Miracle-dz/UniFAR-FTUs huggingface dataset:
Young Novice Drivers’ Cognitive Distraction Detection: Comparing Support Vector Machines and Random Forest Model of Vehicle Control Behavior

The use of mobile phones has become one of the major threats to road safety, especially in young novice drivers. To avoid crashes induced by distraction, adaptive distraction mitigation systems have been developed that can determine how to detect a driver’s distraction state. A driving simulator experiment was conducted in this paper to better explore the relationship between drivers’ cognitive distractions and traffic safety, and to better analyze the mechanism of distracting effects on young drivers during the driving process. A total of 36 participants were recruited and asked to complete an n-back memory task while following the lead vehicle. Drivers’ vehicle control behavior was collected, and an ANOVA was conducted on both lateral driving performance and longitudinal driving performance. Indicators from three aspects, i.e., lateral indicators only, longitudinal indicators only, and combined lateral and longitudinal indicators, were inputted into both SVM and random forest models, respectively. Results demonstrated that the SVM model with parameter optimization outperformed the random forest model in all aspects, among which the genetic algorithm had the best parameter optimization effect. For both lateral and longitudinal indicators, the identification effect of lateral indicators was better than that of longitudinal indicators, probably because drivers are more inclined to control the vehicle in lateral operation when they were cognitively distracted. Overall, the comprehensive model built in this paper can effectively identify the distracted state of drivers and provide theoretical support for control strategies of driving distraction.
Supercontinuum growth in a highly nonlinear fiber with a low-coherence semiconductor laser diode

A low-coherence, amplified, cw semiconductor laser diode is used as a pump to demonstrate supercontinuum (SC) generation in a highly nonlinear, dispersion-shifted fiber (HNLF). At a launch power of 1.6W into the anomalous-dispersion regime of 5km of HNLF, a SC extending from 1230nm to greater than 1770nm is achieved. The SC grows through the seeding effect of modulation instability that also converts the cw beam into short pulses so that subsequent spectral broadening becomes similar to pumping with pulsed laser sources. The experimental data show the manifestation of soliton self-frequency shift associated with a Stokes band as the launch power is increased. Amplification of the continuum noise with respect to the cw pump is also reported.
The transmission of vertical whole-body vibration to the body segments of standing subjects

Abstract The effects of body postures in standing position on the transmission of whole-body vibration to body segments have been investigated. The magnitude acceleration in the Z -axis direction of six body segments: the metatarsus, ankle, knee, hip, shoulder and head has been measured during exposure to random vibration. Ten male subjects exposed to floor vibration stood in ten postures described as: relaxed standing, legs stiffened, legs bent, standing on the toes, standing on one leg with or without support of the other foot and standing in steps. The transmissibility of random vibration from the floor to the body points was calculated at frequencies ranging from 4–250 Hz in 1/3 octave bands. The body postures of the subjects modified both the width of the resonant bands and the transmissibility values. The squared multiple correlation coefficient ( R 2 ) between the transmissibility and the 16 variables (10 postures, 6 body segments) was not very high at resonance frequencies in the range 4–12·5 Hz but above 25 Hz, 50% of the variability in the transmissibility was due to the postures and the body segments.
BraceNet: Graph-Embedded Neural Network For Brain Network Analysis

Multimodal brain networks extracted from functional magnetic resonance imaging (fMRI) characterize complex connectivities among brain regions from both structural and functional, showing great potential for mental health analysis. Deep neural network models have led a tremendous success in various downstream tasks. However, common property in brain network data, the small number of samples compared with the huge amount of features, hinders the application of deep learning techniques for brain network analysis. This work presents a graph-embedding method by leveraging the unique characteristics of brain networks to unleash the power of deep neural networks and achieve outstanding prediction performance with proper explainability. Experiment results show clear advancements in our proposed braceNet on both real and synthetic datasets.
Electro-Tunable Defect Mode in One-Dimensional Periodic Structure Containing Nematic Liquid Crystal as a Defect Layer

Electrical tuning of defect modes in a one-dimensional periodic structure has been demonstrated using a nematic liquid crystal as a defect layer in the periodic structure. The wavelength of the defect mode shifts upon applying the electric field, which is due to the refractive index change in the defect layer caused by the field-induced realignment of the liquid crystal molecules. The theoretical calculation based on a simple transfer matrix has been carried out, and the result has been found to agree with the experimental result.
In Tandem Control of La-Doping and CuO-Heterojunction on SrTiO3 Perovskite by Double-Nozzle Flame Spray Pyrolysis: Selective H2 vs. CH4 Photocatalytic Production from H2O/CH3OH

ABO3 perovskites offer versatile photoactive nano-templates that can be optimized towards specific technologies, either by means of doping or via heterojunction engineering. SrTiO3 is a well-studied perovskite photocatalyst, with a highly reducing conduction-band edge. Herein we present a Double-Nozzle Flame Spray Pyrolysis (DN-FSP) technology for the synthesis of high crystallinity SrTiO3 nanoparticles with controlled La-doping in tandem with SrTiO3/CuO-heterojunction formation. So-produced La:SrTiO3/CuO nanocatalysts were optimized for photocatalysis of H2O/CH3OH mixtures by varying the La-doping level in the range from 0.25 to 0.9%. We find that, in absence of CuO, the 0.9La:SrTiO3 material achieved maximal efficient photocatalytic H2 production, i.e., 12 mmol g−1 h−1. Introduction of CuO on La:SrTiO3 enhanced selective production of methane CH4. The optimized 0.25La:SrTiO3/0.5%CuO catalyst achieved photocatalytic CH4 production of 1.5 mmol g−1 h−1. Based on XRD, XRF, XPS, BET, and UV-Vis/DRS data, we discuss the photophysical basis of these trends and attribute them to the effect of La atoms in the SrTiO3 lattice regarding the H2-production, plus the effect of interfacial CuO on the promotion of CH4 production. Technology-wise this work is among the first to exemplify the potential of DN-FSP for scalable production of complex nanomaterials such as La:SrTiO3/CuO with a diligent control of doping and heterojunction in a single-step synthesis.
Microsatellite Instability and Aberrant Pre-mRNA Splicing: How Intimate Is It?

Cancers that belong to the microsatellite instability (MSI) class can account for up to 15% of all cancers of the digestive tract. These cancers are characterized by inactivation, through the mutation or epigenetic silencing of one or several genes from the DNA MisMatch Repair (MMR) machinery, including MLH1, MLH3, MSH2, MSH3, MSH6, PMS1, PMS2 and Exo1. The unrepaired DNA replication errors turn into mutations at several thousand sites that contain repetitive sequences, mainly mono- or dinucleotides, and some of them are related to Lynch syndrome, a predisposition condition linked to a germline mutation in one of these genes. In addition, some mutations shortening the microsatellite (MS) stretch could occur in the 3′-intronic regions, i.e., in the ATM (ATM serine/threonine kinase), MRE11 (MRE11 homolog) or the HSP110 (Heat shock protein family H) genes. In these three cases, aberrant pre-mRNA splicing was observed, and it was characterized by the occurrence of selective exon skipping in mature mRNAs. Because both the ATM and MRE11 genes, which as act as players in the MNR (MRE11/NBS1 (Nibrin)/RAD50 (RAD50 double strand break repair protein) DNA damage repair system, participate in double strand breaks (DSB) repair, their frequent splicing alterations in MSI cancers lead to impaired activity. This reveals the existence of a functional link between the MMR/DSB repair systems and the pre-mRNA splicing machinery, the diverted function of which is the consequence of mutations in the MS sequences.
Revisiting Microstructure Sensor Responses with Implications for Double-Diffusive Fluxes

Thinhigh-gradientinterfacesthatoccurnaturallywithindouble-diffusivestaircasesareusedtoestimatethe response characteristics of temperature and conductivity microstructure sensors. The knowledge of these responses is essentialfor resolvingsmall-scaleturbulencein natural waterbodies and for determining doublediffusive fluxes of heat and salt. Here, the authors derive microstructure sensor responses from observed differences in the statistical distributions of interface thicknesses at various profiling speeds in Lake Kivu (central Africa). In contrast to the standard approach for determining sensor responses, this method is independent of any knowledge of the true in situ temperature and salinity structure. Assuming double-pole frequency response functions, the time constants for the Sea-Bird Electronics SBE-7 conductivity sensor and the Rockland Scientific International FP07 thermistor are estimated to be 2.2 and 10ms, respectively. In contrast to previous assumptions, the frequency response for the SBE-7 is found to be substantial and dominates the wavenumber response for profiling speeds larger than 0.19ms 21 .
Full-Spectrum INFT Algorithm for Dual-Polarization NFDM Transmission

Nonlinear Fourier transform (NFT)-based nonlinear frequency division multiplexing (NFDM) system has the potential to overcome the limit of fiber nonlinearity. In the NFDM system, the symbol information is modulated onto the nonlinear spectra, which consist of continuous and discrete spectrum. In theory, the dual-polarization (DP) NFDM system with the continuous and discrete spectrum (full spectrum, FS) modulation has the potential to achieve higher spectral efficiency. However, due to the complexity of the NFT and inverse NFT (INFT) numerical algorithms, the DP-FS modulated NFDM system is rarely reported. For the FS-NFDM system, the existing INFT algorithms either only support q-modulation and present poor performance, or have large discrete spectral error as the continuous spectrum energy increases. In this paper, we propose an INFT algorithm design theory. Based the theory, an accurate DP-INFT algorithm is proposed. The algorithm supports not only q-modulation, but also b-modulation with better performance. Employing the proposed INFT algorithm, we demonstrate, for the first time, a 174.5 Gbit/s FS modulated NFDM transmission system with 1440 km.
Collisions in soccer kicking

An equation to describe the velocity of the soccer ball after the collision with a foot was derived. On the basis of experimental results it was possible to exclude certain factors and only describe the angular momentum of the system, consisting of the shank, the foot and the ball, leading to an equation that was simple and useful. Furthermore, it was found that the main reasons for changes in ball velocity are the velocity of the foot before impact and the coefficient of restitution. The mass of the shank–foot segment does not influence the velocity of the ball significantly.
Spin-spin correlation functions in the frustrated two-dimensional planar model

The low-temperature limit of the frustrated 2-D $x\ensuremath{-}y$ model is studied via the generalized Villain model. The spin-spin correlation functions are calculated for two limits of the density of frustrated plaquettes "${x}_{f}$. " In the dilute case the model is described in terms of the usual spin waves, vortex and symmetry-breaking excitations, plus the "curved" or frustrated half-integer static charges. In this limit, to lowest order in ${x}_{f}$, the infinite susceptibility phase of the ferromagnetic model remains. The stability of this result is shown to hold including higher excited states for the static vortices although there seems to be a lower critical temperature. In the special limit ${x}_{f}\ensuremath{\sim}\frac{1}{2}$ a model with only vortex, symmetry-breaking, and frustrated plaquettes is studied. The spin-spin correlation functions are calculated for large separation distances. There, the susceptibility has an exponential behavior to lowest order in an expansion in the density of thermal vortices. We discuss under which conditions this result would lead us to the nonexistence of spin-glass ordering for the planar model in two dimensions.
Spoken Word Recognition across Language Boundary: ERP Evidence of Prosodic Transfer Driven by Pitch

Extensive research has explored the perception of English lexical stress by Chinese EFL learners and tried to unveil the underlying mechanism of the prosodic transfer from a native tonal language to a non-native stress language. However, the role of the pitch as the shared cue by lexical stress and lexical tone during the transfer remains controversial when the segmental cue (i.e., reduced vowel) is absent. By employing event-related potential (ERP) measurements, the current study aimed to further investigate the role of the pitch during the prosodic transfer from L1 lexical tone to L2 lexical stress and the underlying neural responses. Two groups of adult Chinese EFL learners were compared, as both Mandarin and Cantonese are tonal languages with different levels of complexity. The results showed that Cantonese speakers relied more than Mandarin speakers on pitch cues, not only in their processing of English lexical stress but also in word recognition. Our findings are consistent with the arguments of Cue Weighting and attest to the influence of native tonal language experience on second language acquisition. The results may have implications on pedagogical methods that pitch could be an important clue in second language teaching.
QuoGNN: Quotient Graph Neural Network for Urban Flow Forecasting

Urban traffic flow prediction plays a crucial role in smart city management. Since the flow volume of one road (treated as a node in a traffic network) in future time units (after time t) depends on the historical volume (before and including time t) of this road (node) itself and its neighboring roads (nodes), the traffic flow prediction problem has recently been studied by utilizing a spatial-temporal adjacency matrix (AM) of traffic nodes constructed from the historical traffic and node connections. The construction of AM is often based on statistical traffic information before t, instead of using the volume at individual time unit level. In addition, the spatial and temporal relations between traffic nodes are manually fused in AM, rather than in a trainable fusion. In order to conquer these issues, we propose a trainable context enhanced similarity graph, which fuses the unit-level similarity of traffic time series and multiple inter-node contextual relations through a learnable embedding model. In addition, a Quotient Neural Network is proposed to perceive the explicit relation among short-memory flow values and facilitate the forecasting. Based on the two modules, we propose a novel Quotient Graph Neural Network (QuoGNN). Experiments on four real-world benchmark datasets demonstrate the superior performance of our proposed model over the state-of-the-art baselines on multiple evaluation metrics. The implementation of the model and datasets are available1.
The effect of favouritism on employee competencies in the hotel industry: Mediating role of employee silence

This study aims to examine the effect of favouritism on competencies through employee silence. The phenomenon of employee silence has been defined as a mediating variable that is affected by favouritism, and which affects employee competencies. Data collected from 420 employees working in hotels in the Thrace Region based on a face-to-face survey method were used to test the research hypotheses with partial least square structural equation modelling (PLS-SEM). The results reveal that favouritism is an obstacle that causes employee silence and, more importantly, reduces the competencies of employees, as they are not treated fairly in terms of their skills, experience, knowledge, and abilities. In addition, it may be concluded that employee silence is a factor that directly reduces competencies. While there is some discussion about the possible impacts of obstacles such as favouritism and employee silence on competencies, it can be observed that there are few studies that address their relationship separately. This research is among the first to empirically reveal employee silence as the mediator between favouritism practices and employee competencies, expanding the understanding of how silence can work as a mediator in the hospitality businesses.
Stochastic orders in partition and random testing of software

Testing in order to produce software of high reliability is an area of major concern in software engineering. In an effort to find efficient methods of testing, the comparison of partition and random sampling testing methods has received considerable attention in the literature. A standard criterion for comparisons between random and partition testing, based on their expected efficacy in program debugging, is the probability of detecting at least one failure causing input in the program's domain. However, the goal in software testing is usually to find as many faults as possible in a reasonable period of time, and therefore stochastic comparisons of the number of faults obtained in partition and random testing may provide more valuable information on which testing procedures to use. We establish various conditions which guarantee that the number of faults discovered in partition testing is stochastically greater than the number discovered in random testing (using a fixed total sample size) for many of the well-established stochastic orders (including the usual stochastic order, the hazard rate order, the likelihood ratio order, and the variability order). The results established also allow us to obtain both upper and lower bounds with these stochastic orders for the sum of n independent Bernoulli random trials (with varying probability of success) in terms of the binomial distribution with parameters n and p.
An Efficient Compressive Sensed Video Codec with Inter-Frame Decoding and Low-Complexity Intra-Frame Encoding

This paper is dedicated to video coding based on a compressive sensing (CS) framework. In CS, it is assumed that if a video sequence is sparse in some transform domain, then it could be reconstructed from a much lower number of samples (called measurements) than the Nyquist–Shannon theorem requires. Here, the performance of such a codec depends on how the measurements are acquired (or sensed) and compressed and how the video is reconstructed from the decoded measurements. Here, such a codec potentially could provide significantly faster encoding compared with traditional block-based intra-frame encoding via Motion JPEG (MJPEG), H.264/AVC or H.265/HEVC standards. However, existing video codecs based on CS are inferior to the traditional codecs in rate distortion performance, which makes them useless in practical scenarios. In this paper, we present a video codec based on CS called CS-JPEG. To the author’s knowledge, CS-JPEG is the first codec based on CS, combining fast encoding and high rate distortion results. Our performance evaluation shows that, compared with the optimized software implementations of MJPEG, H.264/AVC, and H.265/HEVC, the proposed CS-JPEG encoding is 2.2, 1.9, and 30.5 times faster, providing 2.33, 0.79, and 1.45 dB improvements in the peak signal-to-noise ratio, respectively. Therefore, it could be more attractive for video applications having critical limitations in computational resources or a battery lifetime of an upstreaming device.
Putative Mitoviruses without In-Frame UGA(W) Codons: Evolutionary Implications

Mitoviruses are small vertically transmitted RNA viruses found in fungi, plants and animals. Taxonomically, a total of 105 species and 4 genera have been formally recognized by ICTV, and recently, 18 new putative species have been included in a new proposed genus. Transcriptomic and metatranscriptomic studies are a major source of countless new virus-like sequences that are continually being added to open databases and these may be good sources for identifying new putative mitoviruses. The search for mitovirus-like sequences in the NCBI databases resulted in the discovery of more than one hundred new putative mitoviruses, with important implications for taxonomy and also for the evolutionary scenario. Here, we propose the inclusion of four new putative members to the genus Kvaramitovirus, and the existence of a new large basally divergent lineage composed of 144 members that lack internal UGA codons (subfamily “Arkeomitovirinae”), a feature not shared by the vast majority of mitoviruses. Finally, a taxonomic categorization proposal and a detailed description of the evolutionary history of mitoviruses were carried out. This in silico study supports the hypothesis of the existence of a basally divergent lineage that could have had an impact on the early evolutionary history of mitoviruses.
On the asymptotic properties of ldu-based tests of the rank of a matrix

Abstract Gill and Lewbel recently introduced a test for the rank of a matrix based on the LDU decomposition. Unfortunately, the asymptotic distribution suggested by them is incorrect except in a very limited problem. In general, the asymptotic distribution is that of a highly complicated nonlinear function of a normally distributed random vector that appears to defy useful characterization. The LDU decomposition can be used to produce a valid test asymptotically equivalent to the minimum-X 2 test.
Blow-Up in Quasilinear Parabolic Equations

The aim of the series is to present new and important developments in pure and applied mathematics. Well established in the community over two decades, it offers a large library of mathematics including several important classics. The volumes supply thorough and detailed expositions of the methods and ideas essential to the topics in question. In addition, they convey their relationships to other parts of mathematics. The series is addressed to advanced readers wishing to thoroughly study the topic. Editorial Board Lev Birbrair, Universidade Federal do Ceara, Fortaleza, Brasil Victor P. Maslov, Russian Academy of Sciences, Moscow, Russia Walter D. Neumann, Columbia University, New York, USA Markus J. Pflaum, University of Colorado, Boulder, USA Dierk Schleicher, Jacobs University, Bremen, Germany"