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

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

Study on Thermal Energy Conversion Theory in Drilling Process of Coal and Rock Mass with Different Stresses

In view of the problem that the evolutionary mechanism of bit temperature during the drilling process is still unclear and the influencing factors are complex, this paper analyzes the causes of heat generation and the factors of heat production when the drill bit interacts with the coal and rock mass. Considering the stress field distribution of coal and rock mass and the dynamic characteristics of drilling, a three-dimensional mechanical structure model of bit drilling is established in this paper, based on the energy conservation theory and introducing the friction heat micro-distribution mechanism. The corresponding relationship between coal stress and the bit temperature variation rate is obtained in this paper. Therefore, the temperature rise condition model and the coal stress identification model can be verified, combined with the existing experimental data. The result shows that the temperature of bit drilling is affected by factors such as bit geometry and drilling parameters, as well as the strength and stress state of the coal and rock. Without considering other factors, the rate of increase in bit temperature is proportional to the stress of the coal and rock mass. Based on the research results, the temperature rate of the drill bit can be used as an index to identify the stress areas of coal and rock mass. Research results provide a theoretical basis for the identification of high-stress risk areas in coal mines

Ti/PbO₂ Electrode Efficiency in Catalytic Chloramphenicol Degradation and Its Effect on Antibiotic Resistance Genes

Livestock farming has led to the rapid accumulation of antibiotic resistance genes in the environment. Chloramphenicol (CAP) was chosen as a model compound to investigate its degradation during electrochemical treatment. Ti/PbO2 electrodes were prepared using electrodeposition. The prepared Ti/PbO2-La electrodes had a denser surface and a more complete PbO2 crystal structure. Ti/PbO2-Co electrodes exhibited improved electrochemical catalytic activity and lifetime in practice. The impact of different conditions on the effectiveness of CAP electrochemical degradation was investigated, and the most favorable conditions were identified (current density: I = 15.0 mA/cm, electrolyte concentration: c = 0.125 mol/L, solution pH = 5). Most importantly, we investigated the effects of the different stages of treatment with CAP solutions on the abundance of resistance genes in natural river substrates (intI1, cmlA, cmle3, and cata2). When CAP was completely degraded (100% TOC removal), no effect on resistance gene abundance was observed in the river substrate; incomplete CAP degradation significantly increased the absolute abundance of resistance genes. This suggests that when treating solutions with antibiotics, they must be completely degraded (100% TOC removal) before discharge into the environment to reduce secondary pollution. This study provides insights into the deep treatment of wastewater containing antibiotics and assesses the environmental impact of the resulting treated wastewater

Research on the correlation between three-dimensional morphology and temperature changes in potato slices during drying

Drying is an effective method to reduce potato storage loss. However, potatoes have high porosity with high water content. Shrinkage during drying can lead to folding and cracking of the dried product form. Therefore, this study explored the correlation between the 3D morphology and temperature distribution changes of potato slices during drying, with the aim of providing a reference for the detection of quality changes. An online automatic acquisition device to obtain 3D morphology and temperature information was designed and built. Hot air-drying experiments were conducted on the potato slices. 3D morphology images and temperature images of the potato slices were acquired by 3D and temperature sensors, and the two images were registered using the random sample consensus (RANSAC) algorithm. The region of interest of each image was extracted by algorithms such as threshold segmentation, hole filling and morphological erosion, and the 3D morphology information and temperature information were obtained. The mapping, range and average of each acquisition point were calculated for correlation analysis. Spearman's rank correlation coefficients and Maximum Information Coefficient (MIC) values were selected as measures for the correlation study. The results showed that the Spearman's rank correlation coefficients between average height and average temperature were mostly above 0.7 in absolute value, and the MICs were mostly above 0.9. The average values of the 3D information and temperature information exhibited an extremely strong correlation. This paper gives a new approach to investigate the morphological changes in the drying process by quantifying the relationship between 3D morphology and temperature distribution. This can guide the improvement of potato drying and processing methods