nils-herrmann/clean_scirepeval huggingface dataset:
Analyzing Thermal and Visual Clues of Deception for a Non-Contact Deception Detection Approach

With increased levels of security threats and the long-term consequences of falsely accusing the innocent and freeing the guilty, there is a growing need for reliable and efficient deception detection systems. Polygraph tests are invasive and require elongated time and human expertise, which is subject to bias and error. In this paper, we analyze thermal and visual clues of deception using a dataset collected from 30 subjects and multiple scenarios. We analyze expressions and other visual features and provide the first comparison between thermal facial regions to identify areas with higher capability of indicating deceit. Our experimental results show that our non-contact feature fusion model outperforms traditional physiological measurements, paving the road for non-invasive deception detection methodologies.
Fast Fourier Transforms for Nonequispaced Data

Fast Fourier Transforms for Nonequispaced Data Alok Dutt Yale University 1993 Two groups of algorithms are presented generalizing the fast Fourier transform (FFT) to the case of non-integer frequencies and nonequispaced nodes on the interval [-7r, 7r]. These schemes are based on combinations of certain analytical considerations with the classical fast Fourier transform, and generalize both the forward and backward FFTs. The number of arithmetic operations required by each of the algorithms is proportional to Nlog N + Nlog(I/e), where 6 is the desired precision of computations and N is the number of nodes. Several related algorithms are also presented, each of which utilizes a similar set of techniques from analysis and linear algebra. These include an efficient version of the Fast Multipole Method in one dimension and fast algorithms for the evaluation, integration and differentiation of Lagrange polynomial interpolants. Several numerical examples are used to illustrate the efficiency of the approach, and to compare the performances of the two sets of nonuniform FFT algorithms. The work of this author was supported in part by the Office of Naval Research under Grant N00014-89-J-1527 and in part by the National Science Foundation under Grant DMS9012751. Approved for public release: distribution is unlimited.
Continual One-Shot Learning of Hidden Spike-Patterns with Neural Network Simulation Expansion and STDP Convergence Predictions

This paper presents a constructive algorithm that achieves successful oneshot learning of hidden spike-patterns in a competitive detection task. It has previously been shown (Masquelier et al., 2008) that spike-timing-dependent plasticity (STDP) and lateral inhibition can result in neurons competitively tuned to repeating spike-patterns concealed in high rates of overall presynaptic activity. One-shot construction of neurons with synapse weights calculated as estimates of converged STDP outcomes results in immediate selective detection of hidden spike-patterns. The capability of continual learning is demonstrated through the successful one-shot detection of new sets of spike-patterns introduced after long intervals in the simulation time. Simulation expansion (Lightheart et al., 2013) has been proposed as an approach to the development of constructive algorithms that are compatible with simulations of biological neural networks. A simulation of a biological neural network may have orders of magnitude fewer neurons and connections than the related biological neural systems; therefore, simulated neural networks can be assumed to be a subset of a larger neural system. The constructive algorithm is developed using simulation expansion concepts to perform an operation equivalent to the exchange of neurons between the simulation and the larger hypothetical neural system. The dynamic selection of neurons to simulate within a larger neural system (hypothetical or stored in memory) may be a starting point for a wide range of developments and applications in machine learning and the simulation of biology.
Mr. DLib's Living Lab for Scholarly Recommendations

We introduce the first living lab for scholarly recommender systems. This lab allows recommender-system researchers to conduct online evaluations of their novel algorithms for scholarly recommendations, i.e., research papers, citations, conferences, research grants etc. Recommendations are delivered through the living lab ́s API in platforms such as reference management software and digital libraries. The living lab is built on top of the recommender system as-a-service Mr. DLib. Current partners are the reference management software JabRef and the CORE research team. We present the architecture of Mr. DLib’s living lab as well as usage statistics on the first ten months of operating it. During this time, 970,517 recommendations were delivered with a mean click-through rate of 0.22%.
Accuracy of Ultrasound-Guided Genicular Nerve Block: A Cadaveric Study.

Genicular nerve block has recently emerged as a novel alternative treatment in chronic knee pain. The needle placement for genicular nerve injection is made under fluoroscopic guidance with reference to bony landmarks.



To investigate the anatomic landmarks for medial genicular nerve branches and to determine the accuracy of ultrasound-guided genicular nerve block in a cadaveric model.



Cadaveric accuracy study.



University hospital anatomy laboratory.



Ten cadaveric knee specimens without surgery or major procedures were used in the study. The anatomic location of the superior medial genicular nerve (SMGN) and the inferior medial genicular nerve (IMGN) was examined using 4 knee dissections. The determined anatomical sites of the genicular nerves in the remaining 6 knee specimens were injected with 0.5 mL red ink under ultrasound guidance. The knee specimens were subsequently dissected to assess for accuracy. If the nerve was dyed with red ink, it was considered accurate placement. All other locations were considered inaccurate.



The course of the SMGN is that it curves around the femur shaft and passes between the adductor magnus tendon and the femoral medial epicondyle, then descends approximately one cm anterior to the adductor tubercle. The IMGN is situated horizontally around the tibial medial epicondyle and passes beneath the medial collateral ligament at the midpoint between the tibial medial epicondyle and the tibial insertion of the medial collateral ligament. The adductor tubercle for the SMGN and the medial collateral ligament for the IMGN were determined as anatomic landmarks for ultrasound. The bony cortex one cm anterior to the peak of the adductor tubercle and the bony cortex at the midpoint between the peak of the tibial medial epicondyle and the initial fibers inserting on the tibia of the medial collateral ligament were the target points for the injections of SMGN and IMGN, respectively. In the cadaver dissections both genicular nerves were seen to be dyed with red ink in all the injections of the 6 knees.



The small number of cadavers might have led to some anatomic variations of genicular nerves being overlooked.



The result of this cadaveric study suggests that ultrasound-guided medial genicular nerve branch block can be performed accurately using the above-stated anatomic landmarks.
Detecting Factual and Non-Factual Content in News Articles

News articles are a major source of facts about the current state and events of our surrounding world. However, not all news articles are equally rich in presenting the facts. In this paper, we consider the problem of detecting factual and non-factual parts in news articles. We present a comprehensive survey on the existing literature on fact classification on news articles as well as a related and more widely studied problem of subjectivity vs objectivity classification of statements. Combining these techniques and some new features we design a framework for classifying facts and non-facts in news articles. We present extensive experiments on this task using several features and combinations of those on two datasets, one of which was used for subjectivity classification in previous works. We show that standard textual dataset dependent features such as n-grams produce good results on both datasets, but more general features such as part of speech tags and entity types produce inconsistent results. We analyze the results based on the nature of the datasets to present insights on the usefulness of the features and their applicability in the classification task we are considering.
The Impact of Experimental Setup in Prepaid Churn Prediction for Mobile Telecommunications: What to Predict, for Whom and Does the Customer Experience Matter?

Prepaid customers in mobile telecommunications are not bound by a contract and can therefore change operators (‘churn’) at their convenience and without notification. This makes the task of predicting prepaid churn both challenging and financially rewarding. This paper presents an explorative, real world study of prepaid churn modeling by varying the experimental setup on three dimensions: data, outcome definition and population sample. Firstly, we add Customer Experience Management (CEM) data to data traditionally used for prepaid churn prediction. Secondly, we vary the outcome definition of prepaid churn. Thirdly, we alter the sample of the customers included, based on their inactivity period at the time of recording. While adding CEM parameters did not influence the predictability of churn, one variation on the sample and especially a particular change in the outcome definition had a substantial
Does core strength training influence running kinetics, lower-extremity stability, and 5000-M performance in runners?

Although strong core muscles are believed to help athletic performance, few scientific studies have been conducted to identify the effectiveness of core strength training (CST) on improving athletic performance. The aim of this study was to determine the effects of 6 weeks of CST on ground reaction forces (GRFs), stability of the lower extremity, and overall running performance in recreational and competitive runners. After a screening process, 28 healthy adults (age, 36.9 +/- 9.4 years; height, 168.4 +/- 9.6 cm; mass, 70.1 +/- 15.3 kg) volunteered and were divided randomly into 2 groups (n = 14 in each group). A test-retest design was used to assess the differences between CST (experimental) and no CST (control) on GRF measures, lower-extremity stability scores, and running performance. The GRF variables were determined by calculating peak impact, active vertical GRFs (vGRFs), and duration of the 2 horizontal GRFs (hGRFs), as measured while running across a force plate. Lower-extremity stability was assessed using the Star Excursion Balance Test. Running performance was determined by 5000-m run time measured on outdoor tracks. Six 2 (pre, post) x 2 (CST, control) mixed-design analyses of variance were used to determine the influence of CST on each dependent variable, p < 0.05. Twenty subjects completed the study (nexp = 12 and ncon = 8). A significant interaction occurred, with the CST group showing faster times in the 5000-m run after 6 weeks. However, CST did not significantly influence GRF variables and lower-leg stability. Core strength training may be an effective training method for improving performance in runners.
Pincer-Search: An Efficient Algorithm for Discovering the Maximum Frequent Set

Discovering frequent itemsets is a key problem in important data mining applications, such as the discovery of association rules, strong rules, episodes, and minimal keys. Typical algorithms for solving this problem operate in a bottom-up, breadth-first search direction. The computation starts from frequent 1-itemsets (the minimum length frequent itemsets) and continues until all maximal (length) frequent itemsets are found. During the execution, every frequent itemset is explicitly considered. Such algorithms perform well when all maximal frequent itemsets are short. However, performance drastically decreases when some of the maximal frequent itemsets are relatively long. We present a new algorithm which combines both the bottom-up and the top-down searches. The primary search direction is still bottom-up, but a restricted search is also conducted in the top-down direction. This search is used only for maintaining and updating a new data structure, the maximum frequent candidate set. It is used to prune early candidates that would normally encountered in the bottom-up search. A very important characteristic of the algorithm is that it does not require explicite examination of every frequent itemset. Therefore the algorithm performs well even when some maximal frequent itemsets are long. As its output, the algorithm produces the maximum frequent set, i.e., the set containing all maximal frequent itemsets, thus specifying immediately all frequent itemsets. We evaluate the performance of the algorithm using well-known synthetic benchmark databases and real-life census and ∗Applied Research, Telcordia Technologies, Inc., 445 South Street, Morristown, NJ 07960 +1 973 829 4740, tlin@research.telcordia.com. †Department of Computer Science, Courant Institute of Mathematical Sciences, New York University, 251 Mercer St., New York, NY 100121185, +1 212 998 3101,
Trust in school : a pathway to inhibit teacher burnout ?

The purpose of this paper is to consider trust as an important relational source in schools by exploring whether trust lowers teacher burnout. The authors examine how trust relationships with different school parties such as the principal relate to distinct dimensions of teacher burnout. The authors further analyze whether school-level trust additionally influences burnout. In doing this, the authors account for other teacher and school characteristics.  The authors use quantitative data gathered during the 2008-2009 school year from 673 teachers across 58 elementary schools in Flanders (i.e. the northern Dutch-speaking region of Belgium). Because teacher and school characteristics are simultaneously related to burnout, multilevel modeling is applied.  Trust can act as a buffer against teacher burnout. Teachers’ trust in students demonstrates the strongest association with burnout compared to trust in principals or colleagues. Exploring relationships of trust in distinct school parties with different burnout dimensions yield interesting additional insights such as the specific importance of teacher-principal trust for teachers’ emotional exhaustion. Burnout is further an individual teacher matter to which school-level factors are mainly unrelated.  Principals fulfill an important role in inhibiting emotional exhaustion among teachers. They are advised to create a school atmosphere that is conducive for different kinds of trust relationships to develop. Actions to strengthen trust and inhibit teacher burnout are necessary, although further qualitative and longitudinal research is desirable.  This paper offers a unique contribution by examining trust in different school parties as a relational buffer against teacher burnout. It indicates that principals can affect teacher burnout and prevent emotional exhaustion by nurturing trusting relationships in school.
Brainstem responses to speech syllables

To establish reliable procedures and normative values to quantify brainstem encoding of speech sounds.



Auditory brainstem responses to speech syllables presented in quiet and in background noise were obtained from 38 normal children. Brainstem responses consist of transient and sustained, periodic components-much like the speech signal itself. Transient peak responses were analyzed with measures of latency, amplitude, area, and slope. Magnitude of sustained, periodic frequency-following responses was assessed with root mean square, fundamental frequency, and first formant amplitudes; timing was assessed by stimulus-to-response and quiet-to-noise inter-response correlations.



Measures of transient and sustained components of the brainstem response to speech syllables were reliably obtained with high test-retest stability and low variability across subjects. All components of the brainstem response were robust in quiet. Background noise disrupted the transient responses whereas the sustained response was more resistant to the deleterious effects of noise.



The speech-evoked brainstem response faithfully reflects many acoustic properties of the speech signal. Procedures to quantitatively describe it have been developed.



Accurate and precise manifestation of stimulus timing at the auditory brainstem is a hallmark of the normal perceptual system. The brainstem response to speech sounds provides a mechanism for understanding the neural bases of normal and deficient attention-independent auditory function.
"Strong beats skinny every time": Disordered eating and compulsive exercise in women who post fitspiration on Instagram.

Fitspiration is a recent Internet trend designed to motivate people to eat healthily and to exercise. The aim of the study was to investigate disordered eating and exercise in women who post fitspiration on Instagram.



Participants were 101 women who post fitspiration images on Instagram and a comparison group of 102 women who post travel images. Both groups completed measures of disordered eating and compulsive exercise.



Women who post fitspiration images scored significantly higher on drive for thinness, bulimia, drive for muscularity, and compulsive exercise. Almost a fifth (17.5%) of these women were at risk for diagnosis of a clinical eating disorder, compared to 4.3% of the travel group. Compulsive exercise was related to disordered eating in both groups, but the relationship was significantly stronger for women who post fitspiration images.



For some women, posting fitspiration images on Instagram may signify maladaptive eating and exercise behaviors.
A Customizable Framework for Prioritizing Systems Security Engineering Processes, Activities, and Tasks

As modern systems become increasingly complex, current security practices lack effective methodologies to adequately address the system security. This paper proposes a repeatable and tailorable framework to assist in the application of systems security engineering (SSE) processes, activities, and tasks as defined in the recently released National Institute of Standards and Technology (NIST) Special Publication 800–160. First, a brief survey of systems-oriented security methodologies is provided. Next, an examination of the relationships between the NIST-defined SSE processes is conducted to provide context for the engineering problem space. These findings inform a mapping of the NIST SSE processes to seven system-agnostic security domains which enable prioritization for three types of systems (conventional IT, cyber-physical, and defense). These concrete examples provide further understanding for applying and prioritizing the SSE effort. The goal of this paper is assist practitioners by informing the efficient application of the 30 processes, 111 activities, and 428 tasks defined in NIST SP 800–160. The customizable framework tool is available online for developers to employ, modify, and tailor to meet their needs.
Transparent triboelectric nanogenerators and self-powered pressure sensors based on micropatterned plastic films.

Transparent, flexible and high efficient power sources are important components of organic electronic and optoelectronic devices. In this work, based on the principle of the previously demonstrated triboelectric generator, we demonstrate a new high-output, flexible and transparent nanogenerator by using transparent polymer materials. We have fabricated three types of regular and uniform polymer patterned arrays (line, cube, and pyramid) to improve the efficiency of the nanogenerator. The power generation of the pyramid-featured device far surpassed that exhibited by the unstructured films and gave an output voltage of up to 18 V at a current density of ∼0.13 μA/cm(2). Furthermore, the as-prepared nanogenerator can be applied as a self-powered pressure sensor for sensing a water droplet (8 mg, ∼3.6 Pa in contact pressure) and a falling feather (20 mg, ∼0.4 Pa in contact pressure) with a low-end detection limit of ∼13 mPa.
Self-supervised learning of a facial attribute embedding from video

The architecture of the encoders and decoders is based on pix2pix  but without skipconnections . It consists of encoders (with shared weights) and corresponding symmetrical decoders (also with shared weights). The face embedding vectors which are the outputs of the encoder have channel size 256. At the centre of the network, the source embedding vectors are concatenated pairwise with the target embedding vector. This 512channel vector serves as input to the decoders. The sampler decoders predict a 2⇥ 256⇥ 256 output which determines how to sample from the source frame. When using multiple source frames, the network is augmented with confidence map decoders whose architecture is identical to the sampler decoders, except that the last layer outputs a 1-channel image. The confidence decoders also have shared weights for the different source frames.
Assessing and Quantifying Network Effects in an Online Dating Market

We empirically examine and quantify network effects on a large online dating platform in Brazil. We exploit a natural experiment, wherein a focal platform acquired its Brazilian competitor and subsequently imported the competitor’s base of 150,000+ users over a 3-day period; a large exogenous shock to the composition of the purchasing platform. Our study context and the natural experiment provide two unique sources of identification: i) accounts purchased from the competitor were almost exclusively heterosexual users, even though the purchasing platform also played host to homosexual users, and ii) the treatment varied across cities, in that the “value” of new users to the existing user base differed. because purchased users differed from existing users in terms of their average characteristics (e.g., location within the city). We leverage the former to estimate a difference-in-differences specification, treating homosexual enrollment and exit rates as a plausible control for those of the heterosexual population, whereas the latter provides us with an opportunity to explore the importance of local market structure in the manifestation of network effects. We find that the treatment increased both rates of enrollment and rates of exit, amongst both genders, with a net positive effect that translated to a 17% increase in short-term revenue for the platform. We find clear evidence of local network effects; in cities where the average spatial distance between new users and existing users was larger, the treatment effect was significantly weaker. We discuss the implications for the literature and practice, and we suggest a number of avenues for future work in this space. ∗Assistant Professor, Information Systems Department, Carlson School of Management, University of Minnesota. gburtch@umn.edu. †Associate Professor, Information Systems Department, Desautels Faculty of Management, McGill University. jui.ramaprasad@mcgill.ca.