Miracle-dz/UniFAR-FTUs huggingface dataset:
Purple grape juice improves endothelial function and reduces the susceptibility of LDL cholesterol to oxidation in patients with coronary artery disease.

BACKGROUND In vitro, the flavonoid components of red wine and purple grape juice are powerful antioxidants that induce endothelium-dependent vasodilation of vascular rings derived from rat aortas and human coronary arteries. Although improved endothelial function and inhibition of LDL oxidation may be potential mechanisms by which red wine and flavonoids reduce cardiovascular risk, the in vivo effects of grape products on endothelial function and LDL oxidation have not been investigated. This study assessed the effects of ingesting purple grape juice on endothelial function and LDL susceptibility to oxidation in patients with coronary artery disease (CAD). METHODS AND RESULTS Fifteen adults with angiographically documented CAD ingested 7.7+/-1.2 mL. kg(-1). d(-1) of purple grape juice for 14 days. Flow-mediated vasodilation (FMD) was measured using high-resolution brachial artery ultrasonography. Susceptibility of LDL particles to oxidation was determined from the rate of conjugated diene formation after exposure to copper chloride. At baseline, FMD was impaired (2.2+/-2. 9%). After ingestion of grape juice, FMD increased to 6.4+/-4.7% (P=0.003). In a linear regression model that included age, artery diameter, lipid values, and use of lipid-lowering and antioxidant therapies, the effect of grape juice on FMD remained significant (mean change 4.2+/-4.4%, P<0.001). After ingestion of grape juice, lag time increased by 34.5% (P=0.015). CONCLUSIONS Short-term ingestion of purple grape juice improves FMD and reduces LDL susceptibility to oxidation in CAD patients. Improved endothelium-dependent vasodilation and prevention of LDL oxidation are potential mechanisms by which flavonoids in purple grape products may prevent cardiovascular events, independent of alcohol content.
Damage response of XRCC 1 at sites of DNA single strand breaks is regulated by phosphorylation and ubiquitination after degradation of poly ( ADP ) ribose Running title : XRCC 1 dissociation kinetics in live cells

Affiliation 1 Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA 2 Division of Dynamic Proteome; Institute of Development, Aging, and Cancer; Tohoku University, Seiryomachi 4-1, Sendai 980-8575, Japan 3 Division of Genome Stability Research, National Cancer Center Research Institute, Tsukiji 5-1-1, Tokyo, 104-0045 Japan
A flow label hash compression method applied to IPv6 network traffic analysis system

With the development of IPv6 network and the rapid increase of IPv6 network traffic. To meet the increasing demand on IPv6 network management, it requires the identification, analysis and statistics on IPv6 network traffic. In this paper, we propose a method which makes hash compression on IPv6 flow label in network traffic management devices, and also undertake performance analysis and research on Hash Collision Probability and False Positive Rate caused by this method.
Towards Leakage Containment

Functional programs are organized into procedures, each encapsulating a speci c task. A procedure should not cause its callers to repeat its work. This forced repetition of work we call leakage. In this paper we describe several common instances of leakage, and show how they can be eliminated using an extension of continuation-passing style.
Text independent automatic speaker recognition system in Malayalam

Due to the rapid advances in algorithms, VLSI design and computer technology, security systems based on speaker recognition are on the verge of commercial success. In this thesis, an improved strategy for Text Tndependent Automatic Speaker Verification (TI-ASV) system based on Malayalam has been proposed and results are observed. The system performs on Gaussian Mixture Model (GMM) technique with cepstral based features. Different speech pre-processing techniques like pre-emphasis filtering, frame blocking and windowing have been used to process the speech utterances. MFCC, ΔMFCC and ΔΔMFCC have been used to extract the features. Speaker identification is performed using Continuous Hidden Markov Model. The performance is analyzed in terms of Percentage Correctness (PC) and accuracy. An application with Graphical User Interface (GUI) is also developed for security purposes using the system. The system is developed using the framework of Hidden Markov Model Tool Kit (HTK).
A practical solution for functional reconfiguration of real-time service based applications through partial schedulability

Timely reconfiguration in distributed real-time systems is a complex problem with many sides to it ranging from system-wide concerns down to the intrinsic non-robust nature of the specific middleware software and the used programming techniques. In an completely open distributed system, it is not possible to achieve time-deterministic functional reconfiguration; the set of possible target configurations that the system can transition to could be extremely large threatening the temporal predictability of the reconfiguration process. Therefore, a set of bounds and limitations to the structure of systems and to their open nature need to be imposed. In this paper, we present the different sides of the problem of reconfiguration. We provide a solution for timely reconfiguration based on reducing the solution space of solutions of partially closed applications; we have enhanced the logic of a middleware for distributed soft real-time applications with the proposed technique. As a result, applications require a limited number of schedulability tests to search for the valid target configuration. We present some results on the actual reduction of the configuration space achieved by our middleware. Keywords-reconfiguration; distributed systems; middleware;
FAULT DETECTION AND ISOLATION USING SPECTRAL ANALYSIS

In this work, spectral signal analyses are employed in fault detection and isolation scheme. The procedure was applied to detect the presence of fault in proces and suppose the processing in frequency domain of the data acquisition, which represent the known commands and the actual measure outcome. The approach has been applied to electrical motor and the results show that the fault detection scheme designed can detect incipient faults. Also, the effects of faults on the diagnostic residuals are maximised. The technique was tested by simulation and the results are good.
Suppression of arthritis by an inhibitor of nitric oxide synthase

Nitric oxide (NO), a toxic radical gas produced during the metabolism of L-arginine by NO synthase (NOS), has been implicated as a mediator of immune and inflammatory responses. A single injection of streptococcal cell wall fragments (SCW) induces the accumulation of inflammatory cells within the synovial tissue and a cell-mediated immune response that leads destructive lesions. We show here that NO production is elevated in the inflamed joints of SCW-treated rats. Administration of NG-monomethyl-L-arginine, an inhibitor of NOS, profoundly reduced the synovial inflammation and tissue damage as measured by an articular index and reflected in the histopathology. These studies implicate the NO pathway in the pathogenesis of an inflammatory arthritis and demonstrate the ability of a NOS inhibitor to modulate the disease.
Systematic Generation Of Models For Crystal Structures

A method is given for the systematic generation of graphs representing known or hypothetical polyhedral topologies of crystals. The method is complete for some interesting types of polyhedral topologies insofar as all topologies which are possible under reasonable assumptions concerning crystal properties are generated. Restriction modules can be coupled with the enumeration algorithm such that only graphs are obtained representing topologies with speciic properties. For tetrahedral topologies, a technique is described for the embedding of graphs into three{dimensional Euclidean space.
Association between cervical lesion grade and micronucleus frequency in the Papanicolaou test

The aim of this study was to evaluate the association between the frequency of micronuclei (MN) and the cellular changes detected in the conventional Papanicolaou test. One hundred and seventy-four Papanicolaou test smears with cellular changes were examined. MN screening was done in cytopathological smears by counting 1,000 cervical cells in a light microscope. MN frequencies were significantly higher in the group with cellular changes compared to the control group (p < 0.001). The mean MN frequencies were 0.95 ± 1.12 (mean ± SD) in the control group (n = 223), 2.98 ± 1.20 in individuals with atypical squamous cells of undetermined significance (ASC-US) (n = 50), 4.04 ± 1.45 in cervical intraepithelial neoplasia (CIN) I (n = 52), 5.97 ± 1.83 in CIN II (n = 30), 7.29 ± 1.55 in CIN III (n = 17) and 8.64 ± 1.55 in invasive cancer (n = 25). These findings suggest that MN monitoring should be included as an additional criterion for the early detection of cytogenetic damage in routine examinations. This monitoring should be done in the same smear as used for cytopathological examination. More specific and systematic studies are necessary to confirm this proposal.
Extended Metaphors are the Home Runs of Persuasion: Don’t Fumble the Phrase

ABSTRACT Metaphors pervade discussions of critical issues and influence how people reason about these domains. For instance, when crime is a beast people are more likely to suggest enforcement-oriented approaches to crime-reduction (e.g., by augmenting the police force); reading that crime is a virus, on the other hand, leads people to suggest systemic reforms for the affected community. In the current study, we find that extending metaphoric language into the descriptions of policy interventions bolstered the persuasive influence of metaphoric frames for important issues. That is, in response to a crime virus people were even more likely to endorse social reforms that were described as “treatments,” while in response to a crime beast people were even more likely to endorse “attacking” the problem with harsh enforcement tactics. Of note, people were not simply drawn to extensions of previously instantiated metaphors: when extended metaphors were paired with a conceptually incongruent policy intervention (e.g., “treating” a crime [virus] by augmenting the police force), we found no preference for the policy response.
A CMOS smart temperature sensor with a 3/spl sigma/ inaccuracy of /spl plusmn/0.1/spl deg/C from -55/spl deg/C to 125/spl deg/C

A smart temperature sensor in 0.7 /spl mu/m CMOS is accurate to within /spl plusmn/0.1/spl deg/C (3/spl sigma/) over the full military temperature range of -55/spl deg/C to 125/spl deg/C. The sensor uses substrate PNP transistors to measure temperature. Errors resulting from nonidealities in the readout circuitry are reduced to the 0.01/spl deg/C level. This is achieved by using dynamic element matching, a chopped current-gain independent PTAT bias circuit, and a low-offset second-order sigma-delta ADC that combines chopping and correlated double sampling. Spread of the base-emitter voltage characteristics of the substrate PNP transistors is compensated by trimming, based on a calibration at one temperature. A high trimming resolution is obtained by using a sigma-delta current DAC to fine-tune the bias current of the bipolar transistors.
Anomaly Detection Based on Sensor Data in Petroleum Industry Applications

Anomaly detection is the problem of finding patterns in data that do not conform to an a priori expected behavior. This is related to the problem in which some samples are distant, in terms of a given metric, from the rest of the dataset, where these anomalous samples are indicated as outliers. Anomaly detection has recently attracted the attention of the research community, because of its relevance in real-world applications, like intrusion detection, fraud detection, fault detection and system health monitoring, among many others. Anomalies themselves can have a positive or negative nature, depending on their context and interpretation. However, in either case, it is important for decision makers to be able to detect them in order to take appropriate actions. The petroleum industry is one of the application contexts where these problems are present. The correct detection of such types of unusual information empowers the decision maker with the capacity to act on the system in order to correctly avoid, correct or react to the situations associated with them. In that application context, heavy extraction machines for pumping and generation operations, like turbomachines, are intensively monitored by hundreds of sensors each that send measurements with a high frequency for damage prevention. In this paper, we propose a combination of yet another segmentation algorithm (YASA), a novel fast and high quality segmentation algorithm, with a one-class support vector machine approach for efficient anomaly detection in turbomachines. The proposal is meant for dealing with the aforementioned task and to cope with the lack of labeled training data. As a result, we perform a series of empirical studies comparing our approach to other methods applied to benchmark problems and a real-life application related to oil platform turbomachinery anomaly detection.
Using Scan-Dump Values to Improve Functional-Diagnosis Methodology

In this paper, we identify two main bottlenecks in the functional diagnosis flow and propose new ways to overcome these. Our approach completely eliminates the "primary input (PI) pattern generation and simulation" step and instead employs scan-dump values extracted from the tester. We utilize backward and forward logic implications of the scan-dump values to reconstruct more logic values for the circuit signals. Furthermore, we employ the reset state for the non-scan latches of the design to increase the number of specified signals in the overall circuit. Experimental results on stuck-at faults on industrial designs show that, in most cases, these reconstructed values are sufficient to correctly diagnose a fault, thereby avoiding hours of conventional functional diagnosis runtimes.
Towards a completely implantable, light-sensitive intraocular retinal prosthesis

A completely implantable, light-sensitive retinal prosthesis must include the capability for both phototransduction and stimulus current generation, two power intensive functions. These devices will be implanted in the eye, creating a significant source of heat that must be dissipated by the ocular tissue without damaging the retina. However, significant technological hurdles remain. The amount of heat that can be safely dissipated by the eye and surrounding head without harming the retina, depends significantly on the position of the heater. Technology for, a high-density electrode array is advancing, but high-quality wires of biocompatible material in dimensions usable for a retinal prosthesis material have yet to be achieved.
Nonvisual and Visual Object Shape Representations in Occipitotemporal Cortex: Evidence from Congenitally Blind and Sighted Adults

Knowledge of object shape is primarily acquired through the visual modality but can also be acquired through other sensory modalities. In the present study, we investigated the representation of object shape in humans without visual experience. Congenitally blind and sighted participants rated the shape similarity of pairs of 33 familiar objects, referred to by their names. The resulting shape similarity matrices were highly similar for the two groups, indicating that knowledge of the objects' shapes was largely independent of visual experience. Using fMRI, we tested for brain regions that represented object shape knowledge in blind and sighted participants. Multivoxel activity patterns were established for each of the 33 aurally presented object names. Sighted participants additionally viewed pictures of these objects. Using representational similarity analysis, neural similarity matrices were related to the behavioral shape similarity matrices. Results showed that activity patterns in occipitotemporal cortex (OTC) regions, including inferior temporal (IT) cortex and functionally defined object-selective cortex (OSC), reflected the behavioral shape similarity ratings in both blind and sighted groups, also when controlling for the objects' tactile and semantic similarity. Furthermore, neural similarity matrices of IT and OSC showed similarities across blind and sighted groups (within the auditory modality) and across modality (within the sighted group), but not across both modality and group (blind auditory–sighted visual). Together, these findings provide evidence that OTC not only represents objects visually (requiring visual experience) but also represents objects nonvisually, reflecting knowledge of object shape independently of the modality through which this knowledge was acquired.
DCSH - Matching Patches in RGBD Images

We extend patch based methods to work on patches in 3D space. We start with Coherency Sensitive Hashing (CSH), which is an algorithm for matching patches between two RGB images, and extend it to work with RGBD images. This is done by warping all 3D patches to a common virtual plane in which CSH is performed. To avoid noise due to warping of patches of various normals and depths, we estimate a group of dominant planes and compute CSH on each plane separately, before merging the matching patches. The result is DCSH - an algorithm that matches world (3D) patches in order to guide the search for image plane matches. An independent contribution is an extension of CSH, which we term Social-CSH. It allows a major speedup of the k nearest neighbor (kNN) version of CSH - its runtime growing linearly, rather than quadratic ally, in k. Social-CSH is used as a subcomponent of DCSH when many NNs are required, as in the case of image denoising. We show the benefits of using depth information to image reconstruction and image denoising, demonstrated on several RGBD images.
Periodontal Responses to Augmented Corticotomy with Collagen Membrane Application during Orthodontic Buccal Tipping in Dogs

This prospective randomized split-mouth study was performed to examine the effects of absorbable collagen membrane (ACM) application in augmented corticotomy using deproteinized bovine bone mineral (DBBM), during orthodontic buccal tipping movement in the dog. After buccal circumscribing corticotomy and DBBM grafting into the decorticated area, flaps were repositioned and sutured on control sides. ACM was overlaid and secured with membrane tacks, on test sides only, and the flaps were repositioned and sutured. Closed coil springs were used to apply 200 g orthodontic force in the buccolingual direction on the second and third premolars, immediately after primary flap closure. The buccal tipping angles were 31.19 ± 14.60° and 28.12 ± 11.48° on the control and test sides, respectively. A mean of 79.5 ± 16.0% of the buccal bone wall was replaced by new bone on the control side, and on the test side 78.9 ± 19.5% was replaced. ACM application promoted an even bone surface. In conclusion, ACM application in augmented corticotomy using DBBM might stimulate periodontal tissue reestablishment, which is useful for rapid orthodontic treatment or guided bone regeneration. In particular, ACM could control the formation of mesenchymal matrix, facilitating an even bone surface.
Low-cost open-page prefetch scheduling in chip multiprocessors

The pressure on off-chip memory increases significantly as more cores compete for the same resources. A CMP deals with the memory wall by exploiting thread level parallelism (TLP), shifting the focus from reducing overall memory latency to memory throughput. This extends to the memory controller where the 3D structure of modern DRAM is exploited to increase throughput. Traditionally, prefetching reduces latency by fetching data before it is needed. In this paper we explore how prefetching can be used to increase memory throughput. We present our own low-cost open-page prefetch scheduler that exploits the 3D structure of DRAM when issuing prefetches. We show that because of the complex structure of modern DRAM, prefetches can be made cheaper than ordinary reads, thus making prefetching beneficial even when prefetcher accuracy is low. As a result, prefetching with good coverage is more important than high accuracy. By exploiting this observation our low-cost open page scheme increases performance and QoS. Furthermore, we explore how prefetches should be scheduled in a state of the art memory controller by examining sequential, scheduled region, CZone/delta correlation and reference prediction table prefetchers.
A miniature multi-joint wall-climbing robot based on new Vibration Suction Robotic Foot

Vibration suction method (VSM) is a new kind of suction strategy for wall-climbing robot. The first vibration suction robotic foot (VSRF) was built and tested to verify the applicability of VSM in former works. But the suction capability, safety, and wall adaptability of the first VSRF are not enough. A new generation of VSRF was designed, fabricated and tested. Experiment results show that the new robotic foot performs better than the former design. A miniature multi-joint wall-climbing robot was designed and implemented based on the new VSRF. Kinematics analysis and gait planning of the robot were made. Experiments proved that this robot can finish three kinds of walking function: walking in straight line, turning and making face-to-face transfer successfully.
Gravitino Dark Matter in the CMSSM With Improved Constraints from BBN

In the framework of the Constrained MSSM we re--examine the gravitino as the lightest superpartner and a candidate for cold dark matter in the Universe. Unlike in other recent studies, we include both a thermal contribution to its relic population from scatterings in the plasma and a non--thermal one from neutralino or stau decays after freeze--out. Relative to a previous analysis [1] we update, extend and considerably improve our treatment of constraints from observed light element abundances on additional energy released during BBN in association with late gravitino production. Assuming the gravitino mass in the GeV to TeV range, and for natural ranges of other supersymmetric parameters, the neutralino region is excluded, while for smaller values of the gravitino mass it becomes allowed again. The gravitino relic abundance is consistent with observational constraints on cold dark matter from BBN and CMB in some well defined domains of the stau region but, in most cases, only due to a dominant contribution of the thermal population. This implies, depending on the gravitino mass, a large enough reheating temperature. If $\mgravitino>1$ GeV then $T_R>10^7$ GeV, if allowed by BBN and other constraints but, for light gravitinos, if $\mgravitino>100$ keV then $T_R>3\times 10^3$ GeV. On the other hand, constraints mostly from BBN imply an upper bound $T_R \lsim {a few}x 10^8\times10^9$ GeV which appears inconsistent with thermal leptogenesis. Finally, most of the preferred stau region corresponds to the physical vacuum being a false vacuum. The scenario can be partially probed at the LHC.
On a Topic Model for Sentences

Probabilistic topic models are generative models that describe the content of documents by discovering the latent topics underlying them. However, the structure of the textual input, and for instance the grouping of words in coherent text spans such as sentences, contains much information which is generally lost with these models. In this paper, we propose sentenceLDA, an extension of LDA whose goal is to overcome this limitation by incorporating the structure of the text in the generative and inference processes. We illustrate the advantages of sentenceLDA by comparing it with LDA using both intrinsic (perplexity) and extrinsic (text classification) evaluation tasks on different text collections.