An improved energy demand forecasting model is built based on the autoregressive distributed lag (ARDL) bounds testing approach and an adaptive genetic algorithm (AGA) to obtain credible energy demand forecasting results. The ARDL bounds analysis is first employed to select the appropriate input variables of the energy demand model. After the existence of a cointegration relationship in the model is confirmed, the AGA is then employed to optimize the coefficients of both linear and quadratic forms with gross domestic product, economic structure, urbanization, and technological progress as the input variables. On the basis of historical annual data from 1985 to 2015, the simulation results indicate that the proposed model has greater accuracy and reliability than conventional optimization methods. The predicted results of the proposed model also demonstrate that China will demand approximately 4.9, 5.6, and 6.1 billion standard tons of coal equivalent in 2020, 2025, and 2030, respectively. 相似文献
Objective: A novel anthropomorphic test device (ATD) representative of the 50th percentile male soldier is being developed to predict injuries to a vehicle occupant during an underbody blast (UBB). The main objective of this study was to develop and validate a finite element (FE) model of the ATD lower limb outfitted with a military combat boot and to insert the validated lower limb into a model of the full ATD and simulate vertical loading experiments.
Methods: A Belleville desert combat boot model was assigned contacts and material properties based on previous experiments. The boot model was fit to a previously developed model of the barefoot ATD. Validation was performed through 6 matched pair component tests conducted on the Vertically Accelerated Loads Transfer System (VALTS). The load transfer capabilities of the FE model were assessed along with the force-mitigating properties of the boot. The booted lower limb subassembly was then incorporated into a whole-body model of the ATD. Two whole-body VALTS experiments were simulated to evaluate lower limb performance in the whole body.
Results: The lower limb model accurately predicted axial loads measured at heel, tibia, and knee load cells during matched pair component tests. Forces in booted simulations were compared to unbooted simulations and an amount of mitigation similar to that of experiments was observed. In a whole-body loading environment, the model kinematics match those recorded in experiments. The shape and magnitude of experimental force–time curves were accurately predicted by the model. Correlation between the experiments and simulations was backed up by high objective rating scores for all experiments.
Conclusion: The booted lower limb model is accurate in its ability to articulate and transfer loads similar to the physical dummy in simulated underbody loading experiments. The performance of the model leads to the recommendation to use it appropriately as an alternative to costly ATD experiments. 相似文献
Maintenance of biodiversity through seed banks and botanical gardens, where the wealth of species’ genetic variation may be preserved ex situ, is a major goal of conservation. However, challenges can persist in optimizing ex situ collections if trade-offs exist among cost, effort, and conserving species evolutionary potential, particularly when genetic data are not available. We evaluated the genetic consequences of population preservation informed by geographic (isolation by distance [IBD]) and environmental (isolation by environment [IBE]) distance for ex situ collections for which population provenance is available. We used 19 genetic and genomic data sets from 15 plant species to assess the proportion of population genetic differentiation explained by geographic and environmental factors and to simulate ex situ collections prioritizing source populations based on pairwise geographic distance, environmental distance, or both. Specifically, we tested the impact prioritizing sampling based on these distances may have on the capture of neutral, functional, or putatively adaptive genetic diversity and differentiation. Individually, IBD and IBE explained limited population genetic differences across all 3 genetic marker classes (IBD, 10–16%; IBE, 1–5.5%). Together, they explained a substantial proportion of population genetic differences for functional (45%) and adaptive (71%) variation. Simulated ex situ collections revealed that inclusion of IBD, IBE, or both increased allelic diversity and genetic differentiation captured among populations, particularly for loci that may be important for adaptation. Thus, prioritizing population collections based on environmental and geographic distance data can optimize genetic variation captured ex situ. For the vast majority of plant species for which there is no genetic information, these data are invaluable to conservation because they can guide preservation of genetic variation needed to maintain evolutionary potential within collections. 相似文献
The availability of genomic data for an increasing number of species makes it possible to incorporate evolutionary processes into conservation plans. Recent studies show how genetic data can inform spatial conservation prioritization (SCP), but they focus on metrics of diversity and distinctness derived primarily from neutral genetic data sets. Identifying adaptive genetic markers can provide important information regarding the capacity for populations to adapt to environmental change. Yet, the effect of including metrics based on adaptive genomic data into SCP in comparison to more widely used neutral genetic metrics has not been explored. We used existing genomic data on a commercially exploited species, the giant California sea cucumber (Parastichopus californicus), to perform SCP for the coastal region of British Columbia (BC), Canada. Using a RAD-seq data set for 717 P. californicus individuals across 24 sampling locations, we identified putatively adaptive (i.e., candidate) single nucleotide polymorphisms (SNPs) based on genotype–environment associations with seafloor temperature. We calculated various metrics for both neutral and candidate SNPs and compared SCP outcomes with independent metrics and combinations of metrics. Priority areas varied depending on whether neutral or candidate SNPs were used and on the specific metric used. For example, targeting sites with a high frequency of warm-temperature-associated alleles to support persistence under future warming prioritized areas in the southern coastal region. In contrast, targeting sites with high expected heterozygosity at candidate loci to support persistence under future environmental uncertainty prioritized areas in the north. When combining metrics, all scenarios generated intermediate solutions, protecting sites that span latitudinal and thermal gradients. Our results demonstrate that distinguishing between neutral and adaptive markers can affect conservation solutions and emphasize the importance of defining objectives when choosing among various genomic metrics for SCP. 相似文献