红树林湿地模型研究进展

红树林是位于海岸潮间带的森林湿地生态系统,具有抗风削浪、保护堤岸、封存CO₂缓解全球气候变化等多种功能。然而,由于地理位置及生存环境特殊,红树林湿地模型的研究相对内陆湿地滞后。为了推动红树林湿地模型的研究,本文将目前常见红树林湿地模型按功能划分为植被生长生产模型、水文模型、物流能流模型三类,以阐述相关模型研究的进展,并对目前红树林湿地模型研究提出几点看法:(1)现有红树林湿地模型在不同区域、尺度下运行的有效性有待进一步验证;(2)国内对红树林生态系统服务及植被恢复工作相关模型研究较少,今后需加强该方面的研究。     

On the Use of Enterprise Models

This paper presents the results of a field study designed to determine how enterprise models are used. The paper begins with an introduction to enterprise models then provides an overview of the survey method used. No known empirical studies have been conducted to determine how enterprise models actually are used by industry. The research is designed to answer this question. A screening sample and complete web-based survey of 72 enterprise modelers was conducted. The primary research question of this survey was on the use of enterprise models, with particular focus on the three dimensions of living models: scope, enactment, and dynamicity. Half the respondents claim that their enterprise models were of their entire division, multiple divisions, and even multiple enterprises. It is encouraging to see that enterprise models are used on such a wide scope. The enactment of the enterprise models was not as large as was expected. Of the respondents, 75% claimed that their models did not receive information from the enterprise more frequently than quarterly. The same was true for how often the models provided information to the enterprise. Seventy-five percent did not update their models more than five times (although, 32% did update the model three to five times). Finally, additional areas of research are proposed.     

Modeling the effects of light and temperature on algae growth: State of the art and critical assessment for productivity prediction during outdoor cultivation

The ability to model algal productivity under transient conditions of light intensity and temperature is critical for assessing the profitability and sustainability of full-scale algae cultivation outdoors. However, a review of over 40 modeling approaches reveals that most of the models hitherto described in the literature have not been validated under conditions relevant to outdoor cultivation. With respect to light intensity, we therefore categorized and assessed these models based on their theoretical ability to account for the light gradients and short light cycles experienced in well-mixed dense outdoor cultures. Type I models were defined as models predicting the rate of photosynthesis of the entire culture as a function of the incident or average light intensity reaching the culture. Type II models were defined as models computing productivity as the sum of local productivities within the cultivation broth (based on the light intensity locally experienced by individual cells) without consideration of short light cycles. Type III models were then defined as models considering the impacts of both light gradients and short light cycles. Whereas Type I models are easy to implement, they are theoretically not applicable to outdoor systems outside the range of experimental conditions used for their development. By contrast, Type III models offer significant refinement but the complexity of the inputs needed currently restricts their practical application. We therefore propose that Type II models currently offer the best compromise between accuracy and practicability for full scale engineering application. With respect to temperature, we defined as “coupled” and “uncoupled” models the approaches which account and do not account for the potential interdependence of light and temperature on the rate of photosynthesis, respectively. Due to the high number of coefficients of coupled models and the associated risk of overfitting, the recommended approach is uncoupled models. Most of models do not include the modeling of endogenous respiration and the modeling of light and temperature acclimation in spite of their potential effect on productivity.     

Process‐based models not always better than empirical models for simulating budburst of Norway spruce and birch in Europe

Budburst models have mainly been developed to capture the processes of individual trees, and vary in their complexity and plant physiological realism. We evaluated how well eleven models capture the variation in budburst of birch and Norway spruce in Germany, Austria, the United Kingdom and Finland. The comparison was based on the models performance in relation to their underlying physiological assumptions with four different calibration schemes. The models were not able to accurately simulate the timing of budburst. In general the models overestimated the temperature effect, thereby the timing of budburst was simulated too early in the United Kingdom and too late in Finland. Among the better performing models were three models based on the growing degree day concept, with or without day length or chilling, and an empirical model based on spring temperatures. These models were also the models least influenced by the calibration data. For birch the best calibration scheme was based on multiple sites in either Germany or Europe, and for Norway spruce the best scheme included multiple sites in Germany or cold years of all sites. Most model and calibration combinations indicated greater bias with higher spring temperatures, mostly simulating earlier than observed budburst.     

Dustbathing as a regulatory mechanism

Three mathematical models were developed to describe how some species of birds, such as bobwhite quail (Colinus virginianus) regulate the amount of oil on their plumage. The models assume that dustbathing plays a significant role in this regulatory process. They differed primarily in their assumptions about the relationship between oiling and dustbathing behavior. Several experiments were run to check on the implications of the models.     

Modeling cell migration in 3D

Cell migration is a multi-scale process that integrates signaling, mechanics and biochemical reaction kinetics. Various mathematical models accurately predict cell migration on 2-D surfaces, but are unable to capture the complexities of 3D migration. Additionally, quantitative 3D cell migration models have been few and far between. In this review we look and characterize various mathematical models available in literature to predict cell migration in 3-D matrices and analyze their strengths and possible changes to these models that could improve their predictive capabilities.     

Comparative modeling and protein-like features of hydrophobic-polar models on a two-dimensional lattice

Lattice models of proteins have been extensively used to study protein thermodynamics, folding dynamics, and evolution. Our study considers two different hydrophobic-polar (HP) models on the 2D square lattice: the purely HP model and a model where a compactness-favoring term is added. We exhaustively enumerate all the possible structures in our models and perform the study of their corresponding folds, HP arrangements in space and shapes. The two models considered differ greatly in their numbers of structures, folds, arrangements, and shapes. Despite their differences, both lattice models have distinctive protein-like features: (1) Shapes are compact in both models, especially when a compactness-favoring energy term is added. (2) The residue composition is independent of the chain length and is very close to 50% hydrophobic in both models, as we observe in real proteins. (3) Comparative modeling works well in both models, particularly in the more compact one. The fact that our models show protein-like features suggests that lattice models incorporate the fundamental physical principles of proteins. Our study supports the use of lattice models to study questions about proteins that require exactness and extensive calculations, such as protein design and evolution, which are often too complex and computationally demanding to be addressed with more detailed models.     

A two-stage sequential planning scheme for integrated operations planning and scheduling system using MILP: the case of an engine assembler

This paper presents an operations planning scheme based on mathematical programming models (specifically, Mixed-Integer Linear Programming (MILP) models) integrated into a web-enabled Advanced Planning and Scheduling System (APS), developed for and implemented in an engine assembler that supplies the car industry. One objective of this paper is to provide empirical insights into some operations planning characteristics in the automotive industry. The other main objective is to show MILP models and their use to create plans that enable the coordination of different planning levels (mid-term and short-term) and planning domains (procurement, production and distribution). The APS fulfills the requirements of an engine assembler in the automotive sector (namely lean-type constraints and objectives). The system is based on two MILP models, which have been purposely developed together along with their relations. The models presented herein provide a solution that considers supply chain objectives and constraints, and are integrated by means of data and constraints which have proven sufficient to fulfill users?? and stakeholders?? requirements. This case study presents the models?? most relevant aspects and their implementation.     

Development of a new version of the Liverpool Malaria Model. II. Calibration and validation for West Africa

Mathematical models have been used to provide an explicit framework for understanding malaria transmission dynamics in human population for over 100 years. With the disease still thriving and threatening to be a major source of death and disability due to changed environmental and socio-economic conditions, it is necessary to make a critical assessment of the existing models, and study their evolution and efficacy in describing the host-parasite biology. In this article, starting from the basic Ross model, the key mathematical models and their underlying features, based on their specific contributions in the understanding of spread and transmission of malaria have been discussed. The first aim of this article is to develop, starting from the basic models, a hierarchical structure of a range of deterministic models of different levels of complexity. The second objective is to elaborate, using some of the representative mathematical models, the evolution of modelling strategies to describe malaria incidence by including the critical features of host-vector-parasite interactions. Emphasis is more on the evolution of the deterministic differential equation based epidemiological compartment models with a brief discussion on data based statistical models. In this comprehensive survey, the approach has been to summarize the modelling activity in this area so that it helps reach a wider range of researchers working on epidemiology, transmission, and other aspects of malaria. This may facilitate the mathematicians to further develop suitable models in this direction relevant to the present scenario, and help the biologists and public health personnel to adopt better understanding of the modelling strategies to control the disease     

Mouse models of oxidative phosphorylation defects: powerful tools to study the pathobiology of mitochondrial diseases

Defects in the oxidative phosphorylation system (OXPHOS) are responsible for a group of extremely heterogeneous and pleiotropic pathologies commonly known as mitochondrial diseases. Although many mutations have been found to be responsible for OXPHOS defects, their pathogenetic mechanisms are still poorly understood. An important contribution to investigate the in vivo function of several mitochondrial proteins and their role in mitochondrial dysfunction, has been provided by mouse models. Thanks to their genetic and physiologic similarity to humans, mouse models represent a powerful tool to investigate the impact of pathological mutations on metabolic pathways. In this review we discuss the main mouse models of mitochondrial disease developed, focusing on the ones that directly affect the OXPHOS system.     

Mathematical Models of Localized Muscle Fatigue: Sensitivity Analysis and Assessment of Two Occupationally-Relevant Models

Muscle fatigue models (MFM) have broad potential application if they can accurately predict muscle capacity and/or endurance time during the execution of diverse tasks. As an initial step toward facilitating improved MFMs, we assessed the sensitivity of selected existing models to their inherent parameters, specifically that model the fatigue and recovery processes, and the accuracy of model predictions. These evaluations were completed for both prolonged and intermittent isometric contractions, and were based on model predictions of endurance times. Based on a recent review of the literature, four MFMs were initially chosen, from which a preliminary assessment led to two of these being considered for more comprehensive evaluation. Both models had a higher sensitivity to their fatigue parameter. Predictions of both models were also more sensitive to the alteration of their parameters in conditions involving lower to moderate levels of effort, though such conditions may be of most practical, contemporary interest or relevance. Although both models yielded accurate predictions of endurance times during prolonged contractions, their predictive ability was inferior for more complex (intermittent) conditions. When optimizing model parameters for different loading conditions, the recovery parameter showed considerably larger variability, which might be related to the inability of these MFMs in simulating the recovery process under different loading conditions. It is argued that such models may benefit in future work from improving their representation of recovery process, particularly how this process differs across loading conditions.     

Proton channel models: Filling the gap between experimental data and the structural rationale

Voltage-gated proton channels are integral membrane proteins with the capacity to permeate elementary particles in a voltage and pH dependent manner. These proteins have been found in several species and are involved in various physiological processes. Although their primary topology is known, lack of details regarding their structures in the open conformation has limited analyses toward a deeper understanding of the molecular determinants of their function and regulation. Consequently, the function-structure relationships have been inferred based on homology models. In the present work, we review the existing proton channel models, their assumptions, predictions and the experimental facts that support them. Modeling proton channels is not a trivial task due to the lack of a close homolog template. Hence, there are important differences between published models. This work attempts to critically review existing proton channel models toward the aim of contributing to a better understanding of the structural features of these proteins.     

Warning colouration in pseudocerotid flatworms (Platyhelminthes,Polycladida). A preliminary study

Many species of tropical and subtropical pseudocerotid flatworms are noted for their brilliant colour patterns and conspicuous behaviour and are suitable candidates for the investigation of aposematic colouration. This study gives the first experimental evidence of aposematic colouration in pseudocerotid flatworms. Coloured and uncoloured agar models of flatworms were used to determine whether a fish predator, the moon wrasse Thalassoma lunare, could learn to avoid colourful flatworms on the basis of their colour pattern. The results showed that uncoloured models were more significantly attacked than coloured models (1% significance) and that there was no significant difference between attacks made to live flatworms and their respective models. These results clearly indicate the operation of aposematism in brightly coloured flatworms and demonstrate the operation of mimicry as the agar models were essentially non-living mimics of the flatworms. This revised version was published online in July 2006 with corrections to the Cover Date.     

陆地植被净初级生产力计算模型研究进展

植被净初级生产力(NPP)研究是全球变化与陆地生态系统的核心内容之一。在回顾NPP模型研究的基础上,综合分析了气候模型、生态生理过程模型、光能利用率模型各自的优缺点,并对NPP模型研究做出展望。生态生理过程模型是当前陆地NPP估算研究的主要手段,而区域尺度转换则是它所面临的关键问题。近年来光能利用率模型已成为NPP估算的一种全新手段,它利用遥感所获得的全覆盖数据,使区域及全球尺度的NPP估算成为可能,但其生态学机理还有待于进一步研究。已有研究表明,“生态一遥感耦合模型”将是陆地NPP估算的主要发展方向,它融合了生态生理过程模型和光能利用率模型的优点,增强了NPP模型估算的可靠性和可操作性。     

Recent advances in reconstruction and applications of genome-scale metabolic models

In the last decade, reconstruction and applications of genome-scale metabolic models have greatly influenced the field of systems biology by providing a platform on which high-throughput computational analysis of metabolic networks can be performed. The last two years have seen an increase in volume of more than 33% in the number of published genome-scale metabolic models, signifying a high demand for these metabolic models in studying specific organisms. The diversity in modeling different types of cells, from photosynthetic microorganisms to human cell types, also demonstrates their growing influence in biology. Here we review the recent advances and current state of genome-scale metabolic models, the methods employed towards ensuring high quality models, their biotechnological applications, and the progress towards the automated reconstruction of genome-scale metabolic models.     

Models of Hopfield-type quaternion neural networks and their energy functions

Recently models of neural networks that can directly deal with complex numbers, complex-valued neural networks, have been proposed and several studies on their abilities of information processing have been done. Furthermore models of neural networks that can deal with quaternion numbers, which is the extension of complex numbers, have also been proposed. However they are all multilayer quaternion neural networks. This paper proposes models of fully connected recurrent quaternion neural networks, Hopfield-type quaternion neural networks. Since quaternion numbers are non-commutative on multiplication, some different models can be considered. We investigate dynamics of these proposed models from the point of view of the existence of an energy function and derive their conditions for existence.     

Responses to selection on genotypic or phenotypic values in the presence of genes with major effects

Summary Average genotypic responses were compared after selection for genotypic values and for phenotypic values on the basis of single-gene models and multigene models in simulated livestock populations. Single-gene models dealt with single gene control of the genetic differences between animals, while multigene models considered a collection of genes with various magnitudes of effects on a trait. In each case, selection lasted through discrete generations until the fixation of the gene frequencies occurred. Generations to reach fixation were used to compare various models, and the two criteria for selection, for their efficiency in selection. Implications of using these models versus using infinitesimal models for selection in practice are presented.     

Kinetic models of spike-timing dependent plasticity and their functional consequences in detecting correlations

Spike-timing dependent plasticity (STDP) is a type of synaptic modification found relatively recently, but the underlying biophysical mechanisms are still unclear. Several models of STDP have been proposed, and differ by their implementation, and in particular how synaptic weights saturate to their minimal and maximal values. We analyze here kinetic models of transmitter-receptor interaction and derive a series of STDP models. In general, such kinetic models predict progressive saturation of the weights. Various forms can be obtained depending on the hypotheses made in the kinetic model, and these include a simple linear dependence on the value of the weight (“soft bounds”), mixed soft and abrupt saturation (“hard bound”), or more complex forms. We analyze in more detail simple soft-bound models of Hebbian and anti-Hebbian STDPs, in which nonlinear spike interactions (triplets) are taken into account. We show that Hebbian STDPs can be used to selectively potentiate synapses that are correlated in time, while anti-Hebbian STDPs depress correlated synapses, despite the presence of nonlinear spike interactions. This correlation detection enables neurons to develop a selectivity to correlated inputs. We also examine different versions of kinetics-based STDP models and compare their sensitivity to correlations. We conclude that kinetic models generally predict soft-bound dynamics, and that such models seem ideal for detecting correlations among large numbers of inputs.     

Supporting upper-level undergraduate students in building a systems perspective in a botany course

Undergraduate biology majors require biological literacy about the critical and dynamic relationships between plants and ecosystems and the effect human-made processes have on these systems. To support students in understanding systems relationships, we redesigned an undergraduate botany course using an ecological framework and embedded systems modelling to support students in understanding the criticality of plant processes to the global carbon cycle. The class meetings included lectures, opportunities to develop systems models identifying the relationships between plant processes and other systems, reflections on their systems understanding and open-floor discussions about assigned primary and secondary readings that explored the relationships between plant systems, abiotic and biotic processes and global carbon cycling in their systems models. We used the systems models students developed at the beginning and end of the course to examine how their systems understanding grew. Our results suggest that at the beginning of term, students’ ideas about plants were egocentric identifying the purpose of plants was to support human life and they did not consider relationships between plants and global carbon systems. By the end of the term, their models and reflections identified elements of a systems perspective and the students considered human impact on this delicate balance.