Crossover between distinct symmetries in solid solutions of rare earth nickelates

in APL MATERIALS (2021), 9(8),

A strong coupling of the lattice to functional properties is observed in many transition metal oxide systems, such as the ABO(3) perovskites. In the quest for tailor-made materials, it is essential to be ... [more ▼]

A strong coupling of the lattice to functional properties is observed in many transition metal oxide systems, such as the ABO(3) perovskites. In the quest for tailor-made materials, it is essential to be able to control the structural properties of the compound(s) of interest. Here thin film solid solutions that combine NdNiO3 and LaNiO3, two materials with the perovskite structure but distinct space groups, are analyzed. Raman spectroscopy and scanning transmission electron microscopy are combined in a synergistic approach to fully determine the mechanism of the structural crossover with chemical composition. It is found that the symmetry transition is achieved by phase coexistence in a way that depends on the substrate selected. These results carry implications for analog-tuning of physical properties in future functional materials based on these compounds. [less ▲]

Crosstalk between different family members: IL27 recapitulates IFNγ responses in HCC cells, but is inhibited by IL6-type cytokines

in BBA Molecular Cell Research (2017)

Interleukin-27 (IL27) is a type-I-cytokine of the IL6/IL12 family predominantly secreted by activated macrophages and dendritic cells. In the liver, IL27 expression was observed to be upregulated in ... [more ▼]

Interleukin-27 (IL27) is a type-I-cytokine of the IL6/IL12 family predominantly secreted by activated macrophages and dendritic cells. In the liver, IL27 expression was observed to be upregulated in patients with hepatitis B, and sera of hepatocellular carcinoma (HCC) patients contain significantly elevated levels of IL27 compared to healthy controls or patients with hepatitis and/or liver cirrhosis. In this study, we show that IL27 induces STAT1 and STAT3 phosphorylation in 5 HCC lines and 3 different types of non-transformed liver cells. We were especially interested in the relevance of the IL27-induced STAT3 activation in liver cells. Thus, we compared the IL27 responses with those induced by IFNγ (STAT1-dominated response) or IL6-type cytokines (IL6, hyper-IL6 (hy-IL6) or OSM) (STAT3-dominated response) by microarray analysis and find that in HCC cells, IL27 induces an IFNγ-like, STAT1-dependent transcriptional response, but we do not find an effective STAT3-dependent response. Validation experiments corroborate the finding from the microarray evaluation. Interestingly, the availability of STAT1 seems critical in the shaping of the IL27 response, as the siRNA knock-down of STAT1 revealed the ability of IL27 to induce the acute-phase protein γ-fibrinogen, a typical IL6 family characteristic. Moreover, we describe a crosstalk between the signaling of IL6-type cytokines and IL27: responses to the gp130-engaging cytokine IL27 (but not those to IFNs) can be inhibited by IL6-type cytokine pre-stimulation, likely by a SOCS3-mediated mechanism. Thus, IL27 recapitulates IFNγ responses in liver cells, but differs from IFNγ by its sensitivity to SOCS3 inhibition. [less ▲]

Crowdsensed Data Learning-Driven Prediction of Local Businesses Attractiveness in Smart Cities

in IEEE Symposium on Computers and Communications (ISCC), Barcelona, Spain, 2019 (2019, July)

Urban planning typically relies on experience-based solutions and traditional methodologies to face urbanization issues and investigate the complex dynamics of cities. Recently, novel data-driven ... [more ▼]

Urban planning typically relies on experience-based solutions and traditional methodologies to face urbanization issues and investigate the complex dynamics of cities. Recently, novel data-driven approaches in urban computing have emerged for researchers and companies. They aim to address historical urbanization issues by exploiting sensing data gathered by mobile devices under the so-called mobile crowdsensing (MCS) paradigm. This work shows how to exploit sensing data to improve traditionally experience-based approaches for urban decisions. In particular, we apply widely known Machine Learning (ML) techniques to achieve highly accurate results in predicting categories of local businesses (LBs) (e.g., bars, restaurants), and their attractiveness in terms of classes of temporal demands (e.g., nightlife, business hours). The performance evaluation is conducted in Luxembourg city and the city of Munich with publicly available crowdsensed datasets. The results highlight that our approach does not only achieve high accuracy, but it also unveils important hidden features of the interaction of citizens and LBs. [less ▲]

CrowdSenSim: a Simulation Platform for Mobile Crowdsensing in Realistic Urban Environments

in IEEE Access (2017)

Smart cities take advantage of recent ICT developments to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the ... [more ▼]

Smart cities take advantage of recent ICT developments to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the Internet more pervasive where objects equipped with computing, storage and sensing capabilities are interconnected with communication technologies. Because of the widespread diffusion of IoT devices, applying the IoT paradigm to smart cities is an excellent solution to build sustainable Information and Communication Technology (ICT) platforms. Having citizens involved in the process through mobile crowdsensing (MCS) techniques augments capabilities of these ICT platforms without additional costs. For proper operation, MCS systems require the contribution from a large number of participants. Simulations are therefore a candidate tool to assess the performance of MCS systems. In this paper, we illustrate the design of CrowdSenSim, a simulator for mobile crowdsensing. CrowdSenSim is designed specifically for realistic urban environments and smart cities services. We demonstrate the effectiveness of CrowdSenSim for the most popular MCS sensing paradigms (participatory and opportunistic) and we present its applicability using a smart public street lighting scenario. [less ▲]

CROWDSOURCED ARCHIVES - PRIVATE ARCHIVES AND PERSONAL COLLECTIONS

Speeches/Talks (2022)

Data collections are essential for historical research. In addition to official archives and state institutions, collections from research institutions and private holders face different challenges in ... [more ▼]

Data collections are essential for historical research. In addition to official archives and state institutions, collections from research institutions and private holders face different challenges in creation and consistency, preservation and use. While most private collections are stored in official and state archives due to donations or the acquisition of private holdings, crowdsourcing data as private collections is a different approach. Crowdsourcing has become popular in Citizen Science and public history projects in the last decade. Although crowdsourcing is not (always) meant to create an archive, the data or contributions collected are an archive nonetheless. This paper aims to highlight the possibilities and pitfalls of crowdsourcing to build an archive of private origin. In February 2021, a team at the Luxembourg Centre for Contemporary and Digital History at the University of Luxembourg launched a call for contributions to collect ego documents about the war generation. As part of the project, "WARLUX - War Experiences in Luxembourg", the team is researching the personal side of the history of the Luxembourgish war generation. To uncover the individual experiences of these men, women and families, the team asked the public to share their family stories, letters, diaries, photographs and other personal documents. The researchers aimed to enrich records on individuals, which had not yet been collected or published. While the crowdsourcing campaign was intended as complementary research material, we have created a unique digital archive of personal memories and individual voices in the form of first-hand documents and a novelty in the cultural landscape in the Grand-Duchy of Luxembourg. In my presentation and paper, I will explore the possibilities of crowdsourced (digital) private archives, their pitfalls and challenges such as copyright and GDRP and sensitive information and its future implementation into official cultural institutions. [less ▲]

CROWDSOURCED DATA FOR MOBILITY ANALYSIS

Doctoral thesis (2023)

The importance of data in transportation research has been widely recognized since it plays a crucial role in understanding and analyzing the movement of people, identifying inefficiencies in ... [more ▼]

The importance of data in transportation research has been widely recognized since it plays a crucial role in understanding and analyzing the movement of people, identifying inefficiencies in transportation systems, and developing strategies to improve mobility services. This use of data, known as mobility analysis, involves collecting and analyzing data on transport infrastructure and services, traffic flows, demand, and travel behavior. However, traditional data sources have limitations. The widespread use of mobile devices, such as smartphones, has enabled the use of Information and Communications Technology (ICT) to improve data sources for mobility analysis. Mobile crowdsensing (MCS) is a paradigm that uses data from smart devices to provide researchers with more detailed and real-time insights into mobility patterns and behaviors. However, this new data also poses challenges, such as the need to fuse it with other types of information to obtain mobility insights. In this thesis, the primary source of data that is being examined and leveraged is the popularity index of local businesses and points of interest from Google Popular Times (GPT) data. This data has significant potential for mobility analysis as it overcomes limitations of traditional mobility data, such as data availability and lack of reflection of demand for secondary activities. The main objective of this thesis is to investigate how crowdsourced data can contribute to reduce the limitations of traditional mobility datasets. This is achieved by developing new tools and methodologies to utilize crowdsourced data in mobility analysis. The thesis first examines the potential of GPT as a source to provide information on the attractiveness of secondary activities. A data-driven approach is used to identify features that impact the popularity of local businesses and classify their attractiveness based on these features. Secondly, the thesis evaluates the possible use of GPT as a source to estimate mobility patterns. A tool is created to use the crowdness of a station to estimate transit demand information and map the precise volume and temporal dynamics of entrances and exits at the station level. Thirdly, the thesis investigates the possibility of leveraging the popularity of activities around stations to estimate flows in and out of stations. A method is proposed to profile stations based on the dynamic information of activities in catchment areas. Through this data, machine learning techniques are used to estimate transit flows at the station level. Finally, this study concludes by exploring the possibility of exploiting crowdsourced data not only for extracting mobility insights under normal conditions but also to extract mobility trends during anomalous events. To this end, we focused on analyzing the recovery of mobility during the first outbreak of COVID-19 for different cities in Europe. [less ▲]

The Crowdsourced Replication Initiative: Investigating Immigration and Social Policy Preferences. Executive Report.

E-print/Working paper (2019)

In an era of mass migration, social scientists, populist parties and social movements raise concerns over the future of immigration-destination societies. What impacts does this have on policy and social ... [more ▼]

In an era of mass migration, social scientists, populist parties and social movements raise concerns over the future of immigration-destination societies. What impacts does this have on policy and social solidarity? Comparative cross-national research, relying mostly on secondary data, has findings in different directions. There is a threat of selective model reporting and lack of replicability. The heterogeneity of countries obscures attempts to clearly define data-generating models. P-hacking and HARKing lurk among standard research practices in this area.This project employs crowdsourcing to address these issues. It draws on replication, deliberation, meta-analysis and harnessing the power of many minds at once. The Crowdsourced Replication Initiative carries two main goals, (a) to better investigate the linkage between immigration and social policy preferences across countries, and (b) to develop crowdsourcing as a social science method. The Executive Report provides short reviews of the area of social policy preferences and immigration, and the methods and impetus behind crowdsourcing plus a description of the entire project. Three main areas of findings will appear in three papers, that are registered as PAPs or in process. [less ▲]

Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge

in npj Digital Medicine (2021), 4(53),

Consumer wearables and sensors are a rich source of data about patients’ daily disease and symptom burden, particularly in the case of movement disorders like Parkinson’s Disease (PD). However ... [more ▼]

Consumer wearables and sensors are a rich source of data about patients’ daily disease and symptom burden, particularly in the case of movement disorders like Parkinson’s Disease (PD). However, interpreting these complex data into so-called digital biomarkers requires complicated analytical approaches, and validating these biomarkers requires sufficient data and unbiased evaluation methods. Here we describe the use of crowdsourcing to specifically evaluate and benchmark features derived from accelerometer and gyroscope data in two different datasets to predict the presence of PD and severity of three PD symptoms: tremor, dyskinesia and bradykinesia. Forty teams from around the world submitted features, and achieved drastically improved predictive performance for PD status (best AUROC=0.87), as well as tremor- (best AUPR=0.75), dyskinesia- (best AUPR=0.48) and bradykinesia-severity (best AUPR=0.95). [less ▲]

Crowdsourcing the linguistic landscape of a multilingual country. Introducing Lingscape in Luxembourg

in Linguistik Online (2017), 85(6/2017), 185-206

Crowned Heads and Succession Crises : The Design and Reception of Bernard Gui’s Arbor genealogiae regum francorum

in Augustyn, Wolfgang; Worm, Andrea (Eds.) Visualisieren – Ordnen – Aktualisieren. Geschichtskonzepte des Mittelalters und der Frühen Neuzeit im Bild (2020)

Bernard Gui is known for his career as an inquisitor but he was also a prolific historian. His illustrated genealogical tree of the kings of France, revised over several decades in the early 14th c ... [more ▼]

Bernard Gui is known for his career as an inquisitor but he was also a prolific historian. His illustrated genealogical tree of the kings of France, revised over several decades in the early 14th c., foregrounds the anxieties and crises that affected the end of the direct Capetian line by stressing a single line of male succession. However, the reception of Bernard's Arbor in Avignon stresses the opposing idea, suggesting that genealogies are complex, discontinuous and multiple. [less ▲]