Miracle-dz/UniFAR-FTUs huggingface dataset:
Est-il possible d’annoter la naturalité des pauses lors de la lecture d’un texte à haute voix ?

Vincent P. Martin1 Jean-Luc Rouas1 Agathe Basse2 Benoît Caudron2 Marie Huillet2 Pierre Philip3 (1) LaBRI, Univ. Bordeaux, CNRS UMR 5800, Bordeaux INP, 256 cours de la Libération, 33405 Talence, France (2) CFUOB, Univ. Bordeaux, 146 Rue Léo Saignat, 33076 Bordeaux, France (3) SANPSY, Univ. Bordeaux, CNRS UMR 6033, CHU de Bordeaux, 13ème étage, aile 3, Place Amélie-Raba-Léon, 33076 Bordeaux, France {vincent.martin,rouas}@labri.fr, {agathe.basse, benoit.caudron, marie.huillet}@etu.u-bordeaux.fr, pierre.philip@u-bordeaux.fr
PCB Hardware Trojan Run-Time Detection Through Machine Learning

The modern semiconductor electronic devices are becoming increasingly vulnerable to malicious implants called Hardware Trojans (HT). This problem is also greatly related to Printed Circuit Boards (PCB), which are widely used in almost all electronic devices. In this paper, two machine learning (ML) methods have been applied to detect HTs running on power from I/Os of legitimate chips on a PCB. A PCB prototype has been fabricated to obtain real-life data, which was used to train two ML algorithms: One-Class Support Vector Machine and Local Outlier Factor. For validation of the ML classifiers, one hundred categories of HT devices have been modelled and inserted into the Validation and Testing datasets. Simulation results show that using the proposed methodology an HT device can be detected with high prediction accuracy (F1-score above <inline-formula><tex-math notation="LaTeX">$99.7\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>99</mml:mn><mml:mo>.</mml:mo><mml:mn>7</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="piliposyan-ieq1-3230877.gif"/></alternatives></inline-formula> for a <inline-formula><tex-math notation="LaTeX">$50mW$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>50</mml:mn><mml:mi>m</mml:mi><mml:mi>W</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="piliposyan-ieq2-3230877.gif"/></alternatives></inline-formula> HT). Further, the ML model has been uploaded to the prototype PCB for hard-silicon validation of the methodology. To the best of our knowledge, this is the first work on real-time detection of PCB HTs, which are powered from the I/O pins of legitimate ICs. Experimental results show that the performance of the ML model on a real-life prototype is consistent with that of the simulations.
Direct Inhibition of SARS-CoV-2 Spike Protein by Peracetic Acid

Peracetic acid (PAA) disinfectants are effective against a wide range of pathogenic microorganisms, including bacteria, fungi, and viruses. Several studies have shown the efficacy of PAA against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); however, its efficacy in SARS-CoV-2 variants and the molecular mechanism of action of PAA against SARS-CoV-2 have not been investigated. SARS-CoV-2 infection depends on the recognition and binding of the cell receptor angiotensin-converting enzyme 2 (ACE2) via the receptor-binding domain (RBD) of the spike protein. Here, we demonstrated that PAA effectively suppressed pseudotyped virus infection in the Wuhan type and variants, including Delta and Omicron. Similarly, PAA reduced the authentic viral load of SARS-CoV-2. Computational analysis suggested that the hydroxyl radicals produced by PAA cleave the disulfide bridges in the RBD. Additionally, the PAA treatment decreased the abundance of the Wuhan- and variant-type spike proteins. Enzyme-linked immunosorbent assay showed direct inhibition of RBD-ACE2 interactions by PAA. In conclusion, the PAA treatment suppressed SARS-CoV-2 infection, which was dependent on the inhibition of the interaction between the spike RBD and ACE2 by inducing spike protein destabilization. Our findings provide evidence of a potent disinfection strategy against SARS-CoV-2.
Separable states and separability criteria

A quantum state which can be written as a convex sum of product states is a separable state; such a convex sum allows for a local description. There are many different local descriptions for a given separable state, and some new results about the minimal number of product states in the convex sum wil be given in this paper. Any quantum state is either entangled or separable. However it is very difficult to tell whether a given state is separable or entangled. This difficulty has not been solved yet although a lot of separability criteria have already be proposed. The various separability criteria will also be discussed.
A metabarcoding framework for wild bee assessment in Luxembourg

Wild bees are crucial organisms for terrestrial environments. Their ongoing decline could cause irreparable damage to ecosystem services vital to plant reproduction and human food production. The importance of taking swift action to prevent further declines is widely acknowledged, but the current deficit of reliable taxonomic information complicates the development of efficient conservation strategies targeting wild bees. DNA metabarcoding can help to improve this situation by providing rapid and standardized mass identification. This technique allows the analysis of large numbers of specimens without the need for specialized taxonomic knowledge by matching high-throughput sequencing reads against public DNA barcode reference libraries. However, the validation of this approach for wild bees requires the evaluation of potential error sources on a regional scale. Here we analyzed the effects of three potential error sources on a metabarcoding pipeline customized for the wild bee fauna of Luxembourg. In an in silico study, we checked the completeness of the BOLD reference library for 349 species found in the country, the correspondence between molecular and morphological species delimitation for these taxa, and the amplification efficiency of three commonly used metabarcoding primer pairs (mlCOlintF/HCO2198, LepF1/MLepF1-Rev and BF2/BR2). The detection power of the pipeline was evaluated based on the species recovery rates from mock communities of known composition under variable DNA concentration treatments. The reference barcode library evaluation results show that 97% of the species have at least a single barcode in BOLD Systems (minimal length 196 bp) and that 85% of species have ≥ 5 barcodes in the public domain. The mlCOlintF/HCO2198 target fragment presented the highest coverage (77.94% of the species with full barcode sequences), followed by the target fragments of LepF1/MLepF1-Rev (77.65%) and BF2/BR2 (68.48%). Only 60% of the morphospecies presented a complete coverage of the prominent Folmer region (658 bp). The in silico amplification efficiency analysis shows that the BF2/BR2 primer pair has the best-predicted amplification performance, but none of the primer combinations evaluated can be expected to efficiently amplify all local wild bee genera. Finally, all species detection rates in the mock communities, except for the sample with the most discrepant
Automatic Local Smoothing for Spectral Density Estimation

This article uses local polynomial techniques to fit Whittle's likelihood for spectral density estimation. Asymptotic sampling properties of the proposed estimators are derived, and adaptation of the proposed estimator to the boundary effect is demonstrated. We show that the Whittle likelihood‐based estimator has advantages over the least‐squares based log‐periodogram. The bandwidth for the Whittle likelihood‐based method is chosen by a simple adjustment of a bandwidth selector proposed in Fan & Gijbels (1995). The effectiveness of the proposed procedure is demonstrated by a few simulated and real numerical examples. Our simulation results support the asymptotic theory that the likelihood based spectral density and log‐spectral density estimators are the most appealing among their peers
Epigenetic Insights on PARP-1 Activity in Cancer Therapy

Simple Summary PARP-1 and poly(ADP-ribosyl)ation control gene expression, DNA repair pathways, and genomic stability in multiple ways, such as affecting chromatin remodelling. This review article summarises how PARP-1 activity directly modifies histone proteins and the enzymes involved in DNA/histone epigenetic modifications to mould chromatin structure during transcription and DNA damage response. Understanding the role of poly(ADP-ribosyl)ation in the epigenetic regulation of chromatin organisation will help clarify resistance mechanisms to PARP inhibitors and highlight the clinical relevance of a combinatory approach based on epigenetic drugs. Abstract The regulation of chromatin state and histone protein eviction have been proven essential during transcription and DNA repair. Poly(ADP-ribose) (PAR) polymerase 1 (PARP-1) and poly(ADP-ribosyl)ation (PARylation) are crucial mediators of these processes by affecting DNA/histone epigenetic events. DNA methylation/hydroxymethylation patterns and histone modifications are established by mutual coordination between all epigenetic modifiers. This review will focus on histones and DNA/histone epigenetic machinery that are direct targets of PARP-1 activity by covalent and non-covalent PARylation. The effects of these modifications on the activity/recruitment of epigenetic enzymes at DNA damage sites or gene regulatory regions will be outlined. Furthermore, based on the achievements made to the present, we will discuss the potential application of epigenetic-based therapy as a novel strategy for boosting the success of PARP inhibitors, improving cell sensitivity or overcoming drug resistance.
Transparency of Financial Reporting According to the S&P500 Indices and its Implications for Accounting Information Risks - Evidence from the Iraq Stock Exchange

The current research aims to test and analyze the relationship between the level of transparency of financial reporting and the risks of accounting information for a sample of private commercial banks in the Iraq Stock Exchange. The transparency of financial reporting was assessed using the S&P500 indices, and the level of accounting information risk was evaluated using the S&P500 indices, representing fragmented and reduced risks. Unanswered information within the S&P500 indices' requirements consists of 98 conditions. To achieve the research objectives and test its hypotheses, the applied approach was used to evaluate the research variables in a sample of commercial banks listed on the Iraq Stock Exchange, which amounted to (10) selected banks for the period (2016-2021). In comparison, the inferential statistical method was used to test and analyze the research hypotheses using Excel and SPSS26 programs. The research reached a set of conclusions, the most important of which was the low level of transparency in private commercial banks, especially in the two main categories of (S&P500) indicators: ownership structure and shareholder rights, and the board of directors and management procedures, as both had the largest share of risks, which indicates a high risk of accounting information. The research concluded with several recommendations, the most important of which was working to oblige banks to expand disclosure and work with the mechanisms of S & P500 indicators and apply them annually to follow up on the level of transparency development in them to reduce the risks of accounting information.
Model matching for SAR ATR based on probabilistic distance transforms

In this paper we present an analysis of distance transform methods of matching object models to SAR data. We show that by properly defining the distance function, the likelihood of each observed SAR feature data point given the model is given as a function of position. This allows calculation of a likelihood of observing a set of data features, given a model and its associated pose and other parameters. The issue of normalization resulting from the non-correspondence based distance transform method is discussed. When prior densities of the model features are available, maximum a- posteriori results are obtainable. This method allows the use of priors of models and individual features, along with the geometric probability densities associated with the feature prediction and measurement processes, to be incorporated within a fast correlation-type distance transform matching module. The method also potentially allows exploitation of persistent scatterers over a limited range of SAR model-to-target imaging parameters.
On (cid:2) -solutions for convex optimization problems with uncertainty data

We consider (cid:2) -solutions (approximate solutions) for a robust convex optimization problem in the face of data uncertainty. Using robust optimization approach (worst-case approach), we establish an optimality theorem and duality theorems for (cid:2) -solutions for the robust convex optimization problem. Moreover, we give an example illustrating the duality theorems.
Comparison of Stroke Care Costs in Urban and Nonurban Hospitals and Its Association With Outcomes in New Zealand: A Nationwide Economic Evaluation

Background: Although geographical differences in treatment and outcomes after stroke have been described, we lack evidence on differences in the costs of treatment between urban and nonurban regions. Additionally, it is unclear whether greater costs in one setting are justified given the outcomes achieved. We aimed to compare costs and quality-adjusted life years in people with stroke admitted to urban and nonurban hospitals in New Zealand. Methods: Observational study of patients with stroke admitted to the 28 New Zealand acute stroke hospitals (10 in urban areas) recruited between May and October 2018. Data were collected up to 12 months poststroke including treatments in hospital, inpatient rehabilitation, other health service utilization, aged residential care, productivity, and health-related quality of life. Costs in New Zealand dollars were estimated from a societal perspective and assigned to the initial hospital that patients presented to. Unit prices for 2018 were obtained from government and hospital sources. Multivariable regression analyses were conducted when assessing differences between groups. Results: Of 1510 patients (median age 78 years, 48% female), 607 presented to nonurban and 903 to urban hospitals. Mean hospital costs were greater in urban than nonurban hospitals ($13 191 versus $11 635, P=0.002), as were total costs to 12 months ($22 381 versus $17 217, P<0.001) and quality-adjusted life years to 12 months (0.54 versus 0.46, P<0.001). Differences in costs and quality-adjusted life years remained between groups after adjustment. Depending on the covariates included, costs per additional quality-adjusted life year in the urban hospitals compared to the nonurban hospitals ranged from $65 038 (unadjusted) to $136 125 (covariates: age, sex, prestroke disability, stroke type, severity, and ethnicity). Conclusions: Better outcomes following initial presentation to urban hospitals were associated with greater costs compared to nonurban hospitals. These findings may inform greater targeted expenditure in some nonurban hospitals to improve access to treatment and optimize outcomes.
Distributed fiber optic sensor development, testing, and evaluation for geotechnical monitoring applications

In this paper, an overview of optical sensor development, testing and evaluation for several geotechnical monitoring applications is presented. Additionally, sensor integration and data interpretation are addressed as key influences to the overall success of the monitoring project. They should be taken into consideration already in the design stage. Particular focus is given on strain sensor development to minimize the slippage of the fiber inside the protection. For the first time, slippage progression monitoring by high spatially resolved Brillouin measurements is presented as a new tool for sensor testing and evaluation for geotechnical projects. The main findings of the study are that in a geotechnical monitoring project, special care has to be taken by choosing the sensor slippage properties, longitudinal stiffness and robustness, as well as in the design of the sensor system itself (fixation, gauge length and bond strength). With appropriate alignment of these factors, reasonable monitoring data can be obtained, as shown in the applications proposed in this manuscript.
Effects of Space Weather on Technology Infrastructure

An interdisciplinary NATO Advanced Research Workshop on Effects of Space Weather on Technology Infrastructure (ESPRIT) was held in Rhodes, Greece, on 25‐29 March 2003, bringing together internationally renowned experts from the physics, engineering, and application/user communities to review and assess the current knowledge on space weather dynamics and its technological and societal consequences.
Detection of mixed modulation

According to Goldstein's 1967 theory [J. Acoust. Soc. Am. 41, 458–479 (1967)] modulation is detected by the detection of energy fluctuations in a critical band filter centered on the lower modulation sideband. This theory predicts the relative detectabilities of AM and FM. We have generalized the theory to the detection of mixed modulation, MM, viz., combined AM and FM. The parameter space of MM is rich; AM and FM may be combined in any proportion and with any relative phase; the ratio of upper to lower sideband levels may take on any value. Therefore, MM experiments provide a stringent test of the general detection theory. In particular, as the upper sideband level is increased relative to the lower it becomes advantageous to the listener to change to a critical band filter centered on the upper sideband. The conditions for this transition can be predicted from pure tone masking data. We performed parallel AM, FM, MM, and masking experiments. Although most data support the theory, thresholds at the trans.
Asymptotic results for nonlinear outdiffusion

Asymptotic methods are applied to the outdiffusion of a diffusant whose behaviour is governed by a power-law diffusivity. Both semi-infinite and finite domain problems are considered. The ‘fast’ diffusion (negative power-law) case is of particular interest, and the results are significantly different from those for the corresponding indiffusion problem.
Manipulation of second harmonic generation from metasurfaces

We manipulate the second harmonic generation (SHG) near-field and far-field radiation properties from metasurfaces composed of split ring resonators (SRRs). The manipulation is done by inverting the symmetry of the SRRs in periodic manner. We show by numerical models and experimentally that by that the nonlinear emission can be directed and that the emission direction can be controlled by changing the properties of the arrays or by changing the wavelength of the exciting beam at the first harmonic. This can be used as a new form of all-optical nonlinear scanner based on extremely thin metasurface. These methods open the door for development of new integrated nonlinear active devices based on metasurfaces and can be used to enhance the efficiency of the nonlinear output, therefore it provides a major step forward towards the development of efficient nonlinear metamaterials.
Robust invariance for a class of time-delay systems with repeated eigenvalues

Abstract This paper focuses on the set invariance of linear systems characterized by transition matrices with repeated eigenvalues and geometric multiplicity inferior to the algebraic multiplicity. The goal is to model the variable delay affecting the input by polytopic type of uncertainty in order to preserve the linear convex description. It is shown that the embedding problem can be translated into a polytopic containment problem and a iterative approach to the construction of tight, low complexity embedding (simplex) is proposed. A design procedure for the construction of a robust positively invariant set for the system affected by time delay and subject to input and state constraints completes the paper.
Genome-wide association and mendelian randomisation study of metabolites and pregnancy dysglycemia in a UK multi-ethnic birth cohort

Gestational diabetes mellitus (GDM) is the most common pregnancy complication worldwide and is associated with short- and long-term health implications for both mother and child. Prevalence of GDM varies between ethnicities, with South Asians (SAs) experiencing up to three times the risk compared to white Europeans (WEs). This study aimed to evaluate the causal role of metabolic characteristics in the ethnic-associated differences in gestational dysglycemia. A one-sample Mendelian Randomisation (MR) was performed separately on 3688 SA and 3354 WE women (<28th week of pregnancy) from the Born in Bradford (BiB) cohort for 146 metabolites exposures for the outcomes of fasting glucose and 2-hr post glucose (P [≤] 1 x 10-5 was considered significant). Additional GWAS and MR analyses on 22 composite measures of metabolite classes were also conducted. Through an extensive GWAS analysis this study identified 15 novel genome-wide significant (GWS) SNPs associated with tyrosine in the FOXN and SLC13A2 genes and 1 novel GWS SNP (currently in no known gene) associated with acetate in SAs. Through the utilisation of a MR analysis. 14 metabolites were found to be associated with postprandial glucose in WEs, while in SAs a distinct panel of 11 metabolites were identified. In WEs cholesterols were most common metabolite class identified, whereas in SAs saturated fatty acids were most common. Furthermore, in SAs a composite measure of the fatty acid class was also found to associate with 2-hour post glucose. The presence of ethnic-specific causal relationships between a comprehensive set of metabolites and postprandial glucose measures (fasting glucose and 2-hour post glucose) in mid-pregnancy has been established in a UK SA and WE population. Future work should aim to investigate the biological mechanisms of metabolites on GDM risk in order to inform ethnically tailored GDM prevention strategies.
Deep Learning of Electrocardiograms Enables Scalable Human Disease Profiling

The electrocardiogram (ECG) is an inexpensive and widely available diagnostic tool, and therefore has great potential to facilitate disease detection in large-scale populations. Both cardiac and noncardiac diseases may alter the appearance of the ECG, though the extent to which diseases across the human phenotypic landscape can be detected on the ECG remains unclear. We developed a deep learning variational autoencoder model that encodes and reconstructs ECG waveform data within a multidimensional latent space. We then systematically evaluated whether associations between ECG encodings and a broad range of disease phenotypes could be detected using the latent space model by deriving disease vectors and projecting individual ECG encodings onto the vectors. We developed models for both 12- and single-lead ECGs, akin to those used in wearable ECG technology. We leveraged phecodes to generate disease labels using International Classification of Disease (ICD) codes for about 1,600 phenotypes in three different datasets linked to electronic health record data. We tested associations between ECG encodings and disease phenotypes using a phenome-wide association study approach in each dataset, and meta-analyzed the results. We observed that the latent space ECG model identified associations for 645 (40%) diseases tested in the 12-lead model. Associations were enriched for diseases of the circulatory (n=140, 82% of category-specific diseases), respiratory (n=53, 62%), and endocrine/metabolic (n=73, 45%) systems, with additional associations evident across the human phenome; results were similar for the single-lead models. The top ECG latent space association was with hypertension in the 12-lead ECG model, and cardiomyopathy in the single-lead ECG model (p<2.2x10-308 for each). The ECG latent space model demonstrated a greater number of associations than ECG models using standard ECG intervals alone, and generally resulted in improvements in discrimination of diseases compared to models comprising only age, sex, and race. We further demonstrate how a latent space model can be used to generate disease-specific ECG waveforms and facilitate disease profiling for individual patients.