Advanced Electrical Machines and Machine-Based Systems for Electric and Hybrid Vehicles

The paper presents a number of advanced solutions on electric machines and machine-based systems for the powertrain of electric vehicles (EVs). Two types of systems are considered, namely the drive systems designated to the EV propulsion and the power split devices utilized in the popular series-parallel hybrid electric vehicle architecture. After reviewing the main requirements for the electric drive systems, the paper illustrates advanced electric machine topologies, including a stator permanent magnet (stator-PM) motor, a hybrid-excitation motor, a flux memory motor and a redundant motor structure. Then, it illustrates advanced electric drive systems, such as the magnetic-geared in-wheel drive and the integrated starter generator (ISG). Finally, three machine-based implementations of the power split devices are expounded, built up around the dual-rotor PM machine, the dual-stator PM brushless machine and the magnetic-geared dual-rotor machine. As a conclusion, the development trends in the field of electric machines and machine-based systems for EVs are summarized

Direct contact membrane distillation of refining waste stream from precious metal recovery:Chemistry of silica and chromium (III) in membrane scaling

Precious metals, such as platinum group metals (PGMs) with distinct catalytic activity, are widely used as active components in various industrial catalysts. It is, therefore, highly desirable to recover these valuable components from the end-of-life products. We explored treatment of refining wastewater from precious metals recovery using direct contact membrane distillation (DCMD). The role of various initial pH of refining wastewater on DCMD performance was assessed. Results suggested that hydrochloride acid (HCl) and high-quality water can be reclaimed from the real refining wastewater by adjusting initial pH. Furthermore, DCMD water flux decline was mainly caused by silica and chromium (III) scaling, which was dependent on initial pH of refining wastewater. Silica scaling was responsible for the decrease of DCMD performance when the initial pH of refining wastewater increased from original 0.03 to 5 and 7. Silica oligomers in the concentrated feed with various initial pH were identified using mass spectra. Dichlorotetraaquochromiun was identified by X-ray photoelectron spectroscopy and ultraviolet and visible absorbance spectra as the main species contributing to the green colour and scaling on the PTFE membrane surface. Our results suggest that DCMD can be used as a promising and feasible solution for resource recovery from acidic refining waste stream.</p

Tunable plasmon modes in single silver nanowire optical antennas characterized by far-field microscope polarization spectroscopy

Performing far-field microscope polarization spectroscopy and finite element method simulations, we investigated experimentally and theoretically the surface plasmon modes in single Ag nanowire antennas. Our results show that the surface plasmon resonances in the single Ag nanowire antenna can be tuned from the dipole plasmon mode to a higher order plasmon mode, which would result in the emission with different intensities and polarization states, for the semiconductor quantum dots coupled to the nanowire antenna. The fluorescence polarization is changed with different polarized excitation of the 800 nm light beam, while it remains parallel to the Ag nanowire axis at the 400 nm excitation. The 800 nm incident tight interacts nonresonantly with the dipole plasmon mode with the polarized excitation parallel to the Ag nanowire axis, while it excites a higher order plasmon mode with the perpendicular excitation. Under excitation of 400 nm, either the parallel or perpendicular excitation can only result in a dipole plasmon mode. In addition, we demonstrate that the single Ag nanowire antenna can work as an energy concentrator for enhancing the two-photon excited fluorescence of semiconductor quantum dots

A network-state management service

Abstract-We present Statesman, a network-state management service that allows multiple network management applications to operate independently, while maintaining network-wide safety and performance invariants. Network state captures various aspects of the network such as which links are alive and how switches are forwarding traffic. Statesman uses three views of the network state. In observed state, it maintains an up-to-date view of the actual network state. Applications read this state and propose state changes based on their individual goals. Using a model of dependencies among state variables, Statesman merges these proposed states into a target state that is guaranteed to maintain the safety and performance invariants. It then updates the network to the target state. Statesman has been deployed in ten Microsoft Azure datacenters for several months, and three distinct applications have been built on it. We use the experience from this deployment to demonstrate how Statesman enables each application to meet its goals, while maintaining network-wide invariants

Multiparametric MRI radiomics fusion for predicting the response and shrinkage pattern to neoadjuvant chemotherapy in breast cancer

PurposeDuring neoadjuvant chemotherapy (NACT), breast tumor morphological and vascular characteristics are usually changed. This study aimed to evaluate the tumor shrinkage pattern and response to NACT by preoperative multiparametric magnetic resonance imaging (MRI), including dynamic contrast-enhanced MRI (DCE-MRI), diffuse weighted imaging (DWI) and T2 weighted imaging (T2WI).MethodIn this retrospective analysis, female patients with unilateral unifocal primary breast cancer were included for predicting tumor pathologic/clinical response to NACT (n=216, development set, n=151 and validation set, n=65) and for discriminating the tumor concentric shrinkage (CS) pattern from the others (n=193; development set, n=135 and validation set, n=58). Radiomic features (n=102) of first-order statistical, morphological and textural features were calculated on tumors from the multiparametric MRI. Single- and multiparametric image-based features were assessed separately and were further combined to feed into a random forest-based predictive model. The predictive model was trained in the testing set and assessed on the testing dataset with an area under the curve (AUC). Molecular subtype information and radiomic features were fused to enhance the predictive performance.ResultsThe DCE-MRI-based model showed higher performance (AUCs of 0.919, 0.830 and 0.825 for tumor pathologic response, clinical response and tumor shrinkage patterns, respectively) than either the T2WI or the ADC image-based model. An increased prediction performance was achieved by a model with multiparametric MRI radiomic feature fusion.ConclusionsAll these results demonstrated that multiparametric MRI features and their information fusion could be of important clinical value for the preoperative prediction of treatment response and shrinkage pattern

MOF Acetylates the Histone Demethylase LSD1 to Suppress Epithelial-to-Mesenchymal Transition

SummaryThe histone demethylase LSD1 facilitates epithelial-to-mesenchymal transition (EMT) and tumor progression by repressing epithelial marker expression. However, little is known about how its function may be modulated. Here, we report that LSD1 is acetylated in epithelial but not mesenchymal cells. Acetylation of LSD1 reduces its association with nucleosomes, thus increasing histone H3K4 methylation at its target genes and activating transcription. The MOF acetyltransferase interacts with LSD1 and is responsible for its acetylation. MOF is preferentially expressed in epithelial cells and is downregulated by EMT-inducing signals. Expression of exogenous MOF impedes LSD1 binding to epithelial gene promoters and histone demethylation, thereby suppressing EMT and tumor invasion. Conversely, MOF depletion enhances EMT and tumor metastasis. In human cancer, high MOF expression correlates with epithelial markers and a favorable prognosis. These findings provide insight into the regulation of LSD1 and EMT and identify MOF as a critical suppressor of EMT and tumor progression