Landscape Ecology:Coupling of Pattern,Process,and Scale

Landscape ecology provides new theoretical frameworks and methodologies for understanding complex ecological phenomena at multiple scales.Studies of landscape ecology focus on understanding the dynamics of eco-logical patterns and processes,and highlight the integration of multiple disciplines.In this paper,we discussed the problems and challenges that landscape ecology is currently facing,emphasizing the limitations of current methods used to describe dynamic landscape patterns and processes.We suggested that the focus should be on the integration of ground-based observation,mobile monitoring,transect survey,and remote-sensing monitoring,as well as improved coupling of experimental and model simulations.In addition,we outlined the research frontiers in landscape ecology,including scaling,integrated pattern and process modeling,and regional synthesis.Lastly,a brief review of pat-tern-process-scale coupling studies in China was provided.We concluded by pointing out that pattern-process-scale interactions,correlations between natural,economic,and social processes,and the coupling of human and natural systems will be major research areas in landscape ecology in the future.

An overview of the spatial patterns of land surface processes over arid and semiarid regions

With data from the project Collaborative Observation of Semi-arid/Arid Regions in North China, collected during July and September 2008, the spatial patterns of land surface processes over arid and semiarid regions have been investigated based on the ordinary Kriging interpolation approach. Generally, for the radiation processes, downward and upward short-wave radiation have a uniformly increasing trend with latitude, but the spatial patterns of long-wave radiation present notable regional differences: both upward and downward long-wave radiation increase with latitude in the west of North China, while in the east they vary inversely with latitude, suggesting surface temperature and clouds respectively have feedbacks to the long-wave radiation in the west and east of North China. The surface net radiation basically has a negative latitudinal trend. Long-wave radiation budget plays an important role in the spatial pattern of surface net radiation, particularly in the east of North China, although short-wave radiation budget largely determines the magnitude of surface net radiation. For the energy processes, latent and sensible heat flux varies conversely with latitude: more available land surface energy is consumed by evaporating soil water at lower latitudes while more is used for heating the atmosphere at higher latitudes. A soil heat flux maximum and minimum are found in Loess Plateau and Qinghai Plateau respectively, and a maximum is seen in the northeast China.

Modeling study on the flow patterns of gas–liquid flow for fast decarburization during the RH process

A water model and a high-speed video camera were utilized in the 300-t RH equipment to study the effect of steel flow patterns in a vacuum chamber on fast decarburization and a superior flow-pattern map was obtained during the practical RH process. There are three flow patterns with different bubbling characteristics and steel surface states in the vacuum chamber： boiling pattern（BP）, transition pattern（TP）, and wave pattern（WP）. The effect of the liquid-steel level and the residence time of the steel in the chamber on flow patterns and decarburization reaction were investigated, respectively. The liquid-steel level significantly affected the flow-pattern transition from BP to WP, and the residence time and reaction area were crucial to evaluate the whole decarburization process rather than the circulation flow rate and mixing time. A superior flow-pattern map during the practical RH process showed that the steel flow pattern changed from BP to TP quickly, and then remained as TP until the end of decarburization.

Dynamic evolution patterns of the degree of ground resistivity anisotropy and the sets mogenic process

Following a new train of thinking, this paper has explored first the potential information in the ground resistivitydata observed by the existing geoelectric observation system, investigated and proposed a new dimensionlessgeoelectric precursor factor, the degree of ground resistivity anisotropy, S, and studied the characteristics of dynamic evolution pattern of S during the seismogenic process. The results show that, during the seismogenic process, the degree of ground resistivity anisotropy (S) displays h process of 'normal' → 'abnormal strengthening(amplitude, range)' → 'abnormal weakening'→ 'earthquake occurrence'→ 'normal'. The earthquake wouldoccur at the time when the S value has entered the late stage of strengthening and turns to weaken and in the gradient belt on the margin ofS anomaly region. The dynamic evolution pattern ofS reflects the changes of the tectonicstress field during the seismogenic process. Therefore, it would be possible to trace the process of earthquake generation and occurrence from the dynamic evolution pattern ofS so as to service eaJ'thquake prediction.

Effect of process parameters on density of magnesium alloy parts by low-pressure expendable pattern casting

The combination of magnesium alloys with the low-pressure expendable pattern casting(LP-EPC) process would bright future for application of magnesium alloys. The researches are focused on the effect of process parameters on the internal casting quality of magnesium alloy parts. AZ91D magnesium alloy castings were produced for different combinations of the LP-EPC process parameters. Specifically,pouring temperature,vacuum,filling velocity and coupling action of these factors were manipulated to observe their effect on the casting porosity and density distribution. The results indicate that the pouring temperature with LP-EPC process is lower than it in gravity casting. The selected process parameters,such as vacuum,filling velocity and coupled modes of them,must ensure melt metal flowing front profile exhibiting smooth and convex shape. The optimal process parameters for the castings are pouring temperature 983-1 023 K,vacuum 0.02-0.03 MPa,filling velocity 60-95 mm/s,and simultaneous filling with sucking.

Experiments on Development of Channel Pattern in the Process of River Reformation

The changing of flow conditions caused by construction of hydro-projects will result in river's refor- mation and development of channel pattern.In this paper,the development of channel pattern in the process of reformation is studied by means of flume experiments.Influence of slope,grain size,angle-of-inflow,dis- charge and discharge process are comprehensively analyzed according to the experimental data.It was found that the channel would be widened as the river slope or discharge increased and grain s...

Metallogenic Processes:Evidencesfrom Zoning Patterns of Mineralization and alteration and fluid inclusion geochemistryin the Lehong Zn-Pb Deposit in Northeastern Yunnan, China

1 Introduction The large clusters of Zn-Pb deposits in northeastern Yunnan,located in the southwestern margin of the Yangtze Block,are an important part of the Sichuan-YunnanGuizhou Pb-Zn Poly-metallic Metallogenic Triangle Area

Effect of Vibrational Modes on Sand Pressure and Pattern Deformation in the EPC Process

During the EPC (expendable pattern casting) process, one of the essential requirements is to prevent pattern distortion duringsand filling and compaction. A new method which vibrates the system in a two-dimensional circular mode has been appliedto the EPC process. The molding properties of unbonded sand obtained by this new vibration mode are investigated andcompared with those in the one-dimensional vertical mode. For adequate compaction of sand. the circular vibration mode ismore effective than the vertical mode. Sand became more fluidized by the circular vibration and the particle pressure coefficientwas close to unity The particle pressure coefficient, which is defined as the ratio of horizontal to vertical sand pressure, isresponsible for the effectiveness of sand filling.

APPEARANCE PATTERN OF TOOTH GERMS WITH DEVELOPMENTAL PROCESS IN MYLOPHARYNGODON PICEUS

The pharyngeal dental formula of Mylopharyngodon piceus is 4-5 as a rule, and the dentition isasymmetrical. It is difficult to identify each tooth in the larval dentition. In this paper the appearancepattem of tooth germ with developmental process in this fish is described in detail. The formationpattern of the left dentition is contrasted with that of the right one. In the developmental process,the left pharyngeal dentition lacks teeth at position An3. Thus the left dentition is D-type as designatedby Nakajima(1984), while the right one is A-type.

Optimization and Process Design Tools for Estimation of Weekly Exposure to Air Pollution Integrating Travel Patterns during Pregnancy

A growing number of international studies have highlighted that ambient air pollution exposures are related to different health outcomes. To do so, researchers need to estimate exposure levels to air pollution throughout everyday life. In the literature, the most commonly used estimate is based on home address only or taking into account, in addition, the work address. However, several studies have shown the importance of daily mobility in the estimate of exposure to air pollutants. In this context, we developed an R procedure that estimates individual exposures combining home addresses, several important places, and itineraries of the principal mobility during a week. It supplies researchers a useful tool to calculate individual daily exposition to air pollutants weighting by the time spent at each of the most frequented locations (work, shopping, residential address, etc.) and while commuting. This task requires the efficient calculation of travel time matrices or the examination of multimodal transport routes. This procedure is freely available from the Equit’Area project website: (https://www.equitarea.org). This procedure is structured in three parts: the first part is to create a network, the second allows to estimate main itineraries of the daily mobility and the last one tries to reconstitute the level of air pollution exposure. One main advantage of the tool is that the procedure can be used with different spatial scales and for any air pollutant.

Modal Frequency Prediction of Chladni Patterns Using Machine Learning

The introduction of machine learning (ML) in the research domain is a new era technique. The machine learning algorithm is developed for frequency predication of patterns that are formed on the Chladni plate and focused on the application of machine learning algorithms in image processing. In the Chladni plate, nodes and antinodes are demonstrated at various excited frequencies. Sand on the plate creates specific patterns when it is excited by vibrations from a mechanical oscillator. In the experimental setup, a rectangular aluminum plate of 16 cm x 16 cm and 0.61 mm thickness was placed over the mechanical oscillator, which was driven by a sine wave signal generator. 14 Chladni patterns are obtained on a Chladni plate and validation is done with modal analysis in Ansys. For machine learning, a large number of data sets are required, as captured around 200 photos of each modal frequency and around 3000 photos with a camera of all 14 Chladni patterns for supervised learning. The current model is written in Python language and model has one convolution layer. The main modules used in this are Tensor Flow Keras, NumPy, CV2 and Maxpooling. The fed reference data is taken for 14 frequencies between 330 Hz to 3910 Hz. In the model, all the images are converted to grayscale and canny edge detected. All patterns of frequencies have an almost 80% - 99% correlation with test sample experimental data. This approach is to form a directory of Chladni patterns for future reference purpose in real-life application. A machine learning algorithm can predict the resonant frequency based on the patterns formed on the Chladni plate.

Facies and Fracture Network Modeling by a Novel Image Processing Based Method

A wide range of methods for geological reservoir modeling has been offered from which a few can reproduce complex geological settings, especially different facies and fracture networks. Multi Point Statistic (MPS) algorithms by applying image processing techniques and Artificial Intelligence (AI) concepts proved successful to model high-order relations from a visually and statistically explicit model, a training image. In this approach, the patterns of the final image (geological model) are obtained from a training image that defines a conceptual geological scenario for the reservoir by depicting relevant geological patterns expected to be found in the subsurface. The aim is then to reproduce these training patterns within the final image. This work presents a multiple grid filter based MPS algorithm to facies and fracture network images reconstruction. Processor is trained by training images (TIs) which are representative of a spatial phenomenon (fracture network, facies...). Results shown in this paper give visual appealing results for the reconstruction of complex structures. Computationally, it is fast and parsimonious in memory needs.

Automated Identification of Basic Control Charts Patterns Using Neural Networks

The identification of control chart patterns is very important in statistical process control. Control chart patterns are categorized as natural and unnatural. The presence of unnatural patterns means that a process is out of statistical control and there are assignable causes for process variation that should be investigated. This paper proposes an artificial neural network algorithm to identify the three basic control chart patterns;natural, shift, and trend. This identification is in addition to the traditional statistical detection of runs in data, since runs are one of the out of control situations. It is assumed that a process starts as a natural pattern and then may undergo only one out of control pattern at a time. The performance of the proposed algorithm was evaluated by measuring the probability of success in identifying the three basic patterns accurately, and comparing these results with previous research work. The comparison showed that the proposed algorithm realized better identification than others.

Process Optimization for AZ91 Mg-alloy Low-pressure EPC Process

The influence of a key process variable on the mold filling characteristics of AZ91 Mg-alloy was studied in the low pressure EPC process.The applied flow quantity of insert gas from 1 to 5 m~3/h associated with the pressurizing rate in the low pressure EPC casting process was considered for rectangle and L-shape plate casting. The experimental results show that there is an optimal flow quantity of insert gas for good mold filling characteristics in AZ91 Mg-alloy low-pressure EPC process. The optimal flow quantity of insert gas for the specimens is 3 to 4 m~3/h. Either less or higher than the optimal flow quantity of insert gas would lead to misrun defects or folds, blisters and porosity defects. The practice of hub casting confirmed that the low-pressure EPC process with an optimal processing variable exemplified as 4 m~3/h gas flow quantity was capable of producing complicated magnesium castings without misrun defects.

IMAGE DATABASE FOR PATTERN DESIGN SYSTEM

This paper discusses a pattern design system in textile industry,the establishment of an imagedatabase which is used to store various kinds of source materials for designers’ reference in order tospeed up design process.Pattern design image database (PDIDB) runs on the double-machine hardware system com-posed of ALTOS-986 and IBM PC/XT microcomputer.The former (host) manages imagedatabase,and the latter works both as a terminal to operate PDIDB and as an image processingstation to input,output,edit and display image data.PDIDB has two mainparts,the image storage management system and the image attributemanagement system and provides some functions,such as retrieval,deleting and updating.

Spatial analysis of plant detritus processing in a Mediterranean River type: the case of the River Tirso Basin, Sardinia, Italy

The river continuum concept represents the most general framework addressing the spatial variation of both structure and function in river ecosystems. In the Mediterranean ecoregion, summer drought events and dams constitute the main sources of local disturbance to the structure and functioning of river ecosystems occurring in the river basin. In this study, we analysed patterns of spatial variation of detritus processing in a 7th order river of the Mediterranean ecoregion(River Tirso, Sardinia-Italy) and in three 4th order sub-basins which were exposed to different summer drought pressures. The study was carried out on Phragmites australis and Alnus glutinosa leaf detritus at 31 field sites in seasonal field experiment Detritus processing rates were higher for Alnus glutinosa than for Phragmites australis plant detritus. Processing rates of Alnus glutinosa leaves varied among seasons and study sites from 0.006 d -1 to 0.189 d -1 and those of Phragmites australis leaves ranged from 0.0008 d -1 to 0.102 d -1, with the lowest values occurring at sites exposed to summer drought. Seasons and sites accounted for a significant proportion of such variability. Alder detritus decay rates generally decreased with increasing stream order, while reed detritus decay rates generally increased on the same spatial gradient. Summer drought events affected these spatial patterns of variation by influencing significantly the decay rates of both plant detritus. The comparisons among and within sub-basins showed strong negative influence of summer drought on detritus processing rates. Similarly, in the entire River Tirso basin decay rates were always lower at disturbed than at undisturbed sites for each stream order; decay rates of reed detritus remained lower at those sites even after the end of the disturbance events, while alder decay rates recovered rapidly from the summer drought perturbations. The different recovery of the processing rates of the two leaves could also explain the different patterns of spatial variation observed between the two leaves.

A New Image Processing Algorithm for Log Cross Section Image

With characteristics of log cross-section image taken into consideration,this paper presents a new image processing algorithm for recognization and measurement of log cross sections,by which the number and area of quasi-circular log cross sections can be calculated automatically,thereby obtaining the total cross-section area and log volume.

组织变革情境下高管团队断层激活过程的多案例研究

基于组织变革情境,以5家存在高管团队断层现象的企业为研究对象,采用探索性多案例研究方法,运用扎根理论构建组织变革中高管团队断层激活过程与激活模式模型。研究结果表明:组织变革背景下,高管团队断层涉及利益相关断层、权威特征断层及信息认知断层3种类型;三者的激活过程均体现为高管团队构成因素与结构因素在情境因素的催化下引起成员的亚群体归类行为,进而激活断层;三者在断层激活的条件基础和情境动力方面又存在一定差异性,分别侧重于利益要素、资源要素和信息要素驱动断层激活过程;不同类型断层间还存在交互作用,导致各高管团队断层强度呈现明显不同,依据成员间的分化程度可能呈现出平稳式、分化式、激化式3种激活模式。

小波分析概述:从信号处理的视角

本文从信号处理的视角对20世纪80年代末兴起的小波分析做一个通俗的概述.内容包括小波分析产生的基本问题背景和关键历史事件,小波分析的基本理论,及其对信号处理的意义和作用.希望透过本文能科普性地展示小波的基本理论以及为什么要建立这样的理论.除此以外,笔者还对小波分析之后时频分析领域所出现的经验模型分解方法和图信号处理的基本问题给出简要的介绍.作为中山大学百年校庆的约稿综述,本文对中山大学小波分析研究团队的基本阵容以及历年来所开展的重要学术事件进行了简单的回顾.