Graphical representations of the class I MHC cleft

We describe computer graphics and computer aided manufacture of three-dimensional models designed specifically to elucidate the cleft in the class I human leukocyte antigen. The models evolve from computer graphical representations and provide a geometrically and chemically concise and detailed view of the antigen binding site. The techniques provide a new approach to representations of binding sites. The model provides sufficient detail to support binding specificities analysis of active sites involved in protein and DNA binding.     

鄂尔多斯高原植物群落季节生长格局模拟

影响大尺度空间生态模型模拟结果与资源管理整合的因素主要有两种:一是一些模型生态学意义不明确,二是一些模型所需要的生态输入信息过于复杂。建立一个基于基本的生态学公理且输入较为简单的生态学模型,便于更加有效地服务于资源环境管理。该模型用于模拟发生严重荒漠化的鄂尔多斯高原植物群落的季节及年生长、叶片投影盖度、蒸发系数。模型首先基于降雨、蒸散、渗漏及土壤水分特性与蒸发系数(k)的关系,采用迭代的计算方法,模拟植物群落蒸散与土壤可利用水分达到平衡状态时的k值,进而采用得到广泛验证的经验公式计算植物群落的其它参数。野外N PP观察数据对模型的验证表明:模拟结果与观察值相符较好。模拟结果表明:蒸发系数小于0 .35×10 - 2 ,显示鄂尔多斯高原气候较为干燥;叶片投影盖度低于5 0 % ;除东部的准格尔旗外,植物群落净第一性生产力均低于1t/(hm2·a) ,近90 %的N PP累积集中于5至8月份。根据该文的模拟结果,在进行植被恢复时,恢复植被密度必须低于5 0 % ,放牧密度以0 .8～2 .0个/hm2 羊单位为宜     

3D reconstruction and manufacture of real abdominal aortic aneurysms: from CT scan to silicone model

Abdominal aortic aneurysm (AAA) can be defined as a permanent and irreversible dilation of the infrarenal aorta. AAAs are often considered to be an aorta with a diameter 1.5 times the normal infrarenal aorta diameter. This paper describes a technique to manufacture realistic silicone AAA models for use with experimental studies. This paper is concerned with the reconstruction and manufacturing process of patient-specific AAAs. 3D reconstruction from computed tomography scan data allows the AAA to be created. Mould sets are then designed for these AAA models utilizing computer aided designcomputer aided manufacture techniques and combined with the injection-moulding method. Silicone rubber forms the basis of the resulting AAA model. Assessment of wall thickness and overall percentage difference from the final silicone model to that of the computer-generated model was performed. In these realistic AAA models, wall thickness was found to vary by an average of 9.21%. The percentage difference in wall thickness recorded can be attributed to the contraction of the casting wax and the expansion of the silicone during model manufacture. This method may be used in conjunction with wall stress studies using the photoelastic method or in fluid dynamic studies using a laser-Doppler anemometry. In conclusion, these patient-specific rubber AAA models can be used in experimental investigations, but should be assessed for wall thickness variability once manufactured.     

An Internet-based simulation model for nitrogen management in agricultural settings

Complex chemical, physical, and biological processes mediate nitrogen (N) transformations and movement during agricultural production, making the optimization of fertilizer use and environmental protection exceedingly difficult. Various computer models have been developed to simulate the site-specific fate and transport of N resulting from different crop production scenarios, but these models are very complex and difficult to use for most farmers, consultants, and conservationists. In an effort to facilitate access and simplify the use of sophisticated models, the U.S. Department of Agriculture (USDA) has developed an Internet-based nitrogen analysis tool. Based on the Nitrate Leaching and Economic Analysis Package (NLEAP), the Web site allows a user to conduct multiyear N simulation modeling specific to a crop field. Servers handle much of the required data assembly and formatting, thus sparing the user"s resources. Model runs are executed on the servers and the results are transmitted to the user. This new tool is presented along with early implementation results.     

Robust optimization of total joint replacements incorporating environmental variables.

Direct search techniques for the optimal design of biomechanical devices are computationally intensive requiring many iterations before converging to a global solution. This, along with the incorporation of environmental variables such as multiple loading conditions and bone properties, makes direct search techniques infeasible. In this study, we introduced new methods that are based on the statistical design and analysis of computer experiments to account efficiently for environmental variables. Using data collected at a relatively small set of training sites, the method employs a computationally inexpensive predictor of the structural response that is statistically motivated. By using this predictor in place of the simulator (e.g., finite element model), a sufficient number of iterations can be performed to facilitate the optimization of the complex system. The applicability of these methods was demonstrated through the design of a femoral component for total hip arthroplasty incorporating variations in joint force orientation and cancellous bone properties. Beams on elastic foundation (BOEF) finite element models were developed to simulate the structural response. These simple models were chosen for their short computation time. This allowed us to represent the actual structural response surface by an exhaustive enumeration of the design and environmental variable space, and provided a means by which to validate the statistical predictor. We were able to predict the structural response and the optimal design accurately using only 16 runs of the computer code. The general trends predicted by the BOEF models were in agreement with previous three-dimensional finite element computer simulations, and experimental and clinical results, which demonstrated that the important features of intramedullary fixation systems were captured. These results indicate that the statistically based optimization methods are appropriate for optimization studies using computationally demanding models.     

Influence of custom-made implant designs on the biomechanical performance for the case of immediate post-extraction placement in the maxillary esthetic zone: a finite element analysis

Due to the increasing adoption of immediate implantation strategies and the rapid development of the computer aided design/computer aided manufacturing technology, a therapeutic concept based on patient-specific implant dentistry has recently been reintroduced by many researchers. However, little information is available on the designs of custom-made dental implant systems, especially their biomechanical behavior. The influence of the custom-made implant designs on the biomechanical performance for both an immediate and a delayed loading protocol in the maxillary esthetic zone was evaluated by means of the finite element (FE) method. FE models of three dental implants were considered: a state of the art cylindrical implant and two custom-made implants designed by reverse engineering technology, namely a root-analogue implant and a root-analogue threaded implant. The von Mises stress distributions and micro-motions around the bone-implant interfaces were calculated using ANSYS software. In a comparison of the three implant designs for both loading protocols, a favorable biomechanical performance was observed for the use of root-analogue threaded implant which approximated the geometry of natural anterior tooth and maintained the original long-axis. The results indicated that bone-implant interfacial micro-motion was reduced and a favorable stress distribution after osseointegration was achieved.     

The animat: new frontiers in whole brain modeling

The researchers at Boston University (BU)'s Neuromorphics Laboratory, part of the National Science Foundation (NSF)-sponsored Center of Excellence for Learning in Education, Science, and Technology (CELEST), are working in collaboration with the engineers and scientists at Hewlett-Packard (HP) to implement neural models of intelligent processes for the next generation of dense, low-power, computer hardware that will use memristive technology to bring data closer to the processor where computation occurs. The HP and BU teams are jointly designing an optimal infrastructure, simulation, and software platform to build an artificial brain. The resulting Cog Ex Machina (Cog) software platform has been successfully used to implement a large-scale, multicomponent brain system that is able to simulate some key rat behavioral results in a virtual environment and has been applied to control robotic platforms as they learn to interact with their environment.     

Computer-aided drug design,quantum-mechanical methods for biological problems

Quantum chemistry enables to study systems with chemical accuracy (<1 kcal/mol from experiment) but is restricted to a handful of atoms due to its computational expense. This has led to ongoing interest to optimize and simplify these methods while retaining accuracy. Implementing quantum mechanical (QM) methods on modern hardware such as multiple-GPUs is one example of how the field is optimizing performance. Multiscale approaches like the so-called QM/molecular mechanical method are gaining popularity in drug discovery because they focus the application of QM methods on the region of choice (e.g., the binding site), while using efficient MM models to represent less relevant areas. The creation of simplified QM methods is another example, including the use of machine learning to create ultra-fast and accurate QM models. Herein, we summarize recent advancements in the development of optimized QM methods that enhance our ability to use these methods in computer aided drug discovery.     

灵芝胞外多糖分批发酵非结构动力学模型

在２Ｌ搅拌发酵罐上提出了描述了灵芝胞外多糖分批发酵过程中菌球生长、底物消耗和胞外多糖形成的非结构动力学模型。首先研究了灵芝分批发酵特性,结果表明该发酵过程属菌体生长和产物形成相偶联型。然后在总结文献的基础上,运用动力学模型,经过非线性回归,得到了模型中的参数值。通过计算机模拟,证明模型预测值与实际实验值具有良好的拟合性。     

Modeling the electrical behavior of anatomically complex neurons using a network analysis program: Excitable membrane

We present methods for using the generalpurpose network analysis program, SPICE, to construct computer models of excitable membrane displaying Hodgkin-Huxley-like kinetics. The four non-linear partial differential equations of Hodgkin and Huxley (H-H; 1952) are implemented using electrical circuit elements. The H-H rate constants, and , are approximated by polynomial functions rather than exponential functions, since the former are handled more efficiently by SPICE. The process of developing code to implement the H-H sodium conductance is described in detail. The Appendix contains a complete listing of the code required to simulate an H-H action potential. The behavior of models so constructed is validated by comparison with the space-clamped and propagating action potentials of Hodgkin and Huxley. SPICE models of multiply branched axons were tested and found to behave as predicted by previous numerical solutions for propagation in inhomogeneous axons. New results are presented for two cases. First, a detailed, anatomically based model is constructed of group Ia input to an -motoneuron with an excitable soma, a myelinated axon and passive dendrites. Second, we simulate interactions among clusters of mixed excitable and passive dendritic spines on an idealized neuron. The methods presented in this paper and its companion (Segev et al. 1985) should permit neurobiologists to construct and explore models which simulate much more closely the real morphological and physiological characteristics of nerve cells.     

宏观植物生态模型的研究现状与展望

概述了3种主要植物生态模型的发展现状1)种群动态模型,主要模拟在一个生态系统中单个种的植物个体发芽、成长和死亡过程,及其种内竞争和种间相互作用,是研究开发最早的一类生态模型之一.该类模型主要应用于分析植物种群之间相互作用.2)演替模型,主要模拟植物种类(动物与此相伴)在整个生态系统发展过程的变化,包括植被类型的转变和相关的生物地球化学循环过程的改变.可用于研究生物群落对气候变化的响应.3)生态系统模型,是把生态系统当作一个功能整体来模拟的一类模型,主要有以下3类(1)SVAT模型,主要模拟地表生态系统过程,以BATS、SiB、SiB2和LEAF为代表,多用于气候研究;(2)BGC模型,主要模拟3个关键循环碳,水和营养物质循环.常用的BGC模型有FOREST-BGC、BIOME-BGC、CENTURY、TEM、DOLY以及由它们衍生而来的整合模型组;(3)BG模型,模拟群落、生物群区中植物分布,比较具有代表性的 BGMs包括BIOME2和MAPSS,它们主要用于研究因气候变化而引起的生物分布的变迁.最后,结合我们的实际工作展望了生态模型在未来几年内的几个发展方向1)与基础学科相结合,比如把物候学引入生态模型研究中来,以寻求新的支撑点;2)与现代非线性理论相结合,重新评价模型的假设基础;3)与现代科学技术相结合,利用3S技术和计算机技术为模型的发展提供更强大的技术支持;4)在研究方法上,从还原论转向整体论,尽可能地把生态系统当作一个功能整体来模拟研究.     

Large Neural Network Simulations on Multiple Hardware Platforms

To efficiently simulate very large networks of interconnected neurons, particular consideration has to be given to the computer architecture being used. This article presents techniques for implementing simulators for large neural networks on a number of different computer architectures. The neuronal simulation task and the computer architectures of interest are first characterized, and the potential bottlenecks are highlighted. Then we describe the experience gained from adapting an existing simulator, SWIM, to two very different architectures–vector computers and multiprocessor workstations. This work lead to the implementation of a new simulation library, SPLIT, designed to allow efficient simulation of large networks on several architectures. Different computer architectures put different demands on the organization of both data structures and computations. Strict separation of such architecture considerations from the neuronal models and other simulation aspects makes it possible to construct both portable and extendible code.     

Review of forest landscape models: Types, methods, development and applications

Forest landscape models simulate forest change through time using spatially referenced data across a broad spatial scale (i.e. landscape scale) generally larger than a single forest stand. Spatial interactions between forest stands are a key component of such models. These models can incorporate other spatio-temporal processes such as natural disturbances (e.g. wildfires, hurricanes, outbreaks of native and exotic invasive pests and diseases) and human influences (e.g. harvesting and commercial thinning, planting, fire suppression). The models are increasingly used as tools for studying forest management, ecological assessment, restoration planning, and climate change. In this paper, we define forest landscape models and discuss development, components, and types of the models. We also review commonly used methods and approaches of modeling forest landscapes, their application, and their strengths and weaknesses. New developments in computer sciences, geographic information systems (GIS), remote sensing technologies, decision-support systems, and geo-spatial statistics have provided opportunities for developing a new generation of forest landscape models that are increasingly valuable for ecological research, restoration planning and resource management.     

Review of forest landscape models: Types, methods, development and applications

Forest landscape models simulate forest change through time using spatially referenced data across a broad spatial scale (i.e. landscape scale) generally larger than a single forest stand. Spatial interactions between forest stands are a key component of such models. These models can incorporate other spatio-temporal processes such as natural disturbances (e.g. wildfires, hurricanes, outbreaks of native and exotic invasive pests and diseases) and human influences (e.g. harvesting and commercial thinning, planting, fire suppression). The models are increasingly used as tools for studying forest management, ecological assessment, restoration planning, and climate change. In this paper, we define forest landscape models and discuss development, components, and types of the models. We also review commonly used methods and approaches of modeling forest landscapes, their application, and their strengths and weaknesses. New developments in computer sciences, geographic information systems (GIS), remote sensing technologies, decision-support systems, and geo-spatial statistics have provided opportunities for developing a new generation of forest landscape models that are increasingly valuable for ecological research, restoration planning and resource management.     

Active site model of cytochrome P-450 LM2

Based on (i) a detailed analysis of the physicochemical properties of selected benzphetamine derived substrates and (ii) the identification of Tyr-380 as active site residue trans to thiolate theoretical studies (computer aided molecular design) revealed a model of the substrate binding site of cytochrome P-450 LM2. The results indicate that substrates with a butterfly-like bulky conformation exhibit the highest intrinsic activity. Those substrates which preferably exist in an extended conformation are sterically hindered to intensively interact with the binding site which is demonstrated by computer graphics.     

A new model-based RSA method validated using CAD models and models from reversed engineering

Roentgen stereophotogrammetric analysis (RSA) was developed to measure micromotion of an orthopaedic implant with respect to its surrounding bone. A disadvantage of conventional RSA is that it requires the implant to be marked with tantalum beads. This disadvantage can potentially be resolved with model-based RSA, whereby a 3D model of the implant is used for matching with the actual images and the assessment of position and rotation of the implant. In this study, a model-based RSA algorithm is presented and validated in phantom experiments. To investigate the influence of the accuracy of the implant models that were used for model-based RSA, we studied both computer aided design (CAD) models as well as models obtained by means of reversed engineering (RE) of the actual implant. The results demonstrate that the RE models provide more accurate results than the CAD models. If these RE models are derived from the very same implant, it is possible to achieve a maximum standard deviation of the error in the migration calculation of 0.06 mm for translations in x- and y-direction and 0.14 mm for the out of plane z-direction, respectively. For rotations about the y-axis, the standard deviation was about 0.1 degrees and for rotations about the x- and z-axis 0.05 degrees. Studies with clinical RSA-radiographs must prove that these results can also be reached in a clinical setting, making model-based RSA a possible alternative for marker-based RSA.     

Impact of derived global weather data on simulated crop yields

Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long‐term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water‐limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well‐maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26–72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA‐POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12–19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location‐specific observed daily weather databases combined with an appropriate upscaling method.     

Computer Aided Drug Design: Some Fundamental Aspects

Understanding the molecular basis of drug action and exploring the chemical interactions involved in the complex processes of drug delivery are among the most important goals of contemporary drug design. The major recent advances in the detailed, mechanistic interpretation of molecular interactions, the global and local shape analysis of electron density clouds making up the actual fuzzy bodies of molecules, novel similarity and complementary measures, the detailed and accurate computational visualization techniques of molecular level "Computational Microscopy", the advances in computer modeling of conformational processes and chemical reactions of drug molecules, the computer aided design of molecular templates fitting various receptor sites are among the powerful tools of computer aided drug discovery. In this contribution some of the latest advances are reviewed.     

Anin numero study of glucose-insulin interaction

A mathematical model has been developed to simulate the glucose-insulin interaction following a glucose load such as occurs in an IVGTT. This model differs from earlier models in that the insulin response to glucose loading is a recurring all or none threshold response. The model has been simulated on a digital computer using the digital analog simulation language CSMP.     

Shape memory alloy clip for compression colonic anastomosis

This study was setup to investigate the design and performance of a shape memory alloy clip for colonic anastomosis. The thermo-mechanical properties of the shape memory alloy material were studied and the data were used to derive a nonlinear material model. This enabled the development of computer computer aided design models and finite element analysis of the clip and tissue compression. The maximum strain of the anastomosis clip was within the recoverable range, and it exerted parallel compression of the colonic walls with a uniform pressure distribution. The design of the anastomosis clip was optimized for safe, simple, and effective use in colon surgery.