试论景观规划的目标、任务和基本原则

试论景观规划的目标、任务和基本原则肖笃宁李晓文（中国科学院沈阳应用生态研究所，１１００１５）ＯｎｔｈｅＴａｒｇｅｔａｎｄＰｒｉｎｃｉｐｌｅｓｏｆＬａｎｄｓｃａｐｅＰｌａｎｎｉｎｇ．ＸｉａｏＤｕｎｉｎｇ，ＬｉＸｉａｏｗｅｎ（ＩｎｓｔｉｔｕｔｅｏｆＡｐ?..

地震波场延拓+菲涅尔体叠加方法及成像效果

In the increasingly enlarged exploration target, deep target layer(especially for the reservoir of lava) is a potential exploration area. As well known, the reflective energy becomes weak because the seismic signals of reflection in deep layer are absorbed and attenuate by upper layer. Caustics and multi-values traveltime in wavefield are aroused by the complexity of stratum. The ratio of signal to noise is not high and the fold numbers are finite(no more than 30). All the factors above affect the validity of conventional processing methods. So the high S/N section of stack can't always be got with the conventional stack methods even if the prestack depth migration is used. So it is inevitable to develop another kind of stack method instead. In the last a few years, the differential solution of wave equation was hold up by the condition of computation. Kirchhoff integral method rose in the initial stages of the ninetieth decade of last century. But there exist severe problems in it, which is are too difficult to resolve, so new method of stack is required for the oil and gas exploration. It is natural to think about upgrading the traditionally physic base of seismic exploration methods and improving those widely used techniques of stack. On the other hand, great progress is depended on the improvement in the wave differential equation prestack depth migration. The algorithm of wavefield continuation in it is utilized. In combination with the wavefield extrapolation and the Fresnel zone stack, new stack method is carried out It is well known that the seismic wavefield observed on surface comes from Fresnel zone physically, and doesn't comes from the same reflection points only. As to the more complex reflection in deep layer, it is difficult to describe the relationship between the reflective interface and the travel time. Extrapolation is used to eliminate caustic and simplify the expression of travel time. So the image quality is enhanced by Fresnel zone stack in target. Based on wave equation, high-frequency ray solution and its character are given to clarify theoretical foundation of the method. The hyperbolic and parabolic travel time of the reflection in layer media are presented in expression of matrix with paraxial ray theory. Because the reflective wave field mainly comes from the Fresnel Zone, thereby the conception of Fresnel Zone is explained. The matrix expression of Fresnel zone and projected Fresnel zone are given in sequence. With geometrical optics, the relationship between object point in model and image point in image space is built for the complex subsurface. The travel time formula of reflective point in the nonuniform media is deduced. Also the formula of reflective segment of zero-offset and nonzero offset section is provided. For convenient application, the interface model of subsurface and curve surface derived from conventional stacks DMO stack and prestack depth migration are analyzed, and the problem of these methods was pointed out in aspects of using data. Arc was put forward to describe the subsurface, thereby the amount of data to stack enlarged in Fresnel Zone. Based on the formula of hyperbolic travel time, the steps of implementation and the flow of Fresnel Zone stack were provided. The computation of three model data shows that the method of Fresnel Zone stack can enhance the signal energy and the ratio of signal to noise effectively. Practical data in Xui Jia Wei Zhi, a area in Daqing oilfield, was processed with this method. The processing results showed that the ability in increasing S/N ratio and enhancing the continuity of weak events as well as confirming the deep configuration of volcanic reservoir is better than others. In deeper target layer, there exists caustic caused by the complex media overburden and the great variation of velocity. Travel time of reflection can't be exactly described by the formula of travel time. Extrapolation is bring forward to resolve the questions above. With the combination of the phase operator and differential operator, extrapolating operator adaptable to the variation of lateral velocity is provided. With this method, seismic records were extrapolated from surface to any different deptlis below. Wave aberration and caustic caused by the inhomogenous layer overburden were eliminated and multi-value curve was transformed into the curve.of single value. The computation of Marmousi shows that it is feasible. Wave field continuation extends the Fresnel Zone stack's application.

A Soft Computing Approach to Acute Coronary Syndrome

Acute Coronary Syndrome (ACS) is transversal to a broad and heterogeneous set of human beings, and assumed as a serious diagnosis and risk stratification problem. Although one may be faced with or had at his disposition different tools as biomarkers for the diagnosis and prognosis of ACS, they have to be previously evaluated and validated in different scenarios and patient cohorts. Besides ensuring that a diagnosis is correct, attention should also be directed to ensure that therapies are either correctly or safely applied. Indeed, this work will focus on the development of a diagnosis decision support system in terms of its knowledge representation and reasoning mechanisms, given here in terms of a formal framework based on Logic Programming, complemented with a problem solving methodology to computing anchored on Artificial Neural Networks. On the one hand it caters for the evaluation of ACS predisposing risk and the respective Degree-of-Confidence that one has on such a happening. On the other hand it may be seen as a major development on the Multi-Value Logics to understand things and ones behavior. Undeniably, the proposed model allows for an improvement of the diagnosis process, classifying properly the patients that presented the pathology (sensitivity ranging from 89.7% to 90.9%) as well as classifying the absence of ACS (specificity ranging from 88.4% to 90.2%).

Test and evaluation system for multi-protocol sampled value protection schemes

Proposed transmission smart grids will use a digital platform for the automation of substations operating at voltage levels of 110 kV and above. The IEC 61850 series of standards, released in parts over the last ten years, provide a specification for substation communications networks and systems. These standards, along with IEEE Std 1588-2008 Precision Time Protocol version 2 (PTPv2) for precision timing, are recommended by the both IEC Smart Grid Strategy Group and the NIST Framework and Roadmap for Smart Grid Interoperability Standards for substation automation. IEC 61850-8-1 and IEC 61850-9-2 provide an inter-operable solution to support multi-vendor digital process bus solutions, allowing for the removal of potentially lethal voltages and damaging currents from substation control rooms, a reduction in the amount of cabling required in substations, and facilitates the adoption of non-conventional instrument transformers (NCITs). IEC 61850, PTPv2 and Ethernet are three complementary protocol families that together define the future of sampled value digital process connections for smart substation automation. This paper describes a specific test and evaluation system that uses real time simulation, protection relays, PTPv2 time clocks and artificial network impairment that is being used to investigate technical impediments to the adoption of SV process bus systems by transmission utilities. Knowing the limits of a digital process bus, especially when sampled values and NCITs are included, will enable utilities to make informed decisions regarding the adoption of this technology.

Value management in design planning : a systems-based framework for multi-disciplinary team involvement

This thesis investigates the Value Management processes used by construction project clients that effects project team involvement in VM workshops during the design stage of the projects. It is based on five case studies of the Malaysian international airport construction project packages. The focus of the research is on how issues related to infrastructure design that can improve construction processes on-site are being identified, analysed and resolved through multi-disciplinary team participation. The degrees of interaction, diversity of visualisation aids, certain cultural dimensions and the system thinking approach are found to have significant influence in maximizing participation among project team members during the entire VM workshop process.

Influence limitation in multi-campaign social networks: A Shapley value based approach

We investigate the problem of influence limitation in the presence of competing campaigns in a social network. Given a negative campaign which starts propagating from a specified source and a positive/counter campaign that is initiated, after a certain time delay, to limit the the influence or spread of misinformation by the negative campaign, we are interested in finding the top k influential nodes at which the positive campaign may be triggered. This problem has numerous applications in situations such as limiting the propagation of rumor, arresting the spread of virus through inoculation, initiating a counter-campaign against malicious propaganda, etc. The influence function for the generic influence limitation problem is non-submodular. Restricted versions of the influence limitation problem, reported in the literature, assume submodularity of the influence function and do not capture the problem in a realistic setting. In this paper, we propose a novel computational approach for the influence limitation problem based on Shapley value, a solution concept in cooperative game theory. Our approach works equally effectively for both submodular and non-submodular influence functions. Experiments on standard real world social network datasets reveal that the proposed approach outperforms existing heuristics in the literature. As a non-trivial extension, we also address the problem of influence limitation in the presence of multiple competing campaigns.

Value Estimation and Comparison in Multi-Attribute Choice

The following work explores the processes individuals utilize when making multi-attribute choices. With the exception of extremely simple or familiar choices, most decisions we face can be classified as multi-attribute choices. In order to evaluate and make choices in such an environment, we must be able to estimate and weight the particular attributes of an option. Hence, better understanding the mechanisms involved in this process is an important step for economists and psychologists. For example, when choosing between two meals that differ in taste and nutrition, what are the mechanisms that allow us to estimate and then weight attributes when constructing value? Furthermore, how can these mechanisms be influenced by variables such as attention or common physiological states, like hunger?

In order to investigate these and similar questions, we use a combination of choice and attentional data, where the attentional data was collected by recording eye movements as individuals made decisions. Chapter 1 designs and tests a neuroeconomic model of multi-attribute choice that makes predictions about choices, response time, and how these variables are correlated with attention. Chapter 2 applies the ideas in this model to intertemporal decision-making, and finds that attention causally affects discount rates. Chapter 3 explores how hunger, a common physiological state, alters the mechanisms we utilize as we make simple decisions about foods.

The mean value concept in mono-linear regression of multi-variables and its application to trace studies in geosciences

IEECAS SKLLQG

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multi-trait and random regression mature weight heritability and breeding value estimates in Nelore cattle

Mature weight breeding values were estimated using a multi-trait animal model (MM) and a random regression animal model (RRM). Data consisted of 82 064 weight records from 8 145 animals, recorded from birth to eight years of age. Weights at standard ages were considered in the MM. All models included contemporary groups as fixed effects, and age of dam (linear and quadratic effects) and animal age as covariates. In the RRM, mean trends were modelled through a cubic regression on orthogonal polynomials of animal age and genetic maternal and direct and maternal permanent environmental effects were also included as random. Legendre polynomials of orders 4, 3, 6 and 3 were used for animal and maternal genetic and permanent environmental effects, respectively, considering five classes of residual variances. Mature weight (five years) direct heritability estimates were 0.35 (MM) and 0.38 (RRM). Rank correlation between sires' breeding values estimated by MM and RRM was 0.82. However, selecting the top 2% (12) or 10% (62) of the young sires based on the MM predicted breeding values, respectively 71% and 80% of the same sires would be selected if RRM estimates were used instead. The RRM modelled the changes in the (co)variances with age adequately and larger breeding value accuracies can be expected using this model. © South African Society for Animal Science.

Limited predictive value of FDG-PET for response assessment in the preoperative treatment of esophageal cancer: results of a prospective multi-center trial (SAKK 75/02)

BACKGROUND: Only responding patients benefit from preoperative therapy for locally advanced esophageal carcinoma. Early detection of non-responders may avoid futile treatment and delayed surgery. PATIENTS AND METHODS: In a multi-center phase ll trial, patients with resectable, locally advanced esophageal carcinoma were treated with 2 cycles of induction chemotherapy followed by chemoradiotherapy (CRT) and surgery. Positron emission tomography with 2[fluorine-18]fluoro-2-deoxy-d-glucose (FDG-PET) was performed at baseline and after induction chemotherapy. The metabolic response was correlated with tumor regression grade (TRG). A decrease in FDG tumor uptake of less than 40% was prospectively hypothesized as a predictor for histopathological non-response (TRG > 2) after CRT. RESULTS: 45 patients were included. The median decrease in FDG tumor uptake after chemotherapy correlated well with TRG after completion of CRT (p = 0.021). For an individual patient, less than 40% decrease in FDG tumor uptake after induction chemotherapy predicted histopathological non-response after completion of CRT, with a sensitivity of 68% and a specificity of 52% (positive predictive value 58%, negative predictive value 63%). CONCLUSIONS: Metabolic response correlated with histopathology after preoperative therapy. However, FDG-PET did not predict non-response after induction chemotherapy with sufficient clinical accuracy to justify withdrawal of subsequent CRT and selection of patients to proceed directly to surgery.

The impact of learning outcomes in business education: assessing value, relevance and graduate ability in a multi-country study of employers and business graduates

This paper discusses critical findings from a two-year EU-funded research project involving four European countries: Austria, England, Slovenia and Romania. The project had two primary aims. The first of these was to develop a systematic procedure for assessing the balance between learning outcomes acquired in education and the specific needs of the labour market. The second aim was to develop and test a set of meta-level quality indicators aimed at evaluating the linkages between education and employment. The project was distinctive in that it combined different partners from Higher Education, Vocational Training, Industry and Quality Assurance. One of the key emergent themes identified in exploratory interviews was that employers and recent business graduates in all four countries want a well-rounded education which delivers a broad foundation of key business knowledge across the various disciplines. Both groups also identified the need for personal development in critical skills and competencies. Following the exploratory study, a questionnaire was designed to address five functional business areas, as well as a cluster of 8 business competencies. Within the survey, questions relating to the meta-level quality indicators assessed the impact of these learning outcomes on the workplace, in terms of the following: 1) value, 2) relevance and 3) graduate ability. This paper provides an overview of the study findings from a sample of 900 business graduates and employers. Two theoretical models are proposed as tools for predicting satisfaction with work performance and satisfaction with business education. The implications of the study findings for education, employment and European public policy are discussed.