To effectively fuse speech and visual features, this letter proposes a multi-modal emotion recognition method by fusing correlation features of speech-visual. Firstly, speech and visual features are ...extracted by two-dimensional convolutional neural network (2D-CNN) and three-dimensional convolutional neural network (3D-CNN), respectively. Secondly, the speech and visual features is processed by feature correlation analysis algorithm in multi-modal fusion. In addition, the class information of speech and visual features are also applied to the feature correlation analysis algorithm, which can effectively fuse speech and visual features and improve the performance of multi-modal emotion recognition. Finally, support vector machines (SVM) completes the classification of multi-modal speech and visual emotion recognition. Experimental results on the RML, eNTERFACE05, BAUM-1 s datasets show that the recognition rate of our method is higher than other state-of-the-art methods.
•Pseudomonas sp. exhibited the HN-AD ability using PCL as a sole carbon source.•The amoA, napA, nirS, cnorB and nosZ genes were successfully expressed.•The weight loss of PCL films reached 94.03% ...after 60-days degradation.•The increase in PCL concentrations led to a decrease in nitrogen removal rate.
The novel isolated strain JQ-H3 exhibited heterotrophic nitrification-aerobic denitrification (HN-AD) ability using poly (ε-caprolactone) (PCL) as a sole carbon source under aerobic conditions. This was the first time that a PCL-degrading bacterium was characterized to be with capability of nitrifying and denitrifying performances. Strain JQ-H3 removed approximately 95.40% of NH4+-N (102.40 mg/L), about 91.1% of NO3−-N (99.01 mg/L), with the maximum specific removal rates of 0.308 mg NH4+-N/mg DCW/h and 0.220 mg NO3−-N/mg DCW/h, respectively. The functional genes amoA, napA, nirS, cnorB, and nosZ were successfully expressed during the nitrogen removal process. An increasing PCL concentrations caused a decline in cell growth and nitrogen removal efficiency, which was attributed to the decrease in the rate of the PCL hydrolysis and the amount of dissolved organic carbon (DOC) release. These results demonstrated the strain as an ideal candidate for nitrogen removal from wastewater by using PCL as carbon source.
Source localization is a key technology in array signal processing. However, it has a serious problem that the direction of arrival (DOA) estimation accuracy is reduced at low signal-to-noise ratio ...(SNR). Thus, this Letter proposes an improved near-field multiple signal classification (INF-MUSIC) algorithm to improve DOA estimation accuracy at low SNR. Firstly, the fourth-order cumulant is used to construct a Hermitian matrix with only DOA information. Secondly, the spatial spectrum has physical property that is a breakpoint and approaches a larger value at the DOA, thus first derivative of spatial spectrum is used to improve DOA estimation accuracy at low SNR. Finally, the corresponding ranges are estimated one by one by the one-dimensional MUSIC algorithm. The simulation results show that the INF-MUSIC algorithm makes the DOA estimation accuracy improved by 2° at low SNR.
The field of orthopedics has long struggled with the challenge of repairing and regenerating bone defects, which involves a complex process of osteogenesis requiring coordinated interactions among ...different types of cells. The crucial role of endothelial cells and osteoblasts in bone vascularization and osteogenesis underscores the importance of their intimate interaction. However, efforts to bioengineer bone tissue have been impeded by the difficulty in establishing proper angiogenesis and osteogenesis in tissue structures. This study presents a novel approach to bone tissue engineering, involving a three-dimensional composite hydrogel scaffold composed of sodium alginate microspheres encapsulated in type I collagen. Using this scaffold, a three-dimensional indirect co-culture system was established for osteoblasts and endothelial cells to evaluate the osteogenic differentiation potential of osteoblasts. Results demonstrate that the non-contact co-culture system of endothelial cells and osteoblasts constructed by the composite hydrogel scaffold loaded with microspheres holds promise for bone tissue engineering. The innovative concept of an indirect co-culture system presents exciting prospects for conducting intercellular communication studies and offers a valuable in vitro tissue platform to investigate tissue regeneration.
Cinnamon essential oil with many bioactivities is an important raw material for the production of various chemicals, and the conventional hydrodistillation (HD) for cinnamon oil extraction always ...require a longer extraction time. In this work, ultrasound-assisted hydrodistillation extraction (UAHDE) technique was employed to enhance the extraction efficiency of essential oils from cinnamon barks. The parameters with significant effects on the essential oil extraction efficiency (ultrasound time, ultrasound power, extraction time, liquid–solid ratio) were optimized, and the proposed UAHDE was compared with the conventional HD extraction in terms of the extraction time, extraction yield, and physicochemical properties of extracted oils. Compared to the HD extraction, the UAHDE resulted in a shorter extraction time and a higher extraction yield. Using GC–MS analysis, the UAHDE provided more valuable essential oil with a high content of the vital trans-cinnamaldehyde compounds compared with the HD. Scanning electron micrograph (SEM) confirmed the efficiency of ultrasound irradiation for cinnamon oil extraction. In addition, the analysis of electric consumption and CO2 emission shows that the UAHDE process is a more economic and environment-friendly approach. Thus, UAHDE is an efficient and green technology for the cinnamon essential oil extraction, which could improve the quantity and quality of cinnamon oils.
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•Extraction of cinnamon oil via ultrasound assisted hydrodistillation extraction.•The parameters with significant effects on essential oil extraction are optimized.•UAHDE is superior to traditional HD in terms of duration and yield of oils.•UAHDE could obtain higher trans-cinnamaldehyde concentration in cinnamon oil.•Ultrasound treatment disrupts the plant tissue structure, accelerating oil release.
Diabetic cardiomyopathy (DCM) is a common complication of diabetes and is characterized by chronic myocardial inflammation. Mesenchymal stem cell (MSC) infusions have recently been suggested to ...alleviate myocardial injury and ameliorate cardiac function. However, few studies have focused on the effects of MSCs in DCM. Therefore, we explored the effects of MSC-regulated macrophage polarization on myocardial repair in DCM.
A DCM rat model was induced by a high-fat diet and streptozotocin (STZ) administration and infused 4 times with MSCs. Rat blood and heart tissue were analyzed for blood glucose levels, lipid levels, echocardiography, histopathology, macrophage phenotype ratios and inflammatory cytokines, respectively. We mimicked chronic inflammation in vitro by inducing peritoneal macrophages with high glucose and LPS, then cocultured these macrophages with MSCs to explore the specific mechanism of MSCs on macrophage polarization.
DCM rats exhibited abnormal blood glucose levels and lipid metabolism, cardiac inflammation and dysfunction. MSC infusion ameliorated metabolic abnormalities and preserved cardiac structure and function in DCM rats. Moreover, MSC infusion significantly increased the M2 phenotype macrophages and alleviated cardiac inflammation. Interestingly, this in vitro study revealed that the MSCs pretreated with a COX-2 inhibitor had little effect on M2 macrophage polarization, but this phenomenon could be reversed by adding prostaglandin E2 (PGE2).
Our results suggested that MSC infusions can protect against cardiac injury in DCM rats. The underlying mechanisms may include MSC-enhanced M2 macrophage polarization via the COX-2-PGE2 pathway.
•A circumfluent circulatory separator system (CCSS) was designed.•Separtion performance of CCSS was discussed.•Comparisons of the separtion performance of the CCSS, the CFC and the CC were presented.
...Removal of fine particles from exhaust gases is an importance task currently. These particles, which are hazardous to human health or have to be recovered for products, are difficult to remove by conventional separation technology. In this work, the separation performance of fine dust in a new designed circumfluent circulatory separator system (CCSS) was investigated experimentally. The separator system that we have developed consists mainly of two circumfluent cyclones (CFC) and a separation column. Experiments were carried out to investigate the effects of inlet gas velocity and the refluxing mode on the removal efficiency of fine particles. The separator system showed 100% removal efficiency of particles equal and greater than 1.0 μm, and 97% for particles 0.3–0.6 μm in diameter at the inlet gas velocity range of 17–36.5 m/s when the gas discharged from the second separator returned to the separation column. In addition, the pressure drops of CCSS are only about 20% higher than that of the common cyclone. This work demonstrates that CCSS has a low pressure drop and higher removal efficiency of fine particles. Consequently, it provides an easy, cheap and efficient alternative approach for removal of fine particles from gas steam.
Purpose
Thoracic spinal stenosis (TSS) is a rare disease secondary to multiple pathological changes that differ in prevalence and clinical characteristics. The epidemiological characteristics of ...these pathologies are largely unknown due to the limited case samples and regional differences. Therefore, a systematic review was conducted to elucidate the prevalence and clinical characteristics of TSS.
Methods
Case series and case reports on the ossification of the posterior longitudinal ligaments (OPLL), ossification of the ligamentum flavum (OLF) and thoracic disk herniation (TDH) were screened from PubMed, Embase and Web of Science databases and systematically reviewed. Epidemiological, demographic and segmental distribution data were extracted and analyzed.
Results
A total of 129 studies including 1935 subjects were selected, of which 361 (18.7%) were diagnosed with OPLL, 804 (41.5%) with OLF, 143 (7.4%) with OPLL + OLF and 627 (32.4%) with TDH. Most reports were from China, Japan and USA. Thoracic OPLL occurred mostly at the middle-thoracic spine (43.4%), while OLF predominately occurred at the lower-thoracic spine (63.1%). TDH was mainly localized in the middle (46.0%) and lower-thoracic (50.3%) spine. Thirty-two studies involving 524 patients described tandem spinal stenosis, of which 52.1% had accompanying cervical diseases and 35.9% lumbar diseases.
Conclusions
There are significant differences in the age, sex and segment distribution characteristics of different pathologies leading to TSS. Tandem spinal stenosis is not uncommon and should be considered when diagnosing TSS. Our findings provide new insights into the prevalence and clinical characteristics of TSS and can help reduce misdiagnosis.
The human brain is a large-scale integrated network in the functional and structural domain. Graph theoretical analysis provides a novel framework for analysing such complex networks. While previous ...neuroimaging studies have uncovered abnormalities in several specific brain networks in patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures, little is known about changes in whole-brain functional and structural connectivity networks. Regarding functional and structural connectivity, networks are intimately related and share common small-world topological features. We predict that patients with idiopathic generalized epilepsy would exhibit a decoupling between functional and structural networks. In this study, 26 patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures and 26 age- and sex-matched healthy controls were recruited. Resting-state functional magnetic resonance imaging signal correlations and diffusion tensor image tractography were used to generate functional and structural connectivity networks. Graph theoretical analysis revealed that the patients lost optimal topological organization in both functional and structural connectivity networks. Moreover, the patients showed significant increases in nodal topological characteristics in several cortical and subcortical regions, including mesial frontal cortex, putamen, thalamus and amygdala relative to controls, supporting the hypothesis that regions playing important roles in the pathogenesis of epilepsy may display abnormal hub properties in network analysis. Relative to controls, patients showed further decreases in nodal topological characteristics in areas of the default mode network, such as the posterior cingulate gyrus and inferior temporal gyrus. Most importantly, the degree of coupling between functional and structural connectivity networks was decreased, and exhibited a negative correlation with epilepsy duration in patients. Our findings suggest that the decoupling of functional and structural connectivity may reflect the progress of long-term impairment in idiopathic generalized epilepsy, and may be used as a potential biomarker to detect subtle brain abnormalities in epilepsy. Overall, our results demonstrate for the first time that idiopathic generalized epilepsy is reflected in a disrupted topological organization in large-scale brain functional and structural networks, thus providing valuable information for better understanding the pathophysiological mechanisms of generalized tonic-clonic seizures.
The discrimination of microseismic events and quarry blasts has been examined in this paper. To do so, Principal Component Analysis (PCA) and Artificial Neural Networks (ANN) have been used. The ...procedure proposed has been tested on 22 seismic parameters of 1600 events. In this work, the PCA has been used to transform the original dataset into a new dataset of uncorrelated variables. The new dataset generated has been used as input for ANN and compared to Logistic Regression (LR), Bayes and Fisher classifiers, which classify microseismic events and quarry blasts. The results have shown that PCA is effective for rating variables and reducing data dimension. Furthermore, the classification result based on PCA has been better than those based Ref. 22 and without PCA methods. Moreover, the ANN classifier has obtained the best classification result. The Matthew's Correlation Coefficient (MCC) results of the PCA, Ref. 22 and without PCA based methods have reached 89.00%, 73.68% and 82.04%, respectively, thus showing the reliability and potential of the PCA based method.
•Principal Component Analysis (PCA) and Artificial Neural Networks (ANN) are used to improve the classification of microseismic events and quarry blasts.•The classification results based on PCA are better than those based on 22 and without PCA methods.•The classification results using the ANN classifier are better than the Logistic Regression (LR), the Bayes and Fisher classifiers.
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