A Constraint Programming Approach to Automatic Layout Definition for Search Results

In this paper we describe a general framework based on constraint programming techniques to address the automatic layout definition problem for Web search result pages, considering heterogeneous result items types (e.g., web links, images, videos, maps, etc.). Starting from the entity type(s) specified in the search query and the result types deemed more relevant for the given entity type, we define an optimization problem and a set of constraints that grant the optimal positioning of results in the page, modeled as a grid with assigned weights depending on the visibility

A Multi-Resident Number Estimation Method for Smart Homes

Population aging requires innovative solutions to increase the quality of life and preserve autonomous and independent living at home. A need of particular significance is the identification of behavioral drifts. A relevant behavioral drift concerns sociality: older people tend to isolate themselves. There is therefore the need to find methodologies to identify if, when, and how long the person is in the company of other people (possibly, also considering the number). The challenge is to address this task in poorly sensorized apartments, with non-intrusive sensors that are typically wireless and can only provide local and simple information. The proposed method addresses technological issues, such as PIR (Passive InfraRed) blind times, topological issues, such as sensor interference due to the inability to separate detection areas, and algorithmic issues. The house is modeled as a graph to constrain transitions between adjacent rooms. Each room is associated with a set of values, for each identified person. These values decay over time and represent the probability that each person is still in the room. Because the used sensors cannot determine the number of people, the approach is based on a multi-branch inference that, over time, differentiates the movements in the apartment and estimates the number of people. The proposed algorithm has been validated with real data obtaining an accuracy of 86.8%

haptic and visual rendering for multi modal exploration of molecular information

The paper presents a system for the multi-modal rendering of molecules. Chemists typically deal with phenomena that are not directly experienceable and usually described by huge amount of data awkward to understand directly. Software tools have been introduced to support data interpretation, without a high degree of interactivity and explorability of the data. This work goes beyond the classical visual representations of molecules and introduces some new ways of exploration and navigation of information on which inter-molecular interactions are based. Target users are researchers and teachers, as integration to their activities. Two different modalities are used: haptical and visual. The former modality consists in the addition of a haptic interface that enables users to feel the interaction forces exerted by the electric field around a molecule. The latter modality shows the features of the same electric field by allowing the user to navigate the information about the values of the field using a visual color-based rendering and adding other visual cues. Implementation details, case studies, and results on the two modalities are described. Eye-tracking, awareness tools, machine learning, coordination, expertis

Age-related effects of exogenous melatonin on anxiety-like behavior in C57/B6J mice

The synthesis of melatonin (MLT) physiologically decreases during aging. Treatment with MLT has shown anxiolytic, hypnotic, and analgesic effects, but little is known about possible age-dependent differences in its efficacy. Therefore, we studied the effects of MLT (20 mg/kg, intraperitoneal) on anxiety-like behavior (open field (OFT), elevated plus maze (EPMT), three-chamber sociability, and marble-burying (MBT) tests), and the medial prefrontal cortex (mPFC)-dorsal hippocampus (dHippo) circuit in adolescent (35-40 days old) and adult (three-five months old) C57BL/6 male mice. MLT did not show any effect in adolescents in the OFT and EPMT. In adults, compared to vehicles, it decreased locomotor activity and time spent in the center of the arena in the OFT and time spent in the open arms in the EPMT. In the MBT, no MLT effects were observed in both age groups. In the three-chamber sociability test, MLT decreased sociability and social novelty in adults, while it increased sociability in adolescents. Using local field potential recordings, we found higher mPFC-dHippo synchronization in the delta and low-theta frequency ranges in adults but not in adolescents after MLT treatment. Here, we show age-dependent differences in the effects of MLT in anxiety paradigms and in the modulation of the mPFC-dHippo circuit, indicating that when investigating the pharmacology of the MLT system, age can significantly impact the study outcomes

A Constraint Programming Approach to Automatic Layout Definition for Search Results

In this paper we describe a general framework based on constraint programming techniques to address the automatic layout definition problem for Web search result pages, considering heterogeneous result items types (e.g., web links, images, videos, maps, etc.). Starting from the entity type(s) specified in the search query and the result types deemed more relevant for the given entity type, we define an optimization problem and a set of constraints that grant the optimal positioning of results in the page, modeled as a grid with assigned weights depending on the visibility

Supporting Alzheimer’s Residential Care - A Novel Indoor Localization System

This work illustrates a localization system specifically designed to be applied in “Il Paese Ritrovato”, a highly innovative health-care facility for people affected by Alzheimer’s disease in Monza, Italy. Patients are provided with an iBeacon bracelet broadcasting data packets that are collected through the use of a dense network of devices acting as receiving antennas. The system evaluates the path-loss of the received signal and corrects the computed position with a probabilistic approach to avoid wall-crossing. Localization data are merged with information from other IoT devices such as smart sensors, appliances and expert annotations; the resulting dataset will be extremely important to analyze behaviors, habits and social interactions among patients

Behavior Drift Detection Based on Anomalies Identification in Home Living Quantitative Indicators

Home Automation and Smart Homes diffusion are providing an interesting opportunity to implement elderly monitoring. This is a new valid technological support to allow in-place aging of seniors by means of a detection system to notify potential anomalies. Monitoring has been implemented by means of Complex Event Processing on live streams of home automation data: this allows the analysis of the behavior of the house inhabitant through quantitative indicators. Different kinds of quantitative indicators for monitoring and behavior drift detection have been identified and implemented using the Esper complex event processing engine. The chosen solution permits us not only to exploit the queries when run “online”, but enables also “offline” (re-)execution for testing and a posteriori analysis. Indicators were developed on both real world data and on realistic simulations. Tests were made on a dataset of 180 days: the obtained results prove that it is possible to evidence behavior changes for an evaluation of a person’s condition

Identification of a serum and urine extracellular vesicle signature predicting renal outcome after kidney transplant

Background A long-standing effort is dedicated towards the identification of biomarkers allowing the prediction of graft outcome after kidney transplant. Extracellular vesicles (EVs) circulating in body fluids represent an attractive candidate, as their cargo mirrors the originating cell and its pathophysiological status. The aim of the study was to investigate EV surface antigens as potential predictors of renal outcome after kidney transplant. Methods We characterized 37 surface antigens by flow cytometry, in serum and urine EVs from 58 patients who were evaluated before, and at 10-14 days, 3 months and 1 year after transplant, for a total of 426 analyzed samples. The outcome was defined according to estimated glomerular filtration rate (eGFR) at 1 year. Results Endothelial cells and platelets markers (CD31, CD41b, CD42a and CD62P) in serum EVs were higher at baseline in patients with persistent kidney dysfunction at 1 year, and progressively decreased after kidney transplant. Conversely, mesenchymal progenitor cell marker (CD1c, CD105, CD133, SSEEA-4) in urine EVs progressively increased after transplant in patients displaying renal recovery at follow-up. These markers correlated with eGFR, creatinine and proteinuria, associated with patient outcome at univariate analysis and were able to predict patient outcome at receiver operating characteristics curves analysis. A specific EV molecular signature obtained by supervised learning correctly classified patients according to 1-year renal outcome. Conclusions An EV-based signature, reflecting the cardiovascular profile of the recipient, and the repairing/regenerative features of the graft, could be introduced as a non-invasive tool for a tailored management of follow-up of patients undergoing kidney transplant