Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of a multiple series-connected IGBT converter for large-capacity STATCOM

This paper reports the development of a converter for a large-capacity STATCOM. The converter consists of multiple series-connected 1.7kV module-type IGBTs. An active gate controlled circuit that we developed was applied to the IGBT gate drive circuit, eliminating large-capacity voltage-clamped snubber circuits or voltage balancing circuits that are conventionally needed for a series-connected IGBT converter, which considerably simplifies the converter. A rated-power test was performed, the results of which confirmed satisfactory performance of the developed converter.
Development of a silicon gamma ray spectrometer

We present the initial results obtained with double-sided silicon strip detectors used as a nonimaging gamma ray spectrometer. Silicon detectors have previously been proposed as sensors for the scatterer of a regular Compton telescope, or as sensors for a multiple scatter Compton imager where three or more interactions in the silicon are used to image and determine the energy of a gamma ray, even if all the energy is not absorbed. This work extends that concept to the case where the source location is known, as in solar physics, and where the main interest is a high-resolution spectrum. With the source location known, only two interactions are required to reconstruct a spectrum of the source. We made a proof of concept demonstration using two small silicon detectors. The detectors were 63 /spl times/63 mm in area and 2 mm thick, with 0.9-mm orthogonal strips on both faces. A full-energy peak with an energy resolution of /spl sim/40 keV was obtained at 662 keV. This was in good agreement with our simulations. Using detectors with a finer strips pitch an energy resolution of 15 keV (68% containment) can be achieved at 662 keV. This is limited by the momentum distribution of the electrons in silicon. The energy resolution can be improved by kinematically selecting events, although at the cost of detector efficiency. Another unique feature of this approach is the fact that a spectrum is reconstructed with a full energy peak but without any Compton continuum.
Comparative Rhetoric: An Integration of Perspectives.

A discussion of approaches to comparative rhetoric looks at diverse approaches and proposes that analysis can be enriched by incorporating the perspective of ethnography of communication. Contributions to the field of comparative rhetoric from second language learning and teaching mainstream rhetoric, and text linguistics are discussed, focusing on differences in definition, scope and focus, and on the major limitations and biases of each. An ethnography of communication perspective is then outlined. It is suggested that a comparative functional emphasis that incorporates rich specification of contextual factors from internal cultural perspectives can significantly enhance validity of interpretation. Practical and theoretical applications of an ethnography of communication approach to comparative rhetoric are discussed. Contains 42 references. (Author/MSE) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. *********************************************************************** Pragmatics and Language Learning Monograph Series, Volume 5, 1994 COMPARATIVE RHETORIC: AN INTEGRATION OF PERSPECTIVES U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement DUCATIONAL RESOURCES INFORMATION CENTER (ERIC) This document has been reproduced as received from the person or organization originating it. Minor changes have been made to improve reproduction quality.
Portfolio Management Using Artificial Trading Systems Based on Technical Analysis

Evolutionary algorithms consist of several heuristics able to solve optimization tasks by imitating some aspects of natural evolution. In the field of computational finance, this type of procedures, combined with neural networks, swarm intelligence, fuzzy systems and machine learning has been successfully applied to a variety of problems, such as the prediction of stock price movements and the optimal allocation of funds in a portfolio.
High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis

The authors review the theoretical basis of determination of cerebral blood flow (CBF) using dynamic measurements of nondiffusible contrast agents, and demonstrate how parametric and nonparametric deconvolution techniques can be modified for the special requirements of CBF determination using dynamic MRI. Using Monte Carlo modeling, the use of simple, analytical residue models is shown to introduce large errors in flow estimates when actual, underlying vascular characteristics are not sufficiently described by the chosen function. The determination of the shape of the residue function on a regional basis is shown to be possible only at high signal‐to‐noise ratio. Comparison of several nonparametric deconvolution techniques showed that a nonparametric deconvolution technique (singular value decomposition) allows estimation of flow relatively independent of underlying vascular structure and volume even at low signal‐to‐noise ratio associated with pixel‐by‐pixel deconvolution.
Passage time distributions in large Markov chains

Probability distributions of response times are important in the design and analysis of transaction processing systems and computer-communication systems. We present a general technique for deriving such distributions from high-level modelling formalisms whose state spaces can be mapped onto finite Markov chains. We use a load-balanced, distributed implementation to find the Laplace transform of the first passage time density and its derivatives at arbitrary values of the transform parameter s. Setting s = 0 yields moments while the full passage time distribution is obtained using a novel distributed Laplace transform inverter based on the Laguerre method. We validate our method against a variety of simple densities, cycle time densities in certain overtake-free (tree-like) queueing networks and a simulated Petri net model. Our implementation is thereby rigorously validated and has already been applied to substantial Markov chains with over 1 million states. Corresponding theoretical results for semi-Markov chains are also presented.
Accuracy of the Michaelis–Menten approximation when analysing effects of molecular noise

Quantitative biology relies on the construction of accurate mathematical models, yet the effectiveness of these models is often predicated on making simplifying approximations that allow for direct comparisons with available experimental data. The Michaelis–Menten (MM) approximation is widely used in both deterministic and discrete stochastic models of intracellular reaction networks, owing to the ubiquity of enzymatic activity in cellular processes and the clear biochemical interpretation of its parameters. However, it is not well understood how the approximation applies to the discrete stochastic case or how it extends to spatially inhomogeneous systems. We study the behaviour of the discrete stochastic MM approximation as a function of system size and show that significant errors can occur for small volumes, in comparison with a corresponding mass-action system. We then explore some consequences of these results for quantitative modelling. One consequence is that fluctuation-induced sensitivity, or stochastic focusing, can become highly exaggerated in models that make use of MM kinetics even if the approximations are excellent in a deterministic model. Another consequence is that spatial stochastic simulations based on the reaction–diffusion master equation can become highly inaccurate if the model contains MM terms.
Prevention of norovirus infection in schools and childcare facilities

A public consultation on this technical report was opened on ECDC's website from 12 July to 31 August 2012. Information about the public consultation was broadly communicated to stakeholders. The objective of this technical report is to provide guidance for use in the European Union (EU) that synthesises current international guideline recommendations using an ADAPTE i methodology, and reviews findings related to the prevention and control of gastroenteritis outbreaks in schools and childcare facilities. The target group of this report is public health institutions at the national and local level involved in health promotion and education. The particular focus of the report is on norovirus, which is of major public health importance. It is one of the most common causes of childhood gastroenteritis and with epidemiological characteristics that promote a high rate of infectivity and transmission. The report also aims to contribute to identifying the key facts that can support message development for the implementation of health communication activities in childcare settings. Providing diagnostic guidance for norovirus was not within the scope of this work. The report is divided into four sections outlining: primary prevention measures to be taken to prevent gastroenteritis outbreaks in school and childcare settings action to be taken upon an outbreak of gastroenteritis (norovirus or otherwise) key infection control measures to be taken during an outbreak action to be taken at the conclusion of an outbreak, including training and remediation planning. Validation of the guidance has been done by internal review, external (peer) review, and an expert panel meeting held in Stockholm in December 2011. Following consultation, any additional documents or information, including regional protocols, that were referred to us during the peer review process, were reviewed to ensure that the information contained within this report was broadly consistent with that of other sources. The evidence base surrounding infection control interventions to prevent and control outbreaks of gastroenteritis, in particular norovirus, in childcare facilities is fairly limited. No systematic reviews or randomised controlled trials that provide firm evidence to support the effectiveness of any infection control measures, including exclusion strategies, hand hygiene or surface cleaning and disinfection were identified. This may reflect the difficulties in ethical approval for such studies, in addition to the relative cost. There are several observational and experimental studies that support the value of hand hygiene methods in preventing the carriage and transfer of infective organisms (washing with soap and water and …
Faster time-aligned phonetic transcriptions through partial automation

A semi-automatic process for generating time-aligned transcriptions of speech data at the word and phone level is described. At each stage in the process, segment durations are estimated to generate approximate boundary markers, which are then corrected by hand. Corrections at one level are taken into account in the generation of boundaries for the next level, such that the error is reduced at each successive stage. A test implementation based on Praat was applied to a corpus of Brazilian Portuguese and a comparison against a fully manual process revealed a reduction of 54% in the time required to generate phonetic transcriptions and an average error of 21 ms in the time-alignment of phonetic boundaries.
Modeling and Verifying Complex Objects: A Declarative Approach Based on Description Logics

Description logics are good candidates for representing co mplex objects. Their expressive and computational properties ha ve been extensively studied and are well understood. However, from a knowledge engineering perspective, the current reasoning servi ces provided by description logic systems do not suffice for representing objects. Adding services (e.g help for debugging) is necessar y to make description logic systems useful tools for building object -centered knowledge bases. In this paper, we present a principled glass-box approach both for trace-based debugging and for supporting transparent modeling of whole-part relationship, using descrip tion logics. This approach has been proven very useful for a real application of modeling components of power plants.
DAFOE: An Ontology Building Platform - From Texts or Thesauri

This paper describes a new platform for building ontologies using many entries (texts, terminologies, thesauri or database). However, They may be build from scratch and bound with texts afterwards. After a description of the used data model, a meta-modelisation architecture is presented as well as the database implementation, which allows to manage large ontologies with large corpora.
IL4 gene polymorphisms in Iranian patients with autoimmune hepatitis

ABSTRACT Background: Autoimmune hepatitis (AIH) is a chronic long-lasting hepatocellular inflammation associated with circulating auto antibodies. In addition to the genetic component, several cytokines have been implicated to be involved in AIH. This study was performed to investigate potential associations of AIH with IL4 gene variants. Method: The studied alleles and genotypes included: IL4G/T allele polymorphisms at position -1098 and C/T allele polymorphisms at two positions (-33 and -590) on the IL4 gene, in addition to the A/G allele polymorphisms at position +1902 on the IL4RA gene. Result: The IL4 C allele and CC genotype at position -590 and TT genotype at position -33 had a significantly higher frequency in AIH patients. Conclusion: This study identified the IL4 C allele and CC genotype susceptibility gene in AIH, which will provide better insights into the mechanisms of AIH and potential therapeutic interventions.
An adaptive virtual machine replication algorithm for highly-available services

This paper presents an adaptive algorithm for the replication process of a primary virtual machine (VM) hosting a service that must be provided high-availability. Running the service in a VM and replicating the entire VM is a general strategy, totally transparent for the service itself and its clients. The replication takes place in phases, which are run asynchronous for efficiency reasons. The replication algorithm adapts to the running context, consisting of the behavior of the service and the available bandwidth between primary and backup nodes. The length of each replication phase is determined dynamically, in order to reduce as much as possible the latencies experienced by the clients of the service, especially in the case of a degraded connectivity between primary and backup nodes. We implemented our replication algorithm as an extension of the Xen hypervisor's VM migration operation. It proved better than its non-adaptive variants.
The Potential of Stem Cells in the Treatment of Skeletal Muscle Injury and Disease

Tissue engineering is a pioneering field with huge advances in recent times. These advances are not only in the understanding of how cells can be manipulated but also in potential clinical applications. Thus, tissue engineering, when applied to skeletal muscle cells, is an area of huge prospective benefit to patients with muscle disease/damage. This could include damage to muscle from trauma and include genetic abnormalities, for example, muscular dystrophies. Much of this research thus far has been focused on satellite cells, however, mesenchymal stem cells have more recently come to the fore. In particular, results of trials and further research into their use in heart failure, stress incontinence, and muscular dystrophies are eagerly awaited. Although no doubt, stem cells will have much to offer in the future, the results of further research still limit their use.
A Fluid Mechanical Interpretation of Hysteresis in Rhinomanometry

A hysteresis effect in the pressure/flow rate relationship of nasal breathing has frequently been observed in clinical tests and in lab investigations. Explanations that have been given in the literature are missing a fluid mechanic storage effect coming into play in reciprocating flows. This effect depends primarily on the way the rhinomanometric measurements are set up and not so much on the nose flow itself. This is to be shown by calculations and experiments. The experiments are carried out with orifices because they can represent nose flow and are often implemented in rhinomanometric equipment as flow gauges. To mimic reality also a 1 : 1 nose model is used. It is shown where the hysteresis comes from and what the key parameters for its prediction are. With these results hysteresis in nasal breathing appears in a new light.
Mechanisms of olfactory receptor neuron specification in Drosophila

Detection of a broad range of chemosensory signals is necessary for the survival of multicellular organisms. Chemical signals are the main facilitators of foraging, escape, and social behaviors. To increase detection coverage, animal sensory systems have evolved to create a large number of neurons with highly specific functions. The olfactory system, much like the nervous system as a whole, is astonishingly diverse.1‐3 The mouse olfactory system has millions of neurons with over a thousand classes, whereas the more compact Drosophila genome has approximately 80 odorant receptor genes that give rise to 50 neuronal classes and 1300 neurons in the adult.4 Understanding how neuronal diversity is generated remains one of the central questions in developmental neurobiology. Here, we review the current knowledge on the development of the adult Drosophila olfactory system and the progress that has been made toward answering this central question. WIREs Dev Biol 2015, 4:609–621. doi: 10.1002/wdev.197
Proteomic Identification of an Upregulated Isoform of Annexin A3 in the Spinal Cords of Rats in a Neuropathic Pain Model

Neuropathic pain (NP) is induced by nerve damage or a disturbance in the peripheral or central nervous systems. Nerve damage causes the activation of sensitizing mechanisms in the peripheral and central nervous systems, which induces transcriptional and post-transcriptional alterations in sensory nerves. However, the underlying mechanisms of NP remain elusive. In the study, Two-dimensional gel electrophoresis (2DGE)-based comparative proteomics identified 38 differential gel spots, and 15 differentially expressed proteins (DEPs) between the sham and the chronic constriction injury (CCI)-induced neuropathic pain rats. Of them, Annexin A3 (ANXA3) was significantly increased after CCI with Western blot analysis and immunofluorescence imaging. A lentivirus delivering ANXA3 shRNA (LV-shANXA3) was administered intrathecally to determine the analgesic effects of ANXA3 on allodynia and hyperalgesia in a CCI-induced neuropathic pain model in rats. Further study showed that LV-shANXA3 reversed the upregulation of ANXA3, alleviated CCI-induced mechanical allodynia and thermal hyperalgesia. The study indicated that ANXA3 may play an important role in neuropathic pain.
Beyond Association Rules: Generalized Rule Discovery

Generalized rule discovery is a rule discovery framework that subsumes association rule discovery and the type of search employed to nd individual rules in classication rule discovery. This new rule discovery framework escapes the limitations of the support-condence framework inherent in association rule discovery. This empowers data miners to identify the types of rules that they wish to discover and develop ecien t algorithms for discovering those rules. This paper presents a scalable algorithm applicable to a wide range of generalized rule discovery task and demonstrates its eciency .
Assessment of Cyber Security Challenges in Nuclear Power Plants Security Incidents , Threats , and Initiatives

Nuclear power plants play an important role in electricity production for many countries. They supply power to industries, centers, government facilities, and residential areas. Yet, upon review, several cases reveal that even a small-scale attack on a nuclear power plant could lead to catastrophic consequences for a country’s citizens, economy, infrastructure, and security. In recent years, there has been increased attention to the area of nuclear cybersecurity due to attacks or incidents designed to disrupt NPP operations. In spite of this rise of nuclear-related cyber attacks, the security for NPPs has not been holistically addressed. Literature review reveals the lack of a comprehensive information security framework to secure nuclear power plants from internal and external threats. This research highlights the significance of performing security assessments within NPPs as it relates to cyber defense. The contribution of this paper is twofold. First, it presents a detailed review of cyber challenges and security incidents that have occurred within NPPs, followed by a discussion on the initiatives taken by governments and regulatory bodies in mitigating such security challenges. Contextual background information on Critical Infrastructure Protection, nuclear power plants and information security risk management has been supplied to aid reader understanding. Additionally, this research posits that any kind of cyber incident on nuclear infrastructure may lead to catastrophic results, from which recovery may be impossible. Therefore, there is a significant need to perform detailed threat and vulnerability assessments that address either stand-alone attacks or coordinated attacks against the use of computer systems on NPPs. Following this discussion, a threat modelling is presented using an established methodology, which identifies possible threats to, vulnerabilities in, and adversaries of a generic Instrumentation and Control (I&C) system of a NPP by considering its characteristics and architecture. The analysis reveals that NPPs are not fully armed against cyber attacks and identifies a significant need to conduct security assessments such as the Information Security Risk Assessment, which would provide comprehensive and reliable risk analysis functionality to NPPs.
Regionlets for Generic Object Detection

Generic object detection is confronted by dealing with different degrees of variations in distinct object classes with tractable computations, which demands for descriptive and flexible object representations that are also efficient to evaluate for many locations. In view of this, we propose to model an object class by a cascaded boosting classifier which integrates various types of features from competing local regions, named as region lets. A region let is a base feature extraction region defined proportionally to a detection window at an arbitrary resolution (i.e. size and aspect ratio). These region lets are organized in small groups with stable relative positions to delineate fine grained spatial layouts inside objects. Their features are aggregated to a one-dimensional feature within one group so as to tolerate deformations. Then we evaluate the object bounding box proposal in selective search from segmentation cues, limiting the evaluation locations to thousands. Our approach significantly outperforms the state-of-the-art on popular multi-class detection benchmark datasets with a single method, without any contexts. It achieves the detection mean average precision of 41.7% on the PASCAL VOC 2007 dataset and 39.7% on the VOC 2010 for 20 object categories. It achieves 14.7% mean average precision on the Image Net dataset for 200 object categories, outperforming the latest deformable part-based model (DPM) by 4.7%.