Miracle-dz/UniFAR-FTUs huggingface dataset:
Diagnosis of timed automata : Theory and application to the DAMADICS actuator benchmark problem

This paper concerns the problem of fault diagnosis in discrete-event systems which are represented by timed automata. The diagnostic algorithm for timed automata detects and identifies faults in the system based on the investigation whether the measured input and output sequences are consistent with the timed automaton. This diagnostic approach can be applied spontaneously to the discrete-event system since no a priori information about the initial state of the system is required. It is shown in the paper how the timed automaton which represents the DAMADICS actuator can be obtained and how the diagnostic algorithm based on the timed automaton is applied to detect and identify actuator faults. A representative diagnostic result is presented and discussed to illustrate the effectiveness of the method. r 2005 Elsevier Ltd. All rights reserved.
Time-series and real options analysis of energy markets

After the deregulation of electricity industries on the premise of increasing economic efficiency, market participants have been exposed to financial risks due to uncertain energy prices. Using time-series analysis and the real options approach, we focus on modelling energy prices and optimal decision-making in energy projects. Since energy prices are highly volatile with unexpected spikes, capturing this feature in reduced-form models leads to more informed decision-making in energy investments. In this thesis, non-linear regime-switching models and models with mean-reverting stochastic volatility are compared with ordinary linear models. Our numerical examples suggest that with the aim of valuing a gas-fired power plant, non-linear models with stochastic volatility, specifically for logarithms of electricity prices, provide better out-of-sample forecasts. Among a comprehensive scope of mitigation measures for climate change, CO2 capture and sequestration (CCS) plays a potentially significant role in industrialised countries. Taking the perspective of a coal-fired power plant owner that may decide to invest in either full CCS or partial CCS retrofits given uncertain electricity, CO2, and coal prices, we develop an analytical real options model that values the choice between the two technologies. Our numerical examples show that neither retrofit is optimal immediately, and the optimal stopping boundaries are highly sensitive to CO2 price volatility. Taking the perspective of a load-serving entity (LSE), on the other hand, we value a multiple-exercise interruptible load contract that allows the LSE to curtail electricity provision to a representative consumer multiple times for a specified duration at a defined capacity payment given uncertain wholesale electricity price. Our numerical examples suggest that interruption is desirable at relatively high electricity prices and that uncertainty favours a delay in interrupting. Moreover, we show that a deterministic approximation captures most of the value of the interruptible load contract if the volatility is low and the exercise constraints are not too severe.
Financial Development and Economic Growth in Egypt: A Re-Investigation

In light of the political and economic conditions that Egypt has challenged during the last two years and its influences, it is crucial to re-investigate the link between financial sector and economic growth using recent data sample. This paper re-explores it using annual data for the period from 1988 to 2012. The results imply that the banking sector development has a unidirectional causal impact on economic growth. However, stock market development does not cause growth. The interpretation of such outcomes has to be taken with caution since other relevant factors are more likely to affect this link.
Translocation of dendrin to the podocyte nucleus in acute glomerular injury in patients with IgA nephropathy.

BACKGROUND It has been reported that podocytopenia has been occurring with increasing disease severity in patients with IgA nephropathy (IgAN). Dendrin is localized at the slit diaphragm (SD) in podocytes. We showed that dendrin translocates to the nucleus of injured podocytes in experimental nephritis and the nuclear dendrin promotes podocyte apoptosis. It is still unknown whether dendrin translocates from the SD to podocyte nucleus in IgAN. We investigated the presence of nuclear dendrin in patients with IgAN and the association between the translocated dendrin to the podocyte nucleus and disease activity. METHODS Fourteen adult patients with IgAN were enrolled. The pathological parameters were analyzed. Immunostaining of renal biopsy specimens and urinary sediments from IgAN or minimal change nephrotic syndrome (MCNS) as the control was performed. RESULTS A positive correlation was observed between an acute extracapillary change and the number of dendrin-positive nuclei. The location of dendrin in the nuclei was found in urinary podocytes of IgAN. The number of dendrin-positive nuclei in urinary podocytes of IgAN was significantly higher than that of MCNS. Urinary podocytes, which expressed the apoptosis marker annexin V, were also detected in IgAN. The translocation of dendrin to the podocyte nucleus as well as strong cathepsin L staining were detected in the glomeruli of IgAN. CONCLUSION An increasing number of dendrin-positive nuclei in the glomeruli suggest acute glomerular injury in IgAN. Apoptotic podocytes were detectable in the urine of IgAN. It appears that the translocation of dendrin to the podocyte nuclei enhances podocyte apoptosis in acute glomerular injury and leads to podocytopenia in patients with IgAN.
Extraction of Family Relations between Entities

Nowadays, there is a growing need to automatically extract information from texts. In this active research field much eort has been invested to improve the identification and classification of named enti- ties, the detection of time expressions, and the identification of semantic relations between text entities. This paper presents a system that iden- tifies and classifies family relations. The directives, the options used, the implementation and the results obtained are here presented. Resumo. Existe uma necessidade crescente em extrair informacao a partir de um texto, nomeadamente na identificacao e classificacao de en- tidades mencionadas e na identificacao de relacoes semanticas entre essas entidades. Este artigo apresenta um sistema que identifica relacoes famil- iares. Descrevem-se as directivas de identificacao e anotacao, as opcoes adoptadas, a implementacao do sistema e os resultados obtidos.
A new approach to query by humming in music retrieval

In this paper, we present a method for querying desired songs from music database by humming a tune. Since errors are inevitable in humming, tolerance should be considered. In order to suit or adapt to people’s humming habit, a new melody representation and new hierarchical matching method are proposed in this paper. Query processing and database processing algorithm are also described in detail. The proposed approach achieves high performance in experimental evaluation. For 88% queries, the correct song can be retrieved among the top 10 matches.
Cycle Inhibiting Factors (Cifs): Cyclomodulins That Usurp the Ubiquitin-Dependent Degradation Pathway of Host Cells

Cycle inhibiting factors (Cifs) are type III secreted effectors produced by diverse pathogenic bacteria. Cifs are “cyclomodulins” that inhibit the eukaryotic host cell cycle and also hijack other key cellular processes such as those controlling the actin network and apoptosis. This review summarizes current knowledge on Cif since its first characterization in enteropathogenic Escherichia coli, the identification of several xenologues in distant pathogenic bacteria, to its structure elucidation and the recent deciphering of its mode of action. Cif impairs the host ubiquitin proteasome system through deamidation of ubiquitin or the ubiquitin-like protein NEDD8 that regulates Cullin-Ring-ubiquitin Ligase (CRL) complexes. The hijacking of the ubiquitin-dependent degradation pathway of host cells results in the modulation of various cellular functions such as epithelium renewal, apoptosis and immune response. Cif is therefore a powerful weapon in the continuous arm race that characterizes host-bacteria interactions.
Investigation of Technical Equipment in Computer Stereo Vision : Camera Calibration Techniques

The sense of vision plays an important role in the life of human: it allows them to infer spatial properties of the environment. Vision is necessary to explore unfamiliar surroundings, detect and recognize distances in physical space. A visual system is a collection of devices that transform measurements of light into information about spatial and material properties of a scene. There is necessary to have photosensitive sensors (a camera), also computational mechanisms (a computer) that allows to extract information from the sensors. Certainly the pixel values recorded with a camera depend on the shape of objects in the scene: if the shape has been changed, there is noticeable a change in the image. Therefore, images depend on the geometry of the scene. However, they also depend on its photometry, the illumination and the material properties of objects. Visual measurements depend on the dynamics of the environment. In general, we do not know the shape of the scene, its material properties and motion. The goal is to infer a representation of the world from collection of images. This goal can be achieved by various tasks and algorithms, those include [1]: • Given two images, compute matches between the images, and the 3D position of the points that generate these matches and the cameras that generate the images. • Given three images, compute the matches between images of points and lines, and the position in 3D of these points and lines and the cameras. • Compute the epipolar geometry of a stereo rig, and trifocal geometry of a trinocular rig, without requiring a calibration object. • Compute the internal calibration of a camera from a sequence of images of natural scenes. This paper is concentrated on the analysis of camera calibration techniques in computer stereo vision when given two or more images and no other information and the calibration is done with a calibration object or without it.
GWAS identifies a single selective sweep for age of maturation in wild and cultivated Atlantic salmon males

Background Sea age at sexual maturation displays large plasticity for wild Atlantic salmon males and varies between 1-5 years. This flexibility can also be observed in domesticated salmon. Previous studies have uncovered a genetic predisposition for age at maturity with moderate heritability, thus suggesting a polygenic nature of this trait. The aim with this study was to identify genomic regions and associated SNPs and genes conferring age at maturity in salmon. Results We performed a GWAS using a pool sequencing approach (n=20 per river and trait) of salmon returning as sexually mature either after one sea winter (2009) or after three sea winters (2011) in six rivers in Norway. The study revealed one major selective sweep, which covered 76 significant SNP in a 230 kb region of Chr 25. A SNP assay of other year classes of wild salmon and from cultivated fish supported this finding. The assay in cultivated fish reduced the haplotype conferring the trait to a region which covered 4 SNPs of a 2386 bp region containing the vgll3 gene. 2 of these SNPs caused miss-sense mutations in vgll3. Conclusions This study presents a single selective region in the genome for age at maturation in male Atlantic salmon. The SNPs identified may be used as QTLs to prevent early maturity in aquaculture and in monitoring programs of wild salmon. Interestingly, the identified vgll3 gene has previously been linked to time of puberty in humans, suggesting a conserved mechanism for time of puberty in vertebrates. CC-BY-NC-ND 4.0 International license not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was . http://dx.doi. org/10.1101/024927 doi: bioRxiv preprint first posted online Aug. 17, 2015;
Update on hidradenitis suppurativa: connecting the tracts

Hidradenitis suppurativa (HS) is a debilitating skin disease characterized by recurrent abscesses, sinus tract formation, and scarring. Prevalence estimates range from 0.053% to 4.1%, although HS is likely an underdiagnosed disease. Although the first reports of HS date back to the mid-19th century, the disease continues to plague patients and physicians desperate for a definitive treatment. Advances in the understanding of the disease process include the possibility of a defective basement membrane at the sebofollicular junction of the folliculopilosebaceous unit (FPSU; that is, where the sebaceous gland empties into the hair follicle) as an initiating event followed by secondary bacterial colonization. New evidence suggests that bacteria living in a community, known as a biofilm, rather than single planktonic bacteria in HS lesions may explain why HS can be resistant to current antibiotic treatment regimens. Available treatment options have expanded to include triple-antibiotic therapy, tumor necrosis factor (TNF-α) and interleukin-1 (IL-1) inhibitors (biologics), laser therapy, and surgical excision, including the skin tissue-sparing excision with electrosurgical peeling procedure. Despite the array of treatments available, many patients continue to struggle with the embarrassment, pain, odor, and frustration that accompany this often isolating disease. Physicians should address comorbidities in HS, including the psychosocial issues patients with HS frequently encounter. Patients can be directed to HS support groups, where they can openly discuss their frustrations, share their experiences in dealing with HS, and band together to advocate for themselves. HS is misunderstood by both patients and physicians, often resulting in a delay in clinical presentation and diagnosis. Patients and physicians across multiple specialties must work together to expand awareness of and interest in HS, so that one day, individuals with HS can be freed from this crippling disease.
Space-time surface reconstruction using incompressible flow

We introduce a volumetric space-time technique for the reconstruction of moving and deforming objects from point data. The output of our method is a four-dimensional space-time solid, made up of spatial slices, each of which is a three-dimensional solid bounded by a watertight manifold. The motion of the object is described as an incompressible flow of material through time. We optimize the flow so that the distance material moves from one time frame to the next is bounded, the density of material remains constant, and the object remains compact. This formulation overcomes deficiencies in the acquired data, such as persistent occlusions, errors, and missing frames. We demonstrate the performance of our flow-based technique by reconstructing coherent sequences of watertight models from incomplete scanner data.
Dezocine for Preventing Postoperative Pain: A Meta-Analysis of Randomized Controlled Trials

Background Dezocine is considered to be an alternative medication for managing postoperative pain. The aim of this study was to assess the efficacy and safety of this drug in this regard. Methods Medline, EMBASE and the Cochrane Central Register of Control Trials (CENTRAL) were searched to identify all randomized controlled trials (RCTs) that compare dezocine with placebo or dezocine with morphine on postoperative pain. The data were extracted and pooled using Mantel-Haenszel random effects model. Heterogeneity was tested using the I 2 statistic with values >50% and Chi2 test with P ≤ 0.05 indicating obvious heterogeneity between the studies. Results Seven trials evaluating 665 patients were included. The number of patients with at least 50% pain relief was increased (N = 234; RR 3.04, 95% CI 2.27 to 4.08) and physician (N = 465; RR 2.84, 95% CI 1.66 to 4.84) and patient satisfaction (N = 390; RR 2.81, 95% CI 1.85 to 4.26) were improved following the administration of dezocine compared with the placebo. The effects of dezocine were similar to those of morphine in terms of the number of patients reporting at least 50% pain relief within 2–6 h after surgery (N = 235; RR 1.29, 95% CI 1.15 to 1.46) and physician (N = 234; RR 1.18, 95% CI 0.93 to 1.49) and patient (N = 158; RR 1.33, 95% CI 0.93 to 1.92) satisfaction. While, the number of patients with at least 50% pain relief within 0–1 h after surgery increased following dezocine compared with morphine treatment (N = 79; RR 1.45, 95% CI 1.18 to 1.77). There was no difference in the incidence of postoperative nausea and vomiting (PONV) following dezocine treatment compared with the placebo (N = 391; RR 1.06, 95% CI 0.42 to 2.68) or morphine treatment (N = 235; RR 0.65, 95% CI 0.14 to 2.93). Conclusion Dezocine is a promising analgesic for preventing postoperative pain, but further studies are required to evaluate its safety.
On Achieving the Maximum Internet Capacity in Wireless Mesh Networks

A Wireless Mesh Network (WMN) is connected by multiple wireless mesh routers that are able to operate multiple channels for increased network capacity. At the same time, the infrastructure such as Internet gateway provides the Internet connectivity and thus the mobile users in the network can access the Internet by multi-hop route of mesh routers. As other wireless networks, the network capacity is a fundamental issue in the WMN. The analytical results in this paper show that the upper bound of network capacity. Only when the number of Internet gateway nodes asymptotically grows with the number of mesh routers, the network capacity achieves significant capacity gain. We theoretically compute the WMN upper bounds of the infrastructure network capacity and its ad hoc capacity as well.
Interactive simulation of elastic deformable materials.

A novel, fast, stable, physics-based numerical method for interactive simulation of elastically deformable objects is presented. Starting from elasticity theory, the deformation energy is modeled in terms of the positions of point masses using the linear shape functions of finite element analysis, providing for an exact correspondence between the known physical properties of deformable bodies such as Young’s modulus, and the simulation parameter. By treating the infinitely stiff case as a kinematic constraint on a system of point particles and using a regularization technique, a stable first order stepping algorithm is constructed which allows the simulation of materials over the entire range of stiffness values, including incompressibility. The main cost of this method is the solution of a linear system of equations which is large but sparse. Commonly available sparse matrix packages can process this problem with linear complexity in the number of elements for many cases. This method is contrasted with other well-known point mass models of deformable solids which rely on penalty forces constructed from simple local geometric quantities, e.g., spring-and-damper models. For these, the mapping between the simulation parameters and the physical observables is not well defined and they are either strongly limited to the low stiffness case when using explicit integration methods, or produce grossly inaccurate results when using simple linearly implicit method. Validation and timing tests on the new method show that it produces very good physical behavior at a moderate computational cost, and it is usable in the context of real-time interactive simulations. CR Categories: I.3. 5 [Computer Graphics]: Physically based modeling— [I.3. 7]: Computer Graphics—Virtual reality
Optimizing Peer-to-Peer content discovery over wireless mobile ad hoc networks

Peer-to-Peer (P2P) networks are frequenlty used for data sharing over mobile ad hoc networks (MANETs) due to their decentralization and high tolerance to failures. However, P2P networks do not perform well on MANETs. Structured P2P networks have a high level of unsuccessful queries due to the message drops, while unstructured networks saturate quickly due to the high number of messages sent. This work proposes ameliorations to both P2P approaches. Our solutions reduce the average energy consumption and delay in unstructured approaches at the expense of a smaller loss on the success ratio, while in structured approaches our modifications increase the success ratio at the expense of average energy consumption and delay.
A Corpus-Based Approach to Speech Enhancement From Nonstationary Noise

Temporal dynamics and speaker characteristics are two important features of speech that distinguish speech from noise. In this paper, we propose a method to maximally extract these two features of speech for speech enhancement. We demonstrate that this can reduce the requirement for prior information about the noise, which can be difficult to estimate for fast-varying noise. Given noisy speech, the new approach estimates clean speech by recognizing long segments of the clean speech as whole units. In the recognition, clean speech sentences, taken from a speech corpus, are used as examples. Matching segments are identified between the noisy sentence and the corpus sentences. The estimate is formed by using the longest matching segments found in the corpus sentences. Longer speech segments as whole units contain more distinct dynamics and richer speaker characteristics, and can be identified more accurately from noise than shorter speech segments. Therefore, estimation based on the longest recognized segments increases the noise immunity and hence the estimation accuracy. The new approach consists of a statistical model to represent up to sentence-long temporal dynamics in the corpus speech, and an algorithm to identify the longest matching segments between the noisy sentence and the corpus sentences. The algorithm is made more robust to noise uncertainty by introducing missing-feature based noise compensation into the corpus sentences. Experiments have been conducted on the TIMIT database for speech enhancement from various types of nonstationary noise including song, music, and crosstalk speech. The new approach has shown improved performance over conventional enhancement algorithms in both objective and subjective evaluations.
An effective access from cloud data using attribute based encryption

Cloud Computing is an important way of communicating and share data over Internet. Cloud Computing enables transmission of data over Internet and resource utilization at data centers. But during data sharing and resource utilization security plays a vital role since the chances of attacks increases. The data to be stored at data centers needs to be retrieved without any data loss and attack. Hence a multi key based data retrieved with encryption is proposed previously but the techniques require more computational time and hence increase the overall cost. Here in this paper a new and efficient is implemented which uses the concept of Cipher text policy attribute based encryption using elliptic curve based key generation. The implementation is based on the concept of generating a new attribute for each and every data to be send and encrypt the data using the generated attribute and forms a tupple and stored at the storage site. The receiver then authenticates himself and enters the attribute and hence decrypts the data. The proposed methodology implemented here provides efficient retrieval of data over cloud as well as reduces computational time and cost.