Designing a generalised reward for Building Energy Management Reinforcement Learning agents

The reduction of the carbon footprint of buildings is a challenging task, partly due to the conflicting goals of maximising occupant comfort and minimising energy consumption. An intelligent management of Heating, Ventilation and Air Conditioning (HVAC) systems is creating a promising research line in which the creation of suitable algorithms could reduce energy consumption maintaining occupants' comfort. In this regard, Reinforcement Learning (RL) approaches are giving a good balance between data requirements and intelligent operations to control building systems. However, there is a gap concerning how to create a generalised reward signal that can train RL agents without delimiting the problem to a specific or controlled scenario. To tackle it, an analysis and discussion is presented about the necessary requirements for the creation of generalist rewards, with the objective of laying the foundations that allow the creation of generalist intelligent agents for building energy management.The work described in this paper was partially supported by the Basque Government under ELKARTEK project (LANTEGI4.0 KK-2020/00072)

An IoT-Aware Architecture for Collecting and Managing Data Related to Elderly Behavior

The world population will be made up of a growing number of elderly people in the near future. Aged people are characterized by some physical and cognitive diseases, like mild cognitive impairment (MCI) and frailty, that, if not timely diagnosed, could turn into more severe diseases, like Alzheimer disease, thus implying high costs for treatments and cares. Information and Communication Technologies (ICTs) enabling the Internet of Things (IoT) can be adopted to create frameworks for monitoring elderly behavior which, alongside normal clinical procedures, can help geriatricians to early detect behavioral changes related to such pathologies and to provide customized interventions. As part of the City4Age project, this work describes a novel approach for collecting and managing data about elderly behavior during their normal activities. The data capturing layer is an unobtrusive and low-cost sensing infrastructure abstracting the heterogeneity of physical devices, while the data management layer easily manages the huge quantity of sensed data, giving them semantic meaning and fostering data shareability. This work provides a functional validation of the proposed architecture and introduces how the data it manages can be used by the whole City4Age platform to early identify risks related to MCI/frailty and promptly intervene

An IoT-Aware Approach for Elderly-Friendly Cities

The ever-growing life expectancy of people requires the adoption of proper solutions for addressing the particular needs of elderly people in a sustainable way, both from service provision and economic point of view. Mild cognitive impairments and frailty are typical examples of elderly conditions which, if not timely addressed, can turn out into more complex diseases that are harder and costlier to treat. Information and communication technologies, and in particular Internet of Things technologies, can foster the creation of monitoring and intervention systems, both on an ambient-assisted living and smart city scope, for early detecting behavioral changes in elderly people. This allows to timely detect any potential risky situation and properly intervene, with benefits in terms of treatment's costs. In this context, as part of the H2020-funded City4Age project, this paper presents the data capturing and data management layers of the whole City4Age platform. In particular, this paper deals with an unobtrusive data gathering system implementation to collect data about daily activities of elderly people, and with the implementation of the related linked open data (LOD)-based data management system. The collected data are then used by other layers of the platform to perform risk detection algorithms and generate the proper customized interventions. Through the validation of some use-cases, it is demonstrated how this scalable approach, also characterized by unobtrusive and low-cost sensing technologies, can produce data with a high level of abstraction useful to define a risk profile of each elderly person

Major histocompatibility complex associations of ankylosing spondylitis are complex and involve further epistasis with ERAP1

Ankylosing spondylitis (AS) is a common, highly heritable, inflammatory arthritis for which HLA-B*27 is the major genetic risk factor, although its role in the aetiology of AS remains elusive. To better understand the genetic basis of the MHC susceptibility loci, we genotyped 7,264 MHC SNPs in 22,647 AS cases and controls of European descent. We impute SNPs, classical HLA alleles and amino-acid residues within HLA proteins, and tested these for association to AS status. Here we show that in addition to effects due to HLA-B*27 alleles, several other HLA-B alleles also affect susceptibility. After controlling for the associated haplotypes in HLA-B, we observe independent associations with variants in the HLA-A, HLA-DPB1 and HLA-DRB1 loci. We also demonstrate that the ERAP1 SNP rs30187 association is not restricted only to carriers of HLA-B*27 but also found in HLA-B*40:01 carriers independently of HLA-B*27 genotype

An Innovative Approach for Elderly Behavioral Analysis by adopting enabling IoT Technologies

As the average age of the citizens increases, cities must provide new services for the emerging problem. The City4Age project aims to provide meaningful interventions to address the problems related to Mild Cognitive Impairment and Frailty in elderly citizens. As part of the City4Age project we have developed a flexible and scalable data capturing and management infrastructure which combines both the Internet of Things and Linked Open Data paradigms. A proof-of-concept validation illustrates how data are collected, managed and computed by the proposed system to make them available for MCI and frailty risk detection algorithms and for third parties

An IoT-Aware Architecture for Collecting and Managing Data Related to Elderly Behavior

The world population will be made up of a growing number of elderly people in the near future. Aged people are characterized by some physical and cognitive diseases, like mild cognitive impairment (MCI) and frailty, that, if not timely diagnosed, could turn into more severe diseases, like Alzheimer disease, thus implying high costs for treatments and cares. Information and Communication Technologies (ICTs) enabling the Internet of Things (IoT) can be adopted to create frameworks for monitoring elderly behavior which, alongside normal clinical procedures, can help geriatricians to early detect behavioral changes related to such pathologies and to provide customized interventions. As part of the City4Age project, this work describes a novel approach for collecting and managing data about elderly behavior during their normal activities.Thedata capturing layer is an unobtrusive and low-cost sensing infrastructure abstracting the heterogeneity of physical devices, while the datamanagement layer easily manages the huge quantity of sensed data, giving them semantic meaning and fostering data shareability. This work provides a functional validation of the proposed architecture and introduces how the data it manages can be used by the whole City4Age platform to early identify risks related to MCI/frailty and promptly intervene

A rapid diagnostic multiplex PCR approach for xenomonitoring of human and animal schistosomiasis in a 'One Health' context

Studying the epidemiology of schistosomiasis-the most prevalent gastropod-borne human disease and an economic burden for the livestock industry-relies on adequate monitoring tools. Here we describe a molecular assay for detecting human and animal African schistosome species in their planorbid gastropod host (xenomonitoring) using a two-step approach. First, schistosome infections are detected and discriminated from other trematode infections using a multiplex polymerase chain reaction (PCR) that includes a trematode-specific marker (in 18S rDNA), a Schistosoma genus-specific marker (in internal transcribed spacer 2 [ITS2]) and a general gastropod marker (in 18S rDNA) as an internal control. Upon Schistosoma sp. detection, a second multiplex PCR is performed to discriminate among Schistosoma haematobium, Schistosoma mansoni, Schistosoma mattheei and Schistosoma bovis/Schistosoma curassoni/Schistosoma guineensis using markers of differential lengths in the cytochrome c oxidase subunit 1 (COX1) gene. The specificity of these assays was validated with adult worms, naturally infected gastropods and human urine and stool samples. Sensitivity was tested on experimentally infected snail specimens that were sacrificed 10 and 40 days post-infection in order to mimic a natural prepatent and mature infection, respectively. The assay provides a diagnostic tool to support the xenomonitoring of planorbid gastropods for trematode infections in a One Health context, with a focus on the transmission monitoring of schistosomiasis.status: publishe

A rapid diagnostic multiplex PCR approach for xenomonitoring of human and animal schistosomiasis in a 'One Health' context

Studying the epidemiology of schistosomiasis-the most prevalent gastropod-borne human disease and an economic burden for the livestock industry-relies on adequate monitoring tools. Here we describe a molecular assay for detecting human and animal African schistosome species in their planorbid gastropod host (xenomonitoring) using a two-step approach. First, schistosome infections are detected and discriminated from other trematode infections using a multiplex polymerase chain reaction (PCR) that includes a trematode-specific marker (in 18S rDNA), a Schistosoma genus-specific marker (in internal transcribed spacer 2 [ITS2]) and a general gastropod marker (in 18S rDNA) as an internal control. Upon Schistosoma sp. detection, a second multiplex PCR is performed to discriminate among Schistosoma haematobium, Schistosoma mansoni, Schistosoma mattheei and Schistosoma bovis/Schistosoma curassoni/Schistosoma guineensis using markers of differential lengths in the cytochrome c oxidase subunit 1 (COX1) gene. The specificity of these assays was validated with adult worms, naturally infected gastropods and human urine and stool samples. Sensitivity was tested on experimentally infected snail specimens that were sacrificed 10 and 40 days post-infection in order to mimic a natural prepatent and mature infection, respectively. The assay provides a diagnostic tool to support the xenomonitoring of planorbid gastropods for trematode infections in a One Health context, with a focus on the transmission monitoring of schistosomiasis

A Performance Analysis of an IoT-aware Elderly Monitoring System

The growing average age of the urban population, with an increasing number of 65+ years old citizens, is calling for the cities to provide global services specifically geared to elderly people. In this context, collecting data from the elderly’s environment and his/her habits and making them available in a structured way to third parties for analysis, is the first step towards the realization of innovative user-centric services. This paper is focused on a performance analysis of three main blocks of an IoT-aware monitoring system: (i) data capturing in home and in the city, (ii) data store and management in the Cloud and, (iii) data analytics. Critical points in the system architecture have been highlighted trying also to define potential solutions able to overcome them. The analyzed system architecture is used by the H2020 City4Age project to help geriatricians in identifying the onset of Mild Cognitive Impairment (MCI) and frailty conditions

Comparison of the clinical expression of patients with ankylosing spondylitis from Europe and Latin America.

To compare the clinical, demographic, and serologic characteristics and the treatment of patients diagnosed with ankylosing spondylitis (AS) from Europe (EU) and Latin America (LA).Comparative StudyJournal ArticleMulticenter StudyRESPONDIA group ;ASPECT study group ;REGISPONSER study groupinfo:eu-repo/semantics/publishe