Error Thresholds in Single-Peak Gaussian Distributed Fitness Landscapes

Based on the Eigen and Crow-Kimura models with a single-peak fitness landscape, we propose the fitness values of all sequence types to be Gausslan distributed random variables to incorporate the effects of the fluctuations of the fitness landscapes （noise of environments） and investigate the concentration distribution and error threshold of quasispecies by performing an ensemble average within this theoretical framework. We find that a small fluctuation of the fitness landscape causes only a slight change in the concentration distribution and error threshold, which implies that the error threshold is stable against small perturbations. However, for a sizable fluctuation, quite different from the previous deterministic models, our statistical results show that the transition from quasi-species to error catastrophe is not so sharp, indicating that the error threshold is located within a certain range and has a shift toward a larger value. Our results are qualitatively in agreement with the experimental data and provide a new implication for antiviral strategies.

STUDIES OF BEAUTIFUL GEOGRAPHY

This paper studies an interdisciplinary subject of aesthetics andgeography-beautiful geography .Firsly,it expounds and proves theobjective existence of the beautiful geography from the aims and tasks,objects and contents of study in aesthetics and geography in relation totheir branch sciences.Secondly, it discusses the study objects and studycontents and nature of the beautiful geography.It concludes that studyobjects of beautiful geography is the beautifolness of geographic objects.The contents of study contain:1) aesthetic laws and principles of thegeographic objects and human experience to the geographic objects,2)aesthetic value and appraisal of the geographic objects, use of aestheticvalue of the geographic objects; 3) perceptional and behavior effction of the beatiful geographic objects along with its uses; and 4) beautification ofthe geographic objects and constructing beautiful geographic objects.Lastly, it investigates the significance and use of the beautiful geography,especially in distribution of production,urban planning, the appraisal ofresources and regionalization and planning and the construction of tourism.

Envisioning Landscape Justice:Interdisciplinary Dialogue,Collaboration,and Exploration

As an extension of environmental justice,landscape justice emphasizes achieving inclusive and equitable planning and design in both built and natural environments,allowing different social groups to enjoy and share landscape resources and benefits more equally.By endowing landscape design with a“just”orientation,landscape justice significantly improves the spatial and environmental benefits while promotes the process of environmental justice.Landscape justice is characterized by its interdisciplinary nature,showing great variability in spatio-temporal scales,site dimensions and attributes,and social groups and scenarios,the research of which urgently requires in-depth dialogues,sincere collaborations,and active explorations among multiple disciplines.We call for enriching the connotation of landscape justice through interdisciplinary perspectives and addressing practical issues,to provide innovative spatial propositions and paths for creating sustainable urban environments and landscapes.

Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

With the promotion of“dual carbon”strategy,data center(DC)access to high-penetration renewable energy sources(RESs)has become a trend in the industry.However,the uncertainty of RES poses challenges to the safe and stable operation of DCs and power grids.In this paper,a multi-timescale optimal scheduling model is established for interconnected data centers(IDCs)based on model predictive control(MPC),including day-ahead optimization,intraday rolling optimization,and intraday real-time correction.The day-ahead optimization stage aims at the lowest operating cost,the rolling optimization stage aims at the lowest intraday economic cost,and the real-time correction aims at the lowest power fluctuation,eliminating the impact of prediction errors through coordinated multi-timescale optimization.The simulation results show that the economic loss is reduced by 19.6%,and the power fluctuation is decreased by 15.23%.