Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation robuste de la matrice de covariance en traitement du signal

De nombreuses applications de traitement de signal necessitent la connaissance de la matrice de covariance des donnees recues. Lorsqu'elle n'est pas directement accessible, elle est estimee prealablement a l'aide de donnees d'apprentissage. Traditionnellement, le milieu est considere comme gaussien. L'estimateur du maximum de vraisemblance est alors la sample covariance matrix (SCM). Cependant, dans de nombreuses applications, notamment avec l'arrivee des techniques haute resolution, cette hypothese n'est plus valable. De plus, meme en milieu gaussien, il s'avere que la SCM peut-etre tres influencee par des perturbations (donnees aberrantes, donnees manquantes, brouilleurs.) sur les donnees. Dans cette these nous nous proposons de considerer un modele plus general, celui des distributions elliptiques. Elles permettent de representer de nombreuses distributions et des campagnes de mesures ont montre leur bonne adequation avec les donnees reelles, dans de nombreuses applications telles que le radar ou l'imagerie hyperspectrale. Dans ce contexte, nous proposons des estimateurs plus robustes et plus adaptes : les M-estimateurs et l'estimateur du point-fixe (FPE). Leurs performances et leur robustesse sont etudiees et comparees a celles de la SCM. Nous montrons ainsi que dans de nombreuses applications, ces estimateurs peuvent remplacer tres simplement la SCM, avec de meilleures performances lorsque les donnees sont non-gaussiennes et des performances comparables a la SCM lorsque les donnees sont gaussiennes. Les resultats theoriques developpes dans cette these sont ensuite illustres a partir de simulations puis a partir de donnees reels dans le cadre de traitements spatio-temporels adaptatifs.
Motor Current Model for Detecting Localized Defects in Planet Rolling Bearings

A motor current model for the diagnosis of localized defects in planet rolling bearings (PRBs) is proposed in this study. A dynamic analysis of the motor-driven planetary gearbox system is conducted, and a translational-torsional vibration model of the system is developed. Both the additional time-varying impact caused by localized defects and the influence of the Hertzian contact and radial clearance on the translational support forces of PRBs are considered in the model. Based on the magnetic equivalent circuit network model, vibrational-electromagnetic coupling analysis is performed with the aid of the air-gap permeance and electromagnetic torque. By iteratively solving the nonlinear algebraic differential equations describing the dynamic characteristics of the coupling system, the motor current variation curve with localized defects in the PRB is obtained. Taking a typical motor-driven planetary gearbox system as the object, electromagnetic finite element calculations and dynamic response tests are performed to verify the proposed motor current model. The results show that the characteristic motor current frequencies are a combination of the fault passing frequency and power supply frequency when the inner race of the PRB has a localized spall fault. When the outer race (or roller) has a localized spall fault, the combination of current characteristic frequencies, which generally consists of the fault passing frequency, power supply frequency, and PRB outer-race rotational frequency (outer-race spall) or cage revolution frequency (roller spall), become complex. By discussing the effect of the spall width on the motor current spectra in detail, the characteristic frequencies sensitive to defects are extracted, providing a theoretical basis for the quantitative diagnosis of PRB-localized defects.
Laboratory Experiments with Supersonic Radiatively Cooled Jets: Jet Deflection via Crosswinds and Magnetic Tower Outflows

We present results of high energy density laboratory experiments on the production of supersonic radiatively cooled plasma jets with dimensionless parameters (Mach number ∼30, cooling parameter ∼1 and density contrast ρj/ρa ∼10) similar to those in YSO jets. The jets are produced using two modifications of wire array Z‐pinch driven by 1MA, 250ns current pulse of MAGPIE facility at Imperial College London. In the first set of experiments the produced jets are purely hydrodynamic and are used to study deflection of the jets by the plasma cross‐wind, including the structure of internal oblique shocks in the jets. In the second configuration the jets are driven by the pressure of the toroidal magnetic field and this configuration is relevant to the astrophysical models of jet launching mechanisms. Modifications of the experimental configuration allowing addition of the poloidal magnetic field and angular momentum to the jets are also discussed. We also present three‐dimensional resistive magneto‐hydrodynamic (MHD) simulations of the experiments and discuss the scaling of the experiments to the astrophysical systems.
Genetic algorithm‐based higher‐order model reduction of proton exchange membrane fuel cell

This study investigates the performance and simulation analysis of a larger‐scale proton exchange membrane fuel cell model using a lower‐order model. With model order reduction studies, the present work aims to demonstrate the effectiveness of the proposed Genetic algorithm technique in terms of various reduced order transfer functions. The proposed methodology can assist the higher‐order model in meeting its requirements, including stability, computation complexity, and the issue of local optima entrapment. This study demonstrates the efficacy of the proposed method by comparing it to other reduction techniques, such as the factor division method, the stability method, and the truncation method, utilizing a variety of performance metrics, including error indices, non‐parametric tests, through in frequency, and time‐domain analyses. The proposed method for model reduction offers advantages in terms of perturbation, stability, and parameter uncertainty.
Study of Cherenkov Light Lateral Distribution Function around the Knee Region in Extensive Air Showers

The Cherenkov light lateral distribution function (LDF) was simulated with the CORSIKA code, in the energy range (10^13-10^16) eV. This simulation was performed for conditions and configurations of the Tunka EAS Cherenkov array for two primary particles (p and Fe). Basing on the simulated results, many approximated functions are structured for two primary particles and different zenith angles. This allowed us to reconstruct the EAS events, which is, to determine the type and energy of the primary particles that produced showers from signal amplitudes of Cherenkov radiation which measured with Tunka Cherenkov array experiment. Comparison of the calculated LDF of Cherenkov radiation with that measured at the Tunka EAS array shows the ability for identifying of the primary particle that initiated the EAS cascades determining of its primary energy around the knee region of the cosmic ray spectrum.
Local glucose elevation activates pyroptosis via NLRP3 inflammasome in ovarian granulosa cells of overweight patients

Overweight, with an increasing prevalence worldwide, significantly impairs the clinical outcomes following in vitro fertilization (IVF). Hyperglycemia, hyperlipidemia, and metabolic disorders are always accompanied by the majority of overweight patients. The association between granulosa cell function and metabolic alterations in follicular fluid including lipids, proteins, and growth factors has been extensively documented. However, the effects of higher glucose level on ovarian granulosa cells (GCs), remain largely unknown. In this study, we identified that overweight women had elevated follicular glucose level which profoundly activated NLRP3 inflammasome and pyroptosis. An in vitro correlation between follicular high glucose, NLRP3 inflammasome and pyroptosis was also established. More importantly, in granulosa cells of overweight patients, the activation of the NLRP3 inflammasome and pyroptosis induced by high glucose was involved in the dysregulation of estradiol synthesis. Our study may provide new options to interpretate and improve IVF outcomes in overweight women.
Designation of optimal reference strains representing the infant gut bifidobacterial species through a comprehensive multi‐omics approach

Abstract The genomic era has resulted in the generation of a massive amount of genetic data concerning the genomic diversity of bacterial taxa. As a result, the microbiological community is increasingly looking for ways to define reference bacterial strains to perform experiments that are representative of the entire bacterial species. Despite this, there is currently no established approach allowing a reliable identification of reference strains based on a comprehensive genomic, ecological, and functional context. In the current study, we developed a comprehensive multi‐omics approach that will allow the identification of the optimal reference strains using the Bifidobacterium genus as test case. Strain tracking analysis based on 1664 shotgun metagenomics datasets of healthy infant faecal samples were employed to identify bifidobacterial strains suitable for in silico and in vitro analyses. Subsequently, an ad hoc bioinformatic tool was developed to screen local strain collections for the most suitable species‐representative strain alternative. The here presented approach was validated using in vitro trials followed by metagenomics and metatranscriptomics analyses. Altogether, these results demonstrated the validity of the proposed model for reference strain selection, thus allowing improved in silico and in vitro investigations both in terms of cross‐laboratory reproducibility and relevance of research findings.
Matroids and complexity

We consider different ways of describing a matroid to a Turing machine by listing the members of various families of subsets, and we construct an order on these different methods of description. We show that, under this scheme, several natural matroid problems are complete in classes thought not to be equal to P. We list various results linking parameters of basis graphs to parameters of their associated matroids. For small values of k we determine which matroids have the clique number, chromatic number, or maximum degree of their basis graphs bounded above by k. If P is a class of graphs that is closed under isomorphism and induced subgraphs, then the set of matroids whose basis graphs belong to P is closed under minors. We characterise the minor-closed classes that arise in this way, and exhibit several examples. One way of choosing a basis of a matroid at random is to select a total ordering of the ground set uniformly at random and use the greedy algorithm. We consider the class of matroids having the property that this procedure chooses a basis uniformly at random. Finally we consider a problem mentioned by Oxley. He asked if, for every two elements and n - 2 cocircuits in an n-connected matroid, there is a circuit that contains both elements and that meets every cocircuit. We show that a slightly stronger property holds for regular matroids.
Direct Position Determination of Noncircular Sources with Multiple Nested Arrays via Weighted Subspace Data Fusion

Direct position determination (DPD) of noncircular (NC) sources for multiple nested arrays (NA) is researched in this study. For noncircular sources, the dimension reduction method is used to decrease the computing complexity and remove the noncircular phase. Furthermore, nested array and noncircular sources extend spatial degree of freedom. Due to inferior stability and noise susceptibility of original algorithm, we propose SNR weighted subspace data fusion (W-SDF) algorithm. Each observation station places a nested array, spatial smoothing technology, and sum and difference co-array are used to deal with the nested array. Simulation results show that under nested array and noncircular sources, the proposed W-SDF algorithm has decreased the complexity of the algorithm and improved the location accuracy, degree of freedom, and resolution.
MicroRNA-34a, Prostate Cancer Stem Cells, and Therapeutic Development

Simple Summary Prostate cancer is still the most common cancer among men in the US. Current standard-of-care therapies for metastatic castration-resistant prostate cancer can offer survival benefits measured only in months. The patients eventually develop drug resistance and tumor relapse. There is strong evidence that during treatment, prostate cancer stem cells may become the predominant population within tumor bulk, and function as the “root cause” for drug resistance. microRNA-34a, a bona fide tumor-suppressive miRNA, represents a potent cancer stem cell suppressor by targeting many molecules essential for cancer stem cell survival. This article will review the tumor suppressive role of miRNA-34a in prostate cancer, and its therapeutic development strategies for advanced prostate cancer patients. Abstract Prostate cancer (PCa) is a highly heterogeneous disease and typically presents with multiple distinct cancer foci. Heterogeneity in androgen receptor (AR) expression levels in PCa has been observed for decades, from untreated tumors to castration-resistant prostate cancer (CRPC) to disseminated metastases. Current standard-of-care therapies for metastatic CRPC can only extend life by a few months. Cancer stem cells (CSCs) are defined as a subpopulation of cancer cells that exists in almost all treatment-naive tumors. Additionally, non-CSCs may undergo cellular plasticity to be reprogrammed to prostate cancer stem cells (PCSCs) during spontaneous tumor progression or upon therapeutic treatments. Consequently, PCSCs may become the predominant population in treatment-resistant tumors, and the “root cause” for drug resistance. microRNA-34a (miR-34a) is a bona fide tumor-suppressive miRNA, and its expression is dysregulated in PCa. Importantly, miR-34a functions as a potent CSC suppressor by targeting many molecules essential for CSC survival and functions, which makes it a promising anti-PCSC therapeutic. Here, we conducted a comprehensive literature survey of miR-34a in the context of PCa and especially PCSCs. We provided an updated overview on the mechanisms of miR-34a regulation followed by discussing its tumor suppressive functions in PCa. Finally, based on current advances in miR-34a preclinical studies in PCa, we offered potential delivery strategies for miR-34a-based therapeutics for treating advanced PCa.
An Acceleration-Based Nonlinear Time-Series Analysis of Effects of Robotic Walkers on Gait Dynamics During Assisted Walking

This article aimed to identify the effects of a robotic walker on gait dynamics during assisted walking via the analysis of acceleration data. Walking experiments were conducted with 11 healthy young subjects under different conditions, including normal, rollator-assisted, and robotic-walker-assisted walking. We collected acceleration data from the trunk and pelvis to extract measures for evaluating the properties of gait dynamics, including periodicity, complexity, and determinism. These measures include maximum Lyapunov exponent (MLE), multiscale entropy (MSE), multiscale permutation entropy (MPE), correlation dimension (CD), and percentage of determinism (%DET, from recurrence plot). Significant differences in the complex measures, MSE and MPE between normal and walker-assisted walking for trunk acceleration data in anteroposterior (AP) and mediolateral (ML) directions were observed. The determinism measures, CD and %DET, demonstrated significant differences between normal and robotic-walker-assisted walking for trunk acceleration data in the AP direction, while significant differences in the periodicity measures and MLE were not observed between the three conditions. These results imply mostly unchanged local dynamic stability, reduced deterministic patterns, and increased complexity in the gait dynamics of healthy young subjects, especially for the upper body. The robotic walker’s assistance is considered appropriate because of no significant difference between rollator-assisted and robotic-walker-assisted walking. This study provides new insights into the biomechanical effects of the robotic walker on gait. It also suggests that the used methods can be applied to the assistance evaluation of walking assistive devices like lower-limb exoskeletons and assess the ability to resist perturbations with a robotic walker for rehabilitation applications such as perturbation-based gait training.
Improvement in mechanical and physical properties of starch-based films provided by cellulose nanocrystals extracted from rice straw

Films based on starch (ST) have been widely used for food packaging; however, it is necessary to improve their mechanical properties. In this context, eco-friendly starch films incorporated with cellulose nanocrystal (CNC) were prepared using the casting method. CNCs were isolated using acid hydrolysis from rice straw (RS) as raw material and characterized by FESEM, TEM, FIIR, XRD, TGA and zeta potential analyzer. The isolated CNC presented a rod-like structure, high crystallinity (75%) with a diameter of around 12 nm. Subsequently, the starch-based films reinforced with various concentrations of CNC (2, 5, 10, and 15 wt%) were characterized for their morphological features, mechanical, barrier, and thermal properties and compared with control film. It was shown that the addition of CNCs to the film improved the mechanical properties and decreased the water vapor permeability, as important characteristics in food packaging materials.
Relation between near field and far field acoustic measurements

Several approaches to the problem of determining the far field directivity of an acoustic source located in a reverberant environment, such as a wind tunnel, are investigated analytically and experimentally. The decrease of sound pressure level with distance is illustrated; and the spatial extent of the hydrodynamic and geometric near fields, the far field, and the reverberant field are described. A previously-prosposed analytical technique for predicting the far field directivity of the acoustic source on the basis of near field data is investigated. Experiments are conducted with small acoustic sources and an analysis is performed to determine the variation with distance from the source of the directionality of the sound field. A novel experiment is conducted in which the sound pressure measured at various distances from an acoustic driver located in the NASA Ames 40 x 80 ft wind tunnel is crosscorrelated with the driver excitation voltage.
Marine Alga Ulva fasciata-Derived Molecules for the Potential Treatment of SARS-CoV-2: An In Silico Approach

SARS-CoV-2 is the causative agent of the COVID-19 pandemic. This in silico study aimed to elucidate therapeutic efficacies against SARS-CoV-2 of phyco-compounds from the seaweed, Ulva fasciata. Twelve phyco-compounds were isolated and toxicity was analyzed by VEGA QSAR. Five compounds were found to be nonmutagenic, noncarcinogenic and nontoxic. Moreover, antiviral activity was evaluated by PASS. Binding affinities of five of these therapeutic compounds were predicted to possess probable biological activity. Fifteen SARS-CoV-2 target proteins were analyzed by the AutoDock Vina program for molecular docking binding energy analysis and the 6Y84 protein was determined to possess optimal binding affinities. The Desmond program from Schrödinger’s suite was used to study high performance molecular dynamic simulation properties for 3,7,11,15-Tetramethyl-2-hexadecen-1-ol—6Y84 for better drug evaluation. The ligand with 6Y84 had stronger binding affinities (−5.9 kcal/mol) over two standard drugs, Chloroquine (−5.6 kcal/mol) and Interferon α-2b (−3.8 kcal/mol). Swiss ADME calculated physicochemical/lipophilicity/water solubility/pharmacokinetic properties for 3,7,11,15-Tetramethyl-2-hexadecen-1-ol, showing that this therapeutic agent may be effective against SARS-CoV-2.
In vivo modelling of cutaneous T-cell lymphoma: The role of SOCS1

Introduction Mycosis fungoides (MF), the most common type of Cutaneous T cell Lymphoma (CTCL), is characterized by an inflamed skin intermixed with proliferating malignant mature skin-homing CD4+ T cells. Detailed genomic analyses of MF skin biopsies revealed several candidate genes possibly involved in genesis of these tumors and/or potential targets for therapy. These studies showed, in addition to common loss of cell cycle regulator CDKN2A, activation of several oncogenic pathways, most prominently and consistently involving JAK/STAT signaling. SOCS1, an endogenous inhibitor of the JAK/STAT signaling pathway, was identified as a recurrently deleted gene in MF, already occurring in the earliest stages of the disease. Methods To explore the mechanisms of MF, we create in vivo mouse models of autochthonous CTCLs and these genetically engineered mouse models (GEMMS) can also serve as valid experimental models for targeted therapy. We describe the impact of allelic deletion of Socs1 in CD4 T cells of the skin. To achieve this, we crossed inducible Cre-transgenic mice in the CD4 lineage with transgenic mice carrying floxed genes of Socs1. We first determined optimal conditions for Socs1 ablation with limited effects on circulating CD4 T-cells in blood. Next, we started time-course experiments mimicking sustained inflammation, typical in CTCL. FACS analysis of the blood was done every week. Skin biopsies were analyzed by immunocytochemical staining at the end of the experiment. Results We found that the Socs1 knockout transgenic group had thicker epidermis of treated skin compared with the control group and had more CD3 and CD4 in the skin of the transgenic group compared to the control group. We also noted more activation of Stat3 by staining for P-Stat3 in Socs1 knockout compared to wt CD4+T cells in the skin. The results also indicated that single copy loss of Socs1 in combination with sustained inflammation is insufficient to start a phenotype resembling early stage mycosis fungoides within eight weeks in these mice. Conclusion In sum, we developed and optimized an autochthonous murine model permitting selective knockout of Socs1 in skin infiltrating CD4 T-cells. This paves the way for more elaborate experiments to gain insight in the oncogenesis of CTCL.
Social Network Evolution of Multiagent Groups in Task Allocation

The social network and group structure can improve the effectiveness of tasks and the management of multiagent systems (MASs). However, in complex task environments, the fixed network and social relation are not necessarily the optimal design. Therefore, agents should be able to adjust social relations in a distributed and self-organized manner to adapt to different task demands. To solve this problem, a hybrid social evolution mechanism based on Q-learning is proposed in this article. The evolution of social relations is realized from the perspective of individual, group, and global situations to improve the success rate and comprehensive effectiveness of task allocation in the system while reducing the communication cost during task execution. In addition, the hybrid evolution mechanism considers the balance of interests between the global and the individual, which can guarantee the rationality of task benefit distribution while improving the global effectiveness. The experiments show that compared with the single-form evolution method, the hybrid mechanism proposed in this article has more advantages in the success rate, communication cost, and comprehensive effectiveness of task allocation. Moreover, the rationality of benefit distribution is also improved, and a strong and harmonious social system is realized.