特色小镇的特色化策略

特色小镇作为中国新型城镇化、城乡融合发展的攻坚突破口,关键在于特色。“特色”有别于“特点”,其评判有多方面的标准,具体把握较为复杂。以此为背景,从特色小镇的内涵特征与现存问题出发,在分析探讨特色思维的局限性、发展非线性、不确定性、特色活态性等深层命题的基础上,提出特色小镇的特色化不只在于区域性差异化、理想性差异化,还在于规划控制体系的前馈性差异化、在历史长河与竞争过程中适应性选择的差异化。因此,需要完善周期管控机制、市场采纳机制,采用历史评判法、评特为主评优为辅等特别的对策措施和评选标准。最后,围绕特色化策略的逻辑主线—促进中国城乡发展智慧地走上适应性之道,从5个领域具体探讨了产业特色化、环境与社区特色化、文化特色化、设施与服务特色化、体制机制创新等若干对策。     

Suitability for conservation as a criterion in regional conservation network selection

The process of selecting candidate areas for inclusion in a regional conservation network should include not only delineating appropriate land units for selection and defining targets for representing features of interest, but also determining the suitability of land units for conservation purposes. We developed an explicit rating of conservation suitability by applying fuzzy-logic functions in a knowledge base to ecological condition and socio-economic attributes of land units in the interior Columbia River basin, USA. Suitability was converted to unsuitability to comprise a cost criterion in selecting regional conservation networks. When unsuitability was the sole cost criterion or was combined with land area as cost, only about one-third of the area selected was rated suitable, due to inclusion of unsuitable land to achieve representation of conservation targets (vegetation cover-type area). Selecting only from land units rated suitable produced networks that were 100% suitable, reasonably efficient, and most likely to be viable and defensible, as represented in our knowledge-based system. However, several conservation targets were not represented in these networks. The tradeoff between suitability and effectiveness in representing targets suggests that a multi-stage process should be implemented to address both attributes of candidate conservation networks. The suitability of existing conservation areas was greater than that of most alternative candidate networks, but 59% of land units containing conservation areas received a rating of unsuitable, due in part to the presence of units only partially occupied by conservation areas, in which unsuitability derived from conditions in non-conserved areas.     

Using crisp and fuzzy modelling to identify favourability hotspots useful to perform gap analysis

In this study, we propose the use of a favourability function to perform Gap Analysis. To exemplify this, we modelled the distribution of terrestrial mammal species in Andalusia (South of Spain) on the basis of their presence/absence on a grid of 10 km × 10 km UTM cells (n = 961). Using logistic regression and 30 variables related with the environment, space and human influence, we obtained probabilities of occurrence for each species in each cell. We computed a crisp favourability index considering the areas as favourable or unfavourable for a species if the probability of occurrence was higher or lower than the species prevalence, respectively. We also used a favourability function and fuzzy logic to level all species to the same threshold of favourability, which allowed to compare and to combine species distributions. Adding up the fuzzy favourability values for each species in each cell we obtained a fuzzy favourability index that we compared with species richness (sum of species in each cell) and with the crisp favourability index. We performed Gap Analysis by overlapping these results with the current reserve network of Andalusia. Gaps were grouped in fewer and bigger zones after applying the favourability indices. Considerations and recommendations for the use of the favourability function to select areas of conservation interest are discussed.     

A Fuzzy Reed–Frost Model for Epidemic Spreading

In this paper, we present a fuzzy approach to the Reed–Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed–Frost generalization.     

The universal fuzzy logical framework of neural cir-cuits and its application in modeling primary visual cortex

Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. Al- though there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.     

乙型肝炎病毒前S1抗原与HBV血清标志物同时检测及临床意义

目的 :了解前S1抗原与HBV血清标志物的关系。方法 :采用ELSIA方法同时检测 2 1 0 1例乙型肝炎病毒感染者的前S1抗原和HBV血清标志物。结果 :2 9例HBsAg( )、HBeAg( )标本中 ,有 2 8例前S1抗原阳性 ,阳性率 96.5 5 % ;784例HBsAg( )、HBeAg( )、抗HBc( )标本中 ,有 679例前S1抗原阳性 ,阳性率 86.61 % ;2 76例HBsAg( )、抗HBc( )标本中 ,有 1 97例前S1抗原阳性 ,阳性率 71 .38% ;1 0 1 2例HBsAg( )、抗Hbe( )、抗HBc( )标本中 ,有 468例前S1抗原阳性 ,阳性率 46.2 5 %。结论 :前S1抗原作为病毒复制的指标与HBeAg具有很好的一致性 ,又具有其独立的检测价值 ,可弥补HBV血清标志物检测的不足。     

Trabecular bone fracture healing simulation with finite element analysis and fuzzy logic

Trabecular bone fractures heal through intramembraneous ossification. This process differs from diaphyseal fracture healing in that the trabecular marrow provides a rich vascular supply to the healing bone, there is very little callus formation, woven bone forms directly without a cartilage intermediary, and the woven bone is remodelled to form trabecular bone. Previous studies have used numerical methods to simulate diaphyseal fracture healing or bone remodelling, however not trabecular fracture healing, which involves both tissue differentiation and trabecular formation. The objective of this study was to determine if intramembraneous bone formation and remodelling during trabecular bone fracture healing could be simulated using the same mechanobiological principles as those proposed for diaphyseal fracture healing. Using finite element analysis and the fuzzy logic for diaphyseal healing, the model simulated formation of woven bone in the fracture gap and subsequent remodelling of the bone to form trabecular bone. We also demonstrated that the trabecular structure is dependent on the applied loading conditions. A single model that can simulate bone healing and remodelling may prove to be a useful tool in predicting musculoskeletal tissue differentiation in different vascular and mechanical environments.     

Real-time fuzzy-knowledge-based control of Baker's yeast production

A real-time fuzzy-knowledge-based system for fault diagnosis and control of bioprocesses was constructed using the object-oriented programming environment Small-talk/V Mac. The basic system was implemented in a Macintosh Quadra 900 computer and built to function connected on line to the process computer. Fuzzy logic was employed in handling uncertainties both in the knowledge and in measurements. The fuzzy sets defined for the process variables could be changed on-line according to process dynamics. Process knowledge was implemented in a graphical two-level hierachical knowledge base. In on-line process control the system first recognizes the current process phase on the basis of top-level rules in the knowledge-base. Then, according to the results of process diagnosis based on measurement data, the appropriate control strategy is subsequently inferred making use of the lower level rules describing the process during the phase in question. (c) 1995 John Wiley & Sons, Inc.     

Effects‐initiated assessments are not risk assessments

True risk assessments address the probability of a future risk occurring given a certain set of circumstances. However, “effects‐initiated assessments”; or “retrospective assessments”; often are improperly included under the broad appellation of “risk assessment”; and are conducted when an apparently adverse effect is seen in some environmental component and the question of cause (i.e., etiology) is raised. Base line risk assessments at Superfund sites or for Natural Resource Damage Assessments are examples of effects‐initiated assessments. We argue here that this type of study is not a risk assessment, either by strict definition of terminology or by logical approach taken in answering the posed question (s), and should more properly be called “diagnostic ecology.”; Diagnostic ecology starts from the premise that ecological effects have occurred and exposure to a Stressor has taken place. The problem then is to pose all possible etiologies and utilize deductive logic to systematically eliminate each agent except for one as the actual cause. A risk assessment, on the other hand, employs inductive reasoning. That is, hypotheses are generated about the possible sources of a stressor and the possible outcome if exposure occurs. Both exercises require an understanding of the ecological relationships of the various components in the ecosystem, both need an understanding of die cause‐and‐effect relationships of agents, and both require a proper framing of the questions being asked. However, risk assessors should not try to fit all environmental impact assessments into a single framework, but rather should recognize that biomedical techniques are better suited for solving diagnostic riddles than are prospective risk assessment approaches.