Modeling and Profiling of Aggregated Industrial Network Traffic

The industrial network infrastructures are transforming to a horizontal architecture to enable data availability for advanced applications and enhance flexibility for integrating new technologies. The uninterrupted operation of the legacy systems needs to be ensured by safeguarding their requirements in network configuration and resource management. Network traffic modeling is essential in understanding the ongoing communication for resource estimation and configuration management. The presented work proposes a two-step approach for modeling aggregated traffic classes of brownfield installation. It first detects the repeated work-cycles and then aims to identify the operational states to profile their characteristics. The performance and influence of the approach are evaluated and validated in two experimental setups with data collected from an industrial plant in operation. The comparative results show that the proposed method successfully captures the temporal and spatial dynamics of the network traffic for characterization of various communication states in the operational work-cycles.

Public Transit Development Predicts Spatial Distribution of Dengue Virus Incidence in Medellín, Colombia

Dengue is a growing global threat in some of the world’s most rapidly growing landscapes. Urbanization and human movement affect the spatial dynamics and magnitude of dengue outbreaks; however, precise effects of urban growth on dengue is not well understood because of a lack of sufficiently fine-scaled data. We analyzed nine years of address-level dengue case data in Medellin, Colombia during a period of public transit expansion. We correlate changes in the spread and magnitude of localized outbreaks to changes in accessibility and usage of public transit. Locations closer to and with a greater utilization of public transit had greater dengue incidence. This relationship was modulated by socioeconomic status; lower socioeconomic status locations experienced stronger effects of public transit accessibility and usage on dengue incidence. Public transit is a vital urban resource, particularly among low socioeconomic populations; these results highlight the importance of public health services concurrent with urban growth.

Bus ridership and its determinants in Beijing: A spatial econometric perspective

Understanding the temporal and spatial dynamics and determinants of public transport ridership play an important role in urban planning. Previous studies have focused on exploring the determinants at the station level using global models, or a local model, geographically weighted regression (GWR), which cannot reveal spatial autocorrelation at the global level. This study explores the factors affecting bus ridership considering spatial autocorrelation using the spatial Durbin model (SDM). Taking the community in Beijing as the basic study unit, this study aims to explore the temporal and spatial dynamics of bus ridership and identify its key determinants considering neighboring effects. The results show the following: (1) The temporal dynamics are quite distinct on weekdays and weekends as well as at different time slots of the day. (2) The spatial patterns of bus ridership varied across different time slots, and the hot areas are mainly located near the central business district (CBD), transport hubs, and residential areas. (3) Key determinants of bus ridership varied across weekends and weekdays and varied at different time slots per day. (4) The spatial neighboring effects had been verified. This study provides a common analytical framework for analyzing the spatiotemporal dynamics and determinants of bus ridership at the community level.

Race, Geography, and School Choice Policy: A Critical Analysis of Detroit Students’ Suburban School Choices

The purpose of this study is to advance our thinking about race and racism in geospatial analyses of school choice policy. To do so, we present a critical race spatial analysis of Detroit students’ suburban school choices. To frame our study, we describe the racial and spatial dynamics of school choice, drawing in particular on the concepts of opportunity hoarding and predatory landscapes. We find that Detroit students’ suburban school choices were circumscribed by racial geography and concentrated in just a handful of schools and districts. We also find notable differences between students in different racial groups. For all Detroit exiters, their schools were significantly more segregated and lower quality than those of their suburban peers. We propose future directions for research on families’ school choices as well as school and district behavior at the intersection of race, geography, and school choice policy.

Composed Cognitive Maps

Composed cognitive maps are a tool based on grounded theory and on Lynch's urban model of cognitive maps, which allow the transfer of information from ethnographic situations to general patterns, and to the so-called spatial dynamics. In criminological matters, they have been applied in the context of environmental and criminology of place to identify criminal situations, criminal patterns, and spatial dynamics of crime. The latter concept has allowed reliable diagnoses for the design of criminal policies. Their advantages are compared with traditional criminometric methods. It introduces a brief compilation of the existing literature on the subject. In a special way, this chapter shows how composed cognitive maps allowed the measurement of drug trafficking networks, police intelligence, and, above all, crime reduction.

Calibrating the temporal and spatial dynamics of the Ediacaran - Cambrian radiation of animals

The Ediacaran-Cambrian transition, which incorporates the radiation of animals, lacks a robust global temporal and spatial framework, resulting in major uncertainty in the evolutionary dynamics of this critical radiation and its relationship to changes in palaeoenvironmental geochemistry. We first present a new δ13Ccarb composite reference curve for the Ediacaran Nama Group of southern Namibia, and we then outline four new possible global age models (A to D) for the interval 551-517 million years ago (Ma). These models comprise composite carbonate-carbon isotope (δ13Ccarb) curves, which are anchored to radiometric ages and consistent with strontium isotope chemostratigraphy, and are used to calibrate metazoan distribution in space and time. These models differ most prominently in the temporal position of the basal Cambrian negative δ13Ccarb excursion (BACE). Regions that host the most complete records show that the BACE nadir always predates the Ediacaran-Cambrian boundary as defined by the first appearance datum (FAD) of the ichnospecies Treptichnus pedum. Whilst treptichnid traces are present in the late Ediacaran fossil record, the FAD of the ichnospecies T. pedum appears to post-date the LAD of in situ Cloudina and Namacalathus in all environments with high-resolution δ13Ccarb data. Two age models (A and B) place the BACE within the Ediacaran, and yield an age of ~538.8 Ma for the Ediacaran-Cambrian boundary; however models C and D appear to be the most parsimonious and may support a recalibration of the boundary age by up to 3 Myr younger. All age models reveal a previously underappreciated degree of variability in the terminal Ediacaran, incorporating notable positive and negative excursions that precede the BACE. Nothwithstanding remaining uncertainties in chemostratigraphic correlation, all models support a pre-BACE first appearance of Cambrian-type shelly fossils in Siberia and possibly South China, and show that the Ediacaran-Cambrian transition was a protracted interval represented by a series of successive radiations.

Higher-order effects, continuous species interactions, and trait evolution shape microbial spatial dynamics

The assembly and maintenance of microbial diversity in natural communities, despite the abundance of toxin-based antagonistic interactions, presents major challenges for biological understanding. A common framework for investigating such antagonistic interactions involves cyclic dominance games with pairwise interactions. The incorporation of higher-order interactions in such models permits increased levels of microbial diversity, especially in communities in which antibiotic-producing, sensitive, and resistant strains coexist. However, most such models involve a small number of discrete species, assume a notion of pure cyclic dominance, and focus on low mutation rate regimes, none of which well represent the highly interlinked, quickly evolving, and continuous nature of microbial phenotypic space. Here, we present an alternative vision of spatial dynamics for microbial communities based on antagonistic interactions—one in which a large number of species interact in continuous phenotypic space, are capable of rapid mutation, and engage in both direct and higher-order interactions mediated by production of and resistance to antibiotics. Focusing on toxin production, vulnerability, and inhibition among species, we observe highly divergent patterns of diversity and spatial community dynamics. We find that species interaction constraints (rather than mobility) best predict spatiotemporal disturbance regimes, whereas community formation time, mobility, and mutation size best explain patterns of diversity. We also report an intriguing relationship among community formation time, spatial disturbance regimes, and diversity dynamics. This relationship, which suggests that both higher-order interactions and rapid evolution are critical for the origin and maintenance of microbial diversity, has broad-ranging links to the maintenance of diversity in other systems.

Assessing the Wall-To-Wall Spatial and Qualitative Dynamics of the Brazilian Pasturelands, between 2010 and 2018, Based on the Analysis of the Landsat Data Archive

The Brazilian livestock is predominantly extensive, with approximately 90% of the production being sustained on pasture, which occupies around 20% of the territory. In the current climate change scenario and where cropland is becoming a limited resource, there is a growing need for a more efficient land use and occupation. It is estimated that more than half of the Brazilian pastures have some level of degradation; however there is still no mapping of the quality of pastures on a national scale. In this study, we mapped and evaluated the spatio-temporal dynamics of pasture quality in Brazil, between 2010 and 2018, considering three classes of degradation: Absent (D0), Intermediate (D1), and Severe (D2). There was no variation in the total area occupied by pastures in the evaluated period, in spite of the accentuated spatial dynamics, with a retraction in the center-south and expansion to the north, over areas of ​​native vegetation. The percentage of non-degraded pastures increased ~12%, due to the recovery of degraded areas and the emergence of new pasture areas as a result of the prevailing spatial dynamics. However, about 44 Mha of the pasture area is currently severely degraded. The dynamics in pasture quality were not homogeneous in property size classes. We observed that in the approximately 2.68 million properties with livestock activity, the proportion with quality gains was twice as low in small properties compared to large ones, and the proportion with losses was three times greater, showing an increase in inequality between properties with more and less resources (large and small, respectively). The areas occupied by pastures in Brazil present an unique opportunity to increase livestock production and make available areas for agriculture, without the need for new deforestation in the coming decades.