nils-herrmann/clean_scirepeval huggingface dataset:
Whisker-based discrimination of object orientation determined with a rapid training paradigm

Rats use their large facial whiskers to discriminate the spatial features of objects. Despite numerous electrophysiological recording studies in the central trigeminal whisker representations that document neurons tuned to the direction of whisker deflection, there is no behavioral evidence to date that rats can use their whiskers to discriminate between object orientations. In the present study, we characterized whisker-dependent orientation discrimination using a one-trial learning procedure. Sprague-Dawley rats were trained and tested in a three-arm 'Y-maze' that was outfitted with 180 independently moveable bars that protruded into the arms of the maze to contact the whiskers. On the first day, the maze was configured to have two arms with only horizontal bars and a third arm with only vertical bars and rats were allowed to freely explore all arms. On the second day, rats were isolated in one arm that contained only vertical bars as a conditioned stimulus (CS) and administered three mild foot shocks. On the third day, the maze was configured identically to the first day and rats were once again allowed to freely explore the maze. We measured the percentage of time spent in each arm of the maze and found that most rats spent significantly less time in the arm containing the CS after training compared to before training. Subsequent control experiments determined that the conditioned avoidance was attributable to orientation cues, was caused by the association of the conditioned and unconditioned stimulus and was whisker-dependent. Avoidance behavior was significantly reduced when the difference between the conditioned and non-conditioned orientation difference was reduced to 45 degrees. Thus, rats can discriminate object orientation with their whiskers and an estimate of their discrimination thresholds can be rapidly acquired through the application of a one-trial learning paradigm.
Automatic fairing algorithm for B-spline curves

One of the basic tasks that a modern CAD system should be able to accomplish, is the generation of a 'fair' or 'visually pleasing' curve from given data points. Even when a very efficient curve scheme like B-splines is used, it is quite possible that for some data sets the resulting curve is not fair enough. In this case, some 'processing' of the geometry of the curve is required in order to obtain an acceptable curve. The current trends regarding geometry processing for curves are the following:
Activation of the prefrontal cortex in the human visual aesthetic perception.

Visual aesthetic perception ("aesthetics") or the capacity to visually perceive a particular attribute added to other features of objects, such as form, color, and movement, was fixed during human evolutionary lineage as a trait not shared with any great ape. Although prefrontal brain expansion is mentioned as responsible for the appearance of such human trait, no current knowledge exists on the role of prefrontal areas in the aesthetic perception. The visual brain consists of "several parallel multistage processing systems, each specialized in a given task such as, color or motion" [Bartels, A. & Zeki, S. (1999) ]. Here we report the results of an experiment carried out with magnetoencephalography which shows that the prefrontal area is selectively activated in humans during the perception of objects qualified as "beautiful" by the participants. Therefore, aesthetics can be hypothetically considered as an attribute perceived by means of a particular brain processing system, in which the prefrontal cortex seems to play a key role.
Programming rich interactions using the hierarchical state machine toolkit

Structured graphics models such as Scalable Vector Graphics (SVG) enable designers to create visually rich graphics for user interfaces. Unfortunately current programming tools make it difficult to implement advanced interaction techniques for these interfaces. This paper presents the Hierarchical State Machine Toolkit (HsmTk), a toolkit targeting the development of rich interactions. The key aspect of the toolkit is to consider interactions as first-class objects and to specify them with hierarchical state machines. This approach makes the resulting behaviors self-contained, easy to reuse and easy to modify. Interactions can be attached to graphical elements without knowing their detailed structure, supporting the parallel refinement of the graphics and the interaction.
Hyperhomocysteinemia: an independent risk factor for vascular disease.

Hyperhomocysteinemia arising from impaired methionine metabolism, probably usually due to a deficiency of cystathionine beta-synthase, is associated with premature cerebral, peripheral, and possibly coronary vascular disease. Both the strength of this association and its independence of other risk factors for cardiovascular disease are uncertain. We studied the extent to which the association could be explained by heterozygous cystathionine beta-synthase deficiency.



We first established a diagnostic criterion for hyperhomocysteinemia by comparing peak serum levels of homocysteine after a standard methionine-loading test in 25 obligate heterozygotes with respect to cystathionine beta-synthase deficiency (whose children were known to be homozygous for homocystinuria due to this enzyme defect) with the levels in 27 unrelated age- and sex-matched normal subjects. A level of 24.0 mumol per liter or more was 92 percent sensitive and 100 percent specific in distinguishing the two groups. The peak serum homocysteine levels in these normal subjects were then compared with those in 123 patients whose vascular disease had been diagnosed before they were 55 years of age.



Hyperhomocysteinemia was detected in 16 of 38 patients with cerebrovascular disease (42 percent), 7 of 25 with peripheral vascular disease (28 percent), and 18 of 60 with coronary vascular disease (30 percent), but in none of the 27 normal subjects. After adjustment for the effects of conventional risk factors, the lower 95 percent confidence limit for the odds ratio for vascular disease among the patients with hyperhomocysteinemia, as compared with the normal subjects, was 3.2. The geometric-mean peak serum homocysteine level was 1.33 times higher in the patients with vascular disease than in the normal subjects (P = 0.002). The presence of cystathionine beta-synthase deficiency was confirmed in 18 of 23 patients with vascular disease who had hyperhomocysteinemia.



Hyperhomocysteinemia is an independent risk factor for vascular disease, including coronary disease, and in most instances is probably due to cystathionine beta-synthase deficiency.
Post-quantum key exchange - a new hope

Earlier in 2015, Bos, Costello, Naehrig, and Stebila () proposed an instantiation of Peikert’s ringlearning-with-errors (Ring-LWE) based key-exchange protocol (PQCrypto 2014), together with an implementation integrated into OpenSSL, with the affirmed goal of providing post-quantum security for TLS. In this work we revisit their instantiation and stand-alone implementation. Specifically, we propose new parameters and a better suited error distribution, analyze the scheme’s hardness against attacks by quantum computers in a conservative way, introduce a new and more efficient errorreconciliation mechanism, and propose a defense against backdoors and all-for-the-price-of-one attacks. By these measures and for the same lattice dimension, we more than double the security parameter, halve the communication overhead, and speed up computation by more than a factor of 8 in a portable C implementation and by more than a factor of 20 in an optimized implementation targeting current Intel CPUs. These speedups are achieved with comprehensive protection against timing attacks.
Accurate and Novel Recommendations: An Algorithm Based on Popularity Forecasting

Recommender systems are in the center of network science, and they are becoming increasingly important in individual businesses for providing efficient, personalized services and products to users. Previous research in the field of recommendation systems focused on improving the precision of the system through designing more accurate recommendation lists. Recently, the community has been paying attention to diversity and novelty of recommendation lists as key characteristics of modern recommender systems. In many cases, novelty and precision do not go hand in hand, and the accuracy--novelty dilemma is one of the challenging problems in recommender systems, which needs efforts in making a trade-off between them.
 In this work, we propose an algorithm for providing novel and accurate recommendation to users. We consider the standard definition of accuracy and an effective self-information--based measure to assess novelty of the recommendation list. The proposed algorithm is based on item popularity, which is defined as the number of votes received in a certain time interval. Wavelet transform is used for analyzing popularity time series and forecasting their trend in future timesteps. We introduce two filtering algorithms based on the information extracted from analyzing popularity time series of the items. The popularity-based filtering algorithm gives a higher chance to items that are predicted to be popular in future timesteps. The other algorithm, denoted as a novelty and population-based filtering algorithm, is to move toward items with low popularity in past timesteps that are predicted to become popular in the future. The introduced filters can be applied as adds-on to any recommendation algorithm. In this article, we use the proposed algorithms to improve the performance of classic recommenders, including item-based collaborative filtering and Markov-based recommender systems. The experiments show that the algorithms could significantly improve both the accuracy and effective novelty of the classic recommenders.
Acute effects of low-level laser therapy irradiation on blood lactate and muscle fatigue perception in hospitalized patients with heart failure—a pilot study

The objective of the present study is to evaluate the acute effects of low-level laser therapy (LLLT) on functional capacity, perceived exertion, and blood lactate in hospitalized patients with heart failure (HF). Patients diagnosed with systolic HF (left ventricular ejection fraction <45 %) were randomized and allocated prospectively into two groups: placebo LLLT group (n = 10)—subjects who were submitted to placebo laser and active LLLT group (n = 10)—subjects who were submitted to active laser. The 6-min walk test (6MWT) was performed, and blood lactate was determined at rest (before LLLT application and 6MWT), immediately after the exercise test (time 0) and recovery (3, 6, and 30 min). A multi-diode LLLT cluster probe (DMC, São Carlos, Brazil) was used. Both groups increased 6MWT distance after active or placebo LLLT application compared to baseline values (p = 0.03 and p = 0.01, respectively); however, no difference was observed during intergroup comparison. The active LLLT group showed a significant reduction in the perceived exertion Borg (PEB) scale compared to the placebo LLLT group (p = 0.006). In addition, the group that received active LLLT showed no statistically significant difference for the blood lactate level through the times analyzed. The placebo LLLT group demonstrated a significant increase in blood lactate between the rest and recovery phase (p < 0.05). Acute effects of LLLT irradiation on skeletal musculature were not able to improve the functional capacity of hospitalized patients with HF, although it may favorably modulate blood lactate metabolism and reduce perceived muscle fatigue.
A multicenter randomized controlled trial of a 3-L/kg/min versus 2-L/kg/min high-flow nasal cannula flow rate in young infants with severe viral bronchiolitis (TRAMONTANE 2)

High-flow nasal cannula (HFNC) therapy is increasingly proposed as first-line respiratory support for infants with acute viral bronchiolitis (AVB). Most teams use 2 L/kg/min, but no study compared different flow rates in this setting. We hypothesized that 3 L/kg/min would be more efficient for the initial management of these patients. A randomized controlled trial was performed in 16 pediatric intensive care units (PICUs) to compare these two flow rates in infants up to 6 months old with moderate to severe AVB and treated with HFNC. The primary endpoint was the percentage of failure within 48 h of randomization, using prespecified criteria of worsening respiratory distress and discomfort. From November 2016 to March 2017, 142 infants were allocated to the 2-L/kg/min (2L) flow rate and 144 to the 3-L/kg/min (3L) flow rate. Failure rate was comparable between groups: 38.7% (2L) vs. 38.9% (3L; p = 0.98). Worsening respiratory distress was the most common cause of failure in both groups: 49% (2L) vs. 39% (3L; p = 0.45). In the 3L group, discomfort was more frequent (43% vs. 16%, p = 0.002) and PICU stays were longer (6.4 vs. 5.3 days, p = 0.048). The intubation rates [2.8% (2L) vs. 6.9% (3L), p = 0.17] and durations of invasive [0.2 (2L) vs. 0.5 (3L) days, p = 0.10] and noninvasive [1.4 (2L) vs. 1.6 (3L) days, p = 0.97] ventilation were comparable. No patient had air leak syndrome or died. In young infants with AVB supported with HFNC, 3 L/kg/min did not reduce the risk of failure compared with 2 L/kg/min. This clinical trial was recorded on the National Library of Medicine registry (NCT02824744).
Agile Software Development Methodologies and Practices

Beginning in the mid-1990s, a number of consultants independently created and evolved what later came to be known as agile software development methodologies. Agile methodologies and practices emerged as an attempt to more formally and explicitly embrace higher rates of change in software requirements and customer expectations. Some prominent agile methodologies are Adaptive Software Development, Crystal, Dynamic Systems Development Method, Extreme Programming (XP), Feature-Driven Development (FDD), Pragmatic Programming, and Scrum. This chapter presents the principles that underlie and unite the agile methodologies. Then, 32 practices used in agile methodologies are presented. Finally, three agile methodologies (XP, FDD, and Scrum) are explained. Most often, software development teams select a subset of the agile practices and create their own hybrid software development methodology rather than strictly adhere to all the practices of a predefined agile methodology. Teams that use primarily agile practices are most often smallto medium-sized, colocated teams working on less complex projects. 1. A gile Origins and Manifesto . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2. A gile and Lean Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2 .1.
Face synthesis and recognition from a single image under arbitrary unknown lighting using a spherical harmonic basis morphable model

Understanding and modifying the effects of arbitrary illumination on human faces in a realistic manner is a challenging problem both for face synthesis and recognition. Recent research demonstrates that the set of images of a convex Lambertian object obtained under a wide variety of lighting conditions can be approximated accurately by a low-dimensional linear subspace using spherical harmonics representation. Morphable models are statistical ensembles of facial properties such as shape and texture. In this paper, we integrate spherical harmonics into the morphable model framework, by proposing a 3D spherical harmonic basis morphable model (SHBMM) and demonstrate that any face under arbitrary unknown lighting can be simply represented by three low-dimensional vectors: shape parameters, spherical harmonic basis parameters and illumination coefficients. We show that, with our SHBMM, given one single image under arbitrary unknown lighting, we can remove the illumination effects from the image (face "delighting") and synthesize new images under different illumination conditions (face "re-lighting"). Furthermore, we demonstrate that cast shadows can be detected and subsequently removed by using the image error between the input image and the corresponding rendered image. We also propose two illumination invariant face recognition methods based on the recovered SHBMM parameters and the de-lit images respectively. Experimental results show that using only a single image of a face under unknown lighting, we can achieve high recognition rates and generate photorealistic images of the face under a wide range of illumination conditions, including multiple sources of illumination.
A High-Speed Current-Mode Data Driver With Push-Pull Transient Current Feedforward for Full-HD AMOLED Displays

A push-pull transient current feedforward driver is designed to have a complete push-pull function and loop gain control that enhances the data current drivability. The sink and source current capability of the proposed driver makes it insensitive to the initial voltage levels on the data lines and provides a reduced settling time. The gain control in the positive feedback loop offers a fast settling time without ringing over the complete range of pixel drive currents. The data driver exhibits a settling time of better than 6 μs for drive currents from 20 nA to 5 μA into an equivalent full-HD AMOLED display panel parasitic load of 4 kΩ series resistance and 90 pF shunt capacitance. The driver consumes a static current of 4.5 μA/channel.
Descending and ascending spinal cord evoked potentials from oesophago-vertebral electrical stimulation in normal awake man.

Electrical stimulation of the spinal cord at C7D1 evoked triphasic descending spinal cord evoked potentials (DSCEP) from an oesophago-vertebral recording at D8D8 or D1OD1O. Ascending SCEPs (ASCEP) larger and similar in shape were also observed when the orientation of the stimulating and recording dipoles was reversed. Both SCEPs are in part generated by descending and ascending synchronous excitation of neuronal volume-conducted spinal cord dipoles.
Matching Long Text Documents via Graph Convolutional Networks

Identifying the relationship between two text objects is a core research problem underlying many natural language processing tasks. A wide range of deep learning schemes have been proposed for text matching, mainly focusing on sentence matching, question answering or query document matching. We point out that existing approaches do not perform well at matching long documents, which is critical, for example, to AI-based news article understanding and event or story formation. The reason is that these methods either omit or fail to fully utilize complicated semantic structures in long documents. In this paper, we propose a graph approach to text matching, especially targeting long document matching, such as identifying whether two news articles report the same event in the real world, possibly with different narratives. We propose the Concept Interaction Graph to yield a graph representation for a document, with vertices representing different concepts, each being one or a group of coherent keywords in the document, and with edges representing the interactions between different concepts, connected by sentences in the document. Based on the graph representation of document pairs, we further propose a Siamese Encoded Graph Convolutional Network that learns vertex representations through a Siamese neural network and aggregates the vertex features though Graph Convolutional Networks to generate the matching result. Extensive evaluation of the proposed approach based on two labeled news article datasets created at Tencent for its intelligent news products show that the proposed graph approach to long document matching significantly outperforms a wide range of state-of-the-art methods.
The Long-Term Benefits of Positive Self-Presentation via Profile Pictures, Number of Friends and the Initiation of Relationships on Facebook for Adolescents’ Self-Esteem and the Initiation of Offline Relationships

Social networking sites are a substantial part of adolescents' daily lives. By using a longitudinal approach the current study examined the impact of (a) positive self-presentation, (b) number of friends, and (c) the initiation of online relationships on Facebook on adolescents' self-esteem and their initiation of offline relationships, as well as the mediating role of positive feedback. Questionnaire data were obtained from 217 adolescents (68% girls, mean age 16.7 years) in two waves. Adolescents' positive self-presentation and number of friends were found to be related to a higher frequency of receiving positive feedback, which in turn was negatively associated with self-esteem. However, the number of Facebook friends had a positive impact on self-esteem, and the initiation of online relationships positively influenced the initiation of offline relationships over time, demonstrating that Facebook may be a training ground for increasing adolescents' social skills. Implications and suggestions for future research are provided.
BIRDS OF A FEATHER : Homophily in Social Networks

■ Abstract Similarity breeds connection. This principle—the homophily principle—structures network ties of every type, including marriage, friendship, work, advice, support, information transfer, exchange, comembership, and other types of relationship. The result is that people’s personal networks are homogeneous with regard to many sociodemographic, behavioral, and intrapersonal characteristics. Homophily limits people’s social worlds in a way that has powerful implications for the information they receive, the attitudes they form, and the interactions they experience. Homophily in race and ethnicity creates the strongest divides in our personal environments, with age, religion, education, occupation, and gender following in roughly that order. Geographic propinquity, families, organizations, and isomorphic positions in social systems all create contexts in which homophilous relations form. Ties between nonsimilar individuals also dissolve at a higher rate, which sets the stage for the formation of niches (localized positions) within social space. We argue for more research on: ( a) the basic ecological processes that link organizations, associations, cultural communities, social movements, and many other social forms; ( b) the impact of multiplex ties on the patterns of homophily; and ( c) the dynamics of network change over time through which networks and other social entities co-evolve.
Social flocks: a crowd simulation framework for social network generation, community detection, and collective behavior modeling

This work combines the central ideas from two different areas, crowd simulation and social network analysis, to tackle some existing problems in both areas from a new angle. We present a novel spatio-temporal social crowd simulation framework, Social Flocks, to revisit three essential research problems, (a) generation of social networks, (b) community detection in social networks, (c) modeling collective social behaviors in crowd simulation. Our framework produces social networks that satisfy the properties of high clustering coefficient, low average path length, and power-law degree distribution. It can also be exploited as a novel dynamic model for community detection. Finally our framework can be used to produce real-life collective social behaviors over crowds, including community-guided flocking, leader following, and spatio-social information propagation. Social Flocks can serve as visualization of simulated crowds for domain experts to explore the dynamic effects of the spatial, temporal, and social factors on social networks. In addition, it provides an experimental platform of collective social behaviors for social gaming and movie animations. Social Flocks demo is at http://mslab.csie.ntu.edu.tw/socialflocks/ .