How phonemes contribute to deep speaker models?

Which phonemes convey more speaker traits is a long-standing question, and various perception experiments were conducted with human subjects. For speaker recognition, studies were conducted with the conventional statistical models and the drawn conclusions are more or less consistent with the perception results. However, which phonemes are more important with modern deep neural models is still unexplored, due to the opaqueness of the decision process. This paper conducts a novel study for the attribution of phonemes with two types of deep speaker models that are based on TDNN and CNN respectively, from the perspective of model explanation. Specifically, we conducted the study by two post-explanation methods: LayerCAM and Time Align Occlusion (TAO). Experimental results showed that: (1) At the population level, vowels are more important than consonants, confirming the human perception studies. However, fricatives are among the most unimportant phonemes, which contrasts with previous studies. (2) At the speaker level, a large between-speaker variation is observed regarding phoneme importance, indicating that whether a phoneme is important or not is largely speaker-dependent

Preparation and sintering behavior of ultrafine Cu–20W composite powders by sol–gel with hydrogen reduction technology

Cu–20%W (mass fraction) ultrafine composite powders were prepared by the combination of sol–gel with hydrogen reduction method, using ammonium metatungstate and copper nitrate as the raw materials, and the Cu–20W samples were obtained by pressing and sintering. The morphology and particle size of the powders were characterized, and the effects of sintering temperatures on the microstructure and properties of the Cu–20W sintered samples were investigated. The results show that the Cu–20W composite powders are obtained by the combination of sol–gel with hydrogen reduction method with the average particle size of less than 100 nm. With the increase of sintering temperature, the physical and mechanical properties of the sintered Cu–20W samples are improved. The relative density of the samples sintered at 1080 ℃ is 97.20%, the electrical conductivity (IACS), thermal conductivity, Vickers hardness, and tensile strength are reached as 91.73%, 351.52 W·m–1·K–1, HV 96.1, and 431.03 MPa, respectively. In the temperature range of 100～400 ℃, the coefficient of thermal expansion for the sintered Cu–20W samples is 14.871×10–6~17.422×10–6·K–1

Single-cell sequencing combined with machine learning reveals the mechanism of interaction between epilepsy and stress cardiomyopathy

BackgroundEpilepsy is a disorder that can manifest as abnormalities in neurological or physical function. Stress cardiomyopathy is closely associated with neurological stimulation. However, the mechanisms underlying the interrelationship between epilepsy and stress cardiomyopathy are unclear. This paper aims to explore the genetic features and potential molecular mechanisms shared in epilepsy and stress cardiomyopathy.MethodsBy analyzing the epilepsy dataset and stress cardiomyopathy dataset separately, the intersection of the two disease co-expressed differential genes is obtained, the co-expressed differential genes reveal the biological functions, the network is constructed, and the core modules are identified to reveal the interaction mechanism, the co-expressed genes with diagnostic validity are screened by machine learning algorithms, and the co-expressed genes are validated in parallel on the epilepsy single-cell data and the stress cardiomyopathy rat model.ResultsEpilepsy causes stress cardiomyopathy, and its key pathways are Complement and coagulation cascades, HIF-1 signaling pathway, its key co-expressed genes include SPOCK2, CTSZ, HLA-DMB, ALDOA, SFRP1, ERBB3. The key immune cell subpopulations localized by single-cell data are the T_cells subgroup, Microglia subgroup, Macrophage subgroup, Astrocyte subgroup, and Oligodendrocytes subgroup.ConclusionWe believe epilepsy causing stress cardiomyopathy results from a multi-gene, multi-pathway combination. We identified the core co-expressed genes (SPOCK2, CTSZ, HLA-DMB, ALDOA, SFRP1, ERBB3) and the pathways that function in them (Complement and coagulation cascades, HIF-1 signaling pathway, JAK-STAT signaling pathway), and finally localized their key cellular subgroups (T_cells subgroup, Microglia subgroup, Macrophage subgroup, Astrocyte subgroup, and Oligodendrocytes subgroup). Also, combining cell subpopulations with hypercoagulability as well as sympathetic excitation further narrowed the cell subpopulations of related functions

Mechanisms of Myocardial Stunning in Stress-Induced Cardiomyopathy

Stress-induced cardiomyopathy, in contrast to acute myocardial infarction, is a type of acute heart failure characterized by reversible left ventricular dysfunction. Cardiac imaging primarily reveals left ventricle myocardial stunning, 81.7% of which is apical type. Emotional or psychological stress usually precedes the onset of stress-induced cardiomyopathy, which is increasingly being recognized as a unique neurogenic myocardial stunning disease. To distinguish between acute myocardial infarction and acute viral or auto-immune myocarditis, this review summarizes specific mechanisms of myocardial stunning in stress-induced cardiomyopathy, such as calcium disorders, metabolic alterations, anatomical and histological variations in different parts of the left ventricle, and microvascular dysfunction

The Role of Sleep Deprivation in Arrhythmias

Sleep is essential to the normal psychological and physiological activities of the human body. Increasing evidence indicates that sleep deprivation is associated with the occurrence, development, and poor treatment effects of various arrhythmias. Sleep deprivation affects not only the peripheral nervous system but also the central nervous system, which regulates the occurrence of arrhythmias. In addition, sleep deprivation is associated with apoptotic pathways, mitochondrial energy metabolism disorders, and immune system dysfunction. Although studies increasingly suggest that pathological sleep patterns are associated with various atrial and ventricular arrhythmias, further research is needed to identify specific mechanisms and recommend therapeutic interventions. This review summarizes the findings of sleep deprivation in animal experiments and clinical studies, current challenges, and future research directions in the field of arrhythmias

A Maximum Power Transfer Tracking Method for WPT Systems with Coupling Coefficient Identification Considering Two-Value Problem

Maximum power transfer tracking (MPTT) is meant to track the maximum power point during the system operation of wireless power transfer (WPT) systems. Traditionally, MPTT is achieved by impedance matching at the secondary side when the load resistance is varied. However, due to a loosely coupling characteristic, the variation of coupling coefficient will certainly affect the performance of impedance matching, therefore MPTT will fail accordingly. This paper presents an identification method of coupling coefficient for MPTT in WPT systems. Especially, the two-value issue during the identification is considered. The identification approach is easy to implement because it does not require additional circuit. Furthermore, MPTT is easy to realize because only two easily measured DC parameters are needed. The detailed identification procedure corresponding to the two-value issue and the maximum power transfer tracking process are presented, and both the simulation analysis and experimental results verified the identification method and MPTT