Understanding mass transfer directions via data-driven models with application to mobile phone data

The aim of this paper is to solve an inverse problem which regards a mass moving in a bounded domain. We assume that the mass moves following an unknown velocity field and that the evolution of the mass density can be described by a partial differential equation, which is also unknown. The input data of the problems are given by some snapshots of the mass distribution at certain times, while the sought output is the velocity field that drives the mass along its displacement. To this aim, we put in place an algorithm based on the combination of two methods: first, we use the dynamic mode decomposition to create a mathematical model describing the mass transfer; second, we use the notion of Wasserstein distance (also known as earth mover's distance) to reconstruct the underlying velocity field that is responsible for the displacement. Finally, we consider a real-life application: the algorithm is employed to study the travel flows of people in large populated areas using, as input data, density profiles (i.e., the spatial distribution) of people in given areas at different time instants. These kinds of data are provided by the Italian telecommunication company TIM and are derived by mobile phone usage

Using WebGIS to Develop a Spatial Bibliography for Organizing, Mapping, and Disseminating Research Information: A Case Study of Quaking Aspen

On the Ground • Spatial data is valuable to researchers for locating studies that occur in a particular area of interest, or one with similar attributes. • Without a standard in publishing protocol, spatial data largely goes unreported, or is difficult to find without searching the publication. • Assigning location data and displaying points on a public web map makes locating publications based on spatial location possible

Remotely Sensed Canopy Nitrogen Correlates With Nitrous Oxide Emissions in a Lowland Tropical Rainforest

Tropical forests exhibit significant heterogeneity in plant functional and chemical traits that may contribute to spatial patterns of key soil biogeochemical processes, such as carbon storage and greenhouse gas emissions. Although tropical forests are the largest ecosystem source of nitrous oxide (N2O), drivers of spatial patterns within forests are poorly resolved. Here, we show that local variation in canopy foliar N, mapped by remote‐sensing image spectroscopy, correlates with patterns of soil N2O emission from a lowland tropical rainforest. We identified ten 0.25 ha plots (assemblages of 40–70 individual trees) in which average remotely‐sensed canopy N fell above or below the regional mean. The plots were located on a single minimally‐dissected terrace (km2) where soil type, vegetation structure and climatic conditions were relatively constant. We measured N2O fluxes monthly for 1 yr and found that high canopy N species assemblages had on average three‐fold higher total mean N2O fluxes than nearby lower canopy N areas. These differences are consistent with strong differences in litter stoichiometry, nitrification rates and soil nitrate concentrations. Canopy N status was also associated with microbial community characteristics: lower canopy N plots had two‐fold greater soil fungal to bacterial ratios and a significantly lower abundance of ammonia‐oxidizing archaea, although genes associated with denitrification (nirS, nirK, nosZ) showed no relationship with N2O flux. Overall, landscape emissions from this ecosystem are at the lowest end of the spectrum reported for tropical forests, consist with multiple metrics indicating that these highly productive forests retain N tightly and have low plant‐available losses. These data point to connections between canopy and soil processes that have largely been overlooked as a driver of denitrification. Defining relationships between remotely‐sensed plant traits and soil processes offers the chance to map these processes at large scales, potentially increasing our ability to predict N2O emissions in heterogeneous landscapes

Stop & Go waves: a microscopic and a macroscopic description

In this paper we investigate a typical phenomenon of congested traffic: the stop-and-go waves. Since modelling properly this phenomenon is crucial for developing techniques aimed at reducing it, we present two different models: a microscopic and a macroscopic one, both of them able to reproduce stop-and-go waves. In the former, vehicles’ dynamics are described by a second-order microscopic Follow-the-Leader model, which is calibrated and validated by real measurements. Data are analysed and compared with the numerical solutions computed by the microscopic model. The latter provides a description of traffic dynamic via the macroscopic second-order CGARZ model. With the numerical implementation, by means of the 2CTM scheme, we test the ability of the model of capturing stop-and-go waves. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG

Fractional SIS epidemic models

In this paper, we consider the fractional SIS (susceptible-infectious-susceptible) epidemic model (α-SIS model) in the case of constant population size. We provide a representation of the explicit solution to the fractional model and we illustrate the results by numerical schemes. A comparison with the limit case when the fractional order α converges to 1 (the SIS model) is also given. We analyze the effects of the fractional derivatives by comparing the SIS and the α-SIS models

Effects of fractional derivatives with different orders in SIS epidemic models

We study epidemic Susceptible–Infected–Susceptible (SIS) models in the fractional setting. The novelty is to consider models in which the susceptible and infected populations evolve according to different fractional orders. We study a model based on the Caputo derivative, for which we establish existence results of the solutions. Furthermore, we investigate a model based on the Caputo–Fabrizio operator, for which we provide existence of solutions and a study of the equilibria. Both models can be framed in the context of SIS models with time-varying total population, in which the competition between birth and death rates is macroscopically described by the fractional orders of the derivatives. Numerical simulations for both models and a direct numerical comparison are also provided

Comparison of the efficacy of gesture-verbal treatment and doll therapy for managing neuropsychiatric symptoms in older patients with dementia

Background: The prevalence of neuropsychiatric symptoms (NPS) diminishes the quality of life and increases the care burden in patients with dementia. Despite the clinical importance of dementia-associated NPS, no protocols for treating NPS are already well established. Attention has turned to the effectiveness of nonpharmacological treatments for NPS since their potential safe alternative to pharmacotherapy. Objective: This study is aimed to compare the effects in older individuals with dementia living in a residential care, of two intervention programs, the gesture-verbal treatment (GVT), a treatment implemented by us on a previous method for word retrieval in individuals with aphasia, and the better-known doll therapy (DT). The GVT would act on both receptive and expressive language skills, the DT on attachment and emotional connections. Methods: We evaluated NPS by the neuropsychiatric inventory in a total of 30 patients divided into 3 groups, the GVT, the DT, and control groups, using a pre-post design. The treatment groups completed 12-week nonpharmacological interventions in addition to standard rehabilitative therapies, while the control group participated only in standard rehabilitative therapies. Results: The DT group showed significant improvements in agitation, irritability, apathy, depression, and delusions relative to controls. The GVT group showed significant improvements in apathy and depression with respect to controls. The DT intervention ameliorated symptoms of agitation compared to the GVT intervention whereas the GVT intervention improved apathy compared to the DT intervention. Conclusion: Improved understanding of the potential therapeutic benefits of different treatments for neuropsychiatric symptoms is crucial for establishing nonpharmacological interventions in dementia

Data from: Environmental controls on canopy foliar N distributions in a neotropical lowland forest

Distributions of foliar nutrients across forest canopies can give insight into their plant functional diversity and improve our understanding of biogeochemical cycling. We used airborne remote sensing and Partial Least Squares Regression (PLSR) to quantify canopy foliar nitrogen (N) across ~164 km2 of wet lowland tropical forest in the Osa Peninsula, Costa Rica. We determined the relative influence of climate and topography on the observed patterns of canopy foliar N using a gradient boosting model (GBM) technique. At a local scale, where climate and substrate where constant, we explored the influence of slope position on canopy N by quantifying canopy N on remnant terraces, their adjacent slopes and knife edged ridges. In addition, we climbed and sampled 540 trees and analyzed foliar N in order to quantify the role of species identity (phylogeny) and environmental factors in predicting canopy N. Observed canopy N heterogeneity reflected environmental factors working at multiple spatial scales. Across the larger landscape, elevation and precipitation had the highest relative influence on predicting canopy foliar N (30 and 24%), followed by soils (15%), site exposure (9%), compound topographic index (8%), substrate (6%), and landscape dissection (6%). Phylogeny explained ~75% of the variation in the filed collected foliar N data, suggesting that phylogeny largely underpins the response to the environmental factors. Taken together, these data suggest that a large fraction of the variance in canopy N across the landscape is proximately driven by species composition, though ultimately this is likely a response to abiotic factors such as climate and topography. Future work should focus on the mechanisms and feedbacks involved, and how shifts in climate may translate to changes in forest function