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With escalating mortality rates associated with cardiovascular disease, the early detection of arrhythmias assumes ever-increasing significance. This study introduces a novel multimodal network that concurrently classifies electrocardiogram (ECG) and wrist pulse signal (WPS). Both ECG and WPS, as human physiological signals, share closely related distributions and characteristics, holding potential to accurately reflect underlying cardiovascular conditions. The proposed ICMT-Net utilizes continuous wavelet transform to partition 5-second ECG and WPS segments into spectrograms. It incorporates an improved ConvNeXt, a multimodal transformer layer, and a fused multi-layer perceptron to extract and fuse multimodal features for ECG classification. Subsequently, the network is adapted to WPS and coronary heart disease classification tasks through transfer learning techniques. In comparison to existing methods, our approach achieves heightened sensitivity in detecting supraventricular and ventricular ectopic segments, while also outperforming established WPS classification methodologies. Importantly, the proposed network adeptly handles multimodal signals and excels in classification accuracy, particularly within the realm of physiological signals.

Abstract Background The principal objective of this study was to gain a better understanding of the mechanisms of type 2 diabetes mellitus (T2DM) patients with fatigue (D-T2DM) through exome and transcriptome sequencing. Methods After whole-exome sequencing on peripheral blood of 6 D-T2DM patients, the consensus mutations were screen out and analyzed by a series of bioinformatics analyses. Then, we combined whole-exome sequencing and transcriptome sequencing results to find the important genes that changed at both the DNA and RNA levels. Results The results showed that a total of 265,393 mutation sites were found in D-T2DM patients compared with normal individuals, 235 of which were consensus mutations shared with D-T2DM patients. These genes significantly enriched in HIF-1 signaling pathway and sphingolipid signaling pathway. At the RNA level, a total of 375 genes were identified to be differentially expressed. After the DNA-RNA joint analysis, eight genes were screened that changed at both DNA and RNA levels. Among these genes, FUS and LMNA were related to carbohydrate metabolism, energy metabolism, and mitochondrial function. Subsequently, we predicted the herbs, including Qin Pi and Hei Zhi Ma, that might play a therapeutic role in D-T2DM through the SymMap database. Conclusion These findings have significant implications for understanding the mechanisms of D-T2DM and provide potential targets for D-T2DM diagnosis and treatment.

Abstract Medical image segmentation is a fundamental step in medical analysis and diagnosis. In recent years, deep learning networks have been used for precise segmentation. Numerous improved encoder–decoder structures have been proposed for various segmentation tasks. However, high-level features have gained more research attention than the abundant low-level features in the early stages of segmentation. Consequently, the learning of edge feature maps has been limited, which can lead to ambiguous boundaries of the predicted results. Inspired by the encoder–decoder network and attention mechanism, this study investigates a novel multilayer edge attention network (MEA-Net) to fully utilize the edge information in the encoding stages. MEA-Net comprises three major components: a feature encoder module, a feature decoder module, and an edge module. An edge feature extraction module in the edge module is designed to produce edge feature maps by a sequence of convolution operations so as to integrate the inconsistent edge information from different encoding stages. A multilayer attention guidance module is designed to use each attention feature map to filter edge information and select important and useful features. Through experiments, MEA-Net is evaluated on four medical image datasets, including tongue images, retinal vessel images, lung images, and clinical images. The evaluation values of the Accuracy of four medical image datasets are 0.9957, 0.9736, 0.9942, and 0.9993, respectively. The values of the Dice coefficient are 0.9902, 0.8377, 0.9885, and 0.9704, respectively. Experimental results demonstrate that the network being studied outperforms current state-of-the-art methods in terms of the five commonly used evaluation metrics. The proposed MEA-Net can be used for the early diagnosis of relevant diseases. In addition, clinicians can obtain more accurate clinical information from segmented medical images.

A multi-channel gliding arc (MCGA) plasma with an average power of 6000 W is utilized to control the flame flashback in a dual-mode scramjet combustor with a cavity flameholder. Optical measurements, including synchronous high-speed CH* emissions and high-speed schlieren, simultaneous high-speed camera with the oblique view and high-speed CH* emission, accompanied by the three-dimensional RANS simulation, were employed to characterize the flame flashback with or without the MCGA plasma. The results show that a typical flame flashback cycle can be observed with a period of ∼2 ms in the combustor. The back pressure reduced by the dynamic heat release of the reaction zone is not sufficient to form the steady thermal choking in the mainstream in the absence of the MCGA, which results in the oblique shocks and bow shocks appearing in dual-mode scramjet combustion. When the plasma is added, the flame is strengthened near the plasma region, and the combustion oscillation is suppressed significantly. The re-ignition and attachment characteristics of the MCGA plasma provide the new flame kernels to the mainstream flame, and the leading edge of the mainstream flame follows the MCGA plasma. Due to the relatively stable heat release near the fuel jet assisted by the plasma, the thermal choking is stable presented in the combustor with bow shocks by higher back pressure, indicating that the combustion oscillation is suppressed by the MCGA plasma in the dual-mode scramjet combustor.

A plasma-assisted internal combustion engine model is established based on detailed plasma kinetics, combustion kinetics, and physical compression/expansion processes. The effects of nanosecond repetitively pulsed discharge (NRPD) on plasma-assisted ignition characteristics of mixtures under different fuel concentrations are studied under HCCI engine-relevant conditions. The coupled plasma and chemical kinetic model are validated with experiments. The comparison between NRPD and thermal ignition with a certain amount of input energy is carried out, and the results show that the former can ignite a mixture owing to the kinetic effect of nonequilibrium plasma, but the latter cannot ensure ignition. Path flux analysis shows that excited states and electrons react with fuel, providing O and H directly, increasing the possibility of ignition at a low temperature. The effect of NRPD on combustion performance under various equivalence ratios (φ) is investigated. It was found that in ICEs with NRPD, the ignition delay time under the lean-burn condition (φ = 0.5) is the shortest among three demonstrative cases. Even though the leaner mixture case with φ = 0.2 is more favorable for the production of O and OH during the discharge, after discharge, the heat release in case 2 with φ = 0.5 dramatically increases, resulting in the temperature exceeding that in the ultra-lean case. As the piston moves up, the higher amounts of CH3, HO2, and H2O2 as well as higher temperature for the lean-burn (φ = 0.5) case lead to the rapid increase of OH and O, which accelerates the consumption of methane and finally the earliest hot ignition near TDC. Finally, a series of parameter studies are performed to show the effects of E/N, current density, φ, and discharge timing on the ignition process. The results suggest that discharge parameters E/N and current density together with discharge timings and equivalence ratios can improve ignitability in internal combustion engines.

Danshen (Salvia miltiorrhiza) is a herb which has been widely used in China. Salvianolic acid B (SalB) is an aqueous bioactive component derived from Danshen. Here, we aimed to estimate the effect of SalB on glycometabolism and lipid metabolism in rats and mice. We searched four databases until November 2020. The outcome measures were fasting blood glucose (FBG), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLc), and low-density lipoprotein cholesterol (LDLc). Twenty-four studies involving 547 animals were included. The meta-analysis showed effects of SalB on decreasing the level of FBG, TC, TG, LDLc, and increasing the level of HDLc compared with the control group. In conclusion, the result showed that SalB may regulate the glycometabolism and lipid metabolism in rats or mice, and may be a potential agent for treating metabolic diseases such as diabetes and hyperlipidemia.

The ethylene-fueled flameholding characteristics of a cavity-based scramjet combustor are experimentally and numerically investigated. The test facility used the air heater, which heats air from room temperature to total temperature 1477 K. A nozzle is installed behind the heater outlet to increase the air speed to Mach 2.52. Two cavity geometries with different rear-wall heights of 8 mm and 10 mm and two injection distances upstream of the cavities of 10 mm and 40 mm are compared to show the effect of these parameters. The CH* spontaneous emission images obtained by dual-camera synchronous shooting and the wall-pressure distribution obtained by a pressure-scan system are used to capture the flame dynamics. The global equivalence ratio range for different combination schemes is controlled from 0.14 to 0.27 in this paper. The results show that the conventional cavity (the rear-wall height is 10 mm) and the shorter injection distance can effectively decrease the lean blowoff limit of the combustor, while the rear-wall-expansion cavity (the rear-wall height is 8 mm) and the longer injection distance can effectively increase the rich blowoff limit. Compared with the injection distance, the rear-wall height of the cavity has little effect on the oscillation distribution of the shear layer-stabilized flame. However, the fuel-injection distance and cavity rear-wall height both have great influence on the spatial distribution of the flame.

Purpose: The purpose of this study is to explore the differences in transcriptome expression profiles between healthy subjects and type 2 diabetes mellitus patients with thirst and fatigue (D-T2DM) and, in addition, to investigate the possible role of noncoding ribonucleic acids (RNAs) in the pathogenesis of D-T2DM.Methods: We constructed the expression profiles of RNAs by RNA sequencing in the peripheral blood of D-T2DM patients and healthy subjects and analyzed differentially expressed RNAs.Results: Compared with healthy subjects, a total of 469 mRNAs, 776 long non-coding RNAs (lncRNAs), and 21 circular RNAs (circRNAs) were differentially expressed in D-T2DM patients. Furthermore, several genes associated with insulin resistance, inflammation, and mitochondrial dysfunction were identified within the differentially expressed mRNAs. Differentially expressed lncRNAs were primarily involved in biological processes associated with immune responses. In addition, differentially expressed circRNAs may target miRNAs associated with glucose metabolism and mitochondrial function.Conclusions: Our results may bring a new perspective on differential RNA expression involved in the pathogenesis of D-T2DM and promote the development of novel treatments for this disease.

Effects of additional cavity floor injection on the ethylene ignition and combustion processes in a cavity-based scramjet combustor are investigated experimentally in a Mach 2.0 supersonic flow using flame luminosity and CH* (CH radical) spontaneous emission methods and static pressure measurements. Numerical calculation is performed to study the non-reacting flow-field structures prior to ignition. Two injection schemes, including the cavity upstream injection scheme and the combined injection scheme with an additional cavity floor injection, are compared to study the effects of the additional cavity floor injection on the ignition and combustion processes. It is found that there exists an equivalence ratio upper limit for maintaining stable combustion for the cavity upstream injection scheme. As the equivalence ratio further increases, the fuel jet penetration is improved accordingly, and thus, the interaction between the fuel jet and the cavity is weakened, which can lead to the ignition failure and flame blowout during combustion. On the contrary, although the combined injection scheme has a minor effect on combustion enhancement at the same global equivalence ratio, it can also provide a more favorable flow-field environment that enables more successful ignitions and better flame stabilizations. For the combined injection scheme, as the equivalence ratio increases, the initial flame propagations are observed to perform different routines during the ignition process, and the major combustion reaction zone tends to move further downstream the cavity shear layer. It is concluded that the advantages of the combined injection scheme with an additional cavity floor injection are more significant when the equivalence ratio is higher, as well as that the interaction between the fuel jet and the cavity becomes weaker.