Erasable/Inerasable L1 Transfer in Interlanguage Phonology:An Optimality Theory Analysis of/aʊn/and Sentence Stress in Chinese Learners of English

The areas affected by the L1 transfer to L2,such as phonotactics and stress,appear to have different degrees of erasability through training and practice.This paper attempts a theoretical analysis to account for empirical observations of L1 transfer in diphthong-coda coalescence and in sentence stress for Chinese learners of English in an American accent training course.Using the framework and tableau method of Optimality Theory(Prince and Smolensky 1993),the phonological paradigm that views languages’differences as symptomatic of differences in rankings of a set of universal violable constraints,this paper posits the underlying ranking at work in(a)the segmental case where[aŋ]is the observed output for/aʊn/;(b)the suprasegmental case where no stress contrast is observed for a pair of phonologically similar sentences with contrastive stress.It is argued that,in the segmental case,the coalescence of the second vowel of a diphthong with an alveolar nasal coda results from the high ranking of markedness constraints,including Complex Syllable;and in the suprasegmental case,sentence stress is greatly affected by changes in the ranking of the constraint culminativity.Aside from shedding light on the understudied issue of diphthong-coda coalescence,this research also contributes to the discussion of the comparative erasability of L1 transfer for the two areas and demonstrates how a deduction-based theoretical method may actually have practical implications for guiding the design of L2 teaching methodology of English pronunciation as well as for promoting native English speakers’clearer understanding of Chinese learners of English on the global stage.

Optimal and robust control of population transfer in asymmetric quantum-dot molecules

We present an optimal and robust quantum control method for efficient population transfer in asymmetric double quantum-dot molecules.We derive a long-duration control scheme that allows for highly efficient population transfer by accurately controlling the amplitude of a narrow-bandwidth pulse.To overcome fluctuations in control field parameters,we employ a frequency-domain quantum optimal control theory method to optimize the spectral phase of a single pulse with broad bandwidth while preserving the spectral amplitude.It is shown that this spectral-phase-only optimization approach can successfully identify robust and optimal control fields,leading to efficient population transfer to the target state while concurrently suppressing population transfer to undesired states.The method demonstrates resilience to fluctuations in control field parameters,making it a promising approach for reliable and efficient population transfer in practical applications.

Method of Fire Image Identification Based on Optimization Theory

In view of some distinctive characteristics of the early-stage flame image, a corresponding method of characteristic extraction is presented. Also introduced is the application of the improved BP algorithm based on the optimization theory to identifying fire image characteristics. First the optimization of BP neural network adopting Levenberg-Marquardt algorithm with the property of quadratic convergence is discussed, and then a new system of fire image identification is devised. Plenty of experiments and field tests have proved that this system can detect the early-stage fire flame quickly and reliably.

Computing Open-Loop Optimal Control of the q-Profile in Ramp-Up Tokamak Plasmas Using the Minimal-Surface Theory

The q-profile control problem in the ramp-up phase of plasma discharges is consid- ered in this work. The magnetic diffusion partial differential equation （PDE） models the dynamics of the poloidal magnetic flux profile, which is used in this work to formulate a PDE-constrained op-timization problem under a quasi-static assumption. The minimum surface theory and constrained numeric optimization are then applied to achieve suboptimal solutions. Since the transient dy- namics is pre-given by the minimum surface theory, then this method can dramatically accelerate the solution process. In order to be robust under external uncertainties in real implementations, PID （proportional-integral-derivative） controllers are used to force the actuators to follow the computational input trajectories. It has the potential to implement in real-time for long time discharges by combining this method with the magnetic equilibrium update.

Decision-Making Model for Farmer Choosing Land Use Based upon Dynamic Optimization Theory

Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily applied, decision rules for farmer with a single static expectation were given.

A Stochastic Optimal Control Theory to Model Spontaneous Breathing

Respiratory variables, including tidal volume and respiratory rate, display significant variability. The probability density function (PDF) of respiratory variables has been shown to contain clinical information and can predict the risk for exacerbation in asthma. However, it is uncertain why this PDF plays a major role in predicting the dynamic conditions of the respiratory system. This paper introduces a stochastic optimal control model for noisy spontaneous breathing, and obtains a Shrödinger’s wave equation as the motion equation that can produce a PDF as a solution. Based on the lobules-bronchial tree model of the lung system, the tidal volume variable was expressed by a polar coordinate, by use of which the Shrödinger’s wave equation of inter-breath intervals (IBIs) was obtained. Through the wave equation of IBIs, the respiratory rhythm generator was characterized by the potential function including the PDF and the parameter concerning the topographical distribution of regional pulmonary ventilations. The stochastic model in this study was assumed to have a common variance parameter in the state variables, which would originate from the variability in metabolic energy at the cell level. As a conclusion, the PDF of IBIs would become a marker of neuroplasticity in the respiratory rhythm generator through Shr?dinger’s wave equation for IBIs.

ENVELOPING THEORY BASED METHOD FOR THE DETERMINATION OF PATH INTERVAL AND TOOL PATH OPTIMIZATION FOR SURFACE MACHINING

An enveloping theory based method for the determination of path interval in three axis NC machining of free form surface is presented, and a practical algorithm and the measures for improving the calculating efficiency of the algorithm are given. Not only the given algorithm can be used for ball end cutter, flat end cutter, torus cutter and drum cutter, but also the proposed method can be extended to arbitrary milling cutters. Thus, the problem how to strictly calculate path interval in the occasion of three axis NC machining of free form surfaces with non ball end cutters has been resolved effectively. On this basis, the factors that affect path interval are analyzed, and the methods for optimizing tool path are explored.

The Morphophonology of Moroccan Arabic Derived Causatives

This paper aims at investigating the morphophonological make-up of derived causatives in Moroccan Arabic within the framework of Optimality Theory (Prince &Smolensky, 2004). Causative verbs in MA are characterized by the systematic gemination of their medial consonants. However, it is not easy to determine the morphological nature of the causative morpheme involved in this derivation. Also, it is not clearly known why the causative morpheme gets realized exactly on the second segment of the base form.Therefore, we seek to achieve the following goals. First, we intend to determine the nature of the causative morpheme. Second, we aim to explain why the causative morpheme is realized on the second segment of the base form. In this respect, we show that the causative morpheme is represented by a featureless consonantal mora that targets the second segment of the base root, turning it into a geminate. We also show that the causative morpheme gets infixed thanks to the privileged status of root-initial segments.

Optimal design theories of tuned mass dampers with nonlinear viscous damping

Optimal design theory for linear tuned mass dampers （TMD） has been thoroughly investigated, but is still under development for nonlinear TMDs. In this paper, optimization procedures in the time domain are proposed for design of a TMD with nonlinear viscous damping. A dynamic analysis of a structure implemented with a nonlinear TMD is conducted first. Optimum design parameters for the nonlinear TMD are searched using an optimization method to minimize the performance index. The feasibility of the proposed optimization method is illustrated numerically by using the Taipei 101 structure implemented with TMD. The sensitivity analysis shows that the performance index is less sensitive to the damping coefficient than to the frequency ratio. Time history analysis is conducted using the Taipei 101 structure implemented with different TMDs under wind excitation. For both linear and nonlinear TMDs, the comfort requirements for building occupants are satisfied as long as the TMD is properly designed. It was found that as the damping exponent increases, the relative displacement of the TMD decreases but the damping force increases.

Energy Efficiency Maximization Strategy for Sink Node in SWIPT-Enabled Sensor-Cloud Based on Optimal Stopping Rules

Leveraging energy harvesting abilities in wireless network devices has emerged as an effective way to prolong the lifetime of energy constrained systems.The system gains are usually optimized by designing resource allocation algorithm appropriately.However,few works focus on the interaction that channel’s time-vary characters make the energy transfer inefficiently.To address this,we propose a novel system operation sequence for sensor-cloud system where the Sinks provide SWIPT for sensor nodes opportunistically during downlink phase and collect the data transmitted from sensor nodes in uplink phase.Then,the energy-efficiency maximization problem of the Sinks is presented by considering the time costs and energy consumption of channel detection.It is proved that the formulated problem is an optimal stopping process with optimal stopping rules.An optimal energy-efficiency(OEE)algorithm is designed to obtain the optimal stopping rules for SWIPT.Finally,the simulations are performed based on the OEE algorithm compared with the other two strategies to verify the effectiveness and gains in improving the system efficiency.

New development of theories in gas drilling

Theories established from engineering fundamentals have been of great value in supporting the design and execution of drilling operations in gas drilling where gas is used as a drilling fluid.This work presents an overview of new theories developed in recent years for special gas drilling operations including horizontal wells.These new theories are found in the areas of gas-mixture flow hydraulics in deviated and horizontal boreholes,hole cleaning of solids accumulation,hole cleaning of formation water,flow diverging for washout control,bit orifice optimization,and depression of formation water influx.This paper provides drilling engineers with updated mathematical models and methods for optimizing design to improve gas drilling performance.

Fuzzy linear model for production optimization of mining systems with multiple entities

Planning and production optimization within multiple mines or several work sites （entities） mining systems by using fuzzy linear programming （LP） was studied. LP is the most commonly used operations research methods in mining engineering. After the introductory review of properties and limitations of applying LP, short reviews of the general settings of deterministic and fuzzy LP models are presented. With the purpose of comparative analysis, the application of both LP models is presented using the example of the Bauxite Basin Niksic with five mines. After the assessment, LP is an efficient mathematical modeling tool in production planning and solving many other single-criteria optimization problems of mining engineering. After the comparison of advantages and deficiencies of both deterministic and fuzzy LP models, the conclusion presents benefits of the fuzzy LP model but is also stating that seeking the optimal plan of production means to accomplish the overall analysis that will encompass the LP model approaches.

Probing structural and electronic properties of divalent metal Mg_(n+1) and SrMgn (n=2–12) clusters and their anions

Divalent metal clusters have received great attention due to the interesting size-induced nonmetal-to-metal transition and fascinating properties dependent on cluster size,shape,and doping.In this work,the combination of the CALYPSO code and density functional theory(DFT)optimization is employed to explore the structural properties of neutral and anionic Mg_(n+1) and SrMgn(n=2-12)clusters.The results exhibit that as the atomic number of Mg increases,Sr atoms are more likely to replace Mg atoms located in the skeleton convex cap.By analyzing the binding energy,second-order energy difference and the charge transfer,it can be found the SrMg9 cluster with tower framework presents outstanding stability in a studied size range.Further,bonding characteristic analysis reveals that the stability of SrMg9 can be improved due to the strong s-p interaction among the atomic orbitals of Sr and Mg atoms.

Theoretical Study of Geometric Structures for Ground-state Al_nC(n=2-7) Clusters

With the aid of the molecular orbital DMol3 program,the energetics and electronic structures of several AlnC（n = 2-7） configurations have been searched and calculated by improved minimum energy paths（MEPs） by setting ＂imaging product＂.A new high symmetry,supervalence isomer of Al5C cluster,i.e.,D5h-Al5C,at the local minimum in the MEPs is detected.Several parameters,such as binding energy,HOMO-LUMO energy gap,vertical electron detachment energy and electron affinity energy,are calculated to characterize and evaluate the stability of three Al5C configurations,i.e.,D5h-Al5C,Cs-Al5C and C1-Al5C.The results show that the D5h-Al5C cluster is the ground state structure instead of Cs-Al5C.Due to the formation of many central σ bonds after polymerizing for D5h-Al5C,the decrease of the energy for HOMO orbit results in more territory for HOMO electrons of dislocation effect,then the energy difference between HOMO and LUMO is increasing to enhance the stability of molecules to produce such supervalence structure of Al5C cluster.The configuration evolution between D5h-Al5C,Cs-Al5C and C1-Al5C and the synthesis preference in the mode of Al5 ＋ C → Al5C reveals that the Cs-Al5C and C1-Al5C con-figurations are permissive to coexist with D5h-Al5C structure in energetics.

On the Connection between the Hamilton-Jacobi-Bellman and the Fokker-Planck Control Frameworks

In the framework of stochastic processes, the connection between the dynamic programming scheme given by the Hamilton-Jacobi-Bellman equation and a recently proposed control approach based on the Fokker-Planck equation is discussed. Under appropriate assumptions it is shown that the two strategies are equivalent in the case of expected cost functionals, while the Fokker-Planck formalism allows considering a larger classof objectives. To illustratethe connection between the two control strategies, the cases of an Itō stochastic process and of a piecewise-deterministic process are considered.

Yield Stress Prediction Model of RAFM Steel Based on the Improved GDM-SA-SVR Algorithm

With the development of society and the exhaustion of fossil energy,researcher need to identify new alternative energy sources.Nuclear energy is a very good choice,but the key to the successful application of nuclear technology is determined primarily by the behavior of nuclear materials in reactors.Therefore,we studied the radiation performance of the fusion material reduced activation ferritic/martensitic(RAFM)steel.The main novelty of this paper are the statistical analysis of RAFM steel data sets through related statistical analysis and the formula derivation of the gradient descent method(GDM)which combines the gradient descent search strategy of the Convex Optimization Theory to get the best value.Use GDM algorithm to upgrade the annealing stabilization process of simulated annealing algorithm.The yield stress performance of RAFM steel is successfully predicted by the hybrid model which is combined by simulated annealing(SA)with support vector machine(SVM)as the first time.The effect on yield stress by the main physical quantities such as irradiation temperature,irradiation dose and test temperature is also analyzed.The related prediction process is:first,we used the improved annealing algorithm to optimize the SVR model after training the SVR model on a training data set.Next,we established the yield stress prediction model of RAFM steel.The model can predict up to 96%of the data points with the prediction in the test set and the original data point in the 2range.The statistical test analysis shows that under the condition of confidence level=0.01,the calculation results of the regression effect significance analysis pass the T-test.

Riemann Hypothesis, Catholic Information and Potential of Events with New Techniques for Financial and Other Applications

In this research we are going to define two new concepts: a) “The Potential of Events” (EP) and b) “The Catholic Information” (CI). The term CI derives from the ancient Greek language and declares all the Catholic (general) Logical Propositions () which will true for every element of a set A. We will study the Riemann Hypothesis in two stages: a) By using the EP we will prove that the distribution of events e (even) and o (odd) of Square Free Numbers (SFN) on the axis Ax(N) of naturals is Heads-Tails (H-T) type. b) By using the CI we will explain the way that the distribution of prime numbers can be correlated with the non-trivial zeros of the function ζ(s) of Riemann. The Introduction and the Chapter 2 are necessary for understanding the solution. In the Chapter 3 we will present a simple method of forecasting in many very useful applications (e.g. financial, technological, medical, social, etc) developing a generalization of this new, proven here, theory which we finally apply to the solution of RH. The following Introduction as well the Results with the Discussion at the end shed light about the possibility of the proof of all the above. The article consists of 9 chapters that are numbered by 1, 2, …, 9.

On Optimal Sparse-Control Problems Governed by Jump-Diffusion Processes

A framework for the optimal sparse-control of the probability density function of a jump-diffusion process is presented. This framework is based on the partial integro-differential Fokker-Planck (FP) equation that governs the time evolution of the probability density function of this process. In the stochastic process and, correspondingly, in the FP model the control function enters as a time-dependent coefficient. The objectives of the control are to minimize a discrete-in-time, resp. continuous-in-time, tracking functionals and its L2- and L1-costs, where the latter is considered to promote control sparsity. An efficient proximal scheme for solving these optimal control problems is considered. Results of numerical experiments are presented to validate the theoretical results and the computational effectiveness of the proposed control framework.

The self-organizing worm algorithm

A new multi-modal optimization algorithm called the self-organizing worm algorithm （SOWA） is presented for optimization of multi-modal functions. The main idea of this algorithm can be described as follows： disperse some worms equably in the domain; the worms exchange the information each other and creep toward the nearest high point; at last they will stop on the nearest high point. All peaks of multi-modal function can be found rapidly through studying and chasing among the worms. In contrast with the classical multi-modal optimization algorithms, SOWA is provided with a simple calculation, strong convergence, high precision, and does not need any prior knowledge. Several simulation experiments for SOWA are performed, and the complexity of SOWA is analyzed amply. The results show that SOWA is very effective in optimization of multi-modal functions.

Skewperiodic Boundary Value Problems for Second Order Nonlinear Differential Equations

In this paper a uniqueness theorem for a skewperiodic boundary value problem is obtained. By using the optimal control method, we derive the best estimate for the integration mean ensuring that the results hold.