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Exotic tree species, though widely used in forestry and restoration projects, pose great threats to local ecosystems. They need to be replaced with native species from natural forests. We hypothesized that natural forests contain large, fast-growing, dominant native tree species that are suitable for specific topographic conditions in forestry. We tested this hypothesis using data from a 50-ha forest dynamics plot in subtropical China. We classified the plot into the ridge, slope, and valley habitats and found that 34/87 species had significant associations with at least one topographic habitat. There were 90 tree species with a maximum diameter ≥ 30 cm, and their abundances varied widely in all habitat types. In all habitat types, for most species, rate of biomass gain due to recruitment was < 1% of its original biomass, and rate of biomass gain due to tree growth was between 1 and 5% of its original biomass. For most species, biomass loss due to tree mortality was not significantly different than biomass gain due to recruitment, but the resulting net biomass increment rates did not significantly differ from zero. The time required to reach a diameter of 30 cm from 1 cm diameter for Altingia chinensis in the slope habitat, for Quercus chungii and Morella rubra in the ridge habitat and for Castanopsis carlesii in all habitats could be as short as 30 years in our simulations based on actual distributions of tree growth observed in the forest. Principal component analyses of maximum diameter, abundance and net biomass increment rates suggested several species were worthy of further tests for use in forestry. Our study provides an example for screening native tree species from natural forests for forestry. Because native tree species are better for local ecosystems, our study will also contribute to biodiversity conservation in plantations. [ABSTRACT FROM AUTHOR]

As the global population is continuously increasing, the supply of food with equal accessibility has become a major issue and future challenge. To meet both the worldwide demand for food security and new environmental needs, agriculture must increase food production and quality while decreasing its detrimental impacts on ecosystems and the environment). However, new agricultural land is limited, so sustainable production and increasing productivity of existing agricultural land is an important aspect to address global food security. Climate change affects precipitations, water flows, humidity and temperature. These changes will influence crop growth, phenology and yields, in the end leading to drastic changes in areas that are suitable for specific plant cultivation and land use changes. The paper presents considerations for the simulation of plant growth, taking into account temperature, lighting, water availability and fertilization. [ABSTRACT FROM AUTHOR]

Winter wheat is the main grain crop in the Yellow River Basin, and optimizing water and nitrogen management can not only improve the yield, but also reduce water and fertilizer waste and environmental pollution. Using two years of winter wheat field trials, the Aquacrop model was calibrated and validated, and 36 different water and nitrogen application scenarios were simulated and analyzed. Among them, the field trials were divided into three N application levels, and three lower limits of water control. The results showed that: (1) the model has good applicability to simulate the growth process of winter wheat in the Yellow River Basin. (2) At a constant level of irrigation or nitrogen application, crop yield initially increased and subsequently decreased with the enhancement of either irrigation or nitrogen application. Finally, through response surface analysis of regression equations, the recommended irrigation volume was determined to be between 296 and 303 mm, and the fertilizer application rate was set between 229 and 261 kg/ha. At these levels, the PFP could achieve over 60% of its maximum. This research provides a theoretical basis for the water-saving, fertilizer-saving and high-yield water and fertilizer management system of winter wheat in the irrigated area of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer-Aided Design & Computer Graphics / Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study was performed to evaluate the AquaCrop model in the crop yield, biomass, crop, and biomass water use efficiency of greenhouse cucumber with two methods of the capillary wick and drip irrigation and three soil textures including Clay-Loam marked with (S1), Sandy-Clay-Loam (S2) and Sandy-Loam (S3) in three replications and two cultivation periods in spring 2018 period (1) and autumn 2018 period (2). Data analysis was done based on compound analysis of variance and mean comparison was done based on Duncan's multi-range test. The data of the first period was used for calibration and sensitivity analysis, and the data of the second period was used to validate the model. The root-mean-square error (nRMSE) and coefficient of determination (R²) were used to validate the model. Based on results in the drip irrigation system, the maximum yield, and water use productivity were observed with 79.64 ton/ha and 46.54 kg/m³ in T2S1 treatment, and in the capillary wick irrigation system, the highest yield, and water use efficiency were observed with 62.05 ton/ha and 44.76 kg/m3 in W2S3. The model investigation results revealed that the highest simulation accuracy was observed in W2S3 treatment so that the nRMSE index in crop yield, biomass yield, crop water use efficiency and biomass water use efficiency were respectively 2.80, 1.70, 1.10, and 1.70 percent were calculated. Due to the optimality of all conditions in the model, most of the estimated parameters were higher than the observational data, still, the increasing and decreasing trend of model simulation in estimating product performance values was completely consistent with the observed data. [ABSTRACT FROM AUTHOR]

Abstract：Field scale crop growth simulation based on the assimilation of observation data and crop growth models is an important method for optimizing field management, agricultural auxiliary decision-making, and crop growth evaluation, which is of great significance for precise management of farmland. In order to construct a numerical model that can accurately simulate the growth and yield of spring wheat in arid areas, this study combined the SWAP (soil water atmosphere plant) model with the IES (iterative ensemble smoother) algorithm to construct a SWAP-IES assimilation simulation system suitable for simulating spring wheat growth in arid areas. Using field test data from 2019 to 2020, the roles of soil water content (SW), leaf area index (LAI), and soil water combination in simulating the growth and yield of spring wheat in arid areas were evaluated, and the impact of assimilation data observation on the yield estimation accuracy of the SWAP-IES system was analyzed and evaluated. The results indicate that: 1) When only assimilating SW, the SWAP-IES system had the highest accuracy in simulating soil moisture (R2=0.87), indicating that assimilating soil moisture can lay the foundation for accurately simulating water stress conditions, evapotranspiration, etc. 2) When there was no assimilation, the R² of the SWAP-IES system for simulating LAI, plant height, and biomass of spring wheat ranged from 0.31 to 0.67, and all treatments were below medium accuracy. The accuracy of LAI simulation for spring wheat was significantly improved when assimilating LAI (R² between 0.76 and 0.96 for each treatment), while LAI+SW had the highest simulation accuracy for spring wheat biomass (R² between 0.73 and 0.92 for each treatment). There was no obvious pattern in plant height, and the simulation of plant height by assimilating LAI and LAI+SW achieved high accuracy (R² ranging from 0.71 to 0.96). Thus, it was necessary to select appropriate observation variables for assimilation simulation based on the research purpose. 3) The accuracy of the SWAP-IES system in predicting spring wheat yield without assimilation was relatively low, with R² of 0.45 and SRE ranging from 10.89% to 40.34%. The yield estimation had improved when assimilating SW, but the results were still of medium accuracy. The accuracy of yield estimation significantly was improved when assimilating LAI (R² was 0.79), while the overall accuracy of spring wheat yield simulation is the highest when assimilating LAI+SW (R² was 0.87). During the two years, T1, T2, and T3 treatments have the lowest estimated SRE when assimilating LAI+SW (SRE ranging from 3.87% to 8.38%), while T4 and T5 treatments had the lowest estimated SRE when assimilating LAI (all within 10%). 4) The effect of assimilating LAI+SW at flowering stage in single growth period observation data on improving the yield estimation accuracy of SWAP-IES system was the greatest (R² increased from 0.45 without assimilation to 0.74), followed by assimilating observation data at jointing stage and booting stage. Assimilating observation data from multiple growth stages can significantly improve the accuracy of the model's yield estimation. When assimilating LAI+SW observation data from jointing and flowering stages, the estimated yield R2 was 0.79, while when assimilating LAI+SW observation data from jointing, booting, and flowering stages, the estimated yield R² reached 0.83. The SWAP-IES assimilation simulation system constructed in this study can effectively simulate the growth and yield formation process of spring wheat under different water conditions by integrating LAI+SW observation data of key growth stages such as flowering and jointing stages, especially under water stress conditions. The results can provide valuable information for using observation equipment such as drones and ground cameras to carry out spring wheat growth monitoring, yield estimation, and precise management under different water management conditions in arid areas. [ABSTRACT FROM AUTHOR]

Winter wheat is the main grain crop in the Yellow River Basin, and optimizing water and nitrogen management can not only improve the yield, but also reduce water and fertilizer waste and environmental pollution. Using two years of winter wheat field trials, the Aquacrop model was calibrated and validated, and 36 different water and nitrogen application scenarios were simulated and analyzed. Among them, the field trials were divided into three N application levels, and three lower limits of water control. The results showed that: (1) the model has good applicability to simulate the growth process of winter wheat in the Yellow River Basin. (2) At a constant level of irrigation or nitrogen application, crop yield initially increased and subsequently decreased with the enhancement of either irrigation or nitrogen application. Finally, through response surface analysis of regression equations, the recommended irrigation volume was determined to be between 296 and 303 mm, and the fertilizer application rate was set between 229 and 261 kg/ha. At these levels, the PFP could achieve over 60% of its maximum. This research provides a theoretical basis for the water-saving, fertilizer-saving and high-yield water and fertilizer management system of winter wheat in the irrigated area of the Yellow River Basin.

In New Zealand, potato crop yields of 90 t ha−1 are achievable but at 55 t ha−1, the average is becoming economically unsustainable. In 2012/13, a grower-initiated survey found that Rhizoctonia solani and Spongospora subterranea (soil-borne pathogens) and soil compaction were widespread in 11 Canterbury potato crops. Targeted areas in these crops had measured yield losses of 0 (healthy plants) – 42 (diseased, resource constrained plants) t ha−1, limiting the farmer-measured field yield to a 56 t ha−1 average. In 2014/15, growth, water use and health of three contrasting crops were measured. Near-potential yield was achieved in one crop when disease incidence and severity were low and resources adequate. The other two crops yielded less than potential; one had an inadequate water supply and the other widespread soil-borne disease. Any suspected links between soil-borne disease, soil compaction and yield were further investigated by using them as factors in replicated experiments reported elsewhere. [ABSTRACT FROM AUTHOR]

Chronic otitis media enables the appearance of a benign middle ear tumor, known as a cholesteatoma, that may compromise hearing. To evaluate the influence of a cholesteatoma growth on the hearing function, a computational middle ear model based on the finite element method was used and three different size of cholesteatoma were modeled. The cholesteatoma solidification and the consequent degradation of the ossicles were also simulated as two condition that commonly occurs during cholesteatoma evolution. A sound pressure level of 80 dB SPL was applied in the tympanic membrane and a steady state analysis was performed for frequencies from 100 Hz to 10 kHz. The displacements of both the tympanic membrane and the stapes footplate were measured. The results were compared with a healthy case and it was shown that the cholesteatoma development leads to a decrease in the umbo and stapes displacements. The ossicles degradation simulation showed the higher difference comparing with the cholesteatoma in an initial stage, with lower displacements in the stapes footplate mainly for high frequencies. The observed displacement differences are directly connected to hearing loss, being possible to conclude that cholesteatoma evolution in the middle ear will lead to hearing problems, mainly in an advanced stage. [ABSTRACT FROM AUTHOR]

Mathematical models have been widely employed for the simulation of growth dynamics of annual crops, thereby performing yield prediction, but not for fruit tree species such as jujube tree (Zizyphus jujuba). The objectives of this study were to investigate the potential use of a modified WOFOST model for predicting jujube yield by introducing tree age as a key parameter. The model was established using data collected from dedicated field experiments performed in 2016–2018. Simulated growth dynamics of dry weights of leaves, stems, fruits, total biomass and leaf area index (LAI) agreed well with measured values, showing root mean square error (RMSE) values of 0.143, 0.333, 0.366, 0.624 t ha−1 and 0.19, and R2 values of 0.947, 0.976, 0.985, 0.986 and 0.95, respectively. Simulated phenological development stages for emergence, anthesis and maturity were 2, 3 and 3 days earlier than the observed values, respectively. In addition, in order to predict the yields of trees with different ages, the weight of new organs (initial buds and roots) in each growing season was introduced as the initial total dry weight (TDWI), which was calculated as averaged, fitted and optimized values of trees with the same age. The results showed the evolution of the simulated LAI and yields profiled in response to the changes in TDWI. The modelling performance was significantly improved when it considered TDWI integrated with tree age, showing good global (R2≥0.856, RMSE≤0.68 t ha−1) and local accuracies (mean R2≥0.43, RMSE≤0.70 t ha−1). Furthermore, the optimized TDWI exhibited the highest precision, with globally validated R2 of 0.891 and RMSE of 0.591 t ha−1, and local mean R2 of 0.57 and RMSE of 0.66 t ha−1, respectively. The proposed model was not only verified with the confidence to accurately predict yields of jujube, but it can also provide a fundamental strategy for simulating the growth of other fruit trees.

Ceratophyllum demersum L. is a common aquatic herbaceous plant with strong vitality and wide temperature adaptability. It can grow well when the water temperature is as low as 4°C. It is found in natural waters in North China, East China, Central China, and Southwest China. It is distributed and is an important primary producer of ecosystems. The purpose of this study is to establish a numerical model of Ceratophyllum demersum L. individual growth, using the visual modeling software STELLA to describe the key process of Ceratophyllum demersum L. growth and its relationship with environmental parameters, with net growth (Ngrowth) = total growth (Ggrowth) - Respiration - Ekelp is the basic framework to simulate and predict the biomass and leaf length changes of Ceratophyllum demersum L. The model simulates the fit between the length and dry weight results of Ceratophyllum demersum L. and the measured values. The R2 values are 0.945 and 0.964, respectively, indicating that the model can well reflect the true growth of Ceratophyllum demersum L. A reliable individual growth model is the basis for evaluating the cultivation capacity of Ceratophyllum demersum L. and can provide the basis for decision-making for the spatial planning of the cultivation area of Ceratophyllum demersum L. [ABSTRACT FROM AUTHOR]

Colletotrichum species are the most important postharvest spoilage fungi of papaya fruit. The objective of this research was to evaluate the effect of temperature and relative humidity on growth rate and time for growth to become visible of five strains of Colletotrichum gloeosporioides isolated from papaya fruit in a complex medium. As a primary model, the radial growth rates were estimated using the Baranyi and Roberts model in papaya agar. The Solver MS Excel function was used to obtain the time to visible mycelium (tv). Secondary models obtained with the Rosso et al. cardinal model of inflection were applied to describe the effect of temperature on the growth rate (μ). The Arrhenius-Davey model was used to model tv. The obtained models seem to be satisfactory for describing both μ and tv. The relative humidity had an effect on μ and tv for all tested C. gloeosporioides isolates, but no model accurately described the behavior of the fungus. External validation of models was performed with papaya fruit. Growth models were developed with the same models used in vitro. The bias and the accuracy factors as indices for performance evaluation of predictive models in food microbiology as a function of temperature and RH were 1.22 and 1.33, respectively, for μ and 1.18 and 1.62, respectively, for tv, indicating accurate predictions. The supply chain of papaya is complex and requires constant conditions, and poor conditions can result in damage to the fruit. Knowledge of the behavior of C. gloeosporioides on papaya fruit and application of the developed models in the supply chain will help to establish transport control strategies to combat these fungi. This research has contributed to development of the first models of growth for C. gloeosporioides in Mexico. Temperature greatly affected fungal rot of papaya at the postharvest stage. Fungal growth occurred when water was available, regardless of the relative humidity. Predictive models may help food processors make decisions for suboptimal supply chains. [ABSTRACT FROM AUTHOR]

Key message: This synthesis of the literature on incorporation of genetic gain into growth and yield models reveals a fundamental challenge associated with the rapid progress in genetics and breeding and limited empirical data on improved stands. Model improvements depend on a better understanding of both the biological basis for gain and of interactions between genetic and non-genetic factors on gain. Context: Continued development of new genetic varieties of trees requires accurate stand growth and yield models to predict growth trajectories and genetic gain of the new varieties using early-age growth data. Aims: To identify how the effects of genetic variety on growth and yield models could be analyzed and genetic information could be incorporated into these models for accurate growth simulation and improved yield prediction of genetically improved stands. Results: Genetic variety may affect one or several of the asymptotic parameters, shape parameters, and rate parameters of growth and yield models, which can be assessed by testing the parameter differences of the models. After determination of the influence of genetic varieties on model parameters and considering the existing general stand growth equation, the genetic gain can be incorporated into growth and yield models by calculation of genetic gain multipliers, adjustment of the site index, and calibration of the new model parameters. Conclusion: Accurate and effective growth and yield models for genetically improved stands require a better understanding of the effects of genetics, environment, and silviculture measures on tree and stand growth. [ABSTRACT FROM AUTHOR]

This article focuses on the layout design of grooved condenser wick structures to improve the surface temperature uniformity for vapor chamber heat spreaders. The design is formulated as a general "area-to-point" (AP) heat conduction problem in disk-shaped configuration. The fundamental relationship between the heat transfer performance and the grooved wick layouts is discussed from the perspective of constructal optimization. The first-order constructs of the heat generating disk are theoretically optimized when the constraint of minimum length scale is imposed for manufacturability of the high conductivity channels (HCCs) (wick grooves). According to the first-order constructs, the disk domain is divided into a number of identical sectors whose boundaries are all adiabatic. A new growth simulator is then developed to obtain the full constructal layouts, where the HCCs are treated as being alive and the optimization is viewed as an adaptive growth procedure. In each sector, the HCCs sprout from the disk center, extend toward the perimeter, and finally converge at a unique topology that exhibits dichotomous, hierarchical, and branching characteristics. Numerical comparison indicates that the new wick structure improves both the temperature uniformity and the capillary pressure, which can contribute to the vapor chamber heat spreaders with better thermal performance. [ABSTRACT FROM AUTHOR]

Virtual geographic environments related to dynamic processes contribute to a human understanding of the real world. The results of growth simulations provide good estimations of the future status of forests, but they are typically expressed in plain text summaries, tables or static displays, making it difficult to analyse, understand and further apply the forecast data. The objectives of this study were to propose a strategy for integrating a three-dimensional (3D) geographic environment with growth models and to develop a 3D stand visualization software prototype. Forest growth increments were predicted using the growth models, whereas stand dynamics were simulated using detailed tree models to recognize the changes in the branch whorls and height of individual trees. The spatial structure of the stand was represented by linking each tree diameter class to a spatial distribution according to the features of a Voronoi diagram. The stand visualization system VisForest, which allows users to predict increments in the diameter and height of trees, was extended to estimate the number of trees in each diameter class and to visualize many aspects of a forest stand, e.g., individual tree structure, stem diameter at breast height (DBH, i.e., 1.3 m) distribution and height. The software system provides a specialized, intuitive tool for the visualization of a stand, thus facilitating the participation of various stakeholders in management and education. [ABSTRACT FROM AUTHOR]

[Objective]To master the growth law of Beilschmiedia fordii, and to provide reference for the scientific tending of forest in the rapid growing period and llie improvement of forest quality and yield, the regression relationship between tree height (II) , diameter at breast height (DBH) , volume (V) and age (T) and the optimal growth models of Beilschmiedia fordii were studied. [Method] Investigation was conducted on the growth regularity of Beilschmiedia fordii in a 33-year-old plantation located in Nanning Arboretum of Guangxi. The dynamic changes over the years of tree-measuring factors of Beilschmiedia fordii was measured by the method of trunk analysis. [Result] The average DBH, tree height and valume of 33-year old Beilschmiedia fordii plantation were 23. 6 cm, 19. 7 m, 0. 37471 m3 , respectively. Several cross points were presented in the curves of average and successive growth of H and DBH, and wide variations were observed. However, the individual tree volume growth curve exhibited a rising trend during 33a, showing good growing potential. The growth curves of different variables demonstrated that the growth of Beilschmiedia fordii in 6 - 12 years were fast growing periods. The values of 2 of the simulated models were over 0. 99 with high test precision. [Conclusion] The optimal growth models for height, DBH and valume of Beilschmiedia fordii are Schumacher equation, Gomperlz equation and Campez equation, respectively. The volume growth between 30a and 32a is mature; the filled model has high precision and can be used in production practice predictions. [ABSTRACT FROM AUTHOR]

Terrestrial plants have evolved remarkable adaptability that enables them to sense environmental stimuli and use this information as a basis for governing their growth orientation and root system development. In this paper, we explain the foraging behaviors of plant root and develop simulation models based on the principles of adaptation processes that view root growing as optimization. This provides us with new methods for global optimization. Accordingly a novel bioinspired optimizer, namely the root system growth algorithm (RSGA), is proposed, which adopts the root foraging, memory and communication and auxin-regulated mechanism of the root system. Then RSGA is benchmarked against several state-of-the-art reference algorithms on a suit of CEC2014 functions. Experimental results show that RSGA can obtain satisfactory performances on several benchmarks in terms of accuracy, robustness and convergence speed. Moreover, a comprehensive simulation is conducted to investigate the explicit adaptability of root system in RSGA. That is, in order to be able to climb noisy gradients in nutrients in soil, the foraging behaviors of root system are social and cooperative that is analogous to animal foraging behaviors. [ABSTRACT FROM AUTHOR]

Microalgal industrial production requires high surface area, resulting in production costs currently unacceptable. A possible optimization of land use for the cultivation of Scenedesmus obliquus is proposed, by conjoint production of biomass and electricity using photovoltaic cells (PV). For this purpose, biomass cultivation in a continuously operated 1 ha open pond placed inside a greenhouse was considered, at two different Italian latitudes, as case studies. The greenhouse roof surface was partially covered with commercial PV modules, resulting in a reduced average irradiation. The light profiles and the average temperatures inside the greenhouse were simulated for different seasons, and the corresponding microalgal productivities were calculated based on a validated growth model. The partial pond shading limited photoinhibition in summer at Southern location, resulting in higher productivities. On the other hand, the loss of sunlight, due to the partial roof covering, resulted in a lower productivity in the other cases and for the Northern location. The presence of PV, however, allowed a better exploitation of light to produce electricity, which supports the energy duties of the process, with an additional net electricity production. Finally, an economic analysis was carried out showing a reduction of biomass production costs when PV is present. [ABSTRACT FROM AUTHOR]

This study simulated the bulk structure and surface energy of Al2O3 based on the density of states (DOS) and studied the synthesis and microstructure of one-dimensional Al2O3 whiskers. The simulation results indicate that the (001) surface has a higher surface energy than the others. The growth mechanism of Al2O3 whiskers follows vapor-solid (VS) growth. For the (001) surface with the higher surface energy, the driving force of crystal growth would be more intense in the (001) plane, and the alumina crystal would tend to grow preferentially along the direction of the (001) plane from the tip of the crystal. The Al2O3 grows to the shape of whisker with [001] orientation, which is proved both through modeling and experimentation. [ABSTRACT FROM AUTHOR]

Molds are responsible for postharvest spoilage of citrus fruits. The objective of this study was to evaluate the effect of temperature on growth rate and the time to visible growth of Aspergillus niger strains isolated from citrus fruits. The growth of these strains was studied on agar lime medium (AL) at different temperatures, and growth rate was estimated using the Baranyi and Roberts model (Int. J. Food Microbiol. 23:277–294, 1994). The Rosso et al. cardinal model with inflexion (L. Rosso, J. R. Lobry, S. Bajard, and J. P. Flandrois, J. Theor. Biol. 162:447–463, 1993) was used as a secondary model to describe the effect of temperature on growth rate and the lag phase. We hypothesized that the same model could be used to calculate the time for the mycelium to become visible (tv) by substituting the lag phase (1/λ and 1/λopt) with the time to visible colony (1/tv-opt and 1/tv), respectively, in the Rosso et al. model. High variability was observed at suboptimal conditions. Extremes of temperature of growth for A. niger seem to have a normal variability. For the growth rate and time tv, the model was satisfactorily compared with results of previous studies. An external validation was performed in lime fruits; the bias and accuracy factors were 1.3 and 1.5, respectively, for growth rate and 0.24 and 3.72, respectively, for the appearance time. The discrepancy may be due to the influence of external factors. A. niger grows significantly more slowly on lime fruit than in culture medium, probably because the nutrients are more easily available in medium than in fruits, where the peel consistency may be a physical barrier. These findings will help researchers understand the postharvest behavior of mold on lime fruits, host-pathogen interactions, and environmental conditions infecting fruit and also help them develop guidelines for future work in the field of predictive mycology to improve models for control of postharvest fungi. [ABSTRACT FROM AUTHOR]

This paper has proposed an additive design method for the design of stiffening topology of load-bearing structures in a growth manner. The idea of the method is drawn from the observation that branching structures in nature (e.g., leaf venation) can effectively support a relatively large structure or perfuse a relatively large region. The excellent performance of branching structures is considered as a result of their adaptive growth with respect to the environmental conditions and their configuration features of branching and hierarchy. To apply the principle of adaptive growth to stiffener layout design, a mathematical model for growth simulation is constructed. Based on this, an evolutionary algorithm is developed to implement the adaptive growth of stiffeners. A numerical treatment called 'stiffness transforming operation' is introduced to enable stiffeners to grow along arbitrary directions and thus form optimized stiffener layouts. The effectiveness of the proposed method is verified with numerical examples. [ABSTRACT FROM AUTHOR]

This paper proposes a growth simulation approach to optimize the internal cooling geometries in heat conduction system. The idea is inspired by the well-known constructal theory which generates the heat conducting paths by a sequence of optimization and organization steps. Firstly, numerical experiments are implemented to confirm the potential of leaf veins as concept generators for conducting path design. Then, a computational framework is built to simulate the adaptive growth of conductive cooling channels. To make the channels being able to grow freely in the domain, a new method called ‘conductivity spreading approach (CSA)’ is developed to transform nodal temperatures of growing channels into those of the underlying ground structure. With such transformation, growth dependences on the initial ground structure, like the nodes connections and locations, are eliminated and cooling channels can therefore grow towards an arbitrary direction to form an optimum layout solution. To illustrate the growth simulation in a directive and descriptive manner, a fundamental ‘volume-to-point’ problem is considered, in which the high conductivity material grows starting from the heat sink, extends spreading the whole region, and forms at convergence a configuration of tree-like network. The proposed constructal optimization method promises to be an “intelligent” CAD approach for various conductive cooling design applications. [ABSTRACT FROM AUTHOR]

This paper proposes a novel topology optimization method for designing the best-possible heat conduction paths. The design idea is originated from the natural observation that plant roots or leaf veins care by self-adaptive growth to minimize the flow resistance through the whole networks. Based on the analogy between fluid flow and heat flow problems, the natural growth rule is systematically transformed into a mathematical model and written as an algorithm, where the high conductivity material is treated as being alive and the topology optimization process is viewed as plant morphogenesis process. Specifically, a new treatment called ‘conductivity spreading approach (CSA)’ is proposed to transform nodal temperatures of cooling channels into those of the background mesh, by which cooling channels can be separated from the underlying grid so that they can branch and extend freely along any direction. The growth method is used to construct the heat conduction paths for a fundamental ‘volume-to-point’ problem. Unlike other methods, layout solution produced by the suggested method is favorable to practical problems because it provides clear information about the location, orientation and dimensions of each cooling channel. In addition, the growth method requires little of human involvement and is easily delegated to computers, offering great advantage of automated design for large-scale cooling channel layouts in heat conduction systems. [ABSTRACT FROM AUTHOR]

Virtual Geographic Environments (VGEs) represent a new analytical tool for understanding geographic processes. Among the fundamental solutions to advancing and deepening the development of VGEs are geographic modeling, geographic simulation, and geographic knowledge sharing. Forest is a major component of the geographic environment. This article proposes an integrated approach for analyzing and exploring plant growth processes and the relationship between plant growth and the environment, and describes the development of a software prototype that integrates ontology, artificial intelligence (AI) and virtual plant techniques. The strategy is as follows: First, we collect existing information on the growth and development patterns, morphological structure, and environment of a chosen plant from the botany, forestry, and ecology literature. Then, we construct an ontology framework to organize the collected information and individual cases into a knowledge base and support the inferential reasoning, botanical modeling and simulation. Through rule-based reasoning (RBR) and case-based reasoning (CBR), complex relationships between tree growth and the environment can be extracted. Next, the newly derived knowledge is integrated with a 3D method for modeling the growth of individual tree based on the same ontology framework. Finally, based on the description of the tree species, environment, growth stage, and phenophase, among other factors, key tree morphology parameters are derived via semantic reasoning. Using these parameters, a new 3D tree model is generated that is consistent with the specific habitat and growth phase. Our approach is useful for users who have little knowledge of botany or who lack the computer skills to construct realistic 3D tree models that are faithful to botanical features. [ABSTRACT FROM AUTHOR]

Carbon is the most widely studied material today because it exhibits special properties not seen in any other materials when in nano dimensions such as nanotube and graphene. Reduction of material defects created during synthesis has become critical to realize the full potential of carbon structures. Molecular dynamics (MD) simulations, in principle, allow defect formation mechanisms to be studied with high fidelity, and can, therefore, help guide experiments for defect reduction. Such MD simulations must satisfy a set of stringent requirements. First, they must employ an interatomic potential formalism that is transferable to a variety of carbon structures. Second, the potential needs to be appropriately parameterized to capture the property trends of important carbon structures, in particular, diamond, graphite, graphene, and nanotubes. Most importantly, the potential must predict the crystalline growth of the correct phases during direct MD simulations of synthesis to achieve a predictive simulation of defect formation. Because an unlimited number of structures not included in the potential parameterization are encountered, the literature carbon potentials are often not sufficient for growth simulations. We have developed an analytical bond order potential for carbon, and have made it available through the public MD simulation package LAMMPS. We demonstrate that our potential reasonably captures the property trends of important carbon phases. Stringent MD simulations convincingly show that our potential accounts not only for the crystalline growth of graphene, graphite, and carbon nanotubes but also for the transformation of graphite to diamond at high pressure. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

We present an interactive tree modeling and deformation system that supports an efficient collision detection and avoidance using a bounding volume hierarchy of sweep surfaces. Starting with conventional tree models (given as meshes), we convert them into sweep surfaces and deform their branches interactively while detecting and avoiding collisions with many other branches. Multiple tree models (sharing the same topology) can be generated with great ease using this sweep-based approach, and they can serve as a basis for the generation of a multiparameter family of trees. We demonstrate the effectiveness of our approach in an automatic generation of similar trees, the colonization of trees to form a forest, and the tree growth, aging, and withering simulations. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Spectral reflectance of differentially-managed rice canopies was measured over an entire growing season and analyzed with special attention to linking remotely sensed information with a simple growth model. The fraction of absorbed photosynthetically active radiation (fAPAR), which is often used as a key variable in simple process models, was well correlated writh spectral vegetation indices (VI). VIs, such as NDVI and SAVI, were derived from the ratio of reflectance at two wavelengths (R660 nm and R830 nm) and a new VI, termed the normalized difference ND [R1100 nm, R660 nm], was derived from the difference of Rl 100 nm and R660 nm divided by their sum. These close relations between fAPAR and Vis were expressed by exponential formulae with different parameters for the periods before and after heading. These indices became less sensitive to fAPAR when fAPAR was larger than 0.4. The use of R1100 nm and R1650 nm with R660 nm and R830 nm in multiple regression significantly improved the prediction accuracy of fAPAR. A close linear relation was found between a spectral ratio R830 nm/R550 nm and leaf nitrogen content during the ripening period although it was not the case before heading. Results suggested that R830 nm/R550 nm was effective for estimation of leaf nitrogen content when the paddy field was regarded as a big leaf. The total amount of leaf nitrogen was well correlated with ND [R1100 nm, R660 nm] ; nevertheless, the sensitivity was lost when the total amount of leaf nitrogen was greater than 3 g m−2. Multiple regression analysis showed that a combination of four spectral bands R550 nm, R830 nm, R1650 nm and R2200 nm was useful for estimation of the total amount of leaf nitrogen. Remotely-sensed nitrogen variables would be a potential model parameters in a simple model. A real-time recalibration module based on a simplex algorithm was developed and proved effective in linking the remotely-sensed fAPAR with a simple model. This approach was also useful for inferring the physiological parameters such as radiation use efficiency for each rice canopy without destructive sampling. The re-parameterization and/or re-initialization with remotely-sensed information was demonstrated to be a practical and effective approach, especially for operational purposes.

The aim of this study was to develop and apply an implicit yield model based on the Weibull probability density function for the predictions of yield by diameter class for a logged tropical rainforest located in the center of Amazon. The study area is located in the Tropical Forest Experimental Station, 90 km from the urban center of Manaus, AM, Brazil. The data came from 12 permanent 1 ha plots, logged at three levels of basal area removal intensities. In each plot all individuals with DBH 10 cm between 1990 and 2009 were measured annually. Functions were used to describe the dynamics of tree abundance (recruitment and mortality), basal area, summed diameters per hectare, and a new statistic for classification of forest yield, in order to estimate the sample moments of minimum, average and quadratic mean diameter in 2009. The Weibull diameter distribution was fitted using the method of moments and validated by data collected in 2009. The inclusion of variables that reflect the productive potential in the proposed model facilitates the evaluation of forests that have undergone changes in its structural characteristics in the different sites. The use of an alternative technique for classification led to a better understanding of the management regimes applied to the forests under analysis. The proposed model proved efficient by the Kolmogorov-Smirnov test, and thus may be used in updating inventory statistics, calculations of annual cut and in planning forest by companies that work in uneven aged and mixed forests in different sites of the Amazon. [ABSTRACT FROM AUTHOR]

In this paper, we present a new, easy-to-generate system that is capable of creating virtual 3D tree models and simulating a variety of growth processes of a tree from a single, real tree image. We not only construct various tree models with the same trunk through our proposed digital image matting method and skeleton-based abstraction of branches, but we also animate the visual growth of the constructed 3D tree model through usage of the branch age information combined with a scaling factor. To control the simulation of a tree growth process, we consider treegrowing attributes, such as branching orders, branch width, tree size, and branch self-bending effect, at the same time. Other invisible branches and leaves are automatically attached to the tree by employing parametric branch libraries under the conventional procedural assumption of structure having a local selfsimilarity. Simulations with a real image confirm that our system makes it possible to achieve realistic tree models and growth processes with ease. [ABSTRACT FROM AUTHOR]

The present study proposes efficient procedural modeling methods for enabling the growth and creation of various trees with minimal user control. Growth volume algorithms are utilized in order to easily and effectively calculate many parameters that determine tree growth, including branch propagation. Procedural methods are designed so that users' interactive control structures can be applied to these algorithms to create unique tree models efficiently. First, through a two-line-based interactive growth volume control method, the growth information that determines the overall shape of the tree is intuitively adjusted. Thereafter, independent branch control methods designed to control individual branches are added to the growth deformation in order to enable the growth of unique trees. Whether the growth processes of desired trees can be easily and intuitively controlled by the proposed method is verified through experiments. Methods that can apply the proposed methods are also verified. [ABSTRACT FROM AUTHOR]