We aimed at learning deep emotion features to recognize speech emotion. Two convolutional neural network and long short-term memory (CNN LSTM) networks, one 1D CNN LSTM network and one 2D CNN LSTM ...network, were constructed to learn local and global emotion-related features from speech and log-mel spectrogram respectively. The two networks have the similar architecture, both consisting of four local feature learning blocks (LFLBs) and one long short-term memory (LSTM) layer. LFLB, which mainly contains one convolutional layer and one max-pooling layer, is built for learning local correlations along with extracting hierarchical correlations. LSTM layer is adopted to learn long-term dependencies from the learned local features. The designed networks, combinations of the convolutional neural network (CNN) and LSTM, can take advantage of the strengths of both networks and overcome the shortcomings of them, and are evaluated on two benchmark databases. The experimental results show that the designed networks achieve excellent performance on the task of recognizing speech emotion, especially the 2D CNN LSTM network outperforms the traditional approaches, Deep Belief Network (DBN) and CNN on the selected databases. The 2D CNN LSTM network achieves recognition accuracies of 95.33% and 95.89% on Berlin EmoDB of speaker-dependent and speaker-independent experiments respectively, which compare favourably to the accuracy of 91.6% and 92.9% obtained by traditional approaches; and also yields recognition accuracies of 89.16% and 52.14% on IEMOCAP database of speaker-dependent and speaker-independent experiments, which are much higher than the accuracy of 73.78% and 40.02% obtained by DBN and CNN.
China is experiencing a stage of rapid urban development. The energy consumption and related carbon dioxide emissions of households continue to increase. This paper calculates direct and indirect ...carbon dioxide emissions of households based on the input–output method in China from 1996 to 2012. The results reveal that there were more total carbon dioxide emissions from urban households than from rural households, far more indirect emissions from urban households than from rural households, slightly more direct emissions from urban households than from rural households, and differences in direct carbon dioxide emissions from various fuels and in indirect emissions from various sectors between urban and rural households. To examine the causal relationship between urbanization and the carbon dioxide emissions of households, cointegration and Granger causality tests are applied. A unidirectional causal relation was found running from urbanization to both direct and indirect household carbon dioxide emissions, and the direct and indirect carbon dioxide emissions of households would increase 2.9% and 1.1%, respectively, for every increase of one percent in urbanization. We discuss the reasons of why the development of urbanization will lead to more household direct and indirect carbon dioxide emissions, and suggest certain policy implications for urbanization and carbon dioxide emissions based on the results of this study.
•Direct and indirect carbon emissions of households are calculated.•Differences in carbon emissions between urban and rural households are identified.•A unidirectional causal relation was found running from urbanization to emissions.•Reasons of why urbanization leads to more household carbon emissions are discussed.•Policy implications for urbanization and carbon emissions are suggested.
A practicable strategy to rationally obtain the reversible mechanochromic luminescent (MCL) material with high‐contrast ratio (green versus red) has been established. By introducing a volatile third ...party (small‐sized solvent molecules) into the lattice of charge transfer (CT) cocrystal of mixed‐stacking 1:1 coronene (Cor.) and napthalenetetracarboxylic diimide (NDI), a noteworthy reconfigurable molecular assembly is ingeniously achieved owing to the loosely packing arrangement as well as weakened intermolecular interactions. Accordingly, the CT excited state, strongly corresponding to the molecular stacking modes, can be intentionally tailored through external stimulus (heating, grinding, or solvent), accompanying distinct changes in photophysical properties. Subsequently, a high‐contrast reversible MCL with highly sensitive and good reproducibility is realized and the underlying mechanism is thoroughly revealed.
A simple and practicable strategy is established to obtain high‐contrast reversible mechanoresponsive PL switching by introducing a volatile third party into the lattice of mixed‐stacking CT cocrystal. This has the purpose of constructing the loosely packing mode to realize a facile control of molecular assemblies and CT excitons in the solid state.
The main contribution of this paper is the derivation rules summarized from existing high-performance inverters with H6-type configuration, which makes novel topologies possible. In addition, a novel ...high-efficiency single-phase transformerless photovoltaic inverter with hybrid modulation method is also proposed and evaluated as an example. Without input split capacitors, common-mode voltage and leakage current issues in a nonisolated system with H6-type configuration are eliminated, and the feature of a three-level output voltage in the inverter bridge's middle point helps inductors and power quality optimization. The detailed operation principles with hybrid modulation strategy combined with unipolar and bipolar pulsewidth modulation schemes are presented. Experimental results of a 2200VA prototype verify the proposed topology with hybrid modulation method.
Current therapy of malignant glioma in clinic is unsatisfactory with poor patient compliance due to low therapeutic efficiency and strong systemic side effects. Herein, we combined chemo-photothermal ...targeted therapy of glioma within one novel multifunctional drug delivery system. A targeting peptide (IP)-modified mesoporous silica-coated graphene nanosheet (GSPI) was successfully synthesized and characterized, and first introduced to the drug delivery field. A doxorubicin (DOX)-loaded GSPI-based system (GSPID) showed heat-stimulative, pH-responsive, and sustained release properties. Cytotoxicity experiments demonstrated that combined therapy mediated the highest rate of death of glioma cells compared to that of single chemotherapy or photothermal therapy. Furthermore, the IP modification could significantly enhance the accumulation of GSPID within glioma cells. These findings provided an excellent drug delivery system for combined therapy of glioma due to the advanced chemo-photothermal synergistic targeted therapy and good drug release properties of GSPID, which could effectively avoid frequent and invasive dosing and improve patient compliance.
Gradient nano-grained (GNG) materials, inside which grain size increases gradually from nano-scale in the surface to micro-scale in the substrate, have shown synergetic strength and ductility. The ...extra strain hardening of GNG materials is considered to result from both geometrically necessary dislocations (GNDs) accommodating nonuniform plastic deformation and superior kinematic hardening characterized by back stress. However, few quantitative investigations were performed to evaluate the contribution of various strengthening mechanisms to the mechanical response of GNG materials. In this work, we develop a multiple-mechanism-based constitutive model, in which constitutive laws for GNDs and back stress at both grain level and sample level are established. Microstructure-based finite element simulation successfully predicts the uniaxial tensile behavior of a GNG interstitial-free (IF) steel sheet. The simulation results demonstrate that GNDs and back stress at sample level have little influence on the strengthening of the GNG IF-steel, while the back stress induced by pileup GNDs contributes about 35% to the flow stress. The uniform elongation of the GNG sample is improved by the constraint of coarse-grained core on GNG layer. This work helps to understand the contributions of deformation mechanisms to the synergetic strength and ductility of GNG materials and to guide the microstructure design and optimization for improved strength-ductility combination.
•A multiple-mechanism-based model is developed to describe the mechanical behavior of GNG materials.•The effects of different mechanisms on the tensile response of GNG are quantitatively evaluated.•The effects of the constraint of the CG core on the GNG layer and back stress improve the ductility of the GNG sample.
•The Fe49.5Mn30Co10Cr10C0.5 (at.%) interstitial high-entropy alloy (iHEA) exhibited a stress level–dependent ratcheting.•The martensitic phase transformation is more significant during cyclic ...deformation than tensile testing.•Hierarchical structures formed by multiple twins and HCP plates promote the cyclic hardening of the iHEA.•A developed crystal plasticity model helped analyze the relationship between the microstructures and the ratcheting.
The development of high-entropy alloys (HEAs) comprising multiple principal components is an innovative design strategy for metallic materials from the perspective of thermodynamic entropy. However, despite their potential candidacy for engineering applications, the lack of research on the cyclic loading responses as well as constitutive modeling of the HEAs is a major constraint. Therefore, the present work focuses on the cyclic plasticity of a typical carbon-doped interstitial HEA (iHEA) with nominal composition Fe49.5Mn30Co10Cr10C0.5 (at.%). The results of stress-controlled cyclic tests with nonzero mean stress showed that the iHEA exhibits significant cyclic hardening and stress level–dependent ratcheting. Owing to its improved cyclic hardening, the saturated ratcheting strain rate of the iHEA is lower than that of conventional steels such as the 316L stainless steel. Furthermore, microscopic characterizations revealed that the cyclic deformations caused massive martensitic phase transformation and hierarchical structures in the iHEA. The experimental results were used to develop a physical mechanism-based crystal plasticity constitutive model that is capable of describing the cyclic plasticity of the iHEA, which was implemented into a finite element framework. The simulation results showed that the loading stress significantly affected the microstructural evolutions, leading to a stress level–dependent cyclic plasticity. Thus, this investigation provides a fundamental basis for fatigue tests and service life prediction/optimization of the iHEA in the future, which can promote its engineering applications.
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Non-intrusive Load Monitoring (NILM) is a critical technology that enables detailed analysis of household energy consumption without requiring individual metering of every appliance, and has the ...capability to provide valuable insights into energy usage behavior, facilitate energy conservation, and optimize load management. Currently, deep learning models have been widely adopted as state-of-the-art approaches for NILM. In this study, we introduce DiffNILM, a novel energy disaggregation framework that utilizes diffusion probabilistic models to distinguish power consumption patterns of individual appliances from aggregated power. Starting from a random Gaussian noise, the target waveform is iteratively reconstructed via a sampler conditioned on the total active power and encoded temporal features. The proposed method is evaluated on two public datasets, REDD and UKDALE. The results demonstrated that DiffNILM outperforms baseline models on several key metrics on both datasets and shows a remarkable ability to effectively recreate complex load signatures. The study highlights the potential of diffusion models to advance the field of NILM and presents a promising approach for future energy disaggregation research.
The capacitor voltage imbalance is a critical issue of five-level diode-clamped converters (5L-DCC). To address this issue, an inner-hexagon-vector-decomposition-based space-vector modulation ...(VDSVM-H1) approach is provided in the literature, which obtains the capacitor voltage balancing with high modulation index and high power factor, but renders some drawbacks. To overcome these shortcomings, a novel capacitor voltage balancing method is proposed here. First, the previous VDSVM-H1 approach is modified by introducing six new vector sequences to each triangle and applying a new vector selection rule such that the converter will not violate the 5L-DCC switching mechanism in all operating conditions. Second, the variation of the line-to-line voltage output in one sampling period is restricted to one- or two-level in the optimized region, instead of the three-level in the previous VDSVM-H1 approach, which means less harmonics generating in the ac-side outputs. Finally, the simulation and experimental results show that the proposed method can improve the VDSVM-H1 with convincing results.
Roles of Microglia in AD Pathology Rong, Gao; Hongrong, Wu; Qingqi, Li ...
Current Alzheimer research,
2023, Volume:
19, Issue:
13
Journal Article
Peer reviewed
Amyloid plaques and neurofibrillary tangles are two main characteristics of Alzheimer's disease (AD). As cerebral resident phagocytes, microglia have different roles in Aβ pathology and tau ...pathology. In this review, we discuss microglial functions in the formation, clearance, and spread of Aβ and tau. Many receptors and enzymes, which are related to microglia, participate in AD pathologies and thus are thought to be potential targets of AD. So, making use of microglia can be beneficial to confine AD pathologies. To sum up, this article review the roles of microglia in AD pathology and possible corresponding treatments.
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