Study of the Magnetocaloric Effect in La0.5Sm0.2Sr0.3Mn1-xFexO3 (x = 0 and 0.05) Manganites with the Mean-Field Theory

In this paper, the magnetocaloric in La0.5Sm0.2Sr0.3Mn1-xFexO3 compounds with x = 0 (LSSMO) and x = 0.05 (LSSMFO) were simulated using mean field model theory. A strong consistency was observed between the theoretical and experimental curves of magnetizations and magnetic entropy changes, −ΔSM(T). Based on the mean-field generated −ΔSM(T), the substantial Temperature-averaged Entropy Change (TEC) values reinforce the appropriateness of these materials for use in magnetic refrigeration technology within TEC (10) values of 1 and 0.57 J∙kg−1∙K−1under 1 T applied magnetic field.

Calculation of Interaction Parameters from Immiscible Phase Diagram of Alkali Metal or Alkali Earth Metal-Halide System by Means of Subregular Solution Model

In this paper, the interaction parameters in the subregular solution model, λ1 and λ2, are regarded as a linear function of temperature, T. Therefore, the molar excess Gibbs energy of A-B binary system may be reexpressed as follows:Gm^E=xAxB[(λ11+λ12T)+(λ21+λ22T)xB]The calculation of the model parameters, λ11, λ12, λ21and λ22, was carried out numerically from the phase diagrams for 11 alkali metal-alkali halide or alkali earth metal-halide systems. In addition, artificial neural network trained by known data has been used to predict the values of these model parameters. The predicted results are in good agreement with the .calculated ones. The applicability of the subregular solution model to the alkali metal-alkali halide or alkali earth metal-halide systems were tested by comparing the available experimental composition along the boundary of miscibility gap with the calculated ones which were obtained by using genetic algorithm. The good agreement between the calculated and experimental results across the entire liquidus is valid evidence in support of the model.

Performance of cumulant-based rank reduction estimator in presence of unexpected modeling errors

Compared with the rank reduction estimator(RARE) based on second-order statistics(called SOS-RARE), the RARE based on fourth-order cumulants(referred to as FOC-RARE) can handle more sources and restrain the negative impacts of the Gaussian colored noise. However, the unexpected modeling errors appearing in practice are known to significantly degrade the performance of the RARE. Therefore, the direction-of-arrival(DOA) estimation performance of the FOC-RARE is quantitatively derived. The explicit expression for direction-finding(DF) error is derived via the first-order perturbation analysis, and then the theoretical formula for the mean square error(MSE) is given. Simulation results demonstrate the validation of the theoretical analysis and reveal that the FOC-RARE is more robust to the unexpected modeling errors than the SOS-RARE.

A novel hybrid algorithm based on a harmony search and artificial bee colony for solving a portfolio optimization problem using a mean-semi variance approach

Portfolio selection is one of the major capital allocation and budgeting issues in financial management, and a variety of models have been presented for optimal selection. Semi-variance is usually considered as a risk factor in drawing up an efficient frontier and the optimal portfolio. Since semi-variance offers a better estimation of the actual risk portfolio, it was used as a measure to approximate the risk of investment in this work. The optimal portfolio selection is one of the non-deterministic polynomial(NP)-hard problems that have not been presented in an exact algorithm, which can solve this problem in a polynomial time. Meta-heuristic algorithms are usually used to solve such problems. A novel hybrid harmony search and artificial bee colony algorithm and its application were introduced in order to draw efficient frontier portfolios. Computational results show that this algorithm is more successful than the harmony search method and genetic algorithm. In addition, it is more accurate in finding optimal solutions at all levels of risk and return.

Improving control effects of absence seizures using single-pulse alternately resetting stimulation (SARS) of corticothalamic circuit

Presently,we develop a simplified corticothalamic(SCT)model and propose a single-pulse alternately resetting stimulation(SARS)with sequentially applying anodic(A,“+”)or cathodic(C,“−”)phase pulses to the thalamic reticular(RE)nuclei,thalamus-cortex(TC)relay nuclei,and cortical excitatory(EX)neurons,respectively.Abatement effects of ACC-SARS of RE,TC,and EX for the 2 Hz-4 Hz spike and wave discharges(SWD)of absence seizures are then concerned.The m∶n on-off ACC-SARS protocol is shown to effectively reduce the SWD with the least current consumption.In particular,when its frequency is out of the 2 Hz-4 Hz SWD dominant rhythm,the desired seizure abatements can be obtained,which can be further improved by our proposed directional steering(DS)stimulation.The dynamical explanations for the SARS induced seizure abatements are lastly given by calculating the averaged mean firing rate(AMFR)of neurons and triggering averaged mean firing rates(TAMFRs)of 2 Hz-4 Hz SWD.

Modified DIX model for ion-exchange equilibrium of L-phenylalanine on a strong cation-exchange resin

L-phenylalanine, one of the nine essential amino acids for the human body, is extensively used as an ingredient in food, pharmaceutical and nutrition industries. A suitable equilibrium model is required for purification of L-phenylalanine based on ion-exchange chromatography. In this work, the equilibrium uptake of L-phenylalanine on a strong acid-cation exchanger SH11 was investigated experimentally and theoretically. A modified Donnan ion-exchange （DIX） model, which takes the activiW into account, was established to predict the uptake of L-phenylalanine at various solution pH values. The model parameters including selectivity and mean activity coefficient in the resin phase are presented. The modified DIX model is in good agreement with the experimental data. The optimum operating pH value of 2.0, with the highest t-phenylalanine uptake on the resin, is predicted by the model. This basic information combined with the general mass transfer model will lay the foundation for the prediction of dynamic behavior of fixed bed separation process.

Joint modelling of location and scale parameters of the skew-normal distribution

Joint location and scale models of the skew-normal distribution provide useful ex- tension for joint mean and variance models of the normal distribution when the data set under consideration involves asymmetric outcomes. This paper focuses on the maximum likelihood estimation of joint location and scale models of the skew-normal distribution. The proposed procedure can simultaneously estimate parameters in the location model and the scale model. Simulation studies and a real example are used to illustrate the proposed methodologies.

SIMULATION OF NONPROPORTIONAL CYCLICEXPERIMENTS OF IN738LC AT 850℃

In the previous paper, in order to express steadystate ratchetting, the present s extended the cyclic plasticity model proposed by Ohno and Wang (1993), and the validity of the extended model was discussed on the basis of uniaxial ratchetting experiments of 316FR steel at room temperature. In the present paper, the validity of the extended model is discussed further on the basis of nonproportional experiments of IN738LC at 850 such as multiaxial ratchetting, multiaxial cyclic stress relaxation, circular cyclic straining with strain hold, and so on. Predictions based on the OhnoWang model as well as the ArmstrongFrederick model are also given for the sake of comparison. It is shown that the extended model is capable of simulating the nonproportional experiments accurately, and especially that the extended model can predict much less steadystate ratchetting than the ArmstrongFrederick model. It is also shown that the extended model provides almost the same predictions as the OhnoWang and th

Establishment and analysis of global gridded Tm-Ts relationship model

In ground-based GPS meteorology, Tm is a key parameter to calculate the conversion factor that can convert the zenith wet delay（ZWD） to precipitable water vapor（PWV）. It is generally acknowledged that Tm is in an approximate linear relationship with surface temperature Ts, and the relationship presents regional variation. This paper employed sliding average method to calculate correlation coefficients and linear regression coefficients between Tm and Ts at every 2°× 2.5° grid point using Ts data from European Centre for Medium-Range Weather Forecasts（ECMWF） and Tm data from ＂GGOS Atmosphere＂, yielding the grid and bilinear interpolation-based Tm Grid model. Tested by Tm and Ts grid data, Constellation Observation System of Meteorology, Ionosphere, and Climate（COSMIC） data and radiosonde data, the Tm Grid model shows a higher accuracy relative to the Bevis Tm-Ts relationship which is widely used nowadays. The Tm Grid model will be of certain practical value in high-precision PWV calculation.

Carbon Emission of Regional Land Use and Its Decomposition Analysis: Case Study of Nanjing City, China

Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carbon emissions by Logarithmic Mean Divisia Index（LMDI） model. The main conclusions are as follows： 1） Total anthropogenic carbon emission of Nanjing increased from 1.22928 ×10^7 t in 2000 to 3.06939 × 10^7 t in 2009, in which the carbon emission of Inhabitation, mining ＆ manufacturing land accounted for 93% of the total. 2） The average land use carbon emission intensity of Nanjing in 2009 was 46.63 t/ha, in which carbon emission intensity of Inhabitation, mining ＆ manufacturing land was the highest（200.52 t/ha）, which was much higher than that of other land use types. 3） The average carbon source intensity in Nanjing was 16 times of the average carbon sink intensity（2.83 t/ha） in 2009, indicating that Nanjing was confronted with serious carbon deficit and huge carbon cycle pressure. 4） Land use area per unit GDP was an inhibitory factor for the increase of carbon emissions, while the other factors were all contributing factors. 5） Carbon emission effect evaluation should be introduced into land use activities to formulate low-carbon land use strategies in regional development.

Learners’motivational response to the Science,PE,&Me!curriculum:A situational interest perspective

Background:The Science,PE,&Me!(SPEM)curriculum is a concept-based physical education curriculum that offers students coherent educational experiences for constructing health-related fitness knowledge through movement experiences.The purpose of this study was to evaluate students’motivational response to the SPEM curriculum from the situational interest perspective.Methods:The study used a cluster randomized controlled design in which 30 elementary schools in one of the largest metropolitan areas in the eastern United States were randomly assigned to an experimental or comparison condition.Although all students in the 3rd,4th,and 5th grades in the targeted schools were eligible to participate in the study,a random sample of students from the experimental(n=1749;15 schools)and comparison groups(n=1985;15 schools)provided data.Students’motivational response to the SPEM curriculum or comparison curriculum was measured using the previously validated Situational Interest Scale-Elementary.Data were analyzed using structural mean modeling.Results:The results demonstrated that the experimental group(as reference group)showed significantly higher enjoyment(z=-2.01),challenge(z=-6.54),exploration(z=-12.195),novelty(z=-8.80),and attention demand(z=-7.90)than the comparison group.Conclusion:The findings indicate that the SPEM curriculum created a more situationally interesting context for learning than the comparison physical education curriculum.

A New Mean Reversion Model of Close-End Fund

On the basis of fractal theory, one of the nonlinear theories, this paper studies the validity of Chinese fund market fractal time sequence through Hurst exponent, calculates the H value and proposes a new close-end fund mean reversion model. Meanwhile, this paper validates the mean reversion time sequence for consecutive 54 week data of fund market. The result indicates that this model can effectively prove that Chinese close-end fund market follows the biased random walk. The research also proves that the fund discount does have mean reversion tendency and averagely the fund with high discount has a higher excess yield than that of the fund with low discount. The mean excess yield and the ratio between discount rate deviation and standard deviation demonstrate a descending relationship. The optimum investment period based on ＂mean reversion＂ is one month. Consequently this model provides a new arbitrage method through the discount of close-end fund.

A new model of foraging behavior in ant system

Foraging behavior in ant colonies has come to be viewed as a prototypical example to describe how complex group behavior can arise from simple individuals. In order to research the feature of self-organization in swarm intelligence (SI), a mean field model is given and analyzed in foraging process with three sources in this paper. The distance of trails and the richness of each source are considered. Both of the theoretical numerical analysis and Monte Carlo simulation show the power law relationship between the completion time and the flux of foragers. The work presented here guides a better understanding on self-organization and swarm intelligence. It can be used to design more efficient, adaptive, and reliable intelligent systems.

Regulating absence seizures by tri-phase delay stimulation applied to globus pallidus internal

In this paper,a reduced globus pallidus internal(GPI)-corticothalamic(GCT)model is developed,and a tri-phase delay stimulation(TPDS)with sequentially applying three pulses on the GPI representing the inputs from the striatal D_(1)neurons,subthalamic nucleus(STN),and globus pallidus external(GPE),respectively,is proposed.The GPI is evidenced to control absence seizures characterized by 2 Hz–4 Hz spike and wave discharge(SWD).Hence,based on the basal ganglia-thalamocortical(BGCT)model,we firstly explore the triple effects of D_(1)-GPI,GPE-GPI,and STN-GPI pathways on seizure patterns.Then,using the GCT model,we apply the TPDS on the GPI to potentially investigate the alternative and improved approach if these pathways to the GPI are blocked.The results show that the striatum D_(1),GPE,and STN can indeed jointly and significantly affect seizure patterns.In particular,the TPDS can effectively reproduce the seizure pattern if the D_(1)-GPI,GPE-GPI,and STN-GPI pathways are cut off.In addition,the seizure abatement can be obtained by well tuning the TPDS stimulation parameters.This implies that the TPDS can play the surrogate role similar to the modulation of basal ganglia,which hopefully can be helpful for the development of the brain-computer interface in the clinical application of epilepsy.

Associations between Body Mass Index and Breast Cancer Markers

Body mass index(BMI)and breast cancer biomarkers(BCBs)such as resistin,leptin adiponectin,monocyte chemoattractant protein-1(MCP-1)and homeostasis model assessment of insulin resistance(HOMA-IR)are highly associated with each other.The report has focused the inter-relationship between BMI and BCBs based on probabilistic modeling.It has been shown that mean BMI is directly associated with leptin(P<0.0001)and MCP-1(P=0.0002),while it is inversely associated with adiponectin(P=0.0003),HOMA-IR(P<0.0001),and it is higher for healthy women(P=0.0116)than breast cancer women.In addition,variance of BMI is inversely associated with resistin(P=0.1450).On the other hand,mean MCP-1 is directly associated with BMI(P<0.0001).Mean resistin is directly associated with the interaction effect of BMI and leptin(BMI^*Leptin)(P=0.0415),while its variance is directly associated with BMI(P=0.0942),and it is inversely associated with BMI*Adiponectin(P=0.1518).Leptin is directly associated with BMI(P<0.0001).Also adiponectin is inversely associated with BMI(P<0.0001),BMI*Leptin(P=0.1729),while it is directly associated with Age^*BMI(P=0.0017)and BMI^*Resistin(P=0.0615).It can be concluded that BMI and BCBs are strongly associated with each other.Care should be taken on BMI for breast cancer women.

Thermodynamic properties and phase diagram of quark matter within non-extensive Polyakov chiral SU(3)quark mean field model

In the present study,we applied Tsallis non-extensive statistics to investigate the thermodynamic properties and phase diagram of quark matter in the Polyakov chiral SU(3)quark mean field model.Within this model,the properties of the quark matter were modified through the scalar fieldsσ,ζ,δ,χ,vector fieldsω,ρ,ϕ,and Polyakov fieldsΦandΦ¯at finite temperature and chemical potential.Non-extensive effects were introduced through a dimensionless parameter q,and the results were compared to those of the extensive case(q→1).In the non-extensive case,the exponential in the Fermi-Dirac(FD)function was modified to a q-exponential form.The influence of the q parameter on the thermodynamic properties,pressure,energy,and entropy density,as well as trace anomaly,was investigated.The speed of sound and specific heat with non-extensive effects were also studied.Furthermore,the effect of non-extensivity on the deconfinement phase transition as well as the chiral phase transition of u,d,and s quarks was explored.We found that the critical end point(CEP),which defines the point in the(T−μ)phase diagram where the order of the phase transition changes,shifts to a lower value of temperature,TCEP,and a higher value of chemical potential,μCEP,as the non-extensivity is increased,that is,q>1.

A moving average Cholesky factor model in joint mean-covariance modeling for longitudinal data

Modeling the mean and covariance simultaneously is a common strategy to efficiently estimate the mean parameters when applying generalized estimating equation techniques to longitudinal data. In this article, using generalized estimation equation techniques, we propose a new kind of regression models for parameterizing covariance structures. Using a novel Cholesky factor, the entries in this decomposition have moving average and log innovation interpretation and are modeled as the regression coefficients in both the mean and the linear functions of covariates. The resulting estimators for eovarianee are shown to be consistent and asymptotically normally distributed. Simulation studies and a real data analysis show that the proposed approach yields highly efficient estimators for the parameters in the mean, and provides parsimonious estimation for the covariance structure.

The Measurement of Carbon Emission Effect of Construction Land Changes in Anhui Province Based on the Extended LMDI Model

In the context of ＂two-wheel drive＂ development mode, China＇s construction land shows significant expansion characteristics. The carbon emission effect of construction land changes is an important factor for the increase of carbon emissions in the atmosphere. In this study, the drivers of carbon emissions in Anhui Province from 1997 to 2011 were quantitatively measured using the improved Kaya identity and Logarithmic Mean Divisia Index. The results show that： economic growth, expansion of construction land and changes in population density have incremental effects on carbon emissions. The average contribution rate of economic growth as the first driver is 266.32 percent. The construction land expansion is an important driving factor with annual mean carbon effect of 6.4057 million tons and annual mean contribution rate of 187.30 percent. But the change in population density has little impact on carbon emission driving. Energy structure changes and energy intensity reduction have inhibitory effects on carbon emissions, of which the annual mean contribution rate is -212.06 percent and -158.115 percent respectively. The targeted policy approaches of carbon emission reduction were put forward based on the decomposition of carbon emission factors, laying a scientific basis to rationally use the land for the Government, which is conducive to build an ecological province for Anhui and achieve the purpose of emission reduction, providing a reference for the research on carbon emission effect of changes in provincial-scale construction land.

Contextual Meaning and Word Meaning

The paper has three goals: 1) Explain the role of context and word in meaning construction and comprehension. 2) Present a model that can explain meaning generated by both monolingual and multilingual meaning construction systems. 3) Discuss how the model can be applied to explain major issues in pragmatics. Pragmatics is understood here in a narrow sense as defined by Sperber & Noveck: “...pragmatics is the study of how linguistic properties and contextual factors interact in the interpretation of utterances” (Sperber & Noveck 2004∶1). It is argued that world knowledge is available to interlocutors in two forms: as encapsulated in lexical items based on prior encounters and experience (conventionalized cognitive context), and as provided by the actual situational context framed by the situation in which the interaction takes place. Meaning formally expressed in the linguistic interactional context is created on-the-spot, and is the result of the interaction of the two sides of world knowledge and the actual situational context. The paper makes three claims∶ First, supremacy of context is not unconditional in language processing. Second, salient meaning rather than literal meaning of lexical units plays a central role in comprehension. Third, intercultural communication differs from intracultural communication in the conceptual content of conventionalized cognitive contexts rather than in communicative means.

Statistical Diagnosis for HIV Dynamics Based on Mean Shift Outlier Model

Ordinary differential equation(ODE) are widely used for quantifying HIV viral dynamics.It is interesting but challenging to estimate ODE parameters from noisy data, especially when the data have some outliers. In this study, the authors use the Mean Shift Outlier Model(MSOM) to detect outliers in HIV model based on the two-step estimation of ODE. Approximate formula for shift parameter is derived. Furthermore, a score test statistic is constructed and its approximating distribution is established. The simulation results show that: 1) The boundary points have more impact on the parameter estimation relative to interior points. 2) The proposed procedure can detect the outliers effectively. The authors illustrate the proposed approach using an application example from an HIV clinical trial and find similar pattern to the simulation studies.