nils-herrmann/clean_scirepeval huggingface dataset:
Development of a small quadruped robot with bi-articular muscle-tendon complex

Hydraulic and pneumatic actuators are used as actuators of robots. They have large capabilities of instantaneous output, but with problems of increase in size and mass, and difficulty for precise control. In contrast, electromagnetic motors have better controllability, lower cost, and smaller size. However, in order to actuate robots, they are usually used with reducers which have high reduction ratio, and it is difficult to realize creature-like dynamic motions such as fast running and high jumping, due to low backdrivability of joints. To solve the problem, we have developed leg mechanisms, which consist of a spring and a damper inspired by bi-articular muscle-tendon complex of animals. The final target is to develop a quadruped robot which can walk, run fast and jump highly like a cat. A cat mainly uses its hind legs in jumping and front legs in landing. It implies that the hind legs play an important role in jumping, and that the front legs do in landing. For this reason, it is necessary to design different leg structures for front and hind legs. In this paper, we develop a new front leg mechanism suitable to a hind leg mechanism which was already made by our group, and make a small quadruped robot. As the result of experiments for dynamic motions, stable running trot at a speed of 3.5 kilometers per hour and forward jumping of 1 body length per jump have been realized by the robot.
Do Chinese and English speakers think about time differently? Failure of replicating Boroditsky (2001)

English uses the horizontal spatial metaphors to express time (e.g., the good days ahead of us). Chinese also uses the vertical metaphors (e.g., 'the month above' to mean last month). Do Chinese speakers, then, think about time in a different way than English speakers? Boroditsky [Boroditsky, L. (2001). Does language shape thought? Mandarin and English speakers' conceptions of time. Cognitive Psychology, 43(1), 1-22] claimed that they do, and went on to conclude that 'language is a powerful tool in shaping habitual thought about abstract domains' (such as time). By estimating the frequency of usage, we found that Chinese speakers actually use the horizontal spatial metaphors more often than the vertical metaphors. This offered no logical ground for Boroditsky's claim. We were also unable to replicate her experiments in four different attempts. We conclude that Chinese speakers do not think about time in a different way than English speakers just because Chinese also uses the vertical spatial metaphors to express time.
Nutrient timing revisited: is there a post-exercise anabolic window?

Nutrient timing is a popular nutritional strategy that involves the consumption of combinations of nutrients--primarily protein and carbohydrate--in and around an exercise session. Some have claimed that this approach can produce dramatic improvements in body composition. It has even been postulated that the timing of nutritional consumption may be more important than the absolute daily intake of nutrients. The post-exercise period is widely considered the most critical part of nutrient timing. Theoretically, consuming the proper ratio of nutrients during this time not only initiates the rebuilding of damaged muscle tissue and restoration of energy reserves, but it Does So in a supercompensated fashion that enhances both body composition and exercise performance. Several researchers have made reference to an anabolic "window of opportunity" whereby a limited time exists after training to optimize training-related muscular adaptations. However, the importance - and even the existence - of a post-exercise 'window' can vary according to a number of factors. Not only is nutrient timing research open to question in terms of applicability, but recent evidence has directly challenged the classical view of the relevance of post-exercise nutritional intake with respect to anabolism. Therefore, the purpose of this paper will be twofold: 1) to review the existing literature on the effects of nutrient timing with respect to post-exercise muscular adaptations, and; 2) to draw relevant conclusions that allow practical, evidence-based nutritional recommendations to be made for maximizing the anabolic response to exercise.
Music Generation with Deep Learning

The use of deep learning to solve the problems in literary arts has been a recent trend that gained a lot of attention and automated generation of music has been an active area. This project deals with the generation of music using raw audio files in the frequency domain relying on various LSTM architectures. Fully connected and convolutional layers are used along with LSTM’s to capture rich features in the frequency domain and increase the quality of music generated. The work is focused on unconstrained music generation and uses no information about musical structure(notes or chords) to aid learning.The music generated from various architectures are compared using blind fold tests. Using the raw audio to train models is the direction to tapping the enormous amount of mp3 files that exist over the internet without requiring the manual effort to make structured MIDI files. Moreover, not all audio files can be represented with MIDI files making the study of these models an interesting prospect to the future of such models.
Session 4: CVD, diabetes and cancer: Evidence for the use of the Mediterranean diet in patients with CHD.

Diet is associated with the development of CHD. The incidence of CHD is lower in southern European countries than in northern European countries and it has been proposed that this difference may be a result of diet. The traditional Mediterranean diet emphasises a high intake of fruits, vegetables, bread, other forms of cereals, potatoes, beans, nuts and seeds. It includes olive oil as a major fat source and dairy products, fish and poultry are consumed in low to moderate amounts. Many observational studies have shown that the Mediterranean diet is associated with reduced risk of CHD, and this result has been confirmed by meta-analysis, while a single randomised controlled trial, the Lyon Diet Heart study, has shown a reduction in CHD risk in subjects following the Mediterranean diet in the secondary prevention setting. However, it is uncertain whether the benefits of the Mediterranean diet are transferable to other non-Mediterranean populations and whether the effects of the Mediterranean diet will still be feasible in light of the changes in pharmacological therapy seen in patients with CHD since the Lyon Diet Heart study was conducted. Further randomised controlled trials are required and if the risk-reducing effect is confirmed then the best methods to effectively deliver this public health message worldwide need to be considered.
Workplace violence in the health sector Country

Thailand and an additional Australian study Synthesis report by Vittorio di Martino 2002-Workplace violence in the health sector.doc iii Foreword Violence at work has become an alarming phenomenon worldwide. The real size of the problem is largely unknown and recent information shows that the current knowledge is only the tip of the iceberg. The enormous cost of violence at work for the individual, the workplace and the community at large is becoming more and more apparent. Although incidents of violence are known to occur in all work environments, some employment sectors are particularly exposed to it. Violence includes both physical and non-physical violence. Violence is defined as being destructive towards another person. It finds its expression in physical assault, homicide, verbal abuse, bullying, sexual harassment and threat. Violence at work is often considered to be just a reflection of the more general and increasing phenomenon of violence in many areas of social life which has to be dealt with at the level of the whole society. Its prevalence has, however, increased at the workplace, traditionally viewed as a violence-free environment. Employers and workers are equally interested in the prevention of violence at the workplace. Society at large has a stake in preventing violence spreading to working life and recognizing the potential of the workplace by removing such obstacles to productivity, development and peace. Violence is common to such an extent among workers who have direct contact with people in distress, that it may be considered an inevitable part of the job. This is often the case in the health sector (violence in this sector may constitute almost a quarter of all violence at work). 1 While ambulance staff are reported to be at greatest risk, nurses are three times more likely on average to experience violence in the workplace than other occupational groups. Since the large majority of the health workforce is female, the gender dimension of the problem is very evident. Besides concern about the human right of health workers to have a decent work environment, there is concern about the consequences of violence at work. These have a significant impact on the effectiveness of health systems, particularly in developing countries. The equal access of people to primary health care is endangered if a scarce human resource, the health workers, feel under threat in certain geographical and social environments, in situations of general conflict, in work situations where transport …
Mechanical and Aerospace Engineering

Mechanical engineers apply principles of motion, energy, force, materials, and mathematics to design and analyze a wide variety of products and systems. The field requires an understanding of core concepts including mechanics, kinematics, thermodynamics, heat transfer, materials science and controls. Mechanical engineers use these core principles along with tools like computer-aided engineering and product life cycle management to design and analyze manufacturing plants, industrial equipment and machinery, heating and cooling systems, automotive systems, aircraft, robotics, medical devices, and more. Today, mechanical engineers are pursuing developments in such fields as composites, mechatronics, and nanotechnology, and are helping to create a more sustainable future.
Language control and lexical competition in bilinguals: an event-related FMRI study.

Language selection (or control) refers to the cognitive mechanism that controls which language to use at a given moment and context. It allows bilinguals to selectively communicate in one target language while minimizing the interferences from the nontarget language. Previous studies have suggested the participation in language control of different brain areas. However, the question remains whether the selection of one language among others relies on a language-specific neural module or general executive regions that also allow switching between different competing behavioral responses including the switching between various linguistic registers. In this functional magnetic resonance imaging study, we investigated the neural correlates of language selection processes in German-French bilingual subjects during picture naming in different monolingual and bilingual selection contexts. We show that naming in the first language in the bilingual context (compared with monolingual contexts) increased activation in the left caudate and anterior cingulate cortex. Furthermore, the activation of these areas is even more extended when the subjects are using a second weaker language. These findings show that language control processes engaged in contexts during which both languages must remain active recruit the left caudate and the anterior cingulate cortex (ACC) in a manner that can be distinguished from areas engaged in intralanguage task switching.
Opening Learning Management Systems to Personal Learning Environments

New ICT technologies are continuously introducing changes in the way in which society generates, shares and access information. This is changing what society expects and requires of education. eLearning is acting as a vector of this change, introducing pervasive transformations in and out of the classroom. But with Learning Management Systems (LMS) users have reached a plateau of productivity and stability. At the same time outside the walled garden of the LMS new transformative tools, services and ways of learning are already in use, within the PLE and PLN paradigms. The stability and maturity of the LMS may become yet another resistance factor working against the introduction of innovations. New tools and trends cannot be ignored, and this is the reason why learning platforms should become open and flexible environments. In the course of this article the reasons for this change and how it may be addressed will be discussed, together with a proposal for architecture based on Moodle.
Recognizing Facial Expressions Automatically from Video

Facial expressions, resulting from movements of the facial muscles, are the face changes in response to a person’s internal emotional states, intentions, or social communications. There is a considerable history associated with the study on facial expressions. Darwin (1872) was the first to describe in details the specific facial expressions associated with emotions in animals and humans, who argued that all mammals show emotions reliably in their faces. Since that, facial expression analysis has been a area of great research interest for behavioral scientists (Ekman, Friesen, and Hager, 2002). Psychological studies (Mehrabian, 1968; Ambady and Rosenthal, 1992) suggest that facial expressions, as the main mode for non-verbal communication, play a vital role in human face-to-face communication. For illustration, we show some examples of facial expressions in Fig. 1. Computer recognition of facial expressions has many important applications in intelligent human-computer interaction, computer animation, surveillance and security, medical diagnosis, law enforcement, and awareness systems (Shan, 2007). Therefore, it has been an active research topic in multiple disciplines such as psychology, cognitive science, human-computer interaction, and pattern recognition. Meanwhile, as a promising unobtrusive solution, automatic facial expression analysis from video or images has received much attention in last two decades (Pantic and Rothkrantz, 2000a; Fasel and Luettin, 2003; Tian, Kanade, and Cohn, 2005; Pantic and Bartlett, 2007). This chapter introduces recent advances in computer recognition of facial expressions. Firstly, we describe the problem space, which includes multiple dimensions: level of description, static versus dynamic expression, facial feature extraction and
Multistation proprioceptive exercise program prevents ankle injuries in basketball.

To investigate the effectiveness of a multistation proprioceptive exercise program for the prevention of ankle injuries in basketball players using a prospective randomized controlled trial in combination with biomechanical tests of neuromuscular performance.



A total of 232 players participated in the study and were randomly assigned to a training or control group following the CONSORT statement. The training group performed a multistation proprioceptive exercise program, and the control group continued with their normal workout routines. During one competitive basketball season, the number of ankle injuries was counted and related to the number of sports participation sessions using logistic regression. Additional biomechanical pre–post tests (angle reproduction and postural sway) were performed in both groups to investigate the effects on neuromuscular performance.



In the control group, 21 injuries occurred, whereas in the training group, 7 injuries occurred. The risk for sustaining an ankle injury was significantly reduced in the training group by approximately 65%.  The corresponding number needed to treat was 7. Additional biomechanical tests revealed significant improvements in joint position sense and single-limb stance in the training group.



The multistation proprioceptive exercise program effectively prevented ankle injuries in basketball players. Analysis of number needed to treat clearly showed the relatively low prevention effort that is necessary to avoid an ankle injury. Additional biomechanical tests confirmed the neuromuscular effect and confirmed a relationship between injury prevention and altered neuromuscular performance. With this knowledge, proprioceptive training may be optimized to specifically address the demands in various athletic activities.
The acquisition of gender labels in infancy : Implications for sex-typed play

Two aspects of children’s early gender development the spontaneous production of gender labels and sex-typed play were examined longitudinally in a sample of 82 children. Survival analysis, a statistical technique well suited to questions involving developmental transitions, was used to investigate the timing of the onset of children’s gender labeling as based on mothers’ biweekly reports on their children’s language from 9 through 21 months. Videotapes of children’s play both alone and with mother at 17 and 21 months were independently analyzed for play with gender stereotyped and neutral toys. Finally, the relation between gender labeling and sex-typed play was examined. Children transitioned to using gender labels at approximately 19 months on average. Although girls and boys showed similar patterns in the development of gender labeling, girls began labeling significantly earlier than boys. Modest sex differences in play were present at 17 months and increased at 21 months. Gender labeling predicted increases in sex-typed play, suggesting that knowledge of gender categories might influence sex-typing before the age of 2.
CURIOSITY AND MOTIVATION TOWARD VISUAL INFORMATION

Curiosity is thought to be an intrinsically motivated driving force for seeking information. Thus, the opportunity for an information gain (IG) should instil curiosity in humans and result in information gathering actions. To investigate if, and how, information acts as an intrinsic reward, a search task was set in a context of blurred background images which could be revealed by iterative clicking. The search task was designed such that it prevented efficient IG about the underlying images. Participants therefore had to trade between clicking regions with high search target probability or high expected image content information. Image content IG was established from “information-maps” based on participants exploration with the intention of understanding (1) the main theme of the image and (2) how interesting the image might appear to others. Note that IG is in this thesis not identical with the information theoretic concept of information gain, the quantities are however probably related. It was hypothesised that participants would be distracted by visually informative regions and that images independently rated as more interesting would yield higher image based IG. It was also hypothesised that image based IG would increase as a function of time. Results show that participants sometimes explored images driven by curiosity, and that there was considerable individual variation in which images participants were curious about. Independent interest ratings did not account for image based IG. The level of IG increased over trials, interestingly without affecting participants’ performance on the visual search task designed to prevent IG. Results support that IG is rewarding as participants learned to optimize IG over trials without compromising performance on the extrinsically motivated search; managing to both keep the cake and eat it.
Camera Style Adaptation for Person Re-identification

Being a cross-camera retrieval task, person re-identification suffers from image style variations caused by different cameras. The art implicitly addresses this problem by learning a camera-invariant descriptor subspace. In this paper, we explicitly consider this challenge by introducing camera style (CamStyle) adaptation. CamStyle can serve as a data augmentation approach that smooths the camera style disparities. Specifically, with CycleGAN, labeled training images can be style-transferred to each camera, and, along with the original training samples, form the augmented training set. This method, while increasing data diversity against over-fitting, also incurs a considerable level of noise. In the effort to alleviate the impact of noise, the label smooth regularization (LSR) is adopted. The vanilla version of our method (without LSR) performs reasonably well on few-camera systems in which over-fitting often occurs. With LSR, we demonstrate consistent improvement in all systems regardless of the extent of over-fitting. We also report competitive accuracy compared with the state of the art. Code is available at: https://github.com/zhunzhong07/CamStyle
Big Sensor Data Systems for Smart Cities

Recent advances in large-scale networked sensor technologies and the explosive growth in big data computing have made it possible for new application deployments in smart cities ecosystems. In this paper, we define big sensor data systems, and survey progress made in the development and applications of big sensor data research. We classify the existing research based on their characteristics and smart city layer challenges. Next, we discuss several applications for big sensor data systems, and explore the potential of large-scale networked sensor technologies for smart cities in the big data era. We conclude this paper by discussing future work directions highlighting some futuristic applications. The aim of this survey paper is to be useful for researchers to get insights into this important area, and motivate the development of practical solutions toward deployment in smart cities.
Designing Engaging Games Using Bayesian Optimization

We use Bayesian optimization methods to design games that maximize user engagement. Participants are paid to try a game for several minutes, at which point they can quit or continue to play voluntarily with no further compensation. Engagement is measured by player persistence, projections of how long others will play, and a post-game survey. Using Gaussian process surrogate-based optimization, we conduct efficient experiments to identify game design characteristics---specifically those influencing difficulty---that lead to maximal engagement. We study two games requiring trajectory planning, the difficulty of each is determined by a three-dimensional continuous design space. Two of the design dimensions manipulate the game in user-transparent manner (e.g., the spacing of obstacles), the third in a subtle and possibly covert manner (incremental trajectory corrections). Converging results indicate that overt difficulty manipulations are effective in modulating engagement only when combined with the covert manipulation, suggesting the critical role of a user's self-perception of competence.
Mining Association Rules from NoSQL data bases using MapReduce Fuzzy Association Rule Mining Algorithm

Big Data trepidations enormous tome, intricate, emergent records sets with several, self-directed bases. With the fast growth of networking, data storage, and the data pool capacity, Big Data is now quickly escalating in all learning and engineering purviews, including physical, organic and biomedical sciences. In order to get use of these huge and heterogeneous data, data mining is a technique to get utilization of such data. Data mining is also called as facts discovery in databases which is the non-trivial process of detecting the valid, novel, hypothetically beneficial and eventually comprehensible acquaintance in outsized scale data. But the existing data mining techniques are not suitable for such heterogeneous data. In this paper we are proposing a map-reduced based fuzzy based data mining technique.