Miracle-dz/UniFAR-FTUs huggingface dataset:
Transient Fault Tolerance on Chip Multiprocessor Based on Dual and Triple Core Redundancy

To address the increasing susceptibility of microprocessors to transient faults, many techniques have been proposed to exploit the core redundancy of chip multiprocessors (CMPs). But the inter-core communications become critical in these core redundancy based techniques. To reduce the inter-core communication bandwidth demand, two new approaches, dual core redundancy (DCR) and triple core redundancy (TCR), are proposed for fault tolerance in this paper. In DCR, only store instructions are compared before commit, so that the bandwidth demand can be largely reduced. And the fault recovery is achieved by context saving and recovery. While TCR applies triple modular redundancy (TMR) in the core level to efficiently exploit the core resources of CMPs for transient fault masking. In TCR, only the results of store instructions are compared to detect transient fault and reduce the inter-core communication bandwidth demand. Once detecting a single event upset (SEU), TCR can be reconfigured to execute with the two uncorrupted cores for fault detection.The experimental results demonstrate that compared to traditional transient fault recovery scheme CRTR, both DCR and TCR efficiently reduce inter-core bandwidth demand. DCR achieves transient fault recovery with reasonable performance overhead caused by context saving. TCR occupies more core resources and has the lowest performance overhead during normal execution.
Fibrinolysis in Trauma: “Myth,” “Reality,” or “Something in Between”

Abstract The emphasis on fibrinolysis as an important contributor to trauma-induced coagulopathy (TIC) has led to a debate regarding the relative clinical significance of fibrinolysis in the setting of trauma. The debate has centered on two camps. The one camp defines fibrinolysis in trauma by standard coagulation tests as well as fibrin split products, D-dimers, and plasmin/antiplasmin levels. This camp favors a more liberal use of tranexamic acid and attributes more significance to hyperfibrinolysis in TIC. The other camp favors a definition of fibrinolysis based on the viscoelastic tests (VET), rotational thromboelastometry (ROTEM), and thromboelastography (TEG). These whole blood assays define hyperfibrinolysis at a higher threshold than plasma-based tests. Therefore, this VET camp reserves antifibrinolytic treatment for patients who demonstrate severe coagulopathy associated with hyperfibrinolysis. This bimodal attribution of the clinical relevance of fibrinolysis in trauma suggests that there may be an underlying “Myth” of the concept of TIC that was historically defined by plasma-based tests and a future “Reality” of the concept of TIC that is grounded on an understanding of TIC based on a VET-defined “fibrinolytic spectrum” of TIC. This narrative review explores this “Myth” and “Reality” of fibrinolysis in TIC and proposes a direction that will allow a “Future” interpretation of TIC that incorporates both the past “Myth” and present “Reality” of fibrinolysis TIC.
Active Search and Bandits on Graphs using Sigma-Optimality

Many modern information access problems involve highly complex patterns that cannot be handled by traditional keyword based search. Active Search is an emerging paradigm that helps users quickly find relevant information by efficiently collecting and learning from user feedback. We consider active search on graphs, where the nodes represent the set of instances users want to search over and the edges encode pairwise similarity among the instances. Existing active search algorithms are either short of theoretical guarantees or inadequate for graph data. Motivated by recent advances in active learning on graphs, namely the Σ-optimality selection criterion, we propose new active search algorithms suitable for graphs with theoretical guarantees and demonstrate their effectiveness on several real-world datasets. We relate our active search setting to multi-armed bandits whose rewards are binary values indicating search hits or misses and arms cannot be pulled more than once. We also discussed theoretical guarantees for applying Σ-optimality as the exploration term for bandits on graphs.
Dependent Online Kernel Learning With Constant Number of Random Fourier Features

Traditional online kernel learning analysis assumes independently identically distributed (i.i.d.) about the training sequence. Recent studies reveal that when the loss function is smooth and strongly convex, given T i.i. d. training instances, a constant sampling complexity of random Fourier features is sufficient to ensure O(log T/T) convergence rate of excess risk, which is optimal in online kernel learning up to a log T factor. However, the i.i. d. hypothesis is too strong in practice, which greatly impairs their value. In this paper, we study the sampling complexity of random Fourier features in online kernel learning under non-i.i. d. assumptions. We prove that the sampling complexity under non-i.i. d. settings is also constant, but the convergence rate of excess risk is O(log T/T+ φ ), where φ is the mixing coefficient measuring the extent of non-i.i. d. of training sequence. We conduct experiments both on artificial and real large-scale data sets to verify our theories.
Improved Calibration of High-Dimensional Precision Matrices

Estimation of a precision matrix (i.e., the inverse covariance matrix) is a fundamental problem in statistical signal processing applications. When the observation dimension is of the same order of magnitude as the number of samples, the conventional estimators of covariance matrix and its inverse perform poorly. In order to obtain well-behaved estimators in high-dimensional settings, we consider a general class of estimators of covariance matrices and precision matrices based on weighted sampling and linear shrinkage. The estimation error is measured in terms of both quadratic loss and Stein's loss, and these loss functions are used to calibrate the set of parameters defining our proposed estimator. In an asymptotic setting where the observation dimension is comparable in magnitude to the number of samples, we provide estimators of the precision matrix that are as good as their oracle counterparts. We test our estimators with both synthetic data and financial market data, and Monte Carlo simulations show the advantage of our precision matrix estimator compared with well known estimators in finite sample size settings.
Flow Cytometry Total Cell Counts: A Field Study Assessing Microbiological Water Quality and Growth in Unchlorinated Drinking Water Distribution Systems

The objective of this study was to evaluate the application of flow cytometry total cell counts (TCCs) as a parameter to assess microbial growth in drinking water distribution systems and to determine the relationships between different parameters describing the biostability of treated water. A one-year sampling program was carried out in two distribution systems in The Netherlands. Results demonstrated that, in both systems, the biomass differences measured by ATP were not significant. TCC differences were also not significant in treatment plant 1, but decreased slightly in treatment plant 2. TCC values were found to be higher at temperatures above 15°C than at temperatures below 15°C. The correlation study of parameters describing biostability found no relationship among TCC, heterotrophic plate counts, and Aeromonas. Also no relationship was found between TCC and ATP. Some correlation was found between the subgroup of high nucleic acid content bacteria and ATP (R 2 = 0.63). Overall, the results demonstrated that TCC is a valuable parameter to assess the drinking water biological quality and regrowth; it can directly and sensitively quantify biomass, detect small changes, and can be used to determine the subgroup of active HNA bacteria that are related to ATP.
An experimental evaluation of selective mutation

Mutation testing is a technique for unit-testing software that, although powerful, is computationally expensive. The principal expense of mutation is that many variants of the test program, called mutants, must be repeatedly executed. Selective mutation is a way to approximate mutation testing that saves execution by reducing the number of mutants that must be executed. The authors report experimental results that compare selective mutation testing to standard, or nonselective, mutation testing. The results support the hypothesis that selective mutation is almost as strong as nonselective mutation. In experimental trials, selective mutations provide almost the same coverage as nonselective mutation, with significant reductions in cost. <<ETX>>
PROTOTYPES AND MODULATION FUNCTIONS OF CLASSICAL AND NOVEL CONFIGURATIONS OF OPTICAL CHOPPER WHEELS

Optical choppers with rotating wheels are some of the most used macroscopic optomechatronic devices for the controlled modulation, attenuation or obscuration of light in a wide area of applications. We discuss and compare the modulation functions produced by two types of chopper wheels: the classical device, with windows with linear edges, and the eclipse chopper (with windows with circular edges) that, to the best of our knowledge, we have introduced. This discussion is based on the analysis and the design we have previously developed for these various devices, for top-hat (constant over the entire section) light beam distributions. While the comparison of the different shapes of transmitted signals allows for the proper choice of the most appropriate device and parameters to obtain the modulation function that is fit for a certain application, the present work also presents the mechanical setup we have designed and manufactured for testing choppers with rotating wheels. A series of prototype wheels with different, optimized profiles were obtained for the purpose. The simulation and the electro-erosion programs for the wire electro-erosion of aluminum plates to manufacture the wheels are presented. An advantageous double wheel solution has been developed to obtain wheels with windows of different shapes and sizes, and the testing of this final assembly concludes the study.
Statistical model migration in speaker recognition

In large-scale deployments of speaker recognition systems the potential for legacy problems increases as the evolving technology may require configuration changes in the system thus invalidating already existing user voice accounts. Unless the entire database of original speech waveform were stored, users need to reenroll to keep their accounts functional, which, however, may be expensive and commercially not acceptable. We define model migration as a conversion of obsolete models to new-configuration models without additional data and waveform requirements and investigate ways to achieve such a migration with minimum loss of system accuracy. As a proof-of-concept, an algorithm for statistical migration in the Maximum A-Posteriori framework is studied and evaluated experimentally using the NIST SRE-03 dataset. The migration step is discussed in a wider conceptual framework of Conversational Biometrics.
Automatic assessment of the content of essays based on course materials

Assessing free-text responses, like essays, is a demanding task even for a human. To reduce the costs of essay grading, methods to automate the assessment process have been developed. Approaches based on surface features and content have been introduced. We present a method for evaluating the content of essays based on latent semantic analysis (LSA), which was originally developed for information retrieval and has successfully been applied for assessment of essays in several applications. We use LSA to compare the conceptual similarity between the essays and selected text passages from the course material covering the essay assignment-specific subject matter. In our experiment the correlation between the scores given by the system and human grader varied from 0.78 to 0.82.
Children's writing : toward a process theory of the development of skilled writing

The magical number three, plus or minus two: working memory in writing, Deborah McCutchen Working memory as a source of individual differences in children's writing, H. Lee Swanson, Virginia W. Berninger Modifying hayes and flowers model of skilled writing to explain beginning and developing writing, Virginia W. Berninger, H. Lee Swanson Topic knowledge, linguistic knowledge, and revision processes as determinants of text revision, Earl C. Butterfield et al Comprehension monitoring as a writing process, Douglas J. Hacker Helping students with learning disabilities plan compositions: instruction in cognitive and metacognitive strategies, Charles A. MacArthur et al Diverse data about writing processes and their theoretical implications, Earl C. Butterfield.
Comparison of strategies for model predictive control for home heating in future energy systems

Model predictive control is seen as one of the key future enabler in increasing energy efficiency in buildings. This paper presents a comparison of the performance of the control for different formulations of the objective function. This comparison is made in a simulation study on a single building using historical weather and power system data from Denmark. Trade-offs between energy consumption, comfort and incurred CO2 emissions depending on the chosen objective function are quantified, highlighting the need to carefully select the strategy used in future design and implementation, rather than simply operating energy or SPOT price optimisation.
Real-time 6DoF localization for a mobile robot using pre-computed 3D laser likelihood field

This paper proposes a real-time full-6DoF localization method designed for a mobile robot moving in human-inhabited environments. The field of robotics is expanding, and 6DoF pose estimation in the real world is an important function for robots. The proposed method is based on typical Monte-Carlo Localization algorithm, and we expanded it to 6DoF realtime pose estimation. For real-time calculation, the proposed method uses 3D Laser Likelihood Field generated from pre-computed 3D environment map. The 3D Laser Likelihood Field is represented voxels including the distance between its center and the nearest neighbor obstacle. To speed up the calculation of matching score between 3D environmental map and 3D-LIDAR point cloud, we apply it to the measurement process of Monte-Carlo Localization. The system is evaluated with MoCap and demonstrated in human-inhabited environments. As these experiments illustrated, the robot could estimate its self-pose robustly in real-time with the algorithm running on an ordinary notebook PC.
Sign-Constrained Regularized Loss Minimization

In practical analysis, domain knowledge about analysis target has often been accumulated, although, typically, such knowledge has been discarded in the statistical analysis stage, and the statistical tool has been applied as a black box. In this paper, we introduce sign constraints that are a handy and simple representation for non-experts in generic learning problems. We have developed two new optimization algorithms for the sign-constrained regularized loss minimization, called the sign-constrained Pegasos (SC-Pega) and the sign-constrained SDCA (SC-SDCA), by simply inserting the sign correction step into the original Pegasos and SDCA, respectively. We present theoretical analyses that guarantee that insertion of the sign correction step does not degrade the convergence rate for both algorithms. Two applications, where the sign-constrained learning is effective, are presented. The one is exploitation of prior information about correlation between explanatory variables and a target variable. The other is introduction of the sign-constrained to SVM-Pairwise method. Experimental results demonstrate significant improvement of generalization performance by introducing sign constraints in both applications.
Micro-SPE in pipette tips as a tool for analysis of small-molecule drugs in serum.

AIM Micro-SPE in pipette tips (μ-SPE-PT) with particle sorbent has never been used in small-molecule drug analysis. Methodology & results: μ-SPE-PT was used for the extraction of statins from biological materials followed by UHPLC-MS/MS. The commercial and homemade μ-SPE-PT tips filled with particle sorbent were compared. While the homemade tips enabled direct serum sample loading into the sorbent, protein precipitation (PP) had to be implemented before μ-SPE-PT procedure using commercial tips. Three μ-SPE-PT methods were developed and validated: method A: μ-SPE-PT with homemade tips; method B: PP + μ-SPE-PT with homemade tips; and method C: PP + μ-SPE-PT with commercial tips. Method A enabled a simple high-throughput approach (48 samples in 90 min) compared with methods B and C that required three-times longer time. However, PP increased the recoveries of protein-bound analytes and extracts purity in methods B and C. The matrix effects without internal standards correction for method C were significantly higher than those for the methods A and B. CONCLUSION Compared with commercial tips, homemade tips filled with particles were found to be more suitable for drug analysis. Commercial tips tested in this study were found challenging but the conditions under which they could be applicable were also defined.
Self-Organization and Identification of Web Communities

The vast improvement in information access is not the only advantage resulting from the increasing percentage of hyperlinked human knowledge available on the Web. Additionally, much potential exists for analyzing interests and relationships within science and society. However, the Web's decentralized and unorganized nature hampers content analysis. Millions of individuals operating independently and having a variety of backgrounds, knowledge, goals and cultures author the information on the Web. Despite the Web's decentralized, unorganized, and heterogeneous nature, our work shows that the Web self-organizes and its link structure allows efficient identification of communities. This self-organization is significant because no central authority or process governs the formation and structure of hyperlinks.
Tributyltin contamination in bivalves from United States coastal estuaries.

(14) Yalkowsky, S. H. ; Valvani, S. C. J. Chem. Eng. Data 1979, (20) Kier, L. B. ; Hall, L. H. Molecular Connectivity in ChemTechnol. 1982,16,4-10. istry and Drug Research; Academic: New York, 1976. (21) Spiegel, M. R. Schaum's Outline of Theory and Problems Sei. 1983, 72, 866-870. of Probability and Statistics. Schaum's Outline Series in Mathematics; McGraw-Hill: New York, 1975. Sei. 1981, 70, 502-507. (22) Kanazawa, J. Rev. Plant Prot. Res. 1980, 13, 27-36. (23) Tulp, M. Th. M. ; Hutzinger, 0. Chemosphere 1978, 10,
System Demo: A geo-coding service encompassing a geo-parsing tool and integrated digital gazetteer service

We describe a basic Geo-coding service encompassing a geo-parsing tool and integrated digital gazetteer service. The development of a geo-parser comes from the need to explicitly georeference large resource collections such as the Statistical Accounts of Scotland which currently only contain implicit georeferences in the form of placennames thus making such collections inherently geographically searchable.
Established and Novel Initiatives to Reduce Crowding in Emergency Departments

Introduction: The American College of Emergency Physicians (ACEP) Task Force on Boarding described high-impact initiatives to decrease crowding. Furthermore, some emergency departments (EDs) have implemented a novel initiative we term “vertical patient flow,” i.e. segmenting patients who can be safely evaluated, managed, admitted or discharged without occupying a traditional ED room. We sought to determine the degree that ACEP-identified high-impact initiatives for ED crowding and vertical patient flow have been implemented in academic EDs in the United States (U.S.). Methods: We surveyed the physician leadership of all U.S. academic EDs from March to May 2010 using a 2-minute online survey. Academic ED was defined by the primary site of an emergency residency program. Results: We had a response rate of 73% (106/145) and a completion rate of 71% (103/145). The most prevalent hospital-based initiative was inpatient discharge coordination (46% [47/103] of respondents) while the least fully initiated was surgical schedule smoothing (11% [11/103]). The most prevalent ED-based initiative was fast track (79% [81/103]) while the least initiated was physician triage (12% [12/103]). Vertical patient flow had been implemented in 29% (30/103) of responding EDs while an additional 41% (42/103) reported partial/in progress implementation. Conclusion: We found great variability in the extent academic EDs have implemented ACEP’s established high-impact ED crowding initiatives, yet most (70%) have adopted to some extent the novel initiative vertical patient flow. Future studies should examine barriers to implementing these crowding initiatives and how they affect outcomes such as patient safety, ED throughput and patient/provider satisfaction.
The Elliptic Curve Digital Signature Algorithm ( ECDSA ) 1 2

The Elliptic Curve Digital Signature Algorithm (ECDSA) is the elliptic curve analogue of the Digital Signature Algorithm (DSA). It was accepted in 1999 as an ANSI standard, and was accepted in 2000 as IEEE and NIST standards. It was also accepted in 1998 as an ISO standard, and is under consideration for inclusion in some other ISO standards. Unlike the ordinary discrete logarithm problem and the integer factorization problem, no subexponential-time algorithm is known for the elliptic curve discrete logarithm problem. For this reason, the strength-per-key-bit is substantially greater in an algorithm that uses elliptic curves. This paper describes the ANSI X9.62 ECDSA, and discusses related security, implementation, and interoperability issues.
Worker Remittances and Capital Flows to Developing Countries

Worker remittances constitute an increasingly important mechanism for the transfer of resources from developed to developing countries, and remittances are the second-largest source, behind foreign direct investment, of external funding for developing countries. Yet, literature on worker remittances has so far focused mainly on the impact of remittances on income distribution within countries, on the determinants of remittances at a micro-level, or on the effects of migration and remittances for specific countries or regions. The focus of this paper is thus on four questions: First, how important are worker remittances to developing countries in quantitative terms? Second, what are the determinants driving worker remittances? Third, how volatile are worker remittances to developing countries? Fourth, are remittances correlated to other capital flows?
High-order and multilayer perceptron initialization

Proper initialization is one of the most important prerequisites for fast convergence of feedforward neural networks like high-order and multilayer perceptrons. This publication aims at determining the optimal variance (or range) for the initial weights and biases, which is the principal parameter of random initialization methods for both types of neural networks. An overview of random weight initialization methods for multilayer perceptrons is presented. These methods are extensively tested using eight real-world benchmark data sets and a broad range of initial weight variances by means of more than 30000 simulations, in the aim to find the best weight initialization method for multilayer perceptrons. For high-order networks, a large number of experiments (more than 200000 simulations) was performed, using three weight distributions, three activation functions, several network orders, and the same eight data sets. The results of these experiments are compared to weight initialization techniques for multilayer perceptrons, which leads to the proposal of a suitable initialization method for high-order perceptrons. The conclusions on the initialization methods for both types of networks are justified by sufficiently small confidence intervals of the mean convergence times.