An ontology-based approach supporting holistic structural design with the consideration of safety, environmental impact and cost

Early stage decision-making for structural design critically influences the overall cost and environmental performance of buildings and infrastructure. However, the current approach often fails to consider the multi-perspectives of structural design, such as safety, environmental issues and cost in a comprehensive way. This paper presents a holistic approach based on knowledge processing (ontology) to facilitate a smarter decision-making process for early design stage by informing designers of the environmental impact and cost along with safety considerations. The approach can give a reasoning based quantitative understanding of how the design alternatives using different concrete materials can affect the ultimate overall performance. Embodied CO2 and cost are both considered along with safety criteria as indicative multi-perspectives to demonstrate the novelty of the approach. A case study of a concrete structural frame is used to explain how the proposed method can be used by structural designers when taking multi performance criteria into account. The major contribution of the paper lies on the creation of a holistic knowledge base which links through different knowledge across sectors to enable the structural engineer to come up with much more comprehensive decisions instead of individual single objective targeted delivery

Cross-cultural study of problematic Internet use in nine European countries

The main objective of the present study was to investigate the relationships between Problematic Internet Use (PIU) and time spent online, online activities and psychopathology, by taking cross-cultural and gender differences into account. The second objective was to provide the prevalence estimate of PIU among European Internet users. Our total sample consisted of 5593 Internet users (2129 men and 3464 women) of nine European countries, aged between 18 and 87 years old (M = 25.81; SD = 8.61). Recruited online, they completed several scales about their Internet use and psychopathology. PIU was related to time spent online at weekends, obsessive-compulsive symptoms, hostility and paranoid ideation among the total sample of women; among men phobic anxiety was also significant. Regression analyses performed in each sample also suggest the importance of obsessive-compulsive symptoms (in seven samples), somatization (four samples) and hostility (three samples). Many cross-cultural and gender differences have been observed in terms of relationships with psychopathology and online activities. Prevalence estimates of PIU ranged between 14.3% and 54.9%. PIU was more prevalent among women in the respective samples, including the total sample. This European research highlights relevant relationships between PIU, psychopathology and time spent online, as important differences with regards to these variables in respective samples. This study's cross-cultural design also allows a better understanding of gender differences in PIU

The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases.

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes

Psychological well-being in Europe after the outbreak of war in Ukraine

The Russian invasion of Ukraine on February 24, 2022, has had devastating effects on the Ukrainian population and the global economy, environment, and political order. However, little is known about the psychological states surrounding the outbreak of war, particularly the mental well-being of individuals outside Ukraine. Here, we present a longitudinal experience-sampling study of a convenience sample from 17 European countries (total participants = 1,341, total assessments = 44,894, countries with >100 participants = 5) that allows us to track well-being levels across countries during the weeks surrounding the outbreak of war. Our data show a significant decline in well-being on the day of the Russian invasion. Recovery over the following weeks was associated with an individual’s personality but was not statistically significantly associated with their age, gender, subjective social status, and political orientation. In general, well-being was lower on days when the war was more salient on social media. Our results demonstrate the need to consider the psychological implications of the Russo-Ukrainian war next to its humanitarian, economic, and ecological consequences

A global experience-sampling method study of well-being during times of crisis : The CoCo project

We present a global experience-sampling method (ESM) study aimed at describing, predicting, and understanding individual differences in well-being during times of crisis such as the COVID-19 pandemic. This international ESM study is a collaborative effort of over 60 interdisciplinary researchers from around the world in the “Coping with Corona” (CoCo) project. The study comprises trait-, state-, and daily-level data of 7490 participants from over 20 countries (total ESM measurements = 207,263; total daily measurements = 73,295) collected between October 2021 and August 2022. We provide a brief overview of the theoretical background and aims of the study, present the applied methods (including a description of the study design, data collection procedures, data cleaning, and final sample), and discuss exemplary research questions to which these data can be applied. We end by inviting collaborations on the CoCo dataset

Comprehensive reanalysis for CNVs in ES data from unsolved rare disease cases results in new diagnoses

We report the diagnostic results of a comprehensive copy number variant (CNV) reanalysis of 9,171 exome sequencing (ES) datasets from 5,757 families, including 6,143 individuals affected by a rare disease (RD). The data analysed was extremely heterogeneous, having been generated using 28 different exome enrichment kits, and sequenced on multiple short-read sequencing platforms, by 42 different research groups across Europe partnering in the Solve-RD project. Each of these research groups had previously undertaken their own analysis of the ES data but had failed to identify disease-causing variants.We applied three CNV calling algorithms to maximise sensitivity: ClinCNV, Conifer, and ExomeDepth. Rare CNVs overlapping genes of interest in custom lists provided by one of four partner European Reference Networks (ERN) were identified and taken forward for interpretation by clinical experts in RD. To facilitate interpretation, Integrative Genomics Viewer (IGV) screenshots incorporating a variety of custom-made tracks were generated for all prioritised CNVs.These analyses have resulted in a molecular diagnosis being provided for 51 families in this sample, with ClinCNV performing the best of the three algorithms in identifying disease-causing CNVs. We also identified pathogenic CNVs that are partially explanatory of the proband’s phenotype in a further 34 individuals. This work illustrates the value of reanalysing EScold casesfor CNVs even where analyses had been undertaken previously. Crucially, identification of these previously undetected CNVs has resulted in the conclusion of the diagnostic odyssey for these RD families, some of which had endured decades.3. Good health and well-bein

Systematic Collaborative Reanalysis of Genomic Data Improves Diagnostic Yield in Neurologic Rare Diseases

Altres ajuts: Generalitat de Catalunya, Departament de Salut; Generalitat de Catalunya, Departament d'Empresa i Coneixement i CERCA Program; Ministerio de Ciencia e Innovación; Instituto Nacional de Bioinformática; ELIXIR Implementation Studies (CNAG-CRG); Centro de Investigaciones Biomédicas en Red de Enfermedades Raras; Centro de Excelencia Severo Ochoa; European Regional Development Fund (FEDER).Many patients experiencing a rare disease remain undiagnosed even after genomic testing. Reanalysis of existing genomic data has shown to increase diagnostic yield, although there are few systematic and comprehensive reanalysis efforts that enable collaborative interpretation and future reinterpretation. The Undiagnosed Rare Disease Program of Catalonia project collated previously inconclusive good quality genomic data (panels, exomes, and genomes) and standardized phenotypic profiles from 323 families (543 individuals) with a neurologic rare disease. The data were reanalyzed systematically to identify relatedness, runs of homozygosity, consanguinity, single-nucleotide variants, insertions and deletions, and copy number variants. Data were shared and collaboratively interpreted within the consortium through a customized Genome-Phenome Analysis Platform, which also enables future data reinterpretation. Reanalysis of existing genomic data provided a diagnosis for 20.7% of the patients, including 1.8% diagnosed after the generation of additional genomic data to identify a second pathogenic heterozygous variant. Diagnostic rate was significantly higher for family-based exome/genome reanalysis compared with singleton panels. Most new diagnoses were attributable to recent gene-disease associations (50.8%), additional or improved bioinformatic analysis (19.7%), and standardized phenotyping data integrated within the Undiagnosed Rare Disease Program of Catalonia Genome-Phenome Analysis Platform functionalities (18%)

Happiness around the world: A combined etic-emic approach across 63 countries.

What does it mean to be happy? The vast majority of cross-cultural studies on happiness have employed a Western-origin, or "WEIRD" measure of happiness that conceptualizes it as a self-centered (or "independent"), high-arousal emotion. However, research from Eastern cultures, particularly Japan, conceptualizes happiness as including an interpersonal aspect emphasizing harmony and connectedness to others. Following a combined emic-etic approach (Cheung, van de Vijver & Leong, 2011), we assessed the cross-cultural applicability of a measure of independent happiness developed in the US (Subjective Happiness Scale; Lyubomirsky & Lepper, 1999) and a measure of interdependent happiness developed in Japan (Interdependent Happiness Scale; Hitokoto & Uchida, 2015), with data from 63 countries representing 7 sociocultural regions. Results indicate that the schema of independent happiness was more coherent in more WEIRD countries. In contrast, the coherence of interdependent happiness was unrelated to a country's "WEIRD-ness." Reliabilities of both happiness measures were lowest in African and Middle Eastern countries, suggesting these two conceptualizations of happiness may not be globally comprehensive. Overall, while the two measures had many similar correlates and properties, the self-focused concept of independent happiness is "WEIRD-er" than interdependent happiness, suggesting cross-cultural researchers should attend to both conceptualizations

Correction to: Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases

In the original publication of the article, consortium author list was missing in the article

Correction to: Solving patients with rare diseases through programmatic reanalysis of genome-phenome data

In the original publication of the article, consortium author lists were missing in the articl