Miracle-dz/UniFAR-FTUs huggingface dataset:
Disturbed Laminar Blood Flow Vastly Augments Lipoprotein Retention in the Artery Wall: A Key Mechanism Distinguishing Susceptible From Resistant Sites.

OBJECTIVE Atherosclerosis develops initially at branch points and in areas of high vessel curvature. Moreover, experiments in hypercholesterolemic mice have shown that the introduction of disturbed flow in straight, atherosclerosis-resistant arterial segments turns them highly atherosclerosis susceptible. Several biomechanical mechanisms have been proposed, but none has been demonstrated. In the present study, we examined whether a causal link exists between disturbed laminar flow and the ability of the arterial wall to retain lipoproteins. APPROACH AND RESULTS Lipoprotein retention was detected at natural predilection sites of the murine thoracic aorta 18 hours after infusion of fluorescently labeled low-density lipoprotein. To test for causality between blood flow and the ability of these areas to retain lipoproteins, we manipulated blood flow in the straight segment of the common carotid artery using a constrictive collar. Disturbed laminar flow did not affect low-density lipoprotein influx, but increased the ability of the artery wall to bind low-density lipoprotein. Concordantly, disturbed laminar flow led to differential expression of genes associated with phenotypic modulation of vascular smooth muscle cells, increased expression of proteoglycan core proteins associated with lipoprotein retention, and of enzymes responsible for chondroitin sulfate glycosaminoglycan synthesis and sulfation. CONCLUSIONS Blood flow regulates genes associated with vascular smooth muscle cell phenotypic modulation, as well as the expression and post-translational modification of lipoprotein-binding proteoglycan core proteins, and the introduction of disturbed laminar flow vastly augments the ability of a previously resistant, straight arterial segment to retain lipoproteins.
The SOS Pilot Study: A RCT of Routine Oxygen Supplementation Early after Acute Stroke—Effect on Recovery of Neurological Function at One Week

Mild hypoxia is common after stroke and associated with poor long-term outcome. Oxygen supplementation could prevent hypoxia and improve recovery. A previous study of routine oxygen supplementation showed no significant benefit at 7 and 12 months. This pilot study reports the effects of routine oxygen supplementation for 72 hours on oxygen saturation and neurological outcomes at 1 week after a stroke. Methods Patients with a clinical diagnosis of acute stroke were recruited within 24 h of hospital admission between October 2004 and April 2008. Participants were randomized to oxygen via nasal cannulae (72 h) or control (room air, oxygen given only if clinically indicated). Clinical outcomes were assessed by research team members at 1 week. Baseline data for oxygen (n = 148) and control (n = 141) did not differ between groups. Results The median (interquartile range) National Institutes of Health Stroke Scale (NIHSS) score for the groups at baseline was 6 (7) and 5 (7) respectively. The median Nocturnal Oxygen Saturation during treatment was 1.4% (0.3) higher in the oxygen than in the control group (p<0.001) during the intervention. At 1 week, the median NIHSS score had reduced by 2 (3) in the oxygen and by 1 (2) in the control group. 31% of participants in the oxygen group and 14% in the control group had an improvement of ≥4 NIHSS points at 1 week doubling the odds of improvement in the oxygen group (OR: 2.9). Conclusion Our data show that routine oxygen supplementation started within 24 hours of hospital admission with acute stroke led to a small, but statistically significant, improvement in neurological recovery at 1 week. However, the difference in NIHSS improvement may be due to baseline imbalance in stroke severity between the two groups and needs to be confirmed in a larger study and linked to longer-term clinical outcome. Trial Registration Controlled-Trials.com ISRCTN12362720; European Clinical Trials Database 2004-001866-41
Area requirement and symmetry display in drawing graphs

A classical result shows that every planar graph admits a planar drawing with straight-line edges (struight-line druwing) [S, 25,26,34]. However, the existence of planar straight-line drawings with vertices placed at grid points (i.e., with integer coordinates) and polynomial area has been one of the most important and intriguing open problems in this field [23]. This question has been positively settled by de Fraysseix, Path and Pollack [9], and, independently, by Schnyder [24], who show that every n-vertex planar graph admits a planar straight-line drawing with vertices placed at grid points and 0 (n2) area.
The Memory-Enhancing Effects of Hippocampal Estrogen Receptor Activation Involve Metabotropic Glutamate Receptor Signaling

Our laboratory has demonstrated that 17β-estradiol (E2) enhances hippocampal memory consolidation via rapid activation of multiple intracellular signaling cascades, including the ERK/MAPK cascade (Fernandez et al., 2008; Fan et al., 2010). However, the receptor mechanisms responsible for these effects of E2 remain unclear. In vitro, estrogen receptor α (ERα) signaling through metabotropic glutamate receptor 1a (mGluR1a) leads to ERK-dependent CREB phosphorylation (Boulware et al., 2005), suggesting that interactions between ERs and mGluR1a may be vital to the memory-enhancing effects of E2. As such, the present study tested the roles of classical estrogen receptors (ERα and ERβ) and mGluR1a in mediating the effects of E2 on hippocampal memory consolidation. Dorsal hippocampal (DH) infusion of ERα (PPT) or ERβ (DPN) agonists enhanced novel object recognition and object placement memory in ovariectomized female mice in an ERK-dependent manner, suggesting that these receptors influence memory by rapidly activating hippocampal cell signaling. Next, DH infusion of the mGluR1a antagonist LY367385 blocked the object and spatial memory facilitation induced by E2, PPT, and DPN, demonstrating that ER/mGluR1a signaling is critical for the memory-enhancing effects of E2. Finally, we show that ERα, ERβ, mGluR1, and ERK all reside within specialized membrane microdomains of the DH, and that ERα and ERβ physically interact with mGluR1, providing a means through which ERs may activate mGluRs and downstream signaling. Together, these findings provide the first in vivo evidence demonstrating that ER/mGluR signaling can mediate the beneficial effects of E2 on hippocampal memory consolidation.
Transmitter Host IF RF IF RF IF RF IF RF RF IF RF IF RF IF RF IF Receiver Host IF

The HSDPA (High Speed Downlink Packet Access) mode of UMTS provides high data rates to the user. In this contribution comparisons, based on free space measurements, between SISO (Single Input Single Output) HSDPA and MIMO (Multiple Input Multiple Output) HSDPA are shown. For two transmit antennas the STTD (Space-Time Transmit Diversity) mode of UMTS is used to increase the diversity order of the transmission. Measurements with four transmit antennas are carried out incorporating the DSTTD-SGRC (Double Space-Time Transmit Diversity with Sub-Group Rate Control) proposal of MERL (Mitsubishi Electric Research Laboratories). Besides of the comparison of the various HSDPA schemes, this paper focuses on the setup of the radio frequency frontend and its requirements for MIMO transmissions.
Approximation Algorithms for Genome Rearrangements (sorting Signed Permutations by Reversals and Transpositions)

Recently, a new approach to analyze genomes evolving was proposed which is based on comparison of gene orders versus traditional comparison of DNA sequences (Sanko et al, 1992). The approach is based on the global rearrangements (e.g., inversions and transpositions of fragments). Analysis of genomes evolving by inversions and transpositions leads to a combinatorial problem of sorting by reversals and transpositions, i.e., sorting of a permutation using reversals and transpositions of arbitrary fragments. The problem is conjectured as NP-hard. We study sorting of signed permutations by reversals and transpositions, a problem which adequately models genome rearrangements, as the genes in DNA are oriented. We establish a lower bound and give two algorithms for the problem. Based on the lower bound, we show that the rst algorithm is a 2-approximation algorithm. The time complexity of the algorithm may not be bounded by Poly(n), where n is the length of the permutation to be sorted. Setting a time limit to the rst algorithm, we get the second algorithm which is a 2(1 + 1=k)-approximation one, where k 3 is any xed integer, and runs in Poly(n) time.
The Effects of Nutrition Package Claims, Nutrition Facts Panels, and Motivation to Process Nutrition Information on Consumer Product Evaluations

In a laboratory experiment using a between-subjects design, the authors examine the effects on nutrition and product evaluations of nutrition claims made (e.g., “99% fat free; ” “low in calories ”) on a product package, product nutrition value levels, and enduring motivation to process nutrition information. Enduring motivation is shown to moderate the effects of product nutrition value on consumer evaluations. Also, nutrition claims interact with product nutrition value in affecting consumer perceptions of manufacturer credibility. Given the availability of nutrient levels in the Nutrition Facts panel on the back of the mock package, nutrition claims on the front of the package generally did not affect positively consumers’ overall product and purchase intention evaluations. The authors discuss some implications of these findings, suggestions for further research, and study limitations. 1 1. The generalizability of the findings from this laboratory study may be restricted because the mock package used as the stimulus was examined outside of an actual in-store purchase environment. Because consumers in store settings may spend less time and care examining Nutrition Facts panels and are subject to a variety of other influences (Cole and Balasubramanian 1992), findings from this study may not generalize to such settings.
IMPROVING OOS USABILITY OF SOFTWARE TECHNOLOGY IN HIGHER EDUCATION IN CHINA

The increasing popularity and use of Open Source Software (OSS) have led to significant interests from research communities and enterprise practitioners, notably in higher education in China where this type of software offers particular benefits given the financial and human capital constraints faced. Software Technology assumes the mission of improving Intellectual Property (IP) and software innovation in China. The research looks at implications of the emerging IP regime for China and it attempts to improve software technological capabilities. The paper outlines how OSS can support the educational process of Software Technology in general and the WEB Application Development in particular. The primary objective is to identify suitable tools from the open-source landscape and then validate and prove their integration within a real-life Application Development scenario.
Absence of Exercise Capacity Improvement After Exercise Training Program: A Strong Prognostic Factor in Patients With Chronic Heart Failure

Background—Exercise training is established as adjuvant therapy for chronic heart failure, but the prognostic value of improvement in exercise capacity after exercise training has never been evaluated. Methods and Results—In this prospective bicentric study, all chronic heart failure patients with left ventricular ejection fraction <45% who underwent an exercise training program in a cardiac rehabilitation center between January 2004 and September 2006 were consecutively included. Improvement in exercise capacity was assessed by change in peak oxygen consumption (&dgr;PVo2) and in PVo2 expressed as a percentage of predicted PVo2 (&dgr;%PPVo2) measured before and after the training program. We included 155 patients (54±12 years old, male 81%, left ventricular ejection fraction=29.5±7.1%). Patients underwent 20 (10–30) training sessions. PVo2 and %PPVo2 were significantly increased after the training program (14% and 13%, respectively, P<0.001 for both). After 16±6 months follow-up, 27 patients had a cardiac event (death [n=12], cardiac transplantation [n=5], hospitalization for acute heart failure [n=10]). Univariate analysis revealed that among 17 significant predictors of cardiac events, the 2 more powerful ones were level of B-type natriuretic peptide at baseline (P<0.0001) and improvement in exercise capacity as assessed by &dgr;PVo2 and &dgr;%PPVo2 (P<0.0001). Multivariate analysis revealed B-type natriuretic peptide level and &dgr;%PPVo2 as only independent predictive factors of outcome (P=0.01). The risk ratio of cardiac events for nonresponse versus response to the training program (defined as median &dgr;%PPVo2<6%) was 8.2 (P=0.0006). Conclusions—Among patients with chronic heart failure, the lack of improvement in exercise capacity after an exercise training program has strong prognostic value for adverse cardiac events independent of classical predictive factors such as left ventricular ejection fraction, New York Heart Association class, and B-type natriuretic peptide level.
A Retargetable Full System Simulator for Thin Client Platform

There are varieties of hardware designs in high-end embedded systems, and the applications on it cover embedded areas and low-end desktop areas. Thin client is a typical high-embedded system in client/server and browser/server environment, which combines local and remote computing resources. This paper presents the design and implementation of Unichos, a full system simulator for thin client platform. Unichos focuses on retargetability for more architectures of thin client platforms by combining the retargetable instruction template and the extensible device model. Unichos models the complete target hardware system in object-oriented structure, and supports the unmodified Linux 2.4 kernel and all of the applications for thin client. In addition, Unichos can flexibly provide support for performance simulation in different level of detail. Finally, we introduce two case studies based on Unichos, which demonstrate the advantages of Unichos in performance evaluation.
A Conceptual Platform of SLA in Cloud Computing

Cloud computing is a promising technology, where the infrastructure, developing platform, software and storage are delivered as a service. With the development of cloud computing, more and more cloud service providers emerge. However, there are no metrics can be referred to compare these providers, so it is difficult for cloud consumers to select the most reliable providers or resources. Thus we present a platform of Services Level Agreement (SLA) in cloud computing. In the platform, we propose a Reputation System to evaluate the reliability of providers or resources to address this challenge, and we also propose a SLA template pool in order to make the SLA negotiation between cloud providers and cloud consumers become more equitable, transparent and convenient.
The Cycle of Reciprocity: A Social Capital Intervention Strategy for SSTR Operations

Abstract : Is it possible to initiate and sustain a positive cycle of reciprocity between competing actors in a Security, Stability, Transition and Reconstruction (SSTR) environment? The author postulates that an intervention strategy based on fostering "bridging social capital" between two or more competing parties stands a greater probability of success than an intervention strategy based primarily on an infusion of physical or human capital. The author reviews key literature of social capital and examines two cases involving a harvest initiative in Gnjilane, Kosovo (July-September 1999) and the "Village of Hope" in Mosul, Irag (January-December, 2004). Examination of these two instances of convincing recalcitrant ethnicity to cooperate for the greater good yields lessons in civil military relations and provides a template for intervention and for generating "bridging" social capital. Current practices in SSTR operations inadvertently establish a competitive dilemma by introducing significant amounts of fiscal and physical capital in a post-conflict environment. Ethnic groups compete with other groups for financial, human and information capital-to the detriment of the collective civil good. Recommendations for civilian and military interventionists include bringing competing ethnicity together in common, low-level microfinancial projects that foster bridging social capital between kinship-based social networks.
Automatically learning structural units in educational videos with the hierarchical hidden Markov models

In this paper we present a coherent approach using the hierarchical HMM with shared structures to extract the structural units form the building blocks of an education/training video. Rather than using hand-crafted approaches to define the structural units, we use the data from nine training videos to learn the parameters of the HHMM, and thus naturally extract the hierarchy. We then study this hierarchy and examine the nature of the structure at different levels of abstraction. Since the observable is continuous, we also show how to extend the parameter learning in the HHMM to deal with continuous observations.
Target and Non-Target Processing during Oddball and Cyberball: A Comparative Event-Related Potential Study

The phenomenon of social exclusion can be investigated by using a virtual ball-tossing game called Cyberball. In neuroimaging studies, structures have been identified which are activated during social exclusion. But to date the underlying mechanisms are not fully disclosed. In previous electrophysiological studies it was shown that the P3 complex is sensitive to exclusion manipulations in the Cyberball paradigm and that there is a correlation between P3 amplitude and self-reported social pain. Since this posterior event-related potential (ERP) was widely investigated using the oddball paradigm, we directly compared the ERP effects elicited by the target (Cyberball: “ball possession”) and non-target (Cyberball: “ball possession of a co-player) events in both paradigms. Analyses mainly focused on the effect of altered stimulus probabilities of the target and non-target events between two consecutive blocks of the tasks. In the first block, the probability of the target and non-target event was 33% (Cyberball: inclusion), in the second block target probability was reduced to 17%, and accordingly, non-target probability was increased to 66% (Cyberball: exclusion). Our results indicate that ERP amplitude differences between inclusion and exclusion are comparable to ERP amplitude effects in a visual oddball task. We therefore suggest that ERP effects–especially in the P3 range–in the Oddball and Cyberball paradigm rely on similar mechanisms, namely the probability of target and non-target events. Since the simulation of social exclusion (Cyberball) did not trigger a unique ERP response, the idea of an exclusion-specific neural alarm system is not supported. The limitations of an ERP-based approach will be discussed.
How Reliable Can Two-Path Protection Be?

This paper investigates the subject of reliability via two link-disjoint paths in mesh networks. We address the issues of how reliable two-path protection can be and how to achieve the maximum reliability. This work differs from traditional studies, such as MIN-SUM, MIN-MAX, and MIN-MIN, in that the objective in this paper is to maximize the reliability of the two-path connection given the link reliability, or equivalently, to minimize the end-to-end failure probability. We refer to this problem as MAX-REL. Solving MAX-REL provides 100% protection against a single failure while maximizing the reliability regardless of how many link failures occur in the network. We prove that this problem is NP-complete and derive a corresponding upper bound, which is the theoretical maximum reliability for a source-destination pair, and a lower bound, which is the worst case of the proposed algorithm. The time efficiency of the algorithms is analyzed, and the performance of the algorithms is evaluated through simulation. We demonstrate that our heuristic algorithms not only achieve a low computing complexity, but also achieve nearly equivalent performance to the upper bound.
Licensed under Creative Commons Attribution Cc by Unsupervised Feature Selection Algorithms: a Survey

The prodigious usage of features and variables are very high in most of the domains which are often unwanted and noisy . Feature selection is a method which is used to handle high dimensional data into dataset with less dimensions by eliminating most unwanted or repetitive features or attributes. Unsupervised feature selection means that the best features are selected among the large set of unlabelled data. some of the unsupervised feature selection algorithms namely, Clustering guided sparse structural learning(CGSSL), The Linked unsupervised feature selection(LUFS), Unsupervised spatial-spectral feature selection method, Unsupervised feature selection via optic diffraction principle, Joint embedded learning and sparse regression for unsupervised feature selection(JELSR). CGSSL is an iterative approach which integrates cluster analysis and sparse structural analysis and experimentally results are examined. The LUFS focuses on linked data to achieve linked information in selecting features and results are analyzed. The unsupervised spatial-spectral feature selection method bands are represented in prototype space and data are represented in pixel space and optimal features are obtained. Unsupervised feature selection method via optic diffraction principle based on the property of Fourier transform of probability density distribution. In JELSR embedding learning and sparse regression are fused and implemented. In this review paper, survey of above unsupervised feature selection algorithms are discussed.
A New Algorithm for Handling Expression Variation in 3D Face Recognition

We present a new algorithm for 3D face recognition, and compare its performance to that of previous approaches. We focus especially on the case of facial expression change between gallery and probe images. We first establish performance comparisons using a PCA (“eigenface”) algorithm and an ICP (iterative closest point) algorithm similar to ones reported in the literature. Experimental results show that the performance of either approach degrades substantially in the case of varying facial expression. Then we introduce a new algorithm that independently matches multiple facial regions and creates a fused result. This algorithm is fully automated and used no manually selected landmark points. Experimental results show that our new algorithm substantially improves performance in the case of varying facial expression. Our experimental results are based on the largest 3D face dataset to date, with 449 persons, over 4,000 3D images, and substantial lapse between gallery and probe images. This is the first study to compare the PCA and ICP approaches to 3D face recognition, and the first to propose a multiple-region approach to coping with expression variation in 3D face recognition.