Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Data Mining: Exploring Large Rule Spaces by Sampling.

A great challenge for data mining techniques is the huge space of potential rules which can be generated. If there are tens of thousands of items, then potential rules involving three items number in the trillions. Traditional data mining techniques rely on downward-closed measures such as support to prune the space of rules. However, in many applications, such pruning techniques either do not sufficiently reduce the space of rules, or they are overly restrictive. We propose a new solution to this problem, called Dynamic Data Mining (DDM). DDM foregoes the completeness offered by traditional techniques based on downward-closed measures in favor of the ability to drill deep into the space of rules and provide the user with a better view of the structure present in a data set. Instead of a single deterministic run, DDM runs continuously, exploring more and more of the rule space. Instead of using a downward-closed measure such as support to guide its exploration, DDM uses a user-defined measure called weight, which is not restricted to be downward closed. The exploration is guided by a heuristic called the Heavy Edge Property. The system incorporates user feedback by allowing weight to be redefined dynamically. We test the system on a particularlly difficult data set - the word usage in a large subset of the World Wide Web. We find that Dynamic Data Mining is an effective tool for mining such difficult data sets.
Adaptive Speech Enhancement Based on Classification of Voiced/Unvoiced Signal

At low SNR's, the conventional wavelet enhancement algorithm may lose some useful ingredients of the speech, resulting in a low enhancement performance. To solve the problem, this paper presents an improved wavelet enhancement algorithm based on the classification of the voiced/unvoiced signal. First, we eliminate part of the noise through spectral subtraction algorithm and separate voiced signal from unvoiced signal according to its short-time energy. Second, the Wavelet Packet Transform (WPT) is made on unvoiced speech to prevent signal distortion. Then dynamic thresholds are applied to different wavelet analytical scales to avoid a much smoother signal waveform. Finally, a new adaptive threshold function is used to make up the disadvantages of soft and hard thresholding algorithm. Experiments show that the proposed method can remove much noise while keeping intelligibility of the reconstructed speech.
BBS opinion leader mining based on an improved PageRank algorithm using MapReduce

Opinion leaders in bulletin board systems (BBS) play an important role during the formation of public opinion. Opinion leader mining has a positive effect on us to grasp and guide public opinion. The paper designs and implements an opinion leader mining system based on an improved PageRank algorithm using MapReduce. The improved PageRank algorithm uses the method of sentiment analysis to define the weight of the link between users. The system has three main steps. Firstly, adopt web crawler to crawl BBS data and preprocess the data collected. Then construct an online social network with the replying relations between posts and comments mapped to relations between posters and comment authors. Finally, use the improved PageRank algorithm to rank users in BBS in the Hadoop cloud computing environment. Contrast experiments with the origin Pagerank algorithm show that the system is accurate, efficient and practical.
Multiband OFDM UWB Channel Estimation Via a Wavelet Based EM-MAP Algorithm

This paper introduces an expectation-maximization (EM) algorithm within a wavelet domain Bayesian framework for semi-blind channel estimation of multiband OFDM based UWB communications. A prior distribution is chosen for the wavelet coefficients of the unknown channel impulse response, in order to capture the well known sparseness property of the wavelet representation. This prior yields, in maximum a posteriori estimation, a thresholding rule within the EM algorithm. We particularly focus on reducing the number of estimated parameters by iteratively discarding "unsignificant" wavelet coefficients from the estimation process. In addition, the proposed algorithm enhances the estimation accuracy in terms of mean square error with less computational complexity than traditional semi-blind methods. Simulation results using IEEE UWB channel models show that the proposed algorithm outperforms pilot based channel estimation in terms of mean square error and bit error rate
Heteromultimeric Kv1 Channels Contribute to Myogenic Control of Arterial Diameter

Inhibition of vascular smooth muscle (VSM) delayed rectifier K+ channels (KDR) by 4-aminopyridine (4-AP; 200 &mgr;mol/L) or correolide (1 &mgr;mol/L), a selective inhibitor of Kv1 channels, enhanced myogenic contraction of rat mesenteric arteries (RMAs) in response to increases in intraluminal pressure. The molecular identity of KDR of RMA myocytes was characterized using RT-PCR, real-time PCR, and immunocytochemistry. Transcripts encoding the pore-forming Kv&agr; subunits, Kv1.2, Kv1.4, Kv1.5, and Kv1.6, were identified and confirmed at the protein level with subunit-specific antibodies. Kv&bgr; transcript (&bgr;1.1, &bgr;1.2, &bgr;1.3, and &bgr;2.1) expression was also identified. Kv1.5 message was ≈2-fold more abundant than that for Kv1.2 and Kv1.6. Transcripts encoding these three Kv1&agr; subunits were ≈2-fold more abundant in 1st/2nd order conduit compared with 4th order resistance RMAs, and Kv&bgr;1 was 8-fold higher than Kv&bgr;2 message. RMA KDR activated positive to −50 mV, exhibited incomplete inactivation, and were inhibited by 4-AP and correolide. However, neither &agr;-dendrotoxin or &kgr;-dendrotoxin affected RMA KDR, implicating the presence of Kv1.5 in all channels and the absence of Kv1.1, respectively. Currents mediated by channels because of coexpression of Kv1.2, Kv1.5, Kv1.6, and Kv&bgr;1.2 in human embryonic kidney 293 cells had biophysical and pharmacological properties similar to those of RMA KDR. It is concluded that KDR channels composed of heteromultimers of Kv1 subunits play a critical role in myogenic control of arterial diameter.
Building an Annotated Corpus in the Molecular-Biology Domain

Corpus annotation is now a key topic for all areas of natural language processing (NLP) and information extraction (IE) which employ supervised learning. With the explosion of results in molecular-biology there is an increased need for IE to extract knowledge to support database building and to search intelligently for information in online journal collections. To support this we are building a corpus of annotated abstracts taken from National Library of Medicine's MEDLINE database. In this paper we report on this new corpus, its ontological basis, and our experience in designing the annotation scheme. Experimental results are shown for inter-annotator agreement and comments are made on methodological considerations.
RECONFIGURING OR REPRODUCING THE INTRA- PROFESSIONAL BOUNDARIES OF EXPERTISE? GENERALIST AND SPECIALIST KNOWLEDGE IN THE MODERNIZATION OF GENETICS PROVISION IN ENGLAND 1

Efforts to ‘modernize’ public services in England have involved attempts to reconfigure the distribution of knowledge and responsibility between professions and subprofessions. Here, the authors take the example of the ‘mainstreaming’ of clinical genetics in the National Health Service to examine the course of an attempt to increase the genetics knowledge of general practitioners (family physicians). The example illustrates the limits to attempts to promote knowledge sharing, as the threat perceived by clinical geneticists saw them use their institutionalized power base to ensure that the redistribution was a conservative one, which reproduced, rather than reconfiguring, boundaries of knowledge and jurisdiction.
Regulation of Substrate Oxidation Preferences in Muscle by the Peptide Hormone Adropin

Rigorous control of substrate oxidation by humoral factors is essential for maintaining metabolic homeostasis. During feeding and fasting cycles, carbohydrates and fatty acids are the two primary substrates in oxidative metabolism. Here, we report a novel role for the peptide hormone adropin in regulating substrate oxidation preferences. Plasma levels of adropin increase with feeding and decrease upon fasting. A comparison of whole-body substrate preference and skeletal muscle substrate oxidation in adropin knockout and transgenic mice suggests adropin promotes carbohydrate oxidation over fat oxidation. In muscle, adropin activates pyruvate dehydrogenase (PDH), which is rate limiting for glucose oxidation and suppresses carnitine palmitoyltransferase-1B (CPT-1B), a key enzyme in fatty acid oxidation. Adropin downregulates PDH kinase-4 (PDK4) that inhibits PDH, thereby increasing PDH activity. The molecular mechanisms of adropin’s effects involve acetylation (suggesting inhibition) of the transcriptional coactivator PGC-1α, downregulating expression of Cpt1b and Pdk4. Increased PGC-1α acetylation by adropin may be mediated by inhibiting Sirtuin-1 (SIRT1), a PGC-1α deacetylase. Altered SIRT1 and PGC-1α activity appear to mediate aspects of adropin’s metabolic actions in muscle. Similar outcomes were observed in fasted mice treated with synthetic adropin. Together, these results suggest a role for adropin in regulating muscle substrate preference under various nutritional states.
AlexU-Word: A New Dataset for Isolated-Word Closed-Vocabulary Offline Arabic Handwriting Recognition

In this paper, we introduce the first phase of a new dataset for offline Arabic handwriting recognition. The aim is to collect a very large dataset of isolated Arabic words that covers all letters of the alphabet in all possible shapes using a small number of simple words. The end goal is to collect a very large dataset of segmented letter images, which can be used to build and evaluate Arabic handwriting recognition systems that are based on segmented letter recognition. The current version of the dataset contains $25114$ samples of $109$ unique Arabic words that cover all possible shapes of all alphabet letters. The samples were collected from $907$ writers. In its current form, the dataset can be used for the problem of closed-vocabulary word recognition. We evaluated a number of window-based descriptors and classifiers on this task and obtained an accuracy of $92.16\%$ using a SIFT-based descriptor and ANN.
Carotid artery longitudinal wall motion is associated with local blood velocity and left ventricular rotational, but not longitudinal, mechanics

Recent studies have identified a predictable movement pattern of the common carotid artery wall in the longitudinal direction. While there is evidence that the magnitude of this carotid artery longitudinal wall motion (CALM) is sensitive to cardiovascular health status, little is known about the determinants of CALM. The purpose of this integrative study was to evaluate the contribution of left ventricular (LV) cardiac motion and local blood velocity to CALM. Simultaneous ultrasound measurements of CALM, common carotid artery mean blood velocity (MBV), and left ventricular motion were performed in ten young, healthy individuals (6 males; 22 ± 1 years). Peak anterograde CALM occurred at a similar time as peak MBV (18.57 ± 3.98% vs. 18.53 ± 2.81% cardiac cycle; t‐test: P = 0.94; ICC: 0.79, P < 0.01). The timing of maximum retrograde CALM displacement was different, but related, to both peak apical (41.00 ± 7.81% vs. 35.33 ± 5.79% cardiac cycle; t‐test: P < 0.01; ICC: 0.79, P < 0.01) and basal rotation (41.80 ± 6.12% vs. 37.30 ± 5.66% cardiac cycle; t‐test: P < 0.01; ICC: 0.74, P < 0.01) with peak cardiac displacements preceding peak CALM displacements in both cases. The association between basal rotation and retrograde CALM was further supported by strong correlations between their peak magnitudes (r = −0.70, P = 0.02), whereas the magnitude of septal longitudinal displacement was not associated with peak CALM (r = 0.11, P = 0.77). These results suggest that the rotational mechanical movement of the LV base may be closely associated with longitudinal mechanics in the carotid artery. This finding may have important implications for interpreting the complex relationship between ventricular and vascular function.
The Use of The BDI Model As Design Principle for A Migratable Agent

A migratable agent, which has the function of providing an interface between the user and the devices with which it needs to interact, can provide the user with continuous assistance. The relationship established between a human and the agent would enable the user to operate home appliances smoothly. However, few studies which have addressed the primary questions that arise in this regard; for example, how and when the agent should execute the task requested by the user. This paper proposes the use of a design principle based on the BDI model for a migratable agent to ensure that it is capable of carrying out user's tasks appropriately. The BDI model enables the agent to determine the scope of continuing actions to achieve its intended target. The BDI model allows the agent to execute tasks in the clear range of achieving intentions and guarantees the completion of tasks within a reasonable range. We investigated the validity of adopting the BDI model by obtaining feedback via questionnaires related to the design of the migratable agent. The results of the questionnaires indicated that the BDI model would be able to facilitate the design of the migratable agent.
Finding Relations from a Large Corpus using Generalized Patterns

We can find many valuable relations from a text document. Extracting these relations from a document plays an important role in Information Extraction. However, it is not easy to achieve relation extraction task from a large corpus. This is due to the many kinds of relation and it’s appearing patterns. To solve these difficulties, we suggest a method which automatically finds the relations using generalized patterns. In this method, generalized patterns are created using the information at the initial time. The patterns are used to find new terms in the specific relation. The evaluation of our method has been done over a collection of more than 100,000 sentences. The result shows improved performance. Keyword: Information extraction, Generalized pattern, Large corpus.
Performance Analysis of Different Length Packets Processing by Network Processor Based Application

In this work, we present a new methodology to calculate the available compute budget which determines how much processing the network processor can perform on each packet with different length. To evaluate the method, we also did a wide range of tests with different length packets. Then we analysis the MicroEngine states with the test results, which is useful in building the applications on network processors and evaluating its performance. We also give several solutions to solving the applications' performance bounds such as latency bound and compute bound, which are caused by variable length packets
A Single System Explains Human Speed Perception

Motion is fully described by a direction and a speed. The processing of direction information by the visual system has been extensively studied; much less is known, however, about the processing of speed. Although it is generally accepted that the direction of motion is processed by a single motion system, no such consensus exists for speed. Psychophysical data from humans suggest two separate systems processing luminance-based fast and slow speeds, whereas neurophysiological recordings in monkeys generally show continuous speed representation, hinting at a single system. Although the neurophysiological findings hint at a single system, they remain inconclusive as only a limited amount of cells can be measured per study and, possibly, the putative different motion systems are anatomically separate. In three psychophysical motion adaptation experiments, we show that predictions on the basis of the two-motion system hypothesis are not met. Instead, concurrent modeling showed that both here-presented and previous data are consistent with a single system subserving human speed perception. These findings have important implications for computational models of motion processing and the low-level organization of the process.
On Estimating Variances for Topic Set Size Design

Topic set size design is a suite of statistical techniques for determining the appropriate number of topics when constructing a new test collection. One vital input required for these techniques is an estimate of the population variance of a given evaluation measure, which in turn requires a topic-by-run score matrix. Hence, to build a new test collection, a pilot data set is a prerequisite. Recently, we ran an IR task at NTCIR-12 where the number of topics was actually determined using topic set size design with an initial pilot data set based on only ﬁve similar runs; a test collection was then constructed accordingly by pooling 44 runs from 16 participating teams for 100 topics. In this study, we treat the new test collection with the associated runs as a more reliable pilot data set to investigate how many teams and topics are actually necessary in the pilot data for obtaining accurate variance estimates.
Hyaluronan Deficiency Due to Has3 Knock-Out Causes Altered Neuronal Activity and Seizures via Reduction in Brain Extracellular Space

Hyaluronan (HA), a large anionic polysaccharide (glycosaminoglycan), is a major constituent of the extracellular matrix of the adult brain. To address its function, we examined the neurophysiology of knock-out mice deficient in hyaluronan synthase (Has) genes. Here we report that these Has mutant mice are prone to epileptic seizures, and that in Has3−/− mice, this phenotype is likely derived from a reduction in the size of the brain extracellular space (ECS). Among the three Has knock-out models, namely Has3−/−, Has1−/−, and Has2CKO, the seizures were most prevalent in Has3−/− mice, which also showed the greatest HA reduction in the hippocampus. Electrophysiology in Has3−/− brain slices demonstrated spontaneous epileptiform activity in CA1 pyramidal neurons, while histological analysis revealed an increase in cell packing in the CA1 stratum pyramidale. Imaging of the diffusion of a fluorescent marker revealed that the transit of molecules through the ECS of this layer was reduced. Quantitative analysis of ECS by the real-time iontophoretic method demonstrated that ECS volume was selectively reduced in the stratum pyramidale by ∼40% in Has3−/− mice. Finally, osmotic manipulation experiments in brain slices from Has3−/− and wild-type mice provided evidence for a causal link between ECS volume and epileptiform activity. Our results provide the first direct evidence for the physiological role of HA in the regulation of ECS volume, and suggest that HA-based preservation of ECS volume may offer a novel avenue for development of antiepileptogenic treatments.
Fast and Automatic Vessel Centerline Detection for MRA

The extraction of vessel centerlines allows for better understanding of their topology, and can be used for further registration or quantification. We present a new method to extract the centerlines from Magnetic Resonance Angiographies. We use the gradient and the eigenvalues of the Hessian matrix to interpolate the zero-crossing of the gradient vector in the cross-sectional directions. Then, we connect the points belonging to the same cubes. A second connection step allows for the improvement the global connectivity. Our method is fast, extracts sub-voxel centerlines, and does not rely on a preliminary segmentation stage.
The Last Line of Defense: Motivating Employees to Follow Corporate Security Guidelines

Information security has become increasingly important to organizations. Despite the prevalence of technical security measures , individual employees remain the last line – and frequently the weakest link – in corporate defenses. When individuals choose to disregard security policies and procedures , the organization is at risk. How, then, can organizations motivate their employees to follow security guidelin es? Using an organizational control lens, we build a model to explain individual information security precaution -taking behavior . Specific hypotheses are developed and tested using a field survey. We examine elements of control and introduce the concept of “mandatoriness” which we define as the degree to which individuals perceive that compliance with existing security policies and procedures is compulsory or expected by organizational management. We find that the acts of specifying polic ies and evaluat ing behaviors are effective in convincing individuals that security policies are mandatory. The perception of mandatoriness is effective in motivating individuals to take security precautions.
Use of Printing like a Pro! in a School-Based Printing Club to Improve Handwriting Legibility in Primary Grade Students

ABSTRACT Printing Like a Pro! is a free program to help primary-grade students to print legibly. This pre-test post-test study aimed to evaluate the preliminary effectiveness of this program used in a teacher-taught printing club with occupational therapy support. Eleven students in grades 2 and 3 with persistently poor legibility attended the printing club twice-weekly (24 sessions). Handwriting performance, as measured by the Minnesota Handwriting Assessment, improved both meaningfully (≥10% change score) and statistically, with improvements in legibility, form and letter size (p < .008). Students with the lowest initial scores showed the greatest improvements in handwriting quality and legibility.
Measuring the evolution of open source software systems with their communities

Open Source Software (OSS) has become the subject of much commercial and academic interest in last few years. As traditional software, OSS also evolves to fulfill the need of stakeholders. Therefore, providing quantitative metrics for OSS evolution has also become an urgent issue. However, most existing studies of software evolution have been performed on systems developed within a single company using traditional management techniques. These metrics models are inadequate to measure OSS evolution. In this paper, we describe a preliminary evolution metrics set for evaluating OSS. The most significant novelty of this model is that it takes specific properties of Open Source Community (OSC) into consideration. In another word, we measure the evolution of OSS and OSC together. We also provide a lightweight case study on Ubuntu project using this metrics set. We find out that the Open Source Community and its members also play essential role in OSS evolution. We expect this metrics model can bring better understandings and explanations of phenomena in open source development and evolution.