The MIG Framework: Enabling Transparent Process Migration in Open MPI

This paper introduces the mig framework: an Open MPI extension to transparently support the migration of application processes, over different nodes of a distributed High-Performance Computing (HPC) system. The framework provides mechanism on top of which suitable resource managers can implement policies to react to hardware faults, address performance variability, improve resource utilization, perform a fine-grained load balancing and power thermal management. Compared to other state-of-the-art approaches, the mig framework does not require changes in the application code. Moreover, it is highly maintainable, since it is mainly a self-contained solution that has required a very few changes in other already existing Open MPI frameworks. Experimental results have shown that the proposed extension does not introduce significant overhead in the application execution, while the penalty due to performing a migration can be properly taken into account by a resource manager

Integrating home monitoring for transcranial direct current stimulation (tDCS) therapy to professional care environment

Daily management of neurodegenerative diseases is one of the most striking scenarios where an integrated health care system is essential for the continuous assistance to the patient and requires qualification of the caregivers and their training. In particular, patients affected by depression or chronic pain, as well as rehabilitating after stroke, can be treated at home with non-invasive electrical neuromodulation (transcranial Direct Current Stimulation, tDCS) in order to reduce daily travel expenses between home and hospital. Home monitoring of patient undergoing tDCS is essential to (1) optimize the stimulation parameters according to the current health status and to the stimulation outcomes, and (2) assess disease progression. However, monitoring effectiveness depends on the exchange of this information between the patient at home and his/her reference neurologist. Currently, the health IT scenario is composed by two independent environments, one dedicated to healthcare professionals (e.g., Electronic Health Records, EHRs), and one including mobile devices applications dedicated to citizens, caregivers and patients. Safety, communication and interoperability gaps prevented from an effective data exchange between these two environments. The aim of our work is to implement an integrated home monitoring system for tDCS patients, in which a web-based platform for EHR management exchanges data with a patient\u2019s mobile app

Global meteorological drought – Part 2: Seasonal forecasts

Global seasonal forecasts of meteorological drought using the standardized precipitation index (SPI) are produced using two data sets as initial conditions: the Global Precipitation Climatology Centre (GPCC) and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis (ERAI); and two seasonal forecasts of precipitation, the most recent ECMWF seasonal forecast system and climatologically based ensemble forecasts. The forecast evaluation focuses on the periods where precipitation deficits are likely to have higher drought impacts, and the results were summarized over different regions in the world. The verification of the forecasts with lead time indicated that generally for all regions the least reduction on skill was found for (i) long lead times using ERAI or GPCC for monitoring and (ii) short lead times using ECMWF or climatological seasonal forecasts. The memory effect of initial conditions was found to be 1 month of lead time for the SPI-3, 4 months for the SPI-6 and 6 (or more) months for the SPI-12. Results show that dynamical forecasts of precipitation provide added value with skills at least equal to and often above that of climatological forecasts. Furthermore, it is very difficult to improve on the use of climatological forecasts for long lead times. Our results also support recent questions of whether seasonal forecasting of global drought onset was essentially a stochastic forecasting problem. Results are presented regionally and globally, and our results point to several regions in the world where drought onset forecasting is feasible and skilful

Is My Model Up-to-date? Detecting CoViD-19 Variants by Machine Learning

Machine learning extracts models from huge quantities of data. Models trained and validated over past data can be deployed in making forecasts as well as in classifying new incoming data. The real world which generates data may change over time, making the deployed model an obsolete one. To preserve the quality of the currently deployed model, continuous machine learning is required. Our approach retrospectively evaluates in an online fashion the behaviour of the currently deployed model. A drift detector detects any performance slump, and, in case, can replace the previous model with an up-to-date one. The approach experiments on a dataset of 8642 hematochemical examinations from hospitalized patients gathered over 6 months: the outcome of the model predicts the RT-PCR test result about CoViD-19. The method reached an area under the curve (AUC) of 0.794, 6% better than offline and 5% better than standard online-binary classification techniques

Protocollo per il campionamento di fitoplancton in ambiente lacustre

No abstract availabl

Monitoring Dressing Autonomy: A Remote Home Care RFID-Based Solution for People with Dementia

The number of elder people with dementia is steadily increasing, and so is the need for solutions to support remote home care and to facilitate “aging in place”. People affected by dementia often need assistance with daily self-care tasks such as dressing, eating, and bathing. Our focus is on the dressing activity: we analyze the requirements and propose a system that leverages RFID-based technology to support individuals in dressing appropriately, let the individuals reside at home or in assisted living facilities. The system exploits RFID tags, fixed or ironed onto the person’s clothes, and antennas to read and collect data from the tags. The system detects the user’s outfit, eventually providing the individual with immediate feedback and alerting the caregiver. We compare two different RFID technologies: one operating at 13.56 MHz (HF)—commonly adopted in the literature—and one at 868 MHz (UHF). An in-depth analysis of the RFID technology for detecting worn clothes is reported, considering the scenario where the antennas are positioned on one side of a door to achieve comprehensive detection coverage of the entire body

A Methodology to Measure Glucose Metabolism by Quantitative Analysis of PET Images

Positron emission tomography (PET) with F-18 fluorodeoxyglucose (FDG) tracer is the standard clinical technique to measure myocardial and vessel metabolism and viability and to investigate the metabolic syndrome associated with cardiovascular diseases. The quantitative analysis of PET images allows one to study the cardiovascular physiological processes, by extracting quantitative parameters from the analysis of the tracer kinetic. Here, we propose a new methodology to quantify and evaluate the evolution of glucose metabolism inside the myocardium and the large vascular structures over time. We merge and analyze PET and CT cardiac images, extracting different volumes of interest (VOI) and performing quantitative measurements. To validate it, we apply the methodology to merge images of the aorta vessel for patients affected by metabolic syndrome. The application of the proposed approach to the use case reveals a correlation between administered drugs and metabolic syndrome, measuring the glucose metabolic rate (MRGlu) in both the myocardium and aorta. The proposed methodology can be used to evaluate some cardiovascular risk indexes of diabetic patients, too. The proposed methodology can also be deployed to analyze other application domains

Towards a genealogy of critical urban studies

Urban Studie

Protocollo per il campionamento dei parametri chimico-fisici a sostegno degli elementi biologici in ambiente lacustre

Abstract not availableIl protocollo sul campionamento delle acque lacustri integra completandole le metodologie di campionamento ed analisi del fitoplancton, delle macrofite acquatiche e della fauna a macroinvertebrati in ambiente lacustre riportati nei capitoli successivi di questo Manuale. Anche questo protocollo come i precedenti segue le indicazioni della Direttiva 60/2000/CE (Water Framework Directive, WFD) e del Regolamento per la progettazione del programma di monitoraggio emanato dal Ministero dell?Ambiente e della Tutela del Territorio e del Mare

Frictional instabilities in clay illuminate the origin of slow earthquakes

: The shallowest regions of subduction megathrusts mainly deform aseismically, but they can sporadically host slow-slip events (SSEs) and tsunami earthquakes, thus representing a severe hazard. However, the mechanisms behind these remain enigmatic because the frictional properties of shallow subduction zones, usually rich in clay, do not allow earthquake slip according to standard friction theory. We present experimental data showing that clay-rich faults with bulk rate-strengthening behavior and null healing rate, typically associated with aseismic creep, can contemporaneously creep and nucleate SSE. Our experiments document slow ruptures occurring within thin shear zones, driven by structural and stress heterogeneities of the experimental faults. We propose that bulk rate-strengthening frictional behavior promotes long-term aseismic creep, whereas localized frictional shear allows slow rupture nucleation and quasi-dynamic propagation typical of rate-weakening behavior. Our results provide additional understanding of fault friction and illustrate the complex behavior of clay-rich faults, providing an alternative paradigm for interpretation of the spectrum of fault slip including SSEs and tsunami earthquakes