Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimized Collaborative Filtering Algorithm Based on Item Rating Prediction

Collaborative filtering recommendation algorithm is currently the most widely used personalized recommendation algorithm. Sparsity problem of user rating data led to the recommendation quality of traditional collaborative filtering algorithms are far from ideal. To solve the problem, the paper first cloud model and project characteristic attributes to calculate the similarity between the project has taken into consideration in computing project similarity scores were similar between the project and consider the project between the characteristic attribute similarity, and then to predict ungraded items rated. Finally, the cloud model to calculate the similarity between users to obtain the target user's nearest neighbor. Experimental results show that the algorithm improves the accuracy of the similarity of the calculated project, and effectively solve the problem of data sparsity, and improve the quality of the recommendation system recommended.
A Reconfigurable NoC Topology for the Dark Silicon Era

Future chips are expected to feature hundreds of on-die resources, but a considerable portion of silicon area in these chips will be dark that cannot be powered and provided with required bandwidth. As a result, only a limited number of cores of future processors can be powered on simultaneously. The most promising solution to this challenge is to trade off the cheaper silicon area with energy-efficiency by integrating a selection of many diverse application-specific cores into a single multi-core processor and only activate those cores that best match the processing requirements of each running application. Activated cores act as an application-specific CMP for target applications. In this paper, we propose a reconfigurable network-on-chip that leverages the routers of the dark portion of the chip to customize the NoC topology for the active cores at any time. In this design, routers of the dark parts of the chip can be downgraded to simple FPGA-like switches to directly connect distant active nodes in the network. Our experimental results reveal considerable reduction in energy consumption and latency of on-chip communication when compared to state-of-the art NoCs.
Sparse algorithms and bounds for statistically and computationally efficient robust estimation

Robust estimators that provide accurate parameter estimates even under the condition that classical assumptions like outlier-free additive Gaussian measurement noise do not hold exactly are of great practical importance in signal processing and measurement science in general. Lots of methods for deriving robust estimators exist. In this paper, we derive novel algorithms for robust estimation by modeling the outliers as a sparse additive vector of unknown deterministic or random parameters. By exploiting the separability of the estimation problem and applying recently developed sparse estimation techniques, algorithms that remove the effect of the outlying observations can be developed. Monte Carlo simulations show that the performance of the developed algorithms is practically equal to the best possible performance given by the Crámer-Rao lower bound (CRB) and the mean-squared error (MSE) of the oracle estimator [1], demonstrating the high accuracy. It is shown that the algorithms can be implemented in a computationally efficient manner. Furthermore, some interesting connections to the popular least absolute deviation (LAD) estimator are shown.
Thanks, But No Thanks

The stereotype that women are dependent on men is a commonly verbalized, potentially damaging aspect of benevolent sexism. We investigated how women may use behavioral disconfirmation of the personal applicability of the stereotype to negotiate such sexism. In an experiment (N = 86), we manipulated female college students’ awareness that women may be stereotyped by men as dependent. We then placed participants in a situation where they needed help. Women made aware of the dependency stereotype (compared to controls who were not) were less willing to seek help. They also displayed a stronger negative correlation between help-seeking and post help-seeking affect—such that the more help they sought, the worse they felt. We discuss the relevance of these findings for research concerning women’s help-seeking and their management of sexist stereotyping in everyday interaction. We also consider the implications of our results for those working in domains such as health care, teaching, and counseling, where interaction with individuals in need and requiring help is common.
Long‐term survival of beta thalassemia major patients treated with hematopoietic stem cell transplantation compared with survival with conventional treatment

Allogeneic hematopoietic stem cell transplantation (HSCT) in thalassemia remains a challenge. We reported a single‐centre case‐control study of a large cohort of 516 children and adult patients treated with HSCT or blood transfusion support and iron chelation therapy; 258 patients (median age 12, range 1‐45) underwent sibling (67%) or unrelated (33%) HSCT; 97 patients were adults (age ≥ 16 years). The median follow‐up after HSCT was 11 years (range 1‐30). The conditioning regimen was busulfan (80.6%) or treosulfan‐based (19.4%). A cohort of 258 age‐sex matched conventionally treated (CT) patients was randomly selected. In transplanted patients the 30‐year overall survival (OS) and thalassemia‐free survival (TFS) were 82.6 ± 2.7% and 77.8 ± 2.9%, compared to the OS of 85.3 ± 2.7% in CT patients (P = NS); The incidence of grade II‐IV acute and chronic graft versus host disease (GvHD) was 23.6% and 12.9% respectively. The probability of rejection was 6.9%. Transplant‐related mortality (TRM) (13.8%) was similar to the probability of dying of cardiovascular events in CT patients (12.2%). High‐risk Pesaro score (class 3) was associated with lower OS (OR = 1.99, 95% C.I.=1.31‐3.03) and TFS (OR = 1.54, 95% C.I.=1.12‐2.12). In adult patients, the 23‐years OS and TFS after HSCT were 70 ± 5% and 67.3 ± 5%, compared to 71.2 ± 5% of OS in CT (P = NS). Finally, treosulfan was associated with lower risk of acute GvHD (P = .004; OR = 0.28, 95% C.I.=0.12‐0.67). In conclusion, the 30‐year survival rate of ex‐thalassemia patients after HSCT was similar to that expected in CT thalassemia patients, with the vast majority of HSCT survivors cured from thalassemia.
S100A9 is not essential for disease expression in an acute (K/BxN) or chronic (CIA) model of inflammatory arthritis

Objective: S100A8 (calgranulin A, MRP8) and S100A9 (calgranulin B, MRP14) are calcium-binding proteins highly expressed by activated myeloid cells and thought to be involved in the pathogenesis of inflammatory diseases. Circulating levels of S100A8/S100A9 are elevated in both human and experimental models of autoimmune disease, including rheumatoid arthritis (RA). Methods: Mice deficient in S100A9 (S100A9 − /−) and wild-type controls were immunized using standard techniques for the K/BxN serum transfer or the collagen-induced arthritis (CIA) model. Results: S100A9 − /− animals, with defective expression of both S100A8 and S100A9 proteins, had similar arthritis and histopathology to that of wild-type controls in both mouse models. Conclusion: S100A8 and S100A9 are not essential for disease expression in either the K/BxN serum transfer or the CIA model of inflammatory arthritis.
Learning Control of a Robotic System Using Neural Networks

Abstract In this paper, deterministic learning control using neural networks (NNs) is presented for a robotic system with unknown system dynamics. The dynamics of the robotic system are represented by an n-link strict robotic manipulator. The adaptive NNs is employed as the first control strategy to approximate the unknown model of the system and adapt interactions between the robot and a patient. Deterministic learning control using learned knowledge from direct NNs with Radial Basis Functions (RBFs) is employed as the second control strategy to improve the system intelligence for energy conservation and reduce control tasks. Uniform ultimate boundedness (UUB) of the closed loop system is achieved under the condition of the Lyapunov's stability with full state feedback control. Extensive simulations are carried out to expound the efficacy of the proposed control strategies and the advancement of learning control.
Flaw detection in rotating structures by Lamb waves

Rotor damage detection is crucial in order to ensure safe operation of aircraft. We present a technique that detects defects in rotating propellers. A pulsed Nd:YAG laser is scanned across an aluminum sample that rotates at 415 rpm to generate ultrasound while a LDV picks up data. We detected the presence of a surface breaking rectangular notch, determined its position, and calculated its size.
Integrating Linguistic Information in Machine Translation Evaluation

The automatic evaluation of machine translation (MT) has been a very important factor driving the success of statistical machine translation for most of this decade. Prior to automatic metrics, researchers were forced to rely more heavily on human evaluations, which are costly and time-consuming. Automatic metrics allow systems to analyze and reduce errors while they train. Fully automatic machine translation evaluation poses an interesting problem, however. In order to be able to judge whether a translation from a source to target language is a good one, we must rst solve the problem of machine translation. For that reason, human reference translations are created for the purpose of evaluation and the target output is compared against these reference translations. Some metrics also look at the source sentences for length ratios or other statistics. The success of automatic MT evaluation relies heavily upon accurate reference translations. There are at least two assumptions in dealing with reference translations: that the human translation will be adequate in the transmission of information from the target language to the source language and that the human translation will be uent in the target language. It is possible for there to be a many-to-many mapping from sentences with the same meaning in the source language to sentences with the same meaning in the target language. Also, it is still a matter of debate in the linguistic community whether exact meaning-to-meaning mapping is even possible between human languages (cf. the Sapir-Whorf hypothesis (Kay and Kempton, 1984)). Another complication is deciding how best to evaluate the quality of the MT evaluation metrics themselves.
ITRW on Multilingual Speech and Language Processing Stellenbosch , South Africa April 9-11 , 2006

With the demand on providing automatic speech recognition (ASR) systems for many markets the question of porting an ASR system to a new language is of practical interest. Transferring already existing hidden Markov models (HMM) from a source to the target language is seen as a key step to cope with this task. Typically, such a crosslingual model adaptation task consists of a three step procedure. It starts by polyphone decision tree specialisation (PDTS), specialising the phonetic-acoustic decision tree of the source models to the target language. In a second step initial target language models are predicted out of the adjusted decision tree. Finally, the predicted acoustic models are adapted to the target language using a limited amount of target data. In this work we focus on the final model adaptation step in the case of a system architecture employing semi-continuous HMMs (SCHMM). In contrast to continuous density HMMs (CDHMM), adaptation techniques for SCHMMs are not as well developed. In particular, no powerful transformation based adaptation method for adjusting the information bearing mixture weights of the common prototype densities is on-hand. To overcome this problem we introduce a novel adaptation scheme for SCHMM. The method relies on the projection of retrained model parameters to a solution sub-simplex which is obtained through acoustic regression classes derived from the decision tree of the source models. The performance of the procedure is demonstrated by the transfer of multilingual Spanish-English-German models to Slovenian and to French. In the full paper, reference results for a standard maximum likelihood linear regression (MLLR) approach are given too.
Energy Efficient Non-Cooperative Methods for Resource Allocation in Cognitive Radio Networks

In a cognitive radio network wherein primary and secondary users coexist, an efficient power allocation method represents one of the most important key aspects. This paper provides a novel approach based on a game theory framework to solve this problem in a distributed and fair way. Formulated as an optimization problem, the resource allocation problem between secondary users and primary users can be modeled and investigated with the Game Theory, and in particular S-Modular Games, since they provide useful tools for the definition of multi objective distributed algorithms in the context of radio communications. This paper provides also a performance comparison among the proposed game and two other algorithms, frequently used in this context: Simulated Annealing and Water Filling.
On Structuring Multiple Grouping Hypotheses in Generic Object Detection

A novel contour grouping method was recently proposed for the difficult task of detecting and delineating unexpected multi-part objects of unknown specific shape and appearance in a variety of natural images. This method, in many ways original and unique, was generally able to obtain object-level groups of quite good quality for a variety of objects and images. For each tested image, a number of object-level groups are hypothesized and ranked using a generic multicriteria objective function. Experiments shown that object-level groups most similar to the human ground truth usually rank high. However, no object-level group was obtained with some difficult images. This paper proposes three important improvements to that original method. Firstly, fixed parameters are replaced by adaptive parameters, improving the robustness of the method even for the most difficult images. Secondly, a parallel version of the method is developed to either speedup or scale-up the computation, making the method adaptive to practical space and time constraints. Finally, a further structuring of the object-level groups makes it possible to isolate the interesting ones and determine their number. A comparison with previous results illustrates the significance of the improvements.
Attributes of social and human capital disclosure and information asymmetry between managers and investors

We extend the literature on voluntary disclosure by investigating the impact of precision attribute of social and human capital disclosure on information asymmetry. We provide evidence on how the stock market reacts to different levels of information precision. Overall, results suggest that quantitative disclosure reduces share price volatility and increases Tobin's Q. As expected, firm size attenuates the impact of precision attribute of disclosure on information asymmetry. Furthermore, it appears that firms take into account ultimate costs and benefits to shareholders when determining precision attribute of their disclosure. Finally, our results suggest that efficient governance leads to more disclosure. Copyright © 2009 ASAC. Published by John Wiley & Sons, Ltd.
Prognostic implications of arrhythmias during primary percutaneous coronary interventions for ST-elevation myocardial infraction

The authors reviewed current knowledge on occurrence, clinical and prognostic significance, and management of sustained ventricular arrhythmias, atrial fibrillation and bradyarrhythmias in patients with ST-elevation myocardial infarction undergoing primary percutaneous coronary interventions (PCI). Cardiac arrhythmias worsen clinical course and prognosis in patients with ST-elevation myocardial infarction undergoing primary PCI. Sustained ventricular arrhythmias developing during or early after PCI and associated with mechanical restoration of coronary flow and reperfusion do not affect mortality, whereas those related to incomplete revascularization and ongoing ischemia are associated with poor prognosis. New-onset atrial fibrillation increases mortality and stroke rates in patients undergoing primary PCI. Among bradyarrhythmias, high-degree atrioventricular block is associated with short- and long-term mortality. Prompt and complete revascularization is the cornerstone of arrhythmia management. Arrhythmias related to reperfusion do not usually require specific treatment, whereas those because of ongoing ischemia, incomplete revascularization and presence of substrate require adequate management including nonpharmacological and pharmacological therapies.
Emerging drugs for acute lung injury

Introduction: Acute respiratory distress syndromes (ARDS) are devastating disorders of overwhelming pulmonary inflammation and hypoxemia, resulting in high morbidity and mortality. Areas covered: The main pharmacological treatment strategies have focused on the attempted inhibition of excessive inflammation or the manipulation of the resulting physiological derangement causing respiratory failure. Additionally, such interventions may allow reduced occurence mechanical ventilation injury. Despite promising preclinical and small clinical studies, almost all therapies have been shown to be unsuccessful in large-scale randomized controlled trials. The evidence for pharmacological treatment for ARDS is reviewed. Potential future treatments are also presented. Expert opinion: We suggest for future clinical trials addressing prevention and early intervention to attenuate lung injury and progression to respiratory failure.
Improved Cantonese Tone Recognition with Approximated F0 Contour: Implications for Cochlear Implants

This paper describes a periodicity-enhancement strategy which can be used to improve lexical tone perception for cochlear implant (CI) users. We focus on Cantonese, a major Chinese dialect with complex tone system. Acoustical simulations were tested with normal-hearing subjects. Temporal envelope and periodicity components (TEPC) below 500 Hz were extracted from four frequency bands. Stimuli were the combination of TEPC-modulated noises from sub-bands. For enhancement, the original temporal periodicity cues between 20 and 500 Hz were simplified by a sinusoidal wave whose frequency was equal to the exact fundamental frequency (F0) of the original speech or a linearly approximated F0. Tone identification tests were conducted using Cantonese disyllabic words. Results showed that tone scores with periodicity-enhanced TEPCs were significantly higher than the original ones. The approximated F0 contour provides similar tone perception performance to the exact F0 contour, indicating that exact F0 is unnecessary for the periodicity-enhancement strategy in CIs.
The transition from elementary to high school: The pivotal role of mother and child characteristics in explaining trajectories of academic functioning

The present 8-year longitudinal study had two goals. The first goal was to describe different trajectories of academic functioning during the transition to high school using a group-based trajectory method. The second goal was to determine if previous family and child characteristics (notably behavioural problems and prosociality) predict these trajectories. A total of 1003 mothers and teachers participated in the study. Results of the trajectory analysis revealed the presence of three groups. A first group experienced stable and high levels of academic functioning (63%), a second group experienced a significant drop in academic functioning (14%), and a third group experienced stable and low levels of academic functioning (23%). Logistic regression analyses showed that these groups differed in terms of early parental characteristics, child behavioural problems, and prosociality. These results are discussed in light of empirical findings on the transition to high school.
Mathematical/computational challenges in creating deformable and probabilistic atlases of the human brain

Striking variations in brain structure, especially in the gyral patterns of the human cortex, present fundamental challenges in human brain mapping. Probabilistic brain atlases, which encode information on structural and functional variability in large human populations, are powerful research tools with broad applications. Knowledge‐based imaging algorithms can also leverage atlased information on anatomic variation. Applications include automated image labeling, pathology detection in individuals or groups, and investigating how regional anatomy is altered in disease, and with age, gender, handedness and other clinical or genetic factors. In this report, we illustrate some of the mathematical challenges involved in constructing population‐based brain atlases. A disease‐specific atlas is constructed to represent the human brain in Alzheimer's disease (AD). Specialized strategies are developed for population‐based averaging of anatomy. Sets of high‐dimensional elastic mappings, based on the principles of continuum mechanics, reconfigure the anatomy of a large number of subjects in an anatomic image database. These mappings generate a local encoding of anatomic variability and are used to create a crisp anatomical image template with highly resolved structures in their mean spatial location. Specialized approaches are also developed to average cortical topography. Since cortical patterns are altered in a variety of diseases, gyral pattern matching is used to encode the magnitude and principal directions of local cortical variation. In the resulting cortical templates, subtle features emerge. Regional asymmetries appear that are not apparent in individual anatomies. Population‐based maps of cortical variation reveal a mosaic of variability patterns that segregate sharply according to functional specialization and cytoarchitectonic boundaries. Hum. Brain Mapping 9:81–92, 2000. © 2000 Wiley‐Liss, Inc.
Brain Activity During Performance of Naming Tasks: Comparison Between Dyslexic and Regular Readers

This research was aimed at contributing to the current understanding of the underlying factors of naming speed and the causes of naming speed deficits. Forty regular readers and 40 dyslexic university students participated in the study. Electrophysiological (Event-Related Potentials [ERPs]) and behavioral measures were employed. Behavioral baseline tasks assessed general ability, reading skills, reading-related cognitive abilities, and standard Rapid Automatized Naming (RAN) and Rapid Alternating Stimulus tests. ERP tasks included letter and object naming tasks adapted for electrophysiological research presentation. The dyslexics were significantly slower and less accurate than the controls on most of the baseline measures. On all the naming tasks, the peak ERP latencies were elicited later, reaction times were longer, and the P300 latency width was wider among the dyslexics as compared to the regular readers. On the choice reaction time naming tasks, accuracy for both groups was almost perfect. When naming presentation time was controlled by the experiment, the dyslexics were significantly less accurate than the controls. Our data indicated that effective naming speed was related to an earlier P200 latency peak among regular readers and to an earlier P300 latency peak and narrower area component activation in the dyslexic group. The results from this study suggest that effective RAN speed among regular readers might be a result of efficient processing of RAN information at the input stage of stimulis perception and evaluation as well as of updating and processing the information in short-term memory among dyslexics.