Scalable Mining of Common Routes in Mobile Communication Network Traffic Data

A probabilistic method for inferring common routes from mobile communication network traffic data is presented. Besides providing mobility information, valuable in a multitude of application areas, the method has the dual purpose of enabling efficient coarse-graining as well as anonymisation by mapping individual sequences onto common routes. The approach is to represent spatial trajectories by Cell ID sequences that are grouped into routes using locality-sensitive hashing and graph clustering. The method is demonstrated to be scalable, and to accurately group sequences using an evaluation set of GPS tagged data

Learning Latent Factor Models of Travel Data for Travel Prediction and Analysis

Abstract. We describe latent factor probability models of human travel, which we learn from data. The latent factors represent interpretable properties: travel distance cost, desirability of destinations, and affinity between locations. Individuals are clustered into distinct styles of travel. The latent factors combine in a multiplicative manner, and are learned using Maximum Likelihood. We show that our models explain the data significantly better than histogrambased methods. We also visualize the model parameters to show information about travelers and travel patterns. We show that different individuals exhibit different propensity to travel large distances. We extract the desirability of destinations on the map, which is distinct from their popularity. We show that pairs of locations have different affinities with each other, and that these affinities are partly explained by travelers ’ preference for staying within national borders and within the borders of linguistic areas. The method is demonstrated on two sources of travel data: geotags from Flickr images, and GPS tracks from Shanghai taxis.

Trial to encourage adoption and maintenance of a Mediterranean diet (TEAM-MED): Protocol for a randomised feasibility trial of a peer support intervention for dietary behaviour change in adults at high cardiovascular disease risk

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Adoption of a Mediterranean diet (MD) reduces cardiovascular disease (CVD) risk. However, interventions to achieve dietary behaviour change are typically resource intensive. Peer support offers a potentially low-cost approach to encourage dietary change. The primary objective of this randomised controlled trial is to explore the feasibility of peer support versus a previously tested dietetic-led intervention to encourageMDbehaviour change, and to test recruitment strategies, retention and attrition in order to inform the design of a definitive trial. A total of 75 overweight adults at high CVD risk who do not follow a MD (Mediterranean Diet Score (MDS ≤3)) will be randomly assigned to either: a minimal intervention (written materials), a proven intervention (dietetic support, written materials and key MD foods), or a peer support intervention (group-based community programme delivered by lay peers) for 12 months. The primary end-point is change in MDS from baseline to 6 months (adoption of MD). Secondary end-points include: change in MDS from 6 to 12 months (maintenance of MD), effects on nutritional biomarkers and CVD risk factors, fidelity of implementation, acceptability and feasibility of the peer support intervention. This study will generate important data regarding the feasibility of peer support for ease of adoption of MD in an ‘at risk’ Northern European population. Data will be used to direct a larger scale trial, where the clinical efficacy and cost-effectiveness of peer support will be tested

A concept for application of integrated digital technologies to enhance future smart agricultural systems

Future agricultural systems should increase productivity and sustainability of food production and supply. For this, integrated and efficient capture, management, sharing, and use of agricultural and environmental data from multiple sources is essential. However, there are challenges to understand and efficiently use different types of agricultural and environmental data from multiple sources, which differ in format and time interval. In this regard, the role of emerging technologies is considered to be significant for integrated data gathering, analyses and efficient use. In this study, a concept was developed to facilitate the full integration of digital technologies to enhance future smart and sustainable agricultural systems. The concept has been developed based on the results of a literature review and diverse experiences and expertise which enabled the identification of stat-of-the-art smart technologies, challenges and knowledge gaps. The features of the proposed solution include: data collection methodologies using smart digital tools; platforms for data handling and sharing; application of Artificial Intelligent for data integration and analysis; edge and cloud computing; application of Blockchain, decision support system; and a governance and data security system. The study identified the potential positive implications i.e. the implementation of the concept could increase data value, farm productivity, effectiveness in monitoring of farm operations and decision making, and provide innovative farm business models. The concept could contribute to an overall increase in the competitiveness, sustainability, and resilience of the agricultural sector as well as digital transformation in agriculture and rural areas. This study also provided future research direction in relation to the proposed concept. The results will benefit researchers, practitioners, developers of smart tools, and policy makers supporting the transition to smarter and more sustainable agriculture systems

Bias in beliefs about the self is associated with depressive but not anxious mood

Background: Biases in beliefs about the self are associated with psychopathology and depressive and anxious mood, but it is not clear if both negative and positive beliefs are associated with depression or anxiety. We examined these relationships in people who present with a wide range of depressive and anxious mood across diagnostic categories. Methods: We probed positive and negative beliefs about the self with a task in which 74 female participants with either Affective Disorder (depression and/or anxiety), Borderline Personality Disorder or no psychiatric history indicated the degree to which 60 self-related words was “like them” or “not like them”. Depressive and anxious mood were assessed with the Beck Depression Inventory–II and the Beck Anxiety Inventory. Results: The participants with no psychiatric history (n=25) reported a positive bias in their beliefs about the self, the participants with Affective Disorder (n=23) reported no bias, and the participants with BPD (n=26) reported a negative bias. Two hierarchical multiple regressions demonstrated that the positive and negative beliefs contributed additively to the ratings of depression (corrected for anxiety), but did not contribute to the ratings of anxiety (corrected for depression). Limitations: Despite the apparent small sample size, the regression analyses indicated adequate sampling. Anxiety is a much more heterogeneous condition than is depression, so it may be difficult to find relevant self-descriptors. Only measures of endorsement were used. Conclusions: Biases in beliefs about the self are associated with depressed, but not anxious mood, across diagnostic categorie

Antiferromagnetism in the Exact Ground State of the Half Filled Hubbard Model on the Complete-Bipartite Graph

As a prototype model of antiferromagnetism, we propose a repulsive Hubbard Hamiltonian defined on a graph \L={\cal A}\cup{\cal B} with ${\cal A}\cap {\cal B}=\emptyset$ and bonds connecting any element of ${\cal A}$ with all the elements of ${\cal B}$. Since all the hopping matrix elements associated with each bond are equal, the model is invariant under an arbitrary permutation of the ${\cal A}$-sites and/or of the ${\cal B}$-sites. This is the Hubbard model defined on the so called $(N_{A},N_{B})$-complete-bipartite graph, $N_{A}$ ($N_{B}$) being the number of elements in ${\cal A}$ (${\cal B}$). In this paper we analytically find the {\it exact} ground state for $N_{A}=N_{B}=N$ at half filling for any $N$; the repulsion has a maximum at a critical $N$-dependent value of the on-site Hubbard $U$. The wave function and the energy of the unique, singlet ground state assume a particularly elegant form for N \ra \inf. We also calculate the spin-spin correlation function and show that the ground state exhibits an antiferromagnetic order for any non-zero $U$ even in the thermodynamic limit. We are aware of no previous explicit analytic example of an antiferromagnetic ground state in a Hubbard-like model of itinerant electrons. The kinetic term induces non-trivial correlations among the particles and an antiparallel spin configuration in the two sublattices comes to be energetically favoured at zero Temperature. On the other hand, if the thermodynamic limit is taken and then zero Temperature is approached, a paramagnetic behavior results. The thermodynamic limit does not commute with the zero-Temperature limit, and this fact can be made explicit by the analytic solutions.Comment: 19 pages, 5 figures .ep

Africans Who Arrive in the United States before 20 Years of Age Maintain Both Cardiometabolic Health and Cultural Identity: Insight from the Africans in America Study

The overall consensus is that foreign-born adults who come to America age \u3c 20 y achieve economic success but develop adverse behaviors (smoking and drinking) that lead to worse cardiometabolic health than immigrants who arrive age ≥ 20 y. Whether age of immigration affects the health of African-born Blacks living in America is unknown. Our goals were to examine cultural identity, behavior, and socioeconomic factors and determine if differences exist in the cardiometabolic health of Africans who immigrated to America before and after age 20 y. Of the 482 enrollees (age: 38 ± 1 (mean ± SE), range: 20–65 y) in the Africans in America cohort, 23% (111/482) arrived age \u3c 20 y, and 77% (371/482) arrived age ≥ 20 y. Independent of francophone status or African region of origin, Africans who immigrated age \u3c 20 y had similar or better cardiometabolic health than Africans who immigrated age ≥ 20 y. The majority of Africans who immigrated age \u3c 20 y identified as African, had African-born spouses, exercised, did not adopt adverse health behaviors, and actualized early life migration advantages, such as an American university education. Due to maintenance of cultural identity and actualization of opportunities in America, cardiometabolic health may be protected in Africans who immigrate before age 20. In short, immigrant health research must be cognizant of the diversity within the foreign-born community and age of immigration

Trial to Encourage Adoption and Maintenance of a MEditerranean Diet (TEAM-MED): a randomised pilot trial of a peer support intervention for dietary behaviour change in adults from a Northern European population at high cardiovascular disease risk.

Adhering to a Mediterranean Diet (MD) is associated with reduced cardiovascular disease (CVD) risk. This study aimed to explore methods of increasing MD adoption in a non-Mediterranean population at high risk of CVD, including assessing the feasibility of a developed peer support intervention. The Trial to Encourage Adoption and Maintenance of a MEditerranean Diet (TEAM-MED) was a 12-month pilot parallel group RCT involving individuals aged ≥40 y, with low MD adherence, who were overweight, and had an estimated CVD risk ≥20% over ten years. It explored three interventions, a peer support group, a dietician-led support group and a minimal support group to encourage dietary behaviour change and monitored variability in Mediterranean Diet Score (MDS) over time and between the intervention groups, alongside measurement of markers of nutritional status and cardiovascular risk. 118 individuals were assessed for eligibility, and 75 (64%) were eligible. After 12 months there was a retention rate of 69% (PSG 59%; DSG 88%; MSG 63%). For all participants, increases in MDS were observed over 12 months (p<0.001), both in original MDS data and when imputed data were used. Improvements in BMI, HbA1c levels, systolic and diastolic blood pressure in the population as a whole. This pilot study has demonstrated that a non-Mediterranean adult population at high CVD risk can make dietary behaviour change over a 12-month period towards a MD. The study also highlights the feasibility of a peer support intervention to encourage MD behaviour change amongst this population group and will inform a definitive trial