nils-herrmann/clean_scirepeval huggingface dataset:
Augmenting Cognition: Reviewing the Symbiotic Relation Between Man and Machine

One of the goals of augmented cognition is creation of adaptive human-machine collaboration that continually optimizes performance of the human-machine system. Augmented Cognition aims to compensate for temporal limitations in human information processing, for instance in the case of overload, cognitive lockup, and underload. Adaptive behavior, however, may also have undesirable side effects. The dynamics of adaptive support may be unpredictable and may lead to human factors problems such as mode errors, ‘out-of-the-loop’ problems, and trust related issues. One of the most critical challenges in developing adaptive human-machine collaboration concerns system mitigations. A combination of performance, effort and task information should be taken into account for mitigation strategies. This paper concludes with the presentation of an iterative cognitive engineering framework, which addresses the adaptation strategy of the human and machine in an appropriate manner carefully weighing the costs and benefits.
Disentangling Factors of Variation for Facial Expression Recognition

We propose a semi-supervised approach to solve the task of emotion recognition in 2D face images using recent ideas in deep learning for handling the factors of variation present in data. An emotion classification algorithm should be both robust to (1) remaining variations due to the pose of the face in the image after centering and alignment, (2) the identity or morphology of the face. In order to achieve this invariance, we propose to learn a hierarchy of features in which we gradually filter the factors of variation arising from both (1) and (2). We address (1) by using a multi-scale contractive convolutional network (CCNET) in order to obtain invariance to translations of the facial traits in the image. Using the feature representation produced by the CCNET, we train a Contractive Discriminative Analysis (CDA) feature extractor, a novel variant of the Contractive Auto-Encoder (CAE), designed to learn a representation separating out the emotion-related factors from the others (which mostly capture the subject identity, and what is left of pose after the CCNET). This system beats the state-of-the-art on a recently proposed dataset for facial expression recognition, the Toronto Face Database, moving the state-of-art accuracy from 82.4% to 85.0%, while the CCNET and CDA improve accuracy of a standard CAE by 8%.
Time- and Space-Efficient Sliding Window Top-k Query Processing

A sliding window top-k (top-k/w) query monitors incoming data stream objects within a sliding window of size w to identify the k highest-ranked objects with respect to a given scoring function over time. Processing of such queries is challenging because, even when an object is not a top-k/w object at the time when it enters the processing system, it might become one in the future. Thus a set of potential top-k/w objects has to be stored in memory while its size should be minimized to efficiently cope with high data streaming rates. Existing approaches typically store top-k/w and candidate sliding window objects in a k-skyband over a two-dimensional score-time space. However, due to continuous changes of the k-skyband, its maintenance is quite costly. Probabilistic k-skyband is a novel data structure storing data stream objects from a sliding window with significant probability to become top-k/w objects in future. Continuous probabilistic k-skyband maintenance offers considerably improved runtime performance compared to k-skyband maintenance, especially for large values of k, at the expense of a small and controllable error rate. We propose two possible probabilistic k-skyband usages: (i) When it is used to process all sliding window objects, the resulting top-k/w algorithm is approximate and adequate for processing random-order data streams. (ii) When probabilistic k-skyband is used to process only a subset of most recent sliding window objects, it can improve the runtime performance of continuous k-skyband maintenance, resulting in a novel exact top-k/w algorithm. Our experimental evaluation systematically compares different top-k/w processing algorithms and shows that while competing algorithms offer either time efficiency at the expanse of space efficiency or vice-versa, our algorithms based on the probabilistic k-skyband are both time and space efficient.
Clarifying the roles of homeostasis and allostasis in physiological regulation.

Homeostasis, the dominant explanatory framework for physiological regulation, has undergone significant revision in recent years, with contemporary models differing significantly from the original formulation. Allostasis, an alternative view of physiological regulation, goes beyond its homeostatic roots, offering novel insights relevant to our understanding and treatment of several chronic health conditions. Despite growing enthusiasm for allostasis, the concept remains diffuse, due in part to ambiguity as to how the term is understood and used, impeding meaningful translational and clinical research on allostasis. Here, we provide a more focused understanding of homeostasis and allostasis by explaining how both play a role in physiological regulation, and a critical analysis of regulation suggests how homeostasis and allostasis can be distinguished. Rather than focusing on changes in the value of a regulated variable (e.g., body temperature, body adiposity, or reward), research investigating the activity and relationship among the multiple regulatory loops that influence the value of these regulated variables may be the key to distinguishing homeostasis and allostasis. The mechanisms underlying physiological regulation and dysregulation are likely to have important implications for health and disease.
A 4K-Input High-Speed Winner-Take-All (WTA) Circuit with Single-Winner Selection for Change-Driven Vision Sensors

Winner-Take-All (WTA) circuits play an important role in applications where a single element must be selected according to its relevance. They have been successfully applied in neural networks and vision sensors. These applications usually require a large number of inputs for the WTA circuit, especially for vision applications where thousands to millions of pixels may compete to be selected. WTA circuits usually exhibit poor response-time scaling with the number of competitors, and most of the current WTA implementations are designed to work with less than 100 inputs. Another problem related to the large number of inputs is the difficulty to select just one winner, since many competitors may have differences below the WTA resolution. In this paper, a WTA circuit is presented that handles more than four thousand inputs, to our best knowledge the hitherto largest WTA, with response times below the microsecond, and with a guaranty of just a single winner selection. This performance is obtained by the combination of a standard analog WTA circuit and a fast digital single-winner selector with almost no size penalty. This WTA circuit has been successfully employed in the fabrication of a Selective Change-Driven Vision Sensor based on 180 nm CMOS technology. Both simulated and experimental results are presented in the paper, showing that a single pixel event can be selected in just 560 ns, and a multipixel pixel event can be processed in 100 us. Similar results with a conventional approach would require a camera working at more than 1 Mfps for the single-pixel event detection, and 10 kfps for the whole multipixel event to be processed.
Novel compact net-type resonators and their applications to microstrip bandpass filters

Novel compact net-type resonators and their practical applications to microstrip bandpass filters have been presented in this paper. Three kinds of filters are designed and fabricated to demonstrate the practicality of the proposed compact net-type resonators. In addition, by adjusting the structural parameters of the net-type resonators, the spurious frequencies can be properly shifted to higher frequencies. As a result, a three-pole Chebyshev net-type resonator filter with a fractional bandwidth (FBW) of 6.8% has a spurious resonance of up to 4.1f/sub 0/, and it has more than 80% size reduction in comparison with the conventional U-shaped resonator filter. A four-pole quasi-elliptic net-type resonator filter with a FBW of 3.5% has a spurious resonance of up to 5f/sub 0/, and it has approximately 67% size reduction in comparison with the cross-coupled open-loop resonator filter. A three-pole trisection net-type resonator filter with a FBW of 4.7% has a spurious resonance of up to 6.5f/sub 0/, and its size is reduced by 68% in comparison with the trisection open-loop resonator filter. Consequently, each of the designed filters occupies a very small circuit size and has a good stopband response. The measured results are in good agreement with the full-wave simulation results by IE3D.
Path planning for mobile robots using genetic algorithm and probabilistic roadmap

Mobile robots have been employed extensively in various environments which involve automation and remote monitoring. In order to perform their tasks successfully, navigation from one point to another must be done while avoiding obstacles present in the area. The aim of this study is to demonstrate the efficacy of two approaches in path planning, specifically, probabilistic roadmap (PRM) and genetic algorithm (GA). Two maps, one simple and one complex, were used to compare their performances. In PRM, a map was initially loaded and followed by identifying the number of nodes. Then, initial and final positions were defined. The algorithm, then, generated a network of possible connections of nodes between the initial and final positions. Finally, the algorithm searched this network of connected nodes to return a collision-free path. In GA, a map was also initially loaded followed by selecting the GA parameters. These GA parameters were subjected to explorations as to which set of values will fit the problem. Then, initial and final positions were also defined. Associated cost included the distance or the sum of segments for each of the generated path. Penalties were introduced whenever the generated path involved an obstacle. Results show that both approaches navigated in a collision-free path from the set initial position to the final position within the given environment or map. However, there were observed advantages and disadvantages of each method. GA produces smoother paths which contributes to the ease of navigation of the mobile robots but consumes more processing time which makes it difficult to implement in realtime navigation. On the other hand, PRM produces the possible path in a much lesser amount of time which makes it applicable for more reactive situations but sacrifices smoothness of navigation. The presented advantages and disadvantages of the two approaches show that it is important to select the proper algorithm for path planning suitable for a particular application.
High-Quality Real-Time Video Stabilization Using Trajectory Smoothing and Mesh-Based Warping

Some state-of-the-art video stabilization methods can achieve quite good visual effect, but they always cost a lot of time. On the other hand, current real-time video stabilization methods cannot generate satisfactory results. In this paper, we propose a novel trajectory-based video stabilization method which can generate high-quality results in real time. Our method runs very fast, because many techniques are proposed for acceleration. In the trajectory smoothing step, trajectories are extracted, pre-processed, and smoothed. A video splitting algorithm is proposed for pre-processing, and binomial filtering is used for smoothing. Both of them are simple and fast. In the frame warping step, we calculate a spatially varying warp that is directed by a grid mesh for each frame. Instead of solving time consuming global optimization problems, the transformation matrix of each grid is calculated using nearby trajectories in our method, leading to very high speed. We implement our method and run it on a variety of videos. Experiments show that while the stabilization effect is comparable with state-of-the-art methods, our algorithm can run in real time.
Direction of Arrival Estimation of GNSS Signals Based on Synthetic Antenna Array

Jammer and interference are sources of errors in positions estimated by GNSS receivers. The interfering signals reduce signal-to-noise ratio and cause receiver failure to correctly detect satellite signals. Because of the robustness of beamforming techniques to jamming and multipath mitigation by placing nulls in direction of interference signals, an antenna array with a set of multi-channel receivers can be used to improve GNSS signal reception. Spatial reference beam forming uses the information in the Direction Of Arrival (DOA) of desired and interference signals for this purpose. However, using a multi-channel receiver is not applicable in many applications for estimating the Angle Of Arrival (AOA) of the signal (hardware limitations or portability issues). This paper proposes a new method for DOA estimation of jammer and interference signals based on a synthetic antenna array. In this case, the motion of a single antenna can be used to estimate the AOA of the interfering signals.
Automatic Retraction and Full-Cycle Operation for a Class of Airborne Wind Energy Generators

Airborne wind energy systems aim to harvest the power of winds blowing at altitudes higher than what conventional wind turbines reach. They employ a tethered flying structure, usually a wing, and exploit the aerodynamic lift to produce electrical power. In the case of ground-based systems, where the traction force on the tether is used to drive a generator on the ground, a two-phase power cycle is carried out: one phase to produce power, where the tether is reeled out under high traction force, and a second phase where the tether is recoiled under lower load. The problem of controlling a tethered wing in this second phase, the retraction phase, is addressed here, by proposing two possible control strategies. Theoretical analyses, numerical simulations, and experimental results are presented to show the performance of the two approaches. Finally, the experimental results of complete autonomous power generation cycles are reported and compared with those in first-principle models.
Biomechanics of the deformity of septal L-Struts.

A septal L-strut is often preserved or created during septoplasty. The main intention is to provide structural stability and to straighten the nasal septum. Deformity or excessive deformation of the L-strut might cause functional or aesthetic complications. The objectives were to examine the effects of material properties, the boundary conditions, the nasal tip support, and the geometry of the L-struts on the deformity of septal L-struts.



Computer-aided modeling was used to create a spring-supported nasal tip and free nasal tip L strut septal cartilage models upon which simulation was performed to analyse the deformation patterns.



A five-sided septum model was first created from the computed tomography scan of a human subject. Several models with various combinations of wider or narrower dorsal struts as well as arc of cartilage were then constructed from this septum model. The edges connected to bony supports were assumed to be fixed, and the nasal tip was assumed to be spring supported. Finite element analyses were carried out to determine the deformation and stress distribution in the septal strut for different combinations of material properties and nasal tip spring support.



The spring-supported nasal tip model provides a more accurate representation of the boundary conditions in the nose. In both the free and spring-supported nasal tips-the BC junction and the nasal spine are found to be the consistent points of maximum stress regardless of material properties. The preservation of an arc of cartilage and a wider dorsal strut increase the stability of the structure.



The introduction of a spring-supported nasal tip model provided a more accurate representation of the boundary conditions in the nose. The bony-cartilaginous junction and the nasal spine were found to be the consistent points of maximum stress, regardless of material properties. The preservation of an arc of cartilage and a wider dorsal strut increased the stability of the structure.
Pathogens and Politics: Further Evidence That Parasite Prevalence Predicts Authoritarianism

According to a "parasite stress" hypothesis, authoritarian governments are more likely to emerge in regions characterized by a high prevalence of disease-causing pathogens. Recent cross-national evidence is consistent with this hypothesis, but there are inferential limitations associated with that evidence. We report two studies that address some of these limitations, and provide further tests of the hypothesis. Study 1 revealed that parasite prevalence strongly predicted cross-national differences on measures assessing individuals' authoritarian personalities, and this effect statistically mediated the relationship between parasite prevalence and authoritarian governance. The mediation result is inconsistent with an alternative explanation for previous findings. To address further limitations associated with cross-national comparisons, Study 2 tested the parasite stress hypothesis on a sample of traditional small-scale societies (the Standard Cross-Cultural Sample). Results revealed that parasite prevalence predicted measures of authoritarian governance, and did so even when statistically controlling for other threats to human welfare. One additional threat-famine-also uniquely predicted authoritarianism.) Together, these results further substantiate the parasite stress hypothesis of authoritarianism, and suggest that societal differences in authoritarian governance result, in part, from cultural differences in individuals' authoritarian personalities.
GRAVITY-ASSIST: A series elastic body weight support system with inertia compensation

We present GRAVITY-ASSIST, a series elastic active body weight support and inertia compensation system for use in robot assisted gait rehabilitation. The device consists of a single degree of freedom series elastic actuator that connects to the trunk of a patient. The series elastic system is novel in that, it can provide the desired level of dynamic unloading such that the patient experiences only a percentage of his/her weight and inertia. Inertia compensation is important, since the inertial forces can cause significant deviations from the desired unloading force, specially at low support forces and fast walking speeds. Furthermore, this feature enables the inertia of the harness and force sensing unit attached to the patient to be compensated for, making sure that the device does not interfere with the natural gait cycle. We present a functional prototype of the device, its characterization and experimental verification of the approach.
Foot Design for a Large Walking Delta Robot

A large Delta robot has been modified to pick up and place a triangular shaped foot. The robot pushes the foot down to lift the body and the three associated fixed support legs. It then moves the foot sideways so that the body moves in the opposite direction to a new position where the fixed legs are lowered to the ground and the foot lifted ready for a new placement. In this way the robot is able to move in any direction with a tripod gait. The use of a combined foot and gripper for moving heavy objects is investigated. In the implementation reported, the gearboxes used are found to limit the operation and spring assistance is investigated as a trade off with payload. The small prototype, stands as tall as a person, weighs a third of a ton, and has a payload capability of near 100%. It is envisaged as a prototype for a much larger walking robot capable of general-purpose heavy lifting.
Prevalence and Effect of Cyberbullying on Children and Young People: A Scoping Review of Social Media Studies.

Social media has had a profound effect on how children and adolescents interact. While there are many benefits to the use of social media, cyberbullying has emerged as a potential harm, raising questions regarding its influence on mental health.



To review existing publications that examine the health-related effects of cyberbullying via social media among children and adolescents.



We searched 11 electronic databases from January 1, 2000, through January 17, 2012 (updated June 24, 2014). Studies were screened by 2 independent reviewers and were included if they reported primary research, described or evaluated the use of a social media tool in the context of cyberbullying, and were conducted with children or adolescents. Data were extracted by 1 reviewer and verified by a second. All studies were assessed by 2 reviewers for methodological quality using the Mixed Methods Appraisal Tool. Results were not pooled owing to heterogeneity in study objectives and outcomes; a narrative analysis is presented.



Thirty-six studies in 34 publications were included. Most were conducted in the United States (21 [58.3%]), sampled middle and high school populations (24 [66.7%]), and included adolescents who were 12 to 18 years of age (35 [97.2%]). The median reported prevalence of cyberbullying was 23.0% (interquartile range, 11.0%-42.6%). Five studies reported inconsistent and/or weak correlations between cyberbullying and anxiety. Ten studies found a statistically significant association between cyberbullying and report of depression. Five studies investigated self-harm or suicidality, with conflicting results. Results indicate that the most common reason for cyberbullying is relationship issues, with girls most often being the recipients. Responses to cyberbullying are most often passive, with a pervasive lack of awareness or confidence that anything can be done.



There is a consistent relationship across studies between cyberbullying and depression among children and adolescents; however, the evidence of the effect of cyberbullying on other mental health conditions is inconsistent. This review provides important information that characterizes cyberbullying within the context of social media, including attributes of the recipients and perpetrators, reasons for and the nature of bullying behaviors, and how recipients react to and manage bullying behaviors. This information is critical to the development of effective prevention and management strategies.
mTOR regulation of autophagy.

Nutrient starvation induces autophagy in eukaryotic cells through inhibition of TOR (target of rapamycin), an evolutionarily-conserved protein kinase. TOR, as a central regulator of cell growth, plays a key role at the interface of the pathways that coordinately regulate the balance between cell growth and autophagy in response to nutritional status, growth factor and stress signals. Although TOR has been known as a key regulator of autophagy for more than a decade, the underlying regulatory mechanisms have not been clearly understood. This review discusses the recent advances in understanding of the mechanism by which TOR regulates autophagy with focus on mammalian TOR (mTOR) and its regulation of the autophagy machinery.