Miracle-dz/UniFAR-FTUs huggingface dataset:
Path-Constrained Relaxed Schedulability Analysis

The schedulability analysis problem for many realistic task models is known to be hard (NP or coNP). As this severely restricts the application of these task models, recently there has been a considerable amount of interest in relaxed or approximate notions of schedulability, with the hope that they can be checked more efficiently. In this paper we introduce yet another natural notion of relaxed schedulability, which is parameterized in terms of the number of paths in a task set. In the model we consider, each task is represented by a directed acyclic graph where the nodes of such a graph are annotated with execution times and deadlines. Our proposed notion of schedulability allows a certain number of paths from each task graph to be non-schedulable. For describing the relaxed schedulability analysis, we formally define a measure called pseudo-K-schedulability, which corresponds to the situation when the task set has exactly K schedulable paths. At one extreme is the classical notion of schedulability analysis, where the problem is NP hard in our and many other task models. At the other extreme of this spectrum we have the trivial notion of schedulability analysis, where no path needs to be schedulable. Problems in between allow for a flexible notion of schedulability. This paper studies the relaxed schedulability because not all paths in a code are executed. This paper shows a fundamental result, namely the membership of the pseudoschedulability problem to the class of NP-hard problems.
In Vivo Quantitative Measurement of Intact Fibrous Cap and Lipid-Rich Necrotic Core Size in Atherosclerotic Carotid Plaque: Comparison of High-Resolution, Contrast-Enhanced Magnetic Resonance Imaging and Histology

Background— Previous studies with contrast-enhanced magnetic resonance imaging (CEMRI) have shown that the fibrous cap (FC) in atherosclerotic carotid plaques enhances with gadolinium-based contrast agents. Conversely, the lipid-rich necrotic core (LR-NC), lacking both vasculature and matrix, shows no or only slight enhancement. The goal of this study was to assess whether CEMRI can be used to accurately measure the dimensions of the intact FC and LR-NC. Methods and Results— Twenty-one patients scheduled for carotid endarterectomy were imaged with a 1.5-T scanner. Precontrast images and CEMRI were obtained. One hundred eight locations with an intact FC were matched between MRI and the excised histology specimens. Quantitative measurements of FC length along the lumen circumference, FC area, and LR-NC area were collected from CEMRI images and histology sections. Blinded comparison of corresponding MR images and histology slices showed moderate to good correlation for length (r=0.73, P<0.001) and area (r=0.80, P<0.001) of the intact FC. The mean percentage LR-NC areas (LR-NC area/wall area) measured by CEMRI and histology were 30.1% and 32.7%, respectively, and were strongly correlated across locations (r=0.87, P<0.001). Conclusions— In vivo high-resolution CEMRI is capable of quantitatively measuring the dimensions of the intact FC and LR-NC. These new parameters may be useful to evaluate plaque vulnerability and provide continuous variables for characterizing the intact FC and LR-NC in progression and regression studies.
Robust, Adaptive Functional Regression in Functional Mixed Model Framework

Functional data are increasingly encountered in scientific studies, and their high dimensionality and complexity lead to many analytical challenges. Various methods for functional data analysis have been developed, including functional response regression methods that involve regression of a functional response on univariate/multivariate predictors with nonparametrically represented functional coefficients. In existing methods, however, the functional regression can be sensitive to outlying curves and outlying regions of curves, so is not robust. In this article, we introduce a new Bayesian method, robust functional mixed models (R-FMM), for performing robust functional regression within the general functional mixed model framework, which includes multiple continuous or categorical predictors and random effect functions accommodating potential between-function correlation induced by the experimental design. The underlying model involves a hierarchical scale mixture model for the fixed effects, random effect, and residual error functions. These modeling assumptions across curves result in robust nonparametric estimators of the fixed and random effect functions which down-weight outlying curves and regions of curves, and produce statistics that can be used to flag global and local outliers. These assumptions also lead to distributions across wavelet coefficients that have outstanding sparsity and adaptive shrinkage properties, with great flexibility for the data to determine the sparsity and the heaviness of the tails. Together with the down-weighting of outliers, these within-curve properties lead to fixed and random effect function estimates that appear in our simulations to be remarkably adaptive in their ability to remove spurious features yet retain true features of the functions. We have developed general code to implement this fully Bayesian method that is automatic, requiring the user to only provide the functional data and design matrices. It is efficient enough to handle large datasets, and yields posterior samples of all model parameters that can be used to perform desired Bayesian estimation and inference. Although we present details for a specific implementation of the R-FMM using specific distributional choices in the hierarchical model, 1D functions, and wavelet transforms, the method can be applied more generally using other heavy-tailed distributions, higher dimensional functions (e.g., images), and using other invertible transformations as alternatives to wavelets. Supplementary materials for this article are available online.
Temporal Patterns and Periodicity of Entity Dynamics in the Linked Open Data Cloud

We present initial results of finding temporal patterns of entity dynamics on the Linked Open Data (LOD) cloud. For the analysis, we use the dataset of the three-year observation of the Dynamic Linked Data Observatory. Using k-means++ clustering with Euclidean distance, we reveal the temporal patterns of entity dynamics. In addition, we conduct the first investigation of periodicity in entity dynamics on the LOD cloud. While a large portion of entities are static, a certain number of entities have a temporal pattern with substantial changes. We observe different periodicity with respect to temporal patterns of entity dynamics. Knowing about the temporal patterns and their periodicity is important for applications that are depending on fresh data caches and indices of the distributed LOD cloud. They can concentrate in crawling and refreshing those parts of the LOD cloud, which are a) known to have changes in the past and b) currently have their highest periodical change rate.
The Inheritance of Resistance Alleles in Multiple Sclerosis

Multiple sclerosis (MS) is a complex trait in which alleles at or near the class II loci HLA-DRB1 and HLA-DQB1 contribute significantly to genetic risk. HLA-DRB1*15 and HLA-DRB1*17-bearing haplotypes and interactions at the HLA-DRB1 locus increase risk of MS but it has taken large samples to identify resistance HLA-DRB1 alleles. In this investigation of 7,093 individuals from 1,432 MS families, we have assessed the validity, mode of inheritance, associated genotypes, and the interactions of HLA-DRB1 resistance alleles. HLA-DRB1*14-, HLA-DRB1*11-, HLA-DRB1*01-, and HLA-DRB1*10-bearing haplotypes are protective overall but they appear to operate by different mechanisms. The first type of resistance allele is characterised by HLA-DRB1*14 and HLA-DRB1*11. Each shows a multiplicative mode of inheritance indicating a broadly acting suppression of risk, but a different degree of protection. In contrast, a second type is exemplified by HLA-DRB1*10 and HLA-DRB1*01. These alleles are significantly protective when they interact specifically in trans with HLA-DRB1*15-bearing haplotypes. HLA-DRB1*01 and HLA-DRB1*10 do not interact with HLA-DRB1*17, implying that several mechanisms may be operative in major histocompatibility complex–associated MS susceptibility, perhaps analogous to the resistance alleles. There are major practical implications for risk and for the exploration of mechanisms in animal models. Restriction of antigen presentation by HLA-DRB1*15 seems an improbably simple mechanism of major histocompatibility complex–associated susceptibility.
Noncalcified Coronary Plaque Volumes in Healthy People With a Family History of Early Onset Coronary Artery Disease

Background—Although age and sex distributions of calcified coronary plaque have been well described in the general population, noncalcified plaque (NCP) distributions remain unknown. This is important because NCP is a putative precursor for clinical coronary artery disease and could serve as a sentinel for aggressive primary prevention, especially in high-risk populations. We examined the distributions of NCP and calcified coronary plaque in healthy 30- to 74-year-old individuals from families with early onset coronary artery disease. Methods and Results—Participants in the GeneSTAR family study (N=805), mean age 51.1±10.8 years, 56% women, were screened for coronary artery disease risk factors and coronary plaque using dual-source computed tomographic angiography. Plaque volumes (mm3) were quantified using a validated automated method. The prevalence of coronary plaque was 57.8% in men and 35.8% in women (P<0.0001). NCP volume increased with age (P<0.001) and was higher in men than women (P<0.001). Although NCP, as a percentage of total plaque, was inversely related to age (P<0.01), NCP accounted for most of the total plaque volume at all ages, especially in men and women <55 years (>70% and >80%, respectively). Higher Framingham risk was associated with the number of affected vessels (P<0.01), but 44% of men and 20.8% of women considered intermediate risk had left main and 3-vessel disease involvement. Conclusions—The majority of coronary plaque was noncalcified, particularly in younger individuals. These findings support the importance of assessing family history and suggest that early primary prevention interventions may be warranted at younger ages in families with early onset coronary artery disease.
A New Method for Link Prediction Using Various Features in Social Networks

Link prediction is a basic problem in the research of social networks. At present, most link prediction algorithms are based on the features extracted from network structure, few research concerns the effect of natural attributes of nodes for creating a link. In this paper we develop a novel way to predict links based on Random Walk algorithm using the information from both the network topology and rich node attributes. The experiment result show that our method can help improves the prediction accuracy and it proves that node attributes have a real effect on link creation.
Advanced Optimal Extraction for the Spitzer/IRS

We present new advances in the spectral extraction of pointlike sources adapted to the Infrared Spectrograph (IRS) on board the Spitzer Space Telescope. For the first time, we created a supersampled point-spread function of the low-resolution modules. We describe how to use the point-spread function to perform optimal extraction of a single source and of multiple sources within the slit. We also examine the case of the optimal extraction of one or several sources with a complex background. The new algorithms are gathered in a plug-in called AdOpt which is part of the SMART data analysis software.
On the use of instantaneous mean frequency estimated from the Hilbert spectrum of facial electromyography for differentiating core affects

Facial expression comprised of single or combination of facial action units (AUs) is one of the most important communication channels transferring affective states in our social life. Electromyography (EMG) activity captured over specific facial muscles could be used for interpreting one's affective experience. The present study investigated the effects of facial EMG changes in mean instantaneous mean frequency (IMNF) captured over corrugator supercilii and zygomaticus major for differentiating core affects. Firstly, an adaptive filter has been employed to deal with power line interference in the preprocessing of EMG signal. Secondly, a novel method - IMNF estimated via Hilbert spectrum was applied, which enables us to represent the characteristic of facial EMG in joint time-frequency domain. Thirdly, mean IMNF changes of facial EMG activity elicited by affective picture blocks were computed for differentiating core affects which describe affect in valence and arousal. The results indicated that low valence/high arousal affective state can be discriminated by corrugator supercilii EMG from neutral valence/low arousal, high valence/high arousal, high valence/low arousal and low valence/low arousal affective conditions, in which corrugator supercilii EMG in response to low valence/high arousal stimuli was greater than others. In contrast, zygomaticus major EMG indicated high valence/high arousal affective state with the highest response, compared to other four affective states; Zygomaticus major EMG also revealed significant differences between low valence/low arousal and high valence/low arousal, low valence/low arousal and low valence/high arousal.
Nursing Home Quality as a Common Good

A long-standing assumption among economists is that nursing home quality is common across Medicaid and private-pay patients within a shared facility. However, there has been only limited empirical work addressing this issue. Using a unique individual-level panel of residents of nursing homes from seven states, we exploit both within-facility and within-person variation in payer source and quality to examine this issue. We also test the robustness of these results across states with different Medicaid and private-pay rate differentials. Across various identification strategies, our results are consistent with the assumption of common quality across Medicaid and private-paying patients within facilities.
The pattern and course of cognitive impairment in late-life depression

Background Cognitive deficits persist despite clinical recovery in subjects with late-life depression, but more needs to be known about their longer-term outcome and factors affecting their course. To investigate this, we followed the pattern of cognitive impairments over time and examined the effects of current mood, remission status, age of depression onset and antidepressant (AD) treatment on these deficits. Method Sixty-seven subjects aged ⩾60 years with DSM-IV major depressive disorder and 36 healthy comparison subjects underwent tests of global cognition, memory, executive functioning and processing speed at baseline, 6 and 18 months, with some subjects tested again after 4 years. z scores were compared between groups, with analyses of clinical factors that may have influenced cognitive performance in depressed subjects. Results Half of the patients exhibited a generalized cognitive impairment (GCI) that persisted after 18 months. Patients performed worse across all cognitive domains at all time points, without substantial variability due to current mood, remission status or AD treatment. Late age of onset was associated significantly with decline in memory and executive functioning. Impaired processing speed may be a partial mediator of some deficits, but was insufficient to explain differences between patients and controls. Four-year follow-up data suggest impairments persist, but do not further decline. Conclusions Cognitive deficits in late-life depression persist up to 4 years, affect multiple domains and are related to trait rather than state effects. Differences in severity and course between early and late onset depression suggest different pathogenic processes.
Secure Distributed Storage System

—Secure Distributed Storage techniques are gaining importance with the increase of data centers, mobile devices and the need to save encrypted data in a distributed environment. [3] are used while implementing security and Error correction techniques while implementing secure distributed storage systems. Secure Mobile Distributed File system (MDFS) by Huchton [4] is an example of an implementation of such a system. The current implementation schemes of distributed storage system as mentioned in the report by GMU, CERG [5] are used in our system, which are implemented on the PC platform and for Android devices. Previous implementations of such a system had a weakness in the sense that the security of the systems really depended on the security of the underlying Encryption algorithm e.g. AES. In our scheme, we estimate the performance of the system with All or Nothing Transform (AONT) [6,7,8] included in the system in order to eradicate the security weakness. No documented implementation of AONT existed according to previous survey, and hence our project implements the system on PC and Android and estimates the performance of the total scheme taking AONT execution time as a constant, as it is independent of n, t (number of fragments and threshold, as explained in Section II). We have developed a working implementation of such a system on PC and Android and evaluated the performance of various Erasure coding algorithms, Secret sharing algorithms and estimated performance results for the proposed scheme.
Identification of a novel sorting determinant for the regulated pathway in the secretory protein chromogranin A

Chromogranin A (CgA) is the index member of the chromogranin/secretogranin (or `granin') family of regulated secretory proteins that are ubiquitously distributed in amine- and peptide-containing secretory granules of endocrine, neuroendocrine and neuronal cells. Because of their abundance and such widespread occurrence, granins have often been used as prototype proteins to elucidate mechanisms of protein targeting into dense-core secretory granules. In this study, we used a series of full-length, point mutant or truncated CgA-green fluorescent protein (GFP) chimeras to explore routing of CgA in neuroendocrine PC12 cells. Using sucrose gradient fractionation and 3D deconvolution microscopy to determine the subcellular localization of the GFP chimeras, as well as secretagogue-stimulated release, the present study establishes that a CgA-GFP fusion protein expressed in neuroendocrine PC12 cells is trafficked to the dense core secretory granule and thereby sorted to the regulated pathway for exocytosis. We show that information necessary for such trafficking is contained within the N-terminal but not the C-terminal region of CgA. We find that CgA's conserved N-terminal hydrophobic Cys17-Cys38 loop structure may not be sufficient for sorting of CgA into dense-core secretory granules, nor is its stabilization by a disulfide bond necessary for such sorting. Moreover, our data reveal for the first time that the CgA77-115 domain of the mature protein may be necessary (though perhaps not sufficient) for trafficking CgA into the regulated pathway of secretion.
Unpacking critical parameters for interface design: evaluating notification systems with the IRC framework

We elaborate a proposal for capturing, extending, and reusing design knowledge gleaned through usability testing. The proposal is specifically targeted to address interface design for notification systems, but its themes can be generalized to any constrained and well-defined genre of interactive system design. We reiterate arguments for and against using critical parameters to characterize user goals and usability artifacts. Responding to residual arguments, we suggest that clear advantages for research cohesion, design knowledge reuse, and HCI education are possible if several challenges are overcome. As a first step, we recommend a slight variation to the concept of a critical parameter, which would allow both abstract and concrete knowledge representation. With this concept, we demonstrate a feasible approach by introducing equations that elaborate and allow evolution of notification system critical parameters, which is made operational with a variety of usability evaluation instruments. A case study illustrates how one general instrument allowed system designs to be meaningfully compared and resulted in valuable inferences for interface reengineering. Broad implications and conclusions about this approach will be of interest to others concerned with using critical parameters in interface design, development of notification systems interfaces, or approaches to design rationale and knowledge reuse.
Dissecting structural basis of the unique substrate selectivity of human enteropeptidase catalytic subunit

Enteropeptidase is a key enzyme in the digestion system of higher animals. It initiates enzymatic cascade cleaving trypsinogen activation peptide after a unique sequence DDDDK. Recently, we have found specific activity of human enteropeptidase catalytic subunit (L-HEP) being significantly higher than that of its bovine ortholog (L-BEP). Moreover, we have discovered that L-HEP hydrolyzed several nonspecific peptidic substrates. In this work, we aimed to further characterize species-specific enteropeptidase activities and to reveal their structural basis. First, we compared hydrolysis of peptides and proteins lacking DDDDK sequence by L-HEP and L-BEP. In each case human enzyme was more efficient, with the highest hydrolysis rate observed for substrates with a large hydrophobic residue in P2-position. Computer modeling suggested enzyme exosite residues 96 (Arg in L-HEP, Lys in L-BEP) and 219 (Lys in L-HEP, Gln in L-BEP) to be responsible for these differences in enteropeptidase catalytic activity. Indeed, human-to-bovine mutations Arg96Lys, Lys219Gln shifted catalytic properties of L-HEP toward those of L-BEP. This effect was amplified in case of the double mutation Arg96Lys/Lys219Gln, but still did not cover the full difference in catalytic activities of human and bovine enzymes. To find a missing link, we studied monopeptide benzyl-arginine-β-naphthylamide hydrolysis. L-HEP catalyzed it with an order lower K m than L-BEP, suggesting the monopeptide-binding S1 site input into catalytic distinction between two enteropeptidase species. Together, our findings suggest structural basis of the unique catalytic properties of human enteropeptidase and instigate further studies of its tentative physiological and pathological roles.