Synthetic Ground Truth Generation of an Electricity Consumption Dataset

The training of supervised Machine Learning (ML) and Artificial Intelligence (AI) algorithms is strongly affected by the goodness of the input data. To this end, this paper proposes an innovative synthetic ground truth generation algorithm. The methodology is based on applying a data reduction with Symbolic Aggregate Approximation (SAX). In addition, a Classification And Regression Tree (CART) is employed to identify the best granularity of the data reduction. The proposed algorithm has been applied to telecommunication (TLC) sites dataset by analyzing their electricity consumption patterns. The presented approach substantially reduced the dispersion of the dataset compared to the raw dataset, thus reducing the effort required to train the supervised algorithms

Non-Intrusive Load Disaggregation of Industrial Cooling Demand with LSTM Neural Network

As the telecommunication industry becomes more and more energy intensive, energy efficiency actions are crucial and urgent measures to achieve energy savings. The main contribution to the energy demand of buildings devoted to the operation of the telecommunication network is cooling. The main issue in order to assess the impact of cooling equipment energy consumption to support energy managers with awareness over the buildings energy outlook is the lack of monitoring devices providing disaggregated load measurements. This work proposes a Non-Intrusive Load Disaggregation (NILD) tool that exploits a literature-based decomposition with an innovative LSTM Neural Network-based decomposition algorithm to assess cooling demand. The proposed methodology has been employed to analyze a real-case dataset containing aggregated load profiles from around sixty telecommunication buildings, resulting in accurate, compliant, and meaningful outcomes

Research understanding, attitude and awareness towards biobanking: a survey among Italian twin participants to a genetic epidemiological study

<p>Abstract</p> <p>Background</p> <p>The Italian Twin Registry (ITR) has been carrying out several genetic-epidemiological studies. Collection and storage of biological material from study participants has recently increased in the light of biobanking development. Within this scenario, we aimed at investigating understanding, awareness and attitude towards blood/DNA donation of research participants. About these quite unknown dimensions more knowledge is needed from ethical and social perspectives.</p> <p>Methods</p> <p>Cross-sectional mail survey to explore three dimensions: (i) understanding of aims and method of a specific study, (ii) attitude (three ideas for donation: "moral duty", "pragmatism", "spontaneity") and (iii) awareness (i.e. the recall of having been asked to donate) towards blood/DNA donation for research, among all the Italian twins who had participated in Euroclot (n = 181), a large international genetic-epidemiological study. Multivariate models were applied to investigate the association of sex, age, education and modality of Euroclot recruitment (twins enrolled in the ITR and volunteers) with the targeted dimensions. Pair-wise twin concordance for the "pragmatic" attitude was estimated in monozygotic and dizygotic pairs.</p> <p>Results</p> <p>Response rate was 56% (99 subjects); 75.8% understood the Euroclot method, only 33.3% correctly answered about the study aim. A significantly better understanding of aim and method was detected in "volunteers". Graduated subjects were more likely to understand study aim. In the overall sample, the "pragmatic" attitude to blood donation reached 76.8%, and biobanking awareness 89.9%. The latter was significantly higher among women. Monozygotic twins were more concordant than dizygotic twins for the "pragmatic" attitude towards blood/DNA donation for research.</p> <p>Conclusion</p> <p>Level of understanding of aims and methods of a specific research project seems to vary in relation to modalities of approaching research; most of the twins are well aware of having been asked to donate blood for biobanking activities, and seem to be motivated by a "pragmatic" attitude to blood/DNA donation. Genetic influences on this attitude were suggested. The framing of interests and concerns of healthy participants to genetic-epidemiological studies should be further pursued, since research, particularly for "common diseases", is increasingly relying on population surveys and biobanking.</p

Load Profiles Clustering and Knowledge Extraction to Assess Actual Usage of Telecommunication Sites

Deep awareness of a particular industry sector represents a fundamental starting point for its energy efficiency enhancement. In this perspective, a huge amount of industrial facilities' energy measurements are collected thanks to the widespread usage of monitoring systems and Internet-of-Things infrastructures. In this context, data mining techniques allows an effective exploitation of data for knowledge extraction to automatically analyse such enormous amount of data. This paper investigates a large data set including real telecommunication sites' aggregate electrical demand provided by the largest telecommunication service provider in Italy. The goal is the assessment of the actual usage category of telecommunication sites, aiming at supporting the facility management of the company and the energy knowledge discovery of each site category. A novel methodology is proposed that includes i) a proper normalisation method focused on energy Key Performance Indicators for telecommunication network energy management, ii) a time series decomposition tool to extract trends and periodical fluctuation of telecommunication sites' aggregated electric demand, and iii) the application of a k-Means clustering algorithm to assess sites' actual usage. The proposed methodology results in accurate outcomes, which witness the potential for practical application and discloses opportunities for further developments

The influence of autistic symptoms on social and non-social cognition and on real-life functioning in people with schizophrenia: Evidence from the Italian Network for Research on Psychoses multicenter study

BACKGROUND: Autism spectrum disorders (ASDs) and schizophrenia spectrum disorders (SSDs), although conceptualized as separate entities, may share some clinical and neurobiological features. ASD symptoms may have a relevant role in determining a more severe clinical presentation of schizophrenic disorder but their relationships with cognitive aspects and functional outcomes of the disease remain to be addressed in large samples of individuals. AIMS: To investigate the clinical, cognitive, and functional correlates of ASD symptoms in a large sample of people diagnosed with schizophrenia. METHODS: The severity of ASD symptoms was measured with the PANSS Autism Severity Scale (PAUSS) in 921 individuals recruited for the Italian Network for Research on Psychoses multicenter study. Based on the PAUSS scores, three groups of subjects were compared on a wide array of cognitive and functional measures. RESULTS: Subjects with more severe ASD symptoms showed a poorer performance in the processing speed (p\ua0=\ua00.010), attention (p\ua0=\ua00.011), verbal memory (p\ua0=\ua00.035), and social cognition (p\ua0=\ua00.001) domains, and an overall lower global cognitive composite score (p\ua0=\ua00.010). Subjects with more severe ASD symptoms also showed poorer functional capacity (p\ua0=\ua00.004), real-world interpersonal relationships (p\ua0<\ua00.001), and participation in community-living activities (p\ua0<\ua00.001). CONCLUSIONS: These findings strengthen the notion that ASD symptoms may have a relevant impact on different aspects of the disease, crucial to the life of people with schizophrenia. Prominent ASD symptoms may characterize a specific subpopulation of individuals with SSD

Familial aggregation of MATRICS Consensus Cognitive Battery scores in a large sample of outpatients with schizophrenia and their unaffected relatives

The increased use of the MATRICS Consensus Cognitive Battery (MCCB) to investigate cognitive dysfunctions in schizophrenia fostered interest in its sensitivity in the context of family studies. As various measures of the same cognitive domains may have different power to distinguish between unaffected relatives of patients and controls, the relative sensitivity of MCCB tests for relative-control differences has to be established. We compared MCCB scores of 852 outpatients with schizophrenia (SCZ) with those of 342 unaffected relatives (REL) and a normative Italian sample of 774 healthy subjects (HCS). We examined familial aggregation of cognitive impairment by investigating within-family prediction of MCCB scores based on probands' scores

The interplay among psychopathology, personal resources, context-related factors and real-life functioning in schizophrenia: stability in relationships after 4 years and differences in network structure between recovered and non-recovered patients

Improving real-life functioning is the main goal of the most advanced integrated treatment programs in people with schizophrenia. The Italian Network for Research on Psychoses previously explored, by using network analysis, the interplay among illness-related variables, personal resources, context-related factors and real-life functioning in a large sample of patients with schizophrenia. The same research network has now completed a 4-year follow-up of the original sample. In the present study, we used network analysis to test whether the pattern of relationships among all variables investigated at baseline was similar at follow-up. In addition, we compared the network structure of patients who were classified as recovered at follow-up versus those who did not recover. Six hundred eighteen subjects recruited at baseline could be assessed in the follow-up study. The network structure did not change significantly from baseline to follow-up, and the overall strength of the connections among variables increased slightly, but not significantly. Functional capacity and everyday life skills had a high betweenness and closeness in the network at follow-up, as they had at baseline, while psychopathological variables remained more peripheral. The network structure and connectivity of non-recovered patients were similar to those observed in the whole sample, but very different from those in recovered subjects, in which we found few connections only. These data strongly suggest that tightly coupled symptoms/dysfunctions tend to maintain each other's activation, contributing to poor outcome in schizophrenia. Early and integrated treatment plans, targeting variables with high centrality, might prevent the emergence of self-reinforcing networks of symptoms and dysfunctions in people with schizophrenia

The association between insight and depressive symptoms in schizophrenia: Undirected and Bayesian network analyses

Background. Greater levels of insight may be linked with depressive symptoms among patients with schizophrenia, however, it would be useful to characterize this association at symptom-level, in order to inform research on interventions. Methods. Data on depressive symptoms (Calgary Depression Scale for Schizophrenia) and insight (G12 item from the Positive and Negative Syndrome Scale) were obtained from 921 community-dwelling, clinically-stable individuals with a DSM-IV diagnosis of schizophrenia, recruited in a nationwide multicenter study. Network analysis was used to explore the most relevant connections between insight and depressive symptoms, including potential confounders in the model (neurocognitive and social-cognitive functioning, positive, negative and disorganization symptoms, extrapyramidal symptoms, hostility, internalized stigma, and perceived discrimination). Bayesian network analysis was used to estimate a directed acyclic graph (DAG) while investigating the most likely direction of the putative causal association between insight and depression. Results. After adjusting for confounders, better levels of insight were associated with greater self-depreciation, pathological guilt, morning depression and suicidal ideation. No difference in global network structure was detected for socioeconomic status, service engagement or illness severity. The DAG confirmed the presence of an association between greater insight and self-depreciation, suggesting the more probable causal direction was from insight to depressive symptoms. Conclusions. In schizophrenia, better levels of insight may cause self-depreciation and, possibly, other depressive symptoms. Person-centered and narrative psychotherapeutic approaches may be particularly fit to improve patient insight without dampening self-esteem

The interplay among psychopathology, personal resources, context-related factors and real-life functioning in schizophrenia: stability in relationships after 4 years and differences in network structure between recovered and non-recovered patients

Improving real-life functioning is the main goal of the most advanced integrated treatment programs in people with schizophrenia. The Italian Network for Research on Psychoses previously explored, by using network analysis, the interplay among illness-related variables, personal resources, context-related factors and real-life functioning in a large sample of patients with schizophrenia. The same research network has now completed a 4-year follow-up of the original sample. In the present study, we used network analysis to test whether the pattern of relationships among all variables investigated at baseline was similar at follow-up. In addition, we compared the network structure of patients who were classified as recovered at follow-up versus those who did not recover. Six hundred eighteen subjects recruited at baseline could be assessed in the follow-up study. The network structure did not change significantly from baseline to follow-up, and the overall strength of the connections among variables increased slightly, but not significantly. Functional capacity and everyday life skills had a high betweenness and closeness in the network at follow-up, as they had at baseline, while psychopathological variables remained more peripheral. The network structure and connectivity of non-recovered patients were similar to those observed in the whole sample, but very different from those in recovered subjects, in which we found few connections only. These data strongly suggest that tightly coupled symptoms/dysfunctions tend to maintain each other's activation, contributing to poor outcome in schizophrenia. Early and integrated treatment plans, targeting variables with high centrality, might prevent the emergence of self-reinforcing networks of symptoms and dysfunctions in people with schizophrenia