Miracle-dz/UniFAR-FTUs huggingface dataset:
Treatment of early-stage mycosis fungoides with twice-weekly applications of mechlorethamine and topical corticosteroids: a prospective study.

OBJECTIVE To determine if a therapeutic regimen of twice-weekly applications of mechlorethamine hydrochloride and betamethasone dipropionate cream is effective in the treatment of early-stage mycosis fungoides while increasing cutaneous tolerance. DESIGN Prospective nonrandomized study conducted from November 1999 to November 2002. SETTING Eleven university or hospital dermatology departments in France. PATIENTS Sixty-four consecutive patients with newly diagnosed early-stage mycosis fungoides (stage IA, n = 33; stage IB, n = 26; stage IIA, n = 5). INTERVENTIONS Patients were treated with twice-weekly applications of a 0.02% aqueous solution of mechlorethamine followed by an application of betamethasone cream during a 6-month period. MAIN OUTCOME MEASURES The primary end point was the rate of complete response during the treatment. Secondary end points were mean delay to achieve complete response, rate of severe cutaneous reactions of intolerance, and rate of relapse after achieving complete response. RESULTS Thirty-seven patients (58%) had a complete response after a mean +/- SD treatment duration of 3.6 +/- 2.5 months: 20 (61%) of 33 patients with stage IA disease, 15 (58%) of 26 patients with stage IB disease, and 2 (40%) of 5 patients with stage IIA disease. Eighteen patients (28%) developed severe cutaneous reactions of intolerance that necessitated treatment discontinuation. Relapse was observed in 17 patients (46%) after a mean +/- SD time of 7.7 +/- 6.5 months. CONCLUSIONS A regimen of twice-weekly applications of mechlorethamine and betamethasone cream is an effective treatment for early-stage mycosis fungoides. The decreased frequency of applications provides an advantage to the patient by being easy to use with limited adverse effects.
Synthesis of neural networks for spatio-temporal spike pattern recognition and processing

The advent of large scale neural computational platforms has highlighted the lack of algorithms for synthesis of neural structures to perform predefined cognitive tasks. The Neural Engineering Framework (NEF) offers one such synthesis, but it is most effective for a spike rate representation of neural information, and it requires a large number of neurons to implement simple functions. We describe a neural network synthesis method that generates synaptic connectivity for neurons which process time-encoded neural signals, and which makes very sparse use of neurons. The method allows the user to specify—arbitrarily—neuronal characteristics such as axonal and dendritic delays, and synaptic transfer functions, and then solves for the optimal input-output relationship using computed dendritic weights. The method may be used for batch or online learning and has an extremely fast optimization process. We demonstrate its use in generating a network to recognize speech which is sparsely encoded as spike times.
Incentive mechanism and protocol design for crowdsourcing systems

Crowdsourcing systems such as Amazon Mechanical Turk, Yahoo! Answers, and Google Helpouts have attracted extensive attention over the past few years. In a crowdsourcing system, a large group of “workers” solve the tasks outsourced by “requesters”. To make a crowdsourcing system sustainable, it is vital to attract users (both requesters and workers) to participate, and incentivize high-quality solutions. To achieve this objective, we design an effective incentive mechanism and reputation protocol. Our design incorporates various important elements of a crowdsourcing system such as workers having heterogeneous skill sets (i.e., some are “experts” while others are “novices”), and task assignment process, rating system, etc. Our incentive mechanism is composed of a rating system and a reward dividing scheme, and requires the system administrator to divide the reward based on requesters' rating on the solution quality. We derive the minimum reward needed so that “expert” workers are guaranteed provide high-quality solutions. We show that “novice” workers provide low-quality solutions, and our reputation protocol eliminates this undesirable behavior by tracking a worker's solution history and penalizing him when his reputation is poor. We apply repeated game-theoretic frameworks to quantify the impact of this reputation protocol on requesters' cost in guaranteeing high quality solutions.
PKUTM Experiments in NTCIR-8 MOAT Task

This paper describes our work in the Simplified Chinese opinion analysis tasks in NTCIR-8. In the task of detecting opinioned sentences, various sentiment lexicons are used, including opinion indicators, opinion operators, degree adverbs and opinion words. The linear SVM model is selected as the main classifier, and four groups of features are extracted according to punctuations, words and sentiment lexicons. We also try a two-step classification to improve the SVM result. For extracting the opinion holder and target, we use a synthesis of CRF and heuristic rules. The evaluation results on NTCIR-8 MOAT Simplified Chinese side show that our system achieves the best fmeasure in two tasks. This demonstrates that the proposed framework is promising.
Modeling and Discovering Vulnerabilities with Code Property Graphs

The vast majority of security breaches encountered today are a direct result of insecure code. Consequently, the protection of computer systems critically depends on the rigorous identification of vulnerabilities in software, a tedious and error-prone process requiring significant expertise. Unfortunately, a single flaw suffices to undermine the security of a system and thus the sheer amount of code to audit plays into the attacker's cards. In this paper, we present a method to effectively mine large amounts of source code for vulnerabilities. To this end, we introduce a novel representation of source code called a code property graph that merges concepts of classic program analysis, namely abstract syntax trees, control flow graphs and program dependence graphs, into a joint data structure. This comprehensive representation enables us to elegantly model templates for common vulnerabilities with graph traversals that, for instance, can identify buffer overflows, integer overflows, format string vulnerabilities, or memory disclosures. We implement our approach using a popular graph database and demonstrate its efficacy by identifying 18 previously unknown vulnerabilities in the source code of the Linux kernel.
Testing of Eight Medicinal Plant Extracts in Combination with Kresoxim-Methyl for Integrated Control of Botrytis cinerea in Apples

Botrytis cinerea is a fungus that causes gray mold on many fruit crops. Despite the availability of a large number of botryticides, the chemical control of gray mold has been hindered by the emergence of resistant strains. In this paper, tests were done to determine the botryticidal efficacy of selected plant extracts alone or combined with kresoxim-methyl. In total, eight South African medicinal plants viz Artemisia afra, Elyptropappus rhinocerotis, Galenia africana, Hypoxis hemerocallidea, Siphonochilus aetheopicus, Sutherlandia frutescens, Tulbaghia violacea and Tulbaghia alliacea were screened. Allium sativum, a plant species known to have antifungal activity, was included in the in vivo studies. For the in vitro studies, synergistic interactions between the plant extracts and the kresoxim-methyl fungicide were tested with radial growth assays. Data indicated synergistic inhibitory effects between the fungicide and the plant extracts. Next, different doses of plant extracts combined with kresoxim-methyl were used for decay inhibition studies on Granny Smith apples. Synergistic and additive effects were observed for many of the combinations. Even though this study was done using only one strain of B. cinerea, results showed that the tested indigenous South African plant species possess natural compounds that potentiate the activity of kresoxim-methyl.
Effect of Zirconia and Alumina Fillers on the Microstructure and Mechanical Strength of Dental Glass Ionomer Cements

Background: Glass-ionomer cements perform a protective effect on the dentin-pulp complex considering the F ions release and chemical bonding to the dental structures. On the other hand, those materials have poor physic-mechanical properties in comparison with the restorative resin composite. The main aim of this work was to evaluate the influence of zirconia and/or alumina fillers on the microstructure and strength of a resin modified glass-ionomer cement after thermal cycling. Methods: An in vitro experimental study was carried out on 9 groups (n = 10) of cylindrical samples (6 x 4 mm) made from resin modified glass-ionomer (Vitremer, 3M, USA) with different contents of alumina and/or zirconia fillers. A nano-hybrid resin composite was tested as a control group. Samples were mechanically characterized by axial compressive tests and electron scanning microscopy (SEM) coupled to energy dispersive X-ray spectrophotometry (EDS), before and after thermal cycling. Thermal cycling procedures were performed at 3000, 6000 and 10000 cycles in Fusayama´s artificial saliva at 5 and 60 oC. Results: An improvement of compressive strength was noticed on glass-ionomer reinforced with alumina fillers in comparison with the commercial glass ionomer. SEM images revealed the morphology and distribution of alumina or zirconia in the microstructure of glass-ionomers. Also, defects such as cracks and pores were detected on the glass-ionomer cements. The materials tested were not affected by thermal cycling in artificial saliva. Conclusion: Addition of inorganic particles at nano-scale such as alumina can increase the mechanical properties of glass-ionomer cements. However, the presence of cracks and pores present in glass-ionomer can negatively affect the mechanical properties of the material because they are areas of stress concentration.
The Association between Attachment Avoidance and Quality of Life in Bariatric Surgery Candidates

Objective: Patients presenting for bariatric surgery have high rates of psychiatric co-morbidity and reduced health-related quality of life (HRQOL) compared to the general population. In this study, we aimed to determine the relationship between insecure attachment styles and HRQOL in bariatric surgery candidates. Methods: We assessed depression, social support, attachment avoidance, attachment anxiety, HRQOL (SF-36), and eating disorder psychopathology in 70 consecutive patients assessed for bariatric surgery. SF-36 physical (PCS) and mental component scores (MCS) were compared to a normative sample and analyzed using t-tests. Predictors of HRQOL were analyzed using multiple linear regression analyses. Results: SF-36 PCS and MCS in this pre-bariatric surgery sample were significantly lower than in an age-matched reference population. Depression, attachment anxiety, attachment avoidance and eating disorder psychopathology scores were negatively correlated with SF-36 MCS. Depression was associated with lower SF-36 PCS (p = 0.015). SF-36 MCS were significantly predicted by BDI scores (p < 0.001) and attachment avoidance (p = 0.024) in our multiple regression model. Conclusion: This is the first study to demonstrate an association between attachment avoidance and poor mental HRQOL in bariatric surgery candidates. Future studies are needed to examine the effect of attachment avoidance on post-bariatric surgery outcomes.
Robustness of the Eigenfilter for Variations in Listener Responses for Selective Signal Cancellation

Selectively cancelling signals at specific locations within an acoustical environment with multiple listeners is of significant importance for home theater, automobile, teleconferencing, office, industrial and other applications. We have proposed the eigenfilter for selectively cancelling signals in one direction, while attempting to retain them at unintentional directions. In this paper we investigate the behaviour of the performance measure (i.e., the gain) for a vowel and an unvoiced fricative, when the listener moves his head, in an automobile type environment. We show that in such a situation, a large energy in the difference between the impulse responses at a listener's location may affect the gain substantially.
Mining user daily behavior patterns from access logs of massive software and websites

Everyone has a characteristic pattern of daily activities. This study applies cluster analysis to identify a computer user's daily behavior patterns based on 1000 China users' 4-weeks software and web usage. Clustering models are built for 4 different behavior definition methods with different time period divisions and feature measurement selections. With these patterns, we build classification models to predict new users' daily behavior pattern with their half day activity logs. For example, if we know one user use computer for entertainment in the morning, we can predict his behavior in the afternoon and evening. The prediction model can be used to recommend suitable items to users according to their current behavior status. Our method can get 92.5% prediction correctness for the best.
Spinal manipulation and mobilisation for back and neck pain: a blinded review.

OBJECTIVE--To assess the efficacy of spinal manipulation for patients with back or neck pain. DESIGN--Computer aided search for published papers and blinded assessment of the methods of the studies. SUBJECTS--35 randomised clinical trials comparing spinal manipulation with other treatments. MAIN OUTCOME MEASURES--Score for quality of methods (based on four main categories: study population, interventions, measurement of effect, and data presentation and analysis) and main conclusion of author(s) with regard to spinal manipulation. RESULTS--No trial scored 60 or more points (maximum score 100) suggesting that most were of poor quality. Eighteen studies (51%) showed favourable results for manipulation. In addition, five studies (14%) reported positive results in one or more subgroups. Of the four studies with 50-60 points, one reported that manipulation was better, two reported that manipulation was better in only a subgroup, and one reported that manipulation was no better or worse than reference treatment. Eight trials attempted to compare manipulation with some placebo, with inconsistent results. CONCLUSIONS--Although some results are promising, the efficacy of manipulation has not been convincingly shown. Further trials are needed, but much more attention should be paid to the methods of study.
Crosslinguistic Transfer in Automatic Verb Classification

We investigate the use of multilingual data in the automatic classification of English verbs, and show that there is a useful transfer of information across languages. Specifically, we experiment with three lexical semantic classes of English verbs. We collect statistical features over a sample of English verbs from each of the classes, as well as over Chinese translations of those verbs. We use the English and Chinese data, alone and in combination, as training data for a machine learning algorithm whose output is an automatic verb classifier. We demonstrate that Chinese data is indeed useful in helping to classify the English verbs (at 82% accuracy), and furthermore that a multilingual combination of data outperforms the English data alone (85% accuracy). Moreover, our results using monolingual corpora show that it is not necessary to use a parallel corpus to extract the translations in order for this technique to be successful.
Analyzing Gender Bias in Student Evaluations Acknowledgments

Sentiment analysis is a computational linguistics task that characterizes positivenegative tone expressed in language data. We apply sentiment analysis to analyze student comments spanning over eight years of College biology, chemistry, physics and math and explore differences in sentiment conveyed toward male and female faculty. We study differences in perceptions found in categories pertaining to instructor competence, organization/presentation, personality/helpfulness and overall satisfaction. We also use term ranking to identify words that are strongly associated with either gender.
Inhibition of Filiform Corrosion on Organic-Coated Magnesium-Containing Galvanized Steel by Smart-Release Ion Exchange Pigments

This paper describes a systematic kinetic study on the inhibitory effect of anion exchange Hydrotalcite-based pigments on filiform corroding hot dipped Zn-(1-2 w%)Mg-(1-2 w%)Al galvanized steel. Filiform corrosion was initiated via scribing the organic-coated samples and introducing a corrosive electrolyte in the defect. Following filiform corrosion initiation, the time-dependent extent of coating delamination was determined photographically over a period of six weeks. It is positively demonstrated that the addition of smart-release pigments in the organic coating greatly suppresses the rate of filiform corrosion. The inhibitor efficiency is shown to increase in the order: carbonate < benzotriazole < benzotriazolate. The release of carbonates leads to filiform corrosion increase.
Flow Accelerated Corrosion Experience at Comanche Peak Steam Electric Station

Flow accelerated corrosion (FAC) is a major concern in the power industry as it causes thinning of the pipes by the dissolution of the passive oxide layer formed on the pipe surface. Present research deals with comparing the protection offered by the magnetite (Fe3O4) versus maghemite (γ-Fe2O3) phases thickness loss measurements. Fourier transform infrared spectroscopy (FTIR) is used in distinguishing these two elusive phases of iron oxides. Representative pipes are collected from high pressure steam extraction line of the secondary cycle of unit 2 of Comanche Peak Steam Electric Station (CPSES). Environmental scanning electron microscopy (ESEM) is used for morphological analysis. FTIR and X-ray diffraction (XRD) are used for phase analysis. Morphological analysis showed the presence of porous oxide surfaces with octahedral crystals, scallops and "chimney" like vents. FTIR revealed the predominance of maghemite at the most of the pipe sections. Results of thickness measurements indicate severe thickness loss at the bend areas (extrados) of the pipes.
Investigating dynamical information transfer in the brain following a TMS pulse: Insights from structural architecture

Transcranial magnetic stimulation (TMS) has been used for more than 20 years to investigate connectivity and plasticity in the human cortex. By combining TMS with high-density electroencephalography (hd-EEG), one can stimulate any cortical area and measure the effects produced by this perturbation in the rest of the cerebral cortex. The purpose of this paper is to investigate changes of information flow in the brain after TMS from a functional and structural perspective, using multimodal modeling of source reconstructed TMS/hd-EEG recordings and DTI tractography. We prove how brain dynamics induced by TMS is constrained and driven by its structure, at different spatial and temporal scales, especially when considering cross-frequency interactions. These results shed light on the function-structure organization of the brain network at the global level, and on the huge variety of information contained in it.
Molecular Dynamics Modeling of Carbon Nanotube Composite Fracture using ReaxFF

Carbon nanotubes (CNTs) are well known to have exceptionally high mechanical properties when measured individually. Recently, CNT fiber composites have been enabled by the production of high-tex yarns in quantities on the order of kilometers. These high-tex CNT yarns have recently become comparable in specific stiffness and specific strength to carbon fiber. Despite these advancements, CNT yarns still have mechanical properties substantially lower than their CNT constituents. Closing this gap requires understanding load transfer between CNTs and the role of matrix binders such as amorphous carbon at the nanoscale. This work uses reactive molecular dynamics simulations to gain a nanoscale understanding of the key factors of CNT nanocomposite mechanical performance and to place more realistic upper bounds on the target properties. While molecular dynamics simulations using conventional force fields can predict elastic properties, the ReaxFF reactive force field can also model fracture behavior because of its ability to accurately describe bond breaking and formation during a simulation. The upper and lower bounds of CNT composite properties are investigated by comparing systems composed of CNTs continuously connected across the periodic boundary with systems composed of finite length CNTs. These lengths, effectively infinite for the continuous tubes and an aspect ratio of 13 for the finite length case, result from simulation limitations. Experimentally measured aspect ratios are typically on the order of 100,000, so the calculated results should represent upper and lower limits on experimental mechanical properties. Finally, the effect of various degrees of crosslinking to the amorphous carbon matrix is considered in an attempt to identify the amount of CNT-matrix covalent bonding that maximizes overall composite properties.
NumaGiC: a Garbage Collector for Big Data on Big NUMA Machines

On contemporary cache-coherent Non-Uniform Memory Access (ccNUMA) architectures, applications with a large memory footprint suffer from the cost of the garbage collector (GC), because, as the GC scans the reference graph, it makes many remote memory accesses, saturating the interconnect between memory nodes. We address this problem with NumaGiC, a GC with a mostly-distributed design. In order to maximise memory access locality during collection, a GC thread avoids accessing a different memory node, instead notifying a remote GC thread with a message; nonetheless, NumaGiC avoids the drawbacks of a pure distributed design, which tends to decrease parallelism. We compare NumaGiC with Parallel Scavenge and NAPS on two different ccNUMA architectures running on the Hotspot Java Virtual Machine of OpenJDK 7. On Spark and Neo4j, two industry-strength analytics applications, with heap sizes ranging from 160GB to 350GB, and on SPECjbb2013 and SPECjbb2005, ourgc improves overall performance by up to 45% over NAPS (up to 94% over Parallel Scavenge), and increases the performance of the collector itself by up to 3.6x over NAPS (up to 5.4x over Parallel Scavenge).
X-ray reflectivity and mechanical stress in W/Si multilayers deposited on thin substrates of glass, epoxy-replicated aluminum foil, and Si wafer

Reflectivity at (lambda) equals 0.154 nm and mechanical stress in the bulk thin films of tungsten and silicon and single d- spacing multilayers on their basis with d approximately equals 2.8 nm deposited by the magnetron sputtering technique on flat thin substrates of Si wafer (approximately 0.2 mm), glass (approximately 0.3 mm), and epoxy gold replicated aluminum foil (approximately 0.3 mm) have been studied. The interfacial roughness of the multilayers has been calculated from the x- ray reflectivity curves as the following: on Si wafer (sigma) approximately equals 0.31 nm, on glass (sigma) approximately equals 0.32 nm, and on foil (sigma) approximately equals 0.34 nm. There was not observed a significant dependence on the stress in the Si film with change in rf power, Ar gas pressure and biasing. For the W films an increase of dc power results in an increase of stress. A similar relationship is also evident for W films deposited by rf power, but this dependence is less pronounced. The influence of low temperature (up to 200 degrees Celsius) annealing on x-ray reflectivity and stress in the multilayers has been investigated. There was not found an appreciable changes in the absolute value of reflectivity or in d-spacing with annealing temperature. The stress in the coatings changes with annealing temperature from compressive to tensile. There was observed a temperature of annealing at which the stress is no longer present in the film. The absolute value of this temperature measured for W/Si multilayer is approximately 120 degrees Celsius.