Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a Comprehensive Test Suite for Detectors of Design Patterns

Detection of design patterns is an important part of reverse engineering. Availability of patterns provides for a better understanding of code and also makes analysis more efficient in terms of time and cost. In recent years, we have observed a continual improvement in the field of automatic detection of design patterns in source code. Existing approaches can detect a fairly broad range of design patterns, targeting both structural and behavioral aspects of patterns. However, it is not straightforward to assess and compare these approaches. There is no common ground on which to evaluate the accuracy of the detection approaches, given the existence of variants and specific code constructs used to implement a design pattern. We propose a systematic approach to constructing a comprehensive test suite for detectors of design patterns. This approach is applied to construct a test suite covering the Singleton pattern. The test suite contains many implementation variants of these patterns, along with such code constructs as method forwarding, access modifiers, and long inheritance paths. Furthermore, we use this test suite to compare three detection tools and to identify their strengths and weaknesses.
Local Identification of Nonparametric and Semiparametric Models Citation

The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. In parametric models a sufficient condition for local identification is that the vector of moment conditions is differentiable at the true parameter with full rank derivative matrix. We show that additional conditions are often needed in nonlinear, nonparametric models to avoid nonlinearities overwhelming linear effects. We give restrictions on a neighborhood of the true value that are sufficient for local identification. We apply these results to obtain new, primitive identification conditions in several important models, including nonseparable quantile instrumental variable (IV) models, single-index IV models, and semiparametric consumption-based asset pricing models. provided financial support for this paper. Helpful comments were provided by a co-editor, three anonymous referees,
Clinical Features of Suicide Attempts After Traumatic Brain Injury

This study documents demographic, clinical and temporal parameters for suicide attempts after traumatic brain injury (TBI). Clinical interviews and a medical file review were conducted with an outpatient sample (N = 172), identifying 45 clients (26.2%) who had collectively made a lifetime total of 80 suicide attempts. Data were collected on postinjury psychopathology, current hopelessness, and suicide ideation, as well as historical data about the attempts. The sample (N = 43, missing data N = 2) had a lifetime prevalence of 1.86 attempts, with 19 clients (44.2%) making repeat attempts. The majority (70%) of the attempts were made postinjury. Medical attention was provided in 60.7% of attempts. The odds ratio found that respondents with a comorbid postinjury history of psychiatric/emotional disturbance and substance abuse were 21 times more likely to have made an attempt post-TBI compared with respondents with no such history. The findings can inform suicide prevention initiatives among people with TBI.
An Experimental Study of a Hybrid Entity Recognition and Linking System

We present an experimental study of the performance of a hybrid semantic and linguistic system for recognizing and linking entities from formal and informal texts. In the current literature, systems are generally tailored to one or a few types of textual documents (e.g. narrative texts, newswire articles, informal text such as microposts). In contrast, we assess the performance of a hybrid approach that adapts the entity extraction, recognition and linking process to the type of document being analyzed. The hybrid system relies on POS taggers, gazetteers and Twitter user account dereferencing modules to extract entities, NER modules to recognize and type entities and entity popularity, string distance measures and scoring functions to disambiguate entities by ranking potential link candidates. The evaluation results show the robustness of our proposed approach in terms of text-independence compared to the current state-of-the art.
Health literacy and functional health status among older adults.

BACKGROUND Individuals with limited health literacy have less health knowledge, worse self-management skills, lower use of preventive services, and higher hospitalization rates. We evaluated the association between health literacy, self-reported physical and mental health functioning, and health-related activity limitations among new Medicare managed care enrollees. METHODS A cross-sectional survey of 2923 enrollees was conducted in Cleveland, Ohio; Houston, Tex; Tampa, Fla; and Fort Lauderdale-Miami, Fla. Health literacy was measured using the short form of the Test of Functional Health Literacy in Adults. We used outcome measures that included scores on the physical and mental health functioning subscales of the Medical Outcomes Study 36-Item Short-Form Health Survey, difficulties with instrumental activities of daily living and activities of daily living, and limitations because of physical health and pain. RESULTS After adjusting for the prevalence of chronic conditions, health risk behaviors, and sociodemographic characteristics, individuals with inadequate health literacy had worse physical function (67.7 vs 78.0, P<.001) and mental health (76.2 vs 84.0, P<.001) than individuals with adequate health literacy. Individuals with inadequate health literacy were more likely to report difficulties with instrumental activities of daily living (odds ratio [OR], 2.25; 95% confidence interval [CI], 1.74-2.92) and activities of daily living (OR, 2.83; 95% CI, 1.62-4.96), limitations in activity because of physical health (OR, 1.79; 95% CI, 1.39-2.32), fewer accomplishments because of physical health (OR, 1.90; 95% CI, 1.48-2.45), and pain that interferes with normal work activities (OR, 2.01; 95% CI, 1.46-2.77). CONCLUSION Among community-dwelling older adults, inadequate health literacy was independently associated with poorer physical and mental health.
Discovering Organizational Correlations from Twitter

Organizational relationships are usually very complex in real life. It is difficult or impossible to directly measure such correlations among different organizations, because important information is usually not publicly available (e.g., The correlations of terrorist organizations). Nowadays, an increasing amount of organizational information can be posted online by individuals and spread instantly through Twitter. Such information can be crucial for detecting organizational correlations. In this paper, we study the problem of discovering correlations among organizations from Twitter. Mining organizational correlations is a very challenging task due to the following reasons: a) Data in Twitter occurs as large volumes of mixed information. The most relevant information about organizations is often buried. Thus, the organizational correlations can be scattered in multiple places, represented by different forms, b) Making use of information from Twitter collectively and judiciously is difficult because of the multiple representations of organizational correlations that are extracted. In order to address these issues, we propose Multi-CG (Multiple Correlation Graphs based model), an unsupervised framework that can learn a consensus of correlations among organizations based on multiple representations extracted from Twitter, which is more accurate and robust than correlations based on a single representation. Empirical study shows that the consensus graph extracted from Twitter can capture the organizational correlations effectively.
‘We want to be parents like everybody else’: stories of parents with learning disabilities

Objectives This project represents a unique collaboration between creative and research processes using an inclusive qualitative methodology. Method Semi-structured interviews with five mothers and three fathers with learning disabilities were led by learning disabled researchers, and thematic analysis conducted with input from people with learning disabilities. Results Five main themes are presented; (1) subjective experiences of becoming parents, (2) perceptions that other people assume people with learning disabilities are incompetent parents, resulting in a need to prove worthiness, (3) experiences of services, (4) overcoming ‘knock-backs’ and (5) support for the rights of other parents. An additional subgroup analysis is presented: fathers feel ‘left out’. Conclusion Parents felt criticized by others, who they felt questioned their competence as parents unfairly by comparison to those without learning disabilities. The collaboration between academic research and an inclusive theater group allowed dissemination of parents’ stories to wider public, and professional, audiences through creative performances.
AC–DC–AC Three-Phase Converter Based on Three Three-Leg Converters Connected in Series

A unidirectional ac-dc-ac three-phase dc-link converter is proposed in this paper. It is composed of three unidirectional ac-dc-ac three-leg converters. The three-leg converter is composed of a noncontrolled leg, two controlled legs, and a dc-link. A suitable model and control strategy of the system, including a synchronization method, are proposed. The synchronization method, associated with the pulse width modulation (PWM) strategy, imposes that the grid currents and load voltages have the same phase angle of the converter voltages. This method ensures sinusoidal grid currents and mitigate the zero-crossing distortions normally caused by the use of diodes. Simulation and experimental results are also presented for validation purposes.
Response of European sea bass (Dicentrarchus labrax) to graded levels of methionine (total sulfur amino acids) in soya protein-based semi-purified diets

The dietary methionine (Met) and total sulfur amino acid (TSAA) requirements of European sea bass (Dicentrarchus labrax) (initial body weight 13·4 (sd 0·2) g) were estimated in a 12-week dose–response experiment. Seven isonitrogenous (7·6 % DM) and isoenergetic (gross energy, 21·2 MJ/kg DM) diets, based on soya protein and crystalline l-amino acids containing graded levels of l-Met (1·6–16·2 g/kg) at a constant cysteine (4 g/kg) level and a fish meal-based diet, were fed each to triplicate groups of fifty fish kept in 250 litre tanks in a thermoregulated (23 ± 0·5°C) seawater system. The Met and TSAA-deficient diet resulted in higher mortality, impaired feed intake and growth relative to the other treatments (P < 0·01). No signs of lens opacity due to limiting Met intake were observed and no feed intake or growth depression occurred at the highest level of dietary TSAA. Met and TSAA requirements for optimal N deposition or weight gain as fitted with the broken-line model resulted in estimated values of 8·0 and 12·0 g/kg diet (for example, 1·8 and 2·7 % dietary protein) and 9·1 and 13·1 g/kg diet (for example, 2·0 and 3·0 % dietary protein), respectively. Plasma levels of Met, homocysteine and cysteine increased in response to excess dietary TSAA, corroborating requirement estimates from growth data. N gain resulted in a linear function of TSAA consumption at marginal Met (TSAA) intake. The TSAA intake needed to maintain N balance resulted in a value of 20·0 mg TSAA/kg average body weight0·75 per d, which represents 23 % of the total (maintenance+accretion) requirement.
In unity there is strength: Showcasing a unified big data platform with MapReduce Over both object and file storage

Big Data platforms often need to support emerging data sources and applications while accommodating existing ones. Since different data and applications have varying requirements, multiple types of data stores (e.g. file-based and object-based) frequently co-exist in the same solution today without proper integration. Hence cross-store data access, key to effective data analytics, can not be achieved without laborious application re-programming, prohibitively expensive data migration, and/or costly maintenance of multiple data copies. We address this vital issue by introducing a first unified big data platform over heterogeneous storage. In particular, we present a prototype joining Apache Hadoop MapReduce with OpenStack's open-source object store Swift and IBM's cluster file system GPFSTM. A sentiment analysis application using 3 months of real Twitter data is employed to test and showcase our prototype. We have found that our prototype achieves 50% data capacity savings, eliminates data migration overhead, offers stronger reliability and enterprise support. Through our case study, we have learned important theoretical lessons concerning performance and reliability, as well as practical ones related to platform configuration. We have also identified several potentially high-impact research directions.
Influence of Body Size on Dietary Nutrition of White-Tailed Deer Odocoileus virginianus

Abstract Intraspecific competition is one of the major factors that can have an effect on the resources utilized within a habitat. Differences in diet quality of selected forage have been noted in size-dimorphic ungulates. However, on an intraspecific basis, data demonstrating a body size influence on diet quality are lacking. We examined diet quality across a range of body masses (14–76 kg) in white-tailed deer Odocoileus virginianus (n = 108) in a 2,628-ha enclosure at Kerr Wildlife Management Area, Kerr County, Texas, USA. The quality of the diet consumed was determined by crude protein, acid detergent fiber, and neutral detergent fiber content of digesta in the rumen–reticulum. Results indicated that in relation to body mass, the ratio of crude protein to acid detergent fiber was greater for smaller bodied white-tailed deer. By consuming a diet higher in crude protein than did large bodied individuals, small-bodied individuals should meet their high mass-specific metabolic demands more efficiently.
Deep Extreme Feature Extraction: New MVA Method for Searching Particles in High Energy Physics

In this paper, we present Deep Extreme Feature Extraction (DEFE), a new ensemble MVA method for searching $\tau^{+}\tau^{-}$ channel of Higgs bosons in high energy physics. DEFE can be viewed as a deep ensemble learning scheme that trains a strongly diverse set of neural feature learners without explicitly encouraging diversity and penalizing correlations. This is achieved by adopting an implicit neural controller (not involved in feedforward compuation) that directly controls and distributes gradient flows from higher level deep prediction network. Such model-independent controller results in that every single local feature learned are used in the feature-to-output mapping stage, avoiding the blind averaging of features. DEFE makes the ensembles 'deep' in the sense that it allows deep post-process of these features that tries to learn to select and abstract the ensemble of neural feature learners. With the application of this model, a selection regions full of signal process can be obtained through the training of a miniature collision events set. In comparison of the Classic Deep Neural Network, DEFE shows a state-of-the-art performance: the error rate has decreased by about 37\%, the accuracy has broken through 90\% for the first time, along with the discovery significance has reached a standard deviation of 6.0 $\sigma$. Experimental data shows that, DEFE is able to train an ensemble of discriminative feature learners that boosts the overperformance of final prediction.
Long-term potentiation in the hippocampus using depolarizing current pulses as the conditioning stimulus to single volley synaptic potentials

The conditions responsible for the associative properties of long-term potentiation (LTP) were examined in the CA1 region of the hippocampal slice preparation. Intracellularly recorded EPSPs resulting from single- volley stimulation at low frequency (0.15–0.1 Hz) in the stratum radiatum or oriens were paired with depolarizing current pulses (50–100 msec) injected through the recording microelectrode. It is shown that these EPSPs, when paired with pulses of sufficient magnitude, become potentiated. This potentiation generally reached a peak after 20–30 pairing events and could outlast the conditioning period by more than 1 hr. It was specific to the paired input, was blocked by 2-amino-5- phosphonovalerate (APV) and was largely blocked by prior homosynaptic tetanization (and vice versa). In experiments performed with picrotoxin (PTX) in the bath, EPSPs were potentiated using 2–4 nA current pulses, with somewhat higher values in normal solution. The effective current pulses, in both normal and PTX solution, produced a repetitive spike discharge of 7–11 spikes (per 100 msec), and within this range, higher frequencies were associated with larger potentiations. However, since similar degrees of EPSP potentiation were observed following blockade of spike activity by intracellular QX-314, spike activity was not the primary conditioning factor. For the potentiation to appear, the EPSP had to occur together with the current pulse or precede it by less than about 100 msec. No potentiation was observed when the EPSP immediately succeeded the pulse. The results suggest that the cooperativity aspect of LTP is related to a need for sufficient postsynaptic depolarization. (ABSTRACT TRUNCATED AT 250 WORDS)
Analysis of User Behavior for Web Search Success Using Eye Tracker Data

Web log data has been the basis for analyzing user query session behavior for a number of years, but it has several important shortcomings. The main one being that we do not really know what the user is doing - is s/he looking at the screen or doing something else? We have conducted an Eye-Tracking study to analyze user behavior when searching the web and looking for specific information on results and content pages. The goal is to obtain more precise information about the search strategy of the user. Which characteristics make the difference between successful and unsuccessful searches? This research presents results focusing on the number of formulated queries by session, documents clicked, the fixation durations on the documents, and the distribution of the attention in the different areas of the screen, among other aspects.
Software Tools for the Specification Language LOTOS

ion facilities and modularity. In order to be able to suppress irrelevant detail, to decompose a specification into meaningful components, and to make a specification analysable and readable it is essential that an FDT offers these facilities. A good structure also provides the framework for analysis of specifications. 1.2. 2. Examples of Specification Languages Automata theories. Finite state machines (FSM) can be used to describe an input/output function: each input generates a state transition and each state transition can generate an output. For the description of protocol systems finite state machines are usually extended with variables and queues. This technique is the basis for one of the FDTs employed by ISO (Estelle) for the work on OSI [ISO1986]. Another example is Argos [Holzmann1987]. In this approach there is a two level structure imposed on specifications, the first one being the interconnection of modules by queues and the second one being the FSMs themselves. Because of the potentially infinite queue contents, the composition of two modules is no longer a FSM, which implies that the model changes under parallel composition. Petri-nets. Petri-nets [Petri1962] are one of the oldest models for communicating systems. A Petri-net is a directed graph with two types of nodes: places and transitions. The state of a Petri-net is represented by a set of tokens that is distributed over the places. There are input arcs, leading from places (the input places) to transitions, and output arcs, leading from transitions to places. Transitions represent the possible actions of a process. These actions can only occur if each of the input places contains at least one token. When such a transition occurs (is fired), a token is removed from each input place and a token is added to each output place. Because the state is distributed over the net, Petri-nets are a faithful model of true parallelism (as opposed to arbitrary interleaving). The drawbacks of this technique are the lack of abstraction mechanisms (a component of a Petri-net cannot be a Petri-net), the notation (graphs), and the lack of a representation of data structures. Chapter
Design and Characterization of a Three-Phase Brushless Exciter for Aircraft Starter/Generator

This paper evaluates a three-phase ac main exciter (ME) for a wound-field synchronous aircraft starter-generator capable of operating in both starting and generating modes. The research has been based around a 225-kVA generator utilizing the existing single-phase ME hardware. Initially, a reconfiguration of the existing single-phase unit into a three-phase one has been carried out. Subsequently, an optimization of the ME stator has been performed. The hardware evaluations have been performed in parallel to the development of design methodologies suitable for future starter/generator design. The three-phase ac ME design needs to satisfy the required current output at both start and generate modes with minimum input voltampere rating of the inverter required to drive the ME. The ME's output capabilities have been predicted in all operating conditions using a computationally efficient combination of 3-D finite-element models together with a lumped-parameter circuit approach. The theoretical findings from the analyses have been validated on a prototype ME, confirming that the three-phase ac ME is capable of generating the required current output in both operating modes. The developed modeling system allowed for the identification of the ME's optimal operating points with regard to the minimum input apparent power (in voltamperes) at the required output power and a methodology for the accurate and computationally efficient evaluation of future starter/generator designs.
How the food, beverage and alcohol industries presented the Public Health Responsibility Deal in UK print and online media reports

Abstract The Public Health Responsibility Deal (RD) in England is a public–private partnership between government, industry and other stakeholders aiming to improve public health in four key areas: food, alcohol, health at work and physical activity. Wider literature shows that industry engages in framing of public health policy problems, solutions and its role in solutions that is favourable to its interests. As part of an evaluation of the RD, we conducted a media analysis to explore how industry spokespersons (from commercial enterprises, trade associations and social aspects/public relations organisations) represented the RD in newspaper and online reports. We systematically searched databases indexing articles of British national newspapers and the online news services of national broadcasters for articles published between 2010 and 2015. After application of inclusion criteria, we identified 247 relevant articles. We extracted direct quotations by industry spokespersons and analysed them thematically. Media reporting about the RD provided industry spokespersons with a high-profile platform to present frames relating to food, beverages and alcohol that were favourable to advancing or protecting industry positions and agendas. Framing of issues addressed responsibility for public health problems, policy options and the role of industry, also legitimising industry spokespersons to advocate a position on how public health policy should evolve. Media analysis can elucidate industry discourses around public health and examine their engagement in framing to extend their influence in public health policy.