Temporal Aggregation Effects in Spatiotemporal Traffic Modelling

Spatiotemporal models are a popular tool for urban traffic forecasting, and their correct specification is a challenging task. Temporal aggregation of traffic sensor data series is a critical component of model specification, which determines the spatial structure and affects models’ forecasting accuracy. Through extensive experiments with real-world data, we investigated the effects of the selected temporal aggregation level for forecasting performance of different spatiotemporal model specifications. A set of analysed models include travel-time-based and correlation-based spatially restricted vector autoregressive models, compared to classical univariate and multivariate time series models. Research experiments are executed in several dimensions: temporal aggregation levels, forecasting horizons (one-step and multi-step forecasts), spatial complexity (sequential and complex spatial structures), the spatial restriction approach (unrestricted, travel-time-based and correlation-based), and series transformation (original and detrended traffic volumes). The obtained results demonstrate the crucial role of the temporal aggregation level for identification of the spatiotemporal traffic flow structure and selection of the best model specification. We conclude that the common research practice of an arbitrary selection of the temporal aggregation level could lead to incorrect conclusions on optimal model specification. Thus, we recommend extending the traffic forecasting methodology by validation of existing and newly developed model specifications for different temporal aggregation levels. Additionally, we provide empirical results on the selection of the optimal temporal aggregation level for the discussed spatiotemporal models for different forecasting horizons.

Approach to management of heterogeneous swarms of devices

The paper describes an approach to management of heterogeneous swarm of cyber-physical devices. This approach includes 3 functional levels: the aggregation level, the peripheral level and the data collection level. Variants of using this approach are considered: a crisis management network, a robotic complex for monitoring premises and a system for detecting security incidents in premises.

Effect of a-tocopherol on the development of diabetic angiopathy, platelet aggregation, and prostacyclin-thromboxan system of rats with streptozotocin-induced diabetes

Under study were effects of intravenous infusions of a new emulsion, -tocopherol, on the development of diabetic microangiopathy, platelet -tocopherol level, ADP-induced platelet aggregation level, exogenic (from 14C-arachidonic acid) thromboxan (TxA2) biosynthesis in suspension of washed platelets and of prostacyclin (Pgb) one in isolated aortic rings of rats with streptozotocin-induced diabetes. Six-week injections of -tocopherol in a dose 100 mg/100 g b. w. with 48 h intervals immediately after development of streptozotocin-induced diabetes prevented the development of diabetic angiopathy but did not normalize platelet functional activity and Pgl2/TxA2 balance in vessels and platelets. Similar injections of -tocopherol in the presence of developed angiopathy resulted in its regressive development and normalization of the before-said prostanoid balance and platelet characteristics.

The Influence of Phases Division Surface in Nanocomposites Polymer/2D-Nanofiller on their Reinforcement Degree - The Percolation Model

The simple percolation model, in which critical indices are defined by the form of a reinforcing component of nanostructured composite structure, was proposed for the description of reinforcement degree for nanostructured composites polymer/2D-nanofiller. The indicated critical indices are close by absolute values to standard percolation indices. The form of reinforcing component controls the type of nanostructured composite. It has been shown that reinforcement degree of these nanomaterials is independent on modulus of elasticity of nanofiller, but is defined by its structure (aggregation level), created in polymer matrix. The percolation indices of a percolation model, which are due to the form of reinforcing component and nanocomposite type, are defined by its main characteristic – the fraction of phases division surface in overall sample volume and are the basic factor, controlling reinforcement degree of nanostructured composites.

SAT0051 REMISSION IN RHEUMATOID ARTHRITIS PATIENTS: A CLUSTER ANALYSIS TO IDENTIFY AND CHARACTERIZE SUBPOPULATIONS OF PATIENTS

Background:Disease Activity Score (DAS) is a continuous measure of Rheumatoid Arthritis (RA) activity, used in clinical practice for monitoring disease progression and for documenting treatment response. According to EULAR, the clinical desired target is to achieve a remission state (or failing that, low disease activity). However, the population of RA patients in this state could be heterogenous.Objectives:To characterize the level of heterogeneity of RA patients in remission by identifying clusters based on the DAS28 components; and to describe inter and intra-class cluster demographic and clinical characteristicsMethods:Patients from Hospital Clínico San Carlos cohort, stored in a departmental electronic health record from January 1st, 2000 to December 30th, 2018, diagnose with RA according ACR 1986/ 2010 criteria were eligible for this study. Only observations with a DAS28 Erythrocyte Sedimentation Rate (ESR) value < 2.6 value were considered. ESR, patient’s Global Health (GH), and tender and swollen joints were used for calculating the clusters. Different aggregation levels for joints were studied as well as the input variable types. Isolated joints, joints grouped by the type of affectation (swollen or tender) or anatomic location or laterality aggregation levels were considered. Variables expressed as present or absent (i.e. dichotomous), continuous (count of joins) and categorical (type of joints) were also studied. Gower’s distance, used for dealing with variables of different type, was employed to calculate the distance matrix. The number of suitable clusters was chosen from two to seven clusters based on the width value of a Silhouette analyses. Finally, Partitioning Around Medoids (PAM) was used as the clustering algorithm. Differences among clusters regarding demographic and clinical characteristics were analyzed using t-student chi2 test.Results:812 patients with 1,431 observations were analyzed in this study. The joint aggregation level which showed a highest Silhouette width value (0.708) was the anatomic one. In this aggregation level, five dichotomous variables (presence of tenderness and/or swelling in right and/or left shoulder, elbow, wrist, knee and hand (including both metacarpophalangeal and proximal interphalangeal joints) and two continuous variables (ESR and GH) were used. Two clusters were found: the cluster A) with 1,305 observations and 742 patients and the B) with 126 observations and 115 patients. Cluster b) had a statistically significant higher DAS28-ESR value (higher number of tender and swollen joints, and higher GH, but lower ESR), longer follow-up time (6.5 vs. 4.7 years), higher VAS-pain score (10 vs. 2), and higher HAQ score (0.25 vs. 0.12). In addition, the proportion of patients treated with oral corticosteroids (63% s. 50%) and biological therapy (29% vs. 12%) was higher.Conclusion:We have identified two clinically distinct populations of RA patients in remission according to DAS28-ESR <2.6. Each subgroup could be associated with different outcomes during follow-up, such as radiographic progression or risk of relapse.Disclosure of Interests:Alfredo Madrid García: None declared, Dalifer Freites Nuñez: None declared, Judit Font: None declared, Isabel Hernandez: None declared, Leticia León: None declared, Jose Ignacio Colomer: None declared, Isidoro González-Álvaro Grant/research support from: Roche Laboratories, Consultant of: Lilly, Sanofi, Paid instructor for: Lilly, Speakers bureau: Abbvie, MSD, Roche, Lilly, Benjamin Fernandez: None declared, J Angel Jover: None declared, Lydia Abasolo: None declared, Luis Rodriguez Rodriguez: None declared

A “Swiss paradox” in the United States? Level of spatial aggregation changes the association between income inequality and morbidity for older Americans

Although a preponderance of research indicates that increased income inequality negatively impacts population health, several international studies found that a greater income inequality was associated with better population health when measured on a fine geographic level of aggregation. This finding is known as a “Swiss paradox”. To date, no studies have examined variability in the associations between income inequality and health outcomes by spatial aggregation level in the US. Therefore, this study examined associations between income inequality (Gini index, GI) and population health by geographic level using a large, nationally representative dataset of older adults. We geographically linked respondents’ county data from the 2012 Behavioral Risk Factor Surveillance System to 2012 American Community Survey data. Using generalized linear models, we estimated the association between GI decile on the state and county levels and five population health outcomes (diabetes, obesity, smoking, sedentary lifestyle and self-rated health), accounting for confounders and complex sampling. Although state-level GI was not significantly associated with obesity rates (b = − 0.245, 95% CI − 0.497, 0.008), there was a significant, negative association between county-level GI and obesity rates (b = − 0.416, 95% CI − 0.629, − 0.202). State-level GI also associated with an increased diabetes rate (b = 0.304, 95% CI 0.063, 0.546), but the association was not significant for county-level GI and diabetes rate (b = − 0.101, 95% CI − 0.305, 0.104). Associations between both county-level GI and state-level GI and current smoking status were also not significant. These findings show the associations between income inequality and health vary by spatial aggregation level and challenge the preponderance of evidence suggesting that income inequality is consistently associated with worse health. Further research is needed to understand the nuances behind these observed associations to design informed policies and programs designed to reduce socioeconomic health inequities among older adults.

Alteration of the aggregation and spatial organization of the vector of Chagas disease, Triatoma infestans, by the parasite Trypanosoma cruzi

Triatominae insects are vectors of the parasite Trypanosoma cruzi, the etiological agent of Chagas disease affecting millions of people in Latin America. Some species, such as Triatoma infestans, live in the human neighborhood, aggregating in walls or roof cracks during the day and going out to feed blood at night. The comprehension of how sex and T. cruzi infection affect their aggregation and geotaxis is essential for understanding their spatial organization and the parasite dispersion. Experiments in laboratory-controlled conditions were carried out with groups of ten adults of T. infestans able to explore and aggregate on a vertical surface. The influence of the sex (male vs. female) and the proportion of infected insects in the group were tested (100% of infected insects vs. a small proportion of infected insects, named infected and potentially weakly infected groups, respectively). Therefore, four distinct groups of insects were tested: infected males, infected females, potentially weakly infected males, and potentially weakly infected females, with 12, 9, 15, and 16 replicates, respectively. The insects presented a high negative geotaxis and a strong aggregation behavior whatever the sex or their infection. After an exploration phase, these behaviors were stable in time. The insects exhibited a preferential vertical position, head toward the top of the setup. Males had a higher negative geotaxis and a higher aggregation level than females. Both behaviors were enhanced in groups of 100% infected insects, the difference between sexes being maintained. According to a comparison between experimental and theoretical results, geotaxis favors the aggregation that mainly results from the inter-attraction between individuals.