Miracle-dz/UniFAR-FTUs huggingface dataset:
6 Related Work

A real-time duration semantics for circuits. 20 appearance of DC formulas. The system does not prevent the user from explicitly expanding the semantic encoding, nor from introducing intervals in the proof. So far, we have only checked small, well-known examples using the tool: the simple gas burner, a railway crossing, and a water level monitor. As expected, the decision procedures turned out to be useful. Next, the tool must be submitted to the scrutiny of bigger examples and diierent users to obtain a more robust system. Initial experiences indicate that the simple process of writing the speciication in a rigorously typed environment ferrets out a number of errors in the speciication. Using PVS as a semantic framework has exercised it in a useful manner. It has illustrated how the higher-order logic of PVS and the tight integration of decision procedures can be used to encode and reason about modal formalisms. This work has inspired several modiications to PVS: incorporating new parsers within the same tool, user speciied type coercion, and the application of decision procedures to indexed terms. Acknowledgements We are indebted to Sam Owre for his help during the construction of the prototype tool, particularly the PC/DC parser. We are also grateful for the valuable comments from Previously, the semantics of various logics have been encoded within existing theorem proving or proof checking systems. The approach is nicely described by Gordon 10] where he describes an encoding of Hoare Logic 15] within the HOL system 9]. Goldschlag 8] has similarly encoded the Unity logic 3] using the Boyer-Moore theorem prover 2]. Andersen 1] describes an encoding of Unity using the HOL system. An encoding of Timed Transition Systems and Real-Time Temporal Logic in HOL is described by Hale, Cardell-Oliver, and Herbert 11]. The advantage of these encodings is that a signiicant fraction of the capabilities of the underlying base logic and proof checking system can be exploited to support the encoded source logic. The typical disadvantage of the approach is that a user is required to understand the details of the encoding and often has to work directly in the base logic with the encoded form of the source logic. Chou 4] presents a method for lifting the HOL inference rules and tactics to operate at the predicate rather than the Boolean level. This form of lifting is also essential to our encoding of DC in PVS. An alternative …
Repetitive Transcranial Magnetic Stimulation to Supplementary Motor Area in Refractory Obsessive-Compulsive Disorder Treatment: a Sham-Controlled Trial

Background: Repetitive transcranial magnetic stimulation has been explored in patients with obsessive-compulsive disorder, but with negative or conflicting results. This randomized double-blind study was designed to assess the efficacy of 1-Hz repetitive transcranial magnetic stimulation over the presupplementary area. Methods: Forty medication-resistant patients were assigned to 4 weeks of either active or sham repetitive transcranial magnetic stimulation targeting the presupplementary area with the help of a neuronavigation system. Results: According to the Yale-Brown obsessive-compulsive scale, the baseline-week 4 evolution showed no significant differences between groups. Responder rates at week 4 were not different between groups (repetitive transcranial magnetic stimulation 10.5% vs sham 20%; P=.63). Conclusion: Low-frequency repetitive transcranial magnetic stimulation applied to the presupplementary area seems ineffective for the treatment of obsessive-compulsive disorder patients, at least in severe and drug-refractory cases such as those included in this study. Further research is required to determine profiles of responder patients and appropriate repetitive transcranial magnetic stimulation parameters for obsessive-compulsive disorder.
Development cycle 2 of the Modular Earth Submodel System (MESSy2)

Abstract. The Modular Earth Submodel System (MESSy) is an open, multi-institutional project providing a strategy for developing comprehensive Earth System Models (ESMs) with highly flexible complexity. The first version of the MESSy infrastructure and process submodels, mainly focusing on atmospheric chemistry, has been successfully coupled to an atmospheric General Circulation Model (GCM) expanding it into an Atmospheric Chemistry GCM (AC-GCM) for nudged simulations and into a Chemistry Climate Model (CCM) for climate simulations. Here, we present the second development cycle of MESSy, which comprises (1) an improved and extended infrastructure for the basemodel independent coupling of process-submodels, (2) new, highly valuable diagnostic capabilities for the evaluation with observational data and (3) an improved atmospheric chemistry setup. With the infrastructural changes, we place the headstone for further model extensions from a CCM towards a comprehensive ESM. The new diagnostic submodels will be used for regular re-evaluations of the continuously further developing model system. The updates of the chemistry setup are briefly evaluated.
Status, stigma and stereotype: How drug takers and drug suppliers avoid negative labelling by virtue of their ‘conventional’ and ‘law-abiding’ lives

A minority of those who consume or supply illegal drugs are detected and subsequently punished for breaching these laws. Thus, only a minority of active ‘drug offenders’ are ever formally subjected to criminal sanctioning, the criminal label, its stigmatizing effects and the resultant collateral consequences. The current article analyses data from two studies on drug offenders – a sample of 26 users and a sample of 25 suppliers – who form part of the ‘silent majority’ of drug offenders whose offending behaviour goes largely unnoticed and unpunished. Both sets of actors are what we consider ‘law-abiding’ criminals insofar as their regular criminal transgressions are not reflected in the ways broader society, their immediate networks, nor they, view themselves. We argue that the perceived risks posed to their conventional commitments and roles ensure their careful management and subversion of behaviour and information that might otherwise be indicative of their drug offending. Yet, at the same time, we argue that these conventional roles provide sufficient protection that their crimes go unnoticed or, if detected, unpunished. Our conclusions support Mohammed and Fritsvold’s notion of the ‘silent majority’ that only a minority of those that use and supply illicit substances drug offenders are subject to the law, and the collateral consequences of a criminal and deviant label. We argue more research needs to be conducted with these hidden groups to help reduce the inequities, stigmas and stereotypes that befall the subsection of those who are routinely policed, sanctioned and studied.
Regular Polygon Detection as an Interest Point Operator for SLAM

We present a new interest point operator based on the regular polygon detector developed by Loy and Barnes [2004]. This operator finds square-like features as a basis for scene reconstruction and visual Simultaneous Localisation and Mapping (SLAM) from robot camera sequences. In this paper we show results from the application of this detector as an interest point operator on a robot camera sequence in an indoor office environment. The detector shows good results for non-trivial frame baselines.
Concept Based Query Enhancement in the ARCH Search Agent

The quality of the search experience has been an enduring problem for the World Wide Web. One of the well-known difficulties is the tendency of users to use short, under-specified and ambiguous queries, which tend to retrieve large amounts of irrelevant material. Traditional query expansion and relevance feedback approaches have been used to address this problem, but without as much success as these techniques have garnered in more restricted areas such as traditional IR collections. This paper presents ARCH, an interactive query formulation aid that is based on conceptual categories. The user’s query is reformulated to include categories that the user recognizes as important and exclude those that are not important. Unlike query expansion techniques, which might add lists of synonyms to increase recall, ARCH uses the domain knowledge inherent in Web-based classification hierarchies such as Yahoo to add just those terms likely to improve the match with the user’s intent. The goal of the system therefore is to meet the user’s information needs by closing the gap between the user’s stated query and the actual intent of the search. In this paper, we discuss the implementation of ARCH with a particular focus on the query enhancement mechanism. We also discuss our evaluation of the
High performance MPI design using unreliable datagram for ultra-scale InfiniBand clusters

High-performance clusters have been growing rapidly in scale. Most of these clusters deploy a high-speed interconnect, such as Infini-Band, to achieve higher performance. Most scientific applications executing on these clusters use the Message Passing Interface (MPI) as the parallel programming model. Thus, the MPI library has a key role in achieving application performance by consuming as few resources as possible and enabling scalable performance. State-of-the-art MPI implementations over InfiniBand primarily use the Reliable Connection (RC) transport due to its good performance and attractive features. However, the RC transport requires a connection between every pair of communicating processes, with each requiring several KB of memory. As clusters continue to scale, memory requirements in RC-based implementations increase. The connection-less Unreliable Datagram (UD) transport is an attractive alternative, which eliminates the need to dedicate memory for each pair of processes. In this paper we present a high-performance UD-based MPI design. We implement our design and compare the performance and resource usage with the RC-based MVAPICH. We evaluate NPB, SMG2000, Sweep3D, and sPPM up to 4K processes on an 9216-core InfiniBand cluster. For SMG2000, our prototype shows a 60% speedup and seven-fold reduction in memory for 4K processes. Additionally, based on our model, our design has an estimated 30 times reduction in memory over MVAPICH at 16K processes when all connections are created. To the best of our knowledge, this is the first research work that presents a high-performance MPI design over InfiniBand that is completely based on UD and can achieve near identical or better application performance than RC.
The Effects of Inhaled Albuterol in Transient Tachypnea of the Newborn

Purpose Transient tachypnea of the newborn (TTN) is a disorder caused by the delayed clearance of fetal alveolar fluid. β-adrenergic agonists such as albuterol (salbutamol) are known to catalyze lung fluid absorption. This study examined whether inhalational salbutamol therapy could improve clinical symptoms in TTN. Additional endpoints included the diagnostic and therapeutic efficacy of salbutamol as well as its overall safety. Methods From January 2010 through December 2010, we conducted a prospective study of 40 newborns hospitalized with TTN in the neonatal intensive care unit. Patients were given either inhalational salbutamol (28 patients) or placebo (12 patients), and clinical indices were compared. Results The duration of tachypnea was shorter in patients receiving inhalational salbutamol therapy, although this difference was not statistically significant. The duration of supplemental oxygen therapy and the duration of empiric antibiotic treatment were significantly shorter in the salbutamol-treated group. No adverse effects were observed in either treatment group. Conclusions Inhalational salbutamol therapy reduced the duration of supplemental oxygen therapy and the duration of empiric antibiotic treatment, with no adverse effects. However, the time between salbutamol therapy and clinical improvement was too long to allow definitive conclusions to be drawn. Further studies examining a larger number of patients with strict control over dosage and frequency of salbutamol inhalations are necessary to better direct the treatment of TTN.
Metrics suite for maintainability of eXtensible Markup Language web services

The eXtensible Markup Language (XML) web services are emerging as the de-facto mechanism for exchanging structured information between applications. The large popularity and acceptance of web services led the developers to adopt the best practices of web service implementation and to find the ways for managing and maintaining web services more effectively. Maintainability, one of the important factors, which affects the quality of XML web services, can be controlled by the proper software metrics that are specifically designed and developed for it. In this paper, we present a suite of metrics to evaluate the quality of the XML web service in terms of its maintainability. The present suite of metrics includes: data weight of a web service description language, distinct message ratio metric, message entropy metric and message repetition scale metric. All the proposed metrics have been evaluated theoretically and validated empirically. A comparative study with similar measures proves the worth of the metric suite.
Crystallization Papers Biological Crystallography Crystallization and Preliminary Crystallographic Analysis of an Acylphosphatase from the Hyperthermophilic Archaeon Pyrococcus Horikoshii

Acylphosphatases catalyse the hydrolysis of the carboxyl phosphate bond in metabolites such as acetyl phosphate, 1,3-bisphospho-glycerate, succinoyl phosphate and carbamoyl phosphate. In this study, acylphosphatase (91 residues) from the hyperthermophilic archaeon Pyrococcus horikoshii has been cloned, overexpressed, puri®ed and crystallized using the sitting-drop vapour-diffusion method using sodium formate as a precipitant at 289 K. The crystals belong to space group P3 2 21, with unit-cell parameters a = b = 85.65, c = 75.51 A Ê. The asymmetric unit contains two molecules of acylphosphatase, with a corresponding crystal volume per protein weight of 3.9 A Ê Da À1 and a solvent content of 68.6%. A data set diffracting to 1.6 A Ê resolution was collected from a single crystal at 100 K.
SIMPLE NON-EQUILIBRIUM THERMODYNAMICS APPLICATIONS TO POLYMER RHEOLOGY

We review here recent developments in non-equilibrium thermodynamics and their applications to rheology. In particular we review the application of the dissipative Hamiltonian formalism to incompressible, homogeneous and isothermal flows of flexible polymer systems. We show not only the advantages that have been brought up by the nonequilibrium thermodynamics approach but also exactly where the actual contributions are in combination from a variety of specific modeling examples ranging from simple, one-conformation models to most recent coupled multivariable examples. In all cases, special attention is paid to convey the physical significance of the models through a close association to a more detailed microscopic interpretation.
From information visualization to direct manipulation: extending a generic visualization framework for the interactive editing of large datasets

Today's generic data management applications such as accounting, CRM or logging and tracking software, rely on form and menu based interfaces. These applications take only marginal advantage of current graphical user interfaces. This is because the data they handle does not have intrinsic visual representations upon which direct manipulation principles can be used. This article presents how we have extended an Information Visualization framework with generic data manipulation functions. These new data editing capabilities are tuned to take advantage of the characteristics of each view. They enable us to generalize the direct manipulation mechanisms to address many abstract data manipulation needs. In this article we present five uses of the features we have implemented and deduce a general workflow applicable to a variety of contexts. The workflow comprises three steps and five editing actions. The steps are: adjust view, select, and edit. The editing actions are: edit a value or group of values, clone objects, remove objects, add attributes, and remove attributes. The workflow provides complete editing access to table and hierarchical data structures using particularly terse interaction methods. It defines a general data editing model that enables powerful data manipulation tasks without requiring end-user programming or scripting.
Online FOG Identification in Parkinson's disease with a time-frequency combined Algorithm

Parkinson's disease (PD) is a common degenerative neurological disorder. Freezing of Gait (FOG) is a significant symptom in PD. Sudden FOG causes balance disturbances and increases the risk of falls. An online approach for FOG identification is presented using MiMed-Pants and an online test software with a frequency-time combined algorithm. MiMed-Pants are washable jogging-trousers with integrated accelerometers. Eight Parkinson patients with different FOG severity used the MiMed-pants and walked following arbitrary instructions from a physician. FOG events were identified and recorded both by the online approach and by a physician. Results were compared with each other to determine the sensitivity of the developed algorithm. Using this wearable measurement device, FOG events could be identified without distraction of patients' attention.
Prediction of Protein-Protein Interaction Sites Using Support Vector Machines

Protein-protein interactions play an important role in various biological processes. Over the past few years, several studies have been made on protein interface and those results enable us to obtain massive data on various aspects of protein interface. The problem that we have to consider next is predicting the interaction sites on the protein surface. Although several prediction methods are developed, there is still room for improvement. The purpose of this study is to develop a reliable prediction system of protein-protein interaction sites from their three-dimensional structure.
Carotenoid Content in Organically Produced Wheat: Relevance for Human Nutritional Health on Consumption

In this study, 33 spring and winter wheat genotypes were analyzed for carotenoid content and composition. Investigated genotypes were divided into four genotype groups i.e., spelt, landraces, old cultivars and primitive wheat. The results showed a high level of variation among the genotypes in amount of carotenoids in the grain with high values (around 4 mg/Kg) especially in one of the genotypes—Öland 8. Lutein was the most common carotenoid in all the investigated genotypes, contributing 70%–90% of the carotenoids in the grain. Variation in carotenoid content and composition was found not only among genotypes, but also between genotype groups and wheat type, although there is a need to analyze more genotypes to confirm the differences found between groups and types. This study showed that 40% of the daily requirements of lutein can be achieved from the genotypes with the highest lutein content (Öland 8) produced using organic farming through the average human consumption of 200 grams of wheat per day. Furthermore, this study showed, by the use of principal component analyses, an opportunity to select genotypes combining high values of certain nutritional compounds. By a further breeding and commercial production of such genotypes, the nutritional value of wheat flour for human consumption can be improved.
Performance-Oriented Drilling Fluids Design System with a Neural Network Approach

Drilling fluids play a key role in the minimization of well bore problems when drilling oil or gas wells, usually the design of drilling fluids is depended on many experiments with experience. Rule-based and case-based reasoning drilling fluid system was designed with theory of expert system by some researchers. But it is very difficult to get to know and express precious relationship between drilling fluid formulation and its performance. Performance of drilling fluids can be measured with test device when drilling fluid is ready. A performance oriented drilling fluids design system is presented, with supervised artificial neural network algorithm to acquire knowledge by learning from experimental data. The system can be used to design drilling fluid according to specified performance. Experimental results show that drilling fluids designed by the system can satisfy specified performance.
Nonlinear Excitation Control for Transient Stability of Multi–Machine Power Systems using Structure–Preserving Models

Abstract The approach adopted in this paper for the problem of transient stability of multi-machine power systems sees the entire network as the (structure-preserving) interconnection of the network components, described by well known models. These structure-preserving models preserve the identity of the network components and allow for a more realistic treatment of the loads. Our main contribution is the explicit computation of a control law which provides transient stabilization, i.e , prevents the system from loss of synchronism after a large perturbation. The theory is illustrated by means of simulation on a 3-machine power system.
Process Mining Online Assessment Data

Traditional data mining techniques have been extensively applied to find interesting patterns, build descriptive and predictive models from large volumes of data accumulated through the use of different information systems. The results of data mining can be used for getting a better understanding of the underlying educational processes, for generating recommendations and advice to students, for improving management of learning objects, etc. However, most of the traditional data mining techniques focus on data dependencies or simple patterns and do not provide a visual representation of the complete educational (assessment) process ready to be analyzed. To allow for these types of analysis (in which the process plays the central role), a new line of data-mining research, called process mining, has been initiated. Process mining focuses on the development of a set of intelligent tools and techniques aimed at extracting process-related knowledge from event logs recorded by an information system. In this paper we demonstrate the applicability of process mining, and the ProM framework in particular, to educational data mining context. We analyze assessment data from recently organized online multiple choice tests and demonstrate the use of process discovery, conformance checking and performance analysis techniques.
Refinement of Feature Terms and Improvement of Classification Accuracy on Multilingual Text Categorization Using Character N-gram

In our previous paper, we proposed a new classification technique called the Frequency Ratio Accumulation Method (FRAM). This is a simple technique that adds up the ratios of term frequency among categories. However, in FRAM, the use of feature terms is unlimited. Then, we adopt Character N-gram as feature terms improving the particularity of FRAM. That is to say, the proposed method is language-independent because it does not depend on grammatical knowledge peculiar to the language by using Character N-gram. Therefore, we can classify multi-language into some categories using only one program. In the present paper, we will refine the DB of the feature term set using mutual information and frequency ratio, and improve the classification accuracy. Next, the proposed method is evaluated by performing several experiments. In these experiments, we classify newspaper articles from English Reuters-21578 that provides benchmark data in automatic text categorization, Japanese CD-Mainichi 2002 and Chinese China Times 2005 using FRAM. As a result, we show the effectiveness of refining DB of feature terms. Specifically, the macro-averaged F-measure of the proposed method is 92.3% for Reuters-21578.