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Preoperative anxiety is common and often comes with a higher probability of worse recovery. However, the neurological mechanism of the effect of preoperative anxiety on general anesthesia and subsequent awakening remains unknown. In this study, we report an anxious state results in delayed awakening in anxiety model mice from sevoflurane general anesthesia. More profound inhibition of DA neurons in the VTA contributes to delayed awakening. Optogenetic stimulation of VTA DA neurons can reverse the delay. The results indicate that VTA DA neurons may be involved in the delay in awakening from general anesthesia caused by anxiety.

This paper examines choice behaviors pertaining to the time at which users of plug-in hybrid electric vehicle with 24 km electric range charge their vehicles after arriving at home under a dynamic electricity pricing scheme. The following mutually exclusive alternatives are presented: no charging, charging immediately after arriving at home, charging at the cheapest time, and charging at other times. Four versions of a mixed logit model with unobserved heterogeneity are applied to panel data on vehicle usage from 9 households with 2226 observations in Toyota City. Estimation results suggest that users’ willingness to charge become stronger with increasing driving distance when the driving distance is less than the electric range of 24 km, while tend not to charge when the driving distance is longer than the electric range. Users who return home at the cheapest time or during the day are willing to charge immediately after arriving at home. Electricity prices significantly affect choices to charge at the cheapest time for all users, and stay-at-home mother users and users returning home in the evening tend to charge at the cheapest time. Users returning home in the evening also tend to charge at other times, and being accustomed to charge at a certain time increases the probability of charging at other times. In addition, considerable variations are found across individuals with respect to their preferences for charge timing alternatives as well as for electricity prices.

Diabetic cardiomyopathy (DCM) is one of the chief diabetes mellitus complications. Inflammation factors may be one reason for the damage from DM. The purpose of this research is to study the potential protective effects of puerarin on DM and the possible mechanisms of action related to NF-κB signal pathway. Following administration of puerarin to the disease model rat, several changes were observed including the changes of serum biochemical index, improved diastolic dysfunction, and enhanced endogenous antioxidant enzymes activities, further NF-κB signaling activation. Puerarin showed cardio-protective effects on DCM by inhibiting inflammation, and it might be a potential candidate for the treatment of DCM.

Objectives This study is designed to investigate the effects and mechanisms of sinomenine (Sin) in stress load-induced heart failure in mice. Methods We used aortic constriction (AB) to cause pressure overload as our heart failure model. Sin was received in mice as the treatment group. Cardiac function and structural changes were detected using echocardiography. Heart–lung mass ratios were measured. The serum levels of IL-10 and IL-17 proteins were detected by using ELISA, cardiac hypertrophy markers atrial natriuretic peptide (ANP), myocardial I and III collagen mRNA levels were detected by RT-PCR. Myocardial type I and III collagen protein levels were detected by Western blotting. Key findings Sin significantly improved stress load-induced heart failure (P < 0.05), reduced the heart–lung mass ratio, ANP, collagen-I and -III mRNA and protein levels (P < 0.05); Sin can enhance the ratio of IL-10/IL-17. Conclusion Sin may be a promising drug target to improve heart failure. Its role is related to reduce serum ANP levels, inhibit the mRNA and protein level of type I and III collagen and enhance the ratio of IL-10/IL-17.

This study explores how battery electric vehicle users choose where to fast-charge their vehicles from a set of charging stations, as well as the distance by which they are generally willing to detour for fast-charging. The focus is on fast-charging events during trips that include just one fast-charge between origin and destination in Kanagawa Prefecture, Japan. Mixed logit models with and without a threshold effect for detour distance are applied to panel data extracted from a two-year field trial on battery electric vehicle usage in Japan. Findings from the mixed logit model with threshold show that private users are generally willing to detour up to about 1750 m on working days and 750 m on non-working days, while the distance is 500 m for commercial users on both working and non-working days. Users in general prefer to charge at stations requiring a shorter detour and use chargers located at gas stations, and are significantly affected by the remaining charge. Commercial users prefer to charge at stations encountered earlier along their paths, while only private users traveling on working days show such preference and they turn to prefer the stations encountered later when choosing a station in peak hours. Only private users traveling on working days show a strong preference for free charging. Commercial users tend to pay for charging at a station within 500 m detour distance. The fast charging station choice behavior is heterogeneous among users. These findings provide a basis for early planning of a public fast charging infrastructure.

This paper aims to examine choice behavior in respect of the time at which battery electric vehicle users charge their vehicles. The focus is on normal charging after the last trip of the day, and the alternatives presented are no charging, charging immediately after arrival, nighttime charging, and charging at other times. A mixed logit model with unobserved heterogeneity is applied to panel data extracted from a two-year field trial on battery electric vehicle usage in Japan. Estimation results, obtained using separate models for commercial and private vehicles, suggest that state of charge, interval in days before the next travel day, and vehicle-kilometers to be traveled on the next travel day are the main predictors for whether a user charges the vehicle or not, that the experience of fast charging negatively affects normal charging, and that users tend to charge during the nighttime in the latter half of the trial. On the other hand, the probability of normal charging after the last trip of a working day is increased for commercial vehicles, while is decreased for private vehicles. Commercial vehicles tend not to be charged when they arrival during the nighttime, while private vehicles tend to be charged immediately. Further, the correlations of nighttime charging with charging immediately and charging at other times reveal that it may be possible to encourage charging during off-peak hours to lessen the load on the electricity grid. This finding is supported by the high variance for the alternative of nighttime charging.

This study aims to explore how factors including charging infrastructure and battery technology associate the way people currently charge their battery electric vehicles, as well as to explore whether good use of battery capacity can be encouraged. Using a stochastic frontier model applied to panel data obtained in a field trial on battery electric vehicle usage in Japan, the remaining charge when mid-trip fast charging begins is treated as a dependent variable. The estimation results obtained using four models, for commercial and private vehicles, respectively, on working and non-working days, show that remaining charge is associated with number of charging stations, familiarity with charging stations, usage of air-conditioning or heater, battery capacity, number of trips, Vehicle Miles of Travel, paid charging. However, the associated factors are not identical for the four models. In general, EVs with high-capacity batteries are initiated at higher remaining charge, and so are the mid-trip fast charging events in the latter period of this trial. The estimation results also show that there are great opportunities to encourage more efficient charging behavior. It appears that the stochastic frontier modeling method is an effective way to model the remaining charge at which fast-charging should be initiated, since it incorporates trip and vehicle characteristics into the estimation process to some extent.

The deflectable nose missile has a longer range by deflecting its nose to improve its aerodynamic feature. Based on detached eddy simulation (DES), the supersonic flow fields of a missile with deflectable nose are simulated numerically and its aerodynamic force coefficients are calculated under the condition of the deflection angles vary from 0° to 8°, angles of attack, 0°–8°, and mach numbers, 2 to 5. Coupling these aerodynamic coefficients with the plumb plane ballistic equations, the extended flight range has been calculated. Furthermore, the genetic algorithm (GA) is employed for the solution of maximum range of the deflected missile.

Low similarity and unreasonable design now appeared in distracters generation of English words in the process of learning English words. This paper proposed a new algorithm to solve this problem by researching Edit Distance and LCS algorithm. Comparing with traditional algorithms, the accuracy of similarity has been improved in this algorithm. Finally, combined with words’ part of speech, we generated more reasonable distracters in the experiments.

Bidirectional maximum matching algorithm (BMM) combined positive maximal matching and reverse maximal matching algorithm, it was a more commonly used word segmentation method now, but it was low efficient and couldn’t solve the ambiguity. Therefore, an improved method was proposed combining with improved dictionary structure, and changing maximal matching word length dynamically to improve the efficiency of word segmentation. In order to get the correct segmentation results, we also proposed several rules. Compared with traditional segmentation methods, it proves that bidirectional maximal matching word segmentation with rules has higher speed and precision.

In previous work, a method to compensate the divergence between the distributions of natural and generated modulation spectra (MS) has been proposed for hidden Markov model (HMM) based speech synthesis. This method can alleviate the over-smoothing effect of parameter generation when mel-cepstral coefficients (MCC) are used as spectral features. This paper further investigates the MS compensation method for line spectral pairs (LSP). Four approaches to extract MS from LSPs are implemented and compared. These approaches calculate MS vectors using original LSP sequences, log power spectra (LPS) derived from LSPs, MCCs derived from LSPs, and MCCs derived from speech waveforms, respectively. Experimental results show that the naturalness of synthetic speech gets improved after MS compensation when LSPs are used as spectral features for HMM modeling. The degree of improvement depends on the type of spectral features for MS calculation significantly. MCCs derived from LSPs are more suitable for MS compensation than original LSPs and LPS derived from LSPs. Besides, using MCCs derived from speech waveforms also achieves satisfactory performance. This means that MS compensation can also be implemented as a post-filter to synthetic waveforms which does not rely on the type of spectral features and vocoders adopted in the synthesis system.

Objective To compare the effect of zoledronic acid in treatment and prevention of osteoporosis with placebo. Methods Random control trials regarding zoledronic acid in treatment of osteoporosis were retrieved by selecting Medline, EMbase and Pubmed databases till April 2012. The RevMan software was used for all of the statistical analysis. Results A total of 9 trials were included in this meta-analysis. The pooled effect showed that zoledronic acid could increase the bone mineral density by 2.98 times compared with placebo, and reduce the rate of fracture in patients by 32%. The results should the zoledronic acid intervention had significantly less serious adverse events than controls, and the odds ratio was 0.81 (0.76–0.87). The longer term intervention, more than 12 months intervention, could gain a better prevention effect for osteoporosis (OR, 95% CI for BMD was 3.35, 2.77–3.92; for fracture was 0.67, 0.54–0.82). Conclusions This present study shows that zoledronic acid could be effective approach in the prevention of osteoporosis, and could increase the bone mineral density and reduce the risk of facture.

Background Hyperplastic disease of the breast (HDB) is caused by a hormone imbalance experienced among women at a certain age. Slight breast pain is common in women before menstruation without need of treatment; however, if the pain becomes severe, it can cause physical and mental suffering. Therefore, it is of great clinical significance to control this disease. Methods and design This study will follow the principle of evidence-based medicine and adopt various design methods, being conducted as a randomized, controlled, double-blind and multicenter trial based on the cause of HDB defined in Chinese and Western medicine. According to the cause of HDB in Chinese and Western medicine and its pathogenesis and prognosis, this study will conduct syndrome differentiation, adopt external therapy of Chinese medicine by using Sanjie Zhitong plaster as the intervention, take placebo as the control method and aim at relieving pain. The effectiveness and safety of Chinese medicine therapy will be evaluated. During the design process, some confounding factors will be taken into consideration and prevented with corresponding measures. We will also discuss the side effects of the medicine used and corresponding countermeasures to be taken. Discussion On the basis of traditional Chinese medicine (TCM) theory, Sanjie Zhitong plaster takes the advantage of external therapy of TCM. According to the main etiology and pathogenesis of HDB, the treatment principles of warming the meridians and activating blood, smoothing circulation and relieving pain, and removing swelling and dissipating stagnation are put forward. The medicine exerts its effects directly on the lesion site by permeating into the skin and stimulating the meridians, thus improving blood supply to the breast and relieving pain.

With energy and environmental issues outstanding, electric vehicles have got much room for developments, which also brings a lot of security risks different from the traditional internal combustion engine vehicle such as the electrolyte spillage; toxic fumes; electric shock and so on. This paper simulates the progress of a electric bus side collision with LS-DYNA, and analyzes its security mainly from aspects of the electrical injury and electrochemical injury: internal short-circuit occurs in battery monomer, external short-circuit outside the battery pack occurs or even cause a fire, BMS, fast fuse and other electronic components with too large deformation in a collision will lose its ability of monitoring external short-circuit of battery pack. Meanwhile, we analyze reasons for the three phenomena above and propose measures for improvement, fix methods and structure of the weak components in collision zone have been improved. Then this paper verifies vehicle security after improvement reducing the electrical injury and electrochemical injury the vehicle on passengers.

The study on the tailings’ comprehensive utilization is mainly concentrated in minerals in the past, which means we need to use all kinds of research methods and results that we use in the mineralogy nowadays. Maybe we can break away from the research bondage of the modern mineral technology, tracing back to the genesis of the mineral deposits from the genesis of mineral formation, especially some sedimentary deposits, which we can call “natural metallurgical field,” so that we can probably get some new technologies and methods of the tailings’ comprehensive utilization. On the other hand, after re-understanding of the varieties of deposit types and the occurrence states of metal elements, we can select the corresponding technology to recover associated components according to different types of deposits tailings, which will maximize the recovery rate of associated components.

As a neural network provides a non-linear function mapping from input variables to the corresponding network output, without the requirements of having to specify the relation between the input and output variables in the form of mathematical formula, its widely used in modeling for complex non-linear phenomena. In this paper, generalized regression neural network (GRNN) is applied as a new type of model to forecast the red tide. Moreover, experiments with red tide data samples are performed in order to examine the usefulness of the method. Compared with the radial basis function (RBF) neural network, the experimental results are also analyzed.