Miracle-dz/UniFAR-FTUs huggingface dataset:
Glutaredoxin-1 Overexpression Enhances Neovascularization and Diminishes Ventricular Remodeling in Chronic Myocardial Infarction

Oxidative stress plays a critical role in the pathophysiology of cardiac failure, including the modulation of neovascularization following myocardial infarction (MI). Redox molecules thioredoxin (Trx) and glutaredoxin (Grx) superfamilies actively maintain intracellular thiol-redox homeostasis by scavenging reactive oxygen species. Among these two superfamilies, the pro-angiogenic function of Trx-1 has been reported in chronic MI model whereas similar role of Grx-1 remains uncertain. The present study attempts to establish the role of Grx-1 in neovascularization and ventricular remodeling following MI. Wild-type (WT) and Grx-1 transgenic (Grx-1Tg/+) mice were randomized into wild-type sham (WTS), Grx-1Tg/+ Sham (Grx-1Tg/+S), WTMI, Grx-1Tg/+MI. MI was induced by permanent occlusion of the LAD coronary artery. Sham groups underwent identical time-matched surgical procedures without LAD ligation. Significant increase in arteriolar density was observed 7 days (d) after surgical intervention in the Grx-1Tg/+MI group as compared to the WTMI animals. Further, improvement in myocardial functional parameters 30 d after MI was observed including decreased LVIDs, LVIDd, increased ejection fraction and, fractional shortening was also observed in the Grx-1Tg/+MI group as compared to the WTMI animals. Moreover, attenuation of oxidative stress and apoptotic cardiomyocytes was observed in the Grx-1Tg/+MI group as compared to the WTMI animals. Increased expression of p-Akt, VEGF, Ang-1, Bcl-2, survivin and DNA binding activity of NF-κB were observed in the Grx-1Tg/+MI group when compared to WTMI animals as revealed by Western blot analysis and Gel-shift analysis, respectively. These results are the first to demonstrate that Grx-1 induces angiogenesis and diminishes ventricular remodeling apparently through neovascularization mediated by Akt, VEGF, Ang-1 and NF-κB as well as Bcl-2 and survivin-mediated anti-apoptotic pathway in the infarcted myocardium.
Personalized news through content augmentation and profiling

This paper is concerned with the topic of personalized news assembly at the set-top box, based on augmented video. This is video complemented with additional information that is somehow relevant to the semantic video content. We touch upon the technique that is used for video augmentation, which is video subject detection followed by information searches on the subject. The focus of this paper is on subject detection implemented using traditional text analysis tools; video segmentation is based on these results and visual processing. We describe the architecture of such a system and the benefits to the consumer. Further we discuss a preliminary system that shows the viability of the concept.
Multicenter evaluation of the updated and extended API (RAPID) Coryne database 2.0

In a multicenter study, 407 strains of coryneform bacteria were tested with the updated and extended API (RAPID) Coryne system with database 2.0 (bioMérieux, La-Balme-les-Grottes, France) in order to evaluate the system's capability of identifying these bacteria. The design of the system was exactly the same as for the previous API (RAPID) Coryne strip with database 1.0, i.e., the 20 biochemical reactions covered were identical, but database 2.0 included both more taxa and additional differential tests. Three hundred ninety strains tested belonged to the 49 taxa covered by database 2.0, and 17 strains belonged to taxa not covered. Overall, the system correctly identified 90.5% of the strains belonging to taxa included, with additional tests needed for correct identification for 55.1% of all strains tested. Only 5.6% of all strains were not identified, and 3.8% were misidentified. Identification problems were observed in particular for Corynebacterium coyleae, Propionibacterium acnes, and Aureobacterium spp. The numerical profiles and corresponding identification results for the taxa not covered by the new database 2.0 were also given. In comparison to the results from published previous evaluations of the API (RAPID) Coryne database 1.0, more additional tests had to be performed with version 2.0 in order to completely identify the strains. This was the result of current changes in taxonomy and to provide for organisms described since the appearance of version 1.0. We conclude that the new API (RAPID) Coryne system 2.0 is a useful tool for identifying the diverse group of coryneform bacteria encountered in the routine clinical laboratory.
Anomaly detection for big log data using a Hadoop ecosystem

In this paper, we address a novel method to efficiently manage and analyze a large amount of log data. First, we present a new Apache Hive-based data storage and analysis architecture to process a large volume of Hadoop log data, which rapidly occur in multiple nodes. Second, we design and implement three simple but efficient anomaly detection methods. These methods use moving average and 3-sigma techniques to detect anomalies in log data. Finally, we show that all the three methods detect abnormal intervals properly, and the weighted anomaly detection methods are more precise than the basic one. These results indicate that our research is an excellent and simple approach in detecting anomalies of log data on a Hadoop ecosystem.
ScrewBender : Polyscrew Subdivision for Smoothing Interpolating Motions

An ordered series of control poses may be interpolated by a polyscrew rigid body motion composed of a series of screws, each interpolating a pair of consecutive control poses. The trajectory of each point during screw motion is (C∞). Although a polyscrew is continuous, velocities are typically discontinuous at control poses when the motion switches between screws. We obtain a smooth motion by subdividing the polyscrew. Three subdivision schemes are proposed: the interpolating 4-point subdivision, the smooth cubic B-spline subdivision, and the Jarek subdivision, an average of these two. Their implementation is trivial and their computation sufficiently fast for realtime subdivision and animation, which is particularly important for interactive motion editing and hardware support for animation.
An DWT-SVD Based Digital Image Watermarking Using a Novel Wavelet Analysis Function

Digital watermarking techniques have been developed to protect the copyright of multimedia objects such as text, audio, video, etc. In this paper, we propose SVD-based digital watermarking technique for robust watermarking of digital images for copyright protection. The security of the proposed scheme is increased by applying another wavelet function. We also demonstrate the good correlation between the embedded and the extracted watermark with the help of experimental results. One of the major advantages of the proposed scheme is the robustness of the technique on wide set of attacks. Analysis and experimental results show much improved performance of the proposed method in comparison with the pure SVD-based watermarking and the technique without using some wavelet function. Experimental results confirm that the proposed scheme provides good image quality of watermarked images.
Spatial Variation of Soil Seed Bank under Cushion Plants in a Subalpine Degraded Grassland

Cushion plants can affect wind speed and sediment movement patterns that probably modify the water and sediment redistribution along slopes and increase the accumulation of seeds under and around their canopies. This study was carried out to assess the spatial variability of soil seed bank (SSB) and seed bank composition around cushion plants to estimate the SSB potential for restoration of degraded area. Twenty cushions of Onobrychis cornuta were selected in a mountainous rangelands in northern Alborz in Iran, measuring density, richness and composition of SSB at four locations of each cushion (upslope edge, downslope edge, centre and outside). SSB composition and density were determined by seedling emergence method. The results showed that the locations of cushions had significant effect on density and richness of the SSBs. The highest SSB density and richness were observed in the centre and upslope edge of the cushions, while there was no significant differences of density and richness between downslope edge and outside (bare grassland soil) of the cushions. In addition, the results showed that seed bank composition was highly correlated between the four locations in the same cushion. We concluded that cushion plants can act as seed traps specially trapping seeds dispersed by barochory and hydrochory and therefore play an important role in conservation and recovery of degraded areas. Copyright © 2017 John Wiley & Sons, Ltd.
Revisiting Optimal Decoding for Machine Translation IBM Model 4

This paper revisits optimal decoding for statistical machine translation using IBM Model 4. We show that exact/optimal inference using Integer Linear Programming is more practical than previously suggested when used in conjunction with the Cutting-Plane Algorithm. In our experiments we see that exact inference can provide a gain of up to one BLEU point for sentences of length up to 30 tokens.
GPS forward model computing study on CPU/GPU co-processing parallel system using CUDA

Profiles of refraction and bending angle, which computed through the forward model for GPSRO (Global Positioning System radio occultation), are extremely important for GPS radio occultation data assimilation to the forecast system of NWP (Numerical Weather Prediction). The daily processing of GPS RO data in assimilation system costs amount of time, thus there is an urgent need to find a new way to reduce the computing time. GPU is suited for many data computation-intensive task and has emerged as an inexpensive high performance co-processor because of their tremendous computing power. In this paper, we demonstrate how forward model for GPS can be accelerated considerably by using throughput-oriented GPU on a standard PC. Our implementation is based on loop unrolling, CUDA stream, SPMD, and SIMD vector parallel computing. We have successfully implemented the forward model on single GPU platform, and then develop a simple CPU/GPU parallel cluster. The results on GTX 480 for a single-GPU show a speedup of up to 259 over CPU-based program. In comparison to a single node, the speedup on our cluster which has three nodes is 2.68. All results demonstrate that the forward model can be high efficiently parallelized on CPU/GPU cluster. Besides, it also indicates that the cluster has good scalability.
Detecting uber-operons in prokaryotic genomes

We present a study on computational identification of uber-operons in a prokaryotic genome, each of which represents a group of operons that are evolutionarily or functionally associated through operons in other (reference) genomes. Uber-operons represent a rich set of footprints of operon evolution, whose full utilization could lead to new and more powerful tools for elucidation of biological pathways and networks than what operons have provided, and a better understanding of prokaryotic genome structures and evolution. Our prediction algorithm predicts uber-operons through identifying groups of functionally or transcriptionally related operons, whose gene sets are conserved across the target and multiple reference genomes. Using this algorithm, we have predicted uber-operons for each of a group of 91 genomes, using the other 90 genomes as references. In particular, we predicted 158 uber-operons in Escherichia coli K12 covering 1830 genes, and found that many of the uber-operons correspond to parts of known regulons or biological pathways or are involved in highly related biological processes based on their Gene Ontology (GO) assignments. For some of the predicted uber-operons that are not parts of known regulons or pathways, our analyses indicate that their genes are highly likely to work together in the same biological processes, suggesting the possibility of new regulons and pathways. We believe that our uber-operon prediction provides a highly useful capability and a rich information source for elucidation of complex biological processes, such as pathways in microbes. All the prediction results are available at our Uber-Operon Database: , the first of its kind.
Protein secondary structure prediction using support vector machines and a codon encoding scheme

In this study, we evaluate the performance of a protein secondary structure prediction model using a new amino acid "codon" encoding inspired by genetic codon mappings. The dimensionality of the binary codon encoding is less than that of an orthogonal encoding which requires less computations. Protein secondary structure prediction is an important step for machine learning techniques ultimately applied for protein 3D structure prediction. In the proposed model, one-stage binary support vector machines are employed, and the efficiency of the codon encoding to that of a commonly used orthogonal encoding are compared without incorporating protein evolutionary and structural information for an unbiased comparison. The performance of the classification model is measured according to Q3 and segment overlap (SOV) scores. The scores are compared with those of the prediction methods using an orthogonal encoding and protein sequence profiles. The experimental results indicate higher prediction accuracy based on Q3 SOV scores when sequence profiles are not used. Also, the relative classification scores of the proposed method are comparable with the methods incorporating protein global and evolutionary information. The experimental result implies the encoding scheme is able to integrate the evolutionary information into the prediction model since the encoding is based on genetic codon mappings which are the building blocks of amino acid formations at the primary level of biological processes. The codon encoding is worthwhile to be investigated using more complex learning architectures with the profiles and structural properties of proteins.
Expanding human interactions for in-depth testing of web applications

Over the last years, the complexity of web applications has grown significantly, challenging desktop programs in terms of functionality and design. Along with the rising popularity of web applications, the number of exploitable bugs has also increased significantly. Web application flaws, such as cross-site scripting or SQL injection bugs, now account for more than two thirds of the reported security vulnerabilities. Black-box testing techniques are a common approach to improve software quality and detect bugs before deployment. There exist a number of vulnerability scanners, or fuzzers, that expose web applications to a barrage of malformed inputs in the hope to identify input validation errors. Unfortunately, these scanners often fail to test a substantial fraction of a web application’s logic, especially when this logic is invoked from pages that can only be reached after filling out complex forms that aggressively check the correctness of the provided values. In this paper, we present an automated testing tool that can find reflected and stored cross-site scripting (XSS) vulnerabilities in web applications. The core of our system is a black-box vulnerability scanner. This scanner is enhanced by techniques that allow one to generate more comprehensive test cases and explore a larger fraction of the application. Our experiments demonstrate that our approach is able to test more thoroughly these programs and identify more bugs than a number of open-source and commercial web vulnerability scanners.
The implications of program genres for the design of social television systems

In this paper, we look at how television genres can play a role in the use of social interactive television systems (social iTV). Based on a user study of a system for sending and receiving enriched video fragments to and from a range of devices, we discuss which genres are preferred for talking while watching, talking about after watching and for sending to users with different devices. The results show that news, soap, quiz and sport are genres during which our participants talk most while watching and are thus suitable for synchronous social iTV systems. For asynchronous social iTV systems film, news, documentaries and music programs are potentially popular genres. The plot structure of certain genres influences if people are inclined to talk while watching or not, and to which device they would send a video fragment. We also discuss how this impacts the design and evaluation of social iTV systems.
Staying agile in government software projects

Can government software projects be agile? What do Scrum and XP practices have to offer in this regulated and highly political environment? In this experience report, I will discuss some of the unique challenges in our environment and how we have had to adapt these practices to produce commercial-grade software. I will provide a "report card" on our progress in applying Scrum and XP practices to a clinical data management project over a two-year period. In addition, I will describe the practices that were accepted "religiously", adapted to get the job done, and abandoned completely. In particular, I will discuss how we got around bootstrapping, rational tools, documentation needs, and managing a product backlog for a diverse, decentralized user community. Putting these practices to work was hard, but they resulted in better team communication, a more usable product, and improved partnership between the users and the development team. In addition, staying agile is just as hard as becoming agile.
An Exploration of Differential Utility in Iterated Prisoner's Dilemma

While prisoner's dilemma has frequently been used in studies of animal behavior, past work in the area fails to address the question of differential utility. As animals needs change, their behavior also changes. A hungry animal may be less likely to cooperate than a full one. In this study an abstract species is modelled using an energy balance computation that assigns a state of hungry, full, or neither to a given animal together with a modified finite state representation for a prisoner's dilemma strategy that implements distinct but linked strategies for each possible state. The strategy used is conditioned on the animal's current hunger state. An evolutionary algorithm is used to generate effective strategies for this deterministic form of differential utility prisoner's dilemma. A tool called fingerprinting is used to document the strategies that arise. It is shown that the strategies that arise for the three possible hunger states have different distributions among known strategies and also differ from a baseline experiment in which agents are evolved to play prisoner's dilemma without any form of differential utility
Dynamics of load-sensitive adaptive routing

Shortest path first (SPF) routing protocols, such as OSPF and IS-IS are currently the dominant intra-domain IP routing protocols and are widely used in the ISP backbones. Although the traffic on the Internet is highly dynamic, OSPF and IS-IS are not adaptive to the changing traffic, because the shortest path generated by these protocols are based on the link weights, which are fixed and usually can not be changed during network operation. This paper investigates a way of changing the weights in OSPF/IS-IS adaptively according to the changing traffic load on the links. The feedback effect and the stability issue of adaptive routing are analyzed from a control system point of view. The paper shows why minimal-delay adaptive routing, such as the routings in the early ARPANET, is not stable, and proposes some techniques to make our load-sensitive adaptive routing (LSAR) stable. Finally, the performance of LSAR is evaluated by simulation. The result shows that LSAR can significantly improve the QoS of the network by increasing network throughput and reducing packet drop ratio.
The X Chromosome of Hemipteran Insects: Conservation, Dosage Compensation and Sex-Biased Expression

Insects of the order Hemiptera (true bugs) use a wide range of mechanisms of sex determination, including genetic sex determination, paternal genome elimination, and haplodiploidy. Genetic sex determination, the prevalent mode, is generally controlled by a pair of XY sex chromosomes or by an XX/X0 system, but different configurations that include additional sex chromosomes are also present. Although this diversity of sex determining systems has been extensively studied at the cytogenetic level, only the X chromosome of the model pea aphid Acyrthosiphon pisum has been analyzed at the genomic level, and little is known about X chromosome biology in the rest of the order. In this study, we take advantage of published DNA- and RNA-seq data from three additional Hemiptera species to perform a comparative analysis of the gene content and expression of the X chromosome throughout this clade. We find that, despite showing evidence of dosage compensation, the X chromosomes of these species show female-biased expression, and a deficit of male-biased genes, in direct contrast to the pea aphid X. We further detect an excess of shared gene content between these very distant species, suggesting that despite the diversity of sex determining systems, the same chromosomal element is used as the X throughout a large portion of the order.
Optimal power cost management using stored energy in data centers

Since the electricity bill of a data center constitutes a significant portion of its overall operational costs, reducing this has become important. We investigate cost reduction opportunities that arise by the use of uninterrupted power supply (UPS) units as energy storage devices. This represents a deviation from the usual use of these devices as mere transitional fail-over mechanisms between utility and captive sources such as diesel generators. We consider the problem of opportunistically using these devices to reduce the time average electric utility bill in a data center. Using the technique of Lyapunov optimization, we develop an online control algorithm that can optimally exploit these devices to minimize the time average cost. This algorithm operates without any knowledge of the statistics of the workload or electricity cost processes, making it attractive in the presence of workload and pricing uncertainties. An interesting feature of our algorithm is that its deviation from optimality reduces as the storage capacity is increased. Our work opens up a new area in data center power management.