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In humans and in foveated animals visual acuity is highly concentrated at the center of gaze, so that choosing where to look next is an important example of online, rapid decision-making. Computational neuroscientists have developed biologically-inspired models of visual attention, termed saliency maps, which successfully predict where people fixate on average. Using point process theory for spatial statistics, we show that scanpaths contain, however, important statistical structure, such as spatial clustering on top of distributions of gaze positions. Here, we develop a dynamical model of saccadic selection that accurately predicts the distribution of gaze positions as well as spatial clustering along individual scanpaths. Our model relies on activation dynamics via spatially-limited (foveated) access to saliency information, and, second, a leaky memory process controlling the re-inspection of target regions. This theoretical framework models a form of context-dependent decision-making, linking neural dynamics of attention to behavioral gaze data.
Ecologists urgently need a better ability to predict how environmental change affects biodiversity. We examine individual-based ecology (IBE), a research paradigm that promises better a predictive ability by using individual-based models (IBMs) to represent ecological dynamics as arising from how individuals interact with their environment and with each other. A key advantage of IBMs is that the basis for predictions-fitness maximization by individual organisms-is more general and reliable than the empirical relationships that other models depend on. Case studies illustrate the usefulness and predictive success of long-term IBE programs. The pioneering programs had three phases: conceptualization, implementation, and diversification. Continued validation of models runs throughout these phases. The breakthroughs that make IBE more productive include standards for describing and validating IBMs, improved and standardized theory for individual traits and behavior, software tools, and generalized instead of system-specific IBMs. We provide guidelines for pursuing IBE and a vision for future IBE research.
This study presents the development of 1D and 2D Surface Evolution Codes (SECs) and their coupling to any lithospheric-scale (thermo-)mechanical code with a quadrilateral structured surface mesh.
Both SECs involve diffusion as approach for hillslope processes and the stream power law to reflect riverbed incision. The 1D SEC settles sediment that was produced by fluvial incision in the appropriate minimum, while the supply-limited 2D SEC DANSER uses a fast filling algorithm to model sedimantation. It is based on a cellular automaton. A slope-dependent factor in the sediment flux extends the diffusion equation to nonlinear diffusion. The discharge accumulation is achieved with the D8-algorithm and an improved drainage accumulation routine. Lateral incision enhances the incision's modelling. Following empirical laws, it incises channels of several cells width.
The coupling method enables different temporal and spatial resolutions of the SEC and the thermo-mechanical code. It transfers vertical as well as horizontal displacements to the surface model. A weighted smoothing of the 3D surface displacements is implemented. The smoothed displacement vectors transmit the deformation by bilinear interpolation to the surface model. These interpolation methods ensure mass conservation in both directions and prevent the two surfaces from drifting apart.
The presented applications refer to the evolution of the Pamir orogen. A calibration of DANSER's parameters with geomorphological data and a DEM as initial topography highlights the advantage of lateral incision. Preserving the channel width and reflecting incision peaks in narrow channels, this closes the huge gap between current orogen-scale incision models and observed topographies.
River capturing models in a system of fault-bounded block rotations reaffirm the importance of the lateral incision routine for capturing events with channel initiation. The models show a low probability of river capturings with large deflection angles. While the probability of river capturing is directly depending on the uplift rate, the erodibility inside of a dip-slip fault speeds up headward erosion along the fault: The model's capturing speed increases within a fault.
Coupling DANSER with the thermo-mechanical code SLIM 3D emphasizes the versatility of the SEC. While DANSER has minor influence on the lithospheric evolution of an indenter model, the brittle surface deformation is strongly affected by its sedimentation, widening a basin in between two forming orogens and also the southern part of the southern orogen to south, east and west.
An increasing demand on functionality and flexibility leads to an integration of beforehand isolated system solutions building a so-called System of Systems (SoS). Furthermore, the overall SoS should be adaptive to react on changing requirements and environmental conditions. Due SoS are composed of different independent systems that may join or leave the overall SoS at arbitrary point in times, the SoS structure varies during the systems lifetime and the overall SoS behavior emerges from the capabilities of the contained subsystems. In such complex system ensembles new demands of understanding the interaction among subsystems, the coupling of shared system knowledge and the influence of local adaptation strategies to the overall resulting system behavior arise. In this report, we formulate research questions with the focus of modeling interactions between system parts inside a SoS. Furthermore, we define our notion of important system types and terms by retrieving the current state of the art from literature. Having a common understanding of SoS, we discuss a set of typical SoS characteristics and derive general requirements for a collaboration modeling language. Additionally, we retrieve a broad spectrum of real scenarios and frameworks from literature and discuss how these scenarios cope with different characteristics of SoS. Finally, we discuss the state of the art for existing modeling languages that cope with collaborations for different system types such as SoS.