Comparative study of nudged elastic band and molecular dynamics methods for diffusion kinetics in solid-state electrolytes

Considerable efforts are being made to transition current lithium-ion and sodium-ion batteries towards the use of solid-state electrolytes.Computational methods,specifically nudged elastic band(NEB)and molecular dynamics(MD)methods,provide powerful tools for the design of solid-state electrolytes.The MD method is usually the choice for studying the materials involving complex multiple diffusion paths or having disordered structures.However,it relies on simulations at temperatures much higher than working temperature.This paper studies the reliability of the MD method using the system of Na diffusion in MgO as a benchmark.We carefully study the convergence behavior of the MD method and demonstrate that total effective simulation time of 12 ns can converge the calculated diffusion barrier to about 0.01 eV.The calculated diffusion barrier is 0.31 eV from both methods.The diffusion coefficients at room temperature are 4.3×10^(-9) cm^(2)⋅s^(−1) and 2.2×10^(-9) cm^(2)⋅s^(−1),respectively,from the NEB and MD methods.Our results justify the reliability of the MD method,even though high temperature simulations have to be employed to overcome the limitation on simulation time.

Repetitive transcranial magnetic stimulation for hallucination in schizophrenia spectrum disorders A meta-analysis

OBJECTIVE： This study assessed the efficacy and tolerability of repetitive transcranial magnetic stimulation for treatment of auditory hallucination of patients with schizophrenia spectrum disorders. DATA SOURCES： Online literature retrieval was conducted using PubMed, ISI Web of Science, EMBASE, Medline and Cochrane Central Register of Controlled Trials databases from January 1985 to May 2012. Key words were ＂transcranial magnetic stimulation＂, ＂TMS＂, ＂repetitive tran- scranial magnetic stimulation＂, and ＂hallucination＂. STUDY SELECTION： Selected studies were randomized controlled trials assessing therapeutic ef- ficacy of repetitive transcranial magnetic stimulation for hallucination in patients with schizophrenia spectrum disorders. Experimental intervention was low-frequency repetitive transcranial magnetic stimulation in left temporoparietal cortex for treatment of auditory hallucination in schizophrenia spectrum disorders. Control groups received sham stimulation. MAIN OUTCOME MEASURES： The primary outcome was total scores of Auditory Hallucinations Rating Scale, Auditory Hallucination Subscale of Psychotic Symptom Rating Scale, Positive and Negative Symptom Scale-Auditory Hallucination item, and Hallucination Change Scale. Secondary outcomes included response rate, global mental state, adverse effects and cognitive function. RESULTS： Seventeen studies addressing repetitive transcranial magnetic stimulation for treatment of schizophrenia spectrum disorders were screened, with controls receiving sham stimulation. All data were completely effective, involving 398 patients. Overall mean weighted effect size for repeti- tive transcranial magnetic stimulation versus sham stimulation was statistically significant （MD = -0.42, 95%C/： -0.64 to -0.20, P = 0.000 2）. Patients receiving repetitive transcranial magnetic stimulation responded more frequently than sham stimulation （OR = 2.94, 95%C/： 1.39 to 6.24, P =0.005）. No significant differences were found between active repetitive transcranial magnetic stimulation and sham stimulation for positive or negative symptoms. Compared with sham stimulation, active repeti- tive transcranial magnetic stimulation had equivocal outcome in cognitive function and commonly caused headache and facial muscle twitching. CONCLUSION： Repetitive transcranial magnetic stimulation is a safe and effective treatment for auditory hallucination in schizophrenia spectrum disorders,

Early rehabilitation improves neurofunctional outcome after surgery in children with spinal tumors

To investigate the effect of early rehabilitation on neurofunctional outcome after surgery in chil- dren with spinal tumors, this study reviewed the medical charts and radiographic records of 70 pediatric patients （1-17 years old） who received spinal tumor surgical removal. The peddiatric patients received rahabilitation treatment at 4 （range, 2-7） days after surgery for 10 （range, 7-23） days. Results from the Modified McCormick Scale, Functional Independence Measure for Chil- dren, American Spinal Injury Association Impairment Scale and Karnofsky Performance Status Scale demonstrated that the sensory function, motor function and activity of daily living of pedi- atric children who received early rehabilitation were significantly improved. Results also showed that tumor setting and level localization as well as patients＇s clinical symptoms have no influences on neurofunctional outcomes.

Kinetic Model and Simulation Analysis for Toluene Disproportionation and C9-Aromatics Transalkylation

A new kinetic model for commercial unit of toluene disproportionation and C9-armatiocs transalkylation is developed based on the reported reaction scheme.A time based catalyst deactivation function taking weight hourly space velocity(WHSV)into account is incorporated into the model,which reasonably accounts for the loss in activity because of coke deposition on the surface of catalyst during long-term operation.The kinetic parameters are benchmarked with several sets of balanced plant data and estimated by the differential variable metric optimiza- tion method.Sets of plant data at different operating conditions are applied to make sure validation of the model and the results show a good agreement between the model predictions and plant observations.The simulation analysis of key variables such as temperature and WHSV affecting process performance is discussed in detail,giv- ing the guidance to select suitable operating conditions.

Contribution of altered signal transduction associated to glutamate receptors in brain to the neurological alterations of hepatic encephalopathy

Patients with liver disease may present hepatic enceph- alopathy (HE), a complex neuropsychiatric syndrome covering a wide range of neurological alterations, including cognitive and motor disturbances. HE reduces the quality of life of the patients and is associated with poor prognosis. In the worse cases HE may lead to coma or death. The mechanisms leading to HE which are not well known are being studied using animal models. The neurological alterations in HE are a consequence of impaired cerebral function mainly due to alterations in neurotransmission. We review here some studies indicating that alterations in neurotransmission associated to different types of glutamate receptors are responsible for some of the cognitive and motor alterations present in HE. These studies show that the function of the signal transduction pathway glutamate-nitric oxide-cGMP associated to the NMDA type of glutamate receptors is impaired in brain in vivo in HE animal models as well as in brain of patients died of HE. Activation of NMDA receptors in brain activates this pathway and increases cGMP. In animal models of HE this increase in cGMP induced by activation of NMDA receptors is reduced, which is responsible for the impairment in learning ability in these animal models. Increasing cGMP by pharmacological means restores learning ability in rats with HE and may be a new therapeutic approach to improve cognitive function in patients with HE. However, it is necessary to previously assess the possible secondary effects.Patients with HE may present psychomotor slowing, hypokinesia and bradykinesia. Animal models of HE also show hypolocomotion. It has been shown in rats with HE that hypolocomotion is due to excessive activation of metabotropic glutamate receptors (mGluRs) in substantia nigra pars reticulata. Blocking mGluR1 in this brain area normalizes motor activity in the rats, suggesting that a similar treatment for patients with HE could be useful to treat psychomotor slowing and hypokinesia. However, the possible secondary effects of mGluR1 antagonists should be previously evaluated. These studies are setting the basis for designing therapeutic procedures to specifically treat the individual neurological alterations in patients with HE.

Modeling and verifying So S performance requirements of C4ISR systems

System-of-systems （SOS） engineering involves a com- plex process of refining high-level SoS requirements into more detailed systems requirements and assessing the extent to which the performances of to-be systems may possibly satisfy SoS capa- bility objectives. The key issue is how to model such requirements to automate the process of analysis and assessment. This paper suggests a meta-model that defines both functional and non- functional features of SoS requirements for command and control, communication, computer, intelligence, surveillance reconnais- sance （C41SR） systems. A domain-specific modeling language is defined by extending unified modeling language （UML） con- structed of class and association with fuzzy theory in order to model the fuzzy concepts of performance requirements. An effi- ciency evaluation function is introduced, based on Bezier curves, to predict the effectiveness of systems. An algorithm is presented to transform domain models in fuzzy UML into a requirements ontology in description logic （DL） so that requirements verification can be automated with a popular DL reasoner such as Pellet.

Laplace Transformation and Ergodic Potential Kernel for q-Process in Random Environment

This paper introduces some concepts such as q- process in random environment, Laplace transformation, ergodic potential kernel, error function and some basic lemmas.We study the continuity and Laplace transformation of random transition function. Finally, we give the sufficient condition for the existence of ergodic potential kernel for homogeneous q- processes in random environments.

FAST COMPUTATION OF WIDEBAND RCS USING CHARACTERISTIC BASIS FUNCTION METHOD AND ASYMPTOTIC WAVEFORM EVALUATION TECHNIQUE

The Asymptotic Waveform Evaluation (AWE) technique is an extrapolation method that provides a reduced-order model of linear system and has already been successfully used to analyze wideband electromagnetic scattering problems. As the number of unknowns increases, the size of Method Of Moments (MOM) impedance matrix grows very rapidly, so it is a prohibitive task for the computation of wideband Radar Cross Section (RCS) from electrically large object or multi-objects using the traditional AWE technique that needs to solve directly matrix inversion. In this paper, an AWE technique based on the Characteristic Basis Function (CBF) method, which can reduce the matrix size to a manageable size for direct matrix inversion, is proposed to analyze electromagnetic scattering from multi-objects over a given frequency band. Numerical examples are presented to il-lustrate the computational accuracy and efficiency of the proposed method.

A reliability study of springback on the sheet metal forming process under probabilistic variation of prestrain and blank holder force

This work deals with a reliability assessment of springback problem during the sheet metal forming process. The effects of operative parameters and material properties, blank holder force and plastic prestrain, on springback are in- vestigated. A generic reliability approach was developed to control springback. Subsequently, the Monte Carlo simula- tion technique in conjunction with the Latin hypercube sam- pling method was adopted to study the probabilistic spring- back. Finite element method based on implicit/explicit al- gorithms was used to model the springback problem. The proposed constitutive law for sheet metal takes into account the adaptation of plastic parameters of the hardening law for each prestrain level considered. Rackwitz-Fiessler al- gorithm is used to find reliability properties from response surfaces of chosen springback geometrical parameters. The obtained results were analyzed using a multi-state limit reli- ability functions based on geometry compensations.

Stability of Global Solution to Boltzmann-Enskog Equation with External Force

In the presence of external forces depending only on the time and space variables, the Boltzmann-Enskog equation formally conserves only the mass of the . system, and its entropy functional is also nonincreasing. Corresponding to this type of equation, we first give some hypotheses of its bicharacteristic equations and then get some results about the stablity of its global solution with the help of two new Lyapunov functionals： one is to describe interactions between particles with different velocities and the other is to measure the L1 distance between two mild solutions. The former Lyapunov functional yields the time-asymptotic convergence of global classical solutions to the collision free motion while the latter is applied into the veri-fication of the L1 stability of global mild solutions to the Boltzmann-Enskog equation for a moderately or highly dense gas in the influence of external forces.

APPLICATIONS OF HYPERGEOMETRIC SUMMATION THEOREMS OF KUMMER AND DIXON INVOLVING DOUBLE SERIES

Using series iteration techniques identities and apply each of these identities in we derive a number of general double series order to deduce several hypergeometric reduction formulas involving the Srivastava-Daoust double hypergeometric function. The results presented in this article are based essentially upon the hypergeometric summation theorems of Kummer and Dixon.

Generalized Gr?tzsch ring function and generalized elliptic integrals

Abstract. In this paper, we study the quotient of hypergeometric functions μα （r） in the theory of Ramanujan＇s generalized modular equation for α ∈（0, 1/2]. Several new inequalities are given for this and related functions. Our main results complement and generalize some known results in the literature.

改进的神经网络PID在空调温度控制中的应用

为提高候机楼中央空调温度控制水平,针对候机楼中央空调系统具有时滞性、扰动因素较多等特点,提出了一种基于改进天牛须搜索(IBAS,improved beetle antennae search)算法的模糊径向基函数(RBF,radial basis function)神经网络(PID,proportion integration differentiation)控制方法,建立了空调区域温度控制模型,通过模糊RBF神经网络实现PID参数在线整定,解决系统非线性、时变的问题。同时由于神经网络参数存在难以选取问题,提出利用天牛须搜索(BAS,beetle antennae search)算法优化模糊RBF神经网络参数的方法,并引入莱维飞行机制和变步长策略对BAS算法进行改进,提高其跳出局部最优的能力和稳定性。仿真结果表明,采用IBAS算法优化的模糊RBF神经网络PID控制方法有效提高了系统的鲁棒性和自适应能力,对候机楼中央空调系统具有良好的控制效果。

MEAN-FIELD LIMIT OF BOSE-EINSTEIN CONDENSATES WITH ATTRACTIVE INTERACTIONS IN R^2

Starting with the many-body SchrSdinger Hamiltonian in R2, we prove that the ground state energy of a two-dimensional interacting Bose gas with the pairwise attractive interaction approaches to the minimum of the Gross-Pitaevskii energy functional in the mean- field regime, as the particle number N → ∞ and however the scattering length → 0. By fixing N｜k｜, this leads to the mean-field approximation of Bose-Einstein condensates with attractive interactions in R^2.

Improvements in continuum modeling for biomolecular systems

Modeling of biomolecular systems plays an essential role in understanding biological processes, such as ionic flow across channels, protein modification or interaction, and cell signaling. The continuum model described by the Poisson- Boltzmann （PB）/Poisson-Nernst-Planck （PNP） equations has made great contributions towards simulation of these pro- cesses. However, the model has shortcomings in its commonly used form and cannot capture （or cannot accurately capture） some important physical properties of the biological systems. Considerable efforts have been made to improve the con- tinuum model to account for discrete particle interactions and to make progress in numerical methods to provide accurate and efficient simulations. This review will summarize recent main improvements in continuum modeling for biomolecu- lar systems, with focus on the size-modified models, the coupling of the classical density functional theory and the PNP equations, the coupling of polar and nonpolar interactions, and numerical progress.

Improved reproducing kernel particle method for piezoelectric materials

In this paper, the normal derivative of the radial basis function （RBF） is introduced into the reproducing kernel particle method （RKPM）, and the improved reproducing kernel particle method （IRKPM） is proposed. The method can decrease the errors on the boundary and improve the accuracy and stability of the algorithm. The proposed method is applied to the numerical simulation of piezoelectric materials and the corresponding governing equations are derived. The numerical results show that the IRKPM is more stable and accurate than the RKPM.

Command functions of open loop galvanometer scanners with optimized duty cycles

The paper approaches the problem of the command functions of galvanometer-based scanners （GS） that are necessary to produce the linear plus parabolic scanning function of the GS, which we have proved previously to produce the highest possible duty cycle （i.e., time efficiency） of the device. We have completed this theoretical aspect （which contradicted what has been stated previously in the literature, where it has been considered that the linear plus sinusoidal scanning function was the best） with the experimental study of the most used scanning functions of the GSs （sawtooth, sinusoidal and triangular）, with applications in biomedical imaging, in particular in optical coherence tomography, demonstrating that the triangular function is always the best one to be applied, from both an optical and a mechanical point of view. In the present study the input voltage/command function which should be applied to the GS to produce the desired triangular scanning function （with controlled non-linearity for the fastest possible stop-and-turn portions） was determined analytically, in relationship with the active torque that drives the device. This command function is analyzed with regard to the specific, respectively required parameters of the GS： natural frequency and damping factor, respectively scan speed and amplitude. The modeling in an open loop control structure of the GS is finally discussed as a trade-off between using the highest possible duty cycle and minimizing the maximum peaks of the input voltage.

Astrophysical parameters of ten poorly studied open star clusters

We present the fundamental parameters of ten open star clusters, nominated from Kronberger et al. who presented some newly discovered stellar groups on the basis of the Two Micron All Sky Survey photometry and Digitized Sky Survey visual images. Star counts and photometric parameters （radius, membership, distance, color excess, age, luminosity function, mass function, total mass, and dynamical relaxation time） have been determined for these ten clusters for the first time. In order to calibrate our procedures, the main parameters （distance, age, and color excess） have been reestimated for another five clusters, which are also studied by Kronberger et al.

Some Features of Neural Networks as Nonlinearly Parameterized Models of Unknown Systems Using an Online Learning Algorithm

This paper deals with deriving the properties of updated neural network model that is exploited to identify an unknown nonlinear system via the standard gradient learning algorithm. The convergence of this algorithm for online training the three-layer neural networks in stochastic environment is studied. A special case where an unknown nonlinearity can exactly be approximated by some neural network with a nonlinear activation function for its output layer is considered. To analyze the asymptotic behavior of the learning processes, the so-called Lyapunov-like approach is utilized. As the Lyapunov function, the expected value of the square of approximation error depending on network parameters is chosen. Within this approach, sufficient conditions guaranteeing the convergence of learning algorithm with probability 1 are derived. Simulation results are presented to support the theoretical analysis.

Support vector machine with mixture of kernels for automatic image annotation

Automatic image annotation(AIA)has become an important and challenging problem in computer vision due to the existence of semantic gap.In this paper,a novel support vector machine with mixture of kernels(SVM-MK)for automatic image annotation is proposed.On one hand,the combined global and local block-based image features are extracted in order to reflect the intrinsic content of images as complete as possible.On the other hand,SVM-MK is constructed to shoot for better annotating performance.Experimental results on Corel dataset show that the proposed image feature representation method as well as automatic image annotation classifier,SVM-MK,can achieve higher annotating accuracy than SVM with any single kernel and mi-SVM for semantic image annotation.