Miracle-dz/UniFAR-FTUs huggingface dataset:
Age Estimation based on MFCC Speech Features and Machine Learning Algorithms

This paper analyses how well various machine learning algorithms perform when used to infer a person's age from speech in real-world applications including human machine interfaces (HMI), automatic speech recognition (ASR), and interactive voice response (IVR) systems seen in call centers. The difficulty of the present techniques for extracting salient high-level speech features and classification models makes it a difficult challenge in speech processing to categorize speakers according to their age. We combine PCA with machine learning methods including Support Vector machine (SVM), Decision Tree (DT), and Random Forest (RF) to create a novel age estimation strategy to address these issues. These methods, each using a distinct PCA and MFCC, are examined to learn more about how performance relates to the features taken from the voice corpus. Mozilla's Common Voice dataset, a free and crowd sourced voice corpus, was used as the speech corpus for the tests. The results for age categorization utilizing PCA, cross validation, and seeding in training and testing using different machine learning approaches are pretty good. Better accuracy compared to standard classification is provided by the best features chosen by PCA. The outcomes hold promise for usage in automatic speech recognition and interactive voice response systems that interface with humans.
Candida auris as an Emergent Public Health Problem: A Current Update on European Outbreaks and Cases

Candida auris is considered to be an emerging fungal pathogen and is related to high mortality rates, persistent candidemia, inconsistencies in susceptibility testing results and misidentification by available commercial identification systems. Multidrug-resistant (MDR) and pandrug-resistant (PDR) strains are increasingly detected. In Europe, hospital outbreaks caused by C. auris have been reported in the United Kingdom (UK), Italy and Spain; however, several cases have been sporadically detected in all European countries. C. auris is difficult to control despite enhanced control measures due to its ability to survive for a long time in environments and colonize patients for prolonged periods. An adequate laboratory diagnostic capacity and national surveillance are fundamental to rapidly detect new C. auris cases and to apply the correct measures to circumscribe them and prevent their spread. Our narrative review aims to highlight the primary C. auris outbreaks and case reports that have occurred in Europe.
Continuous In Vitro Culture of Babesia duncani in a Serum-Free Medium

Human babesiosis is an emerging tick-borne disease, caused by haemoprotozoa genus of Babesia. Cases of transfusion-transmitted and naturally acquired Babesia infection have been reported worldwide in recent years and causing a serious public health problem. Babesia duncani is one of the important pathogens of human babesiosis, which seriously endangers human health. The in vitro culture systems of B. duncani have been previously established, and it requires fetal bovine serum (FBS) to support long-term proliferation. However, there are no studies on serum-free in vitro culture of B. duncani. In this study, we reported that B. duncani achieved long-term serum-free culture in VP-SFM AGTTM (VP-SFM) supplemented with AlbuMaxTM I. The effect of adding different dilutions of AlbuMaxTM I to VP-SFM showed that 2 mg/mL AlbuMaxTM I had the best B. duncani growth curve with a maximum percentage of parasitized erythrocytes (PPE) of over 40%, and it can be used for long-term in vitro culture of B. duncani. However, the commonly used 20% serum-supplemented medium only achieves 20% PPE. Clearly, VP-SFM with 2 mg/mL AlbuMaxTM I (VP-SFMA) is more suitable for the in vitro proliferation of B. duncani. VP-SFM supplemented with CD lipid mixture was also tested, and the results showed it could support the parasite growth at 1:100 dilution with the highest PPE of 40%, which is similar to that of 2 mg/mL AlbuMaxTM I. However, the CD lipid mixture was only able to support the in vitro culture of B. duncani for 8 generations, while VP-SFMA could be used for long-term culture. To test the pathogenicity, the VP-SFMA cultured B. duncani was also subjected to hamster infection. Results showed that the hamster developed dyspnea and chills on day 7 with 30% PPE before treatment, which is similar to the symptoms with un-cultured B. duncani. This study develops a unique and reliable basis for further understanding of the physiological mechanisms, growth characteristics, and pathogenesis of babesiosis, and provides good laboratory material for the development of drugs or vaccines for human babesiosis and possibly other parasitic diseases.
Modeling SILAC Data to Assess Protein Turnover in a Cellular Model of Diabetic Nephropathy

Protein turnover rate is finely regulated through intracellular mechanisms and signals that are still incompletely understood but that are essential for the correct function of cellular processes. Indeed, a dysfunctional proteostasis often impacts the cell’s ability to remove unfolded, misfolded, degraded, non-functional, or damaged proteins. Thus, altered cellular mechanisms controlling protein turnover impinge on the pathophysiology of many diseases, making the study of protein synthesis and degradation rates an important step for a more comprehensive understanding of these pathologies. In this manuscript, we describe the application of a dynamic-SILAC approach to study the turnover rate and the abundance of proteins in a cellular model of diabetic nephropathy. We estimated protein half-lives and relative abundance for thousands of proteins, several of which are characterized by either an altered turnover rate or altered abundance between diabetic nephropathic subjects and diabetic controls. Many of these proteins were previously shown to be related to diabetic complications and represent therefore, possible biomarkers or therapeutic targets. Beside the aspects strictly related to the pathological condition, our data also represent a consistent compendium of protein half-lives in human fibroblasts and a rich source of important information related to basic cell biology.
Prescription for density profile reconstruction using a heavy ion beam probe

This article presents a method for density profile reconstruction using a heavy ion beam probe. A model calculation is performed to demonstrate the feasibility of the proposed method. The possibility to infer the density profile widely extends the applicability of the heavy ion beam probe by providing fine structural measurements of density profile that is, in principle, continuous in space, with a high temporal resolution of milliseconds.
A novel temporal recovery technique to enable cone beam CT perfusion imaging using an interventional C-arm system

In the current workflow of ischemic stroke management, it is highly desirable to obtain perfusion information with the C-arm CBCT system in the interventional room. Due to hardware limitations, the data acquisition speed of the current Carm CBCT systems is relatively slow and only 7 time frames are available for a 45 s perfusion study. In this study, a novel temporal recovery method was proposed to recover contrast enhancement curves in C-arm CBCT perfusion studies. The proposed temporal recovery problem is a constrained optimization problem. Two numerical methods were used to solve the proposed problem. The feasibility of proposed temporal recovery method was validated with numerical experiments. Both solvers can achieve a satisfactory solution for the temporal recovery problem, while the result of the Bregman algorithm is more accurate than that from the CG. In vivo animal studies were used to demonstrated the improvement of the proposed method in C-arm CBCT perfusion. A stoked canine model was scanned with both C-arm CBCT and diagnostic CT. Perfusion defects can be clearly indentified from the cerebral blood flow (CBF) map of diagnostic CT perfusion. Without the temporal recovery technique, these defects can hardly be identified from the CBCT CBF map. After applying the proposed temporal recovery method, the CBCT CBF map well correlates with the CBF map from diagnostic CT.
Towards the Understanding of the Function of Lanthipeptide and TOMM-Related Genes in Haloferax mediterranei

Simple Summary The knowledge of the biosynthetic pathways and the biological role of secondary metabolites produced by the third domain of life is limited when compared with bacteria or eukaryotes. Herein, we investigated, in more detail, genes encoding enzymes that are predicted to be involved in the biosynthesis of peptide secondary metabolites in halophilic archaea regarding (i) their transcription, (ii) their association with antimicrobial activity, and (iii) the impact of their absence on the biomolecular profile of the cells. Abstract Research on secondary metabolites produced by Archaea such as ribosomally synthesized and post-translationally modified peptides (RiPPs) is limited. The genome of Haloferax mediterranei ATCC 33500 encodes lanthipeptide synthetases (medM1, medM2, and medM3) and a thiazole-forming cyclodehydratase (ycaO), possibly involved in the biosynthesis of lanthipeptides and the TOMMs haloazolisins, respectively. Lanthipeptides and TOMMs often have antimicrobial activity, and H. mediterranei has antagonistic activity towards haloarchaea shown to be independent of medM genes. This study investigated (i) the transcription of ycaO and medM genes, (ii) the involvement of YcaO in bioactivity, and (iii) the impact of YcaO and MedM-encoding genes’ absence in the biomolecular profile of H. mediterranei. The assays were performed with biomass grown in agar and included RT-qPCR, the generation of knockout mutants, bioassays, and FTIR analysis. Results suggest that ycaO and medM genes are transcriptionally active, with the highest number of transcripts observed for medM2. The deletion of ycaO gene had no effect on H. mediterranei antihaloarchaea activity. FTIR analysis of medM and ycaO knockout mutants suggest that MedMs and YcaO activity might be directly or indirectly related t lipids, a novel perspective that deserves further investigation.
Radiophotoluminescent Centers in Silver-Activated Phosphate Glass

ESR studies of radiophotoluminescence (RPL) centers in silver-activated phosphate glass were performed after the glasses had been γ-irradiated at 77°K. It is shown that the silver ions act as traps for both electrons and positive holes. By the separate formation of electron-trapped silver centers and hole-trapped silver center, it was verified that all these silver centers act as RPL centers. It was found that a positive hole in PO 4 tetrahedron is transfered to Ag + ion and this process is the main reason of RPL build-up. Stabilization phenomenon of RPL centers was found. It was found that alkali and or silver ion migration is necessary for stabilization. The reason why RPL in these glasses has high stability and builds-up after γ-irradiation was clarified. The resonances which are considered due to exchange coupled pairs, triads and higher aggregates of electron-trapped silver centers were found.
A Feature-Trajectory-Smoothed High-Speed Model for Video Anomaly Detection

High-speed detection of abnormal frames in surveillance videos is essential for security. This paper proposes a new video anomaly–detection model, namely, feature trajectory–smoothed long short-term memory (FTS-LSTM). This model trains an LSTM autoencoder network to generate future frames on normal video streams, and uses the FTS detector and generation error (GE) detector to detect anomalies on testing video streams. FTS loss is a new indicator in the anomaly–detection area. In the training stage, the model applies a feature trajectory smoothness (FTS) loss to constrain the LSTM layer. This loss enables the LSTM layer to learn the temporal regularity of video streams more precisely. In the detection stage, the model utilizes the FTS loss and the GE loss as two detectors to detect anomalies. By cascading the FTS detector and the GE detector to detect anomalies, the model achieves a high speed and competitive anomaly-detection performance on multiple datasets.
Wearable Ungrounded Tag Antenna for UHF RFID Applications

A single-layer ungrounded tag antenna is designed for on-body radio frequency identification (RFID) applications in the ultrahigh frequency (UHF) band. The ungrounded tag antenna is designed based on a broadside radiating Huygens source. The electric dipole is generated by the center part of an original dipole, while two orthogonal magnetic dipoles are created by stacking another two metallic strips at the edge of the original dipole. The tag antenna shows good robustness of input matching and radiation efficiency with respect to the human-body effect. Furthermore, the designed tag antenna is also able to work with metallic objects and its resonant frequency is stable around 920 MHz. Finally, three tag prototypes, including the proposed tag antenna, are fabricated and tested. The measured reading range confirms the numerical simulations and demonstrates the robustness of the proposed design with respect to different distances between human-body and tag antenna. The proposed tag provides a reading range of 5.0 m (near-body), 8.0 m (free space), and 16.5 m ( $200\times200$ mm metallic plate), respectively.
Modified RLS algorithm for unbiased estimation of FIR system with input and output noise

In the presence of both input and output noise, the classical least squares solution for finite-impulse response (FIR) estimation is biased. It has been shown that bias can be removed by properly scaling the optimal FIR filter coefficients in the least-squares (LS) criterion. A modified recursive least squares (MRLS) algorithm is proposed for accurate identification of a system with both input and output noise. Simulation results show that this method outperforms the modified LMS algorithm under non-stationary interference conditions.
Direct Evidence of the Anisotropic Structure of Vortices Interacting with Columnar Defects in High-Temperature Superconductors through the Analysis of Lorentz Images

Two types of Fresnel contrasts of superconducting vortices in a Lorentz micrograph, corresponding to pinned and unpinned vortices, were obtained by a newly developed 1 MV field-emission transmission electron microscope on a Bi 2 Sr 2 CaCu 2 O 8+δ (Bi-2212) thin specimen containing tilted linear columnar defects introduced by heavy ion irradiation. The main features of the Fresnel contrasts could be consistently interpreted by assuming that the vortices are pinned along the tilted columnar defects and by using a layered or an anisotropic model to calculate the phase shift of the electron wave. The confirmed validity of both models strongly indicates that superconducting vortices in high-critical temperature (high- T c ) layered materials have an anisotropic structure.
3D Printing Ceramics—Materials for Direct Extrusion Process

Additive manufacturing and 3D printing methods based on the extrusion of material have become very popular in recent years. There are many methods of printing ceramics, but the direct extrusion method gives the largest range of sizes of printed objects and enables scaling of processes also in large-scale applications. Additionally, the application of this method to ceramic materials is of particular importance due to its low cost, ease of use, and high material utilization. The paper presents the most important literature reports on ceramics printed by direct extrusion. The review includes articles written in English and published between 2017 and 2022. The aim of this literature review was to present the main groups of ceramic materials produced by extrusion-based 3D printing.
Single-Sensor Engine Multi-Type Fault Detection

Engine fault detection is conducive to improving equipment reliability and reducing maintenance costs. In practical scenarios, high-quality data is difficult to obtain. Usually, only single-sensor data is available. This paper proposes a fault detection method combining Variational Mode Decomposition (VMD) and Random Forest (RF). At first, the spectral energy distribution is obtained by decomposing and statistic the engine data of multiple working conditions. Based on the spectral energy distribution, the overall optimal mode number was identified, and the quadratic penalty term was optimized using SNR. The improved VMD (IVMD) improves mode aliasing and iterative efficiency and unifies feature dimensions. Decomposition of real signals demonstrates the effectiveness. The paper designs a feature vector composed of seven types of attributes, including unit bandwidth energy, center frequency, maximum singular value and so on. The feature vector is then fed to RF for classification. Features are selected in order of importance to classification to improve the training efficiency. By comparing with various algorithms, the proposed method has higher accuracy and faster training efficiency in single-speed, multi-speed and cross-speed single-sensor data diagnosis. The results show that the method has application prospects with little training data and low hardware requirements.
THE MULTIPLE CORRELATION COEFFICIENT AND FISHER'S A STATISTIC 1

Fisher's A statistic, often called the adjusted R2 statistic, is shown to be a close approximation to the maximum likelihood estimate of the multiple correlation coefficient, p2, based on the marginal distribution of R2. Expansions for the estimate are obtained. The same methods lead to maximum marginal likelihood estimators for the noncentrality parameters for noncentral X2 and F.
A Heuristic Machine Learning-Based Optimization Technique to Predict Lung Cancer Patient Survival

Cancer has been a significant threat to human health and well-being, posing the biggest obstacle in the history of human sickness. The high death rate in cancer patients is primarily due to the complexity of the disease and the wide range of clinical outcomes. Increasing the accuracy of the prediction is equally crucial as predicting the survival rate of cancer patients, which has become a key issue of cancer research. Many models have been suggested at the moment. However, most of them simply use single genetic data or clinical data to construct prediction models for cancer survival. There is a lot of emphasis in present survival studies on determining whether or not a patient will survive five years. The personal issue of how long a lung cancer patient will survive remains unanswered. The proposed technique Naive Bayes and SSA is estimating the overall survival time with lung cancer. Two machine learning challenges are derived from a single customized query. To begin with, determining whether a patient will survive for more than five years is a simple binary question. The second step is to develop a five-year survival model using regression analysis. When asked to forecast how long a lung cancer patient would survive within five years, the mean absolute error (MAE) of this technique's predictions is accurate within a month. Several biomarker genes have been associated with lung cancers. The accuracy, recall, and precision achieved from this algorithm are 98.78%, 98.4%, and 98.6%, respectively.
Electromagnetic ion cyclotron waves observed near the oxygen cyclotron frequency by ISEE 1 and 2

Pc 2 electromagnetic ion cyclotron waves at 0.1 Hz, near the oxygen cyclotron frequency, have been observed by ISEE 1 and 2 between L = 7.6 and 5.8 on an inbound near-equatorial pass in the dusk sector. The waves occurred in a thick plasmapause of width ≈1.5 RE and penetrated ≈1 RE into the plasmasphere. Wave onset was accompanied by significant increases in the thermal (0–100 eV) He+ and the warm (0.1–16 keV/e) O+ and He+ heavy ion populations. The most intense waves (8 nT) were observed in the outer plasmasphere where convection drift velocities (E × B)/B² were largest and the Alfven velocity was a minimum. Wave polarization is predominantly left-handed with propagation almost parallel to the ambient magnetic field, and the spectral slot and polarization reversal predicted by cold plasma propagation theory are identified in the wave data. Poynting fluxes calculated during the first 15 min of the event show wave energy propagation directions both parallel and antiparallel to the field. Computations of the experimental wave spectra during the passage through the plasmapause show that the spectral slots relate to local plasma parameters, possibly suggesting an ion cyclotron wave growth source near the spacecraft. A regular wave packet structure seen over the first 30 min of the event may be attributed to the modulation of this energy source by the Pc 5 waves seen at the same time. Overall, the results are considered an example of an electromagnetic ion cyclotron wave-particle interaction occurring during the outer plasmasphere refilling process at the time of the substorm recovery phase.
Influences of the alignment and misalignment spatial filters on the beam quality in high power laser systems

The characteristics of the alignment and misalignment multistage spatial filters are presented in this paper based on their effects on the beam quality. First, the approximate analytical expressions of the modulations of a square beam, which are induced by scatterers and an alignment spatial filter pinhole, are derived. Then, the far field analytical expression of the modulated square beam after its propagation through a nonlinear medium is presented. Subsequently, using a square super Gaussian beam, the modulations induced by an alignment and misalignment spatial filter pinhole are illustrated. The suppressing functions of the alignment and misalignment spatial filters on the hot image are investigated. The effects of the misalignment of the multistage spatial filter pinholes on the output beam quality are studied based on two evaluation factors: fluence beam contrast and fill factor. It is shown that the spatial filter pinhole misalignment has significant influences on both the far field and near field of the downstream beam, especially when nonlinear media exist. The results presented in this paper give important references and guidance for the spatial filter design, installation and alignment.
European Stroke Organisation (ESO) Guidelines on Moyamoya angiopathy Endorsed by Vascular European Reference Network (VASCERN)

The European Stroke Organisation (ESO) guidelines on Moyamoya Angiopathy (MMA), developed according to ESO standard operating procedure and Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology, were compiled to assist clinicians in managing patients with MMA in their decision making. A working group involving neurologists, neurosurgeons, a geneticist and methodologists identified nine relevant clinical questions, performed systematic literature reviews and, whenever possible, meta-analyses. Quality assessment of the available evidence was made with specific recommendations. In the absence of sufficient evidence to provide recommendations, Expert Consensus Statements were formulated. Based on low quality evidence from one RCT, we recommend direct bypass surgery in adult patients with haemorrhagic presentation. For ischaemic adult patients and children, we suggest revascularization surgery using direct or combined technique rather than indirect, in the presence of haemodynamic impairment and with an interval of 6–12 weeks between the last cerebrovascular event and surgery. In the absence of robust trial, an Expert Consensus was reached recommending long-term antiplatelet therapy in non-haemorrhagic MMA, as it may reduce risk of embolic stroke. We also agreed on the utility of performing pre- and post- operative haemodynamic and posterior cerebral artery assessment. There were insufficient data to recommend systematic variant screening of RNF213 p.R4810K. Additionally, we suggest that long-term MMA neuroimaging follow up may guide therapeutic decision making by assessing the disease progression. We believe that this guideline, which is the first comprehensive European guideline on MMA management using GRADE methods will assist clinicians to choose the most effective management strategy for MMA.