Miracle-dz/UniFAR-FTUs huggingface dataset:
SideStep – An Open , Scalable Detouring Service

For both technological and economic reasons, the default path between two end systems in the wide-area Internet can be suboptimal. This has motivated a number of systems that attempt to improve reliability and performance by routing over one or more hops in an overlay. Most of the proposed solutions, however, fall at an extreme in the cost-performance trade-off. While some provide near-optimal performance with an unscalable measurement overhead, others avoid measurement when selecting routes around network failures but make no attempt to optimize performance. We present SideStep, the first globally scalable detouring service that provides high-performance detour paths with a small, constant measurement overhead per node. SideStep’s efficiency comes from its strategic reuse of measurements from other large-scale distributed systems — namely content distribution networks (CDNs). Our approach is to use CDN redirections as hints (i.e. potentially inexact information used to improve a system’s efficiency) on network conditions. By carefully observing these redirection s, higher performance paths can readily be found with little overhead and no active network measurement. We present results from an evaluation of more than 9,000 paths between 133 widely-distributed hosts over a six-week period. In our study, we find that over half of the alternative paths identified through CDN redirections yielded performance improvements over the default one. Of those, 75% resulted in noticeable TCP throughput improvements while over 11% more than doubled throughput as compared to the direct path. Finally, we demonstrate the practicality o f our approach by implementing an FTP suite that uses our publicly available SideStep library to seamlessly take advantage of these improved Internet routes.
Novel Mechanism and Role of Angiotensin II–Induced Vascular Endothelial Injury in Hypertensive Diastolic Heart Failure

Objective—The mechanism and role of angiotensin II–induced vascular endothelial injury is unclear. We examined the molecular mechanism of angiotensin (AII)-induced vascular endothelial injury and its significance for hypertensive diastolic heart failure. Methods and Results—We compared the effect of valsartan and amlodipine on Dahl salt-sensitive hypertensive rats (DS rats). Valsartan improved vascular endothelial dysfunction of DS rats more than amlodipine, by inhibiting endothelial apoptosis and eNOS uncoupling more. Moreover, valsartan inhibited vascular apoptosis signal-regulating kinase 1 (ASK1) more than amlodipine. Thus, AT1 receptor contributed to vascular endothelial apoptosis, eNOS uncoupling, and ASK1 activation of DS rats. Using ASK1−/− mice, we examined the causative role of ASK1 in endothelial apoptosis and eNOS uncoupling. AII infusion in wild-type mice markedly caused vascular endothelial apoptosis and eNOS uncoupling accompanied by vascular endothelial dysfunction, whereas these effects of AII were absent in ASK1−/− mice. Therefore, ASK1 participated in AII-induced vascular endothelial apoptosis and eNOS uncoupling. Using tetrahydrobiopterin, we found that eNOS uncoupling was involved in vascular endothelial dysfunction in DS rats with established diastolic heart failure. Conclusion—AII-induced vascular endothelial apoptosis and eNOS uncoupling were mediated by ASK1 and contributed to vascular injury in diastolic heart failure of salt-sensitive hypertension.
Social Structures: A Network Approach

Part 1 Thinking structurally: structural analysis - from method to metaphor to theory and substance, Barry Wellman understanding simple social structure - kinship units and ties, Nancy Howell the duality of persons and groups, Ronald L.Briger the ralational basis of attitudes, Bonnie Erickson. Part 2 Communities: Networks as personal communities, Barry Wellman, Peter Carrington and Alan Hall work and community in industrializing India, Leslie Howard relations of production and class rule - the hidden basis of patron-clientage, Y.Michal Bodemann. Part 3 Markets: varieties of markets, Harrison White markets and market-areas - some preliminary formulations, S.D. Berkowitz form and substance in the analysis of the world economy, Harriet Friedmann. Part 4 Social change: misreading, then re-reading, 19th-century social change, Charles Tilly structural location and ideological divergence - Jewish Marxist intellectuals in turn-of-the-century Russia, Robert J.Bryam cities and fights - material entailment analysis of the 18th-century chemical revolution, Douglas R.White and H.Gilman McCann. Part 5 Social mobility: collectivity mobility and the persistence of dynasties, Lorne Tepperman social networks and efficient resource allocation - computer models of job vacancy allocation through contacts, John Delany occupational mobility - a structural model, Joel H.Levine and John Spadaro toward a formal structural sociology, S.D. Berkowitz.
Internet Flattening: Monitoring and Analysis of Inter-Domain Routing

The decrease of AS-level route length, called Internet flattening, has a significance impact on the the design of next generation global routing system. However, there is little quantitative assessment of its factors. We report our findings through monitoring and analysis of inter-domain routing. Using BGP routing table and update messages from RouteViews and RIPE RIS, we explore Internet flattening from a view of global inter-domain routing system. Our study shows that Internet flattening is from two dominating sources: (1) ASes close to Tier 1 contribute 36% of the total decrease in route length; and (2) Routes bypassing Tier 1 is responsible for 53% of the total decrease in route length. Our measurement results also indicate that multi-homing is not an important reason of Internet flattening. Besides, leading Content Providers contribute to Internet flattening ten times than that by Internet Service Providers. Base on our result, we propose mechanisms for the performance improvement for Content Providers.
R-Extractor: A Method for Data Extraction from Template-Based Entity-Pages

The challenges in Big Data start during the data acquisition, where it is necessary to transform non-structured data into a structured format. The Big Data Era brought a new challenge to data acquisition: the need for eliminating user intervention. In this context, the domain-centric data extraction (DCDE) methods arose through replacing user intervention with content redundancy. The DCDE methods extract the attribute values of entities of the web that are restricted to a specific application domain. A research gap was identified from various analyzed methods, i.e., the DCDE methods are not effective in extracting attribute values that are differently presented within the same website. We have responded to this research gap by proposing the R-Extractor method, which extends a state-of-the-art DCDE method by adding a reinforcement stage for the treatment of attribute values that are differently presented within the same website. The R-Extractor method re-analyzes the extraction rules to identify those that can be combined to extract the values of a given attribute from all the pages that describe entities on a website. This identification is based on a novel score function that takes into account different features of the extraction rules. We carried out experiments on a dataset with more than 50k web pages from different real-world websites of a wide range of application domains. The R-Extractor method reached 98% of precision. Our method was compared with two baselines (an XPath-based method and a tree-based method) and outperformed them with an increase in precision up to 14%.
Everyday Hassles: Barriers to Recovery in Drug Court

Participants in a drug court are subjects in a study that analyzes the relationship between the everyday problems they identify in discussions with the judge and their patterns of recovery, as measured by compliance with program requirements. 130 types of problems mentioned in court revealed that problems generally are those associated with the individuals themselves (e.g., their physical health), their immediate social milieu (e.g., domestic abuse), and the larger social structure in which they negotiate their lives (e.g., acquiring Medicaid benefits). The most frequently mentioned types of problems were “structural” in nature. Patterns of recovery identified in program graduates resulted in labels of “clear sailers,” “late bloomers,” “occasional stumblers,” and “chronic stumblers. ” A case study of an occasional stumbler reveals some ways in which everyday hassles and her responses to them affected her recovery.
Geocast for wireless sensor networks

An important but relatively less studied class of network layer protocol for sensor networks is geocast. It allows a sensor node to send messages to all nodes in a given geographical area without the sender node having any knowledge about which nodes are present in that area. Developing a robust geocast protocol for practical sensor networks poses several challenges. Geocast messages should be reliably delivered to the destination area in the presence of unreliable wireless links, a typical characteristic of practical sensor network deployments. The protocol should minimize the number of radio transmissions and avoid control traffic to save energy, which is a scarce resource in sensor networks. The protocol should be robust against a wide range of network densities. This paper presents the design, implementation, and evaluation of SGcast — a reliable, robust, and energy-efficient geocast protocol that achieves these goals. For a wide range of experiments conducted using networks of real sensor nodes and simulations, we show that compared to a recent geocast protocol, SGcast achieves up to 11.08x reduction in energy consumption and up to 2.17x improvement in successful delivery of geocast messages to the destination area, while being robust against a wide variability in network densities.
PMSM model discretization for Model Predictive Control algorithms

Drives based on permanent magnet synchronous machines become more and more popular in many industrial applications. In most high-performance applications classical vector control is currently used. While this control method is usually reliable it has some limitations especially in controllers tuning and constraints handling. New control methods like Model Predictive Control become feasible in connection with increasing computational power of controller hardware. The paper deals with enhanced discrete time PMSM model which can be used for efficient predictive control implementation. The other objective of the paper is discussion of prediction horizon length impact on the drive control performance.
Changes in serum albumin during treatment of chronic hepatitis B with lamivudine: effects of response and emergence of drug resistance

OBJECTIVES:In chronic hepatitis B patients treated with lamivudine, the incidence of drug resistance increases with the duration of therapy. The effect of drug resistance on hepatic synthetic function is not well defined. The aim of the present study was to assess the effect of lamivudine therapy on hepatic synthetic function in patients with moderately severe chronic hepatitis B and, particularly, to determine the effect of drug resistance.METHODS:Hepatic synthetic function was assessed using serial measurements of serum albumin in 38 patients (26 with cirrhosis) in an open-label treatment program.RESULTS:An initial antiviral response (hepatitis B virus [HBV] DNA undetectable by hybridization assay) occurred in all patients, and nine of 22 (41%) hepatitis B e antigen–positive cases underwent hepatitis B e antigen seroconversion. Among 29 patients with undetectable serum HBV DNA at the end of observation, the mean serum albumin concentration rose from 39.9 ± 0.7 to 43.2 ± 0.6 g/L, corresponding to a yearly increase of 1.85 g/L (p < 0.001). This was largely attributable to an increase among cirrhotic patients. Nine patients (24%) developed resistance to lamivudine, all after 12 months of treatment. Among them, the mean serum albumin concentration had increased from 39.6 ± 1.2 to 42.9 ± 0.8 g/L before resistance emerged, but then decreased to 39.3 ± 1.7 g/L (p = 0.01) at the time of reappearance of HBV DNA.CONCLUSION:Suppression of viral replication by lamivudine improves hepatic synthetic function in chronic hepatitis B patients, but emergence of drug resistance is associated with a rapid decline in serum albumin, at least to pretreatment levels.
Evaluation of Inflammatory Markers in a Large Sample of Obstructive Sleep Apnea Patients without Comorbidities

Systemic inflammation is important in obstructive sleep apnea (OSA) pathophysiology and its comorbidity. We aimed to assess the levels of inflammatory biomarkers in a large sample of OSA patients and to investigate any correlation between these biomarkers with clinical and polysomnographic (PSG) parameters. This was a cross-sectional study in which 2983 patients who had undergone a polysomnography for OSA diagnosis were recruited. Patients with known comorbidities were excluded. Included patients (n = 1053) were grouped according to apnea-hypopnea index (AHI) as mild, moderate, and severe. Patients with AHI < 5 served as controls. Demographics, PSG data, and levels of high-sensitivity C-reactive protein (hs-CRP), fibrinogen, erythrocyte sedimentation rate (ESR), and uric acid (UA) were measured and compared between groups. A significant difference was found between groups in hs-CRP, fibrinogen, and UA. All biomarkers were independently associated with OSA severity and gender (p < 0.05). Females had increased levels of hs-CRP, fibrinogen, and ESR (p < 0.001) compared to men. In contrast, UA levels were higher in men (p < 0.001). Our results suggest that inflammatory markers significantly increase in patients with OSA without known comorbidities and correlate with OSA severity. These findings may have important implications regarding OSA diagnosis, monitoring, treatment, and prognosis. This trial is registered with ClinicalTrials.gov number NCT03070769.
The impact of an online evidence-based coaching program on goal striving, subjective well-being, and level of hope

The purpose of this study was to measure the effectiveness of an online evidence-based coaching program in terms of goal attainment, subjective well-being and level of hope. Both the coaching industry and use of the Internet have grown dramatically, and some coaches have added online communication to traditional face-to-face and telephonebased interactions with their clients. This research sought to contribute empirical findings to the nascent field of online coaching. The study’s research design was a posttest, random assignment, two-group comparison study. The researcher recruited a sample of adult Internet users in the United States by asking various website owners to mention the study to their audiences. Participants were randomly assigned to either a waitlist control group or to an experimental treatment group that participated in an 8-week online coaching program. The coaching program was an evidence-based coaching program that drew from a variety of validated psychological studies. The program was delivered exclusively online through a series of structured exercises and open discussions. A certified coach with more than 5 years professional coaching experience led the program, and participants interacted with the coach and other participants over the program’s duration. Measures in the present study included a goal attainment questionnaire, the Satisfaction with Life Scale, and the State Hope Scale. Responses were collected from all participants following the completion of the program or waitlist assignment. After a review of prior research, a hypothesis was developed stating that results from the experimental coaching group would be significantly different from those of the waitlist control group. To test the hypothesis, results from the two groups were compared using a One-Way MANOVA with associated post-hoc tests. Omnibus MANOVA results were significant, and a post-hoc ANOVA test was subsequently conducted for each of the study’s dependent variables. Post-hoc univariate tests of goal attainment and subjective well-being were significant. A post-hoc univariate test of hope was nonsignificant. Online coaching was observed to be effective in terms of the identified coaching outcomes. Implications of these findings and recommendations for future research are presented.
Bayesian Approach to Parameter Estimation in Individual Protein Molecule Dynamics

A model for the dynamics of membrane proteins in intact red blood cells was proposed in [3]. The data are obtained with a CCD camera. A nm-scale gold bead is attached to a protein molecule. Differential interference contrast (DIC) video microscopy is used to image the bead, and the images are recorded by a high-speed CCD camera. Because the beads are smaller than the resolution limit of the microscope, the bead images appear as blurred spots. The centroid position of the bead in each image is determined by using a tracking algorithm. In [3] the motion of an individual protein is modeled as a sum of three mutually independent components: a Wiener process, a compound Poisson process, and white Gaussian noise. This approach allows modeling of the interactions of the protein with various types of molecules. Model parameters were estimated by the method of moments applied to each of 10 equal parts of the rajectory. Thus we obtained a histogram for the MOM parameter estimates. In this paper, we propose Bayesian parameter estimation based on Gibbs sampler. The uncertainty in parameter values is quantitfied via credible intervals (see [1]).
Retail Price Stickiness, Market Structure and Distribution Channels

Using Japanese scanner data of transaction prices and sales for more than 1,600 commodity groups from 1988 to 2008, we find a statistically significant negative correlation between the frequency of price changes and the degree of market concentration. We also find that structural factors of a distribution channel are significantly correlated with rigidity in retail prices. Decomposing the frequency of price changes into the frequency of intraday, sale, and regular price changes, we find that both inter- and intra-brand competition positively affect the frequency of sales. Inter-brand competition among manufacturers has a significant and positive effect on the frequency of regular price changes, whereas intra-brand competition among retailers has no such significant effect. We also document that the term of contracts between manufacturers and retailers has a significant and positive effect on price stickiness.
Campus Racial Climate and Student Academic Outcomes: A Critique of Prior Research and Recommendations for Future Study

What explains the persistent gap in college retention between white American college students and those who are members of ethnic minority groups? Some argue that a large part of the answer is campus racial climate: a negative climate disproportionately harms minority students and leads to worse outcomes. Existing theory provides some basis for this expectation. However, we find that empirical support for this claim is weak. Many studies fail to compare findings across racial groups, and the few that do offer at best inconsistent support for the thesis that racial climate helps to explain the retention gap. Furthermore, many studies are plagued with severe methodological problems such as lack of attention to level of analysis and failure to offer rigorous tests of differences across groups. We discuss the implications and offer recommendations for future research.
Ranking Deep Web Text Collections for Scalable Information Extraction

Information extraction (IE) systems discover structured information from natural language text, to enable much richer querying and data mining than possible directly over the unstructured text. Unfortunately, IE is generally a computationally expensive process, and hence improving its efficiency, so that it scales over large volumes of text, is of critical importance. State-of-the-art approaches for scaling the IE process focus on one text collection at a time. These approaches prioritize the extraction effort by learning keyword queries to identify the "useful" documents for the IE task at hand, namely, those that lead to the extraction of structured "tuples. " These approaches, however, do not attempt to predict which text collections are useful for the IE task---and hence merit further processing---and which ones will not contribute any useful output---and hence should be ignored altogether, for efficiency. In this paper, we focus on an especially valuable family of text sources, the so-called deep web collections, whose (remote) contents are only accessible via querying. Specifically, we introduce and study techniques for ranking deep web collections for an IE task, to prioritize the extraction effort by focusing on collections with substantial numbers of useful documents for the task. We study both (adaptations of) state-of-the-art resource selection strategies for distributed information retrieval, and IE-specific approaches. Our extensive experimental evaluation over realistic deep web collections, and for several different IE tasks, shows the merits and limitations of the alternative families of approaches, and provides a roadmap for addressing this critically important building block for efficient, scalable information extraction.
Universal hydrodynamics of non-conformal branes

We examine the hydrodynamic limit of non-conformal branes using the recently developed precise holographic dictionary. We first streamline the discussion of holography for backgrounds that asymptote locally to non-conformal brane solutions by showing that all such solutions can be obtained from higher dimensional asymptotically locally AdS solutions by suitable dimensional reduction and continuation in the dimension. As a consequence, many holographic results for such backgrounds follow from the corresponding results of the Asymptotically AdS case. In particular, the hydrodynamics of non-conformal branes is fully determined in terms of conformal hydrodynamics. Using previous results on the latter we predict the form of the non-conformal hydrodynamic stress tensor to second order in derivatives. Furthermore we show that the ratio between bulk and shear viscosity is fixed by the generalized conformal structure to be ζ/η = 2(1/(d−1)−cs2), where cs is the speed of sound in the fluid.
Diffusion in a Pendulum Lattice

Abstract The main model studied in this paper is a lattice of pendula with a nearestneighbor coupling. If the coupling is weak, then the system is near-integrable and KAM tori fill most of the phase space. For all KAM trajectories the energy of each pendulum stays within a narrow band for all time. Still, we show that for an arbitrarily weak coupling of a certain localized type, the neighboring pendula can exchange energy. In fact, the energy can be transferred between the pendula in any prescribed way. © 2013 Wiley Periodicals, Inc.
Model Predictive Control for Market-Based Demand Response Participation

In this study, we investigate the maximum possible profit for a commercial office building participating in New York’s Day-Ahead Demand Response (DADR) program. We formulate an optimal control problem, assuming perfect knowledge of future weather, occupancy, and day-ahead electricity price predictions to examine this potential benefit. Then, a practical control strategy based upon the framework of Model Predictive Control (MPC) is proposed, which enables a building to participate in the DADR program. The controller decides once every day, whether or not to participate in the Demand Response (DR) event, and then optimizes the electric consumption to increase savings. A simulation study is carried out using a building model extracted from an EnergyPlus model, real measured weather data, and real day-ahead spot market price data for New York. Savings in the range of 23% to 33% are reported.