Combining system dynamic model and CLUE-S model to improve land use scenario analyses at regional scale: A case study of Sangong watershed in Xinjiang, China

Uses of models of land use change are primary tools for analyzing the causes and consequences of land use changes, assessing the impacts of land use change on ecosystems and supporting land use planning and policy. However, no single model is able to capture all of key processes essential to explore land use change at different scales and make a full assessment of driving factors and impacts. Based on the multi-scale characteristics of land use change, combination and integration of currently existed models of land use change could be a feasible solution. Taken Sangong watershed as a case study, this paper describes an integrated methodology in which the conversion of land use and its effect model (CLUE), a spatially explicit land use change model, has been combined with a system dynamic model (SD) to analyze land use dynamics at different scales. A SD model is used to calculate area changes in demand for land types as a whole while a CLUE model is used to transfer these demands to land use patterns. Without the spatial consideration, the SD model ensures an appropriate treatment of macro-economic, demographic and technology developments, and changes in economic policies influencing the demand and supply for land use in a specific region. With CLUE model the land use change has been simulated at a high spatial resolution with the spatial consideration of land use suitability, spatial policies and restrictions to satisfy the balance between land use demand and supply. The application of the combination of SD and CLUE model in Sangong watershed suggests that this methodology have the ability to reflect the complex behaviors of land use system at different scales to some extent and be a useful tool for analysis of complex land use driving factors such as land use policies and assessment of its impacts on land use change. The established SD model was fitted or calibrated with the 1987-1998 data and validated with the 1998-2004 data; combining SD model with CLUE-S model, future land use scenarios were analyzed during 2004-2030. This work could be used for better understanding of the possible impacts of land use change on terrestrial ecosystem and provide scientific support for land use planning and managements of the watershed. (C) 2010 Elsevier B.V. All rights reserved

Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction

Potential crowd flow prediction for new planned transportation sites is a fundamental task for urban planners and administrators. Intuitively, the potential crowd flow of the new coming site can be implied by exploring the nearby sites. However, the transportation modes of nearby sites (e.g. bus stations, bicycle stations) might be different from the target site (e.g. subway station), which results in severe data scarcity issues. To this end, we propose a data driven approach, named MOHER, to predict the potential crowd flow in a certain mode for a new planned site. Specifically, we first identify the neighbor regions of the target site by examining the geographical proximity as well as the urban function similarity. Then, to aggregate these heterogeneous relations, we devise a cross-mode relational GCN, a novel relation-specific transformation model, which can learn not only the correlations but also the differences between different transportation modes. Afterward, we design an aggregator for inductive potential flow representation. Finally, an LTSM module is used for sequential flow prediction. Extensive experiments on real-world data sets demonstrate the superiority of the MOHER framework compared with the state-of-the-art algorithms.Comment: Accepted by the 35th AAAI Conference on Artificial Intelligence (AAAI 2021

Proteome expression patterns in the stress tolerant evergreen Ammopiptanthus nanus under conditions of extreme cold

Low temperature is one of the important environmental changes that affect plant growth. The cold resistance capabilities of evergreen plants are the result of long-term adaptation to extreme environmental conditions. To investigate the responses of Ammopiptanthus nanus, a rare stress-tolerant evergreen plant, to extreme cold stress, we analyzed the proteome expression patterns of stressed plants; this is the first study to report these patterns for A. nanus. We collected adult A. nanus leaves under two conditions of cold stress: extreme cold (-29 degrees C) and relatively less extreme cold (-5 degrees C). Total crude proteins were extracted from leaf blades, separated by two-dimensional gel electrophoresis, and stained with Coomassie brilliant blue. Of the 500 protein spots detected in each of the samples, eight of the spots that exhibited clear changes under the different conditions were identified by MALDI-TOF analyses. Our results suggest that cold stress-related proteins may play diverse roles in the resistance to multiple environmental stresses

IGFBP2 Plays an Essential Role in Cognitive Development during Early Life

Identifying the mechanisms underlying cognitive development in early life is a critical objective. The expression of insulin-like growth factor binding protein 2 (IGFBP2) in the hippocampus increases during neonatal development and is associated with learning and memory, but a causal connection has not been established. Here, it is reported that neurons and astrocytes expressing IGFBP2 are distributed throughout the hippocampus. IGFBP2 enhances excitatory inputs onto CA1 pyramidal neurons, facilitating intrinsic excitability and spike transmission, and regulates plasticity at excitatory synapses in a cell-type specific manner. It facilitates long-term potentiation (LTP) by enhancing N-methyl-d-aspartate (NMDA) receptor-dependent excitatory postsynaptic current (EPSC), and enhances neurite proliferation and elongation. Knockout of igfbp2 reduces the numbers of pyramidal cells and interneurons, impairs LTP and cognitive performance, and reduces tonic excitation of pyramidal neurons that are all rescued by IGFBP2. The results provide insight into the requirement for IGFBP2 in cognition in early life

Neoproterozoic to Paleozoic long-lived accretionary orogeny in the northern Tarim Craton

The Tarim Craton, located in the center of Asia, was involved in the assembly and breakup of the Rodinia supercontinent during the Neoproterozoic and the subduction-accretion of the Central Asian Orogenic Belt (CAOB) during the Paleozoic. However, its tectonic evolution during these events is controversial, and a link between the Neoproterozoic and Paleozoic tectonic processes is missing. Here we present zircon U-Pb ages, Hf isotopes, and whole-rock geochemical data for the extensive granitoids in the western Kuruktag area, northeastern Tarim Craton. Three distinct periods of granitoid magmatism are evident: circa 830–820 Ma, 660–630 Ma, and 420–400 Ma. The magma sources, melting conditions (pressure, temperature, and water availability), and tectonic settings of various granitoids from each period are determined. Based on our results and the geological, geochronological, geochemical, and isotopic data from adjacent areas, a long-lived accretionary orogenic model is proposed. This model involves an early phase (circa 950–780 Ma) of southward advancing accretion from the Tianshan to northern Tarim and a late phase (circa 780–600 Ma) of northward retreating accretion, followed by back-arc opening and subsequent bidirectional subduction (circa 460–400 Ma) of a composite back-arc basin (i.e., the South Tianshan Ocean). Our model highlights a long-lived accretionary history of the southwestern CAOB, which may have initiated as part of the circum-Rodinia subduction zone and was comparable with events occurring at the southern margin of the Siberian Craton, thus challenging the traditional southward migrating accretionary models for the CAOB

System design and control integration for advanced manufacturing

Most existing robust design books address design for static systems, or achieve robust design from experimental data via the Taguchi method. Little work considers model information for robust design particularly for the dynamic system. This book covers robust design for both static and dynamic systems using the nominal model information or the hybrid model/data information, and also integrates design with control under a large operating region. This design can handle strong nonlinearity and more uncertainties from model and parameters