量化计算法在甲状腺功能亢进手术中的应用

目的用科学的方法计算出甲状腺功能亢进手术后腺体的残留量,减少术后复发和甲状腺功能减低的机会。方法把甲状腺功能亢进程度的高低,腺体的大小,促甲状腺激素分泌的多少设计出一个指数,利用三者指数的乘积来计算出术后残留量。结果手术138例,随访4年无复发及甲状腺功能减低发生。结论根据量化计算法结果确定甲状腺功能亢进术后腺体的残留量科学合理,容易掌握,效果好。

分割冻猪瘦肉卫生质量的量化考核

报告一种分割肉卫生质量合格率的计算方法,实践证明,此法可靠,可供借鉴。

Non-dominated sorting quantum particle swarm optimization and its application in cognitive radio spectrum allocation

In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed, and the performance of the NSQPSO is evaluated through five classical benchmark functions. The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value. Therefore, QPSO is used as the evolutionary method of the proposed NSQPSO. Also NSQPSO is used to solve cognitive radio spectrum allocation problem. The methods to complete spectrum allocation in previous literature only consider one objective, i.e. network utilization or fairness, but the proposed NSQPSO method, can consider both network utilization and fairness simultaneously through obtaining Pareto front solutions. Cognitive radio systems can select one solution from the Pareto front solutions according to the weight of network reward and fairness. If one weight is unit and the other is zero, then it becomes single objective optimization, so the proposed NSQPSO method has a much wider application range. The experimental research results show that the NSQPS can obtain the same non-dominated solutions as exhaustive search but takes much less time in small dimensions; while in large dimensions, where the problem cannot be solved by exhaustive search, the NSQPSO can still solve the problem, which proves the effectiveness of NSQPSO.

Research on C—C Bond Length Distribution in Hydrocarbon Molecules

The C--C bond dissociation energy （BDE） is a very important data in research of hydrocarbon cracking reactions, because it reflects the difficulty level of chemical reactions. But it is very difficult to obtain the C--C bond dissociation energy （BDE） by experiments, so using quantum chemistry calculation such as density functional theory （DFT） to study the C--C bond dissociation energy is a very useful means. The impact of acceptor substituents and donor substituents on the C--C bond length distribution was studied.

A simple method to extract glacier length based on Digital Elevation Model and glacier boundaries for simple basin type glacier

Glacier length is a key morphological element that has many glaciological applications; however, it is often difficult to determine, especially for glaciers that cover larger spatial areas or those that exhibit frequent temporal change. In this paper, we describe a new Arc GIS-based method that can derive glacier flow lines for determining glacier length based on digital elevation model and glacier outlines. This method involves(1) extraction of the highest and lowest points on a glacier,(2) calculation of 10-m contour lines on the glacier from 10 m to 100 m height, and(3) connection of the midpoints of each contour line with the highest and the lowest points in order to create a flow line, which is subsequently smoothed. In order to assess the reliability of this method, we tested the algorithm's results against flow lines calculated using field measurements, analysing data from the Chinese Glacier Inventory, and manual interpretation. These data showed that the new automated method is effective in deriving glacier flow lines when contour lines are relatively large; in particular, when they are between 70 m and 100 m. Nonetheless, a key limitation of the algorithm is the requirement to automatically delete repeated and closed curves in the pre-treatment processes. In addition to calculating glacier flow lines for derivation of glacier length, this method also can be used to effectively determine glacier terminus change.

PERFORMANCE COMPARISON OF A LINEARLY COMBINED ORDERED-STATISTIC DETECTORS UNDER POSTDETECTION INTEGRATION AND NONHOMOGENEOUS SITUATIONS

Several Constant False Alarm Rate （CFAR） architectures, where radar systems often employ them to automatically adapt the detection threshold to the local background noise or clutter power in an attempt to maintain an approximately constant rate of false alarm, have been recently proposed to estimate the unknown noise power level. Since the Ordered-Statistics （OS） based algorithm has some advantages over the Cell-Averaging （CA） technique, we are concerned here with this type of CFAR detectors. The Linearly Combined Ordered-Statistic （LCOS） processor, which sets threshold by processing a weighted ordered range samples within finite moving window, may actually perform somewhat better than the conventional OS detector. Our objective in this paper is to analyze the LCOS processor along with the conventional OS scheme for the case where the radar receiver incorporates a postdetection integrator amongst its contents and where the operating environments contain a number of secondary interfering targets along with the primary target of concern and the two target types fluctuate in accordance with the Swerling Ⅱ fluctuation model and to compare their performances under various operating conditions.

A topology optimization method based on element independent nodal density

A methodology for topology optimization based on element independent nodal density(EIND) is developed.Nodal densities are implemented as the design variables and interpolated onto element space to determine the density of any point with Shepard interpolation function.The influence of the diameter of interpolation is discussed which shows good robustness.The new approach is demonstrated on the minimum volume problem subjected to a displacement constraint.The rational approximation for material properties(RAMP) method and a dual programming optimization algorithm are used to penalize the intermediate density point to achieve nearly 0-1 solutions.Solutions are shown to meet stability,mesh dependence or non-checkerboard patterns of topology optimization without additional constraints.Finally,the computational efficiency is greatly improved by multithread parallel computing with OpenMP.

Discrete Differential Evolution for Mixed Discrete Non-Linear Problems

Differential evolution （DE） is a global optimizer for continuous design variables. To enhance DE, it is necessary to handle discrete design variables. In this paper, a discrete differential evolution （DDE） algorithm is proposed to handle discrete design variables The proposed DDE is based on the DE/l/rand/bin method. In the proposed DDE, the mutation ratio is regarded as the exchange probability, and thus, no modifications of DE/l/rand/bin are required. In addition, in order to maintain diversity through the search process, we initialize all search points. By introducing the initialization of all search points, global or quasi-optimum solution can be found. We validate the proposed DDE by applying it to several benchmark problems.

Detecting change in process systems with immunocomputing

Proposed a novel approach to detect changes in the product quality of process systems by using negative selection algorithms inspired by the natural immune system. The most important input variables of the process system was represented by artificial immune cells, from which product quality was inferred, instead of directly using the prod- uct quality which was hard to measure online, e.g. the ash content of coal flotation con- centrate. The experiment was presented and then the result was analyzed.

Spectroscopic Parameters of X^3∑^-, a^1△, and A^＇3△ Electronic States of SO Radical

The potential energy curves （PECs） of three low-lying electronic states （X^3∑, a^1△, and a^3△） of SO radical have been studied by ab initio quantum chemical method. The calcula- tions were carried out with the full valence complete active space self-consistent field method followed by the highly accurate valence internally contracted multireference configuration in- teraction （MRCI） approach in combination with correlation-consistent basis sets. Effects of the core-valence correlation and relativistic corrections on the PECs are taken into account. The core-valence correlation correction is carried out with the cc-pCVDZ basis set. The way to consider the relativistic correction is to use the second-order Douglas-Kroll Hamiltonian approximation, and the correction is performed at the level of cc-pV5Z basis set. To obtain more reliable results, the PECs determined by the MRCI calculations are also corrected for size-extensivity errors by means of the Davidson modification （MRCI＋Q）. These PECs are extrapolated to the complete basis set limit by the two-point energy extrapolation scheme. With these PECs, the spectroscopic parameters are determined.

Gravitational Contributions to Running of Gauge Couplings

Gravitational contributions to the running of gauge couplings are calculated by using different regularizationschemes.As the β function concerns counter-terms of dimension four, only quadratic divergences from the gravitationalcontributions need to be investigated.A consistent result is obtained by using a symmetry-preserving loop regularizationwith string-mode regulators which can appropriately treat the quadratic divergences and preserve non-abelian gaugesymmetry.The harmonic gauge condition for gravity is used in both diagrammatical and background field calculations,the resulting gravitational corrections to the β function are found to be nonzero, which is different from previous resultspresented in the existing literatures.

Energy optimization of representative barrier algorithms

Too high energy consumption is widely recognized to be a critical problem in large-scale parallel computing systems.The LogP-based energy-saving model and the frequency scaling method were proposed to reduce energy consumption analytically and systematically for other two representative barrier algorithms:tournament barrier and central counter barrier.Furthermore,energy optimization methods of these two barrier algorithms were implemented on parallel computing platform.The experimental results validate the effectiveness of the energy optimization methods.67.12% and 70.95% energy savings are obtained respectively for tournament barrier and central counter barrier on platforms with 2048 processes with 1.55%?8.80% performance loss.Furthermore,LogP-based energy-saving analytical model for these two barrier algorithms is highly accurate as the predicted energy savings are within 9.67% of the results obtained by simulation.

Calculation on model of weakening hydrogen bond of thick oil of petroleum

The process of use catalyst or functional material that contains iron ion to weaken -O-H-O- hydrogen bond of the thick oil to reduce viscidity or crack, in aspects of the ion charge. covalent bond order, total energy and the average distance of Fe-O. is studied with density function theory and discrete variational method （DFT-DVM）, one of the first principle methods. With the decrease of the distance of Fe-O. the charge of Fe ion increases, the charge of hydrogen ion decreases, and hydrogen bond is weakened. There are obvious and more stable effects to use the catalyst that contains multiple metal ions or increase the catalyst amount in weakening hydrogen bond of the thick oil. This theoretic work is helpful to exploit and process the thick oil of petroleum and maybe overcome the crisis of petroleum energy is approaching to us.

Patterning Nanoroads and Quantum Dots on Fluorinated Graphene

Using ab initio methods we have investigated the fluorination of graphene and find that different stoichiometric phases can be formed without a nucleation barrier, with the complete ＂2D-Teflon＂ CF phase being thermody- namically most stable. The fluorinated graphene is an insulator and turns out to be a perfect matrix-host for patterning nanoroads and quantum dots of pristine graphene. The electronic and magnetic properties of the nanoroads can be tuned by varying the edge orientation and width. The energy gaps between the highest occupied and lowest unoccupied molecular orbitals （HOMO-LUMO） of quantum dots are size-dependent and show a confinement typical of Dirac fermions. Furthermore, we study the effect of different basic coverage of F on graphene （with stoichiometries CF and C4F） on the band gaps, and show the suitability of these materials to host quantum dots of graphene with unique electronic properties.

Challenges and perspectives of combustion chemistry research

In the past decades, combustion chemistry research grew rapidly due to the development of combustion diagnostic methods,quantum chemistry methods, kinetic theory, and computational techniques. A lot of kinetic models have been developed for fuels from hydrogen to transportation fuel surrogates. Besides, multi-scale research method has been widely adopted to develop comprehensive models, which are expected to cover combustion conditions in real combustion devices. However, critical gaps still remain between the laboratory research and real engine application due to the insufficient research work on high pressure and low temperature combustion chemistry. Besides, there is also a great need of predictive pollutant formation model. Further development of combustion chemistry research depends on a closer interaction of combustion diagnostics, theoretical calculation and kinetic model development. This paper summarizes the recent progress in combustion chemistry research briefly and outlines the challenges and perspectives.

FIR Systems Identification Under Quantized Output Observations and a Large Class of Persistently Exciting Quantized Inputs

This paper investigates the FIR systems identification with quantized output observations and a large class of quantized inputs. The limit inferior of the regressors' frequencies of occurrences is employed to characterize the input's persistent excitation, under which the strong convergence and the convergence rate of the two-step estimation algorithm are given. As for the asymptotical efficiency,with a suitable selection of the weighting matrix in the algorithm, even though the limit of the product of the Cram′er-Rao(CR) lower bound and the data length does not exist as the data length goes to infinity, the estimates still can be asymptotically efficient in the sense of CR lower bound. A numerical example is given to demonstrate the effectiveness and the asymptotic efficiency of the algorithm.