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The novel contribution of this paper is to develop a quadratic perturbation method to derive general analytical buckling load formulas for cylindrical shell structures with varying wall thickness under non-uniform lateral pressure loads for the first time. Arbitrary thickness and lateral pressure loads are skillfully described and governing differential equations are derived. A quadratic perturbation method is developed to derive buckling load formulas, which establishes the relation among buckling loads, thickness, and load functions. The presented formulas are adequately validated by comparing with recent results for variable wall thickness or non-uniform external pressure, and exhibit a great advantage in determining buckling loads. For the purpose of engineering application, buckling of a cylinder with linear thickness under linear liquid pressure and wind load is deeply studied by the presented formulas. This study can provide a highly efficient method for buckling load computation, and a guide to design the thickness of the shell under non-uniform lateral loads.

The novelty of this paper is to propose exact three-dimensional analytical solutions to the half infinite thermo-elastic body pressed by a rigid cylindrical structure for the first time, in which uniform heat flux flowing from rigid structure into the half infinite body is considered. Using recent general solutions expressed by four harmonic functions and extending potential theory method to consider heat effect, the governing integral equations are first derived. Then, the equations are analytically solved and displacement, stress, and temperature field components expressed by elementary functions are obtained. To validate the presented solutions, the correctness of the solutions is exactly examined, and normal contact displacement and stress without heat effect are compared with those in literatures. Furthermore, a numerical example which is the stainless steel thermo-elastic body pressed by a displacement restrictor is studied. Displacement, stress, and temperature distributions are analyzed, and the influence of heat flux on the pressed depth is also discussed in detail. The analytical solutions presented in this paper are rather important in engineering practice and can provide a basis for indentation analysis, displacement restrictor design, foundation settlement calculation, and so on.

This paper analytically studies the buckling of a cylindrical shell having varying thickness under non-uniform axial compressive loads for the first time, which widely exists in engineering practice. A novel quadratic perturbation technique is developed to establish general buckling load formulas for the shell. This method overcomes the difficulties of traditional energy methods in solving high order determinants and deriving direct expressions for buckling loads when shell thickness and axial load are unknown. Applying presented formulas, various shell thicknesses and axial loads are analyzed, and a series of new results for buckling loads are obtained and validated. Even for classical cosine thickness variation under uniform axial compression, we also give general conclusions compared with Koiter’s results by the energy method. The effects of thickness variations and load distribution parameters on buckling loads are analyzed in detail. The presented study in this paper fills the gap and establishes a foundation of buckling analysis for non-uniformly loading cylindrical shells with variable thickness. Certainly, the established formulas are general and available for buckling resistance capacity evaluation for the shells under all circumstances involving thickness variations or/and non-uniform axial compressive loads.

Depression is a leading cause of disability worldwide, and objective biomarkers are required for future computer-aided diagnosis. This study aims to assess the variation of frontal alpha complexity among different severity depression patients and healthy subjects, therefore to explore the depressed neuronal activity and to suggest valid biomarkers. 69 depression patients (divided into three groups according to the disease severity) and 14 healthy subjects were employed to collect 3-channel resting Electroencephalogram signals. Sample entropy and Lempel–Ziv complexity methods were employed to evaluate the Electroencephalogram complexity among different severity depression groups and healthy group. Kruskal–Wallis rank test and group t-test were performed to test the difference significance among four groups and between each two groups separately. All indexes values show that depression patients have significantly increased complexity compared to healthy subjects, and furthermore, the complexity keeps increasing as the depression deepens. Sample entropy measures exhibit superiority in distinguishing mild depression from healthy group with significant difference even between nondepressive state group and healthy group. The results confirm the altered neuronal activity influenced by depression severity and suggest sample entropy and Lempel–Ziv complexity as promising biomarkers in future depression evaluation and diagnosis.

Exploring efficient control strategies for heterogeneously congested urban networks remains a big research challenge. The theory of macroscopic fundamental diagram (MFD) provides a new perspective for network-wide congestion control decisions. This paper proposes a coordinated perimeter control strategy for multiregion heterogeneous networks based on optimized transfer flows. First, a two-layer network partitioning method is presented to capture spatial heterogeneity dynamics of urban networks. For this partition, traffic flow equilibrium model based on MFD and multiagent based hierarchical traffic management scheme are built. Then, an improved multinomial logit model is developed for deriving optimized transfer flows among multiple congested regions. A coordinated perimeter control strategy using model predictive control is further proposed, which is aimed at tracking desired accumulations of each congested region. As a case study, the proposed control strategy is applied to the downtown network of Jinan, China, using simulation analysis. The results demonstrate that it can achieve balanced network flow distribution and increased mobility.

Reasonable traffic network model and flexible traffic control strategy play important roles in improving the urban traffic control efficiency. Introducing granular computing theory into traffic network modeling and traffic control is a useful attempt, since granular computing is closer to the human thinking in solving problems. In this paper, the traffic elements are depicted using S-rough set to achieve the granulation partition of traffic network. Four layers are partitioned in the proposed hierarchical multigranularity traffic network model, such as vehicle layer, platoon layer, segment and intersection layer, and subregion layer. Each traffic granule is represented in rough representation form, and the dynamic characteristics are described using the elementary transfer operations based on S-rough set theory. As an application on the proposed traffic network model, an extended max-pressure traffic control strategy is applied on the platoon and segment and intersection layer. Simulation results illustrate that the proposed traffic network model and traffic control strategy achieve better performance.

The car-following model is an important micro-traffic model for simulating car-following behaviour in traffic engineering and research studies. Conventional car-following models are always presented using mathematical equations reflecting ideal traffic conditions. In the big data era, data-driven models become a popular trend. In this study, a data-driven car-following model based on the rough set theory is proposed to consider information hidden in a field data set. On the basis of field data obtained from measurement devices such as the next generation simulation (NGSIM) trajectory data set, and using the methods of the rough set theory, an optimal decision rule set is established. Redundant attributes and redundant attribute values are removed for simplifying the car-following behaviour decision problem. Attribute significance and weights are computed for selecting matching rules. A car-following behaviour decision algorithm is designed to choose appropriate rules to determine the follower's velocity according to current observations. Simulations illustrate that the proposed data-driven car-following model can simulate the micro-traffic behaviour of followers well.

This paper presents an analytical study on thermal buckling of cylindrical shells with non-uniform thickness, which is common in engineering practice. Firstly, the shell thickness is assumed to be arbitrary in the axial direction. After solving the basic partial differential equations by the perturbation method, buckling temperature and modes in terms of thickness function and geometric sizes of the shell are obtained. Using the presented formulas, this paper deeply analyzes and discusses cosine distributed and stepwise thicknesses. For simple cosine distributed thickness, the classical Galerkin method is applied to derive buckling temperature factors, while stepwise thickness is verified by the finite difference method. Results from the Galerkin method and the finite difference method are in accordance with those by presented formulas in this paper. Furthermore, the influence of parameters in thickness functions and buckling modes on buckling temperature factors is discussed, and some interesting conclusions are drawn. The presented buckling temperature formulas can be applied to evaluate stability capacity of the cylinder used in thermal environment.

Recent studies have indicated that physiological parameters change with different emotion states. This study aimed to quantify the changes of vascular function at different emotion and sub-emotion states. Twenty young subjects were studied with their finger photoplethysmographic (PPG) pulses recorded at three distinct emotion states: natural (1 minute), happiness and sadness (10 minutes for each). Within the period of happiness and sadness emotion states, two sub-emotion states (calmness and outburst) were identified with the synchronously recorded videos. Reflection index (RI) and stiffness index (SI), two widely used indices of vascular function, were derived from the PPG pulses to quantify their differences between three emotion states, as well as between two sub-emotion states. The results showed that, when compared with the natural emotion, RI and SI decreased in both happiness and sadness emotions. The decreases in RI were significant for both happiness and sadness emotions (both P< 0.01), but the decreases in SI was only significant for sadness emotion (P< 0.01). Moreover, for comparing happiness and sadness emotions, there was significant difference in RI (P< 0.01), but not in SI (P= 0.9). In addition, significant larger RI values were observed with the outburst sub-emotion in comparison with the calmness one for both happiness and sadness emotions (both P< 0.01) whereas significant larger SI values were observed with the outburst sub-emotion only in sadness emotion (P< 0.05). Moreover, gender factor hardly influence the RI and SI results for all three emotion measurements. This pilot study confirmed that vascular function changes with diffenrt emotion states could be quantified by the simple PPG measurement.

This pilot study investigated the differences of heart rate variability (HRV) indices between two opposite emotion states: happiness and sadness, to reveal the differences of autonomic nervous system activity under different emotional states. Forty-eight healthy volunteers were enrolled for this study. Electrocardiography (ECG) signals were recorded under both emotion states with a random measurement order (first happiness emotion measurement then sadness or reverse). RR interval (RRI) time series were extracted from ECGs and multiple HRV indices, including time-domain (MEAN, SDNN, RMSSD and PNN50), frequency-domain (LFn, HFn and LF/HF) and nonlinear indices (SampEn and FuzzyMEn) were calculated. In addition, the effects of heart rate (HR) and mean artery pressure (MAP) on the aforementioned HRV indices were analyzed for both emotion states. The results showed that experimental order had no significant effect on all HRV indices from both happiness and sadness emotions (all P > 0.05). The key result was that among all nine HRV indices, six indices were identified having significant differences between happiness and sadness emotion states: MEAN (P = 0.028), SDNN (P = 0.002), three frequency-domain indices (all P < 0.0001) and FuzzyMEn (P = 0.047), whereas RMSSD, PNN50 and SampEn had no significant differences between the two emotion states. All indices, except for SampEn, had significant positive correlations (all P < 0.01) for the two emotion states. Four time-domain indices decreased with the increase of HR (all P < 0.01), while frequency-domain and nonlinear indices demonstrated no HR-related changes for each emotional state. In addition, all indices (time-domain, frequency-domain and nonlinear) showed no MAP-related changes. It concluded that HRV indices showed significant differences between happiness and sadness emotion states and the findings could help to better understand the inherent differences of cardiovascular time series between different emotion states in clinical practice.

AimsThis study used entropy- and cross entropy-based methods to explore the cardiorespiratory coupling of depressive patients, and thus to assess the values of those entropy methods for identifying depression patients with different disease severities.MethodsElectrocardiogram (ECG) and respiration signals from 69 depression patients were recorded simultaneously for 5 min. Patients were classified into three groups according to the Hamilton Depression Rating Scale (HDRS) scores: group Non-De (HDRS 0–7), Mid-De (HDRS 8–17), and Con-De (HDRS >17). Sample entropy (SEn), fuzzy measure entropy (FMEn) and high-frequency power (HF) were computed on the original RR interval time series and breath-to-breath interval time series. Cross sample entropy (CSEn) and cross fuzzy measure entropy (CFMEn) were computed on interval time series resampled at 2 Hz and 4 Hz, respectively. The difference among three patient groups and correlation between entropy values and HDRS scores were analyzed by statistical analysis. Surrogate data were also employed to confirm the validation of entropy measures in this study.ResultsA consistent increasing trend has been found among most entropy measures from Non-De, to Mid-De, and to Con-De groups, and a significant (p < 0.05) difference in FMEn of RR intervals exists between Non-De and Mid-De or Con-De groups. Significant differences have been also found in all cross entropies, between Non-De and Con-De groups and between Mid-De and Con-De groups. Furthermore, significant correlations also exist between HDRS scores and FMEn of RR intervals (R = 0.24, p < 0.05), CSEn at 4 Hz (R = 0.26, p < 0.05) or 2 Hz (R = 0.28, p < 0.05) resampling, and CFMEn at 4 Hz (R = 0.31, p < 0.01) or 2 Hz (R = 0.30, p < 0.05) resampling. A significant difference of cardiorespiratory coupling parameters between different depression stages and significant correlations between entropy measures and depression severity both indicate central autonomic dysregulation in depression patients and reflect varying degrees of vagal modulation reduction among different depression levels. Analysis based on surrogate data confirms that the non-linear properties of the physiological signals played a major role in depression recognition.ConclusionThe current study demonstrates the potential of cardiorespiratory coupling in the auxiliary diagnosis of depression based on the entropy method.

On the foundation of the original backpressure-based traffic light control algorithm, a distributed cooperative backpressure-based traffic light control method is proposed in this paper. The urban traffic network is modeled as a smart agent-controlled queuing network, in which the intersection agents exchange the queue length information and the selected activating light phase information of neighboring intersections through communications and determine the activating light phase at each time slot according to local traffic information. The improved phase pressure computation method considers the phase state of downstream intersections instead of only the queue length of the local intersections. Light phase switching coordination among adjacent intersections is achieved using the consensus-based bundle algorithm, in which the cooperative light phase switching problem is viewed as a task assignment issue among adjacent intersections. Simulation results illustrated that the proposed cooperative backpressure-based traffic light control method obtained better performance than the original backpressure-based and fixed-time traffic control methods.

Podocytes, dynamic polarized cells wrapped around glomerular capillaries, are an essential component of the glomerular filtration barrier. BK channels consist of one of the slit diaphragm (SD) proteins in podocytes, interact with the actin cytoskeleton, and play vital roles in glomerular filtration. Mechanistic target of rapamycin (mTOR) complexes regulate expression of SD proteins, as well as cytoskeleton structure, in podocytes. However, whether mTOR complexes regulate podocyte BK channels is still unclear. Here, we investigated the mechanism of mTOR complex regulation of BK channels via real-time PCR, western blot, immunofluorescence, and patch clamping. Inhibiting mTORC1 with rapamycin or downregulating Raptor had no significant effect on BK channel mRNA and protein levels and bioactivity. However, the dual inhibitor of mTORC1 and mTORC2 AZD8055 and short hairpin RNA targeting Rictor downregulated BK channel mRNA and protein levels and bioactivity. In addition, MK2206, GF109203X, and GSK650394, which are inhibitors of Akt, PKCα, and SGK1, respectively, were employed to test the downstream signaling pathway of mTORC2. MK2206 and GF109203X had no effect on BK channel protein levels. MK2206 caused an obvious decrease in the current density of the BK channels. Moreover, GSK650394 downregulated the BK channel protein and mRNA levels. These results indicate mTORC2 not only regulates the distribution of BK channels through Akt, but also modulates BK channel protein expression via SGK1 in podocytes.

This paper presents an analytical study on the buckling of cylindrical shells under arbitrarily distributed axial loads. It has three main innovation points. First, different from the previous studies, the axial loads need not be assumed to be specific forms beforehand and be simple ones such as cosine type, which are arbitrary in this paper (including continuous and discontinuous distributions). Second, combining the separation of variables and perturbation methods, it develops a novel general method to solve the fourth-order partial differential equations with unknown variable coefficients for cylindrical shells under distributed axial loads. Last, it derives the asymptotic formula of buckling loads with respect to shell geometry sizes and load functions for the first time. Using the presented formula, two continuous axial load distributions are analyzed first and the results show a good agreement with previous studies and those by the Bubnov-Galerkin method. Furthermore, one discontinuous axial load distribution is investigated. Comparative study on effects of load distribution parameters and types is also performed. The study has sufficient accuracy and significant engineering application value.

In this study, the problem of car-following stability is considered. This study presents a clustered car-following strategy based on inter-vehicle communications (IVCs), which contributes to derive a more accurate feedback control for improving the stability. In order to maintain car-following stability, two conditions are considered, which are based on the control theory and a modified optimal velocity car-following model. In simulations, the results demonstrate that the strategy is effective on the stability of car-following, and the effect becomes more obvious as the market penetration rates of IVC-equipped vehicles increase. Even in low market penetration rate (5%), the proposed strategy has significant influence on the stability and the recovering time.

This paper presents an analytical investigation on dynamic buckling of cylindrical shells with general thickness variations under exponentially increasing external pressure over the time. Different from the previous studies in literatures, the shell thickness varies arbitrarily and is common in actual engineering, which leads to failure of the existing methods. A new analytical method is first developed to solve the fourth-order governing partial differential equations with variable coefficients for the shell subjected to varying external pressure. Then the asymptotic formulae for dynamic buckling loads considering general thickness variations are derived and expressed by geometry sizes of the shell and thickness variation functions. To validate the presented results, two specific non-axisymmetric thickness cases are discussed in detail. The critical dynamic buckling loads show a great agreement with the previous ones by other researchers for simple and axial thickness variation situation. Finally, example calculations and parametric discussion are performed, and influences of thickness variation types, speed of external pressure and the power exponent of time on the critical dynamic buckling loads are discussed.

Travel time is one of the most critical indexes to describe urban traffic operating states. How to obtain accurate and robust travel time estimates, so as to facilitate to make traffic control decision-making for administrators and trip-planning for travelers, is an urgent issue of wide concern. This paper proposes a reliable estimation method of urban link travel time using multi-sensor data fusion. Utilizing the characteristic analysis of each individual traffic sensor data, we first extract link travel time from license plate recognition data, geomagnetic detector data and floating car data, respectively, and find that their distribution patterns are similar and follow logarithmic normal distribution. Then, a support degree algorithm based on similarity function and a credibility algorithm based on membership function are developed, aiming to overcome the conflicts among multi-sensor traffic data and the uncertainties of single-sensor traffic data. The reliable fusion weights for each type of traffic sensor data are further determined by integrating the corresponding support degree with credibility. A case study was conducted using real-world data from a link of Jingshi Road in Jinan, China and demonstrated that the proposed method can effectively improve the accuracy and reliability of link travel time estimations in urban road systems.

Analysis of heart rate variability (HRV) holds an important potential in emotion recognition, especially when the non-linear entropy methods are involved. Permutation pattern entropy (PPEn) and ordinal pattern entropy (OPEn) are two important Shannon entropy approaches for analyzing the inherent dynamic characteristics of RR interval time series and their performances should be tested in the emotion study. In this study, ECG signals were recorded from 60 healthy subjects by RM6240B multi-channel signal acquirement system under three emotion states: natural, happiness and sadness, at a sample rate of 1000 Hz. For each emotion state, ECG signal was recorded for five minutes. QRS complexes were identified and then the RR interval time series were analyzed by the PPEn and OPEn methods. Compared with natural emotion (1.6834±0.06), PPEn increases significantly in both happiness (1.7205±0.05) and sadness (1.7065±0.05) emotions. Meanwhile, PPEn shows significant difference between happiness and sadness emotions. For OPEn, compared with natural emotion (1.8318±0.07), it also increases in both happiness (1.8545±0.07) and sadness (1.8505±0.07) emotions. However, there is no significant difference between happiness and sadness emotions. The changes of PPEn and OPEn values during the three different emotion states suggests that emotion has a non-negligible influence on the inherent dynamic characteristics in cardiovascular system, and the PPEn and OPEn methods can be used in the emotion recognition study.

To detect traffic state using Smart-phone equipped vehicles (for short, equipped vehicles) data is popular in recent years. Calculating the average speed of all equipped vehicles simply is no longer reasonable without considering random distribution of equipped vehicles. In this paper, a new method of detecting traffic state based on equipped vehicle data was presented. Inspired by information entropy theory, the key homogeneous distribution degree (KHDD) can be obtained, which contributes to correct the detection error caused by the random distribution of equipped vehicles. In simulations, the results show the validity of the proposed method to detect traffic state under the different KHDD.

G-protein-coupled estrogen receptor-30 (GPR30), also known as G-protein estrogen receptor-1 (GPER1), is a putative extranuclear estrogen receptor whose precise functions in the brain are poorly understood. Studies using exogenous administration of the GPR30 agonist, G1 suggests that GPR30 may have a neuroprotective role in cerebral ischemia. However, the physiological role of GPR30 in mediating estrogen (E2)-induced neuroprotection in cerebral ischemia remains unclear. Also unclear is whether GPR30 has a role in mediating rapid signaling by E2 after cerebral ischemia, which is thought to underlie its neuroprotective actions. To address these deficits in our knowledge, the current study examined the effect of antisense oligonucleotide (AS) knockdown of GPR30 in the hippocampal CA1 region upon E2-BSA-induced neuroprotection and rapid kinase signaling in a rat model of global cerebral ischemia (GCI). Immunohistochemistry demonstrated that GPR30 is strongly expressed in the hippocampal CA1 region and dentate gyrus, with less expression in the CA3 region. E2-BSA exerted robust neuroprotection of hippocampal CA1 neurons against GCI, an effect abrogated by AS knockdown of GPR30. Missense control oligonucleotides had no effect upon E2-BSA-induced neuroprotection, indicating specificity of the effect. The GPR30 agonist, G1 also exerted significant neuroprotection against GCI. E2-BSA and G1 also rapidly enhanced activation of the prosurvival kinases, Akt and ERK, while decreasing proapototic JNK activation. Importantly, AS knockdown of GPR30 markedly attenuated these rapid kinase signaling effects of E2-BSA. As a whole, the studies provide evidence of an important role of GPR30 in mediating the rapid signaling and neuroprotective actions of E2 in the hippocampus.

In urban scenario, the imbalanced spatial distribution of traffic flow exerts an important influence on the performance of communication between vehicles and the Roadside Unit (RSU). This paper presents a strategy for RSUs placement based on the road traffic characteristics, aiming at improving connectivity in vehicular ad hoc networks. To divide the coverage area of each RSU, we propose an Expansion and Coloration Algorithm (ECA). The average connectivity model for all vehicles in the network is established based on the results obtained from ECA. The RSUs placement problem is formulated as a combinatorial optimization problem, of which the objective is to maximize the average connectivity probability by searching for an optimal position combination of the given RSUs. Taking part of an actual urban road network as an example, the RSUs placement problem is calculated and the optimal placement scheme is evaluated. Simulation results show that the optimal placement scheme obtained from our strategy leads to the best connectivity compared to uniform placement and hot-spot placement.

Assuming axisymmetric buckling and according to the adjacent equilibrium criterion, a buckling critical stress formula of a perfect tank wall is first obtained through analysis of elastic–plastic buckling carried out by J 2 plastic flow theory. Furthermore, combining the current tank seismic design standards and the results obtained in this paper, a new critical buckling stress formula of the tank wall is derived after correction for material plasticity by introducing a plasticity influence coefficient. Comparisons between the results obtained and those from the relevant formulas in the design standards of America, Japan, China and Europe are also performed. Our research shows that under interaction of high hydraulic and axial compression, the material properties of the tank wall change rapidly, and the buckling strength of the tank wall also decreases rapidly. The relation between the tank wall buckling critical stress and the hydraulic pressure is similar to Rotter's semi-empirical formula. The results presented in this paper can provide technical support in further protection of large oil storage tanks.

The effect of weld reinforcement on axial plastic buckling of welded steel cylindrical shells is investigated through experimental and numerical buckling analysis using six welded steel cylindrical shell specimens. The relationship between the amplitude of weld reinforcement and the axial plastic buckling critical load is explored. The effect of the material yield strength and the number of circumferential welds on the axial plastic buckling is studied. Results show that circumferential weld reinforcement represents a severe imperfect form of axially compressed welded steel cylindrical shells and the axial plastic buckling critical load decreases with the increment of the mean amplitude of circumferential weld reinforcement. The material yield strength and the number of circumferential welds are found to have no significant effect on buckling waveforms; however, the axial plastic buckling critical load can be decreased to some extent with the increase of the number of circumferential welds.

According to traffic information of multi-source heterogeneity and complexity of information processing, the architecture of the dynamic traffic information platform based on middleware is proposed, which enhanced the system stability, generality, and efficiency depending on the high integration and scalability of middleware. This middleware-based platform unifies and encodes the data from all sorts of detectors, and integrates the multi-mode transmission, data preprocessing, and data fusion. On the publishing stage, this platform realizes the interactions between different publishing devices and traffic database through an independent traffic information publishing middleware. The proposed platform overcomes the data loss and data noise, decreases the data redundancy due to the heterogeneous multi-source data, and ensures the data accuracy with better security and expandability. The performance is efficient, reliable with cross-platform information transmission.

G-protein-coupled estrogen receptor-30 (GPR30), also known as G-protein estrogen receptor-1 (GPER1), is a putative extranuclear estrogen receptor whose precise functions in the brain are poorly understood. Studies using exogenous administration of the GPR30 agonist, G1 suggests that GPR30 may have a neuroprotective role in cerebral ischemia. However, the physiological role of GPR30 in mediating estrogen (E2)-induced neuroprotection in cerebral ischemia remains unclear. Also unclear is whether GPR30 has a role in mediating rapid signaling by E2 after cerebral ischemia, which is thought to underlie its neuroprotective actions. To address these deficits in our knowledge, the current study examined the effect of antisense oligonucleotide (AS) knockdown of GPR30 in the hippocampal CA1 region upon E2-BSA-induced neuroprotection and rapid kinase signaling in a rat model of global cerebral ischemia (GCI). Immunohistochemistry demonstrated that GPR30 is strongly expressed in the hippocampal CA1 region and dentate gyrus, with less expression in the CA3 region. E2-BSA exerted robust neuroprotection of hippocampal CA1 neurons against GCI, an effect abrogated by AS knockdown of GPR30. Missense control oligonucleotides had no effect upon E2-BSA-induced neuroprotection, indicating specificity of the effect. The GPR30 agonist, G1 also exerted significant neuroprotection against GCI. E2-BSA and G1 also rapidly enhanced activation of the prosurvival kinases, Akt and ERK, while decreasing proapototic JNK activation. Importantly, AS knockdown of GPR30 markedly attenuated these rapid kinase signaling effects of E2-BSA. As a whole, the studies provide evidence of an important role of GPR30 in mediating the rapid signaling and neuroprotective actions of E2 in the hippocampus.

Vehicular Ad-Hoc Network (VANET) is an essential technology to improve safety and efficiency of Intelligent Transportation System (ITS), it provides vehicle to vehicle as well as vehicle to roadside unit (RSU) wireless communications, so that on board unit (OBU) located in vehicles can share messages related to road traffic with not only other OBU in the same VANET but also transportation management centre depending on retransmission of RSU. It is very important to detect and transmit real time messages of road traffic condition in VANET. This paper presents two application schemes for VANET based on chaos sequence: traffic flow forecast and vehicle secret communications. The principles of these schemes are introduced separately, and performances are verified by theoretical analysis and simulation. DOI: http://dx.doi.org/10.11591/telkomnika.v11i9.3270

In order to overcome the defects such as too many cluster heads and large overhead in traditional single hop VANET clustering algorithms when there are high density vehicles, this article proposes a multi-hop cluster algorithm named the position sensitive clustering algorithm (PSCA). Based on the establishment of cluster structure, initial cluster head is selected following the â??Randomly Competition, First Declare Winâ?? principle. Cluster members transmit their expected status messages through the maintained multiple hop routings. After a series of information fusion and calculation work, the cluster head broadcasts the management messages based on dynamic timestamps. This article also gives the cluster maintaining strategy when the cluster head disappears or new nodes join. Tests performed in the simulation by NS-2 show that the proposed algorithm has less cluster heads and lower control overhead compared to the single hop-based approach (the Lowest-ID algorithm).