Miracle-dz/UniFAR-FTUs huggingface dataset:
Sensitivity of heart rate variability as indicator of driver sleepiness

A number of research studies have been conducted on interventions to minimize accident risks while driving. Among ergonomic interventions is driver sleepiness detection based on biological signals. However, results seem to be inconclusive. This study investigated the sensitivity of sleepiness detection based on drivers' heart rate variability (HRV). Sixteen professional male drivers participated in a laboratory experiment using a driving simulator. Heart beat per minute and peak-to-peak heart beat (RR interval) were monitored during sixty minutes driving, along with theta brain wave activity derived from EEG measurements, Heart rate data were then processed in terms of time-domain, frequency-domain, and fractal (Poincaré plot method). Theta activity was used to determine sleepiness event. Finally, hit rates and false alarm rates were calculated for each heart rate measure to find out the sensitivity in detecting sleepiness. Results showed that the decrement of root mean square of successive differences (RMSSD) of RR interval for 28% and the decrement of short-term variability (SD1) in Poincaré plot for 27% were the two most sensitive parameters for sleepiness detection. Therefore, these biological signals can be considered in developing sleepiness detection system in the future study.
On a 1-d Granular Media Immersed in a Uid

In this paper a 1-D model for the evolution of inelastic particles in a thermal bath is studied. We derive an equation for the evolution of the probability density of the particles in phase space. The analysis of the homogeneous equation is the main objective of this paper. The existence and uniqueness of this equation is addressed. Finally, we prove that the asymptotic behavior is governed by a stationary solution of the homogeneous equation. A formal hydrodynamic set of equations is derived for the non-homogeneous case.
Assignment and Patrol Strategy for Police Cars Based on Computational Intelligence

Police Patrol is a very useful method for managing the social security. Many researches focus on how to obtain the best strategy for police patrol. We got this research topic from The Sixth National Post-Graduate Mathematical Contest in Modeling. In the proposed approach, Greedy Policy and Randomized Strategy are combined with Genetic Algorithm to solve these problems, simulation result shows the assignment and patrol strategy for police cars have a good effect with great concealment.
The HAIRCUT information retrieval system

The complexity of human language makes accessing multilingual information difficult. Most cross-language retrieval systems attempt to address linguistic variation through language-specific techniques and resources. In contrast, APL has developed a multilingual information retrieval system, the Hopkins Automated Information Retriever for Combing Unstructured Text (HAIRCUT), which incorporates five language-neutral techniques: character n-gram tokenization, a proprietary term similarity measure, a language model document similarity metric, pre-translation query expansion, and exploitation of parallel corpora. Through extensive empirical evaluation on multiple internationally developed test sets we have demonstrated that the knowledge-light, language-neutral approach used in HAIRCUT can achieve state-of-the-art retrieval performance. In this article we discuss the key techniques used by HAIRCUT and report on experiments verifying the efficacy of these methods.
Aging Affects Neural Synchronization to Speech-Related Acoustic Modulations

As people age, speech perception problems become highly prevalent, especially in noisy situations. In addition to peripheral hearing and cognition, temporal processing plays a key role in speech perception. Temporal processing of speech features is mediated by synchronized activity of neural oscillations in the central auditory system. Previous studies indicate that both the degree and hemispheric lateralization of synchronized neural activity relate to speech perception performance. Based on these results, we hypothesize that impaired speech perception in older persons may, in part, originate from deviances in neural synchronization. In this study, auditory steady-state responses that reflect synchronized activity of theta, beta, low and high gamma oscillations (i.e., 4, 20, 40, and 80 Hz ASSR, respectively) were recorded in young, middle-aged, and older persons. As all participants had normal audiometric thresholds and were screened for (mild) cognitive impairment, differences in synchronized neural activity across the three age groups were likely to be attributed to age. Our data yield novel findings regarding theta and high gamma oscillations in the aging auditory system. At an older age, synchronized activity of theta oscillations is increased, whereas high gamma synchronization is decreased. In contrast to young persons who exhibit a right hemispheric dominance for processing of high gamma range modulations, older adults show a symmetrical processing pattern. These age-related changes in neural synchronization may very well underlie the speech perception problems in aging persons.
FUZZY LOGIC BASED OVERCURRENT PROTECTION FOR MV NETWORKS

In the paper a novel approach to overcur- rent protection stabilisation based on Fuzzy Logic tech- nique is presented. The scheme is intended for MV over- head lines for which the autoreclosure function is applied to enhance reliability of supply in case of intermediate (vanishing) faults. Protection stabilisation is required for the feeders supplying a part of network with numerous loaded MV/LV transformers that may face inrush condi- tions after reenergising the line. Traditional harmonic restraint approach as for single transformer may not be effective for line overcurrent protection because of differ- ent current spectrum as measured at the MV busbars. The new FL protection developed takes both current and voltage signals for further processing and final decision is issued as a result of aggregation of partial decision sup- port coefficients. Application of signal fuzzification and fuzzy settings enables obtaining a relay with increased sensitivity, reliability and much faster than commonly available solutions. The developed fuzzy protection scheme has been tested with EMTP signals and compared with other standard protection approaches.
Evolving Game Agents Based on Adaptive Constraint of Evolution

Neuro-evolution (NE) has been highly effective in artificial intelligence (AI). Evolving multi-weights neural network (MWNN), which is always used in training game agents, is a kind of NE system. An important question in evolving MWNN is how to code real values onto binary strings and how to escape from premature convergence. We suggest a method called adaptive constraint of evolution (ACE), which can solve both problems of evolving MWNN represented as an non-player-character (NPC) in games based on real-coded genetic algorithm (RCGAs). ACE is then evaluated in training game agents to show its efficiency.
Length Minimization for Space Curves under Nonholonomic Constraints: the Constant Torsion Case

The Griiths formalism is applied to nd constant torsion curves which are extremal for arclength with respect to variations preserving torsion, xing the endpoints and the binormals at the endpoints. The critical curves are elastic rods of constant torsion, which are shown to not realize certain boundary conditions. In the calculus of variations under nonholonomic constraints, one tries to nd the least energy solution among candidates satisfying a given diierential equation. The subject has its roots in the investigations of such classical problems as the Delauney problem 5], where one tries to minimize length among curves in R 3 of xed constant curvature. It has broad applications in optimal control theory, especially in the use of the Pontrjagin maximum principle 10]. In recent years, the subject has come to the attention of geometers again, with the investigations of sub-Riemannian geometry 11], but also with the arrival of a beautiful reformulation of the criticality conditions, in coordinate-free form, due to Griiths and his collaborators 7, 8]. The stated aim in Griiths 1983 book 7] is \to get out formulas" for critical curves. In this note, we carry this out for the problem of length minimization among curves in R 3 of a xed nonzero constant torsion. This is among the examples to which Hsu 8] has applied the Griiths formalism, but here we go further, giving complete formulas for critical curves, and are able to extract more information about what boundary values can and cannot be achieved. This is due to the observation that the critical curves for this problem coincide exactly with the subset of Kirchhoo elastic rod centerlines having constant torsion, and the detailed description of these curves by Langer and Singer 9]. The constant torsion constraint is arrived at by considering of the general case. Suppose we adapt an orthornormal frame (T; U; V) along an oriented curve in R 3 , parametrized by arclength s, such that T is the unit tangent. The frame will satisfy generalized Frenet equations d ds 0 @ T U V 1 A = 0 @ 0 y p ? y 0 r ? p ? r 0 1 A 0 @ T U V 1 A If these vectors are regarded as attached to a rigid object moving along , the functions p; r; y may be visualized as pitch, roll and yaw, respectively. One may always rotate U and V so
Enhancing symbolic execution with built-in term rewriting and constrained lazy initialization

Symbolic execution suffers from problems when analyzing programs that handle complex data structures as their inputs and take decisions over non-linear expressions. For these programs, symbolic execution may incur invalid inputs or unidentified infeasible traces, and may raise large amounts of false alarms. Some symbolic executors tackle these problems by introducing executable preconditions to exclude invalid inputs, and some solvers exploit rewrite rules to address non linear problems. In this paper, we discuss the core limitations of executable preconditions, and address these limitations by proposing invariants specifically designed to harmonize with the lazy initialization algorithm. We exploit rewrite rules applied within the symbolic executor, to address simplifications of inverse relationships fostered from either program-specific calculations or the logic of the verification tasks. We present a symbolic executor that integrates the two techniques, and validate our approach against the verification of a relevant set of properties of the Tactical Separation Assisted Flight Environment. The empirical data show that the integrated approach can improve the effectiveness of symbolic execution.
Aesthetic Appreciation: The View From Neuroimaging

Our understanding of aesthetic appreciation has undergone a profound change during the past 20 years, as a result of the ability to study the human brain through neuroimaging. A number of findings cast into doubt important tenets of previous theories and models. Specifically, neuroscientific evidence suggests that aesthetic appreciation is not a distinct neurobiological process assessing certain objects, but a general system, centered on the mesolimbic reward circuit, for assessing the hedonic value of any sensory object. Furthermore, neuroscientific research also makes it clear that hedonic values are not determined solely by object properties, but subject to a range of object-extrinsic modulatory factors. This article reviews these findings and discusses how they demand a new experimental approach to aesthetic appreciation.
Research of TT&C signal sparsity based on two-stage dictionary learning

The Broadband is a notable trend of the TT&C system, which will be certain to lead to high speed sampling pressure and massive data problem. Theory of compressive sensing can solve the issue. However, signal sparsity is an important prerequisite for compressive sensing. On basis of the dictionary learning, the sparsity of DS TT&C signal was studied preliminarily. Through in-depth analysis of dictionary learning algorithms, a two-stage dictionary learning algorithm is provided that is combined with the DS TT&C signal feature, and the basic learning dictionary can be got. Then the performance of the sparse representation for the DS TT&C signal is studied by the simulation experiment. The results of simulation show that DS TT&C signal can get a strong sparsity in basic learning dictionary, which has some noise reduction performance.
GLUE-IT and PEDEL-AA: new programmes for analyzing protein diversity in randomized libraries

There are many methods for introducing random mutations into nucleic acid sequences. Previously, we described a suite of programmes for estimating the completeness and diversity of randomized DNA libraries generated by a number of these protocols. Our programmes suggested some empirical guidelines for library design; however, no information was provided regarding library diversity at the protein (rather than DNA) level. We have now updated our web server, enabling analysis of translated libraries constructed by site-saturation mutagenesis and error-prone PCR (epPCR). We introduce GLUE-Including Translation (GLUE-IT), which finds the expected amino acid completeness of libraries in which up to six codons have been independently varied (according to any user-specified randomization scheme). We provide two tools for assisting with experimental design: CodonCalculator, for assessing amino acids corresponding to given randomized codons; and AA-Calculator, for finding degenerate codons that encode user-specified sets of amino acids. We also present PEDEL-AA, which calculates amino acid statistics for libraries generated by epPCR. Input includes the parent sequence, overall mutation rate, library size, indel rates and a nucleotide mutation matrix. Output includes amino acid completeness and diversity statistics, and the number and length distribution of sequences truncated by premature termination codons. The web interfaces are available at http://guinevere.otago. ac.nz/stats.html.
Optimal Design of Nonlinear Series Elastic Actuator for Minimization of Actuator Power

In this paper, we propose a methodology to optimize the nonlinear stiffness of nonlinear Series Elastic Actuators (SEAs). The nonlinear restoring forces of the springs are optimized in order to minimize the mechanical power of the actuators of the SEAs. We define the cost function as the time average of the square of the actuator power, and use a 3 order Hermite interpolation to parameterize the restoring force of the nonlinear springs. The cost function is optimized using a Sequential Quadratic Programming (SQP) algorithm. We detail the bounds on the design parameters and the nonlinear optimization constraints. We show an example of optimal design in the case of a 3 Degree Of Freedom (DOF) manipulator, and in the last section we show that the optimal nonlinear springs calculated for this manipulator can be realized using a non-circular cable-spool mechanism.
Regulatory network features in Listeria monocytogenes—changing the way we talk

Our understanding of how pathogens shape their gene expression profiles in response to environmental changes is ever growing. Advances in Bioinformatics have made it possible to model complex systems and integrate data from variable sources into one large regulatory network. In these analyses, regulatory networks are typically broken down into regulatory motifs such as feed-forward loops (FFL) or auto-regulatory feedbacks, which serves to simplify the structure, while the functional implications of different regulatory motifs allow to make informed assumptions about the function of a specific regulatory pathway. Here we review the basic concepts of network features and use this language to break down the regulatory networks that govern the interactions between the main regulators of stress response, virulence, and transmission in Listeria monocytogenes. We point out the advantage that taking a “systems approach” could have for our understanding of gene functions, the detection of distant regulatory inputs, interspecies comparisons, and co-expression.
Increase in common cold symptoms and mouth ulcers following smoking cessation

Objective: To examine changes in reports of common cold symptoms and mouth ulcers following smoking cessation. It was hypothesised that reports of these symptoms would increase on stopping smoking. Design: Smokers were assessed one week before stopping smoking (baseline), then after one, two, and six weeks of smoking abstinence. Participants: 174 smokers attending a seven week smoking cessation programme combining behavioural support with nicotine patches. Main outcome measures: Self reports of cold symptoms, mouth ulcers, and smoking abstinence (validated using expired carbon monoxide) were recorded on each measurement occasion. Results: Following one, two, and six weeks of smoking abstinence 73.0% (127/174), 57.5% (100/174), and 44.8% (78/174) of the participants, respectively, maintained continuous abstinence and provided reports of cold symptoms and mouth ulcers. For those abstinent from smoking for six weeks, relative to baseline, a significant increase in reports of the number of cold symptoms was observed following one and two weeks of smoking abstinence (p = 0.009 and p = 0.038, respectively) and an increase in reports of mouth ulcers after one and two weeks of abstinence (p = 0.004 and p = 0.008, respectively). Following one week of abstinence significant increases in reports of sore throat, coughing, deafness, and sneezing were observed (p = 0.049, p < 0.001, p< 0.039, and p < 0.003, respectively). Conclusions: This is the first study to systematically document significant increases in cold symptoms and mouth ulcers following smoking cessation. Smokers should be informed that they have an increased chance of experiencing these symptoms on stopping smoking. Being psychologically prepared for these effects may reduce their impact on the attempt to stop smoking.
Synergy of volunteer measurements and volunteer computing for effective data collecting, processing, simulating and analyzing on a worldwide scale

The paper concerns the hype idea of “Citizen Science” and the related paradigm shift: to go from the passive “volunteer computing” to other volunteer actions like “volunteer measurements” under guidance of scientists. They can be carried out by ordinary people with standard computing gadgets (smartphone, tablet, etc.) and the various standard sensors in them. Here the special attention is paid to the system of volunteer scientific measurements to study air showers caused by cosmic rays. The technical implementation is based on integration of data about registered night flashes (by radiometric software) in shielded camera chip, synchronized time and GPS-data in ordinary gadgets: to identify night “air showers” of elementary particles; to analyze the frequency and to map the distribution of “air showers” in the densely populated cities. The project currently includes the students of the National Technical University of Ukraine “KPI”, which are compactly located in Kyiv city and contribute their volunteer measurements. The technology would be very effective for other applications also, especially if it will be automated (e.g., on the basis of XtremWeb or/and BOINC technologies for distributed computing) and used in some small area with many volunteers, e.g. in local communities (Corporative/Community Crowd Computing).
Artistic Talent Development for Urban Youth: The Promise and the Challenge. Research Monograph Series.

This longitudinal case study investigated issues that influence successful talent development in the arts and looked at the effects of long-term artistic involvement on the lives of 23 artistically talented young people in New York City. A widely varied group of students aged 10-26, who had all taken part in a dance or music program in their elementary school years, participated in the study. Interviews with the students, their families, arts instructors, school teachers, and other interested adults, provided multiple perspectives on their development as artists and the place that the arts played in their lives. The students' achievements and progress in both the arts and in school were examined through direct observations, academic records, and evaluations from arts instructors. The key issues of the study concern the nature of the obstacles faced by economically disadvantaged and minority students in pursuing artistic talent development and the factors that help some students overcome those obstacles. This study provides information that can help schools, cultural institutions, community organizations, and parents design interventions and programs to help young people who have the talent and drive, but few opportunities to pursue their dreams and aspirations.
Delay exponent of variable-length random binning for point-to-point transmission

Lossless coding for streaming sources is studied under a delay-constrained point-to-point setup. A variant of random binning, known as variable-length sequential random (VLSR) binning, is proposed for this setup. The performance of this binning scheme is evaluated by its delay exponent, which measures the asymptotic rate at which the decoding error probability decays with the delay. An achievable delay exponent is derived for VLSR binning, and numerical results show that the proposed binning achieves a better delay exponent than the existing fixed-length sequential random binning.
Importance sampling techniques for estimation of diffusion models

This article develops a class of Monte Carlo (MC) methods for simulating conditioned diffusion sample paths, with special emphasis on importance sampling schemes. We restrict attention to a particular type of conditioned diffusion, the so-called diffusion bridge processes. The diffusion bridge is the process obtained by conditioning a diffusion to start and finish at specific values at two consecutive times t0 < t1.
Economic analysis of Heart and Stroke Foundation of Ontario’s Hypertension Management Initiative

Objectives Hypertension is suboptimally treated in primary care settings. We evaluated the cost-effectiveness of the Heart and Stroke Foundation of Ontario’s Hypertension Management Initiative (HMI), an interdisciplinary, evidence-informed chronic disease management model for primary care that focuses on improving blood pressure management and control by primary care providers and patients according to clinical best practice guidelines. Methods The perspective of our analysis was that of the Ontario Ministry of Health and Long-Term Care with a lifetime horizon and 5% annual discount rate. Using data from a prospective cohort study from the HMI, we created two matched groups: pre-HMI (standard care), and post-HMI (n = 1720). For each patient, we estimated the 10-year risk of cardiovascular disease (CVD) using the Framingham risk equation and life expectancy from life tables. Long-term health care costs incurred with physician visits, acute and chronic care hospitalizations, emergency department visits, same-day surgeries, and medication use were determined through linkage to administrative databases, using a bottom-up approach. Results The HMI intervention was associated with significant reductions in systolic blood pressure (126 mmHg vs 134 mmHg with standard care; P-value < 0.001). These improvements were associated with a reduction in the 10-year risk of CVD (9.5% risk vs 10.7% in standard care; P-value < 0.001) and a statistically significant improvement in discounted life expectancy (9.536 years vs 9.516 in standard care; P-value < 0.001). The HMI cohort had a discounted mean lifetime cost of $22,884 CAD vs $22,786 CAD for standard care, with an incremental cost-effectiveness ratio of $4939 CAD per life-year gained. Conclusion We found that the HMI is a cost-effective means of providing evidence-informed, chronic disease management in primary care to patients with hypertension.