Dual-Input and Multi-Channel Convolutional Neural Network Model for Vehicle Speed Prediction.

With the development of technology, speed prediction has become an important part of intelligent vehicle control strategies. However, the time-varying and nonlinear nature of vehicle speed increases the complexity and difficulty of prediction. Therefore, a CNN-based neural network architecture with two channel input (DICNN) is proposed in this paper. With two inputs and four channels, DICNN can predict the speed changes in the next 5 s by extracting the temporal information of 10 vehicle signals and the driver's intention. The prediction performances of DICNN are firstly examined. The best RMSE, MAE, ME and R2 are obtained compared with a Markov chain combined with Monte Carlo (MCMC) simulation, a support vector machine (SVM) and a single input CNN (SICNN). Secondly, equivalent fuel consumption minimization strategies (ECMS) combining different vehicle speed prediction methods are constructed. After verification by simulation, the equivalent fuel consumption of the simulation increases by only 4.89% compared with dynamic-programming-based energy management strategy and decreased by 5.40% compared with the speed prediction method with low accuracy.

Energy Management Strategy Based on a Novel Speed Prediction Method.

Vehicle speed prediction can obtain the future driving status of a vehicle in advance, which helps to make better decisions for energy management strategies. We propose a novel deep learning neural network architecture for vehicle speed prediction, called VSNet, by combining convolutional neural network (CNN) and long-short term memory network (LSTM). VSNet adopts a fake image composed of 15 vehicle signals in the past 15 s as model input to predict the vehicle speed in the next 5 s. Different from the traditional series or parallel structure, VSNet is structured with CNN and LSTM in series and then in parallel with two other CNNs of different convolutional kernel sizes. The unique architecture allows for better fitting of highly nonlinear relationships. The prediction performance of VSNet is first examined. The prediction results show a RMSE range of 0.519-2.681 and a R2 range of 0.997-0.929 for the future 5 s. Finally, an energy management strategy combined with VSNet and model predictive control (MPC) is simulated. The equivalent fuel consumption of the simulation increases by only 4.74% compared with DP-based energy management strategy and decreased by 2.82% compared with the speed prediction method with low accuracy.

Numerical Demonstration of 800 Gbps WDM Silicon Photonic Transmitter with Sub-Decibel Surface-Normal Optical Interfaces.

We propose and numerically demonstrate an 800 Gbps silicon photonic transmitter with sub-decibel surface-normal optical interfaces. The silicon photonic transmitter is composed of eight silicon Mach-Zehnder optical modulators and an interleaved AMMI WDM device. This WDM device comprises two 1 × 4 angled MMI and a Mach-Zehnder interferometer (MZI) optical interleaver with an apodized bidirectional grating which has about -0.5 dB coupling loss. Both the Mach-Zehnder electro-optical modulators and MZI optical interleaver regard the bidirectional grating coupler as vertical optical coupler and 3-dB power splitter/combiner. By importing the S-parameter matrices of all the components which have been carefully designed in simulation software, the circuit-level model of the optical transmitter can be built up. On this basis, the static and dynamic performance characterization were carried out numerically. For NRZ modulation, the optical transmitter exhibits the overall optical loss of 4.86-6.72 dB for eight wavelength channels. For PAM4 modulation, the optical loss is about 0.5 dB larger than that of NRZ modulation, which varies between 5.38-7.27 dB. From the eye diagram test results, the WDM silicon photonic transmitter can achieve single channel data transmission at 100 Gb/s NRZ data or 50 GBaud/s PAM4 symbol rate with acceptable bit error rate.

Lysine-specific demethylase 1 induced epithelial-mesenchymal transition and promoted renal fibrosis through Jagged-1/Notch signaling pathway.

OBJECTIVE: TGF-ß1-induced excessive deposition of extracellular matrix (ECM) and epithelial-mesenchymal transition (EMT) process of tubular epithelial cells play critical roles in the progression of renal fibrosis. We are aimed to explore the effects of lysine-specific demethylase 1 (LSD1) in TGF-ß1-treated HK-2 cells and in rats with unilateral ureteral obstruction (UUO), and to investigate the underlying molecular mechanism. METHODS: TGF-ß1-treated HK-2 cells and UUO-treated rats were used to establish the model of renal fibrosis in vitro and in vivo, respectively. Protein expression of LSD1, E-cadherin, a-smooth muscle actin (a-SMA), Vimentin, Jagged-1, Notch-1 and Notch-2 were detected by Western blot. The concentrations of type I collagen (Col-I) and Fibronectin (FN) were measured by ELISA. Transwell assay were used to assess cell invasion. RESULTS: LSD1 was dramatically increased in TGF-ß1-stimulated HK-2 cells. Knockdown of LSD1 decreased the TGF-ß1-induced secretion of Col-I and FN, and suppressed TGF-ß1-induced expression of E-cadherin,α-SMA and Vimentin, while suppressed cell invasion. Consistent with the in vitro data, the severe histopathological damage, collagen deposition and reduced E-cadherin, increased α-SMA induced by UUO was abated by the knockdown of LSD1 in vivo. Moreover, knockdown of LSD1 suppressed TGF-ß1-induced expression of Jagged-1, Notch-1 and Notch-2. Furthermore, we found that inhibition of Notch signaling by a γ-secretase inhibitor RO4929097 almost recapitulated the effects of LSD1 knockdown in TGF-ß1-induced HK-2 cells, and at least in part reversed the effects of LSD1 overexpression on EMT and ECM deposition in HK-2 cells. CONCLUSIONS: Taken together, LSD1 significantly impact on the progression of TGF-ß1-mediated EMT and ECM deposition in HK-2 cells, and it may represent novel target for the prevention strategies of renal fibrosis.

[Point application in literature of Dunhuang stone chamber and its application].

Acupuncture-moxibustion material found in Dunhuang stone chamber shows academic value on research of acupuncture-moxibustion in Tang Dynasty and before. In the paper we summarize its medical prescriptions and the existing acupoint application contents. It is considered that its acupoint application is widely clinically used in dermatological department, cosmetology department, ophthalmology and otorhinolaryngology departments, paediatrics department, gynaecology department, anorectal department, orthopedics and traumatology department. It achieves remarkable effects in dermatological department, orthopedics and traumatology department. Medical literature of Dunhuang is a treasure of TCM with distinctive feature and it deserves to be further explored so as to serve the clinic and promote the inheritance and development of Dunhuang medicine, such as finding out high effect prescription.

[Brief introduction of ZHENG's "golden hook fishing" technique in acupuncture].

Golden hook fishing technique in acupuncture is one of the characteristics for the inheritance of aca-demic school of ZHENG's acupuncture technique. On the theoretic basis of traditional "lifting and thrusting" technique and "biting hook" sensation, by the coordination of the hands, focusing on the gentle lifting and shaking technique, selecting ashi points, the tendon-knotted sites, the eight influential points and experienced effective points, this special acupuncture technique is used for acute pain disorders and brain disorders in clinical application.

[Modern research progress regarding effect mechanism of acupuncture on post-traumatic stress disorder].

From the TCM theoretical basis and the evidences of acupoint selection and acupuncture and moxibustion methods regarding acupuncture for post-traumatic stress disorder (PTSD), a theoretical discussion is made in this article, also a review regarding the key mechanism of experiment researches on acupuncture for PTSD is made from aspects of neurobiology and brain functional imaging, etc., which could further clarify the effect mechanism of acupuncture on PTSD. It is found that PTSD is a kind of stress syndrome accompanied with a variety of abnormal mental symptom , and acupuncture has superior effect on PTSD. Based on these, the research progress and deficiency on current mechanism study of PTSD are reviewed, hoping to offer ideas for upcoming research and to serve the clinical practice better.