nils-herrmann/clean_scirepeval huggingface dataset:
Output Constraint Transfer for Kernelized Correlation Filter in Tracking

The kernelized correlation filter (KCF) is one of the state-of-the-art object trackers. However, it does not reasonably model the distribution of correlation response during tracking process, which might cause the drifting problem, especially when targets undergo significant appearance changes due to occlusion, camera shaking, and/or deformation. In this paper, we propose an output constraint transfer (OCT) method that by modeling the distribution of correlation response in a Bayesian optimization framework is able to mitigate the drifting problem. OCT builds upon the reasonable assumption that the correlation response to the target image follows a Gaussian distribution, which we exploit to select training samples and reduce model uncertainty. OCT is rooted in a new theory which transfers data distribution to a constraint of the optimized variable, leading to an efficient framework to calculate correlation filters. Extensive experiments on a commonly used tracking benchmark show that the proposed method significantly improves KCF, and achieves better performance than other state-of-the-art trackers. To encourage further developments, the source code is made available.
The Use of Virtual Reality in Education

Recent research in the area of multimedia conducted by the author in Australia, the United States and Latin America has re-confirmed the importance and effectiveness of visual features in teaching and learning materials. It has been demonstrated that multimedia can provide a very effective teaching and learning environment in such a way that the learning style preferences (visual, aural, text and kinaesthetic) of the learners are taken into consideration. According to the findings, the visual aspects and interaction with the multimedia system are the most preferred features amongst the surveyed students. In all of these studies, the surveyed students have also indicated that the visual features play a very important role in understanding the concepts. Based on these findings, further research was carried out to investigate the possibilities of creating even richer visual learning environments. The objective was to explore the learning effectiveness of virtual reality educational multimedia systems. Using the virtual reality multimedia, students from two different backgrounds (Nursing and Business) were given a tutorial on topics related to basic human anatomy. After the completion of this tutorial, each student was interviewed and invited to provide comments and feedback. It was concluded that virtual reality multimedia could enhance learning by providing much more realistic images and visual features. Both groups of students found the virtual reality multimedia teaching to be very effective in terms of ease of learning and its very close relationship with the real world. This paper reports the research findings of using virtual reality in teaching and learning. It also investigates the possibilities of incorporating virtual reality technology into the tertiary education courses.
BMI in Childhood and Its Association with Height Gain, Timing of Puberty, and Final Height

No large population-based study has addressed the question of how overnutrition is related to subsequent height gain in childhood, timing of puberty, and final height. The present data represent a large Swedish population-based longitudinal growth study. Height gain in childhood, timing of reaching peak height velocity and height gain during adolescence, and final height were regarded as the short-term, interim, and long-term outcomes of childhood nutritional status, i.e. body mass index (BMI) change between 2 and 8 y. Midparental height was adjusted as the genetic influence on linear growth of the child. Childhood BMI gain was related to an increased height gain during the same period, i.e. an increase of 1 BMI unit was associated with an increase in height of 0.23 cm in boys and 0.29 cm in girls. A higher BMI gain in childhood was related to an earlier onset of puberty; the impact on the timing of puberty was 0.6 y in boys and 0.7 y in girls. Each increased unit of BMI gain in childhood also reduced the height gain in adolescence, 0.88 cm for boys and 0.51 cm for girls. No direct correlation was shown between childhood BMI gain and final height. We conclude that overnutrition between 2 and 8 y of age will not be beneficial from a final height point of view, as the temporary increase in height gain in childhood will be compensated by an earlier pubertal maturity and a subnormal height gain in adolescence.
Total phallic reconstruction after penile amputation for donkey bite: Case report and review of the literature.

There are very few reported cases of traumatic amputation of the male genitalia due to animal bite. The management involves thorough washout of the wounds, debridement, antibiotic prophylaxis, tetanus and rabies immunization followed by immediate reconstruction or primary wound closure with delayed reconstruction, when immediate reconstruction is not feasible. When immediate reconstruction is not feasible, long-term good functional and cosmetic results are still possible in the majority of cases by performing total phallic reconstruction. In particular, it is now possible to fashion a cosmetically acceptable sensate phallus with incorporated neourethra, to allow the patient to void while standing and to ejaculate, and with enough bulk to allow the insertion of a penile prosthesis to guarantee the rigidity necessary to engage in penetrative sexual intercourse.
Attribute Dominance: What Pops Out?

When we look at an image, some properties or attributes of the image stand out more than others. When describing an image, people are likely to describe these dominant attributes first. Attribute dominance is a result of a complex interplay between the various properties present or absent in the image. Which attributes in an image are more dominant than others reveals rich information about the content of the image. In this paper we tap into this information by modeling attribute dominance. We show that this helps improve the performance of vision systems on a variety of human-centric applications such as zero-shot learning, image search and generating textual descriptions of images.
Heterogeneous Knowledge Transfer in Video Emotion Recognition, Attribution and Summarization

Emotion is a key element in user-generated video. However, it is difficult to understand emotions conveyed in such videos due to the complex and unstructured nature of user-generated content and the sparsity of video frames expressing emotion. In this paper, for the first time, we propose a technique for transferring knowledge from heterogeneous external sources, including image and textual data, to facilitate three related tasks in understanding video emotion: emotion recognition, emotion attribution and emotion-oriented summarization. Specifically, our framework (1) learns a video encoding from an auxiliary emotional image dataset in order to improve supervised video emotion recognition, and (2) transfers knowledge from an auxiliary textual corpora for zero-shot recognition of emotion classes unseen during training. The proposed technique for knowledge transfer facilitates novel applications of emotion attribution and emotion-oriented summarization. A comprehensive set of experiments on multiple datasets demonstrate the effectiveness of our framework.
Analysis of recursive state machines

Recursive state machines (RSMs) enhance the power of ordinary state machines by allowing vertices to correspond either to ordinary states or to potentially recursive invocations of other state machines. RSMs can model the control flow in sequential imperative programs containing recursive procedure calls. They can be viewed as a visual notation extending Statecharts-like hierarchical state machines, where concurrency is disallowed but recursion is allowed. They are also related to various models of pushdown systems studied in the verification and program analysis communities.After introducing RSMs and comparing their expressiveness with other models, we focus on whether verification can be efficiently performed for RSMs. Our first goal is to examine the verification of linear time properties of RSMs. We begin this study by dealing with two key components for algorithmic analysis and model checking, namely, reachability (Is a target state reachable from initial states?) and cycle detection (Is there a reachable cycle containing an accepting state?). We show that both these problems can be solved in time O(nθ2) and space O(nθ), where n is the size of the recursive machine and θ is the maximum, over all component state machines, of the minimum of the number of entries and the number of exits of each component. From this, we easily derive algorithms for linear time temporal logic model checking with the same complexity in the model. We then turn to properties in the branching time logic CTL*, and again demonstrate a bound linear in the size of the state machine, but only for the case of RSMs with a single exit node.
Compact dual-band microstrip bandpass filter using stub-loaded stepped-impedance resonator

In this paper, two dual-band microstrip bandpass filters (BPFs) based on the stepped-impedance resonator (SIR) and stub-loaded SIR (SL-SIR) are presented. The characteristics of the SL-SIR are studied by using the even-/odd-mode analysis method. The simulation results show the length of the loaded stub has no influence on the odd-mode resonant frequency, but it can affect the even-mode resonant frequency. In addition, the BPF based on the SL-SIR has higher frequency selectivity and stopband rejection than the one based on the SIR. What's more, the loaded stub can reduce the size of the BPF. Therefore, the BPF based on the SL-SIR can be applied in the modern wireless communication systems.
Adaptive Concurrency Control: Despite the Looking Glass, One Concurrency Control Does Not Fit All

Use of transactional multicore main-memory databases is growing due to dramatic increases in memory size and CPU cores available for a single machine. To leverage these resources, recent concurrency control protocols have been proposed for main-memory databases, but are largely optimized for specific workloads. Due to shifting and unknown access patterns, workloads may change and one specific algorithm cannot dynamically fit all varied workloads. Thus, it is desirable to choose the right concurrency control protocol for a given workload. To address this issue we present adaptive concurrency control (ACC), that dynamically clusters data and chooses the optimal concurrency control protocol for each cluster. ACC addresses three key challenges: i) how to cluster data to minimize cross-cluster access and maintain load-balancing, ii) how to model workloads and perform protocol selection accordingly, and iii) how to support mixed concurrency control protocols running simultaneously. In this paper, we outline these challenges and present preliminary results.
On the assessment of landmark salience for human navigation

In this paper, we propose a conceptual framework for assessing the salience of landmarks for navigation. Landmark salience is derived as a result of the observer’s point of view, both physical and cognitive, the surrounding environment, and the objects contained therein. This is in contrast to the currently held view that salience is an inherent property of some spatial feature. Salience, in our approach, is expressed as a three-valued Saliency Vector. The components that determine this vector are Perceptual Salience, which defines the exogenous (or passive) potential of an object or region for acquisition of visual attention, Cognitive Salience, which is an endogenous (or active) mode of orienting attention, triggered by informative cues providing advance information about the target location, and Contextual Salience, which is tightly coupled to modality and task to be performed. This separation between voluntary and involuntary direction of visual attention in dependence of the context allows defining a framework that accounts for the interaction between observer, environment, and landmark. We identify the low-level factors that contribute to each type of salience and suggest a probabilistic approach for their integration. Finally, we discuss the implications, consider restrictions, and explore the scope of the framework.
Neuroinflammation in Alzheimer's disease

Increasing evidence suggests that Alzheimer's disease pathogenesis is not restricted to the neuronal compartment, but includes strong interactions with immunological mechanisms in the brain. Misfolded and aggregated proteins bind to pattern recognition receptors on microglia and astroglia, and trigger an innate immune response characterised by release of inflammatory mediators, which contribute to disease progression and severity. Genome-wide analysis suggests that several genes that increase the risk for sporadic Alzheimer's disease encode factors that regulate glial clearance of misfolded proteins and the inflammatory reaction. External factors, including systemic inflammation and obesity, are likely to interfere with immunological processes of the brain and further promote disease progression. Modulation of risk factors and targeting of these immune mechanisms could lead to future therapeutic or preventive strategies for Alzheimer's disease.
Bias in Algorithm Portfolio Performance Evaluation

A Virtual Best Solver (VBS) is a hypothetical algorithm that selects the best solver from a given portfolio of alternatives on a per-instance basis. The VBS idealizes performance when all solvers in a portfolio are run in parallel, and also gives a valuable bound on the performance of portfolio-based algorithm selectors. Typically, VBS performance is measured by running every solver in a portfolio once on a given instance and reporting the best performance over all solvers. Here, we argue that doing so results in a flawed measure that is biased to reporting better performance when a randomized solver is present in an algorithm portfolio. Specifically, this flawed notion of VBS tends to show performance better than that achievable by a perfect selector that for each given instance runs the solver with the best expected running time. We report results from an empirical study using solvers and instances submitted to several SAT competitions, in which we observe significant bias on many random instances and some combinatorial instances. We also show that the bias increases with the number of randomized solvers and decreases as we average solver performance over many independent runs per instance. We propose an alternative VBS performance measure by (1) empirically obtaining the solver with best expected performance for each instance and (2) taking bootstrap samples for this solver on every instance, to obtain a confidence interval on VBS performance. Our findings shed new light on widely studied algorithm selection benchmarks and help explain performance gaps observed between VBS and state-of-the-art algorithm selection approaches.
Beyond sensory images: Object-based representation in the human ventral pathway.

We investigated whether the topographically organized, category-related patterns of neural response in the ventral visual pathway are a representation of sensory images or a more abstract representation of object form that is not dependent on sensory modality. We used functional MRI to measure patterns of response evoked during visual and tactile recognition of faces and manmade objects in sighted subjects and during tactile recognition in blind subjects. Results showed that visual and tactile recognition evoked category-related patterns of response in a ventral extrastriate visual area in the inferior temporal gyrus that were correlated across modality for manmade objects. Blind subjects also demonstrated category-related patterns of response in this "visual" area, and in more ventral cortical regions in the fusiform gyrus, indicating that these patterns are not due to visual imagery and, furthermore, that visual experience is not necessary for category-related representations to develop in these cortices. These results demonstrate that the representation of objects in the ventral visual pathway is not simply a representation of visual images but, rather, is a representation of more abstract features of object form.
On the Failure to Detect Changes in Scenes Across Brief Interruptions

When brief blank fields are placed between alternating displays of an original and a modified scene, a striking failure of perception is induced: The changes become extremely difficult to notice, even when they are large, presented repeatedly, and the observer expects them to occur (Rensink, O’Regan, & Clark, 1997). To determine the mechanisms behind this induced “change blindness”, four experiments examine its dependence on initial preview and on the nature of the interruptions used. Results support the proposal that representations at the early stages of visual processing are inherently volatile, and that focused attention is needed to stabilize them sufficiently to support the perception of change.
Anemia of chronic disease.

From the Department of General Internal Medicine, Clinical Immunology and Infectious Diseases, Medical University of Innsbruck, Innsbruck, Austria (G.W.); and the Departments of Pathology and Medicine, Stanford University, Stanford, Calif. (L.T.G.). Address reprint requests to Dr. Weiss at the Department of General Internal Medicine, Clinical Immunology and Infectious Diseases, Medical University of Innsbruck, Anichstr. 35, A-6020 Innsbruck, Austria, or at guenter.weiss@uibk.ac.at.
Analysis of the PeerRank Method for Peer Grading

i in iteration n+1. Ai,j is the peer grade given to student i by student j, Xi is the grade given to student i in iteration n, m is the total number of students, and α and β are changeable parameters in the equation. The term with β incorporates the grader’s accuracy into their own grade. The equation is repeated iteratively until a fixed point is reached, i.e. until .  • Faster • Learning from peers Cons: • Inaccurate grades • Lack of incentive
SCAN. Schedules for Clinical Assessment in Neuropsychiatry.

After more than 12 years of development, the ninth edition of the Present State Examination (PSE-9) was published, together with associated instruments and computer algorithm, in 1974. The system has now been expanded, in the framework of the World Health Organization/Alcohol, Drug Abuse, and Mental Health Administration Joint Project on Standardization of Diagnosis and Classification, and is being tested with the aim of developing a comprehensive procedure for clinical examination that is also capable of generating many of the categories of the International Classification of Diseases, 10th edition, and the Diagnostic and Statistical Manual of Mental Disorders, revised third edition. The new system is known as SCAN (Schedules for Clinical Assessment in Neuropsychiatry). It includes the 10th edition of the PSE as one of its core schedules, preliminary tests of which have suggested that reliability is similar to that of PSE-9. SCAN is being field tested in 20 centers in 11 countries. A final version is expected to be available in January 1990.
Automatic 3D bi-ventricular segmentation of cardiac images by a shape-constrained multi-task deep learning approach

Deep learning approaches have achieved state-of-the-art performance in cardiac magnetic resonance (CMR) image segmentation. However, most approaches have focused on learning image intensity features for segmentation, whereas the incorporation of anatomical shape priors has received less attention. In this paper, we combine a multi-task deep learning approach with atlas propagation to develop a shape-constrained bi-ventricular segmentation pipeline for short-axis CMR volumetric images. The pipeline first employs a fully convolutional network (FCN) that learns segmentation and landmark localisation tasks simultaneously. The architecture of the proposed FCN uses a 2.5D representation, thus combining the computational advantage of 2D FCNs networks and the capability of addressing 3D spatial consistency without compromising segmentation accuracy. Moreover, the refinement step is designed to explicitly enforce a shape constraint and improve segmentation quality. This step is effective for overcoming image artefacts (e.g. due to different breath-hold positions and large slice thickness), which preclude the creation of anatomically meaningful 3D cardiac shapes. The proposed pipeline is fully automated, due to network’s ability to infer landmarks, which are then used downstream in the pipeline to initialise atlas propagation. We validate the pipeline on 1831 healthy subjects and 649 subjects with pulmonary hypertension. Extensive numerical experiments on the two datasets demonstrate that our proposed method is robust and capable of producing accurate, high-resolution and anatomically smooth bi-ventricular 3D models, despite the artefacts in input CMR volumes.
The Factors Affecting Cross-border E-commerce Development of SMEs - An Empirical Study

Recently, there are two mainly methods for SMEs operating cross-border e-commerce in China. One is online store of firms via the cross-border third party platform. The other is the online store of firms built by themselves for export markets expansion. Based on the analysis of cross-border e-commerce process, we explore four factors which may affect the mode selection of cross-border e-commerce of SMEs, namely E-marketing, electronic payment, electronic customs and international logistics. For the methodology, we use Probit model of Logit modeling and then have the finding that the three factors E-marketing, electronic customs and international logistics are the impact of SMEs cross-border e-commerce mode selection, and further find that most of SMEs who are weak at cross-border e-commerce operation stay on third party cross-border e-commerce service platform. Based on the finding, we also have some conclusion. In order to assist SMEs development, the government should establish and improve the trade informational platform. Meanwhile, they should encourage the cross-border e-commerce third-party platform to become bigger and stronger and improve electronic customs clearance continuously to raise large scale cross-border logistic firms and third parties with good service, strong competition and high technologies. For the SMEs, they should adopt the third party cross-border e-commerce platform actively. Some firms should have their own cross-border websites for opening cross-border e-commerce channel actively.
Development of a therapeutic exercise robot for wrist and forearm rehabilitation

In this study, design steps and system concept of a 3 DOF upper limb rehabilitation robot which is called Physiotherabot/WF are introduced. Functional requirements of design, corresponding design parameters and system concept of the robot were examined in detail. Physiotherabot/WF can perform pronation-supination movement for forearm, abduction-adduction and flexion-extension movements for wrist. It can perform passive, active assisted, isotonic, isometric and isokinetic exercises. In order to control the robot, Hybrid Impedance Control (HIC) method is used. The HIC performance is shown by simulation results.