Miracle-dz/UniFAR-FTUs huggingface dataset:
Trustworthy Whole-System Provenance for the Linux Kernel

In a provenance-aware system, mechanisms gather and report metadata that describes the history of each object being processed on the system, allowing users to understand how data objects came to exist in their present state. However, while past work has demonstrated the usefulness of provenance, less attention has been given to securing provenance-aware systems. Provenance itself is a ripe attack vector, and its authenticity and integrity must be guaranteed before it can be put to use. We present Linux Provenance Modules (LPM), the first general framework for the development of provenance-aware systems. We demonstrate that LPM creates a trusted provenance-aware execution environment, collecting complete whole-system provenance while imposing as little as 2.7% performance overhead on normal system operation. LPM introduces new mechanisms for secure provenance layering and authenticated communication between provenance-aware hosts, and also interoperates with existing mechanisms to provide strong security assurances. To demonstrate the potential uses of LPM, we design a Provenance-Based Data Loss Prevention (PB-DLP) system. We implement PBDLP as a file transfer application that blocks the transmission of files derived from sensitive ancestors while imposing just tens of milliseconds overhead. LPM is the first step towards widespread deployment of trustworthy provenance-aware applications.
How Listeria exploits host cell actin to form its own cytoskeleton. I. Formation of a tail and how that tail might be involved in movement

After Listeria is phagocytosed by a macrophage, it dissolves the phagosomal membrane and enters the cytoplasm. The Listeria then nucleates actin filaments from its surface. These actin filaments rearrange to form a tail with which the Listeria moves to the macrophage surface as a prelude to spreading. Since individual actin filaments appear to remain in their same positions in the tail in vitro after extraction with detergent, the component filaments must be cross- bridged together. From careful examination of the distribution of actin filaments attached to the surface of Listeria and in the tail, and the fact that during and immediately after division filaments are not nucleated from the new wall formed during septation, we show how a cloud of actin filaments becomes rearranged into a tail simply by the mechanics of growth. From lineage studies we can relate the length of the tail to the age of the surface of Listeria and make predictions as to the ratio of Listeria with varying tail lengths at a particular time after the initial infection. Since we know that division occurs about every 50 min, after 4 h we would predict that if we started with one Listeria in a macrophage, 16 bacteria would be found, two with long tails, two with medium tails, four with tiny tails, and eight with no tails or a ratio of 1:1:2:4. We measured the lengths of the tails on Listeria 4 h after infection in serial sections and confirmed this prediction. By decorating the actin filaments that make up the tail of Listeria with subfragment 1 of myosin we find (a) that the filaments are indeed short (maximally 0.3 microns in length); (b) that the filament length is approximately the same at the tip and the base of the tail; and (c) that the polarity of these filaments is inappropriate for myosin to be responsible or to facilitate movement through the cytoplasm, but the polarity insures that the bacterium will be located at the tip of a pseudopod, a location that is essential for spreading to an adjacent cell. Putting all this information together we can begin to unravel the problem of how the Listeria forms the cytoskeleton and what is the biological purpose of this tail. Two functions are apparent: movement and pseudopod formation.
Determination of Oleuropein in leaves and fruits of some Syrian olive varieties.

Oleuropein contents (OLE) in leaves and fruits of from seven olive Syrian varieties harvested at spring and fall were determined by high-performance liquid chromatography. The results showed that, the concentr ation of OLE leaves samples measured in spring was higher than tho se determined in fall samples, where the OLE concentration in spring samples ranged between 5.6 - 9.2 mg/g. The highest concentration (9.2 mg/g dry leaves), was found in Jlott variety and the lowest concentration (5.6 mg/g dry leaves) was in Dan mawi. In fall olive leaves samples, the concentration of OLE ranged between 4.3 to 8.2 mg/g dry leaves, where the highest concentration was in Jlott variety and the lowest was in Dan mawi variety. As for fruit samples, the OLE concentration ranged between 635 -1026 mg/kg, where the highest value was in Jlott variety, and the lowest was in Kaissy variety. Co mparisons between olive oil content in fruits and oleuropein content in leaves (in spring and autumn) (using student T test statistical analysis) indicate that the differences in oleuropein contents are affected by the genetic makeup of the olive varieties and not by the environment .
Factors involved in the etiology of temporomandibular disorders - a literature review

Background and aim This review aims at presenting a current view on the most frequent factors involved in the mechanisms causing temporomandibular disorders (TMD). Method We conducted a critical review of the literature for the period January 2000 to December 2014 to identify factors related to TMD development and persistence. Results The etiology of TMD is multidimensional: biomechanical, neuromuscular, bio-psychosocial and biological factors may contribute to the disorder. Occlusal overloading and parafunctions (bruxism) are frequently involved as biomechanical factors; increased levels of estrogen hormones are considered biological factors affecting the temporo-mandibular-joint. Among bio-psychosocial factors, stress, anxiety or depression, were frequently encountered. Conclusions The etiopathogenesis of this condition is poorly understood, therefore TMDs are difficult to diagnose and manage. Early and correct identification of the possible etiologic factors will enable the appropriate treatment scheme application in order to reduce or eliminate TMDs debilitating signs and symptoms.
Comparison of Discretization Accuracy in an Adaptive Multigrid Barotropic Tropical Cyclone Track Model

Abstract : Among the many sources of error in modeling tropical cyclones is discretization error: how well are the governing equations approximated numerically? While discretization error is typically small, numerical methods with smaller errors should be preferred over others, all else being equal. This paper addresses the tradeoff between higher-accuracy discretization and increased computational work in an adaptive multigrid tropical cyclone track model.
Self-sizing and optimization of high-speed multiservice networks

We consider the network design and optimization of high-speed multiservice networks. Meeting different service requirements is facilitated by dividing the network into virtual bands. A band corresponds to a service type. To achieve high transport efficiency, bands should be reconfigured frequently to track the varying traffic. Our work aims at developing a self-sizing system which can allocate network capacity automatically and adaptively using on-line traffic data. We study the optimization problem for band partitioning for high-speed multiservice networks. A two-step optimization approach is presented. An optimization model is developed to partition bandwidth among bands to minimize total system cost under capacity constraints while the QoS at call level and cell level are guaranteed. An online traffic measurement system allows the network to automatically detect the amount of bandwidth necessary to satisfy the QoS requirements at cell level. To this end our system exploits the notion of effective bandwidth. To meet the requirement of frequent band partitioning, a fast algorithm based on simulated annealing is presented to solve the model. Simulation results are reported to demonstrate the effectiveness of the optimization approach.
Effects of cigarette smoking on blood pressure stratified by BMI in Mongolian population, China

Abstract Background. The relationship between smoking and hypertension is still unclear and controversial; we examine effects of smoking on blood pressure stratified by body mass index (BMI) in the Mongolian population. Methods. A total of 2589 Mongolians aged 20 years or more were recruited as study subjects. Demographic data, lifestyle factors, family history of hypertension, blood pressure measurements, physical examination and blood sample were obtained and analyzed for all subjects. Results. Among subjects with BMI<25 kg/m2, adjusted mean diastolic blood pressure in all smokers (82, 83 and 82 mmHg for subjects who smoke 1–9, 10–19 and >20 cigarettes/day, respectively) were lower than that in non-smokers (84 mmHg), all p-values <0.05; among subjects with BMI>25 kg/m2, mean systolic blood pressure (137 mmHg for non-smokers, 141, 135 and 132 mmHg for subjects who smoke 1–9, 10–19 and >20 cigarettes/day, respectively) decreased with amount of smoking and linear trend was statistically significant, p<0.05. Multivariate adjusted odds ratios of hypertension for three smoking groups were all not statistically significant. Conclusions. This study did not provide support that smoking was a risk factor of hypertension and elevated blood pressure.
Mouse mammary tumor gene int-3: a member of the notch gene family transforms mammary epithelial cells

Expression of a 2.3-kb RNA species is induced in mammary tumors as a consequence of insertional mutagenesis at the int-3 locus by the mouse mammary tumor virus. The nucleotide sequence and biological activity of this mammary tumor-specific int-3 RNA species were determined. It contains an open reading frame which encodes a 57-kDa protein. The translated protein possesses six nearly contiguous 32-amino-acid repeats which are related to a similar motif in the Saccharomyces cerevisiae cdc-10-encoded cell cycle protein. In addition, the int-3 cdc-10 repeats are bounded by the PEST amino acid sequence motif which is commonly found in proteins having a rapid turnover and may represent sites for phosphorylation. The int-3 cdc-10 repeat sequences are 50% identical to a portion of the intracellular domain of the neurogenic Drosophila notch gene product. Activation of expression of a recombinant int-3 genomic DNA fragment encoding the 2.3-kb RNA species in HC11 mouse mammary epithelial cells in vitro induces anchorage-independent growth in soft agar.
Locally Training the Log-Linear Model for SMT

In statistical machine translation, minimum error rate training (MERT) is a standard method for tuning a single weight with regard to a given development data. However, due to the diversity and uneven distribution of source sentences, there are two problems suffered by this method. First, its performance is highly dependent on the choice of a development set, which may lead to an unstable performance for testing. Second, translations become inconsistent at the sentence level since tuning is performed globally on a document level. In this paper, we propose a novel local training method to address these two problems. Unlike a global training method, such as MERT, in which a single weight is learned and used for all the input sentences, we perform training and testing in one step by learning a sentence-wise weight for each input sentence. We propose efficient incremental training methods to put the local training into practice. In NIST Chinese-to-English translation tasks, our local training method significantly outperforms MERT with the maximal improvements up to 2.0 BLEU points, meanwhile its efficiency is comparable to that of the global method.
Point Light Source Estimation based on Scenes Recorded by a RGB-D camera

Bastiaan J. Boom1 http://homepages.inf. ed.ac. uk/bboom/ Sergio Orts-Escolano2 http://www.dtic. ua.es/~sorts/ Xin X. Ning1 avener1446@hotmail.com Steven McDonagh1 http://homepages.inf. ed.ac. uk/s0458953/ Peter Sandilands1 http://homepages.inf. ed.ac. uk/s0569500/ Robert B. Fisher1 http://homepages.inf. ed.ac. uk/rbf/ 1 Institute of Perception, Action and Behaviour University of Edinburgh Edinburgh, UK 2 Computer Technology Department University of Alicante Alicante, Spain
Clinical characteristics and management of congenital esophageal stenosis: a report on 14 cases.

PURPOSE The aim of this study was to review 14 patients with congenital esophageal stenosis (CES) from diagnostic and therapeutic points of view. METHODS From 1976 to 1999, 14 patients with CES were treated at the authors' hospital. In each diagnostic examination, an esophagogram, 24-hour pH monitoring, a manometric study, and an endoscopy were performed. The medical, radiologic, and operative reports of these patients were reviewed. RESULTS Esophagogram results showed an abrupt stenosis in 5 patients and a tapered stenosis in 9. After 24-hour pH monitoring and an endoscopy, we were able to rule out the possibility of gastroesophageal reflux with esophagitis in most of the patients. Of the 11 patients who initially underwent bougienage or balloon dilatation, 8 of them had recurrent stenosis. Eleven patients required surgical treatment, including the 8 who had recurrent stenosis after undergoing dilatation. Nine of the patients underwent a resection of the stenotic segment and esophago-esophagostomy. An antireflux procedure was performed on 2 patients. Another patient had an esophageal rupture, which required a jejunal interposition. A histopathologic study showed that tracheobronchial remnants were present in 6 patients, and fibromuscular thickening was found in 4 patients. CONCLUSIONS The efficacy of dilatation seems to be limited and may even result in severe complications such as an esophageal rupture. In this study, most patients ultimately required surgical treatment. Surgical repair for CES is the authors' preferred treatment, although initial dilatation may be effective for some patients.
Advances in Very Deep Convolutional Neural Networks for LVCSR

Very deep CNNs with small 3x3 kernels have recently been shown to achieve very strong performance as acoustic models in hybrid NN-HMM speech recognition systems. In this paper we investigate how to efficiently scale these models to larger datasets. Specifically, we address the design choice of pooling and padding along the time dimension which renders convolutional evaluation of sequences highly inefficient. We propose a new CNN design without timepadding and without timepooling, which is slightly suboptimal for accuracy, but has two significant advantages: it enables sequence training and deployment by allowing efficient convolutional evaluation of full utterances, and, it allows for batch normalization to be straightforwardly adopted to CNNs on sequence data. Through batch normalization, we recover the lost peformance from removing the time-pooling, while keeping the benefit of efficient convolutional evaluation. We demonstrate the performance of our models both on larger scale data than before, and after sequence training. Our very deep CNN model sequence trained on the 2000h switchboard dataset obtains 9.4 word error rate on the Hub5 test-set, matching with a single model the performance of the 2015 IBM system combination, which was the previous best published result.
Motor Imagery EEG Classification for Patients with Amyotrophic Lateral Sclerosis Using Fractal Dimension and Fisher’s Criterion-Based Channel Selection

Motor imagery is based on the volitional modulation of sensorimotor rhythms (SMRs); however, the sensorimotor processes in patients with amyotrophic lateral sclerosis (ALS) are impaired, leading to degenerated motor imagery ability. Thus, motor imagery classification in ALS patients has been considered challenging in the brain–computer interface (BCI) community. In this study, we address this critical issue by introducing the Grassberger–Procaccia and Higuchi’s methods to estimate the fractal dimensions (GPFD and HFD, respectively) of the electroencephalography (EEG) signals from ALS patients. Moreover, a Fisher’s criterion-based channel selection strategy is proposed to automatically determine the best patient-dependent channel configuration from 30 EEG recording sites. An EEG data collection paradigm is designed to collect the EEG signal of resting state and the imagination of three movements, including right hand grasping (RH), left hand grasping (LH), and left foot stepping (LF). Five late-stage ALS patients without receiving any SMR training participated in this study. Experimental results show that the proposed GPFD feature is not only superior to the previously-used SMR features (mu and beta band powers of EEG from sensorimotor cortex) but also better than HFD. The accuracies achieved by the SMR features are not satisfactory (all lower than 80%) in all binary classification tasks, including RH imagery vs. resting, LH imagery vs. resting, and LF imagery vs. resting. For the discrimination between RH imagery and resting, the average accuracies of GPFD in 30-channel (without channel selection) and top-five-channel configurations are 95.25% and 93.50%, respectively. When using only one channel (the best channel among the 30), a high accuracy of 91.00% can still be achieved by the GPFD feature and a linear discriminant analysis (LDA) classifier. The results also demonstrate that the proposed Fisher’s criterion-based channel selection is capable of removing a large amount of redundant and noisy EEG channels. The proposed GPFD feature extraction combined with the channel selection strategy can be used as the basis for further developing high-accuracy and high-usability motor imagery BCI systems from which the patients with ALS can really benefit.
The Sixth PASCAL Recognizing Textual Entailment Challenge

This paper presents the Sixth Recognizing Textual Entailment (RTE-6) challenge. This year a major innovation was introduced, as the traditional Main Task was replaced by a new task, similar to the RTE-5 Search Pilot, in which Textual Entailment is performed on a real corpus in the Update Summarization scenario. A subtask was also proposed, aimed at detecting novel information. To continue the effort of testing RTE in NLP applications, a KBP Validation Pilot Task was set up, in which RTE systems had to validate the output of systems participating in the KBP Slot Filling Task. Eighteen teams participated in the Main Task (48 submitted runs) and 9 in the Novelty Detection Subtask (22 submitted runs). As for the Pilot, 10 runs were submitted by 3 participants. Finally, the exploratory effort started in RTE-5 to perform resource evaluation through ablation tests was not only reiterated in RTE-6, but also extended to tools.
Clinicoeconomics and Outcomes Research Dovepress Application of a Validated Algorithm to Estimate the Effectiveness and Cost of Biologics for Rheumatoid Arthritis in the Us Pharmacy Benefit Manager Context

Background: Several biologic medicines are available to treat rheumatoid arthritis (RA), and they differ in administration method (subcutaneous or intravenous [IV]). We analyzed a pharmacy benefit manager database to estimate claims-based, algorithm-determined effectiveness and cost per effectively treated patient for biologics used to treat RA. Methods: We analyzed the Medco Health Solutions pharmacy benefit manager database to identify patients with one or more claims for a biologic used to treat RA from 2007 to 2012. The first observed claim defined the index date, the previous 180 days were the pre-index period, and follow-up was 365 days after the index date. Effectiveness of a biologic was determined by a validated, published algorithm designed for use in claims database analyses. Cost per effectively treated patient as determined by the algorithm was calculated as the total annual cost of the biologic therapy divided by the number of effectively treated patients. Analyses were conducted for subcutaneous, IV, and individual biologics. Conclusion: Effectiveness according to a validated, claims-based algorithm was higher in subcutaneous versus IV biologics. Cost per effectively treated patient according to the algorithm was approximately $16,000 less in subcutaneous versus IV biologics.
A Multivariate Approach to Iceberg and Ship Classification in HH/HV ASAR Data

Spaceborne synthetic aperture radar (SAR), with its wide area coverage and all-weather operation, is an ideal sensor to provide iceberg surveillance in support of safe shipping and offshore operations. Reliable ship/iceberg discrimination in SAR imagery is at least as important as detection since misclassification can result in expending significant resources for investigation or avoidance. To address this need, the authors have undertaken research to facilitate effective target discrimination using SAR multi-polarization data. The results presented here are for iceberg and ship classification for ENVISAT advanced synthetic aperture radar (ASAR) HH/HV data. Target classification was achieved by maximizing the a posteriori probabilities obtained from Bayes's rule. The maximum likelihood Gaussian classifier was used to model the probability of an unknown target belonging to either the iceberg or ship class. The feature selection algorithms, sequential forward selection (SFS), genetic algorithm (GA), and exhaustive search (ES) were evaluated for optimization of a feature space dependant multivariate classifier. The results from this study show for dual polarized HH/HV ASAR, icebergs and ships can be classified with a 93.5% accuracy using a two-class maximum likelihood model. As well, for the small sample set of 201 iceberg and ship targets presented here, suboptimal feature selection algorithms such as the SFS, GA, and exhaustive ranked search (ERS) are considered. These feature selection methods were considerably less computationally expensive to run than the global exhaustive search and were found to have converging results for both accuracy and features selected.