemble is used for preprocessing the original training set and ant-classifier is used for mining rules from the new training set. Experiments show that the generalization ability of NeAnt and ant-classifier can be better than NEC4.5 and C4.5 respectively
Impact of certification on fruit producers in the Sao Francisco Valley in Brazil

Producers and exporters of fresh fruits and vegetables from developing countries like Brazil are increasingly required to demonstrate the safety and traceability of their produce up to the consumption stage. In fact, the Brazilian export market is still relatively underdeveloped, with an export share of only 2.4% of the total produced volume. However, certification may also have the effect of a non-tariff trade barrier, undermining the capability and financial ability of especially small-scale farmers in exporting to international markets. This study, therefore, aims at providing an economic analysis of certification on mango and grapes producers. A survey of 303 grapes and mango farmers was conducted in 2006 in the Juazeiro and Petrolina regions of the Sao Francisco Valley in Brazil. Certified and non-certified farmers as well as those in process to obtain certification were included in the sample. Empirical analysis using a logit model shows that grapes farmers have higher probability to certify than mango growers. There are two variables which have a positive and significant effect: education and experience. However, small-scale farms, the dependency on non-agricultural income and a trust-based arrangement have a negative but significant effect.
Molecular Network Analysis Suggests Aberrant CREB-Mediated Gene Regulation in the Alzheimer Disease Hippocampus

The pathogenesis of Alzheimer disease (AD) involves the complex interaction between genetic and environmental factors affecting multiple cellular pathways. Recent advances in systems biology provide a system-level understanding of AD by elucidating the genome-wide molecular interactions. By using KeyMolnet, a bioinformatics tool for analyzing molecular interactions on the curated knowledgebase, we characterized molecular network of 2,883 all stages of AD-related genes (ADGs) and 559 incipient AD-related genes (IADGs) identified by global gene expression profiling of the hippocampal CA1 region of AD brains in terms of significant clinical and pathological correlations (Blalock et al., Proc Natl Acad Sci USA 101: 2173-2178, 2004). By the common upstream search, KeyMolnet identified cAMP-response element-binding protein (CREB) as the principal transcription factor exhibiting the most significant relevance to molecular networks of both ADGs and IADGs. The CREB-regulated transcriptional network included upregulated and downregulated sets of ADGs and IADGs, suggesting an involvement of generalized deregulation of the CREB signaling pathway in the pathophysiology of AD, beginning at the early stage of the disease. To verify the in silico observations in vivo, we conducted immunohistochemical studies of 11 AD and 13 age-matched control brains by using anti-phoshorylated CREB (pCREB) antibody. An abnormal accumulation of pCREB imunoreactivity was identified in granules of granulovacuolar degeneration (GVD) in the hippocampal neurons of AD brains. These observations suggest that aberrant CREB-mediated gene regulation serves as a molecular biomarker of AD-related pathological processes, and support the hypothesis that sequestration of pCREB in GVD granules is in part responsible for deregulation of CREB-mediated gene expression in AD hippocampus.
Battlefield Agent Alliance decision-making Two Layer Reinforcement learning algorithm

In the background of Agent Alliance combat deduction, here we present a Two Layer Reinforcement learning algorithm, referred to a TLRL algorithm, for the special requirements of battlefield simulation environment Agents offensive and defensive decision-making study. The algorithm model is classified into two layers: one is the global decision-making Agent, called Commandant Agent, learning from the environment as well as both enemies' and friends' actions, the other is the Servant Agents optimizing the action by receiving local environment feedback. Finally the war situation deduction which is carried out on the simulation platform TBS we set up, has showed the fast convergence and effectiveness of this algorithm.
Reliable routing algorithm on wireless sensor network

This paper provides a novel routing algorithm CLQR (Cumulative Link Quality Routing Algorithm) which leverages LQI to provide a better routing scheme. Unlike other schemes providing maximum link quality, CLQR does not use probe packets to measure the link quality. Instead it uses cumulative link quality as a metric to choose better routing path. Result of simulation shows that it can hold a high throughput and improve path efficiency. Moreover, CLQR can balance network load and extend network life time.
Out-of-sample equity premium prediction: a complete subset quantile regression approach

This paper extends the complete subset linear regression framework to a quantile regression setting. We employ complete subset combinations of quantile forecasts in order to construct robust and accurate equity premium predictions. We show that our approach delivers statistically and economically significant out-of-sample forecasts relative to both the historical average benchmark, the complete subset mean regression approach and the single-variable quantile forecast combination approach. Our recursive algorithm that selects, in real time, the best complete subset for each predictive regression quantile succeeds in identifying the best subset in a time- and quantile-varying manner.
Rough Surfaces and Relief Extraction by Generalized Lambertian's Photometric Model

Within the framework of the analysis of 3D textured environment through image analysis, we approach here the case of the rough surfaces for the analysis of the local variations of their relief. Generally, the interaction between the light and these local relief variations leads to a textured image of these surfaces. The proposed approach is an original stereovision adaptation based on photometric model to the case of surfaces with a high degree of roughness and with Lambert's photometric behaviour. Indeed, the usual approach treats only the case of surfaces with weak roughness, without consideration of the phenomena such as interreflexions, shades or still maskings between elementary facets of surface. We propose to take into account these phenomena through the adaptation of Oren-Nayar's model for the photometric stereovision. A comparative study is done to put out the contribution of the proposed approach in the case of rough surfaces.