Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-World Data on Newly Diagnosed BRCA-Mutated High-Grade Epithelial Ovarian Cancers: The French National Multicenter ESME Database

Simple Summary BRCA-mutated high-grade epithelial ovarian cancers represent a specific subset of gynecological malignancies. Real-world comprehensive data have been elusive to date. As such, we conducted a comprehensive description of clinicopathological and therapeutical characteristics via the Epidemiological Strategy and Medical Economics (ESME) data warehouse, which collects data from 18 French comprehensive cancer centers from the Unicancer network. This led to useful findings regarding the natural disease history of these patients in clinical practice, prior to the advent of poly-ADP ribose polymerase inhibitors. Abstract Background: In spite of the frequency and clinical impact of BRCA1/2 alterations in high-grade epithelial ovarian cancer (HGEOC), real-world information based on robust data warehouse has been scarce to date. Methods: Consecutive patients with BRCA-mutated HGEOC treated between 2011 and 2016 within French comprehensive cancer centers from the Unicancer network were extracted from the ESME database. The main objective of the study was the assessment of clinicopathological and treatments parameters. Results: Out of the 8021 patients included in the ESME database, 266 patients matching the selection criteria were included. BRCA1 mutation was found in 191 (71.8%) patients, while 75 (28.2%) had a BRCA2 mutation only; 95.5% of patients received a cytoreductive surgery. All patients received a taxane/platinum-based chemotherapy (median = six cycles). Complete and partial response were obtained in 53.3% and 20.4% of the cases, respectively. Maintenance therapy was administered in 55.3% of the cases, bevacizumab being the most common agent. After a median follow up of 51.7 months, a median progression-free survival of 28.6 months (95% confidence interval (CI) [26.5; 32.7]) and an estimated 5-year median overall survival of 69.2% (95% CI [61.6; 70.3]) were reported. Notably, BRCA1- and BRCA2-mutated cases exhibited a trend towards different median progression-free survivals, with 28.0 (95% CI [24.4; 32.3]) and 33.3 months (95% CI [26.7; 46.1]), respectively (p-value = 0.053). Furthermore, five-year OS for BRCA1-mutated patients was 64.5% (95% CI [59.7; 69.2]), while it was 82.5% (95% CI [76.6; 88.5]) for BRCA2-mutated ones (p-value = 0.029). Conclusions: This study reports the largest French multicenter cohort of BRCA-mutated HGEOCs based on robust data from the ESME, exhibiting relevant real-world data regarding this specific population.
On the Circular Law

We consider the joint distribution of real and imaginary parts of eigenvalues of random matrices with independent real entries with mean zero and unit variance. We prove the convergence of this distribution to the uniform distribution on the unit disc without assumptions on the existence of a density for the distribution of entries. We assume however that the entries have sub-Gaussian tails or are sparsely non-zero.
Lipidomics-Assisted GWAS (lGWAS) Approach for Improving High-Temperature Stress Tolerance of Crops

High-temperature stress (HT) over crop productivity is an important environmental factor demanding more attention as recent global warming trends are alarming and pose a potential threat to crop production. According to the Sixth IPCC report, future years will have longer warm seasons and frequent heat waves. Thus, the need arises to develop HT-tolerant genotypes that can be used to breed high-yielding crops. Several physiological, biochemical, and molecular alterations are orchestrated in providing HT tolerance to a genotype. One mechanism to counter HT is overcoming high-temperature-induced membrane superfluidity and structural disorganizations. Several HT lipidomic studies on different genotypes have indicated the potential involvement of membrane lipid remodelling in providing HT tolerance. Advances in high-throughput analytical techniques such as tandem mass spectrometry have paved the way for large-scale identification and quantification of the enormously diverse lipid molecules in a single run. Physiological trait-based breeding has been employed so far to identify and select HT tolerant genotypes but has several disadvantages, such as the genotype-phenotype gap affecting the efficiency of identifying the underlying genetic association. Tolerant genotypes maintain a high photosynthetic rate, stable membranes, and membrane-associated mechanisms. In this context, studying the HT-induced membrane lipid remodelling, resultant of several up-/down-regulations of genes and post-translational modifications, will aid in identifying potential lipid biomarkers for HT tolerance/susceptibility. The identified lipid biomarkers (LIPIDOTYPE) can thus be considered an intermediate phenotype, bridging the gap between genotype–phenotype (genotype–LIPIDOTYPE–phenotype). Recent works integrating metabolomics with quantitative genetic studies such as GWAS (mGWAS) have provided close associations between genotype, metabolites, and stress-tolerant phenotypes. This review has been sculpted to provide a potential workflow that combines MS-based lipidomics and the robust GWAS (lipidomics assisted GWAS-lGWAS) to identify membrane lipid remodelling related genes and associations which can be used to develop HS tolerant genotypes with enhanced membrane thermostability (MTS) and heat stable photosynthesis (HP).
Air Pollution Detection Using a Novel Snap-Shot Hyperspectral Imaging Technique

Air pollution has emerged as a global problem in recent years. Particularly, particulate matter (PM2.5) with a diameter of less than 2.5 μm can move through the air and transfer dangerous compounds to the lungs through human breathing, thereby creating major health issues. This research proposes a large-scale, low-cost solution for detecting air pollution by combining hyperspectral imaging (HSI) technology and deep learning techniques. By modeling the visible-light HSI technology of the aerial camera, the image acquired by the drone camera is endowed with hyperspectral information. Two methods are used for the classification of the images. That is, 3D Convolutional Neural Network Auto Encoder and principal components analysis (PCA) are paired with VGG-16 (Visual Geometry Group) to find the optical properties of air pollution. The images are classified into good, moderate, and severe based on the concentration of PM2.5 particles in the images. The results suggest that the PCA + VGG-16 has the highest average classification accuracy of 85.93%.
Chaotic synchronization of neuronet-type stochastic complex networks using decentralized differential minimax controllers

ABSTRACT Based on differential minimax control, this paper develops a novel theoretic design to achieve chaotic synchronization of neuronet-type stochastic complex networks that are heavily influenced by noise signals. According to robust inverse optimality, the proposed method is mathematically formulated by using stochastic Lyapunov technique and the associated Hamilton-Jacobi-Isaacs (HJI) equation, which ensures that the system accomplishes the best rational synchronization in probability, meanwhile, to reduce noises to a predefined level with stability margins. To verify analytical results, a numerical example is given to show the effectiveness of the proposed technique.
Coaching-Based Teleoccupational Guidance for Home-Based Stroke Survivors and Their Family Caregivers: Study Protocol for a Superior Randomized Controlled Trial

Background Home-based rehabilitation has been shown to be useful for stroke survivors to participate in daily life activities and return to their families. However, many home-based stroke survivors face challenges in the lack of professional guidance, rational training plans, and insufficient motivation, which will affect their rehabilitation outcomes to varying degrees. Though occupational therapy and coaching are widely recommended for stroke rehabilitation, studies that combine these two interventions via telerehabilitation in home-based rehabilitation are limited. Hence, this study will explore whether coaching-based teleoccupational guidance (CTG) will help stroke survivors and caregivers obtain satisfactory outcomes. Methods This single-blind (assessor), two-arm parallel superior randomised controlled trial will be conducted in the Hebei General Hospital, Shijiazhuang, China. Ninety-two participant dyads in home-based rehabilitation will be recruited and randomised to either CTG (intervention group) or a standard telerehabilitation group (control group). Participant dyads in the intervention group will follow a 6-step circle procedure and receive 12 teleoccupational coaching sessions over 3 months via WeChat. Data will be collected at baseline, after the intervention (3 months), and follow-up (6 months). The Reintegration to Normal Living Index will be the primary outcome to assess the participation of stroke survivors. Secondary outcomes will not only involve an observation of changes in activities of daily living, intrinsic motivation, motor function, and quality of life of stroke survivors but also will focus on the caregivers' perceived benefit and care burden. Discussion. This trial will assess the effects of CTG compared with standard telerehabilitation. We believe that the results of this study will add to the understanding of occupational therapy for stroke survivors in home-based rehabilitation and provide a reference for developing health policy and facilitating other chronic management. Trial Registration Number. The Chinese Clinical Trial Registry ChiCTR2200061107.
Sound-Based Cough Detection System using Convolutional Neural Network

Sound recording and processing techniques can be used in designing diagnostic solutions for a variety of medical conditions related to the respiratory system. In this spectrum, cough monitoring for chronic or seasonal conditions is a significant medical practice. In this paper, a precise cough identification and monitoring system is presented. The system is utilising a convolutional neural network as a feature extraction algorithm and classification system. Including several functions of loading the audio data into the system and converting it into a set of spectrograms, as well as the pre-segmentation stage function, the model retains its relatively low-complexity, which allows accelerating the learning process, also enhanced using dropout. Due to limited audio data available, the dataset dimension was established at 600 samples, split into two equal-numbered groups - 300 samples of “cough” samples, and 300 of “non-cough” samples. The validation accuracy (thus the percentage of samples labelled correctly by the system during the validation process) yielded over 84%, suggesting that this can be a successful cough detection method for future medical applications and devices, such as potential respiratory system condition diagnostic tool.
Age-related differences in the kinematics of aimed movements in immersive virtual reality: a preliminary study

Immersive virtual reality (VR) represents a viable technology to support rehabilitation and promote the recovery of upper limb functions after stroke. Nonetheless, it has not been determined yet if VR can elicit movements that share the same kinematic characteristics of those occurring in the real world (RW), thus positively impacting arm use in daily life. A previous study enrolling young adults showed promising results: joints' ranges of motion were preserved, although movement times were longer and peak velocity lower in VR. Starting from these results, this work aimed at comparing young and older adults' (i.e., an age-matched sample to stroke survivors) upper limb kinematics while performing aimed movements in RW and immersive VR. The presented study was a within-subject repeated-measures design in which participants had to reach, grasp and transport grocery items from a simplified supermarket shelf unit. The VR condition was performed using an HTC Vive head-mounted display; its controller was used to interact with virtual objects. Three conditions were tested: VR, RW, and RW while holding the controller (RWC, to account for carrying a weight). Ten healthy young adults $(26.7\pm 5.46$ and three older adults $(69.0\pm 2.0)$ were enrolled. The collected data showed that older adults moved slower, more curved, and reached lower peak velocity during both reaching and transfer in VR compared to young adults. Arm ranges of motion seemed to be preserved, whereas thorax movements were different. We hypothesized that these differences might be dependent on age-related vision and cognitive decline, lack of familiarity with VR technology, and lack of force feedback. Further studies are needed to address these issues and confirm or reject our hypotheses.
Microwave Absorption of α-Fe2O3@diatomite Composites

A neoteric round sieve diatomite (De) decorated with sea-urchin-like alpha-type iron trioxide (α-Fe2O3) synthetics was prepared by the hydrothermal method and further calcination. The results of the electromagnetic (EM) parameters of α-Fe2O3-decorated De (α-Fe2O3@D) showed that the minimum reflection loss (RLmin) of α-Fe2O3@D could reach −54.2 dB at 11.52 GHz and the matched absorber thickness was 3 mm. The frequency bandwidth corresponding to the microwave RL value below −20 dB was up to 8.24 GHz (9.76–18 GHz). This indicates that α-Fe2O3@D composite can be a lightweight and stable material; because of the low density of De (1.9–2.3 g/cm3), the density of α-Fe2O3@D composite material is lower than that of α-Fe2O3 (5.18 g/cm3). We found that the combination of the magnetic loss of sea-urchin-like α-Fe2O3 and the dielectric loss of De has the most dominant role in electromagnetic wave absorption and loss. We focused on comparing the absorbing properties before and after the formation of sea-urchin-like α-Fe2O3 and explain in detail the effects of the structure and crystal shape of this novel composite on the absorbing properties.
4-Phenylbutyric Acid (4-PBA) Derivatives Prevent SOD1 Amyloid Aggregation In Vitro with No Effect on Disease Progression in SOD1-ALS Mice

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the degeneration of motor neurons. Mutations in the superoxide dismutase (SOD1) gene, causing protein misfolding and aggregation, were suggested as the pathogenic mechanisms involved in familial ALS cases. In the present study, we investigated the potential therapeutic effect of C4 and C5, two derivatives of the chemical chaperone 4-phenylbutyric acid (4-PBA). By combining in vivo and in vitro techniques, we show that, although C4 and C5 successfully inhibited amyloid aggregation of recombinant mutant SOD1 in a dose-dependent manner, they failed to suppress the accumulation of misfolded SOD1. Moreover, C4 or C5 daily injections to SOD1G93A mice following onset had no effect on either the accumulation of misfolded SOD1 or the neuroinflammatory response in the spinal cord and, consequently, failed to extend the survival of SOD1G93A mice or to improve their motor symptoms. Finally, pharmacokinetic (PK) studies demonstrated that high concentrations of C4 and C5 reached the brain and spinal cord but only for a short period of time. Thus, our findings suggest that use of such chemical chaperones for ALS drug development may need to be optimized for more effective results.
Research on the recovery system of the fixed wing swarm based on the robotic vision in the marine environment

The use of the robotic arm to achieve the recovery of the unmanned aerial vehicles(UAV) has a broad applications in the marine environment; however, due to the complexity of the marine environment(such as the cloud and snow weather, and the high light intensity), in the process of the recovery of the UAVs, the relative position relationship between the robotic arm and the UAV can not be accurately reflected based on the existing methods of the machine vision. In this work, the visual recognition algorithm based on the aruco code of the binocular camera is proposed to solve the above problem. Firstly the median filtering process is added to eliminate the salt and pepper noise in the process of the visual recognition of the two-dimensional code. Then, a new binary conversion method is carried out to obtain the accurate relative position between the robotic arm and the UAV. Finally, based on the information of the relative position, the robotic arm carries out the path planning and the control to realize recovery. The experiments indicate that in cloud and snow weather, the recovery system based on the robot vision can recovery the UAV effectively.
SEE Testing on commercial power MOSFETs

This work compiles the outcome of several irradiation test campaigns, carried out with the aim of studying the susceptibility to hard Single Event Effects (SEE) of various commercial power MOSFET references. Proton, neutron and heavy ion irradiation were performed on the same set of MOSFET references, allowing for a comparison of their respective Single Event Burnout (SEB) and Single Event Gate Rupture (SEGR) sensitiveness under different energy and particle irradiation conditions.
Identification of Effective Indicators of Parasympathetic Activity using Deep Breathing Technique on Corporate Employees

Stress is the body's reflex to an undesirable stimulus which can be both internal or external, where the dominance of sympathetic nervous system is seen. As it creates disturbances in the body's homeostasis, prolonged stress without any intervention could be harmful in the long run. Deep breathing exercise is a proven intervention method to increase parasympathetic activity, thereby reducing stress. Heart Rate Variability (HRV) is universally considered as a standard for qualitative and quantitative analysis of stress. There are many indicators of HRV, obtained using linear analysis (consisting of time domain and frequency domain analyses) and non linear analysis. This study analyses the effect of deep breathing exercise as an effective intervention technique against stress on 50 healthy corporate employees during their work hours. Various indicators of HRV were analysed before and during the period of intervention, i.e., deep breathing exercise. It was found that the average heart rate reduced across the subjects during the intervention. RMSSD and SDNN were found to be the most sensitive, reliable, and hence effective HRV indicators for short term parasympathetic activity. Moreover, the results were confirmed with Repose lifestyle assessment platform which is an effective tool to plot the stress profile of an individual.
Scattering Regimes for Underwater Optical Wireless Communications using Monte Carlo Simulation

Optical wireless communications has shown tremendous potential for underwater applications as it can provide higher bandwidth and better security compared to acoustic technologies. In this paper, an investigation on scattering regimes for underwater links using Monte Carlo simulation has been presented.While the focus of this paper is on diffuse links, the simulation results of collimated links is also provided for comparison purpose. Three types of water namely clear, coastal and turbid water are being used in the simulation. It is shown that the effect of scattering on the path loss cannot be accurately modeled by the existing channel model; ie. Beers-Lambert (BL) law. It has been shown that the distance at which the unscattered light drops to zero can be used to estimate the transition point for the scattering regimes in case of diffuse links. The transition point for diffuse links in coastal water and turbid water can be estimated to be around 22 m and 4 m respectively. Further analysis on the scattering order probability at different scattering regimes illustrates how scattering is affected by beam size, water turbidity and distance. From the frequency response plot, it is estimated that the bandwidth of several order of GHz can be achieved when the links are operating in the minimal scattering region and will reduce to several hundreds of MHz when the link is operating in multiple scattering region.
Parameter Matching and Performance Analysis of a Master-Slave Electro-Hydraulic Hybrid Electric Vehicle

To improve the battery state of charge (SOC) of the electric vehicle (EV), this paper proposes a master–slave electro-hydraulic hybrid electric vehicle (MSEH-HEV). The MSEH-HEV uses a planetary row as the core transmission component to realize the interconversion between mechanical energy, hydraulic energy and electrical energy. Meanwhile, this paper introduces the six working modes in vehicle operation, matches the parameters of key components to the requirements of the vehicle’s performance and designs a rule-based control strategy to dominate the energy distribution and the operating mode switching. The research uses AMESim and Simulink to perform a co-simulation of the MSEH-HEV, and the superiority of MSEH-HEV is testified by comparing it with an AMESim licensed EV. The simulation results show that in the Economic Commission for Europe (ECE) and the Extra Urban Driving Cycle (EUDC), the MSEH-HEV has a 15% reduction in battery consumption, and the motor peak torque is greatly reduced. Moreover, a fuzzy control strategy is designed to optimize the rule-based control strategy. Ultimately, the optimized strategy further reduces the motor torque while maintaining the battery SOC. In this paper, the applicable research consists of the necessary references for the design matching of future electro-hydraulic hybrid electricity systems.
An Output-Boosted 3-ratio Switched-Capacitor DC-DC Converter with 0.5-to-1.8 V Output Voltage Range for Low-Power IoT Applications

This paper presents a fully-integrated reconfigurable switched-capacitor (SC) converter that extracts power from a 1. 5-1.SV input voltage and regulates a 0. 3-1.SV output voltage. The converter employs a proposed output-boosting scheme that increases the output voltage of the conventional 3-ratio SC converter power-efficiently. Therefore, the voltage conversion ratios increase from 3 to 14 without the need for additional cascaded SC converter stages. The proposed converter was designed and simulated with a 0. 1S$\mu$m CMOS process and achieved a peak efficiency of 86.7% and a maximum output current of 0.8 mA.
Static sensitivity of whole-room indirect calorimeters

Whole-room indirect calorimeters (WRIC) are accurate tools to precisely measure energy metabolism in humans via calculation of oxygen consumption and carbon dioxide production. Yet, overall accuracy of metabolic measurements relies on the validity of the theoretical model for gas exchange inside the WRIC volume in addition to experimental and environmental conditions that contribute to the uncertainty of WRIC outcome variables. The aim of this study was to quantitatively study the static sensitivity of a WRIC operated in a push configuration and located at the laboratories of the University Hospital of Pisa with the goal to identify the experimental conditions required to reach the best degree of accuracy for outcome metabolic measurements. Herein we demonstrate that achieving a fractional concentration of carbon dioxide inside the $\text{WRIC} > 0.2{\%}$ at the steady state conditions allows to obtain a relative uncertainty <5% for the outcome metabolic measurements.