nils-herrmann/clean_scirepeval huggingface dataset:
Title On the psychology of self-prediction : Consideration ofsituational barriers to intended actions

When people predict their future behavior, they tend to place too much weight on their current intentions, which produces an optimistic bias for behaviors associated with currently strong intentions. More realistic self-predictions require greater sensitivity to situational barriers, such as obstacles or competing demands, that may interfere with the translation of current intentions into future behavior. We consider three reasons why people may not adjust sufficiently for such barriers. First, self-predictions may focus exclusively on current intentions, ignoring potential barriers altogether. We test this possibility, in three studies, with manipulations that draw greater attention to barriers. Second, barriers may be discounted in the self-prediction process. We test this possibility by comparing prospective and retrospective ratings of the impact of barriers on the target behavior. Neither possibility was supported in these tests, or in a further test examining whether an optimally weighted statistical model could improve on the accuracy of self-predictions by placing greater weight on anticipated situational barriers. Instead, the evidence supports a third possibility: Even when they acknowledge that situational factors can affect the likelihood of carrying out an intended behavior, people do not adequately moderate the weight placed on their current intentions when predicting their future behavior.
Improvement of axial flux single-rotor single-stator induction machine performance by applying semi-magnetic wedges

This research investigates an axial flux single-rotor single-stator asynchronous motor (AFAM) with aluminum and copper cage windings. In order to avoid using die casting of the rotor cage winding an open rotor slot structure was implemented. In future, this technique allows using copper cage winding avoiding critically high temperature treatment as in the die casting processing of copper material. However, an open slot structure leads to a large equivalent air gap length. Therefore, semi-magnetic wedges should be used to reduce the effect of open slots and consequently to improve the machine performance. The paper aims to investigate the feasibility of using open slot rotor structure (for avoiding die casting) and impact of semi-magnetic wedges to eliminate negative effects of open slots. The results were mainly obtained by 2D finite element method (FEM) simulations. Measurement results of mechanical performance of the prototype (with aluminum cage winding) given in the paper prove the simulated results.
Design of brushless permanent-magnet DC motors for racing motorcycles

The use of brushless permanent magnet DC drive motors in racing motorcycles is discussed in this paper. The application requirements are highlighted and the characteristics of the load demand and drive converter outlined. The possible topologies of the machine are investigated and a design for a internal permanent magnet is developed. This is a 6-pole machine with 18 stator slots and coils of one stator tooth pitch. The performance predictions are put forward and these are obtained from design software. Cooling is vital for these machines and this is briefly discussed.
Mycorrhizal compatibility and symbiotic reproduction of Gavilea australis, an endangered terrestrial orchid from south Patagonia

Gavilea australis is a terrestrial orchid endemic from insular south Argentina and Chile. Meeting aspects of mycorrhizal fungi identity and compatibility in this orchid species is essential for propagation and conservation purposes. These knowledge represent also a first approach to elucidate the mycorrhizal specificity of this species. In order to evaluate both the mycorrhizal compatibility and the symbiotic seed germination of G. australis, we isolated and identified its root endophytic fungal strains as well as those from two sympatric species: Gavilea lutea and Codonorchis lessonii. In addition, we tested two other strains isolated from allopatric terrestrial orchid species from central Argentina. All fungal strains formed coilings and pelotons inside protocorms and promoted, at varying degrees, seed germination, and protocorm development until seedlings had two to three leaves. These results suggest a low mycorrhizal specificity of G. australis and contribute to a better knowledge of the biology of this orchid as well as of other sympatric Patagonian orchid species, all of them currently under serious risk of extinction.
The relationship between outcome prediction and cognitive fatigue: A convergence of paradigms.

Cognitive fatigue is common after strenuous cognitive effort. A large body of literature has implicated a network of brain areas in fatigue, including the basal ganglia and cortical areas including ventro-medal prefrontal cortex and anterior cingulate cortex (ACC). Furthermore, the ACC has been shown to be involved in processes such as error and conflict monitoring, outcome prediction, and effort processing. Thus, the ACC appears to be one common denominator between clinical work on fatigue and research on outcome prediction and effort. In the present study, we examined whether the same region of the ACC is activated during the processing of errors and fatigue. Cognitive fatigue was induced by having subjects perform a difficult working memory task, during which they rated on-task fatigue. Activation associated with error processing was determined by using error trials on the working memory task. After localizing the region engaged in error processing, we evaluated whether there was a relationship between BOLD activation of that region and on-task fatigue scores. The results showed that as subjects became more fatigued, they responded with longer latencies and increased accuracy for the more difficult task. Moreover, the ACC areas that were activated by error processing were also associated with fatigue. These results suggest that cognitive fatigue may be related to changes in effort and reward. We speculate that as the brain detects these changes, cognitive fatigue is generated as a way for the brain to signal itself that the effort required for the task no longer merits the rewards received for performing it.
Fetal ventriculomegaly: Diagnosis, treatment, and future directions

Fetal ventriculomegaly (VM) refers to the enlargement of the cerebral ventricles in utero. It is associated with the postnatal diagnosis of hydrocephalus. VM is clinically diagnosed on ultrasound and is defined as an atrial diameter greater than 10 mm. Because of the anatomic detailed seen with advanced imaging, VM is often further characterized by fetal magnetic resonance imaging (MRI). Fetal VM is a heterogeneous condition with various etiologies and a wide range of neurodevelopmental outcomes. These outcomes are heavily dependent on the presence or absence of associated anomalies and the direct cause of the ventriculomegaly rather than on the absolute degree of VM. In this review article, we discuss diagnosis, work-up, counseling, and management strategies as they relate to fetal VM. We then describe imaging-based research efforts aimed at using prenatal data to predict postnatal outcome. Finally, we review the early experience with fetal therapy such as in utero shunting, as well as the advances in prenatal diagnosis and fetal surgery that may begin to address the limitations of previous therapeutic efforts.
Vital Sign Monitoring Through the Back Using an UWB Impulse Radar With Body Coupled Antennas

Radar devices can be used in nonintrusive situations to monitor vital sign, through clothes or behind walls. By detecting and extracting body motion linked to physiological activity, accurate simultaneous estimations of both heart rate (HR) and respiration rate (RR) is possible. However, most research to date has focused on front monitoring of superficial motion of the chest. In this paper, body penetration of electromagnetic (EM) wave is investigated to perform back monitoring of human subjects. Using body-coupled antennas and an ultra-wideband (UWB) pulsed radar, in-body monitoring of lungs and heart motion was achieved. An optimised location of measurement in the back of a subject is presented, to enhance signal-to-noise ratio and limit attenuation of reflected radar signals. Phase-based detection techniques are then investigated for back measurements of vital sign, in conjunction with frequency estimation methods that reduce the impact of parasite signals. Finally, an algorithm combining these techniques is presented to allow robust and real-time estimation of both HR and RR. Static and dynamic tests were conducted, and demonstrated the possibility of using this sensor in future health monitoring systems, especially in the form of a smart car seat for driver monitoring.
An electroencephalographic study on the zen meditation (Zazen).

It is our common knowledge that EEG undergoes striking changes in the transition from wakefulness to sleep, and has become one of the reliable way to assess the state of wakefulness or sleep. In clinical practice, EEG often becomes a good neurophysiological method to find out the disturbance of consciousness. And many studies, both clinical and experimental, on the consciousness have been published during the past 30 years. In recent years electroencephalographic and neurophysiological studies on the consciousness are focused to understanding of the relationship between the brain mechanisms and consciousness in general"). These studies give rise to attempt to relate the various electrographic findings with the psychological states and their behavioral correlatesm) ~
An ontology for satellite databases

This paper demonstrates the development of ontology for satellite databases. First, I create a computational ontology for the Union of Concerned Scientists (UCS) Satellite Database (UCSSD for short), called the UCS Satellite Ontology (or UCSSO). Second, in developing UCSSO I show that The Space Situational Awareness Ontology (SSAO)-—an existing space domain reference ontology—-and related ontology work by the author (Rovetto 2015, 2016) can be used either (i) with a database-specific local ontology such as UCSSO, or (ii) in its stead. In case (i), local ontologies such as UCSSO can reuse SSAO terms, perform term mappings, or extend it. In case (ii), the author_s orbital space ontology work, such as the SSAO, is usable by the UCSSD and organizations with other space object catalogs, as a reference ontology suite providing a common semantically-rich domain model. The SSAO, UCSSO, and the broader Orbital Space Environment Domain Ontology project is online at https://purl.org/space-ontology and GitHub. This ontology effort aims, in part, to provide accurate formal representations of the domain for various applications. Ontology engineering has the potential to facilitate the sharing and integration of satellite data from federated databases and sensors for safer spaceflight.
Approximate entropy (ApEn) as a complexity measure.

Approximate entropy (ApEn) is a recently developed statistic quantifying regularity and complexity, which appears to have potential application to a wide variety of relatively short (greater than 100 points) and noisy time-series data. The development of ApEn was motivated by data length constraints commonly encountered, e.g., in heart rate, EEG, and endocrine hormone secretion data sets. We describe ApEn implementation and interpretation, indicating its utility to distinguish correlated stochastic processes, and composite deterministic/ stochastic models. We discuss the key technical idea that motivates ApEn, that one need not fully reconstruct an attractor to discriminate in a statistically valid manner-marginal probability distributions often suffice for this purpose. Finally, we discuss why algorithms to compute, e.g., correlation dimension and the Kolmogorov-Sinai (KS) entropy, often work well for true dynamical systems, yet sometimes operationally confound for general models, with the aid of visual representations of reconstructed dynamics for two contrasting processes.
Pathogenetic mechanisms in the initiation and perpetuation of Sjögren's syndrome

Sjögren's syndrome (SS), a chronic autoimmune disorder, particularly compromises the function of exocrine glands. The involvement of these glands is characterized by focal, mononuclear cell infiltrates that surround the ducts and replace the secretory units. The pathogenetic mechanisms of this autoimmune exocrinopathy have not been fully elucidated. Immunologically-activated or apoptotic glandular epithelial cells that expose autoantigens in genetically predisposed individuals might drive autoimmune-mediated tissue injury. Alterations in several immune mediators, such as upregulation of type I interferon-regulated genes, abnormal expression of B-cell-activating factor and activation of the interleukin-23–type 17 T-helper cell pathway, have been reported. Extension of the pathological process that affects the exocrine glands into periepithelial and extraepithelial tissue can cause a considerable percentage of patients to exhibit systemic findings that involve the lungs, liver or kidneys. These manifestations develop as a result of lymphocytic invasion or an immune-complex-mediated process, or both, and present as skin vasculitis coupled with peripheral neuropathy or glomerulonephritis (or both). Patients with systemic extraepithelial manifestations display low serum levels of the complement component C4 and mixed type II cryoglobulins, and show an increased risk of developing non-Hodgkin lymphoma, thereby reflecting an overall worse prognosis with higher mortality rates than those without extraepithelial manifestations.
Approximation Algorithms for Minimum K -Cut

Let G=(V,E) be a complete undirected graph, with node set V={v 1 , . . ., v n } and edge set E . The edges (v i ,v j ) ∈ E have nonnegative weights that satisfy the triangle inequality. Given a set of integers K = { k i } i=1 p $(\sum_{i=1}^p k_i \leq |V|$) , the minimum K-cut problem is to compute disjoint subsets with sizes { k i } i=1 p , minimizing the total weight of edges whose two ends are in different subsets. We demonstrate that for any fixed p it is possible to obtain in polynomial time an approximation of at most three times the optimal value. We also prove bounds on the ratio between the weights of maximum and minimum cuts.
Use of virtual reality for adjunctive treatment of adult burn pain during physical therapy: a controlled study.

The pain experienced by burn patients during physical therapy range of motion exercises can be extreme and can discourage patients from complying with their physical therapy. We explored the novel use of immersive virtual reality (VR) to distract patients from pain during physical therapy.



This study was conducted at the burn care unit of a regional trauma center.



Twelve patients aged 19 to 47 years (average of 21% total body surface area burned) performed range of motion exercises of their injured extremity under an occupational therapist's direction.



Each patient spent 3 minutes of physical therapy with no distraction and 3 minutes of physical therapy in VR (condition order randomized and counter-balanced).



Five visual analogue scale pain scores for each treatment condition served as the dependent variables.



All patients reported less pain when distracted with VR, and the magnitude of pain reduction by VR was statistically significant (e.g., time spent thinking about pain during physical therapy dropped from 60 to 14 mm on a 100-mm scale). The results of this study may be examined in more detail at www.hitL.washington.edu/projects/burn/.



Results provided preliminary evidence that VR can function as a strong nonpharmacologic pain reduction technique for adult burn patients during physical therapy and potentially for other painful procedures or pain populations.
(Physio)logical circuits: the intellectual origins of the McCulloch-Pitts neural networks.

This article examines the intellectual and institutional factors that contributed to the collaboration of neuropsychiatrist Warren McCulloch and mathematician Walter Pitts on the logic of neural networks, which culminated in their 1943 publication, "A Logical Calculus of the Ideas Immanent in Nervous Activity." Historians and scientists alike often refer to the McCulloch-Pitts paper as a landmark event in the history of cybernetics, and fundamental to the development of cognitive science and artificial intelligence. This article seeks to bring some historical context to the McCulloch-Pitts collaboration itself, namely, their intellectual and scientific orientations and backgrounds, the key concepts that contributed to their paper, and the institutional context in which their collaboration was made. Although they were almost a generation apart and had dissimilar scientific backgrounds, McCulloch and Pitts had similar intellectual concerns, simultaneously motivated by issues in philosophy, neurology, and mathematics. This article demonstrates how these issues converged and found resonance in their model of neural networks. By examining the intellectual backgrounds of McCulloch and Pitts as individuals, it will be shown that besides being an important event in the history of cybernetics proper, the McCulloch-Pitts collaboration was an important result of early twentieth-century efforts to apply mathematics to neurological phenomena.
Automatic Tablature Transcription of Electric Guitar Recordings by Estimation of Score- and Instrument-Related Parameters

In this paper we present a novel algorithm for automatic analysis, transcription, and parameter extraction from isolated polyphonic guitar recordings. In addition to general score-related information such as note onset, duration, and pitch, instrumentspecific information such as the plucked string, the applied plucking and expression styles are retrieved automatically. For this purpose, we adapted several state-of-the-art approaches for onset and offset detection, multipitch estimation, string estimation, feature extraction, and multi-class classification. Furthermore we investigated a robust partial tracking algorithm with respect to inharmonicity, an extensive extraction of novel and known audio features as well as the exploitation of instrument-based knowledge in the form of plausability filtering to obtain more reliable prediction. Our system achieved very high accuracy values of 98 % for onset and offset detection as well as multipitch estimation. For the instrument-related parameters, the proposed algorithm also showed very good performance with accuracy values of 82 % for the string number, 93 % for the plucking style, and 83 % for the expression style. Index Terms playing techniques, plucking style, expression style, multiple fundamental frequency estimation, string classification, fretboard position, fingering, electric guitar, inharmonicity coefficient,
Formal Security Analysis of Neural Networks using Symbolic Intervals

Due to the increasing deployment of Deep Neural Networks (DNNs) in real-world security-critical domains including autonomous vehicles and collision avoidance systems, formally checking security properties of DNNs, especially under different attacker capabilities, is becoming crucial. Most existing security testing techniques for DNNs try to find adversarial examples without providing any formal security guarantees about the non-existence of such adversarial examples. Recently, several projects have used different types of Satisfiability Modulo Theory (SMT) solvers to formally check security properties of DNNs. However, all of these approaches are limited by the high overhead caused by the solver. In this paper, we present a new direction for formally checking security properties of DNNs without using SMT solvers. Instead, we leverage interval arithmetic to compute rigorous bounds on the DNN outputs. Our approach, unlike existing solver-based approaches, is easily parallelizable. We further present symbolic interval analysis along with several other optimizations to minimize overestimations of output bounds. We design, implement, and evaluate our approach as part of ReluVal, a system for formally checking security properties of Relu-based DNNs. Our extensive empirical results show that ReluVal outperforms Reluplex, a stateof-the-art solver-based system, by 200 times on average. On a single 8-core machine without GPUs, within 4 hours, ReluVal is able to verify a security property that Reluplex deemed inconclusive due to timeout after running for more than 5 days. Our experiments demonstrate that symbolic interval analysis is a promising new direction towards rigorously analyzing different security properties of DNNs.
Students' expectation, satisfaction, and continuance intention to use digital textbooks

The purpose of this study was to investigate the structural relationships among students' expectation, perceived enjoyment, perceived usefulness, satisfaction, and continuance intention to use digital textbooks in middle school, based on Bhattacherjee's (2001) expectation-confirmation model. The subjects of this study were Korean middle school students taking an English class taught by a digital textbook in E middle school, Seoul. Data were collected via a paper-and-pencil-based questionnaire with 17 items; 137 responses were analyzed. The study found that (a) the more expectations of digital textbooks are satisfied, the more likely students are to perceive enjoyment and usefulness of digital textbooks, (b) satisfaction plays a mediating role in linking expectation, perceived enjoyment and usefulness, and continuance intention to use digital textbooks, (c) perceived usefulness and satisfaction have a direct and positive influence on continuance intention to use digital textbooks, and (d) perceived enjoyment has a non-significant influence on continuance intention to use digital textbooks with middle school students. Based on these findings, the implications and recommendations for future research are presented.
MATHEMATICAL MODEL FOR MALARIA TRANSMISSION DYNAMICS IN HUMAN AND MOSQUITO POPULATIONS WITH NONLINEAR FORCES OF INFECTION

This paper presents a seven-dimensional ordinary differential equation modelling the transmission of Plasmodium falciparum malaria between humans and mosquitoes with non-linear forces of infection in form of saturated incidence rates. These incidence rates produce antibodies in response to the presence of parasite-causing malaria in both human and mosquito populations.The existence of region where the model is epidemiologically feasible is established. Stability analysis of the disease-free equilibrium is investigated via the threshold parameter (reproduction number R0) obtained using the next generation matrix technique. The model results show that the disease-free equilibrium is asymptotically stable at threshold parameter less than unity and unstable at threshold parameter greater than unity. The existence of the unique endemic equilibrium is also determined under certain conditions. Numerical simulations are carried out to confirm the analytic results and explore the possible behavior of the formulated model.