Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Information Matrix in Mixed Logit Models Estimation

Advanced discrete choice models—in particular, mixed logit models—are used extensively in transportation. Although much progress in estimation techniques has made them numerically appealing, their properties have not been fully explored. This lack of exploration sometimes leads to confusing quality measurements and misinterpretation of the estimates. In this paper, the regularity conditions for which the information equality holds are reviewed, and some underlying technical difficulties in the context of mixed logit modeling are discussed. This paper specifically addresses the questions of correlations between estimated parameters and the validity of the asymptotic normality assumption in complex models, as nonparametric formulations. In the latter case, the population is resampled with the use of bootstrap principles to construct confidence intervals on the estimated parameters. Numerical tests on simulated data are presented to assess the relevance of the problem and the validity of the methods proposed.
Large eddy simulations of Taylor-Couette-Poiseuille flows in a narrow-gap system

The present paper concerns Large-Eddy Simulations (LES) of turbulent Taylor-Couette-Poiseuille flows in a narrow-gap cavity for six different combinations of rotational and axial Reynolds numbers. The in-house numerical code has been first validated in a middle-gap cavity. Two sets of refined LES results, using the Wall-Adapting Local Eddy Viscosity (WALE) and the Dynamic Smagorinsky subgrid-scale models available within an in-house code based on high-order compact schemes, have been then compared with no noticeable difference on the mean flow field and the turbulent statistics. The WALE model enabling a saving of about 12% of computational effort has been finally used to investigate the influence on the hydrodynamics of the swirl parameter N within the range [1.49 − 6.71]. The swirl parameter N, which compares the effects of rotation of the inner cylinder and the axial flowrate, does not influence significantly the mean velocity profiles. Turbulence intensities are enhanced with increasing values of N with remarkably high peak values within the boundary layers. The inner rotating cylinder has a destabilizing effect inducing asymmetric profiles of the Reynolds stress tensor components. The rotor and stator boundary layers exhibit the main characteristics of two-dimensional boundary layers. Turbulence is also mainly at two-component there. Thin coherent structures appearing as negative (resp. positive) spiral rolls are observed along the rotor (resp. stator) side. Their inclination angle depends strongly on the value of the swirl parameter, which fixes the intensity of the crossflow. On the other hand, the intensity and the size of the coherent structures observed within the boundary layers are governed by the effective Reynolds number. For its highest value, they penetrate the whole gap. Finally, the results have been extended to the non-isothermal case in the forced convection regime. A correlation for the Nusselt number along the rotor has been provided showing a much larger dependence on the axial Reynolds number than expected from previous published works, while it depends classically on the Taylor number to the power 0.145 and on the Prandtl number to the power 0.3.
Experimental and numerical investigation of boundary layer and wake development in a transonic turbine cascade

The flow in a transonic rotor cascade is investigated by both experimental and numerical methods. Measurements include pressure profiles on the blade, total pressure profiles in the blade vane, boundary layer and wake profiles. Computations are performed by two different solvers with different turbulence models and three different transition models. Results indicate that the indroduction of transition models is necessary to have a realistic description of the flow field. Transition is shown to affect also the blade pressure distribution and shock strength mostly on the pressure side boundary layer. Experiments indicate the presence of trailing edge vortex shedding which is not captured by the steady computations. The transition models seem to be adequate for predicting the shock -boundary layer- interaction which induces a small flow separation on the suction side
Transportan 10 Induces Perturbation and Pores Formation in Giant Plasma Membrane Vesicles Derived from Cancer Liver Cells

Continuous progress has been made in the development of new molecules for therapeutic purposes. This is driven by the need to address several challenges such as molecular instability and biocompatibility, difficulties in crossing the plasma membrane, and the development of host resistance. In this context, cell-penetrating peptides (CPPs) constitute a promising tool for the development of new therapies due to their intrinsic ability to deliver therapeutic molecules to cells and tissues. These short peptides have gained increasing attention for applications in drug delivery as well as for their antimicrobial and anticancer activity but the general rules regulating the events involved in cellular uptake and in the following processes are still unclear. Here, we use fluorescence microscopy methods to analyze the interactions between the multifunctional peptide Transportan 10 (TP10) and the giant plasma membrane vesicles (GPMVs) derived from cancer cells. This aims to highlight the molecular mechanisms underlying functional interactions which bring its translocation across the membrane or cytotoxic mechanisms leading to membrane collapse and disruption. The Fluorescence Lifetime Imaging Microscopy (FLIM) method coupled with the phasor approach analysis proved to be the winning choice for following highly dynamic spatially heterogeneous events in real-time and highlighting aspects of such complex phenomena. Thanks to the presented approach, we were able to identify and monitor TP10 translocation into the lumen, internalization, and membrane-induced modifications depending on the peptide concentration regime.
Personality in Daily Life: Multi-Situational Physiological Signals Reflect Big-Five Personality Traits

The popularity of wearable physiological recording devices has opened up new possibilities for the assessment of personality traits in everyday life. Compared with traditional questionnaires or laboratory assessments, wearable device-based measurements can collect rich data about individual physiological activities in real-life situations without interfering with normal life, enabling a more comprehensive description of individual differences. The present study aimed to explore the assessment of individuals’ Big-Five personality traits by physiological signals in daily life situations. A commercial bracelet was used to track the heart rate (HR) data from eighty college students (all male) enrolled in a special training program with a strictly-controlled daily schedule for ten consecutive working days. Their HR activities were divided into five daily situations (morning exercise, morning classes, afternoon classes, free time in the evening, and self-study situations) according to their daily schedule. Regression analyses with HR-based features in these five situations averaged across the ten days revealed significant cross-validated quantitative prediction correlations of 0.32 and 0.26 for the dimensions of Openness and Extraversion, with the prediction correlation trending significance for Conscientiousness and Neuroticism. Moreover, the multi-situation HR-based results were in general superior to those based on single-situation HR-based features, as well as those based on the multi-situation self-reported emotion ratings. Togetherour findings demonstrate the link between personality and daily HR measures using state-of-the-art commercial devices and could shed light on the development of Big-Five personality assessment based on daily multi-situation physiological measures.
Purifying selection decreases the potential for Bangui orthobunyavirus outbreaks in humans

Abstract Pathogens carried by insects, such as bunyaviruses, are frequently transmitted into human populations and cause diseases. Knowing which spillover events represent a public health threat remains a challenge. Metagenomic next-generation sequencing (mNGS) can support infectious disease diagnostics by enabling the detection of any pathogen from clinical specimens. mNGS was performed on blood samples to identify potential viral coinfections in human immunodeficiency virus (HIV)-positive individuals from Kinshasa, the Democratic Republic of the Congo (DRC), participating in an HIV diversity cohort study. Time-resolved phylogenetics and molecular assay development assisted in viral characterization. The nearly complete genome of a novel orthobunyavirus related to Nyangole virus, a virus previously identified in neighboring Uganda, was assembled from a hepatitis B virus–positive patient. A quantitative polymerase chain reaction assay was designed and used to screen >2,500 plasma samples from Cameroon, the DRC, and Uganda, failing to identify any additional cases. The recent sequencing of a US Center for Disease Control Arbovirus Reference Collection revealed that this same virus, now named Bangui virus, was first isolated in 1970 from an individual in the Central African Republic. Time-scaled phylogenetic analyses of Bangui with the related Anopheles and Tanga serogroup complexes indicate that this virus emerged nearly 10,000 years ago. Pervasive and episodic models further suggest that this virus is under purifying selection and that only distant common ancestors were subject to positive selection events. This study represents only the second identification of a Bangui virus infection in over 50 years. The presumed rarity of Bangui virus infections in humans can be explained by its constraint to an avian host and insect vector, precluding efficient transmission into the human population. Our results demonstrate that molecular phylogenetic analyses can provide insights into the threat posed by novel or re-emergent viruses identified by mNGS.
An intelligent film recommender system based on emotional analysis

The existing personalized film recommendation methods take the user’s historical rating as an important basis for recommendation. However, the user’s rating standards are different, so it is difficult to mine the user’s real preferences and form accurate push. Therefore, to achieve high-quality personalized recommendation of films, it is particularly important to mine the emotion of user reviews. In this article, a personalized recommendation method based on sentiment analysis of film reviews is proposed, where natural language processing technology is used to mine the emotional tendency of user reviews. The multi-modal emotional features are weighted and the weighted fusion feature vector after PSO is taken as the overall emotion vector, then the emotional similarity of weighted fusion is calculated by considering the time factor of content publishing and the average emotional tendency of users. By calculating the matching degree of emotional value between users and films, the top-N film recommendation for target users is given. The test results show that the effect of the personalized film recommendation system based on multimodality is superior to that of the comparison method, which effectively solves the problem of different user rating scales, and really increases users’ interest in watching films.
Exploring the Onset of Phonetic Drift in Voice Onset Time Perception

Recent exposure to a second or foreign language (FL) can influence production and/or perception in the first language (L1), a phenomenon referred to as phonetic drift. The smallest amount of FL exposure shown to effect drift in perception is 1.5 h. The present study examined L1 perception at earlier timepoints of FL exposure, to determine whether the phonetic system is able to resist FL influence at an incipient stage. In a longitudinal pre-test/post-test design, L1 English listeners were exposed to Tagalog under different conditions varying in attention directed to the voice onset time (VOT) plosive contrast in the FL; they then completed an identification task on L1 tokens from VOT continua. In every condition, the likelihood of “voiceless” identifications decreased. This change indicates a shift towards a longer VOT crossover point between “voiced” and “voiceless”, consistent with dissimilatory drift in perception. Listeners in a control condition, however, displayed a similar, albeit less lasting, change in L1 judgments, suggesting that the change arose partly from a task effect. We conclude by discussing directions for future research on phonetic drift in perception.
Measurements of alloy composition and strain in thin GexSi1−x layers

The utility of Raman spectroscopy for the simultaneous determination of composition and strain in thin GexSi1−x layers has been investigated. Using data from the literature and new data for the strain shift of the Si‐Si phonon mode presented here, we show how Raman spectra provide several different means of measuring composition and strain in samples as thin as 200 A. We demonstrate that for largely relaxed layers with compositions near x=0.30, Raman scattering can measure the composition, x, with an accuracy of ±0.015 and the strain, e, with an accuracy ±0.0025. The accuracy of the alloy composition obtained from Raman spectra is comparable or, in the case of very thin layers, superior to that measured by other techniques such as x‐ray diffraction, electron microprobe, and Auger electron spectroscopy.
Nonthermal X-Ray Emission from the Shell-Type Supernova Remnant G347.3–0.5

Recent ASCA observations of G347.3-0.5, a supernova remnant (SNR) discovered in the ROSAT All-Sky Survey, reveal nonthermal emission from a region along the northwestern shell. Here we report on new pointed ASCA observations of G347.3-0.5 that confirm this result for all the bright shell regions and also reveal similar emission, although with slightly different spectral properties, from the remainder of the SNR. Curiously, no thermal X-ray emission is detected anywhere in the remnant. We derive limits on the amount of thermal emitting material present in G347.3-0.5 and present new radio continuum, CO, and infrared results that indicate that the remnant is distant and of moderate age. We show that our observations are broadly consistent with a scenario that has most of the supernova remnant shock wave still within the stellar wind bubble of its progenitor star, while part of it appears to be interacting with denser material. A point source at the center of the remnant has spectral properties similar to those expected for a neutron star and may represent the compact relic of the supernova progenitor.
Syndecan-1 predicts hemodynamic instability in critically ill patients under intermittent hemodialysis

ABSTRACT Introduction Up to 70% of intermittent hemodialysis (IHD) sessions in critically ill patients are complicated by hemodynamic instability. Although several clinical characteristics have been associated with hemodynamic instability during IHD, the discriminatory capacity of predicting such events during IHD sessions is less defined. In the present study, we aimed to analyse endothelium-related biomarkers collected before IHD sessions and their capacity to predict hemodynamic instability related to IHD in critically ill patients. Methods In this prospective observational study, we enrolled adult critically ill patients with acute kidney injury who required fluid removal with IHD. We screened each included patient daily for IHD sessions. Thirty minutes before each IHD session, each patient had a 5-mL blood collection for measurement of endothelial biomarkers—vascular cell adhesion molecule-1 (VCAM-1), angiopoietin-1 and -2 (AGPT1 and AGPT2) and syndecan-1. Hemodynamic instability during IHD was the main outcome. Analyses were adjusted for variables already known to be associated with hemodynamic instability during IHD. Results Plasma syndecan-1 was the only endothelium-related biomarker independently associated with hemodynamic instability. The accuracy of syndecan-1 for predicting hemodynamic instability during IHD was moderate [area under the receiver operating characteristic curve 0.78 (95% confidence interval 0.68–0.89)]. The addition of syndecan-1 improved the discrimination capacity of a clinical model from 0.67 to 0.82 (P < .001) and improved risk prediction, as measured by net reclassification improvement. Conclusion Syndecan-1 is associated with hemodynamic instability during IHD in critically ill patients. It may be useful to identify patients who are at increased risk for such events and suggests that endothelial glycocalyx derangement is involved in the pathophysiology of IHD-related hemodynamic instability.
Influence of the active-to-passive area ratio on the electrically induced strain of a fiber-reinforced dielectric elastomer actuator

There is an increasing interest to use novel elastomers with inherent or modified advanced dielectric and mechanical properties, as components of dielectric elastomer actuators (DEA). This requires corresponding techniques to assess their electromechanical performance. One performance criterion is the electrically induced deformation of the active electrode area. In this work, a rectangular DEA is used to investigate the influence of the ratio between the active electrode and the passive area on the actuator deformation. For this purpose, a dielectric silicone film is bonded on one surface to a unidirectional carbon fiber fabric. Thereby, highly anisotropic mechanical properties are implemented. When strains are applied perpendicular to the fiber direction, the composite hardly contracts in the fiber direction due to the superior stiffness of the fibers. In addition, the conductive fiber structure also acts as a highly anisotropic compliant electrode. By application of a second paste-like electrode onto the silicone film a DEA is created that operates in a pure shear configuration. This assembly enables the modification of the active-to-passive area ratio and the investigation of its effect on the actuator deformation. Image-based measurements are used to determine the strain of the active electrode area. The experimental results are compared to a lumped-parameter model that considers the electromechanical properties of the fiber-reinforced DEA. In summary, the ratio of the active-to-passive area has a significant influence on the measured deformation. Especially for novel actuator materials that do not exhibit large strains, an active-to-passive ratio of 50 % proves to be particularly advantageous.
A new hierarchical particle-mesh code for very large scale cosmological N-body simulations

An improved three-dimensional hierarchical particle-mesh (HPM) N-body code for the gravitational evolution of structure in the universe has been developed and tested. The basis of the code is a standard particle-mesh (PM) code where Poisson's equation is solved on a critical grid with fast Fourier transform techniques and periodic boundary conditions. Several subgrids and father grids can fit into a cube. The fields from the father grid, and its father grid, and so on, are treated as external fields. There is no back-reaction to father grids, and particles can enter and exit subgrids. In a four grid code the dynamic range can be extended to 6000 in length and 11 orders of magnitude in mass. The initial conditions are generated with a random phase realization of the power spectrum of the growing mode using the Zel'dovich approximation (1970). The HPM code is much faster than tree codes and particle-particle-mesh codes, and has a much larger dynamic range. 28 refs.
The chemical evolution of a galactic disc with infall and radial motions

Un modele d'evolution chimique du disque galactique est developpe. Il considere un disque en rotation dans un equilibre centrifuge, dans le champ gravitationnel du disque et du halogalactique. Les resultats numeriques de l'evolution du disque avec accretion et ecoulement radial, dans le cas ou le taux de formation stellaire est proportionnel au carre de la densite de surface du gaz, sont presentes
Advancing DNA Barcoding to Elucidate Elasmobranch Biodiversity in Malaysian Waters

Simple Summary One-third of shark and ray species are threatened due to overfishing, but a lack of information on each species makes conservation decisions difficult. To address this issue, we conducted a study to identify the different species of sharks and rays in Malaysian waters using DNA barcoding of the CO1 gene, which is akin to DNA fingerprinting for species. We collected 175 individuals between June 2015 and June 2022, randomly selecting up to six specimens from each species. We successfully generated DNA barcodes for 67 species, belonging to 44 genera, 20 families, and 11 orders. Accurate species identification will improve species-specific catch landing data and accelerate the identification of use and illegal trade in Malaysia. Abstract The data provided in this article are partial fragments of the Cytochrome c oxidase subunit 1 mitochondrial gene (CO1) sequences of 175 tissues sampled from sharks and batoids collected from Malaysian waters, from June 2015 to June 2022. The barcoding was done randomly for six specimens from each species, so as to authenticate the code. We generated barcodes for 67 different species in 20 families and 11 orders. DNA was extracted from the tissue samples following the Chelex protocols and amplified by polymerase chain reaction (PCR) using the barcoding universal primers FishF2 and FishR2. A total of 654 base pairs (bp) of barcode CO1 gene from 175 samples were sequenced and analysed. The genetic sequences were blasted into the NCBI GenBank and Barcode of Life Data System (BOLD). A review of the blast search confirmed that there were 68 valid species of sharks and batoids that occurred in Malaysian waters. We provided the data of the COI gene mid-point rooting phylogenetic relation trees and analysed the genetic distances among infra-class and order, intra-species, inter-specific, inter-genus, inter-familiar, and inter-order. We confirmed the addition of Squalus edmundsi, Carcharhinus amboinensis, Alopias superciliosus, and Myliobatis hamlyni as new records for Malaysia. The establishment of a comprehensive CO1 database for sharks and batoids will help facilitate the rapid monitoring and assessment of elasmobranch fisheries using environmental DNA methods.
Detecting Weak Physical Signal from Noise: A Machine-Learning Approach with Applications to Magnetic-Anomaly-Guided Navigation

Detecting a weak physical signal immersed in overwhelming noises entails separating the two, a task for which machine learning is naturally suited. In principle, such a signal is generated by a nonlinear dynamical system of intrinsically high dimension for which a mathematical model is not available, rendering unsuitable traditional linear or nonlinear state-estimation methods that require an accurate system model (e.g., extended Kalman ﬁlters). We exploit the architectures of reservoir computing and feed-forward neural networks (FNNs) with time-delayed inputs to solve the weak-signal-detection problem. As a prototypical example, we apply the machine-learning schemes to Earth’s magnetic anomaly ﬁeld-based navigation. In particular, the time series are collected from the interior of the cockpit of a ﬂying aircraft during diﬀerent maneuvering phases, where the overwhelmingly strong noise background is the result of other components of Earth’s magnetic ﬁeld and the ﬁelds generated by the electronic devices in the cockpit. We demonstrate that, when combined with the traditional Tolles-Lawson model for Earth’s magnetic ﬁeld, the articulated machine-learning schemes are eﬀective for accurately detecting the weak anomaly ﬁeld from the noisy time series. The schemes can be applied to detecting weak signals in other domains of science and engineering.