nils-herrmann/clean_scirepeval huggingface dataset:
Flavonoid-rich orange juice is associated with acute improvements in cognitive function in healthy middle-aged males

Epidemiological evidence suggests that chronic consumption of fruit-based flavonoids is associated with cognitive benefits; however, the acute effects of flavonoid-rich (FR) drinks on cognitive function in the immediate postprandial period require examination. The objective was to investigate whether consumption of FR orange juice is associated with acute cognitive benefits over 6 h in healthy middle-aged adults.



Males aged 30-65 consumed a 240-ml FR orange juice (272 mg) and a calorie-matched placebo in a randomized, double-blind, counterbalanced order on 2 days separated by a 2-week washout. Cognitive function and subjective mood were assessed at baseline (prior to drink consumption) and 2 and 6 h post consumption. The cognitive battery included eight individual cognitive tests. A standardized breakfast was consumed prior to the baseline measures, and a standardized lunch was consumed 3 h post-drink consumption.



Change from baseline analysis revealed that performance on tests of executive function and psychomotor speed was significantly better following the FR drink compared to the placebo. The effects of objective cognitive function were supported by significant benefits for subjective alertness following the FR drink relative to the placebo.



These data demonstrate that consumption of FR orange juice can acutely enhance objective and subjective cognition over the course of 6 h in healthy middle-aged adults.
AI and Opinion Mining

The advent of Web 2.0 and social media content has stirred much excitement and created abundant opportunities for understanding the opinions of the general public and consumers toward social events, political movements, company strategies, marketing campaigns, and product preferences. Many new and exciting social, geopolitical, and business-related research questions can be answered by analyzing the thousands, even millions, of comments and responses expressed in various blogs (such as the blogosphere), forums (such as Yahoo Forums), social media and social network sites (including YouTube, Facebook, and Flikr), virtual worlds (such as Second Life), and tweets (Twitter). Opinion mining, a subdiscipline within data mining and computational linguistics, refers to the computational techniques for extracting, classifying, understanding, and assessing the opinions expressed in various online news sources, social media comments, and other user-generated content. Sentiment analysis is often used in opinion mining to identify sentiment, affect, subjectivity, and other emotional states in online text.
The Social Dynamics of Pair Programming

This paper presents data from a four month ethnographic study of professional pair programmers from two software development teams. Contrary to the current conception of pair programmers, the pairs in this study did not hew to the separate roles of "driver" and "navigator". Instead, the observed programmers moved together through different phases of the task, considering and discussing issues at the same strategic "range" or level of abstraction and in largely the same role. This form of interaction was reinforced by frequent switches in keyboard control during pairing and the use of dual keyboards. The distribution of expertise among the members of a pair had a strong influence on the tenor of pair programming interaction. Keyboard control had a consistent secondary effect on decision-making within the pair. These findings have implications for software development managers and practitioners as well as for the design of software development tools.
Articulated swimming creatures

We present a general approach to creating realistic swimming behavior for a given articulated creature body. The two main components of our method are creature/fluid simulation and the optimization of the creature motion parameters. We simulate two-way coupling between the fluid and the articulated body by solving a linear system that matches acceleration at fluid/solid boundaries and that also enforces fluid incompressibility. The swimming motion of a given creature is described as a set of periodic functions, one for each joint degree of freedom. We optimize over the space of these functions in order to find a motion that causes the creature to swim straight and stay within a given energy budget. Our creatures can perform path following by first training appropriate turning maneuvers through offline optimization and then selecting between these motions to track the given path. We present results for a clownfish, an eel, a sea turtle, a manta ray and a frog, and in each case the resulting motion is a good match to the real-world animals. We also demonstrate a plausible swimming gait for a fictional creature that has no real-world counterpart.
Grasping Unknown Objects in Clutter by Superquadric Representation

In this paper, a quick and efficient method is presented for grasping unknown objects in clutter. The grasping method relies on real-time superquadric (SQ) representation of partial view objects and incomplete object modelling, well suited for unknown symmetric objects in cluttered scenarios which is followed by optimized antipodal grasping. The incomplete object models are processed through a mirroring algorithm that assumes symmetry to first create an approximate complete model and then fit for SQ representation. The grasping algorithm is designed for maximum force balance and stability, taking advantage of the quick retrieval of dimension and surface curvature information from the SQ parameters. The pose of the SQs with respect to the direction of gravity is calculated and used together with the parameters of the SQs and specification of the gripper, to select the best direction of approach and contact points. The SQ fitting method has been tested on custom datasets containing objects in isolation as well as in clutter. The grasping algorithm is evaluated on a PR2 robot and real time results are presented. Initial results indicate that though the method is based on simplistic shape information, it outperforms other learning based grasping algorithms that also work in clutter in terms of time-efficiency and accuracy.
Numerical Solution of Calculus of Variation Problems via Exponential Spline Method

In this work, an exponential spline method is developed and a nalyzed for approximating solutions of calculus of variati ons problems. The method uses a spline interpolant, which is con structed from exponential spline. It is proved to be secondrder convergent. Finally some illustrative examples are includ ed to demonstrate the applicability of the new technique. Nu merical results confirm the order of convergence predicted by the analysis.
Using confidence intervals in within-subject designs.

We argue that to best comprehend many data sets, plotting judiciously selected sample statistics with associated confidence intervals can usefully supplement, or even replace, standard hypothesis-testing procedures. We note that most social science statistics textbooks limit discussion of confidence intervals to their use in between-subject designs. Our central purpose in this article is to describe how to compute an analogous confidence interval that can be used in within-subject designs. This confidence interval rests on the reasoning that because between-subject variance typically plays no role in statistical analyses of within-subject designs, it can legitimately be ignored; hence, an appropriate confidence interval can be based on the standard within-subject error term-that is, on the variability due to the subject × condition interaction. Computation of such a confidence interval is simple and is embodied in Equation 2 on p. 482 of this article. This confidence interval has two useful properties. First, it is based on the same error term as is the corresponding analysis of variance, and hence leads to comparable conclusions. Second, it is related by a known factor (√2) to a confidence interval of the difference between sample means; accordingly, it can be used to infer the faith one can put in some pattern of sample means as a reflection of the underlying pattern of population means. These two properties correspond to analogous properties of the more widely used between-subject confidence interval.
Home security system based on PIC18F452 microcontroller

We used PIC18F452 microcontroller for hardware and software implementation of our home security system design. Based on PIC18F452, our system can monitor doors and windows of a house and can set alarm and warming signal to a nearest police station if anybody tries to break in. This security system also provides the functionality to identify the residents ID card to get access to the house without turning on the warning signal and alarm. Also, the security system provides a status that is not monitoring the door and windows since there is some possibility that the host do not want the system always checks the status of their house.
An exact algorithm for the Maximum Leaf Spanning Tree problem

Given an undirected graph G with n nodes, the Maximum Leaf Spanning Tree problem asks to find a spanning tree of G with as many leaves as possible. When parameterized in the number of leaves k, this problem can be solved in time O(4poly(n)) using a simple branching algorithm introduced by a subset of the authors [13]. Daligault, Gutin, Kim, and Yeo  improved this branching algorithm and obtained a running time of O(3.72poly(n)). In this paper, we study the problem from an exact exponential time point of view, where it is equivalent to the Connected Dominating Set problem. For this problem Fomin, Grandoni, and Kratsch showed how to break the Ω(2) barrier and proposed an O(1.9407) time algorithm . Based on some properties of [6] and [13], we establish a branching algorithm whose running time of O(1.8966) has been analyzed using the Measure-and-Conquer technique. Finally we provide a lower bound of Ω(1.4422) for the worst case running time of our algorithm.
RtGender: A Corpus for Studying Differential Responses to Gender

Like many social variables, gender pervasively influences how people communicate with one another. However, prior computational work has largely focused on linguistic gender difference and communications about gender, rather than communications directed to people of that gender, in part due to lack of data. Here, we fill a critical need by introducing a multi-genre corpus of more than 25M comments from five socially and topically diverse sources tagged for the gender of the addressee. Using these data, we describe pilot studies on how differential responses to gender can be measured and analyzed and present 30k annotations for the sentiment and relevance of these responses, showing that across our datasets responses to women are more likely to be emotive and about the speaker as an individual (rather than about the content being responded to). Our dataset enables studying socially important questions like gender bias, and has potential uses for downstream applications such as dialogue systems, gender detection or obfuscation, and debiasing language generation.
Tarsal tunnel syndrome.

Tarsal tunnel syndrome, unlike its similar sounding counterpart in the hand, is a significantly misunderstood clinical entity. Confusion concerning the anatomy involved, the presenting symptomatology, the appropriateness and significance of various diagnostic tests, conservative and surgical management, and, finally, the variability of reported results of surgical intervention attests to the lack of consensus surrounding this condition. The terminology involved in various diagnoses for chronic heel pain is also a hodgepodge of poorly understood entities.
Men ’ s attractiveness predicts their preference for female facial femininity when judging for short-term , but not long-term , partners

It is well established that women’s preferences for masculinity are contingent on their own market-value and the duration of the sought relationship, but few studies have investigated similar effects in men. Here, we tested whether men’s attractiveness predicts their preferences for feminine face shape in women when judging for longand short-term relationship partners. We found that attractive men expressed a stronger preference for facial femininity compared to less attractive men. The relationship was evident when men judged women for a short-term, but not for a long-term, relationship. These findings suggest that market-value may influence men’s preferences for feminine characteristics in women’s faces and indicate that men’s preferences may be subject to facultative variation to a greater degree than was previously thought.
Formal verification and simulation for platform screen doors and collision avoidance in subway control systems

For hybrid systems, hybrid automata-based tools are capable of verification, while Matlab Simulink/Stateflow is proficient in simulation. We propose a co-verification procedure, in which the verification tool SpaceEx/PHAVer and simulation tool Matlab are integrated to analyze and verify hybrid systems. For the application of this procedure, a platform screen door system (PSDS, a subsystem of the subway control system), is modeled with hybrid automata and Simulink/Stateflow charts, respectively. The models of PSDS are simulated by Matlab and verified by SpaceEx/PHAVer. The simulation and verification results indicate that the sandwiched situation can be avoided under time interval conditions. We improve the model with four trains and four stations on a subway line and analyze the urgent control scenario for the safety distance requirement. In this paper, the Simulink/Stateflow model is a refinement of the SpaceEx/PHAVer model, which is closer to a final implementation. Moreover, the two models are complementary for some features (e.g.,visualization of simulation, correctness proving by verification), stressing different aspects of the overall system and permitting complementary analysis techniques, i.e., verification versus simulation. We conclude that this integration procedure is competent in verifying subway control systems.
Artificial Neural Networks for Solving Double Dummy Bridge Problems

This paper describes the results of applying artificial neural networks to the double dummy bridge problem. Several feedforward neural networks were trained using resilient backpropagation algorithm to estimate the number of tricks to take by players NS in fully revealed contract bridge deals. Training deals were the only data presented to the networks. The best networks were able to perfectly point the number of tricks in more than one third of deals and gained about 80% accuracy when one trick error was permitted. Only in less than 5% of deals the error exceeded 2 tricks.
Joint inference for cross-document information extraction

Previous information extraction (IE) systems are typically organized as a pipeline architecture of separated stages which make independent local decisions. When the data grows beyond some certain size, the extracted facts become inter-dependent and thus we can take advantage of information redundancy to conduct reasoning across documents and improve the performance of IE. We describe a joint inference approach based on information network structure to conduct cross-fact reasoning with an integer linear programming framework. Without using any additional labeled data this new method obtained 13.7%-24.4% user browsing cost reduction over a state-of-the-art IE system which extracts various types of facts independently.
A Modified Quasi-Yagi Antenna With a New Compact Microstrip-to-Coplanar Strip Transition Using Artificial Transmission Lines

We present a modified quasi-Yagi antenna for use in WLAN access points. The antenna uses a new microstrip-to-coplanar strip (CPS) transition, consisting of a tapered microstrip input, T-junction, conventional 50-ohm microstrip line, and three artificial transmission line (ATL) sections. The design concept, mode conversion scheme, and simulated and experimental S-parameters of the transition are discussed first. It features a compact size, and a 3dB-insertion loss bandwidth of 78.6%. Based on the transition, a modified quasi-Yagi antenna is demonstrated. In addition to the new transition, the antenna consists of a CPS feed line, a meandered dipole, and a parasitic element. The meandered dipole can substantially increase to the front-to-back ratio of the antenna without sacrificing the operating bandwidth. The parasitic element is placed in close proximity to the driven element to improve impedance bandwidth and radiation characteristics. The antenna exhibits excellent end-fire radiation with a front-to-back ratio of greater than 15 dB. It features a moderate gain around 4 dBi, and a fractional bandwidth of 38.3%. We carefully investigate the concept, methodology, and experimental results of the proposed antenna.
Normative curves of fetal nasal bone length for the ethnic Chinese population.

The purpose of this study is to determine the association between fetal nasal bone length (NBL) and gestational age (GA), biparietal diameter (BPD) and head circumference (HC) in women undergoing prenatal assessments and Down syndrome screening.



Cross-sectional data were obtained from 3,003 women with singleton pregnancies who underwent a prenatal ultrasound examination at the Department of Obstetrics and Gynecology, Cheng Hsin General Hospital between August 2006 and July 2009.



Statistical analyses involved linear regression. NBL with GA, BPD and HC as measured between 14(+0) and 35(+6) weeks of gestation were linearly related.



Using multiple parameters (GA, BPD and HC) to estimate NBL is more accurate than using than using GA or BPD or HC alone, as indicated by the higher predictive value.
A 0.45pJ/conv-step 1.2Gs/s 6b full-Nyquist non-calibrated flash ADC in 45nm CMOS and its scaling behavior

A 6-bit 1.2 Gs/s non-calibrated flash ADC in a standard 45nm CMOS process, that achieves 0.45pJ/conv-step at full Nyquist bandwidth, is presented. Power efficient operation is achieved by a full optimization of amplifier blocks, and by innovations in the comparator and encoding stage. The performance of a non-calibrated flash ADC is directly related to device properties; a scaling analysis of our ADC in and across CMOS technologies gives insight into the excellent usability of 45nm technology for AD converter design.
Calibration methods for a multi-channel multi-frequency EIT system.

Multi-channel multi-frequency electrical impedance tomography (EIT) systems require a careful calibration to minimize systematic errors. We describe novel calibration methods for the recently developed KHU Mark1 EIT system. Current source calibration includes maximization of output resistance and minimization of output capacitance using multiple generalized impedance converters. Phase and gain calibrations are used for voltmeters. Phase calibration nulls out the total system phase shift in measured voltage data. Gain calibrations are performed in two steps of intra- and inter-channel calibrations. Intra-channel calibration for each voltmeter compensates frequency dependence of its voltage gain and also discrepancy between design and actual gains. Inter-channel calibration compensates channel-dependent voltage gains of all voltmeters. Using the calibration methods described in this paper, we obtained 1 MOmega minimal output impedance of the current source in the frequency range 10 Hz-500 kHz. The reciprocity error was as small as 0.05% after intra- and inter-channel voltmeter calibrations. To demonstrate effects of calibration in reconstructed images, we used a homogenous phantom from which uniform images should be produced. Reconstructed time- and frequency-difference images using uncalibrated data showed spurious anomalies. By using calibrated data, standard deviations of time- and frequency-difference images of the homogenous phantom were reduced by about 40% and 90%, respectively.
A Visible Light Communication Link Protection Mechanism for Smart Factory

In recent years, wireless networks and applications have achieved marvelous successes in government, enterprise, home, and personal communication systems. The desired features of wireless communications draw lots of attention to the industrial communication and expected to bring benefits such as reduce deployment and maintenance after employed. However, the industrial communication system required real-time communication, which means the control systems in the factory are required accurate control and rapid communication, such as the industrial motion control system. In this type of application, the communication system performance and efficiency will be evaluated to ensure it applicable to the industrial network. However, there are a few original issues in the wireless communication, such as fading, multipath propagation and interference problems, which will affect the reliability and performance of industrial communication system operation. Therefore, we proposed a connection protection mechanism that cooperates with wireless network and visible light communication to achieve reliability and performance in industrial communication network. We will consider implementing this mechanism by using industrial wireless Ethernet in the near future.
Microwaves-Based High Sensitivity Sensors for Crack Detection in Metallic Materials

This paper presents a highly sensitive sensor for crack detection in metallic surfaces. The sensor is inspired by complementary split-ring resonators which have dimensions much smaller than the excitation’s wavelength. The entire sensor is etched in the ground plane of a microstrip line and fabricated using printed circuit board technology. Compared to available microwave techniques, the sensor introduced here has key advantages including high sensitivity, increased dynamic range, spatial resolution, design simplicity, selectivity, and scalability. Experimental measurements showed that a surface crack having 200-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> width and 2-mm depth gives a shift in the resonance frequency of 1.5 GHz. This resonance frequency shift exceeds what can be achieved using other sensors operating in the low GHz frequency regime by a significant margin. In addition, using numerical simulation, we showed that the new sensor is able to resolve a 10-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula>-wide crack (equivalent to <inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>/4000) with 180-MHz shift in the resonance frequency.
Towards automatic personalised content creation for racing games

Evolutionary algorithms are commonly used to create high-performing strategies or agents for computer games. In this paper, we instead choose to evolve the racing tracks in a car racing game. An evolvable track representation is devised, and a multiobjective evolutionary algorithm maximises the entertainment value of the track relative to a particular human player. This requires a way to create accurate models of players' driving styles, as well as a tentative definition of when a racing track is fun, both of which are provided. We believe this approach opens up interesting new research questions and is potentially applicable to commercial racing games.
Deep Face Beautification

The beautification of human photos usually requires professional editing softwares, which are difficult for most users. In this technical demonstration, we propose a deep face beautification framework, which is able to automatically modify the geometrical structure of a face so as to boost the attractiveness. A learning based approach is adopted to capture the underlying relations between the facial shape and the attractiveness via training the Deep Beauty Predictor (DBP). Relying on the pre-trained DBP, we construct the BeAuty SHaper (BASH) to infer the "flows" of landmarks towards the maximal aesthetic level. BASH modifies the facial landmarks with the direct guidance of the beauty score estimated by DBP.