Miracle-dz/UniFAR-FTUs huggingface dataset:
MapReduce based content searching of surveillance system videos

In the last couple of decades, radio-frequency identification (RFID) technology has been widely used in logistics, manufacturing, defense, environment, health care, agriculture, retail, aviation, and information technology. CBIR systems go through sets of stages starting from acquiring the new images, representing these images by extracting the image features, describing the key features and eventually computing the similarity distances to get the most relevant results responding to the query image. In this paper, an integrated CBIR Hadoop-MapReduce based framework which is split into both offline and online phases is introduced. Visual statements are built using the extracted interest points SIFTs. Later on, these visual statements are used to estimate the similarity distances which in turn are used to create the image dataset clusters. A huge vocabulary of SIFTs describing the interest points of the image is constructed. Corresponding statements which reflect the visual content for these features are created by applying the HAC technique.
Predicting CMOS speed with gate oxide and voltage scaling and interconnect loading effects

Sub-quarter micron MOSFET's and ring oscillators with 2.5-6 nm physical gate oxide thicknesses have been studied at supply voltages of 1.5-3.3 V. I/sub dsat/ can be accurately predicted from a universal mobility model and a current model considering velocity saturation and parasitic series resistance. Gate delay and the optimal gate oxide thickness were modeled and predicted. Optimal gate oxide thicknesses for different interconnect loading are highlighted.
Diagnostic Method of Causal Network Model Based on Swarm Intelligence Algorithm

In the procedure of turbine machinery fault diagnosis by probabilistic causal network model, the solution of the diagnostic problem can not be directly gotten by the traditional solving method and, furthermore, multi-level, multi-node complicated causal network may lead to the problem of "combinatorial explosion" and the exponential increase in computational cost etc. To solve these problems, based on the theory of swarm intelligence, the swarm intelligence algorithm model of probabilistic causal network in turbine machinery fault diagnosis is established, and the basic swarm calculation method and the improved method are given. The problems are well settled in the traditional solving method. Finally, the advantages and the engineering practicability are demonstrated by a practical example.
A quick tour of wavelets and PDE techniques in image processing

Wavelets are selected functions that generate orthonormal bases of the square integrable function space L by using dilation and translations. The base functions have certain locality, such as compact support or fast decay property. And they are usually organized according to different scales or resolutions, which are called MultiResolution Analysis (MRA). Fast wavelet transforms are filtering procedures that compute the inner products of any given function and wavelet. The inner products are wavelet coefficients.
Generating anatomical variation through mutations in networks – implications for evolution

Genetic mutation leads to anatomical variation only indirectly because many proteins involved in generating anatomical structures in embryos operate cooperatively within molecular networks. These include gene‐regulatory or control networks (CNs) for timing, signaling and patterning together with the process networks (PNs) for proliferation, apoptosis, differentiation and morphogenesis that they control. This paper argues that anatomical variation is achieved through a two‐stage process: mutation alters the outputs of CNs and perhaps the proliferation network, and such changed outputs alter the ways that PNs construct tissues. This systems‐biology approach has several implications: first, because networks contain many cooperating proteins, they amplify the effects of genetic variation so enabling mutation to generate a wider range of phenotypes than a single changed protein acting alone could. Second, this amplification helps explain how novel phenotypes can be produced relatively rapidly. Third, because even organisms with novel anatomical phenotypes derive from variants in standard networks, there is no genetic barrier to their producing viable offspring. This approach also clarifies a terminological difficulty: classical evolutionary genetics views genes in terms of phenotype heritability rather than as DNA sequences. This paper suggests that the molecular phenotype of the classical concept of a gene is often a protein network, with a mutation leading to an alteration in that network's dynamics.
MuTIny : A MULTI-TIME INTERVAL PATTERN DISCOVERY APPROACH TO PRESERVE THE TEMPORAL INFORMATION IN BETWEEN

Finding trends, patterns, and relationships among patterns are very relevant tasks when dealing with time-oriented data and information. However, most of the proposed methods have a sequence of events as outcome, lacking either any knowledge about the intervals between them or about after how much time a particular pattern will reoccur. We present MuTIny, a novel approach extending the I-Apriori algorithm, which is able to discover so called multi-time interval patterns and we describe how it can be customized according to users’ needs. Moreover, a real world example illustrates its usefulness.
Cognitive-Maps Based Investigation of Digital Security Incidents

Investigation of security incidents is of great importance as it allows to trace back the actions taken by the intruders. In this paper we develop a formal technique for digital investigation based on the use of Incident Response Probabilistic Cognitive Maps. Three main issues are addressed here: (1) construction and extraction of plausible known attack scenarios, (2) construction of hypothetical scenarios and their validation using a logic-based formalism, and (3) selection of optimal counter-measures addressing the detected attacks.
Why general practitioners do not implement evidence: qualitative study

Abstract Objectives: To explore the reasons why general practitioners do not always implement best evidence. Design: Qualitative study using Balint-style groups. Setting: Primary care. Participants: 19 general practitioners. Main outcome measures: Identifiable themes that indicate barriers to implementation. Results: Six main themes were identified that affected the implementation process: the personal and professional experiences of the general practitioners; the patient-doctor relationship; a perceived tension between primary and secondary care; general practitioners' feelings about their patients and the evidence; and logistical problems. Doctors are aware that their choice of words with patients can affect patients' decisions and whether evidence is implemented. Conclusions: General practitioner participants seem to act as a conduit within the consultation and regard clinical evidence as a square peg to fit in the round hole of the patient's life. The process of implementation is complex, fluid, and adaptive. What is already known on this topic General practitioners do not always act on evidence in clinical practice General practitioners are reluctant to jeopardise their relationship with the patient and sometimes feel that patients are unwilling to take drugs What this study adds Implementation of evidence by general practitioners is a complex and fluid process Decisions are influenced by the doctor's personal and professional experience as well as by their knowledge of and relationship with the patient Doctors' choice of words can influence patients' decisions about treatment
DEVISING A TRUST MODEL FOR MULTI-AGENT INTERACTIONS USING CONFIDENCE AND REPUTATION

In open environments in which autonomous agents can break contracts, computational models of trust have an important role to play in determining who to interact with and how interactions unfold. To this end, we develop such a trust model, based on confidence and reputation, and show how it can be concretely applied, using fuzzy sets, to guide agents in evaluating past interactions and in establishing new contracts with one another.
On improvement of transient stage of composite nonlinear feedback control using arbitrary order set point filters

This paper studies the generalization of composite nonlinear feedback (CNF) control using arbitrary order set point filters, which focus on the initial stage of the transient response. The set point filters can be used to provide more performance by shortening the rise and settling times of the control system. Furthermore, the filters operate outside the feedback loop, and hence, they do not sacrifice loop robustness. The new method is illustrated by a benchmark problem found in an open literature. The simulation results show that the proposed method improves the set point response more than 10% in terms of settling time.
Global Regulatory Impact of ClpP Protease of Staphylococcus aureus on Regulons Involved in Virulence, Oxidative Stress Response, Autolysis, and DNA Repair

ABSTRACT Staphylococcus aureus is an important pathogen, causing a wide range of infections including sepsis, wound infections, pneumonia, and catheter-related infections. In several pathogens ClpP proteases were identified by in vivo expression technologies to be important for virulence. Clp proteolytic complexes are responsible for adaptation to multiple stresses by degrading accumulated and misfolded proteins. In this report clpP, encoding the proteolytic subunit of the ATP-dependent Clp protease, was deleted, and gene expression of ΔclpP was determined by global transcriptional analysis using DNA-microarray technology. The transcriptional profile reveals a strong regulatory impact of ClpP on the expression of genes encoding proteins that are involved in the pathogenicity of S. aureus and adaptation of the pathogen to several stresses. Expression of the agr system and agr-dependent extracellular virulence factors was diminished. Moreover, the loss of clpP leads to a complete transcriptional derepression of genes of the CtsR- and HrcA-controlled heat shock regulon and a partial derepression of genes involved in oxidative stress response, metal homeostasis, and SOS DNA repair controlled by PerR, Fur, MntR, and LexA. The levels of transcription of genes encoding proteins involved in adaptation to anaerobic conditions potentially regulated by an Fnr-like regulator were decreased. Furthermore, the expression of genes whose products are involved in autolysis was deregulated, leading to enhanced autolysis in the mutant. Our results indicate a strong impact of ClpP proteolytic activity on virulence, stress response, and physiology in S. aureus.
Altered Resting-State fMRI Signals in Acute Stroke Patients with Ischemic Penumbra

Background Identifying the ischemic penumbra in acute stroke subjects is important for the clinical decision making process. The aim of this study was to use resting-state functional magnetic resonance singal (fMRI) to investigate the change in the amplitude of low-frequency fluctuations (ALFF) of these subjects in three different subsections of acute stroke regions: the infarct core tissue, the penumbra tissue, and the normal brain tissue. Another aim of this study was to test the feasilbility of consistently detecting the penumbra region of the brain through ALFF analysis. Methods Sixteen subjects with first-ever acute ischemic stroke were scanned within 27 hours of the onset of stroke using magnetic resonance imaging. The core of infarct regions and penumbra regions were determined by diffusion and perfusion-weighted imaging respectively. The ALFF were measured from resting-state blood oxygen level dependent (BOLD) fMRI scans. The averaged relative ALFF value of each regions were correlated with the time after the onset of stroke. Results Relative ALFF values were significantly different in the infarct core tissue, penumbra tissue and normal brain tissue. The locations of lesions in the ALFF maps did not match perfectly with diffusion and perfusion-weighted imagings; however, these maps provide a contrast that can be used to differentiate between penumbra brain tissue and normal brain tissue. Significant correlations between time after stroke onset and the relative ALFF values were present in the penumbra tissue but not in the infarct core and normal brain tissue. Conclusion Preliminary results from this study suggest that the ALFF reflects the underlying neurovascular activity and has a great potential to estimate the brain tissue viability after ischemia. Results also show that the ALFF may contribute to acute stroke imaging for thrombolytic or neuroprotective therapies.
Exogenous spermine pretreatment confers tolerance to combined high-temperature and drought stress in vitro in trifoliate orange seedlings via modulation of antioxidative capacity and expression of stress-related genes

Spermine (Spm) is thought to play an important role in drought or high-temperature (HT) tolerance. However, it is not clear whether Spm confers similar resistance in the presence of both drought and HT, which often occur simultaneously. In the present study, the trifoliate orange (Poncirus trifoliata (L.) Raf. ) seedlings were pretreated with 1 mmol L−1 Spm to evaluate their tolerance to combined drought and HT (45 ºC) stress. Spm-pretreated seedlings showed less leaf wilting, less water loss and less electrolyte leakage than control leaves not treated with Spm within 180 min of treatment. Histochemical staining with diaminobenzidine and nitro blue tetrazolium showed that Spm-pretreated seedlings accumulated less hydrogen peroxide and superoxide than those of control plants 60, 120 and 180 min after treatment when exposed to both drought and HT (45 ºC). However, superoxide dismutase, peroxidase and catalase were significantly more active in Spm-pretreated seedlings than in control seedlings. In addition, Spm-pretreated seedlings showed significantly higher expression of heat shock proteins, abscisic acid (ABA)-responsive element binding factor and 9-cis-epoxycarotenoid dioxygenase 3 than controls either before (0 min) or after (60, 120 and 180 min) combined drought and HT treatment. All of these data suggest that exogenous Spm pretreatment confers tolerance to simultaneously occurring drought and HT stresses. Spm may influence this by activating antioxidant enzymes, increasing the effectiveness of scavenging of reactive oxygen species. It may also increase the expression levels of stress-related genes that protect trifoliate orange seedlings from stress damage.
Civic Service: What Difference Does it Make?

Part 1. Ideological and Historical Context 1. The Ideal 2. Policy Evolution Part 2. Evidence and Methods 3. The Nature of the Evidence 4. Methodology: Defining Civic Service Part 3. Research Synthesis Findings 5. Civic Service Outcomes 6. Qualities of Successful Programs Part 4. Summing Up and Taking Stock 7. Drawing Conclusions about Civic Service 8. Policy Implications: The Evolution of Civic Services Objectives Appendices
Simplified applications for network computers

This paper describes the design of HotJava Views, a user environment and suite of applications for a Network Computer. A Network Computer differs from the common Personal Computer in that it has no permanent local storage, but instead obtains its software and data as needed over the network from a central server. We have abandoned some characteristic features of current GUI interfaces, such as the desktop metaphor, file systems, and the distinction be-tween applications and documents. Our design principles are focused on simplicity, efficiency of operation, clarity of the interaction model, and tight integration between applications.
A Data-Driven Dependency Parser for Romanian

We present the first data-driven dependency parser for Romanian, which has been developed using the MaltParser system and trained and evaluated on a dependency treebank for Romanian developed within the RORIC-LING project. The parser achieves a labeled attachment score of 88.6% (unlabeled 92.0%) when evaluated on held-out data from the treebank. We present a partial error analysis, focusing on accuracy for different parts of speech and dependencies of different length.
Stereovision with a Single Camera and Multiple Mirrors

You can create catadioptric omnidirectional stereovision using several mirrors with a single camera. These systems have interesting advantages, for instance in the case of mobile robot navigation and environment reconstruction. Our paper aims at estimating the” quality” of such stereovision system. What happens when the number of mirrors increases? Is it better to increase the base-line or to increase the number of mirrors? We propose some criteria and a methodology to compare different significant categories (seven): three already existing systems and four new designs that we propose. We also study and propose a global comparison between the best configurations.
Acoustic Model Adaptation Using First-Order Linear Prediction for Reverberant Speech

This paper describes a hands-free speech recognition technique based on acoustic model adaptation to reverberant speech. In hands-free speech recognition, the recognition accuracy is degraded by reverberation, since each segment of speech is affected by the reflection energy of the preceding segment. To compensate for the reflection signal we introduce a frame-by-frame adaptation method adding the reflection signal to the means of the acoustic model. The reflection signal is approximated by a first-order linear prediction from the observation signal at the preceding frame, and the linear prediction coefficient is estimated with a maximum likelihood method by using the EM algorithm, which maximizes the likelihood of the adaptation data. Its effectiveness is confirmed by word recognition experiments on reverberant speech.
Individual blade pitch for yaw control

Individual pitch control (IPC) for reducing blade loads has been investigated and proven successful in recent literature. For IPC, the multi-blade co-ordinate (MBC) transformation is used to process the blade load signals from the rotating to a stationary frame of reference. In the stationary frame of reference, the yaw error of a turbine can be appended to generate IPC actions that are able to achieve turbine yaw control for a turbine in free yaw. In this paper, IPC for yaw control is tested on a high-fidelity numerical model of a commercially produced wind turbine in free yaw. The tests show that yaw control using IPC has the distinct advantage that the yaw system loads and support structure loading are substantially reduced. However, IPC for yaw control also shows a reduction in IPC blade load reduction potential and causes a slight increase in pitch activity. Thus, the key contribution of this paper is the concept demonstration of IPC for yaw control. Further, using IPC for yaw as a tuning parameter, it is shown how the best trade-off between blade loading, pitch activity and support structure loading can be achieved for wind turbine design.
Step-Wise Increase in Tigecycline Resistance in Klebsiella pneumoniae Associated with Mutations in ramR, lon and rpsJ

Klebsiella pneumoniae is a gram-negative bacterium that causes numerous diseases, including pneumonia and urinary tract infections. An increase in multidrug resistance has complicated the treatment of these bacterial infections, and although tigecycline shows activity against a broad spectrum of bacteria, resistant strains have emerged. In this study, the whole genomes of two clinical and six laboratory-evolved strains were sequenced to identify putative mutations related to tigecycline resistance. Of seven tigecycline-resistant strains, seven (100%) had ramR mutations, five (71.4%) had lon mutations, one (14.2%) had a ramA mutation, and one (14.2%) had an rpsJ mutation. A higher fitness cost was observed in the laboratory-evolved strains but not in the clinical strains. A transcriptome analysis demonstrated high expression of the ramR operon and acrA in all tigecycline-resistant strains. Genes involved in nitrogen metabolism were induced in the laboratory-evolved strains compared with the wild-type and clinical strains, and this difference in nitrogen metabolism reflected the variation between the laboratory-evolved and the clinical strains. Complementation experiments showed that both the wild-type ramR and the lon genes could partially restore the tigecycline sensitivity of K. pneumoniae. We believe that this manuscript describes the first construct of a lon mutant in K. pneumoniae, which allowed confirmation of its association with tigecycline resistance. Our findings illustrate the importance of the ramR operon and the lon and rpsJ genes in K. pneumoniae resistance to tigecycline.
PENGARUH KONSERVATISME AKUNTANSI DAN GOOD CORPORATE GOVERNANCE PADA KUALITAS LABA

Earnings quality is one of information that affects the stakeholders in making decisions about the company. To analyze the quality of earnings disclosed by the company, it is important to know the factors that affect the quality of earnings. This study was conducted at the companies listed on the Indonesian Stock Exchange and the Corporate Governance Perception Index rating agency or CGPI in 2008-2012. Samples were obtained by 55 by purposive sampling method . The technique of data analysis used is multiple linear regression analysis. proxy for earnings quality measure used is ERC, accounting conservatism measured by the conservatism index , and GCG measured by CGPI index. The results showed that the positive effect of accounting conservatism on earnings quality. So that, companies that use accounting conservatism get a positive response from investors based on earnings presented. Another variable that good corporate governance does not affect the quality of earnings.
The Effect of Majorana Phase in Degenerate Neutrinos

There are physical Majorana phases in the lepton flavor mixing matrix when neutrinos are Majorana fermions. In the case of two degenerate neutrinos, the physical Majorana phase plays the crucial role for the stability of the maximal flavor mixing between the second and the third generations against quantum corrections. The physical Majorana phase of $\pi$ guarantees the maximal mixing to be stable against quantum corrections, while the Majorana phase of zero lets the maximal mixing be spoiled by quantum corrections when neutrino masses are of O(eV). The continuous change of the Majorana phase from $\pi$ to 0 makes the maximal mixing be spoiled by quantum corrections with O(eV) degenerate neutrino masses. On the other hand, when there is the large mass hierarchy between neutrinos, the maximal flavor mixing is not spoiled by quantum corrections independently of the Majorana phase.
Spammer detection based on Hidden Markov Model in micro-blogging

Over the past decade, social network becomes the main way for people to obtain information and communicate with their online friends. With the tremendous increase of social network, spammer also develops rapidly and spam information posted by spammer seriously affects people's daily life. Although the official executes some strict strategies for prevention, spammer evolves dynamically to adapt these strategies at the same time. They disguise as common users with posting interesting tweets and posting spam with irregular time. To deal with this problem, we present a method for spammer detection on the basis of Hidden Markov Model in micro-blogging. The proposed method classifies the user into spammer and non-spammer according to their major count-based features and behavior-based features. The usage of HMM allows us to describe the user behavior with hidden states dynamically, which can be decoded from several observed features. The experimental results based on real data collected from Sina micro-blogging site demonstrate the effectiveness of our method.