Miracle-dz/UniFAR-FTUs huggingface dataset:
METEOR

With increasing application complexity and improvements in process technology, Chip MultiProcessors (CMPs) with tens to hundreds of cores on a chip are becoming a reality. Networks-on-Chip (NoCs) have emerged as scalable communication fabrics that can support high bandwidths for these massively parallel multicore systems. However, traditional electrical NoC implementations still need to overcome the challenges of high data transfer latencies and large power consumption. On-chip photonic interconnects with high performance-per-watt characteristics have recently been proposed as an alternative to address these challenges for intra-chip communication. In this article, we explore using low-cost photonic interconnects on a chip to enhance traditional electrical NoCs. Our proposed hybrid photonic ring-mesh NoC (METEOR) utilizes a configurable photonic ring waveguide coupled to a traditional 2D electrical mesh NoC. Experimental results indicate a strong motivation to consider the proposed architecture for future CMPs, as it can provide about 5× reduction in power consumption and improved throughput and access latencies, compared to traditional electrical 2D mesh and torus NoC architectures. Compared to other previously proposed hybrid photonic NoC fabrics such as the hybrid photonic torus, Corona, and Firefly, our proposed fabric is also shown to have lower photonic area overhead, power consumption, and energy-delay product, while maintaining competitive throughput and latency.
CartaBlanca—a pure‐Java, component‐based systems simulation tool for coupled nonlinear physics on unstructured grids—an update

This paper describes a component‐based nonlinear physical system simulation prototyping package written entirely in Java using object‐oriented design. The package provides scientists and engineers with a ‘developer‐friendly’ software environment for large‐scale computational algorithm and physical model development. The software design centers on the Jacobian‐free Newton–Krylov solution method surrounding a finite‐volume treatment of conservation equations. This enables a clean component‐like implementation. We first provide motivation for the development of the software and then discuss software structure. The discussion includes a description of the use of Java's built‐in thread facility that enables parallel, shared‐memory computations on a wide variety of unstructured grids with triangular, quadrilateral, tetrahedral and hexahedral elements. We also discuss the use of Java's inheritance mechanism in the construction of a hierarchy of physics systems objects and linear and nonlinear solver objects that simplify development and foster software re‐use. We provide a brief review of the Jacobian‐free Newton–Krylov nonlinear system solution method and discuss how it fits into our design. Following this, we show results from example calculations and then discuss plans including the extension of the software to distributed‐memory computer systems. Copyright © 2003 John Wiley & Sons, Ltd.
Advances in Cognitive Therapy for Schizophrenia: Empowerment and Recovery in the Absence of Insight

Lack of awareness of a mental disorder is a prevalent feature of schizophrenia and is associated with poor outcome. Cognitive therapy (CT) is a promising adjunctive treatment for schizophrenia but is believed to be less efficacious for patients with poor insight. This article describes a goal-oriented CT approach that was innovated to circumvent limited insight in a young woman with severe paranoid delusions and auditory hallucinations. The treatment facilitated recovery by targeting avoidance, inactivity, and social withdrawal, and by promoting detachment from psychotic experiences without directly challenging delusional beliefs. The case study demonstrates the involvement of family in CT and the use of behavioral exercises to modify dysfunctional beliefs and behaviors. Results are consistent with recently advanced cognitive conceptualizations of schizophrenia and suggest that when appropriately tailored and focused on functional goals, CT can promote recovery in the absence of insight.
Built-in sequential fault self-testing of array multipliers

Microprocessor datapath architectures operate on signed numbers usually represented in two's-complement or sign-magnitude formats. The multiplication operation is performed by optimized array multipliers of various architectures which are often produced by automatic module generators. Array multipliers have either a standard, nonrecoded signed (or unsigned) architecture or a recoded (modified Booth's algorithm) architecture. High-quality testing of array multipliers based on a comprehensive sequential fault model and not affecting their well-optimized structure has not been proposed in the past. In this paper, we present a built-in self-testing (BIST) architecture for signed and unsigned array multipliers with respect to a comprehensive sequential fault model. The BIST architecture does not alter the well-optimized multiplier structure. The proposed test sets can be applied externally but their regular nature makes them very suitable for embedded, self-test application by simple specialized hardware which imposes small overheads. Two different implementations of the BIST architecture are proposed. The first implementation focuses on the test invalidation problem and targets robust sequential fault testing, while the second one focuses on test cost reduction (test time and hardware overhead).
Edge-based Scheduled BP in LDPC Codes

This paper studies the potential performance gain, referred to as scheduling gain, when decoding LDPC codes using scheduled belief-propagation. Introducing genie-aided scheduling, it is shown that the scheduling-gain can be quite impressive for moderate and short-length codes. Adaptive schedule based on edge ordering is presented. This approach compares favorably with serial scheduling schemes based on random node ordering. Density evolution-based analysis appropriately tailored for decoding finite-length LDPC codes is provided. For serial decoding and genie-aided decoding, it is shown that the performance in the first iteration can be accurately predicted analytically using the proposed technique.
Advancing the Art & Science of Daylighting Design

Associate Professor, Engineering Design & Professional Programs, Pennsylvania State University, 213-F Hammond Building, University Park, PA 16802, Phone: 814-863-9075. Fax: 814-863-7229. E-mail: andylau@psu.edu Associate Professor, Architectural Engineering, Pennsylvania State University, 104 Engineering Unit A, University Park, PA 16802, Phone: 814-863-2086. Fax: 814-863-4789. E-mail: rmistrick@psu.edu
Keeping an eye for HCI

Advanced human-computer interaction (HCI) techniques are required to enhance current computer interfaces. In this paper, we present an eye gaze tracking system based on a robust low-cost real-time pupil detector, and we describe some eye-aware applications that are being developed to enhance HCI. Images of pupils are segmented using an active lighting scheme that exploits very particular properties of eyes. Once the pupil is detected, its center is tracked, along with the corneal reflection (CR) generated by the light sources. Assuming little head motion, the eye gaze direction is computed based on the vector between the centers of the CR and the pupil, after a brief calibration procedure. Other information, such as pupil size and blink rate, can also be made available. The current prototype runs at frame rate, providing 30 samples of the gaze position per second to gaze-aware applications, such as advanced pointing and selection mechanisms.
Regional Controllability of linear and semi linear Hyperbolic Systems

This work concerns regional controllability of linear and semi linear hyperbolic systems as in ([9, 10, 11]) but the results are established with more flexible conditions. Also we consider the case where the subregion of interest is a boundary part of the system evolution domain.Then we give illustrations of different results through many examples and simulations.
On the complexity of learning from counterexamples

The complexity of learning concepts belonging to various concrete concept classes C contained in 2/sup X/ over a finite domain X is analyzed in terms of the number of counterexamples that are needed in the worst case. It turns out that for many interesting concept classes there exist exponential differences between the number of counterexamples that are required by a 'naive' learning algorithm for C (e.g. one that always outputs the minimal consistent hypothesis) and a 'smart' learning algorithm for C, which attempts to make a more sophisticated prediction. theta (log n) bounds are given for the number of counterexamples that are required for learning boxes, balls, and halfspaces in a d-dimensional discrete space X=(1, . . ., n)/sup d/ (for every finite dimension d). Also given are an upper bound of O(d/sup 3/) and a lower bound of Omega (d/sup 2/) for the complexity of learning a threshold function with d input bits (i.e. X=(0, 1)/sup d/). For each of these concept classes one can give learning algorithms that are both optimal (or close to optimal in the case of threshold functions) with regard to the number of counterexamples which they require and computationally feasible. The complexity of learning the concept classes on several variations of the learning model considered is determined. The relationship between these learning models and some related combinatorial invariants is clarified. <<ETX>>
Analysis of Variance for Gene Expression Microarray Data

Spotted cDNA microarrays are emerging as a powerful and cost-effective tool for large-scale analysis of gene expression. Microarrays can be used to measure the relative quantities of specific mRNAs in two or more tissue samples for thousands of genes simultaneously. While the power of this technology has been recognized, many open questions remain about appropriate analysis of microarray data. One question is how to make valid estimates of the relative expression for genes that are not biased by ancillary sources of variation. Recognizing that there is inherent "noise" in microarray data, how does one estimate the error variation associated with an estimated change in expression, i.e., how does one construct the error bars? We demonstrate that ANOVA methods can be used to normalize microarray data and provide estimates of changes in gene expression that are corrected for potential confounding effects. This approach establishes a framework for the general analysis and interpretation of microarray data.
Star formation rates of distant luminous infrared galaxies derived from Hα and IR luminosities

We present a study of the star formation rate ( SFR ) for a sample of 16 distant galaxies detected by ISOCAM at 15 μ m in the CFRS0300+00 and CFRS1400+52 fields. Their high quality and intermediate resolution VLT/FORS spectra have allowed a proper correction of the Balmer emission lines from the underlying absorption. Extinction estimates using the H β /H γ and the H α /H β Balmer decrement are in excellent agreement, providing a robust measurement of the instantaneous SFR based on the extinction-corrected H α luminosity. Star formation has also been estimated exploiting the correlations between IR luminosity and those at MIR and radio wavelengths. Our study shows that the relationship between the two SFR estimates follow two distinct regimes: (1) for galaxies with SFR IR below ~100 $M_{\odot}$/yr, the SFR deduced from H α measurements is a good approximation of the global SFR and (2) for galaxies near ULIRG regime. The corrected H α SFR understimated the SFR by a factor of 1.5 to 2. Our analyses suggest that heavily extincted regions completely hidden in optical bands (such as those found in Arp 220) contribute less than 20% of the global budget of star formation up to $z=1$.
Self-Esteem: Clinical Assessment and Measurement Validation

In this study, self-esteem refers to feelings of satisfaction a person has about himself which reflect the relationship between his self-image and his ideal self-image. Different measures of self-esteem, related to this definition, were studied in a sample of 44 late adolescent Ss. Test measures and interview assessment of self-esteem met certain criteria of validity as outlined by Campbell and Fiske. Clinical configurations of self-esteem, including defensive aspects, are described and related to the test measures.
Time-Course Changes of Oxidative Stress Response to High-Intensity Discontinuous Training versus Moderate-Intensity Continuous Training in Masters Runners

Beneficial systemic effects of regular physical exercise have been demonstrated to reduce risks of a number of age-related disorders. Antioxidant capacity adaptations are amongst these fundamental changes in response to exercise training. However, it has been claimed that acute physical exercise performed at high intensity (>60% of maximal oxygen uptake) may result in oxidative stress, due to reactive oxygen species being generated excessively by enhanced oxygen consumption. The aim of this study was to evaluate the effect of high-intensity discontinuous training (HIDT), characterized by repeated variations of intensity and changes of redox potential, on oxidative damage. Twenty long-distance masters runners (age 47.8±7.8 yr) on the basis of the individual values of gas exchange threshold were assigned to a different 8-weeks training program: continuous moderate-intensity training (MOD, n = 10) or HIDT (n = 10). In both groups before (PRE) and after (POST) training we examined the following oxidative damage markers: thiobarbituric acid reactive substances (TBARS) as marker of lipid peroxidation; protein carbonyls (PC) as marker of protein oxidation; 8-hydroxy-2-deoxy-guanosine (8-OH-dG) as a biomarker of DNA base modifications; and total antioxidant capacity (TAC) as indicator of the overall antioxidant system. Training induced a significant (p<0.05) decrease in resting plasma TBARS concentration in both MOD (7.53±0.30 and 6.46±0.27 µM, PRE and POST respectively) and HIDT (7.21±0.32 and 5.85±0.46 µM, PRE and POST respectively). Resting urinary 8-OH-dG levels were significantly decreased in both MOD (5.50±0.66 and 4.16±0.40 ng mg−1creatinine, PRE and POST respectively) and HIDT (4.52±0.50 and 3.18±0.34 ng mg−1creatinine, PRE and POST respectively). Training both in MOD and HIDT did not significantly modify plasma levels of PC. Resting plasma TAC was reduced in MOD while no significant changes were observed in HIDT. In conclusion, these results suggest that in masters runners high-intensity discontinuous does not cause higher level of exercise-induced oxidative stress than continuous moderate-intensity training, inducing similar beneficial effects on redox homeostasis.
Camera self-Calibration with Varying Parameters from Two views

This work presents a practical and new approach of self-calibration of cameras with varying parameters, by an unknown planar scene. We show that the estimation of the different parameters of the cameras used can be made from only two matches between two images of the planar scene. The strong point of our method resides at minimizing constraints on the self-calibration system (firstly we estimate the different parameters from only two images, secondly we use only two matches between these images, and thirdly we use the cameras having the varying parameters). The principal idea of our approach is based on demonstrating the relationship between two matches which have a best correlation score ZNCC and the relationship between images of absolute conic for the couple of images. These relations permit to formulate a non-linear cost function, its resolution provides the intrinsic parameters of the cameras used. The robustness of our method in terms of simplicity, stability, accuracy and convergence is shown by the experiment results and the simulations realized.
Splice site prediction in Arabidopsis thaliana pre-mRNA by combining local and global sequence information.

Artificial neural networks have been combined with a rule based system to predict intron splice sites in the dicot plant Arabidopsis thaliana. A two step prediction scheme, where a global prediction of the coding potential regulates a cutoff level for a local prediction of splice sites, is refined by rules based on splice site confidence values, prediction scores, coding context and distances between potential splice sites. In this approach, the prediction of splice sites mutually affect each other in a non-local manner. The combined approach drastically reduces the large amount of false positive splice sites normally haunting splice site prediction. An analysis of the errors made by the networks in the first step of the method revealed a previously unknown feature, a frequent T-tract prolongation containing cryptic acceptor sites in the 5' end of exons. The method presented here has been compared with three other approaches, GeneFinder, Gene-Mark and Grail. Overall the method presented here is an order of magnitude better. We show that the new method is able to find a donor site in the coding sequence for the jelly fish Green Fluorescent Protein, exactly at the position that was experimentally observed in A.thaliana transformants. Predictions for alternatively spliced genes are also presented, together with examples of genes from other dicots, monocots and algae. The method has been made available through electronic mail (NetPlantGene@cbs.dtu.dk), or the WWW at http://www.cbs.dtu.dk/NetPlantGene.html
Social Capital and User Acceptance of Enterprise System: Mediating Role of Local Management Commitment

This study builds a multi-level research model to investigate how social capital between business units and the headquarters in large-scale organizations influences individual user acceptance of enterprise systems. Drawing on social capital theory and the human agency theory, this study argues that local management of business units plays the role of interpreting signals and messages from the headquarters, such that it can mediate the effect of social capital (which is composed of structural, relational, and cognitive dimensions) on symbolic adoption of the enterprise technology. To test the research hypotheses, a field study is conducted on 222 users of an enterprise system in 29 business units of a major financial institution in China. The results indicate that the effects of relational capital and cognitive capital on user acceptance are mediated by user perception of local management commitment; and relational capital and cognitive capital mediate the effect of structural capital on user perception of local management commitment. Limitations, theoretical implications are discussed, and practical guidance is suggested.
Skills Mismatch? Military Service, Combat Occupations, and Civilian Earnings

Research has evaluated the impact of military service on socioeconomic outcomes, but little research has assessed the association between such outcomes and military occupations. The following article examines this relationship by analyzing the National Longitudinal Study of Youth 1979. It evaluates whether military occupations produce associations that are consistent with hypotheses based on theories of skills mismatch, selection, or turning points. Contrary to expectations, veterans of combat occupations did not have different earnings from those of other occupations, which suggests that any apparent effects of combat exposure reflect neither skills mismatch nor selection into these roles. Yet veterans earned less than nonveterans at the same years of combined military and civilian experience, regardless of occupation. These findings indicate that employers did not value time in the military as much as time in the civilian labor market.
Missing Cells: Pathophysiology, Diagnosis, and Management of (Pan)Cytopenia in Childhood

Peripheral blood cytopenia in children can be due to a variety of acquired or inherited diseases. Genetic disorders affecting a single hematopoietic lineage are frequently characterized by typical bone marrow findings, such as lack of progenitors or maturation arrest in congenital neutropenia or a lack of megakaryocytes in congenital amegakaryocytic thrombocytopenia, whereas antibody-mediated diseases such as autoimmune neutropenia are associated with a rather unremarkable bone marrow morphology. By contrast, pancytopenia is frequently associated with a hypocellular bone marrow, and the differential diagnosis includes acquired aplastic anemia, myelodysplastic syndrome, inherited bone marrow failure syndromes such as Fanconi anemia and dyskeratosis congenita, and a variety of immunological disorders including hemophagocytic lymphohistiocytosis. Thorough bone marrow analysis is of special importance for the diagnostic work-up of most patients. Cellularity, cellular composition, and dysplastic signs are the cornerstones of the differential diagnosis. Pancytopenia in the presence of a normo- or hypercellular marrow with dysplastic changes may indicate myelodysplastic syndrome. More challenging for the hematologist is the evaluation of the hypocellular bone marrow. Although aplastic anemia and hypocellular refractory cytopenia of childhood (RCC) can reliably be differentiated on a morphological level, the overlapping pathophysiology remains a significant challenge for the choice of the therapeutic strategy. Furthermore, inherited bone marrow failure syndromes are usually associated with the morphological picture of RCC, and the recognition of these entities is essential as they often present a multisystem disease requiring different diagnostic and therapeutic approaches. This paper gives an overview over the different disease entities presenting with (pan)cytopenia, their pathophysiology, characteristic bone marrow findings, and therapeutic approaches.
Multiplicity Adjustment for Composite Binary Endpoints

Summary Background: Binary composite outcome measures are increasingly used as primary endpoints in clinical trials. Composite endpoints combine several events of interest within a single variable. However, as the effect observed for the composite does not necessarily reflect the effects for the individual components, it is recommended in the literature to additionally evaluate each component separately. Objectives: The task is to define an adequate multiple test procedure which focuses on the composite outcome measure but allows for a confirmatory interpretation of the components in case of large effects. Methods: In this paper, we determine the correlation matrix for a multiple binary endpoint problem of a composite endpoint and its components based on the normal approximation test statistic for rates. Thereby, we assume multinomial distributed components. We use this correlation to calculate the adjusted local significance levels. We discuss how to use our approach for a more informative formulation of the test problem. Our work is illustrated by two clinical trial examples. Results: By taking into account the special correlation structure between a binary composite outcome and its components, an adequate multiple test procedure to assess the composite and its components can be defined based on an approximate multivariate normal distribution without much loss in power compared to a test problem formulated exclusively for the composite. Conclusions: By incorporating the correlation under the null hypotheses, the global power for the multiple test problem assessing both the composite and its components can be increased as compared to simple Bonferroni-adjustment. Thus, a confirmatory analysis of the composite and its components might be possible without a large increase in sample size as compared to a single endpoint problem formulated exclusively for the composite