4,330 research outputs found
Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks
Evaluating similarity between graphs is of major importance in several
computer vision and pattern recognition problems, where graph representations
are often used to model objects or interactions between elements. The choice of
a distance or similarity metric is, however, not trivial and can be highly
dependent on the application at hand. In this work, we propose a novel metric
learning method to evaluate distance between graphs that leverages the power of
convolutional neural networks, while exploiting concepts from spectral graph
theory to allow these operations on irregular graphs. We demonstrate the
potential of our method in the field of connectomics, where neuronal pathways
or functional connections between brain regions are commonly modelled as
graphs. In this problem, the definition of an appropriate graph similarity
function is critical to unveil patterns of disruptions associated with certain
brain disorders. Experimental results on the ABIDE dataset show that our method
can learn a graph similarity metric tailored for a clinical application,
improving the performance of a simple k-nn classifier by 11.9% compared to a
traditional distance metric.Comment: International Conference on Medical Image Computing and
Computer-Assisted Interventions (MICCAI) 201
Towards Optimal Energy-Water Supply System Operation for Agricultural and Metropolitan Ecosystems
The energy-water demands of metropolitan regions and agricultural ecosystems
are ever-increasing. To tackle this challenge efficiently and sustainably, the
interdependence of these interconnected resources has to be considered. In this
work, we present a holistic decision-making framework which takes into account
simultaneously a water and energy supply system with the capability of
satisfying metropolitan and agricultural resource demands. The framework
features: (i) a generic large-scale planning and scheduling optimization model
to minimize the annualized cost of the design and operation of the energy-water
supply system, (ii) a mixed-integer linear optimization formulation, which
relies on the development of surrogate models based on feedforward artificial
neural networks and first-order Taylor expansions, and (iii) constraints for
land and water utilization enabling multi-objective optimization. The framework
provides the operational profiles of all energy-water system elements over a
given time horizon, which uncover potential synergies between the essential
food, energy, and water resource supply systems.Comment: Part of the Foundations of Computer-Aided Process Operations and
Chemical Process Control (FOCAPO/CPC) 2023 Proceeding
Proving Fixed-Point Theorems Employing Fuzzy (σ, Z)-Contractive-Type Mappings
In this article, the concept of fuzzy (σ, Z)-contractive mappings is introduced in the setting of fuzzy metric spaces. Thereafter, we utilize our newly introduced concept to prove some existence and uniqueness theorems in M-complete fuzzy metric spaces.
Our obtained theorems extend and generalize the corresponding results in the existing literature.
Moreover, some examples are adopted to exhibit the utility of the newly obtained result
Balance and proprioception impairment, assessment tools, and rehabilitation training in patients with total hip arthroplasty: a systematic review
Background: Osteoarthritis and subsequent total hip arthroplasty (THA) lead to damages to hip joint mechanoceptors, which in turns lead to impairments in proprioception. One of the abilities mainly affected by an altered joint proprioception is balance. The aim of this work was to investigate the balance and proprioception impairments, current assessment tools, and rehabilitation training after THA. Methods: A systematic literature revision was conducted on PubMed, Web of Science and Cochrane databases. Articles reporting balance and proprioception impairments, current assessment tools, or rehabilitation interventions were included. Methodological quality was assessed using the Downs and Black checklist. A total of 41 articles were included, 33 discussing balance and proprioception assessment, and 8 dealing with training. Data related to type of surgical approach, type and timing of assessment protocols, assessment instrumentation, and type, volume and duration of the rehabilitation training were extracted from each study. Results: Thirty-one studies were of high quality, 2 of moderate quality and 8 of low-quality. Literature review showed an improvement in balance following THA in comparison with the pre-operative performance, although balance abnormalities persist up to 5 years after surgery, with THA patients showing an increased risk for falls. Balance training is effective in all the rehabilitation phases if specifically structured for balance enhancement and consistent in training volume. It remains unclear which assessments are more appropriate for the different rehabilitation phases, and if differences exist between the different surgical procedures used for THA. Only two studies assessed proprioception. Conclusion: Balance and proprioception show impairments up to 5 years after THA, increasing the risk of falls. However, patients with THA may benefit of an adequate balance training. Further research is needed to investigate the gaps in balance and proprioception assessment and training following THA surgery
Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases
International audienceSoil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltration-runoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weather-related satellite products (i.e. rain rate estimation) might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent) hydro-geological hazards. Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV). Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques. Recently, using data coming from AMSU (Advanced Microwave Sounding Unit), flying aboard NOAA (National Oceanic and Atmospheric Administration) satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (SWVI), developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past. In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail. This analysis allows us to evaluate the reliability and the efficiency of the proposed technique in identifying different amounts of soil wetness variations in different observational conditions. In particular, the proposed indicator was able to document the actual effects of meteorological events, in terms of space-time evolution of soil wetness changes, for all the analysed HYDROPTIMET test cases. Moreover, in some circumstances, the SWVI was able to identify the presence of a sort of "early" signal in terms of soil wetness variations, which may be regarded as a timely indication of an anomalous value of soil water content. This evidence suggests the opportunity to use such an index in the pre-operational phases of the modern flood warning systems, in order to improve their forecast capabilities and their reliability
An XMM-Newton and INTEGRAL view on the hard state of EXO 1745-248 during its 2015 outburst
CONTEXT - Transient low-mass X-ray binaries (LMXBs) often show outbursts
lasting typically a few-weeks and characterized by a high X-ray luminosity
( erg/sec), while for most of the time they are
found in X-ray quiescence ( erg/sec). EXO 1745-248
is one of them. AIMS - The broad-band coverage, and the sensitivity of
instrument on board of {\xmm} and {\igr}, offers the opportunity to
characterize the hard X-ray spectrum during {\exo} outburst. METHODS - In this
paper we report on quasi-simultaneous {\xmm} and {\igr} observations of the
X-ray transient {\exo} located in the globular cluster Terzan 5, performed ten
days after the beginning of the outburst (on 2015 March 16th) shown by the
source between March and June 2015. The source was caught in a hard state,
emitting a 0.8-100 keV luminosity of ~{\lumcgs}. RESULTS - The
spectral continuum was dominated by thermal Comptonization of seed photons with
temperature keV, by a cloud with moderate optical depth
and electron temperature keV. A weaker soft
thermal component at temperature --0.7 keV and compatible
with a fraction of the neutron star radius was also detected. A rich emission
line spectrum was observed by the EPIC-pn on-board {\xmm}; features at energies
compatible with K- transitions of ionized sulfur, argon, calcium and
iron were detected, with a broadness compatible with either thermal Compton
broadening or Doppler broadening in the inner parts of an accretion disk
truncated at gravitational radii from the neutron star. Strikingly, at
least one narrow emission line ascribed to neutral or mildly ionized iron is
needed to model the prominent emission complex detected between 5.5 and 7.5
keV. (Abridged)Comment: 14 pages, 6 figure, 2 tables. Accepted for publication on A&A
(21/03/2017
Motivating Cord Blood Donation with Information and Behavioral Nudges
Umbilical cord blood is a source of hematopoietic stem cells essential to treat life-threatening diseases, such as leukemia and lymphoma. However, only a very small percentage of parents donate upon delivery. The decision to donate the cord blood occurs at a very specific time and when parents likely experience emotional, informational, and decisional overloads; these features of cord blood donation make it different from other pro-social activities. In collaboration with an OB-GYN clinic in Milan, Italy, we conducted the first randomized controlled trial that applies tools from behavioral science to foster cord blood donation, and quantified the gains that informational and behavioral "nudges" can achieve. We found that information and "soft" commitments increased donations; approaching expecting parents closer to the delivery date and providing them with multiple reminders, moreover, had the strongest impact. However, a significant portion of women who expressed consent to donate could not do so because of organizational constraints. We conclude that simple, non-invasive behavioral interventions that address information gaps and procrastination, and that increase the salience of the activity can substantially enhance altruistic donations of cord blood, especially when coupled with organizational support
Assessing the potential of <i>SWVI</i> (Soil Wetness Variation Index) for hydrological risk monitoring by means of satellite microwave observations
International audienceIn the last years satellite remote sensing applications in hydrology have considerably progressed. A new multi-temporal satellite data-analysis approach has been recently suggested in order to estimate space-time changes of geophysical parameters possibly related to the increase of environmental and hydro-geological hazards. Such an approach has been already used both for flooded area mapping (using AVHRR data) and for soil wetness index estimation (using AMSU data). In this work, a preliminary sensitivity analysis of the proposed Soil Wetness Variation Index (SWVI) is made in the case of low intensity meteorological events by the comparison with hydrological (precipitation) data. This analysis, as a first step of a more complex work in progress, is targeted to a first evaluation of the reliability of the SWVI in describing soil response to precipitations of different duration and intensity
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