Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm

Reverberation, which is generally caused by sound reflections from walls, ceilings, and floors, can result in severe performance degradation of acoustic applications. Due to a complicated combination of attenuation and time-delay effects, the reverberation property is difficult to characterize, and it remains a challenging task to effectively retrieve the anechoic speech signals from reverberation ones. In the present study, we proposed a novel integrated deep and ensemble learning algorithm (IDEA) for speech dereverberation. The IDEA consists of offline and online phases. In the offline phase, we train multiple dereverberation models, each aiming to precisely dereverb speech signals in a particular acoustic environment; then a unified fusion function is estimated that aims to integrate the information of multiple dereverberation models. In the online phase, an input utterance is first processed by each of the dereverberation models. The outputs of all models are integrated accordingly to generate the final anechoic signal. We evaluated the IDEA on designed acoustic environments, including both matched and mismatched conditions of the training and testing data. Experimental results confirm that the proposed IDEA outperforms single deep-neural-network-based dereverberation model with the same model architecture and training data

Why did some firms perform better in the global financial crisis?

We explore what firm and macroeconomic factors assisted Chinese firms to resist the global financial crisis. We find that firms with higher top ten shareholder ratios or firms that are older exhibited saliently higher performance during the crisis, but performed poorly during the non-crisis period. Firm size has a notably negative impact on firm performance. Firms audited by the Big Four accounting firms have a significantly negative correlation with performance. During the crisis, stock markets became less efficient in incorporating firm-specific information into stock prices, signifying that the determinants of firm performance vary across non-crisis and crisis periods

In Situ Monitoring of Temperature inside Lithium-Ion Batteries by Flexible Micro Temperature Sensors

Lithium-ion secondary batteries are commonly used in electric vehicles, smart phones, personal digital assistants (PDA), notebooks and electric cars. These lithium-ion secondary batteries must charge and discharge rapidly, causing the interior temperature to rise quickly, raising a safety issue. Over-charging results in an unstable voltage and current, causing potential safety problems, such as thermal runaways and explosions. Thus, a micro flexible temperature sensor for the in in-situ monitoring of temperature inside a lithium-ion secondary battery must be developed. In this work, flexible micro temperature sensors were integrated into a lithium-ion secondary battery using the micro-electro-mechanical systems (MEMS) process for monitoring temperature in situ

Paxillin facilitates timely neurite initiation on soft-substrate environments by interacting with the endocytic machinery.

Neurite initiation is the first step in neuronal development and occurs spontaneously in soft tissue environments. Although the mechanisms regulating the morphology of migratory cells on rigid substrates in cell culture are widely known, how soft environments modulate neurite initiation remains elusive. Using hydrogel cultures, pharmacologic inhibition, and genetic approaches, we reveal that paxillin-linked endocytosis and adhesion are components of a bistable switch controlling neurite initiation in a substrate modulus-dependent manner. On soft substrates, most paxillin binds to endocytic factors and facilitates vesicle invagination, elevating neuritogenic Rac1 activity and expression of genes encoding the endocytic machinery. By contrast, on rigid substrates, cells develop extensive adhesions, increase RhoA activity and sequester paxillin from the endocytic machinery, thereby delaying neurite initiation. Our results highlight paxillin as a core molecule in substrate modulus-controlled morphogenesis and define a mechanism whereby neuronal cells respond to environments exhibiting varying mechanical properties

Hyperbaric oxygen suppressed tumor progression through the improvement of tumor hypoxia and induction of tumor apoptosis in A549-cell-transferred lung cancer

Tumor cells have long been recognized as a relative contraindication to hyperbaric oxygen treatment (HBOT) since HBOT might enhance progressive cancer growth. However, in an oxygen deficit condition, tumor cells are more progressive and can be metastatic. HBOT increasing in oxygen partial pressure may benefit tumor suppression. In this study, we investigated the effects of HBOT on solid tumors, such as lung cancer. Non-small cell human lung carcinoma A549-cell-transferred severe combined immunodeficiency mice (SCID) mice were selected as an in vivo model to detect the potential mechanism of HBOT in lung tumors. HBOT not only improved tumor hypoxia but also suppressed tumor growth in murine xenograft tumor models. Platelet endothelial cell adhesion molecule (PECAM-1/CD31) was significantly increased after HBOT. Immunostaining of cleaved caspase-3 was demonstrated and apoptotic tumor cells with nuclear debris were aggregated starting on the 14th-day after HBOT. In vitro, HBOT suppressed the growth of A549 cells in a time-dependent manner and immediately downregulated the expression of p53 protein after HBOT in A549 cells. Furthermore, HBOT-reduced p53 protein could be rescued by a proteasome degradation inhibitor, but not an autophagy inhibitor in A549 cells. Our results demonstrated that HBOT improved tissue angiogenesis, tumor hypoxia and increased tumor apoptosis to lung cancer cells in murine xenograft tumor models, through modifying the tumor hypoxic microenvironment. HBOT will merit further cancer therapy as an adjuvant treatment for solid tumors, such as lung cancer

Evolution of superconductivity in K2-xFe4+ySe5: Spectroscopic studies of X-ray absorption and emission.

This study investigates the evolution of superconductivity in K2-xFe4+ySe5 using temperature-dependent X-ray absorption and resonant inelastic X-ray scattering techniques. Magnetization measurements show that polycrystalline superconducting (SC) K1.9Fe4.2Se5 has a critical temperature (T c) of ∼31 K with a varying superconducting volume fraction, which strongly depends on its synthesis temperature. An increase in Fe-structural/vacancy disorder in SC samples with more Fe atoms occupying vacant 4d sites is found to be closely related to the decrease in the spin magnetic moment of Fe. Moreover, the nearest-neighbor Fe-Se bond length in SC samples exceeds that in the non-SC (NS) sample, K2Fe4Se5, which indicates a weaker hybridization between the Fe 3d and Se 4p states in SC samples. These results clearly demonstrate the correlations among the local electronic and atomic structures and the magnetic properties of K2-xFe4+ySe5 superconductors, providing deeper insight into the electron pairing mechanisms of superconductivity

Measuring the Quality of Financial Electronic Payment System: Combined with Fuzzy AHP and Fuzzy TOPSIS

The study aims to apply Fuzzy AHP in TOPSIS to discuss the key factors that foster the success of current third-party online payment platforms. This study organized the quality measurements into four categories and eleven sub-categories. The AHP in TOPSIS is applied to calculate the weighted averages of all categories and sub-categories to measure the quality of third-party online payment platforms. This study finds that “safety quality” is the most emphasized category, “system quality” is the second, “communication quality” is the third, and “service quality” is the least emphasized

Theoretical Study of High Performance Germanium Nanowire Quantum Dot

In this report, we demonstrate that Ge-NWQD (nanowire quantum dots) at low temperatures exhibit apparent Coulomb oscillations than that in Si-NWQD. These oscillations gradually disappear as the temperature increases, indicating the influence of phonon scattering. The increase in Coulomb oscillations enables the device to exhibit multi-level characteristics at low voltage in quantum flash, and the lower barrier high and high mobility of Ge make it advantageous for increasing the storage capacity of quantum flash devices. This research provides design guidelines for optimization of high-performance quantum flash devices.Comment: 2pages,5figures,Silicon Nanoelectronics Workshop 2023(SNW