Miracle-dz/UniFAR-FTUs huggingface dataset:
Oxidative Stress in Diabetic Nephropathy with Early Chronic Kidney Disease

The increase in the prevalence of diabetes mellitus (DM) and the secondary kidney damage produces diabetic nephropathy (DN). Early nephropathy is defined as the presence of microalbuminuria (30–300 mg/day), including normal glomerular filtration rate (GFR) or a mildly decreased GFR (60–89 mL/min/1.73 m2), with or without overt nephropathy. The earliest change caused by DN is hyperfiltration with proteinuria. The acceptable excretion rate of albumin in urine is <30 mg/day. Albuminuria represents the excretion of >300 mg/day. Chronic kidney disease (CKD) is characterized by abnormalities in renal function that persist for >3 months with health implications. Alterations in the redox state in DN are caused by the persistent state of hyperglycemia and the increase in advanced glycation end products (AGEs) with ability to affect the renin-angiotensin system and the transforming growth factor-beta (TGF-β), producing chronic inflammation and glomerular and tubular hypertrophy and favoring the appearance of oxidative stress. In DN imbalance between prooxidant/antioxidant processes exists with an increase in reactive oxygen species (ROS). The overproduction of ROS diminishes expression of the antioxidant enzymes (manganese superoxide dismutase, glutathione peroxidase, and catalase). The early detection of CKD secondary to DN and the timely identification of patients would permit decreasing its impact on health.
A 86mW 98GOPS ANN-searching processor for Full-HD 30fps video object recognition with zeroless locality-sensitive hashing

Increasing database size and massive dimensions of keypoint descriptors caused nearest neighbor searching as a main bottleneck in object recognition systems. Therefore a high throughput approximate nearest neighbor (ANN) searching processor is proposed for real-time object recognition. To reduce the external bandwidth required in nearest neighbor searching, this chip utilizes an on-chip cache for transaction reduction and the zeroless locality-sensitive hashing (zeroless-LSH) operation for required data suppression. As a result, the proposed ANN-searching processor achieves 62,720 vectors/sec throughput and 1,140GOPS/W power efficiency, which are 1.45x and 1.37x higher than the state-of-the-art respectively, enabling real-time object recognition for Full-HD 30fps video streams.
Labor Market Mobility and Expectation Management: Evidence from Enforceability of Non-Compete Provisions

This study examines how managers’ use of expectation management is affected by labor market mobility, measured with the enforceability of non-compete provisions in employment contracts. We find that managers in states with stricter non-compete enforcement are more likely to manage analyst expectations downward, consistent with labor market immobility exacerbating managers’ incentives to ensure meeting expectations. Moreover, we find the effect to be more pronounced for less capable and more junior CEOs, for firms with more intense monitoring, and for firms in more homogenous or more competitive industries. Results from quasi-natural experiments and instrumental variable approach suggest that non-compete enforcement causally affects the use of expectation management. Finally, investors seem to discount the premium on achieving earnings targets through expectation management for firms in high non-compete enforceability states.
Stimulating physical and social activity through open-ended play

In this paper, we describe our design research on tangible play objects that stimulate social and physical play. We illustrate our work by describing a design case about an open-ended play object for children called the ColorFlare. The ColorFlare is an object that detects the player's movements and provides light feedback and that can communicate with other ColorFlares. A user test is described that examined how children use the ColorFlare to collaboratively create various (physical) games. We relate our research to definitions of embodied interaction, for example by describing how children allocate meaning to the interaction behavior of the play objects and jointly create diverse games during the play sessions.
Political Institutions, Populism, and Democracy in Latin America

pat r ic io n av i a a n d ig n ac io wa l k e r ; The end of the cold war coincided with the most widespread and successful wave of democratization that Latin America has experienced in its history. As the decade of the 1980s drew to an end, democracy was on the way to becoming " the only game in town. " Yet, two decades after the auspicious transitions to democracy, the results of the democratic experience have been decidedly mixed. On the one hand, elections have been broadly recognized as the only legitimate mechanism to select authorities ; on the other hand, in many countries and along many dimensions , the quality of democracy is less than satisfactory. Public levels of support for democracy are disturbingly low in some countries. In others, concerns about corruption, low levels of participation, and institutional designs not conducive to adequate accountability point to glaring deficiencies in the region's democracies. Two decades ago, the countries in the region prioritized making transitions to democracy possible. Today, the major challenge consists of ensuring democratic consolidation. Democracy has to be a self-sustaining system capable of producing concrete and positive results for its citizens. When its exercise strengthens institutions , democracy will be a virtuous cycle that produces concrete results and satisfies international standards. In that sense, democracy must be self-sustainable (Przeworski 2005). To take up the challenges faced by the countries of the region, we address two major themes in this chapter. First, we discuss the elements of democracy. We lay out formal criteria that must be present in order for a system to be democratic. We advocate a minimalist definition, and
COMPARISON OF TWO METHODS FOR DESCRIBING THE STRAIN PROFILES IN QUANTUM DOTS

The electronic structure of interfaces between lattice-mismatched semiconductors is sensitive to the strain. We compare two approaches for calculating such inhomogeneous strain—continuum elasticity [(CE), treated as a finite difference problem] and atomistic elasticity. While for small strain the two methods must agree, for the large strains that exist between lattice-mismatched III-V semiconductors (e.g., 7% for InAs/GaAs outside the linearity regime of CE) there are discrepancies. We compare the strain profile obtained by both approaches (including the approximation of the correct C2 symmetry by the C4 symmetry in the CE method) when applied to C2-symmetric InAs pyramidal dots capped by GaAs.
Voxel-Based 6-DOF Haptic Rendering Improvements

An approach is presented for realizing an order-of-magnitude improvement in spatial accuracy for voxel-based 6-DOF haptics. It trades constant-time performance for greater spatial accuracy. This helps to make 6-DOF haptics applicable to extraordinarily complex real-world task simulations, which often admit no other known solution short of physical mockup. A reduction of haptic fidelity is tactically incurred but simultaneously mitigated by augmenting standard voxel-sampling methodology with distance fields, temporal coherence, and culling of redundant polyhedral surface interactions. This is applied to large-scale haptic scenarios involving multiple moving objects and to collaborative virtual environments.
Efficient high speed signal estimation with neuromorphic vision sensors

Recently developed neuromorphic vision sensors present a high speed, event-based alternative to conventional vision in robotic systems. We present a method for the design of simple, low computation estimators that take advantage of the remarkable properties of these sensors to provide low latency, high bandwidth sensing for feedback control of fast dynamical systems. It is shown that under certain circumstances a simple transformation of the event stream from such a sensor can allow it to be treated as an asynchronous configuration sensor, with minimal computation required to achieve high speed signal reconstruction. These results are applicable to any robotic control problems requiring high performance visual feedback control with low computation.
Barrier Operators and Associated Gradient-Like Dynamical Systems for Constrained Minimization Problems

We study some continuous dynamical systems associated with constrained optimization problems. For that purpose, we introduce the concept of elliptic barrier operators and develop a unified framework to derive and analyze the associated class of gradient-like dynamical systems, called A-driven descent method (A-DM). Prominent methods belonging to this class include several continuous descent methods studied earlier in the literature such as steepest descent method, continuous gradient projection methods and Newton-type methods as well as continuous interior descent methods such as Lotka-Volterra-type differential equations and Riemannian gradient methods. Related discrete iterative methods such as proximal interior point algorithms based on Bregman functions and second order homogeneous kernels can also be recovered within our framework and allow for deriving some new and interesting dynamics. We prove global existence and strong viability results of the corresponding trajectories of (A-DM) for a smooth objective function. When the objective function is convex, we analyze the asymptotic behavior at infinity of the trajectory produced by the proposed class of dynamical systems (A-DM). In particular, we derive a general criterion ensuring the global convergence of the trajectory of (A-DM) to a minimizer of a convex function over a closed convex set. This result is then applied to several dynamics built upon specific elliptic barrier operators. Throughout the paper, our results are illustrated with many examples.
The World Price of Earnings Opacity

We analyze the financial statements of 58,653 firm-years from 34 countries for the period 1985-1998 to construct a panel data set measuring three dimensions of reported accounting earnings for each country – earnings aggressiveness, loss avoidance, and earnings smoothing. We hypothesize that these three dimensions are associated with uninformative or opaque earnings, and so we combine these three measures to obtain an overall earnings opacity time-series measure per country. We then explore whether our three measures of earnings opacity affects two characteristics of an equity market in a country – the return the shareholders demand and how much they trade. While not all results are consistent for our three individual earnings opacity measures, our panel data tests document that, after controlling for other influences, an increase in overall earnings opacity in a country is linked to an economically significant increase in the cost of equity and an economically significant decrease in trading in the stock market of that country.
3D Mapping of Mini-mental State Examination Performance in Clinical and Preclinical Alzheimer Disease

The Mini-mental State Examination (MMSE) is a brief cognitive screening instrument frequently used to track Alzheimer disease (AD) progression. We investigated the structural neuroimaging correlates of MMSE performance in patients with clinical and preclinical AD. We analyzed structural magnetic resonance imaging data from 29 probable AD and 5 MCI patients who later converted to probable AD using an advanced 3D cortical mapping technique. MMSE scores were entered as covariates in a general linear model that predicted the gray matter density at each cortical surface point. The results were corrected for multiple comparisons by permutation testing. The global permutation-corrected significance for the maps linking gray matter loss and cognitive decline was P=0.005 for the left and P=0.012 for the right hemisphere. Strongest correlations between MMSE score and gray matter integrity were seen in the entorhinal, parahippocampal, precuneus, superior parietal, and subgenual cingulate/orbitofrontal cortices. Significant correlations were also seen bilaterally in the temporal, the middle frontal and the left angular and supramarginal gyri. As a global cognitive measure, MMSE depends on the integrity of widely distributed cortical areas in both brain hemispheres with left-sided predominance.
Ultrasound-Guided Fine Needle Aspiration of Thyroid Nodules: A Consensus Statement by the Korean Society of Thyroid Radiology

Ultrasound (US)-guided fine needle aspiration (US-FNA) has played a crucial role in managing patients with thyroid nodules, owing to its safety and accuracy. However, even with US guidance, nondiagnostic sampling and infrequent complications still occur after FNA. Accordingly, the Task Force on US-FNA of the Korean Society of Thyroid Radiology has provided consensus recommendations for the US-FNA technique and related issues to improve diagnostic yield. These detailed procedures are based on a comprehensive analysis of the current literature and from the consensus of experts.
OMCat: Catalog of Serendipitous Sources Detected with the XMM-Newton Optical Monitor

The Optical Monitor Catalog of serendipitous sources (OMCat) contains entries for every source detected in the publicly available XMM-Newton Optical Monitor (OM) images taken in either the imaging or “fast” modes. Since the OM is coaligned and records data simultaneously with the X-ray telescopes on XMM-Newton, it typically produces images in one or more near-UV or optical bands for every pointing of the observatory. As of the beginning of 2006, the public archive had covered roughly 0.5% of the sky in 2950 fields. The OMCat is not dominated by sources previously undetected at other wavelengths; the bulk of the objects have optical counterparts. However, the OMCat can be used to extend optical or X-ray spectral energy distributions for known objects into the ultraviolet, to study at higher angular resolution objects detected with GALEX, or to find high-Galactic-latitude objects of interest for UV spectroscopy.
Does merging improve efficiency? A study of English universities

ABSTRACT This paper focuses on the effect of merger on university efficiency. In a first stage analysis, efficiency scores of English universities are derived for a 17-year period using the frontier estimation method data envelopment analysis. A second stage analysis explores the effect of merger and other factors on efficiency. We find that mean efficiency for the sector has varied from around 60% to 70%, but that the efficiency levels of the vast majority of individual higher education institutions (HEIs) are not significantly different from each other. Merged HEIs have an efficiency which is around five percentage points higher post-merger than non-merging HEIs holding all else constant; but we find that the efficiency impact of merger does not last long (not more than a year) after the merger. The transitory nature of the efficiency gain is an important finding which should be noted by politicians and managers considering a policy of merger.
Confirmatory model of mathematics self-efficacy, problem solving skills and prior knowledge on mathematics achievement: a structural equation model

The purpose of the current study was to determine the effects of mathematical problem solving skills and prior mathematics knowledge on mathematics achievement and mathematics self-efficacy. Also the effect of mathematics self-efficacy on mathematics achievement was demonstrated. The subjects of the study were middle school students (males and females) of the academic year 2013. 400 of 8th graders were selected from four public schools of Shiraz in Iran. A two stage Cluster Random Sampling Method was utilized. Structural Equation Model was used to analyze the data. The estimate of Structural Equation Model revealed that mathematical problem solving skills and prior mathematics knowledge had a direct and an indirect effect through mathematics self-efficacy on mathematics achievement. The high goodness-of-fit indices that model had a good fit to the given data (χ2=2.520 < 5). Additionally, Confirmatory Factor Analysis was used for validity and reliability of instruments. The results showed the Construct Reliability value for all of subscales were more than . 70. Furthermore, the finding of this study indicated the significant relationship between predictor’s variables (problem solving skills, prior mathematics knowledge), mathematics self-efficacy as mediator, and mathematics achievement as criterion variable. The findings supported the hypothesized role of self-efficacy in Bandura’s (1986) social cognitive theory and Schoenfeld’s (1985) mathematical problem solving theory. This study hopes to accomplish a perfect framework for educators, students, and the Ministry of Education. The obtained results of the current study will bring advantages to the researchers and educators.
The Influence of Changes in Customer's Technology Portfolio on Supplier's Organization

This research paper studies the influence of the changes in customer's technology portfolio on supplier's organization in the context of the customer's merger with another company. By using Fuzzy Cognitive Maps and taking into account the perceptions of 23 members of the supplier organization, by drawing and analyzing the causality of 63 factors involved in the change situation, it provides an indication about the most important aspects which had to be considered by supplier's management for minimizing the negative impact of the changes occurring on the customer's side. A qualitative simulation of the supplier system is done in order to verify its evolution under different scenarios. Besides the theoretical aspects related to Fuzzy Cognitive Maps the paper provides recommendations for managing similar situations.
Identifying Key Features for P2P Traffic Classification

Many researchers have recently dealt with P2P traffic classification, mainly because P2P applications are continuously growing in number as well as in traffic volume. Additionally, in response to the shift of the operational community from packet-level to flow-level monitoring, witnessed by the widespread use of NetFlow, a number of behavioral classifiers have been proposed. These techniques, usually having P2P applications as their main target, base the classification on the analysis of the pattern of traffic generated by a host and proved accurate even when using only flow-level data. Yet, all these approaches are very specific and the community lacks a broader view of the actual amount of information of behavioral features derived by flow-level data. The preliminary results presented in this paper try to fill this gap. First of all we define a comprehensive framework by means of which we systematically explore the space of behavioral properties and build a large set of potentially expressive features. Thanks to our general approach, most features already used by existing classifiers fall into this set. Then, by employing tools from information theory and data from packet-level traces captured on real networks, we evaluate the amount of information conveyed by each feature, ranking them according to their usefulness for application identification. Finally we show the classification performance of these set of features, using a supervised machine learning algorithm.
SuperMod: Tool support for collaborative filtered model-driven software product line engineering

The increase in productivity implied by model-driven software product line engineering is weakened by the complexity exposed to the user having to manage a multi-variant model. Recently, a new paradigm has emerged: filtered software product line engineering transfers the established check-out/modify/commit workflow from version control to variability management, allowing to iteratively develop the multi-variant model in a single-variant view. This paper demonstrates SuperMod, a tool that supports collaborative filtered model-driven product line engineering, implemented for and with the Eclipse Modeling Framework. Concerning variability management, the tool offers capabilities for editing feature models and specifying feature configurations, both being well-known formalisms in product line engineering. Furthermore, collaborative editing of product lines is provided through distributed version control. The accompanying video shows that SuperMod seamlessly integrates into existing tool landscapes, reduces the complexity of multi-variant editing, automates a large part of variability management, and ensures consistency. A tool demonstration video is available here: http://youtu.be/5XOk3x5kjFc.
RNA-seq Profiles of Immune Related Genes in the Spleen of Necrotic Enteritis-afflicted Chicken Lines

The study aimed to compare the necrotic enteritis (NE)-induced transcriptome differences between the spleens of Marek’s disease resistant chicken line 6.3 and susceptible line 7.2 co-infected with Eimeria maxima/Clostridium perfringens using RNA-Seq. Total RNA from the spleens of two chicken lines were used to make libraries, generating 42,736,296 and 42,617,720 usable reads, which were assembled into groups of 29,897 and 29,833 mRNA genes, respectively. The transcriptome changes were investigated using the differentially expressed genes (DEGs) package, which indicated 3,255, 2,468 and 2,234 DEGs of line 6.3, line 7.2, and comparison between two lines, respectively (fold change ≥2, p<0.01). The transcription levels of 14 genes identified were further examined using qRT-PCR. The results of qRT-PCR were consistent with the RNA-seq data. All of the DEGs were analysed using gene ontology terms, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the DEGs in each term were found to be more highly expressed in line 6.3 than in line 7.2. RNA-seq analysis indicated 139 immune related genes, 44 CD molecular genes and 150 cytokines genes which were differentially expressed among chicken lines 6.3 and 7.2 (fold change ≥2, p<0.01). Novel mRNA analysis indicated 15,518 novel genes, for which the expression was shown to be higher in line 6.3 than in line 7.2 including some immune-related targets. These findings will help to understand host-pathogen interaction in the spleen and elucidate the mechanism of host genetic control of NE, and provide basis for future studies that can lead to the development of marker-based selection of highly disease-resistant chickens.
Determining the main factors affecting consumers’ acceptance of ethical advertising: A review of the Jordanian market

Abstract Studying consumers’ acceptance of the main ethical issues in communication and mainly in advertising has recently been receiving much attention from scholars. It is especially noteworthy when the advertising is seen as a technology-driven communication process and should be prepared based on a sense of consumers’ social responsibility and moral assent. Using a self-reported questionnaire from 450 parents, this study examines the effects of children abuse, sexual appeals, fear appeals and deceptive advertisements on Jordanian parents’ acceptance of ethical advertising. After using the Structural Equation Modeling test, path analysis was used to test the hypothetic relationships employing the Multivariate Regression Models. The study found that sexual appeals and children abuse are the main factors that affect parents’ acceptance of ethical advertising in the Jordanian market.