nils-herrmann/clean_scirepeval huggingface dataset:
Method Pair Enumerator Clone Method Pairs Non-clone Method Pairs

Programmers produce code clones when developing software. By copying and pasting code with or without modification, developers reuse existing code to improve programming productivity. However, code clones present challenges to software maintenance: they may require consistent application of the same or similar bug fixes or program changes to multiple code locations. To simplify the maintenance process, various tools have been proposed to automatically detect clones , , , , , . Some tools tokenize source code, and then compare the sequence or frequency of tokens to reveal clones , , , . Some other tools detect clones using tree-matching algorithms to compare the Abstract Syntax Trees (ASTs) of source code [2], . In this paper, we present CCLEARNER, the first solely token-based clone detection approach leveraging deep learning. CCLEARNER extracts tokens from known method-level code clones and nonclones to train a classifier, and then uses the classifier to detect clones in a given codebase. To evaluate CCLEARNER, we reused BigCloneBench , an existing large benchmark of real clones. We used part of the benchmark for training and the other part for testing, and observed that CCLEARNER effectively detected clones. With the same data set, we conducted the first systematic comparison experiment between CCLEARNER and three popular clone detection tools. Compared with the approaches not using deep learning, CCLEARNER achieved competitive clone detection effectiveness with low time cost. Keywords-deep learning; clone detection; empirical
Moral Responsibility and Determinism : The Cognitive Science of Folk Intuitions

The dispute between compatibilists and incompatibilists must be one of the most persistent and heated deadlocks in Western philosophy. Incompatibilists maintain that people are not fully morally responsible if determinism is true, i.e., if every event is an inevitable consequence of the prior conditions and the natural laws. By contrast, compatibilists maintain that even if determinism is true our moral responsibility is not undermined in the slightest, for determinism and moral responsibility are perfectly consistent.1 The debate between these two positions has invoked many different resources, including quantum mechanics, social psychology, and basic metaphysics. But recent discussions have relied heavily on arguments that draw on people’s intuitions about particular cases. Some philosophers have claimed that people have incompatibilist intuitions (e.g., Kane 1999, 218; Strawson 1986, 30; Vargas 2006); others have challenged this claim and suggested that people’s intuitions actually fit with compatibilism (Nahmias et al. 2005). But although philosophers have constructed increasingly sophisticated arguments about the implications of people’s intuitions, there has been remarkably little discussion about why people have the intuitions they do. That is to say, relatively little has been said about the specific psychological processes that generate or sustain people’s intuitions. And yet, it seems clear that questions about the sources of people’s intuitions could have a major impact on debates
Canine computer interaction: towards designing a touchscreen interface for working dogs

Touchscreens can provide a way for service dogs to relay emergency information about their handlers from a home or office environment. In this paper, we build on work exploring the ability of canines to interact with touchscreen interfaces. We observe new requirements for training and explain best practices found in training techniques. Learning from previous work, we also begin to test new dog interaction techniques such as lift-off selection and sliding gestural motions. Our goal is to understand the affordances needed to make touchscreen interfaces usable for canines and help the future design of touchscreen interfaces for assistance dogs in the home.
Look, My Baby Is Using an iPad! An Analysis of YouTube Videos of Infants and Toddlers Using Tablets

We know very little about the use of computers by children under the age of three. While few children in that age range used computers before the advent of smartphones and tablets, these devices have made computers much more accessible to infants and toddlers. In this paper, we provide a window into how these children are using tablets through an analysis of relevant YouTube videos. A majority of children aged 12 to 17 months in the videos in our dataset showed at least moderate ability to use the tablets. For children aged two, it was over 90 percent who displayed at least moderate ability. Our analysis also includes trends in interaction styles, child and device positioning, social aspects, and app genres. These findings point both to opportunities for research and starting points for design.
A deep multiple instance model to predict prostate cancer metastasis from nuclear morphology

We consider the problem of identifying the patients who are diagnosed with highgrade prostate cancer using the histopathology of tumor in a prostate needle biopsy and are at a very high risk of lethal cancer progression. We hypothesize that the morphology of tumor cell nuclei in digital images from the biopsy can be used to predict tumor aggressiveness and posit the presence of metastasis as a surrogate for disease specific mortality. For this purpose, we apply a compositional multiinstance learning approach which encodes images of nuclei through a convolutional neural network, then predicts the presence of metastasis from sets of encoded nuclei. Through experiments on prostate needle biopsies (PNBX) from a patient cohort with known presence (M1 stage, n = 85) or absence (M0 stage, n = 86) of metastatic disease, we obtained an average area under the receiver operating characteristic curve of 0.71± 0.08 for predicting metastatic cases. These results support our hypothesis that information related to metastatic capacity of prostate cancer cells can be obtained through analysis of nuclei and establish a baseline for future research aimed at predicting the risk of future metastatic disease at a time when it might be preventable.
Educational games for improving the teaching-learning process of a CLIL subject: Physics and chemistry in secondary education

The use of educational games in an academic context seems to be a superb alternative to traditional learning activities, such as drill-type exercises, in order to engage 21st-century students. Consequently, this work tries to raise the following objectives: analyze the effectiveness of game-based learning, characterize game elements that may contribute to create playing experiences, comprehend how different player types interact with games and, finally, design interactive games which may create challenges, set goals and provide feedback on progress while motivating learners to study physics and chemistry in a foreign language in the second cycle of Secondary Education (4th E.S.O. that corresponds to the age of 15-16 years old). Specifically, we have used several Web 2.0 tools (Hot Potatoes, Scratch, What2Learn and SMART Notebook 11) and applications (Microsoft PowerPoint and Microsoft Excel) in order to create the games; and these games are based on the successive contents: laboratory safety, laboratory equipment, stoichiometry, atomic structure, electronic configuration, the periodic table, forces, motion and energy.
A synchronous buck-boost converter on a Silicon-On-Sapphire 0.5µm process

This paper presents the design of a synchronous non-inverting buck-boost DC-DC converter on a Silicon-on-Sapphire (SOS) 0.5μm process. The converter uses voltage-mode feedback and PWM control to regulate the power delivered to a range of output voltages and loads. The circuit has been simulated using Cadence and its performance has been measured. The converter has an output voltage range of 1.2-4V and can deliver up to 750 mA. It is up to 92% efficient with a maximum ripple voltage of 80mV and uses significantly less die area than similar converters on standard CMOS processes.
Predictive reward signal of dopamine neurons.

The effects of lesions, receptor blocking, electrical self-stimulation, and drugs of abuse suggest that midbrain dopamine systems are involved in processing reward information and learning approach behavior. Most dopamine neurons show phasic activations after primary liquid and food rewards and conditioned, reward-predicting visual and auditory stimuli. They show biphasic, activation-depression responses after stimuli that resemble reward-predicting stimuli or are novel or particularly salient. However, only few phasic activations follow aversive stimuli. Thus dopamine neurons label environmental stimuli with appetitive value, predict and detect rewards and signal alerting and motivating events. By failing to discriminate between different rewards, dopamine neurons appear to emit an alerting message about the surprising presence or absence of rewards. All responses to rewards and reward-predicting stimuli depend on event predictability. Dopamine neurons are activated by rewarding events that are better than predicted, remain uninfluenced by events that are as good as predicted, and are depressed by events that are worse than predicted. By signaling rewards according to a prediction error, dopamine responses have the formal characteristics of a teaching signal postulated by reinforcement learning theories. Dopamine responses transfer during learning from primary rewards to reward-predicting stimuli. This may contribute to neuronal mechanisms underlying the retrograde action of rewards, one of the main puzzles in reinforcement learning. The impulse response releases a short pulse of dopamine onto many dendrites, thus broadcasting a rather global reinforcement signal to postsynaptic neurons. This signal may improve approach behavior by providing advance reward information before the behavior occurs, and may contribute to learning by modifying synaptic transmission. The dopamine reward signal is supplemented by activity in neurons in striatum, frontal cortex, and amygdala, which process specific reward information but do not emit a global reward prediction error signal. A cooperation between the different reward signals may assure the use of specific rewards for selectively reinforcing behaviors. Among the other projection systems, noradrenaline neurons predominantly serve attentional mechanisms and nucleus basalis neurons code rewards heterogeneously. Cerebellar climbing fibers signal errors in motor performance or errors in the prediction of aversive events to cerebellar Purkinje cells. Most deficits following dopamine-depleting lesions are not easily explained by a defective reward signal but may reflect the absence of a general enabling function of tonic levels of extracellular dopamine. Thus dopamine systems may have two functions, the phasic transmission of reward information and the tonic enabling of postsynaptic neurons.
Nanoconnectomic upper bound on the variability of synaptic plasticity

Information in a computer is quantified by the number of bits that can be stored and recovered. An important question about the brain is how much information can be stored at a synapse through synaptic plasticity, which depends on the history of probabilistic synaptic activity. The strong correlation between size and efficacy of a synapse allowed us to estimate the variability of synaptic plasticity. In an EM reconstruction of hippocampal neuropil we found single axons making two or more synaptic contacts onto the same dendrites, having shared histories of presynaptic and postsynaptic activity. The spine heads and neck diameters, but not neck lengths, of these pairs were nearly identical in size. We found that there is a minimum of 26 distinguishable synaptic strengths, corresponding to storing 4.7 bits of information at each synapse. Because of stochastic variability of synaptic activation the observed precision requires averaging activity over several minutes.
Electronic QED coherence in brain microtubules

In this paper we show in the water confined within the inner hollow of brain microtubules there exist the conditions to allow a spontaneous QED quantum vacuum phase transition towards a macroscopic coherent quantum state, characterized by a phased oscillation between the water molecules states and an auto-generated electromagnetic field associated to a suitable electronic transition in them. As a result, a field of superradiant photons, whose frequency is smaller than the corresponding frequency belonging to a free photon with the same wavelength, is generated. This superradiant field is characterized by an evanescent tail exceeding the microtubules dimension and whose persistence against environmental decoherence is ensured by its own QED coherent behaviour.  QED coherence, Microtubules, Water, Evanescent Photons.
Critiquing-based recommenders: survey and emerging trends

Critiquing-based recommender systems elicit users’ feedback, called critiques, which they made on the recommended items. This conversational style of interaction is in contract to the standard model where users receive recommendations in a single interaction. Through the use of the critiquing feedback, the recommender systems are able to more accurately learn the users’ profiles, and therefore suggest better recommendations in the subsequent rounds. Critiquing-based recommenders have been widely studied in knowledge-, content-, and preference-based recommenders and are beginning to be tried in several online websites, such as MovieLens. This article examines the motivation and development of the subject area, and offers a detailed survey of the state of the art concerning the design of critiquing interfaces and development of algorithms for critiquing generation. With the help of categorization analysis, the survey reveals three principal branches of critiquing based recommender systems, using respectively natural language based, system-suggested, and user-initiated critiques. Representative example systems will be presented and analyzed for each branch, and their respective pros and cons will be discussed. Subsequently, a hybrid framework is developed to unify the advantages of different methods and overcome their respective limitations. Empirical findings from user studies are further presented, indicating how hybrid critiquing supports could effectively enable end-users to achieve more confident decisions. Finally, the article will point out several future trends to boost the advance of critiquing-based recommenders.
Quality-of-service in cloud computing: modeling techniques and their applications

Recent years have seen the massive migration of enterprise applications to the cloud. One of the challenges posed by cloud applications is Quality-of-Service (QoS) management, which is the problem of allocating resources to the application to guarantee a service level along dimensions such as performance, availability and reliability. This paper aims at supporting research in this area by providing a survey of the state of the art of QoS modeling approaches suitable for cloud systems. We also review and classify their early application to some decision-making problems arising in cloud QoS management.
SCPNet: Spatial-Channel Parallelism Network for Joint Holistic and Partial Person Re-Identification

Holistic person re-identification (ReID) has received extensive study in the past few years and achieves impressive progress. However, persons are often occluded by obstacles or other persons in practical scenarios, which makes partial person re-identification non-trivial. In this paper, we propose a spatial-channel parallelism network (SCPNet) in which each channel in the ReID feature pays attention to a given spatial part of the body. The spatial-channel corresponding relationship supervises the network to learn discriminative feature for both holistic and partial person re-identification. The single model trained on four holistic ReID datasets achieves competitive accuracy on these four datasets, as well as outperforms the state-of-the-art methods on two partial ReID datasets without training.
A Taxonomy of Domain-Specific Aspect Languages

Domain-Specific Aspect Languages (DSALs) are Domain-Specific Languages (DSLs) designed to express crosscutting concerns. Compared to DSLs, their aspectual nature greatly amplifies the language design space. We structure this space in order to shed light on and compare the different domain-specific approaches to deal with crosscutting concerns. We report on a corpus of 36 DSALs covering the space, discuss a set of design considerations, and provide a taxonomy of DSAL implementation approaches. This work serves as a frame of reference to DSAL and DSL researchers, enabling further advances in the field, and to developers as a guide for DSAL implementations.
A Set of Principles for Conducting and Evaluating Interpretive Field Studies in Information Systems

This article discusses the conduct and evaluation of interpretive research in information systems. Whiie the conventions for evaluating information systems case studies conducted according to the natural science model of social science are now widely accepted, this is not the case for interpretive field studies. A set of principles for the conduct and evaluation of interpretive field research in information systems is proposed, along with their philosophical rationale. The usefulness of the principles is illustrated by evaluating three pubiished interpretive field studies drawn from the IS research literature. The intention of the paper is to further reflection and debate on the important subject of grounding interpretive research methodology.
SemSOS: Semantic sensor Observation Service

Sensor Observation Service (SOS) is a Web service specification defined by the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) group in order to standardize the way sensors and sensor data are discovered and accessed on the Web. This standard goes a long way in providing interoperability between repositories of heterogeneous sensor data and applications that use this data. Many of these applications, however, are ill equipped at handling raw sensor data as provided by SOS and require actionable knowledge of the environment in order to be practically useful. There are two approaches to deal with this obstacle, make the applications smarter or make the data smarter. We propose the latter option and accomplish this by leveraging semantic technologies in order to provide and apply more meaningful representation of sensor data. More specifically, we are modeling the domain of sensors and sensor observations in a suite of ontologies, adding semantic annotations to the sensor data, using the ontology models to reason over sensor observations, and extending an open source SOS implementation with our semantic knowledge base. This semantically enabled SOS, or SemSOS, provides the ability to query high-level knowledge of the environment as well as low-level raw sensor data.
Eyes-Free Barcode Localization and Decoding for Visually Impaired Mobile Phone Users

An eyes-free barcode localization and decoding method is presented that enables visually impaired (VI) mobile phone users to decode MSI (Modified Plessy) barcodes on shelves and UPC barcodes on individual boxes, cans, and bottles. Simple and efficient barcode localization and decoding techniques are augmented with an interactive haptic feedback loop that allows the VI user to align the phone’s camera with a fixed surface in the pitch and yaw planes. The method is implemented on a Google Nexus One smart phone running Android 2.1. A laboratory study is presented in which the method was evaluated by one VI and four blindfolded sighted participants.
Introducing qualitative research in psychology Adventures in theory and method

All rights reserved. Except for the quotation of short passages for the purpose of criticism and review, no part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior written permission of the publisher or a licence from the Copyright Licensing Agency Limited. Details of such licences (for reprographic reproduction) may be obtained from the Copyright Introducing qualitative research in psychology: adventures in theory and method / Carla Willig. p. cm. Includes bibliographical references and index.
Suicidal ideation and school bullying experiences after controlling for depression and delinquency.

This cross-sectional study examines differences in the frequency of suicidal ideation and suicidal behaviors across a group of verbal bullies, bully-victims, victims, physically aggressive bullies, and students not involved in bullying.



A large sample of middle school students (n = 661; fifth through eighth grades; ages 10-13 years of age) completed a pencil-and-paper survey that included the University of Illinois Bully, Fight, and Victim scales. Students also self-reported how often they had thought of killing themselves or deliberating hurting themselves in past 6 months, and provided information about delinquent behaviors and symptoms of depression and anxiety.



We used cluster analysis to create bully-victim subtypes: uninvolved (n = 357), victims (n = 110), verbal bullies (n = 114), bully-victims (n = 29), and physically aggressive bullies (n = 42). Approximately 32%-38% of verbal bullies and victims, 60% of bully-victims, and 43% of physically aggressive bullies reported suicidal ideation, compared with 12% of uninvolved youth. Similarly, 24%-28% of verbal bullies and victims, 44% of bully-victims, and 35% of physically aggressive bullies reported deliberately trying to hurt or kill themselves, compared with 8% of uninvolved youth. Females in the bully-victim subtype reported particularly elevated suicidal ideation and behavior. After controlling for delinquency and depression, differences in suicidal thoughts and behaviors emerged only between uninvolved youth and the victim and bully-victim groups, but these differences were minimal.



Findings highlight that at a bivariate level, involvement in bullying in any capacity is linked to increased risk for suicidal ideation and behavior, and echoes previous literature documenting particularly strong mental health implications for bully-victims. Furthermore, this study points to the importance of considering delinquency and depression in conjunction with suicidal ideation and behaviors.
The Neural Network House : An Environment that Adapts to its Inhabitants

Although the prospect of computerized homes has a long history, ho/ne automation has never become terribly popular because the benefits are seldom seen to outweigh the costs. One significant cost of an automated home is that someone has to program it to behave appropriately. Typical inhabitants do not want to program simple devices such as VCRs, let alone a much broader range of electronic devices, appliances, and comfort systems that have even greater functionality. We describe an alternative approach t in which the goal is for the home to essentially program itself by observing the lifestyle and desires of the inhabitants, and learning to anticipate and accommodate their needs. The system we have developed controls basic residential comfort systems--air heating, lighting, ventilation, and water heating. We have constructed a prototype system in an actual residence, and describe initial results and the current state of the project.