Evaluation of the use of the national academic network of advanced technology (renata) in Colombia

This paper models the operation of Internet 2, the advanced national academic network (RENATA) in Colombia, by as-sessing the fundamental services that it supports and its respective performance. The academic and scientific importance of the article lies on discussing the problem of NRAN networks not being harnessed as scientific tools that may have a domino effect by driving the use of said tools in different education and research centers of the highest level. It is concluded that the connectivity model in the associated networks, i.e., the university networks of every important city within RENATA do not effectively use the advantages of bandwidth capacity, hereby proven with 0.039 Gbps.

Study on Production Optimization Method of Fractured Reservoir Based on Connectivity Model

Due to the extensive development of fractures and serious heterogeneity in fractured reservoirs, it is difficult for the traditional numerical simulation method to invert its geology, which greatly limits the efficiency and accuracy of simulation and cannot realize the real-time optimization of production scheme. The connectivity model can only consider the two characteristic parameters of conductivity and connectivity volume, which does not involve complex and rigorous geological modeling. It can quickly and accurately reflect the state of the real reservoir, greatly reducing the simulation time, and is suitable for real-time production performance prediction of the reservoir. Due to the large difference in conductivity of fractured reservoirs, the difficulty of fitting increases. In this paper, the connectivity model is first applied to fractured reservoirs to realize the production dynamic simulation of fractured reservoirs. The optimization principle is used to optimize the injection-production scheme with the economic net present value as the objective function. In order to verify the method, the connectivity model is applied to Mu 30 of Changqing Oilfield in this paper. The results show that this method can effectively reflect the real production situation of the oilfield and the connectivity of the reservoir, and the simulation time is relatively fast. After optimization, the cumulative oil production of the reservoir increases by 8.1%, the cumulative water injection decreases by 2.3%, and the rising rate of water cut decreases by 58.8%, indicating that the connectivity model can realize the real-time production optimization of the reservoir.

Beyond Rings: Gathering in 1-Interval Connected Graphs

We examine the problem of gathering [Formula: see text] agents (or multi-agent rendezvous) in dynamic graphs which may change in every round. We consider a variant of the [Formula: see text]-interval connectivity model [9] in which all instances (snapshots) are always connected spanning subgraphs of an underlying graph, not necessarily a clique. The agents are identical and not equipped with explicit communication capabilities, and are initially arbitrarily positioned on the graph. The problem is for the agents to gather at the same node, not fixed in advance. We first show that the problem becomes impossible to solve if the underlying graph has a cycle. In light of this, we study a relaxed version of this problem, called weak gathering, where the agents are allowed to gather either at the same node, or at two adjacent nodes. Our goal is to characterize the class of 1-interval connected graphs and initial configurations in which the problem is solvable, both with and without homebases. On the negative side we show that when the underlying graph contains a spanning bicyclic subgraph and satisfies an additional connectivity property, weak gathering is unsolvable, thus we concentrate mainly on unicyclic graphs. As we show, in most instances of initial agent configurations, the agents must meet on the cycle. This adds an additional difficulty to the problem, as they need to explore the graph and recognize the nodes that form the cycle. We provide a deterministic algorithm for the solvable cases of this problem that runs in [Formula: see text] number of rounds.

Can fMRI functional connectivity index dynamic neural communication?

In order to continuously respond to a changing environment and support self-generating cognition and behaviour, neural communication must be highly flexible and dynamic at the same time than hierarchically organized. While whole-brain fMRI measures have revealed robust yet changing patterns of statistical dependencies between regions, it is not clear whether these statistical patterns (referred to as functional connectivity) can reflect dynamic large-scale communication in a way that is relevant to cognition. For functional connectivity to reflect actual communication, we propose three necessary conditions: it must span sufficient temporal complexity to support the needs of cognition while still being highly organized so that the system behaves reliably; it must be able to adapt to the current behavioural context; and it must exhibit fluctuations at sufficiently short timescales. In this paper, we introduce principal components of connectivity analysis (PCCA), an approach based on running principal component analysis on multiple runs of a time-varying functional connectivity model to show that functional connectivity follows low- yet multi-dimensional trajectories that can be reliably measured, and that these trajectories meet the aforementioned criteria to index flexible communication between neural populations and support moment-to-moment cognition.

Deterministic, random, or in between? Inferring the randomness level of wildlife movements

Background When assessing connectivity, it is crucial to rely on accurate modeling frameworks that consider species movement preferences and patterns. One important aspect is the level of randomness or unpredictability in the route selection. In this respect, traditional approaches (based on least-cost path or circuit theory) consider species movements unrealistically as totally deterministic or as totally random. A recent approach (randomized shortest path) advocates for choosing intermediate levels of randomness through a single parameter. This parameter may be optimized by validating connectivity surfaces developed from different levels of randomness against observed movement data. However, connectivity models are seldom validated, and it is still unclear how to approach this task. To address this knowledge gap, this paper aims at comparing different validation methods to infer the optimal randomness level in connectivity studies. Additionally, we aimed to disentangle the practical consequences of applying traditional connectivity approaches versus using an optimized level of movement randomness when delineating corridors. Methods These objectives were accomplished through the study case of the Iberian lynx, an endangered species whose maintenance and recovery depend on the current connectivity among its population nuclei. We firstly determined a conductance surface based on point selection functions accounting for the behavioral state (territorial or exploratory) of individuals. Secondly, we identified the level of randomness that better fits lynxes’ movements with independent GPS locations and different validation techniques. Lastly, we delineated corridors between lynx population nuclei through a) the randomized shortest path approach and the extreme and optimal levels of randomness of each validation method, and b) the traditional connectivity approaches. Results According to all used validation methodologies, models with intermediate levels of randomness outperformed those with extreme randomness levels representing totally deterministic or random movements. We found differences in the optimal randomness level among validation methods but similar results in the delineation of corridors. Our results also revealed that models with extreme randomness levels (deterministic and random walk) of the randomized path approach provided equivalent corridor networks to those from traditional approaches. Moreover, these corridor networks calculated with traditional approaches showed notable differences in patterns from the corridor network calculated with an optimized randomness level. Conclusions Here we presented a connectivity model with a solid biological basis that calibrates the level of movement randomness and is supported by comprehensive validation methods. It is thus a step forward in the search and evaluation of connectivity approaches that lead to improved, efficient, and successful management actions.

Hydraulic shortcuts increase the connectivity of arable land areas to surface waters

Surface runoff represents a major pathway for pesticide transport from agricultural areas to surface waters. The influence of artificial structures (e.g. roads, hedges, and ditches) on surface runoff connectivity has been shown in various studies. In Switzerland, so-called hydraulic shortcuts (e.g. inlet and maintenance shafts of road or field storm drainage systems) have been shown to influence surface runoff connectivity and related pesticide transport. Their occurrence and their influence on surface runoff and pesticide connectivity have, however, not been studied systematically. To address that deficit, we randomly selected 20 study areas (average size of 3.5 km2) throughout the Swiss plateau, representing arable cropping systems. We assessed shortcut occurrence in these study areas using three mapping methods, namely field mapping, drainage plans, and high-resolution aerial images. Surface runoff connectivity in the study areas was analysed using a 2×2 m digital elevation model and a multiple-flow algorithm. Parameter uncertainty affecting this analysis was addressed by a Monte Carlo simulation. With our approach, agricultural areas were divided into areas that are either directly, indirectly (i.e. via hydraulic shortcuts), or not at all connected to surface waters. Finally, the results of this connectivity analysis were scaled up to the national level, using a regression model based on topographic descriptors, and were then compared to an existing national connectivity model. Inlet shafts of the road storm drainage system were identified as the main shortcuts. On average, we found 0.84 inlet shafts and a total of 2.0 shafts per hectare of agricultural land. In the study catchments, between 43 % and 74 % of the agricultural area is connected to surface waters via hydraulic shortcuts. On the national level, this fraction is similar and lies between 47 % and 60 %. Considering our empirical observations led to shifts in estimated fractions of connected areas compared to the previous connectivity model. The differences were most pronounced in flat areas of river valleys. These numbers suggest that transport through hydraulic shortcuts is an important pesticide flow path in a landscape where many engineered structures exist to drain excess water from fields and roads. However, this transport process is currently not considered in Swiss pesticide legislation and authorization. Therefore, current regulations may fall short in addressing the full extent of the pesticide problem. However, independent measurements of water flow and pesticide transport to quantify the contribution of shortcuts and validating the model results are lacking. Overall, the findings highlight the relevance of better understanding the connectivity between fields and receiving waters and the underlying factors and physical structures in the landscape.

A dynamic, network scale sediment (dis)connectivity model to reconstruct historical sediment transfers and river reach sediment budgets

<p>Sediment transport and connectivity are key factors for the functioning of fluvial eco-systems, and variations to these drivers deeply affect the geomorphology of the river system. Given that lags often occur in river systems, these changes may appear displaced in time and space from the disturbances that generated them. Modelling sediment (dis)connectivity and its reaction to anthropic pressures with a network-scale perspective is thus necessary to increase the understanding of river processes, to quantify real impacts and estimate future evolutionary trajectories. The CASCADE model (Schmitt et al., 2016) is a sediment connectivity model developed to address this type of research question: it combines concepts of network modelling with empirical sediment transport formulas to quantitatively describe sediment (dis)connectivity in river networks.</p><p>In this work, we present a new version of the CASCADE model which expands on the original model by featuring a dynamic simulation of sediment transport processes in the network (D-CASCADE). This new framework describes sediment connectivity in term of transfer rates through space and time. It takes into consideration multiple factors that can affect sediment transport, such as spatial and temporal variations in water discharge and river geomorphological features (i.e., river gradient and width), different sediment grainsizes, sediment entraining and deposition from and in the river bed and interactions between materials coming from different sources.</p><p>We apply the new D-CASCADE on the Bega River, New South Wales, Australia, which due to anthropic alterations post European colonization after 1850 including large-scale deforestation, removal of riparian vegetation and swamp drainage, has experienced significant alteration to the character and behaviour of streams, widespread channel erosion and massive sediment mobilization (Fryirs and Brierley, 2001). Our objective is to reproduce the historical sediment transfers that occurred across the network and associated river reach sediment budgets. First, we reconstructed the pre-settlement geomorphic features of the river network and the past hydrology from historical observations and expert-based reconstruction, and then modelled the sediment transport processes in the network in the last two centuries introducing the different drivers of change observed historically in the proper chronological sequence. Due to the uncertainty in the reconstruction of the historical conditions, multiple scenarios have been used.</p><p>The D-CASCADE model successfully reproduces the timing and magnitude of the major sediment transfers of the last two centuries in the Bega River network from headwaters swamps to lowland river reaches and associated channel geomorphic adjustments. Using the knowledge acquired by these historical simulations, the model was also applied to provide estimations on future trajectories of sediment transport and sediment budgets at the river reach scale.</p><p>With this research, we demonstrate the potential of the new D-CASCADE model to simulate and quantify at the network-scale sediment transport events generating information on sediment budget transfers from a single event to historical trajectories of the last centuries. Such knowledge paves the way to aid predictions of future impacts of basin-scale management measures and can support decision-making when designing sediment management strategies or river restoration initiatives.</p>