Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonalcoholic Hepatic Steatosis Is a Strong Predictor of High-Risk Coronary-Artery Plaques as Determined by Multidetector CT

Background Nonalcoholic fatty liver disease is associated with a risk of coronary artery disease (e.g., diabetes mellitus, dyslipidemia, metabolic syndrome). We evaluated whether nonalcoholic hepatic steatosis is associated with high-risk plaques as assessed by multidetector computed tomography (CT). Methods This retrospective study involved 414 participants suspected of having coronary artery disease. Nonalcoholic hepatic steatosis was defined as a liver-to-spleen fat ratio of <1.0 and the presence and appropriate characteristics of coronary-artery plaques as assessed by coronary CT angiography. High-risk plaques were identified, as were low-density plaques, positive remodeling, and spotty calcification. Results Compared with patients who did not have nonalcoholic hepatic steatosis, patients with nonalcoholic hepatic steatosis had more low-density plaques (21% vs. 44%, p<0.01), positive remodeling (41% vs. 58%, p = 0.01), and spotty calcification (12% vs. 36%, p<0.01). The number of high-risk plaques in patients with nonalcoholic hepatic steatosis was greater than in those without nonalcoholic hepatic steatosis (p<0.01). Patients with nonalcoholic hepatic steatosis were more likely to have high-risk plaques than were those with only an elevated level of visceral adipose tissue (≥86 cm2; 35% vs. 16%, p<0.01). Multivariate analyses that included nonalcoholic hepatic steatosis, amount of visceral adipose tissue, and the presence/absence of traditional risk factors demonstrated that nonalcoholic hepatic steatosis was an independent predictor of high-risk plaques (odds ratio: 4.60; 95% confidence interval: 1.94–9.07, p<0.01). Conclusions Diagnosis of nonalcoholic hepatic steatosis may be of value when assessing the risk of coronary artery disease.
Demographic Prediction of Mobile User from Phone Usage

In this paper, we describe how we use the mobile phone usage of users to predict their demographic attributes. Using call log, visited GSM cells information, visited Bluetooth devices, visited Wireless LAN devices, accelerometer data, and so on, we predict the gender, age, marital status, job and number of people in household of users. The accuracy of developed classifiers for these classification problems ranges from 45-87% depending upon the particular classification problem.
Non-uniform distributions in quantitative information-flow

Quantitative information-flow analysis (QIF) determines the amount of information that a program leaks about its secret inputs. For this, QIF requires an assumption about the distribution of the secret inputs. Existing techniques either consider the worst-case over a (sub-)set of all input distributions and thereby over-approximate the amount of leaked information; or they are tailored to reasoning about uniformly distributed inputs and are hence not directly applicable to non-uniform use-cases; or they deal with explicitly represented distributions, for which suitable abstraction techniques are only now emerging. In this paper we propose a novel approach for a precise QIF with respect to non-uniform input distributions: We present a reduction technique that transforms the problem of QIF w.r. t. non-uniform distributions into the problem of QIF for the uniform case. This reduction enables us to directly apply existing techniques for uniform QIF to the non-uniform case. We furthermore show that quantitative information flow is robust with respect to variations of the input distribution. This result allows us to perform QIF based on approximate input distributions, which can significantly simplify the analysis. Finally, we perform a case study where we illustrate our techniques by using them to analyze an integrity check on non-uniformly distributed PINs, as they are used for banking.
A 33fJ/Step SAR Capacitance-to-Digital Converter Using a Chain of Inverter-Based Amplifiers

A 12 – <italic>bit</italic> energy-efficient capacitive sensor interface circuit that fully relies on capacitance-domain successive approximation (SAR) technique is presented. Analysis shows that for SAR capacitance-to-digital converter (CDC) comparator offset voltage will result in parasitic-dependent conversion errors, which necessitates using an offset cancellation technique. Based on the presented analysis, a SAR CDC that uses a chain of cascode inverter-based amplifiers with near-threshold biasing is proposed to provide robust, energy-efficient, and fast operation. A hybrid coarse-fine capacitive digital-to-analog converter (CapDAC) achieves 11.7 – <italic>bit</italic> effective resolution, and provides 83% area saving compared to a conventional binary weighted implementation. The prototype fabricated in a <inline-formula> <tex-math notation="LaTeX">$0.18\mu m$ </tex-math></inline-formula> CMOS technology is experimentally verified using MEMS capacitive pressure sensor. Experimental results show an energy efficiency figure-of-merit (FoM) of <inline-formula> <tex-math notation="LaTeX">$33fJ/Step$ </tex-math></inline-formula> which outperforms the state-of-the-art. The CDC output is insensitive to analog references; thus, a very low temperature sensitivity of <inline-formula> <tex-math notation="LaTeX">$2.3ppm/ {^{\circ }}C$ </tex-math></inline-formula> is achieved without the need for calibration.
Predicting disulfide connectivity patterns

Disulfide bonds play an important role in stabilizing protein structure and regulating protein function. Therefore, the ability to infer disulfide connectivity from protein sequences will be valuable in structural modeling and functional analysis. However, to predict disulfide connectivity directly from sequences presents a challenge to computational biologists due to the nonlocal nature of disulfide bonds, i.e., the close spatial proximity of the cysteine pair that forms the disulfide bond does not necessarily imply the short sequence separation of the cysteine residues. Recently, Chen and Hwang (Proteins 2005;61:507–512) treated this problem as a multiple class classification by defining each distinct disulfide pattern as a class. They used multiple support vector machines based on a variety of sequence features to predict the disulfide patterns. Their results compare favorably with those in the literature for a benchmark dataset sharing less than 30% sequence identity. However, since the number of disulfide patterns grows rapidly when the number of disulfide bonds increases, their method performs unsatisfactorily for the cases of large number of disulfide bonds. In this work, we propose a novel method to represent disulfide connectivity in terms of cysteine pairs, instead of disulfide patterns. Since the number of bonding states of the cysteine pairs is independent of that of disulfide bonds, the problem of class explosion is avoided. The bonding states of the cysteine pairs are predicted using the support vector machines together with the genetic algorithm optimization for feature selection. The complete disulfide patterns are then determined from the connectivity matrices that are constructed from the predicted bonding states of the cysteine pairs. Our approach outperforms the current approaches in the literature. Proteins 2007. © 2007 Wiley‐Liss, Inc.
Neural precursor cells from a fatal human motoneuron disease differentiate despite aberrant gene expression

Precursor cells of the human central nervous system can be cultured in vitro to reveal pathogenesis of diseases or developmental disorders. Here, we have studied the biology of neural precursor cells (NPCs) from patients of lethal congenital contracture syndrome (LCCS), a severe motoneuron disease leading to prenatal death before the 32nd gestational week. LCCS fetuses are immobile because of a motoneuron defect, seen as degeneration of the anterior horn and descending tracts of the developing spinal cord. The genetic defect for the syndrome is unknown. We show that NPCs isolated postmortem from LCCS fetuses grow and are maintained in culture, but display increased cell cycle activity. Global transcript analysis of undifferentiated LCCS precursor cells present with changes in EGF‐related signaling when compared with healthy age‐matched human controls. Further, we show that LCCS‐derived NPCs differentiate into cells of neuronal and glial lineage and that the initial differentiation is not accompanied by overt apoptosis. Cells expressing markers Islet‐1 and Hb9 are also generated from the LCCS NPCs, suggesting that the pathogenic mechanism of LCCS does not directly affect the differentiation capacity or survival of the cells, but the absence of motoneurons in LCCS may be caused by a noncell autonomous mechanism. © 2007 Wiley Periodicals, Inc. Develop Neurobiol, 2007
Exploring Interactions with Smart Windows for Sunlight Control

Window facades play an increasingly important role in modern architecture. Regular shutters and blinds allow only coarse control over the sunlight coming through windows. Smart windows using see-through displays can be controlled on a per-pixel basis and thereby have the potential of fine-grained control. In this paper, we explore future interaction with such smart windows and conducted an elicitation study with 16 potential users. We provide both a mid-air gesture set and a smartphone interface to define regions for glare protection and brightness control. The study was conducted on a working 1.6 x 2.6 m smart window prototype with 130 x 144 individually switchable pixels.
Les modèles multiniveau dans l'analyse écologique : le cas de la recherche en éducation

Pascal Bressoux, Paul Coustere, Christine Leroy-Audouin : Die Mehrebenenmodele der okologischen Analyse : der Fall der Forschung im Erziehungswesen. dem Bedurfnis, die Frage der Wahl der Analyseneinheit zu beantworten, wenn die Daten eine hierarchische Struktur aufweisen. Ein bevorzugtes Gebiet der Mehrebenenanalysen ist das Erziehungswesen, wo der Lernprozess der Schuler in einer Klasse und in einer Schule ablauft. Die Technik der Mehrebenenanalysen ist ein zusatzlicher Vorteil auf dem Gebiet der Spezifizierung zum Fortschritt auf dem okonometrischen Gebiet, weil sie insbesondere gleichzeitig die Modellisierung der Effizienz- und der Gerechtigkeitsdimensionen der Erziehungsmassnahmen erlaubt. Der Aufsatz mochte die klassischen Naherungsweisen und die Mehrebenenbehandlung des Problems der okologischen Analyse vergleichen, sowohl vom theoretischen Standpunkt aus, als auch vom Standpunkt der empirischen Ergebnisse. Hieraus entsteht ein besonders breites Anwendungsfeld der Mehrebenenanalysen zur Bewertung des Erziehungssystems und daruber hinaus zur Forschung in den Sozialwissenschaften. ; ; Die Mehrebenenanalysen sind eine kurzlich entstandene Modellisierung, angepasst an das Problem der okologischen Analyse in den Sozialwissenschaften, das heisst geeignet dazu, die Auswirkungen des Milieus auf das Verhalten des Einzelnen zu erklaren. Sie entstanden aus dem Bedurfnis, die Frage der Wahl der Analyseneinheit zu beantworten, wenn die Daten eine hierarchische Struktur aufweisen. Ein bevorzugtes Gebiet der Mehrebenenanalysen ist das Erziehungswesen, wo der Lernprozess der Schuler in einer Klasse und in einer Schule ablauft. Die Technik der Mehrebenenanalysen ist ein zusatzlicher Vorteil auf dem Gebiet der Spezifizierung zum Fortschritt auf dem okonometrischen Gebiet, weil sie insbesondere gleichzeitig die Modellisierung der Effizienz- und der Gerechtigkeitsdimensionen der Erziehungsmassnahmen erlaubt. Der Aufsatz mochte die klassischen Naherungsweisen und die Mehrebenenbehandlung des Problems der okologischen Analyse vergleichen, sowohl vom theoretischen Standpunkt aus, als auch vom Standpunkt der empirischen Ergebnisse. Hieraus entsteht ein besonders breites Anwendungsfeld der Mehrebenenanalysen zur Bewertung des Erziehungssystems und daruber hinaus zur Forschung in den Sozialwissenschaften.
Population-Based Estimate of Prostate Cancer Risk for Carriers of the HOXB13 Missense Mutation G84E

The HOXB13 missense mutation G84E (rs138213197) is associated with increased risk of prostate cancer, but the current estimate of increased risk has a wide confidence interval (width of 95% confidence interval (CI) >200-fold) so the point estimate of 20-fold increased risk could be misleading. Population-based family studies can be more informative for estimating risks for rare variants, therefore, we screened for mutations in an Australian population-based series of early-onset prostate cancer cases (probands). We found that 19 of 1,384 (1.4%) probands carried the missense mutation, and of these, six (32%) had a family history of prostate cancer. We tested the 22 relatives of carriers diagnosed from 1998 to 2008 for whom we had a DNA sample, and found seven more carriers and one obligate carrier. The age-specific incidence for carriers was estimated to be, on average, 16.4 (95% CI 2.5–107.2) times that for the population over the time frame when the relatives were at risk prior to baseline. We then estimated the age and birth year- specific cumulative risk of prostate cancer (penetrance) for carriers. For example, the penetrance for an unaffected male carrier born in 1950 was 19% (95% CI 5–46%) at age 60 years, 44% (95% CI 18–74%) at age 70 years and 60% (95% CI 30–85%) at age 80 years. Our study has provided a population-based estimate of the average risk of prostate cancer for HOXB13 missense mutation G84E carriers that can be used to guide clinical practice and research. This study has also shown that the majority of hereditary prostate cancers due to the HOXB13 missense mutation are ‘sporadic’ in the sense that unselected cases with the missense mutation do not typically report having a family history of prostate cancer.
Production , isolation and characterization of alkaline protease from Aspergillus versicolor PF / F / 107

An alkaline protease producing strain, Aspergillus versicolor PF/F/107 was isolated from soil samples of poultry farm of Jabalpur district of Madhya Pradesh and enzyme production was optimized under submerged conditions. Maximum enzyme production by the test isolate under optimized conditions occurred in mesophilic temperature 35°C and pH 9.0. Wheat bran and sodium nitrate proved to be the best carbon and nitrogen sources respectively. The enzyme showed optimum activity at pH 9.0 and found to retain residual activity at pH 8.0. Protease of Aspergillus versicolor PF/F/107 showed remarkably good activity at 50C with optimum at 40C indicating thermo tolerant nature of the enzyme. The enzyme was stable to desired levels of non-ionic surfactants such as Tween-20, Tween-80, Triton X-100 and ionic surfactants such as SDS. The enzyme retained 50%-76% of its original activity at 40C in the presence of detergents in the following order: Ghadi, Ujalla, Surf excel, Ariel and Tide indicating its suitability for application in detergent industry.
A urban rail transport network carrying capacity calculation method based on the logit model

This study proposed the definition of carrying capacity of rail network, and presents a method to calculate the networked railway carrying capacity. The main idea of this method is that, given the total initial send amount of the network, we increase an incremental to it each time, then obtained the OD matrix based on the OD distribution rate, and allocate the incremental passenger flow to each section of the network by using the Logit Model. So we can find the section which has the largest traffic in each line, determine whether it satisfies the limit of the departure interval and the load factor. If not continue to increase the fixed incremental and calculate circularly until it satisfies the restrictions. The finally calculated result is the carrying capacity of the rail network. Finally we take part of the Beijing subway network an a case to test the capacity calculation method. It shows that the method is feasible.
UNED: Improving Text Similarity Measures without Human Assessments

This paper describes the participation of UNED NLP group in the SEMEVAL 2012 Semantic Textual Similarity task. Our contribution consists of an unsupervised method, Heterogeneity Based Ranking (HBR), to combine similarity measures. Our runs focus on combining standard similarity measures for Machine Translation. The Pearson correlation achieved is outperformed by other systems, due to the limitation of MT evaluation measures in the context of this task. However, the combination of system outputs that participated in the campaign produces three interesting results: (i) Combining all systems without considering any kind of human assessments achieve a similar performance than the best peers in all test corpora, (ii) combining the 40 less reliable peers in the evaluation campaign achieves similar results; and (iii) the correlation between peers and HBR predicts, with a 0.94 correlation, the performance of measures according to human assessments.
Using Statistical Techniques and WordNet to Reason with Noisy Data

We collected data from non-experts over the web to create a common sense knowledge base for indoor home and office environments. In this paper, we discuss how we use statistical data dimension reduction and clustering techniques to determine consensus in the knowledge base. We explain the use of Latent Semantic Indexing in finding consensus. These statistical techniques make our system robust to noisy data in the knowledge base. Our work contrasts with traditional AI systems which are typically brittle as well as difficult to extend due to handcrafted pieces of knowledge in their knowledge bases. We then discuss how the WordNet hypernym hierarchy is used to generalize knowledge and perform inference about objects not in the knowledge base. WordNet also makes the reasoning system robust to vocabulary differences among people by using synonyms.
Using Semantic Web Technologies to Query and Manage Information within Federated Cyber-Infrastructures

A standardized descriptive ontology supports efficient querying and manipulation of data from heterogeneous sources across boundaries of distributed infrastructures, particularly in federated environments. In this article, we present the Open-Multinet (OMN) set of ontologies, which were designed specifically for this purpose as well as to support management of life-cycles of infrastructure resources. We present their initial application in Future Internet testbeds, their use for representing and requesting available resources, and our experimental performance evaluation of the ontologies in terms of querying and translation times. Our results highlight the value and applicability of Semantic Web technologies in managing resources of federated cyber-infrastructures.
Extremely-low-noise CMOS Image Sensor with high saturation capacity

We have developed a flat device structure, which we call “FLAT”, with no isolation grooves/ridges and no Si substrate etching in the imaging area of the CMOS Image Sensor (CIS). We employed this FLAT structure to achieve a 1.12 µm pitch pixel CIS with a 1.25 transistor/pixel architecture and excellent image quality. It uses FLAT transistors(Trs) that generate greatly-reduced 1/f noise, and FLAT isolators (Isos) that increase the saturation capacity (Qs) due to increasing both effective photodiode (PD) area and PD potential under low dark current.
Mouse Adenovirus Type 1 Infection in SCID Mice: an Experimental Model for Antiviral Therapy of Systemic Adenovirus Infections

ABSTRACT The importance of human adenovirus infections in immunocompromised patients urges for new and adequate antiadenovirus compounds. Since human adenoviruses are species specific, animal models for systemic adenovirus infections rely on a nonhuman adenovirus. We established mouse adenovirus type 1 (MAV-1) infection of BALB/c SCID mice as a model for the evaluation of antiadenovirus therapy. In vitro studies with mouse embryonic fibroblasts pointed to the acyclic nucleoside phosphonate cidofovir and the N-7-substituted acyclic derivative 2-amino-7-(1,3-dihydroxy-2-propoxymethyl)purine (S-2242) as markedly active compounds against MAV-1. SCID mice, infected intranasally with MAV-1, developed a fatal disseminated infection after approximately 19 days, characterized by hemorrhagic enteritis. Several techniques were optimized to monitor viral, immunological, and pathological aspects of MAV-1 infection. Real-time PCR quantification of viral DNA revealed that after replication in the lungs, virus disseminated to several organs, including the brain, liver, spleen, intestine, heart, and kidneys (resulting in viruria). Immunohistochemical staining showed that MAV-1 was localized in the endothelial cells of the affected organs. Using reverse transcription-PCR, tissue levels of proinflammatory cytokines (i.e., interleukin-1β and tumor necrosis factor alpha) were found to be markedly increased. The MAV-1/SCID model appears to be an appropriate model for in vivo evaluation of antiadenovirus agents. Treatment with cidofovir or S-2242 at a dose of 100 mg per kg of body weight resulted in a significant delay in MAV-1-related death, although these antivirals were unable to completely suppress virus replication despite continued drug treatment. These findings suggest that complete virus clearance during antiviral therapy for disseminated adenovirus infection may require an efficient adaptive immune response from the host.
An architecture to automate performance tests on microservices

The microservices architecture provides a new approach to develop applications. As opposed to monolithic applications, in which the application comprises a single software artifact, an application based on the microservices architecture is composed by a set of services, each one designed to perform a single and well-defined task. These services allow the development team to decouple several parts of the application using different frameworks, languages and hardware for each part of the system. One of the drawbacks for adopting the microservices architecture to develop applications is testability. In a single application test boundaries can be more easily established and tend to be more stable as the application evolves, while with microservices we can have a set of hundreds of services that operate together and are prone to change more rapidly. Each one of these services needs to be tested and updated as the service changes. In addition, the different characteristics of these services such as languages, frameworks or the used infrastructure have to be considered in the testing phase. Performance tests are applied to assure that a particular software complies with a set of non-functional requirements such as throughput and response time. These metrics are important to ensure that business constraints are respected and to help finding performance bottlenecks. In this paper, we present a new approach to allow the performance tests to be executed in an automated way, with each microservice providing a test specification that is used to perform tests. Along with the architecture, we also provide a framework that implements some key concepts of this architecture. This framework is available as an open source project1.