Miracle-dz/UniFAR-FTUs huggingface dataset:
An infrastructure for tractable verification of JavaScript programs

The highly dynamic nature of JavaScript, coupled with its intricate semantics, makes the understanding and development of correct JavaScript code notoriously difficult. We believe that logic-based verification has much to offer to JavaScript. In particular, separation logic has been successfully applied to verification tools for static languages. However, it has hardly been used to reason about programs written in dynamic languages in general, and JavaScript in particular. This thesis presents JaVerT, a semi-automatic JavaScript Verification Toolchain for tractable logicbased verification of JavaScript programs. JaVerT verifies JavaScript programs annotated with function specifications in the form of preand postconditions, loop invariants, and annotations for the folding and unfolding of user-defined predicates. We design natural JavaScript abstractions that allow JavaScript developers wishing to verify JavaScript programs to not think about almost any internals of the language. The actual process of how JaVerT verifies the given annotated JavaScript program is not visible to the JavaScript developer, and is achieved using our JSIL verification infrastructure. This infrastructure includes: JSIL, a simple goto language, suitable for logic-based verification of JavaScript; JSIL Logic, a sound separation logic for JSIL; and JSIL Verify, a semi-automatic verification tool, based on JSIL Logic. The joining ingredient of JaVerT is a JavaScript frontend to our JSIL verification infrastructure, tightly connecting programs and reasoning at the level of JavaScript to programs and reasoning at the level of JSIL. This frontend includes a well-tested compiler from JavaScript code to JSIL code, a translator from JavaScript Logic to JSIL Logic, and well-tested JSIL reference implementations and verified axiomatic specifications of the JavaScript internal functions. We demonstrate the feasibility of JaVerT to specify and verify simple data structure libraries, illustrating our ideas using an implementation of a priority queue. Our given specifications ensure prototype safety of library operations, in that they describe the conditions under which these operations exhibit the desired behaviour.
Control optimization for a low-cost flywheel module

This paper describes a modeling and design approach in finding the optimal controller for a low-cost hybrid drive train on a pre-defined driving cycle. The hybrid drive train is characterized by a small energy capacity (flywheel) and discrete shifts between operation modes, due to the use of clutches. The main design criterion, is the minimization of the overall fuel consumption, whereas constraints are defined to describe the systems dynamics, kinematics and constraints. In addition, comfort criteria are defined as constraints, to avoid uncomfortable driving conditions. These criteria are used to find the optimal sequence of driving modes and generated engine torque over a defined driving cycle. Simulations show a fuel saving potential of 22% to 39%, dependent on the chosen driving cycle.
Human Papillomavirus (HPV) Vaccine Effectiveness and Potential Herd Immunity for Reducing Oncogenic Oropharyngeal HPV-16 Prevalence in the United Kingdom: A Cross-sectional Study

Abstract Background Oropharyngeal cancer incidence is rapidly rising due to human papillomavirus (HPV) type 16 infection. The dearth of data on effectiveness of national female-only vaccination programs in preventing oral HPV infection and potential herd immunity in unvaccinated males has resulted in considerable controversy regarding the need to vaccinate males, especially in countries with high female vaccination coverage. Methods Subjects aged 0–65 years undergoing tonsillectomy for nonmalignant indications were recruited in 6 hospitals in the United Kingdom. Oral samples were collected as follows: oral rinse, tongue base, and pharyngeal wall brushes, then tonsil tissue (tonsillectomy). Vaccination data were obtained from regional health authorities. All samples were centrally tested for HPV DNA by polymerase chain reaction. Results Of 940 subjects, 243 females and 69 males were aged 12–24 years (median age, 18.6 years), with 189 (78%) females and no males vaccinated against HPV. Overall, oropharyngeal HPV-16 prevalence was significantly lower in vaccinated versus unvaccinated females (0.5% vs 5.6%, P = .04). In contrast, prevalence of any oropharyngeal HPV type was similar in vaccinated and unvaccinated females (19% vs 20%, P = .76). Oropharyngeal HPV-16 prevalence in unvaccinated males was similar to vaccinated females (0% vs 0.5%, P > .99), and lower than unvaccinated females (0% vs 5.6%, P = .08). Conclusions Our findings indicate that the UK female-only vaccination program is associated with significant reductions in oropharyngeal HPV-16 infections. These are also the first data to suggest potential herd immunity from female-only vaccination against oropharyngeal HPV infection in contemporaneously aged males.
Research on XIDM-Based Schema Mapping in Multidatabase Systems

Establishing schema mappings among different schemas is a key to solve the problem of schema heterogeneity in multidatabase systems Since an integrated data model suitable for the transformation is the basis of schema mappings, an XML based integrated data model (XIDM) is presented as the common data model to integrate multiple heterogeneous data sources such as database tables, files and web documents in a multidatabase system An XIDM based approach of schema mapping among global schemas, export schemas, and local schemas is also given Then, the illustration and implementation of global and local mappings in multidatabase prototype—Panorama system are shown, and finally, the performance evaluation and analysis of XIDM based schema mapping are also discussed
A CBR approach to Behaviour-Based Navigation for an Autonomous Mobile Robot

This paper presents a new CBR navigation scheme based on three behaviours: wall following, corridor following and door crossing. The system switches among CBR behaviours depending on a local grid built around the robot from sonar sensor readings. The main advantage of the proposed system is that it can easily adapt to any robot and environment, learning, both by training and by its own experience. The method has been successfully tested in real environments with a Pioneer robot equipped with 8 frontal sonar sensors.
Convolutional Neural Networks for Raw Speech Recognition

State-of-the-art automatic speech recognition (ASR) systems map the speech signal into its corresponding text. Traditional ASR systems are based on Gaussian mixture model. The emergence of deep learning drastically improved the recognition rate of ASR systems. Such systems are replacing traditional ASR systems. These systems can also be trained in end-to-end manner. End-to-end ASR systems are gaining much popularity due to simpli- fied model-building process and abilities to directly map speech into the text without any predefined alignments. Three major types of end-to-end architectures for ASR are atten- tion-based methods, connectionist temporal classification, and convolutional neural network (CNN)-based direct raw speech model. In this chapter, CNN-based acoustic model for raw speech signal is discussed. It establishes the relation between raw speech signal and phones in a data-driven manner. Relevant features and classifier both are jointly learned from the raw speech. Raw speech is processed by first convolutional layer to learn the feature representation. The output of first convolutional layer, that is, intermediate representation, is more discriminative and further processed by rest convolutional layers. This system uses only few parameters and performs better than traditional cepstral fea- ture-based systems. The performance of the system is evaluated for TIMIT and claimed similar performance as MFCC.
Help on the spot: online assistance for writing scientific English

Publishing in English represents a major challenge for non-native speakers (NNS) of English since they face the dual requirements of producing good quality research and presenting it in good quality English. Many NNS researchers learn how to write scientific English in a haphazard way, and few receive specific formal training in this field. This leads to misunderstandings on their part about how to write scientific English and what actually constitutes a reliable model to be imitated. Guidance exists in the form of style manuals and published writing courses, but these may prove unwieldy and too time-consuming to consult. We therefore sought to develop a dragand droppable form of online assistance in which NNS researchers’ initial drafts are processed didactically as models.
Using Program Slicing Technique to Reduce the Cost of Software Testing

Systems of computers and their application in the lives of modern human beings are vastly expanding. In any kind of computer application, failure in computer systems can lead to a range of financial and mortal losses. Indeed, the major origin of software failure can be located in designing or implementing software. With regard to these statistics, 30% of the software projects have been prosperous and successful. The proposed method is intended to reduce the cost and time of testing and it focuses on enhancing the efficiency of software testing methods. In this paper, we investigated the effect of slicing techniques on the reduction rate of testing cost and time. The results of experiments show that we can cover a large number of program instructions, branches and paths by a small number of test cases in the sliced program.
Effect of multi-functional UPFC upon power system oscillation stability

This paper presents the analysis of the interaction between the damping and other control functions of a unified power flow controller (UPFC) installed in power systems. A case of negative interaction between the UPFC damping control and voltage control of the DC link capacitor is studied and then an algorithm for their co-ordinated design is suggested. An example is given in the paper to demonstrate the analytical results and the success of the co-ordinated design.
Design of Data-centroid Radial Basis Function Neural Network with Extended Polynomial Type and Its Optimization

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.
A new Strategy to Improve the Pathfinding in Wireless ad-hoc Networks

In link-state computer networks it is usual that every node knows the topology of the entire network and can make the routing decisions based on that. One of the protocols in use is OLSR. The OLSR routing protocol implements the algorithm of Dijkstra to find the shortest paths from the nodes to the gateways of the network. For that purpose, Dijkstra’s algorithm has to be executed k times, while k is the number of gateways. In this paper, we present a strategy that generalizes all gateways to one gateway. We call this the General Gateway Strategy. Using this, the Algorithm of Dijkstra has to be executed only one time, which significantly increases the performance of the overall algorithm to find the shortest paths to the gateways. Keywords-Wireless mesh networks; Ad hoc networks; Wi-Fi; Shortest path problem.
2.45GHz CMOS Up-conversion Mixer & LO Buffer Design

A 2.45GHz double-balanced modified Gilbert-type CMOS up-conversion mixer design is introduced, where the PMOS current-reuse bleeding technique is demonstrated to be efficient in improving conversion gain, linearity, and noise performance. An LO buffer is included in the mixer design to perform single-ended to differential conversion of the LO signal on chip. Simulation results of the design based on careful modeling of all active and passive components are examined to explain in detail about the characteristic improvement and degradation provided by the proposed design. Two kinds of chips were fabricated using a standard 0. 35µm CMOS process, one of which is the mixer chip without the LO buffer and the other is the one with it. The measured characteristics of the fabricated chips are quite excellent in terms of conversion gain, linearity, and noise, and they are in close match to the simulation results, which demonstrates the adequacy of the modeling approach based on the macro models for all the active and passive devices used in the design. Above all the benefits provided by the current-reuse bleeding technique, the improvement in noise performance seems most valuable.
Research on Influencing Factors of Usage Intension to Use Mobile Intelligent Wearable Device

Although the rise of mobile intelligent wearable devices, however it is still in the primary stage and consumers have some doubts about its network stability and device stability. Therefore, what factors may affect the willingness and behavior of consumers to wear mobile intelligent devices will become the key problem to be solved by mobile intelligent wearable device manufacturers. This study cites a decision making and evaluation laboratory (DEMATEL) to comprehensively analyze the influence between factors. The advantage is that not only a small amount of samples are needed, but also the influence degree between the factors can be analyzed from the influence relationship between the factors, thereby obtaining the management decision direction.
A research on wireless sensor networks’ node positioning mechanism based on Narrowband Internet of Things data linking

NB-IoT (Narrowband Internet of Things), as a part of new-generation cellular communication technology, leads an innovation in wireless sensor networks. It pushes wireless sensor networks to be applied in more application fields. NB-IoT Release 14 has got the ability of positioning from cellular network service. To solve the positioning problem of new wireless sensor networks based on NB-IoT, instead of static three-point measuring way DV-HOP (distance vector hop), NB-IoT connecting point node is deployed to work as an anchor node that moves among three different places and receives signals from all other unknown nodes in the cluster. Based on the DV-HOP algorithm, in this article a topological structure for new-generation wireless sensor networks is built and the NBIOT-DVHOP mechanism combining the NB-IoT cellular network positioning ability and the DV-HOP algorithm is proposed. According to the simulation on the MATLAB platform, the effectiveness of this mechanism is verified and the deviation rate of each point from the relative position is presented. The deviation rate is related to the communication radius and the numbers of unknown nodes and anchor nodes. The simulation results can support the next step of research in NB-IoT-based wireless sensor networks, especially in data collection and fast positioning of unknown sensor nodes.
Research on Parallel Rasterization Algorithm Based on Containment Test Method

With the rapid development of earth observation technology and dramatic expansion in data size,rapid rasterization for vector data has become an important issue in GIS(Geographic Information System)field.In this paper,the parallel computing technology is applied into the study of rasterization and a parallel rasterization algorithm is proposed based on containment test method.The primary issues in rasterization,including vector data decomposition and different cases of raster cells on the boundaries of polygons,are also studied.A land use data with large volume is used in experiments.The accuracy and efficiency of the proposed parallel algorithm are studied.Results show that the speedup increases dramatically when the number of processes is less than the number of cores and reaches a plateau when more processes are used.In addition,the parallel efficiency is closely related with the data decomposition strategy and data storage method.An appropriate data decomposition strategy can improve the parallel efficiency.
An Analysis of the Impact of Age and Proximity of Death on Health Care Costs in Ireland

Research has shown that older individuals are far more likely to avail of health care and there is concern in a number of countries that the trend toward population ageing may mean that health care expenditures increase to unsustainable levels. However, there is a growing body of evidence that the approach of death rather than age per se may be the main determinant of health care costs. Previous analyses of the relationship between proximity to death and costs have used rare longitudinal data on costs and whether died and none have used a national sample. In this paper we use a more commonly found data type ? a national panel survey to show that proximity to death is indeed a more significant predictor of expenditure on GP and hospital services than age. Using random effects panel models we show that there is a significant gradient in costs as death approaches. Controlling for proximity to death there is no age gradient in costs. This conclusion remains unchanged adjusting for differential health inpatient costs across age groups. In fact, adjustment steepens the gradient in costs as death approaches.
A Hybrid Fusion Algorithm for Integrated INS/UWB Navigation and Its Application in Vehicle Platoon Formation Control

The vehicle positioning technology is playing an important role in Cooperative Vehicle Infrastructure System (CVIS). In those single positioning modes, the precision of wireless positioning is greatly affected by the environment. However, the accumulative errors of inertial navigation system (INS) and positioning can not be eliminated. In this paper, a hybrid fusion algorithm based on UWB (Ultra Wide Band) and INS is proposed and applied to the vehicle platoon formation control system. The hybrid fusion algorithm can overcome the shortcomings of non-line-of-sight (NLOS) problem in UWB positioning algorithm and accumulative errors of INS. This algorithm can also significantly enhance positioning accuracy in vehicle platoon formation control. The application scene consists of three types: road scene, junction scene and parking lot scene. The hybrid fusion algorithm can be used in combination with different scenarios to ensure the smooth operation of the vehicle platoon. Keywords—UWB (Ultra Wide Band); INS (inertial navigation system); hybrid fusion algorithm; vehicle platoon formation control
Practice‐based evidence: benchmarking NHS primary care counselling services at national and local levels

There are a number of problems for evidence-based practice (EBP) including limited generalizability of efficacy research results, the consequent lack of confidence in the relevance of such research, and the conceptual distance of most practitioners from the research process. The result is that EBP, although sound in principle, often fails to achieve its aim of improving practice. Practice-based evidence (PBE) provides a complementary bridge for the gap between research and practice to offset some of these problems, promoting collaboration between mental health services and academic institutions. This paper presents the initial results of such a collaboration via three phases: (1) the development of a referential database for primary care counselling services, (2) ‘practitioner-friendly’ feedback on grouped data to services, and (3) the combination of the two to build an evidence base for work with ethnic minorities—an area in which research trials are not well adapted to provide much evidence. Copyright © 2003 John Wily & Sons, Ltd.
Reduced-Intensity Chemotherapy in Patients With Advanced-Stage Hodgkin Lymphoma

Abstract The international, randomized phase 3 HD15 trial established 6xeBEACOPP as standard therapy for patients with newly diagnosed advanced-stage Hodgkin lymphoma (HL) within the German Hodgkin Study Group (GHSG). We performed a follow-up analysis to assess long-term efficacy and safety of this approach. Between 2003 and 2008, 2182 patients aged 18 to 60 years were recruited and randomized in a 1:1:1 ratio between 8 or 6 cycles of eBEACOPP or 8 cycles of the dose-dense BEACOPP-14 regimen, each followed by 30 Gy radiotherapy in case of positron emission tomography (PET)-positive residual lesions ≥2.5 cm. The study aimed at demonstrating non-inferiority regarding efficacy of the 2 experimental arms on a significance level of 2.5% each. The intention-to-treat analysis comprised 2126 patients with a median follow-up of 102 months. Ten-year progression-free survival was 81% (97.5% CI 77–85) with 8xeBEACOPP, 84% (80–87) with 6xeBEACOPP, and 84% (80–87) with 8xBEACOPP-14; the non-inferiority margin of 1.51 for the hazard ratio (HR) could be excluded for both comparisons (6xeBEACOPP, HR = 0.7, 97.5% CI 0.5–1.0; 8xBEACOPP-14, HR = 0.9, 97.5% CI 0.7–1.2). Overall survival at 10 years was 88% (85–91), 90% (88–93), and 92% (89–94), respectively. A total of 142 second malignancies corresponding to 10-year cumulative incidences of 10%, 7%, and 7% and standardized incidence ratios of 4.3, 2.5, and 2.8 were reported for 8xeBEACOPP, 6xeBEACOPP, and 8xBEACOPP-14, respectively. This updated analysis of the HD15 trial thus confirms the efficacy and reports on the long-term safety of a shortened first-line chemotherapy consisting of 6xeBEACOPP followed by PET-guided radiotherapy in advanced-stage HL.