nils-herrmann/clean_scirepeval huggingface dataset:
Examples of Applications of Queueing Theory in Canada

As part of the 50th anniversary of the Canadian Operational Research Society, we reviewed queueing applications by Canadian researchers and practitioners. We concentrated on finding real applications, but also considered theoretical contributions to applied areas that have been developed by the authors based on real applications. There were a surprising number of applications, many not well documented. Thus, this paper features examples of queueing theory applications over a spectrum of areas, years and types. One conclusion is that some of the successful queueing applications were achieved and ameliorated by using simple principles gained from studying queues and not by complex mathematical models.
Activation of NLRP 3 inflammasome in the ovaries during the development and treatment of polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is considered as a highly heterogeneous and complex disease. Dimethyldiguanide (DMBG) is widely used to improve the reproductive dysfunction in women with PCOS. However, the precise mechanism by which DMBG exerts its benefical effect on PCOS remains largely unknown. The present study was designed to explore the effects of DMBG on the changes of oxidative stress and the activation of nucleotide leukin rich polypeptide 3 (NLRP3) inflammasome in the ovaries during the development and treatment of PCOS. A letrozole-induced rat PCOS model was developed. The inflammatory status was examined by analyzing the serum high sensitive C-reactive protein (hsCRP) levels in ras. We found that DMBG treatment rescued PCOS rats, which is associated with the reduced chronic low grade inflammation in these rats. In PCOS rats, the NLRP3 and the adaptor protein apoptosis-associated speck-like protein (ASC) mRNA levels, caspase-1 activation, and IL-1β production were unregulated, which was markedly attenuated by DMBG treatment. Moreover, oxidative stress was enhanced in PCOS rats as shown by increased lipid peroxidation (LPO) and activity of superoxide dismutase (SOD) and catalase. DMBG significantly decreased LPO, while it had no effects on SOD and catalase activities. Together, these results indicate that DMBG treatment may rescue PCOS rats by suppressing oxidative stress and NLRP3 inflammasome activation in PCOS ovaries.
Development of MIL-STD-1553 B Synthesizable IP Core for Avionic Applications

MIL-STD-1553, Digital Time Division Command/Response Multiplex Data Bus, is a military standard (presently in revision B), which has become one of the basic tools being used today for integration of weapon systems. The standard describes the method of communication and the electrical interface requirements for subsystems connected to the data bus. The 1 Mbps serial communication bus is used to achieve aircraft avionic (MIL-STD-1553B) and stores management (MILSTD1760B) integration. The standard defines four hardware elements. These are 1) The transmission media, 2) Remote terminals, 3) Bus controllers, 4) Bus monitors. The main objective of this paper is to develop an IP (Intellectual Property) core for the MIL-STD-1553 IC. This IP core can be used as bus monitors or remote terminals or bus monitors. The main advantage of this IP core is to provide small foot print, flexibility and reduce the cost of the system, as we can integrate this with other logic.
DDD17: End-To-End DAVIS Driving Dataset

Event cameras, such as dynamic vision sensors (DVS), and dynamic and activepixel vision sensors (DAVIS) can supplement other autonomous driving sensors by providing a concurrent stream of standard active pixel sensor (APS) images and DVS temporal contrast events. The APS stream is a sequence of standard grayscale global-shutter image sensor frames. The DVS events represent brightness changes occurring at a particular moment, with a jitter of about a millisecond under most lighting conditions. They have a dynamic range of >120 dB and effective frame rates >1 kHz at data rates comparable to 30 fps (frames/second) image sensors. To overcome some of the limitations of current image acquisition technology, we investigate in this work the use of the combined DVS and APS streams in endto-end driving applications. The dataset DDD17 accompanying this paper is the first open dataset of annotated DAVIS driving recordings. DDD17 has over 12 h of a 346x260 pixel DAVIS sensor recording highway and city driving in daytime, evening, night, dry and wet weather conditions, along with vehicle speed, GPS position, driver steering, throttle, and brake captured from the car’s on-board diagnostics interface. As an example application, we performed a preliminary end-toend learning study of using a convolutional neural network that is trained to predict the instantaneous steering angle from DVS and APS visual data.
FPGA based floating-point library for CORDIC algorithms

Computation of floating-point transcendental functions has a relevant importance in a wide variety of scientific applications, where the area cost, error and latency are important requirements to be attended. This paper describes a flexible FPGA implementation of a parameterizable floating-point library for computing sine, cosine, arctangent and exponential functions using the CORDIC algorithm. The novelty of the proposed architecture is that by sharing the same resources the CORDIC algorithm can be used in two operation modes, allowing it to compute the sine, cosine or arctangent functions. Additionally, in case of the exponential function, the architectures change automatically between the CORDIC or a Taylor approach, which helps to improve the precision characteristics of the circuit, specifically for small input values after the argument reduction. Synthesis of the circuits and an experimental analysis of the errors have demonstrated the correctness and effectiveness of the implemented cores and allow the designer to choose, for general-purpose applications, a suitable bit-width representation and number of iterations of the CORDIC algorithm.
Vehicle Safety Distance Warning System: A Novel Algorithm for Vehicle Safety Distance Calculating Between Moving Cars

A novel algorithm for vehicle safety distance between driving cars for vehicle safety warning system is presented in this paper. The presented system concept includes a distance obstacle detection and safety distance calculation. The system detects the distance between the car and the in front of vehicles (obstacles) and uses the vehicle speed and other parameters to calculate the braking safety distance of the moving car. The system compares the obstacle distance and braking safety distance which are used to determine the moving vehicle's safety distance is enough or not. This paper focuses on the solution algorithm presentation.
The mortality rate from anorexia nervosa.

We determined the standardized mortality ratio (SMR) in our anorexia nervosa (AN) patient population.



We used a cross-sectional design to study an inception cohort (1981-2000) drawn from the provincial tertiary care eating disorders program at St. Paul's Hospital (British Columbia, Canada). All patients who completed their initial assessment for an eating disorder were included in the study. Vital status, date and cause of death from British Columbia Vital Statistics Agency, date of assessment, date of birth, and diagnosis at the time of assessment were collected for each patient.



Of 954 patients, 326 diagnosed with AN completed an assessment over the 20 years. The SMR was 10.5 (95% confidence interval [CI] = 5.5-15.5) for AN.



Some studies in the literature report that AN has the highest mortality rate of any psychiatric disorder in young females. However, others dispute this fact and report an SMR lower than the normal population mortality (SMR = 0.71). Contrary to some reports in the literature, our study confirms a high mortality rate within the AN population.
Correlating Synthetic Aperture Radar (CoSAR)

This paper presents the correlating synthetic aperture radar (CoSAR) technique, a novel radar imaging concept to observe statistical properties of fast decorrelating surfaces. A CoSAR system consists of two radars with a relative motion in the along-track (cross-range) dimension. The spatial autocorrelation function of the scattered signal can be estimated by combining quasi-simultaneously received radar echoes. By virtue of the Van Cittert-Zernike theorem, estimates of this autocorrelation function for different relative positions can be processed by generating images of several properties of the scene, including the normalized radar cross section, Doppler velocities, and surface topography. Aside from the geometric performance, a central aspect of this paper is a theoretical derivation of the radiometric performance of CoSAR. The radiometric quality is proportional to the number of independent samples available for the estimation of the spatial correlation, and to the ratio between the CoSAR azimuth resolution and the real-aperture resolution. A CoSAR mission concept is provided where two geosynchronous radar satellites fly at opposing sides of a quasi-circular trajectory. Such a mission could provide bidaily images of the ocean backscatter, mean Doppler, and surface topography at resolutions on the order of 500 m over wide areas.
Music Intervention Leads to Increased Insular Connectivity and Improved Clinical Symptoms in Schizophrenia

Schizophrenia is a syndrome that is typically accompanied by delusions and hallucinations that might be associated with insular pathology. Music intervention, as a complementary therapy, is commonly used to improve psychiatric symptoms in the maintenance stage of schizophrenia. In this study, we employed a longitudinal design to assess the effects of listening to Mozart music on the insular functional connectivity (FC) in patients with schizophrenia. Thirty-six schizophrenia patients were randomly divided into two equal groups as follows: the music intervention (MTSZ) group, which received a 1-month music intervention series combined with antipsychotic drugs, and the no-music intervention (UMTSZ) group, which was treated solely with antipsychotic drugs. Resting-state functional magnetic resonance imaging (fMRI) scans were performed at the following three timepoints: baseline, 1 month after baseline and 6 months after baseline. Nineteen healthy participants were recruited as controls. An FC analysis seeded in the insular subregions and machine learning techniques were used to examine intervention-related changes. After 1 month of listening to Mozart music, the MTSZ showed increased FC in the dorsal anterior insula (dAI) and posterior insular (PI) networks, including the dAI-ACC, PI-pre/postcentral cortices, and PI-ACC connectivity. However, these enhanced FCs had vanished in follow-up visits after 6 months. Additionally, a support vector regression on the FC of the dAI-ACC at baseline yielded a significant prediction of relative symptom remission in response to music intervention. Furthermore, the validation analyses revealed that 1 month of music intervention could facilitate improvement of the insular FC in schizophrenia. Together, these findings revealed that the insular cortex could potentially be an important region in music intervention for patients with schizophrenia, thus improving the patients' psychiatric symptoms through normalizing the salience and sensorimotor networks.
A Variational Perspective on Accelerated Methods in Optimization

Accelerated gradient methods play a central role in optimization, achieving optimal rates in many settings. Although many generalizations and extensions of Nesterov's original acceleration method have been proposed, it is not yet clear what is the natural scope of the acceleration concept. In this paper, we study accelerated methods from a continuous-time perspective. We show that there is a Lagrangian functional that we call the Bregman Lagrangian, which generates a large class of accelerated methods in continuous time, including (but not limited to) accelerated gradient descent, its non-Euclidean extension, and accelerated higher-order gradient methods. We show that the continuous-time limit of all of these methods corresponds to traveling the same curve in spacetime at different speeds. From this perspective, Nesterov's technique and many of its generalizations can be viewed as a systematic way to go from the continuous-time curves generated by the Bregman Lagrangian to a family of discrete-time accelerated algorithms.
Processing video-SAR data with the fast backprojection method

Video synthetic aperture radar (video-SAR) is a land-imaging mode where a sequence of images is continuously formed when the radar platform either flies by or circles the scene. In this paper, the fast backprojection (FBP) algorithm is introduced for video-SAR image formation. It avoids unnecessary duplication of processing for the overlapping parts between consecutive video frames and achieves O(N2 log N) complexity through a recursive procedure. To reduce the processing complexity in video-SAR system, the scene is partitioned into the general region (GR) and the region of interest (ROI). In different regions, different aperture lengths are used. The proposed method allows a direct trade between processing speed and focused quality for the GR, meanwhile reserving particular details in the ROI. The effectiveness is validated both for a simulated scene and for X-band SAR measurements from the Gotcha data set.
Stress, coping and burn-out in nursing students.

To explore the relationship between sources of stress and psychological burn-out and to consider the moderating and mediating role played sources of stress and different coping resources on burn-out.



Most research exploring sources of stress and coping in nursing students construes stress as psychological distress. Little research has considered those sources of stress likely to enhance well-being and, by implication, learning.



A questionnaire was administered to 171 final year nursing students. Questions were asked which measured sources of stress when rated as likely to contribute to distress (a hassle) and rated as likely to help one achieve (an uplift). Support, control, self-efficacy and coping style were also measured, along with their potential moderating and mediating effect on burn-out.



The sources of stress likely to lead to distress were more often predictors of well-being than sources of stress likely to lead to positive, eustress states. However, placement experience was an important source of stress likely to lead to eustress. Self-efficacy, dispositional control and support were other important predictors. Avoidance coping was the strongest predictor of burn-out and, even if used only occasionally, it can have an adverse effect on burn-out. Initiatives to promote support and self-efficacy are likely to have the more immediate benefits in enhancing student well-being.



Nurse educators need to consider how course experiences contribute not just to potential distress but to eustress. How educators interact with their students and how they give feedback offers important opportunities to promote self-efficacy and provide valuable support. Peer support is a critical coping resource and can be bolstered through induction and through learning and teaching initiatives.
Generative Adversarial Positive-Unlabelled Learning

In this work, we consider the task of classifying binary positive-unlabeled (PU) data. Existing discriminative learning based PU models attempt to seek an optimal reweighting strategy for unlabeled (U) data, so that a decent decision boundary can be found. However, given limited positive (P) data, the conventional PU models tend to suffer from overfitting when adapted to very flexible deep neural networks. In contrast, we are the first to innovate a totally new paradigm to attack the binary PU task, from the perspective of generative learning by leveraging the powerful generative adversarial networks (GAN). Our generative positive-unlabeled (GenPU) framework incorporates an array of discriminators and generators that are endowed with different roles in simultaneously producing positive and negative realistic samples. We also provide theoretical analysis to justify that, at equilibrium, GenPU is capable of recovering both positive and negative data distributions. Moreover, we show GenPU is generalizable and closely related to the semi-supervised classification. Given rather limited P data, experiments on both synthetic and realworld dataset demonstrate the effectiveness of our proposed framework. With infinite realistic and diverse samples generated from GenPU, a very flexible classifier can then be trained using deep neural networks.
Syndromic surveillance systems

ion This approach creates a series of intermediate abstractions up to a syndrome category from the individual data (e.g., signs, lab tests) for syndromes indicative of illness due to an agent of bioterrorism. The BioStorm system (Buckeridge et al., 2002; Crubézy, O’Connor, Pincus, & Musen, 2005; Shahar & Musen, 1996)
Distributed Cognition as a Theoretical Framework for Information Visualization

Even though information visualization (InfoVis) research has matured in recent years, it is generally acknowledged that the field still lacks supporting, encompassing theories. In this paper, we argue that the distributed cognition framework can be used to substantiate the theoretical foundation of InfoVis. We highlight fundamental assumptions and theoretical constructs of the distributed cognition approach, based on the cognitive science literature and a real life scenario. We then discuss how the distributed cognition framework can have an impact on the research directions and methodologies we take as InfoVis researchers. Our contributions are as follows. First, we highlight the view that cognition is more an emergent property of interaction than a property of the human mind. Second, we argue that a reductionist approach to study the abstract properties of isolated human minds may not be useful in informing InfoVis design. Finally we propose to make cognition an explicit research agenda, and discuss the implications on how we perform evaluation and theory building.
Validity of the school setting interview for students with special educational needs in regular high school – a Rasch analysis

Participation in education is a vital component of adolescents' everyday life and a determinant of health and future opportunities in adult life. The School Setting Interview (SSI) is an instrument which assesses student-environment fit and reflects the potential needs for adjustments to enhance students' participation in school activities. The aim of the study was to investigate the psychometric properties of the SSI for students with special educational needs in regular high school.



A sample of 509 students with special educational needs was assessed with the SSI. The polytomous unrestricted Rasch model was used to analyze the psychometric properties of the SSI regarding targeting, model fit, differential item functioning (DIF), response category functioning and unidimensionality.



The SSI generally confirmed fit to assumptions of the Rasch model. Reliability was acceptable (0.73) and the SSI scale was able to separate students into three different levels of student-environment fit. DIF among gender was detected in item "Remember things" and in item "Homework" DIF was detected among students with or without diagnosis. All items had disordered thresholds. The SSI demonstrated unidimensionality and no response dependence was present among items.



The results suggest that the SSI is valid for use among students with special educational needs in order to provide and evaluate environmental adjustments. However, the items with the detected DIF and the SSI rating scale with its disordered thresholds needs to be further scrutinized.
Improving the scaffolds of a mobile-assisted Chinese character forming game via a design-based research cycle

This paper reports on one cycle of a design-based research (DBR) study in which mCSCL was explored through an iterative process of (re)designing and testing the collaboration and learning approach with students. A unique characteristic of our mCSCL approach is the student-led emergent formation of groups. The mCSCL application assigns each student a component of a Chinese character and requires them to form groups that can assemble a Chinese character using the components held by the group members. The enactment of the learning design in two modes (with and without the digital technology) was observed, and the actual process of students being scaffolded technologically or socially to accomplish their task was analyzed. Students were found to favor the card mode over the phone mode due to the emergent game strategy (social scaffold) of “trial and error” that they found it comfortable in applying. That triggered us to examine the scaffolding strategies by conducting another round of literature review. We explored domainoriented theories (i.e. in Chinese character learning) to inform and guide them in deciding how they should further accommodate or rectify the students‟ use of the strategy. This cycle of DBR in Chinese-PP project has effectively reshaped the overall learning model design. This paper brings to the fore the value of the interplay and iterations of theories, implementations and reflections, in no fixed order, as advocated by DBR.
Practicality of intermittent fasting in humans and its effect on oxidative stress and genes related to aging and metabolism.

Caloric restriction has consistently been shown to extend life span and ameliorate aging-related diseases. These effects may be due to diet-induced reactive oxygen species acting to up-regulate sirtuins and related protective pathways, which research suggests may be partially inhibited by dietary anti-oxidant supplementation. Because caloric restriction is not sustainable long term for most humans, we investigated an alternative dietary approach, intermittent fasting (IF), which is proposed to act on similar biological pathways. We hypothesized that a modified IF diet, where participants maintain overall energy balance by alternating between days of fasting (25% of normal caloric intake) and feasting (175% of normal), would increase expression of genes associated with aging and reduce oxidative stress and that these effects would be suppressed by anti-oxidant supplementation. To assess the tolerability of the diet and to explore effects on biological mechanisms related to aging and metabolism, we recruited a cohort of 24 healthy individuals in a double-crossover, double-blinded, randomized clinical trial. Study participants underwent two 3-week treatment periods-IF and IF with anti-oxidant (vitamins C and E) supplementation. We found strict adherence to study-provided diets and that participants found the diet tolerable, with no adverse clinical findings or weight change. We detected a marginal increase (2.7%) in SIRT3 expression due to the IF diet, but no change in expression of other genes or oxidative stress markers analyzed. We also found that IF decreased plasma insulin levels (1.01 μU/mL). Although our study suggests that the IF dieting paradigm is acceptable in healthy individuals, additional research is needed to further assess the potential benefits and risks.