THE GLOBAL AND LOCAL C^(2)-SOLUTIONS FOR THE WAVE EQUATION □u = G(u_t, Du) IN THREE SPACE DIMENSIONS

Kunio Hidano[4] has shown that the global and local C2-solutions for semilinear wave equations with spherical symmetry in three space dimensions. This paper studies the global and local C2-solutions for the semilinear wave equations without spherical symmetry in three space dimensions. A problem put forward by Hiroyuki Takamura[2] is partially answered.

The Two Faces of Urbanity： Exploring Global and Local Values---Two Urban Studios in Taksim Square and along the Shores of the Golden Horn in Istanbul

Since the 18th century, the irritating but also fascinating scenes of urbanity--a complex phenomenon with cultural, social, political, economic, temporal, spatial, functional, and formal dimensions--have been described in literary works. Many seemingly opposite facts, such as individuality/society, freedom/loneliness/socialization, anonymity/strangeness/identity/belonging, diversity/chaos/segregation, indifferent city-dweller/initiative citizenship, have been revealed through literary works, travel and utopian writing, urban theories, scientific studies, manifestos, and newspaper articles. On the one hand, there are those who advocate a life outside the city because they consider the problems produced by the city and the phenomenon of density which they perceive merely in quantitative terms, as unsolvable problems. On the other hand, there are those who see the production of loose urban fabric as a solution or those who accept the （seemingly） opposite facts of urbanity as positive values and therefore support city life. All of these ideas are still as actual today as they were in the past. We are often unable to use our citizen rights to the city, to encounter different classes （social/etlmic/religious）, to experience heterogeneity as an aspect inherent in city life and in the route of our daily life--following the orders of the capitalist system mainly organized around work--and we are often drawn into the same districts on the same paths. Our perception of our urban environments may get monotonous and shallow, but the irritating yet fascinating features of the first big cities still exist and may be grasped and brought into consciousness. Throughout their architectural education, especially in urban design studios, students can be encouraged to investigate the rhythm of their daily life, the conditions of their urban environments, and discovering the city as an intellectual and sensual programme, so that the phenomenon of urbanity can be grasped not just on formal, but on various other dimensions as well. This study focuses on the process and outcomes of two urban studios located in Taksim Square and along the shores of the Golden Horn in Istanhul. Taking the multidimensional content of urbanity into account, acquired theoretically through literary works and studies on urban planning and its history, the main aim of these studios has been the phenomenological understanding of the dynamic content of urbanity by the students. Through creative analysis of permanent/temporary spaces engendered by the diversity of user profiles and actions discovered on phenomenological excursions, students examine the qualitative values of density and global and local dynamics. We believe that designing spaces as ＂prototypes＂ helps highlight the multidimensional content of urbanity. The present study aims not only to highlight the multidimensional content of urbanity, but also to encourage its discussion in architectural design education and to emphasize the positive contribution of theoretical readings and phenomenological studies to urban design studios. The present study also aims to emphasize the beneficial correlation of global and local dynamics as the two faces of urbanity; important more than ever for the big cities of the 21 st century if we advocate for a vivid and resilient city life and citizens.

Object tracking method based on joint global and local feature descriptor of 3D LIDAR point cloud

To fully describe the structure information of the point cloud when the LIDAR-object distance is long,a joint global and local feature(JGLF)descriptor is constructed.Compared with five typical descriptors,the object recognition rate of JGLF is higher when the LIDAR-object distances change.Under the situation that airborne LIDAR is getting close to the object,the particle filtering(PF)algorithm is used as the tracking frame.Particle weight is updated by comparing the difference between JGLFs to track the object.It is verified that the proposed algorithm performs 13.95%more accurately and stably than the basic PF algorithm.

Unsupervised Nonlinear Adaptive Manifold Learning for Global and Local Information

In this paper,we propose an Unsupervised Nonlinear Adaptive Manifold Learning method(UNAML)that considers both global and local information.In this approach,we apply unlabeled training samples to study nonlinear manifold features,while considering global pairwise distances and maintaining local topology structure.Our method aims at minimizing global pairwise data distance errors as well as local structural errors.In order to enable our UNAML to be more efficient and to extract manifold features from the external source of new data,we add a feature approximate error that can be used to learn a linear extractor.Also,we add a feature approximate error that can be used to learn a linear extractor.In addition,we use a method of adaptive neighbor selection to calculate local structural errors.This paper uses the kernel matrix method to optimize the original algorithm.Our algorithm proves to be more effective when compared with the experimental results of other feature extraction methods on real face-data sets and object data sets.

A Quadratically Approximate Framework for Constrained Optimization,Global and Local Convergence

This paper presents a quadratically approximate algorithm framework （QAAF） for solving general constrained optimization problems, which solves, at each iteration, a subproblem with quadratic objective function and quadratic equality together with inequality constraints. The global convergence of the algorithm framework is presented under the Mangasarian-Fromovitz constraint qualification （MFCQ）, and the conditions for superlinear and quadratic convergence of the algorithm framework are given under the MFCQ, the constant rank constraint qualification （CRCQ） as well as the strong second-order sufficiency conditions （SSOSC）. As an incidental result, the definition of an approximate KKT point is brought forward, and the global convergence of a sequence of approximate KKT points is analysed.

Global And Local

Robert Walters Delivers Professional Service and Ideas to Chinese Market Robert Walters,a global leading specialist recruitment consultancy,held an Annual Client Event in Beijing on November 16,at which a lot of colleagues and industry peers had a talk face to face about China’s recruitment market.

Dispersion of ventricular repolarization: Temporal and spatial

Repolarization heterogeneity(RH)is an intrinsic property of ventricular myocardium and the reason for T-wave formation on electrocardiogram(ECG).Exceeding the physiologically based RH level is associated with appearance of life-threatening ventricular arrhythmias and sudden cardiac death.In this regard,an accurate and comprehensive evaluation of the degree of RH parameters is of importance for assessment of heart state and arrhythmic risk.This review is devoted to comprehensive consideration of RH phenomena in terms of electrophysiological processes underlying RH,cardiac electric field formation during ventricular repolarization,as well as clinical significance of RH and its reflection on ECG parameters.The formation of transmural,apicobasal,left-toright and anterior-posterior gradients of action potential durations and end of repolarization times resulting from the heterogenous distribution of repolarizing ion currents and action potential morphology throughout the heart ventricles,and the different sensitivity of myocardial cells in different ventricular regions to the action of pharmacological agents,temperature,frequency of stimulation,etc.,are being discussed.The review is focused on the fact that RH has different aspects–temporal and spatial,global and local;ECG reflection of various RH aspects and their clinical significance are being discussed.Strategies for comprehensive assessment of ventricular RH using different ECG indices reflecting various RH aspects are presented.

Multi-Label Learning Based on Transfer Learning and Label Correlation

In recent years,multi-label learning has received a lot of attention.However,most of the existing methods only consider global label correlation or local label correlation.In fact,on the one hand,both global and local label correlations can appear in real-world situation at same time.On the other hand,we should not be limited to pairwise labels while ignoring the high-order label correlation.In this paper,we propose a novel and effective method called GLLCBN for multi-label learning.Firstly,we obtain the global label correlation by exploiting label semantic similarity.Then,we analyze the pairwise labels in the label space of the data set to acquire the local correlation.Next,we build the original version of the label dependency model by global and local label correlations.After that,we use graph theory,probability theory and Bayesian networks to eliminate redundant dependency structure in the initial version model,so as to get the optimal label dependent model.Finally,we obtain the feature extraction model by adjusting the Inception V3 model of convolution neural network and combine it with the GLLCBN model to achieve the multi-label learning.The experimental results show that our proposed model has better performance than other multi-label learning methods in performance evaluating.

Global parameter estimation of the Cochlodinium polykrikoides model using bioassay data

Cochlodinium polykrikoides is a notoriously harmful algal species that inflicts severe damage on the aquacultures of the coastal seas of Korea and Japan. Information on their expected movement tracks and boundaries of influence is very useful and important for the effective establishment of a reduction plan. In general, the information is supported by a red-tide（a.k.a algal bloom） model. The performance of the model is highly dependent on the accuracy of parameters, which are the coefficients of functions approximating the biological growth and loss patterns of the C. polykrikoides. These parameters have been estimated using the bioassay data composed of growth-limiting factor and net growth rate value pairs. In the case of the C. polykrikoides, the parameters are different from each other in accordance with the used data because the bioassay data are sufficient compared to the other algal species. The parameters estimated by one specific dataset can be viewed as locally-optimized because they are adjusted only by that dataset. In cases where the other one data set is used, the estimation error might be considerable. In this study, the parameters are estimated by all available data sets without the use of only one specific data set and thus can be considered globally optimized. The cost function for the optimization is defined as the integrated mean squared estimation error, i.e., the difference between the values of the experimental and estimated rates. Based on quantitative error analysis, the root-mean squared errors of the global parameters show smaller values, approximately 25%–50%, than the values of the local parameters. In addition, bias is removed completely in the case of the globally estimated parameters. The parameter sets can be used as the reference default values of a red-tide model because they are optimal and representative. However, additional tuning of the parameters using the in-situ monitoring data is highly required.As opposed to the bioassay data, it is necessary because the bioassay data have limitations in terms of the in-situ coastal conditions.

Spatial modeling of the carbon stock of forest trees in Heilongjiang Province, China

Heilongjiang province is the largest forest zone in China and the forest coverage rate is 46%. Forests of Heilongjiang province play an important role in the forest ecosystem of China. In this study we investi- gated the spatial distribution of forest carbon storage in Heilongjiang province using 3083 plots sampled in 2010. We attempted to fit two global models, ordinary least squares model （OLS）, linear mixed model （LMM）, and a local model, geographically weighted regression model （GWR）, to the relationship between forest carbon content and stand, environment, and climate factors. Five predictors significantly affected forest carbon storage and spatial distribution, viz. average diameter of stand （DBH）, number of trees per hectare （TPH）, elevation （Elev）, slope （Slope） and the product of precipitation and temperature （Rain Temp）. The GWR model outperformed the two global models in both model fitting and prediction because it successfully reduced both spatial auto- correlation and heterogeneity in model residuals. More importantly, the GWR model provided localized model coefficients for each location in the study area, which allowed us to evaluate the influences of local stand conditions and topographic features on tree and stand growth, and forest carbon stock. It also helped us to better understand the impacts of silvi- cultural and management activities on the amount and changes of forest carbon storage across the province. The detailed information can be readily incorporated with the mapping ability of GIS software to provide excellent tools for assessing the distribution and dynamics of the for- est-carbon stock in the next few years.

Novel Adaptive Binarization Method for Degraded Document Images

Achieving a good recognition rate for degraded document images is difficult as degraded document images suffer from low contrast,bleedthrough,and nonuniform illumination effects.Unlike the existing baseline thresholding techniques that use fixed thresholds and windows,the proposed method introduces a concept for obtaining dynamic windows according to the image content to achieve better binarization.To enhance a low-contrast image,we proposed a new mean histogram stretching method for suppressing noisy pixels in the background and,simultaneously,increasing pixel contrast at edges or near edges,which results in an enhanced image.For the enhanced image,we propose a new method for deriving adaptive local thresholds for dynamic windows.The dynamic window is derived by exploiting the advantage of Otsu thresholding.To assess the performance of the proposed method,we have used standard databases,namely,document image binarization contest(DIBCO),for experimentation.The comparative study on well-known existing methods indicates that the proposed method outperforms the existing methods in terms of quality and recognition rate.

Detailed Quantum Mechanical QSAR Analysis of Certain Aminopyrimidoisoquinolinequinones with Anticancer Activity

A detailed quantum mechanical analysis of electronic disposition of five aminopyrimidoisoquinolinequinones (APIQs) was performed after extraction of this subset of compounds from a larger data set of APIQs via a reported clustering methodology (Elfaki, et al. 2020). Both semi empirical PM3 method and DFT quantum mechanical methods were used to calculate global and local quantum mechanical descriptors (QMDs) to define the electronic environment of these molecules in attempt to rationalize their observed anti-cancer response variability. The biological response is the anticancer activity against human gastric adenocarcenoma (AGS) cell line. The correlation matrix between the calculated global electronic descriptors and biological activity demonstrated that the global dipole moment gives the highest correlation. The local electronic environment was analysed by The Mullikan charges (MC) and Fukui functions for N-5, C-6, C-8 in addition to the N atom of phenylamino side group at C-8. MCs furnished no useful information as each of these atoms had almost identical MC values for all the five compounds with exception of C-6 which gave varied values. Regressing MCs of C-6 against the response traces 60% of the latter variability. As C-6 is an extra annular methyl carbon adjacent to N-5 in isoquinoline residue of APIQ, we reasoned that the chemical reactivities of 4 out of the 5 APIQs might be due to a Chichibabin-type tautomerism implying a possible alkylation aspect in their mechanism of action. The corresponding Fukui functions (f-, f+ and f0) showed a considerable consistency with the patterns of chemical reactivity exhibited by this small set of APIQs.

Bioimage-based protein subcellular location prediction： a comprehensive review

Subcellular localization of proteins can provide key hints to infer their functions and structures in cells. With the breakthrough of recent molecule imaging techniques, the usage of 2D bioimages has become increasingly popular in automatically analyzing the protein subcellular location pat- terns. Compared with the widely used protein 1D amino acid sequence data, the images of protein distribution are more intuitive and interpretable, making the images a better choice at many applications for revealing the dynamic char- acteristics of proteins, such as detecting protein translocation and quantification of proteins. In this paper, we systemati- cally reviewed the recent progresses in the field of automated image-based protein subcellular location prediction, and clas- sified them into four categories including growing of bioim- age databases, description of subcellular location distribution patterns, classification methods, and applications of the pre- diction systems. Besides, we also discussed some potential directions in this field.

On the Cauchy problem for a doubly nonlinear degenerate parabolic equation with strongly nonlinear sources

In this article, we consider the existence of local and global solution to the Cauchy problem of a doubly nonlinear equation. By introducing the norms |||f||| h and 〈f〉h, we give the sufficient and necessary conditions on the initial value to the existence of local solution of doubly nonlinear equation. Moreover some results on the global existence and nonexistence of solutions are considered.

A TRUST-REGION METHOD FOR NONSMOOTH NONCONVEX OPTIMIZATION

We propose a trust-region type method for a class of nonsmooth nonconvex optimization problems where the objective function is a summation of a(probably nonconvex)smooth function and a(probably nonsmooth)convex function.The model function of our trust-region subproblem is always quadratic and the linear term of the model is generated using abstract descent directions.Therefore,the trust-region subproblems can be easily constructed as well as efficiently solved by cheap and standard methods.When the accuracy of the model function at the solution of the subproblem is not sufficient,we add a safeguard on the stepsizes for improving the accuracy.For a class of functions that can be“truncated”,an additional truncation step is defined and a stepsize modification strategy is designed.The overall scheme converges globally and we establish fast local convergence under suitable assumptions.In particular,using a connection with a smooth Riemannian trust-region method,we prove local quadratic convergence for partly smooth functions under a strict complementary condition.Preliminary numerical results on a family of Ei-optimization problems are reported and demonstrate the eficiency of our approach.