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BOLD MINDS aspires to enhance the understanding of vulnerability factors underlying the emergence of borderline personality disorder (BPD), with an ultimate aim of increasing the potential for young individuals to receive early, evidence-based help when their mental health is at risk. BOLD MINDS will achieve this by investigating whether disruptions in two aspects of autobiographical memory (AM), narrative identity (NI) and involuntary AM (IAM), are associated with BPD features and problem behaviours in adolescents concurrently and over time. In doing so, BOLD MINDS will strengthen the understanding of mechanisms underlying the emergence of BPD in adolescence and lay a groundwork for developing evidence-based early interventions for BPD. While currently limited, the study of AM in this field is essential for two reasons. Firstly, because the aspects of AM under investigation, NI and IAM, are known to be involved in identity formation and emotion regulation which represent two key psychological processes that are disrupted in adults with BPD and are linked to problem behaviours such as self-harm and suicidality. Secondly, because promising research is emerging on the use of AM targets in the treatment of emotional disorder in adults, and provides a strong model for future treatment development with vulnerable adolescents. In addition, this timely research program aligns with calls from international organizations to prioritize early interventions to promote adolescent mental health. BOLD MINDS will adopt and adapt state-of-the-art ecological momentary assessment and analytical techniques and work at the crossroads of clinical and cognitive psychological perspectives, allowing for a multidimensional approach to understanding BPD vulnerability. Training-through-research and formalized training of the experienced researcher will prepare her for a permanent academic position and the founding of her own research lab specializing in AM and early interventions for BPD.

Borderline Personality Disorder: Memory and Identity in Adolescence

Bilingual Experiences, Cognitive Ageing and underlying Mechanisms

The goal of the Bilingual Experiences, Cognitive Ageing and underlying Mechanisms (BECAME) project is to examine the functional neuroplastic mechanisms underlying mitigatory effects of bilingual experience on age-related cognitive decline. While evidence is available for structural brain changes supporting bilingualism-induced effects on cognitive aging (CA), functional mechanisms underlying such effects are not yet well understood. BECAME aims to fill this gap by investigating the trajectory of bilingualism-induced functional neuroplasticity across the adult lifespan (ages 18-85), crucially adopting an individual differences approach related to measurable degree of bilingual engagement. Importantly, although such benefits are thought to be rooted early in the lifespan, evidence for the timeframe and conditions of their early emergence is scarce. The choice of including the whole adult lifespan allows us to investigate these mechanisms and their emergence more directly from a lifespan perspective. I combine behavioral testing with brain recordings via electroencephalography (EEG). EEG is widely used in cognitive neuroscience to assess brain activity and the degree of communication between brain regions (functional connectivity) in response to stimuli and at rest. Combining behavioral and EEG modalities will allow me to test bilingualism’s effect on functional connectivity, as well as its consequences for functional efficiency, the minimum required neural activation to successfully perform a task. This will enable a detailed, evidence-based account of the protective effects observed in older-aged bilinguals, and how they are built from earlier life stages. By illuminating the relationship between multilingualism and resulting neurocognitive adaptations, BECAME will enable to capitalize on it as a health initiative, with manifold societal implications and the potential to be translated into actionable policies exploiting multilingualism to ameliorate effects of CA.

WHeelchair Activity Monitoring project (WHAM)

Wheelchair users (WCU) are three to five times more inactive than the general population, leading to a high risk of developing preventable secondary conditions. Although physical activity (PA) guidelines have been specifically developed for WCU, we lack systematic approaches to implement them in practice, as well as valid algorithms to monitor PA change in WCU through sensor-based solutions. Accordingly, the overall scientific aim of the WHeelchair Activity Monitoring project (WHAM) is to advance PA research and practice in WCU by developing valid digital markers for monitoring of and providing feedback on PA, paving the way for implementation and intervention. I will accomplish this through combining the complementary research fields of 1) behavioural intervention studies focusing on increasing PA in WCU (core competence University of British Columbia, UBC; outgoing phase) and 2) sensor-based PA monitoring (core competence Norwegian University of Science and Technology, NTNU; returning phase – consolidated by non-academic placement at Maastricht Instruments, which develop research prototypes including PA monitors). WHAM’s scientific aim is achieved through three objectives: 1) Measure the effect of a pragmatic exercise intervention trial on self-reported physical activity levels and cardio-respiratory fitness, 2) Develop valid algorithms for tracking PA markers in WCU, and 3) Co-create a framework that outlines how PA can be conjointly monitored and provided feedback on in WCU. This fellowship will enable me to become established as an internationally recognized researcher in the field of “physical activity and disability”, while bringing together ongoing national disjointed research activities in this field. Altogether, my overall ambition is to contribute to reducing inequalities in daily-life participation among WCU compared to the rest of the population.

Longitudinal Investigation of Visual and Numerical Perception in Preterm and Full-term Infants

The number of preterm births is on the rise -now more than 1 in 10 babies- and being born preterm is associated with having difficulties in two very important and related cognitive skills that we rely on daily: numerical and visual perception. However, a knowledge gap exists on neural and behavioural associations of numerical and visual perception in full-term and preterm infants. PrePER aims to uncover the underlying neural signatures of the cognitive dysfunctions that preterm infants might display in the first year of their lives and the role of parent-baby interaction to predict preterm infants that are at risk of developing these cognitive difficulties in the second year of their lives. The purpose is to establish criteria to identify infants (especially preterm) at-risk of having cognitive difficulties in numerical and visual perception. Shedding light on normal and impaired cognitive functions in infancy is an essential stepping stone that will pave the way for early diagnostic tools and interventions that would correct the cognitive dysfunctions more efficiently while the brain is still developing. The activities in PrePER will lead to original and innovative outcomes that are beneficial for four parties: 1) Scientific communities will be interested in the results as the ambitious research objectives address questions that have not been asked before. 2) Parents of preterm infants, health-care providers, and policy makers will be interested in the results as the overall aim is to establish criteria to identify infants at-risk of having cognitive-developmental difficulties in the first year of their lives. 3) The researcher will be accelerating her career progression as the training objectives meet her specific needs. 4) The supervisor will be enlarging her research interest and network as the research objectives include a topic within the researcher’s expertise.

AQUASERV – RESEARCH INFRASTRUCTURE SERVICES FOR SUSTAINABLE AQUACULTURE, FISHERIES AND THE BLUE ECONOMY

The overarching objectives of AQUASERV are to bring together, enhance, integrate and customise RI capacities (including facilities, instruments and expertise) and through the provision of transnational access (on-site or remote) and/or virtual access, to significantly further scientific advance and promote and facilitate the implementation of European Common Fisheries Policy, the Farm to Fork Strategy, the Sustainable Blue Economy and the European Green Deal. 

AQUASERV will achieve these objectives by offering scientists from academia and business remote and on-site transnational (TA) and virtual (VA) access to an advanced set of European research infrastructures and its nodes related to research and management of marine and freshwater biological resources, food and biotechnology. These include the European Marine Biological Resource Centre ERIC (EMBRC), the Analysis and Experimentation on Ecosystems ERIC, The Aquaculture for Excellence for Aquaculture in Fish (Aquaexcel), and the Infrastructure for Promoting Metrology in Food and Nutrition (METROFOOD), as well as the International Council for Exploration of the Sea, both a service provider and stakeholder. It also includes the Research Infrastructure for Science and Innovation Policy Studies (RISIS) to bring contributions from the social sciences and to bring results nearer to policy makers ensuring societal impact. 

To enhance, integrate and customise RI capacities, collaboration between partners and new pipelines to meet the objectives of the project will be developed during the first 3 years and will make available  to users.  To ensure these capacities will not be lost, a sustainability work package involving stakeholders will address the project legacy.  

To maximize impact, AQUASERV will build a communication network among the partnership and develop a dissemination and outreach programme. Furthermore, an advanced training programme will be developed to capture future users and will be updated during the p

IMProving User experience, Long-term sustainability and Services of EU-OPENSCREEN

EU-OPENSCREEN (EU-OS), the distributed European Research Infrastructure for Chemical Biology and early drug discovery, provides world-class services in high-throughput compound screening and medicinal chemistry to users from academia and industry. As one of the largest open-access initiative globally, EU-OPENSCREEN plays an increasingly important role in facilitating early stage drug discovery in Europe. It recently integrated fragment-based drug discovery and chemoproteomics as two new services, but the increasing complexity of modern drug discovery projects requires an even more comprehensive portfolio and integration of emerging technologies. To ensure that EU-OS continues to offer a comprehensive suite of relevant services and support a growing user community to conduct forefront research, IMPULSE will develop, validate and integrate new services in AI/ML, new chemical modalities, and innovative disease-relevant cell models combined with CRISPR-Cas9/RNAi-based genetic screening. IMPULSE will work towards the implementation of common operational and data standards to increase data reproducibility and FAIRness. Bespoke outreach and training activities will raise awareness among key user groups of its new services and advance operational excellence and reproducibility in pre-clinical drug discovery. New models for pre-competitive drug discovery with industry or charities, and growing ERIC member community will reinforce the sustainability and accessibility of EU-OPENSCREEN.

Strengthening resilience and mental wellbeing through the Support4Resilience toolbox for leaders in elderly care

European elderly care experiences labor shortages, lack of qualified workers and a mismatch between capacity and demands, causing stress, burnout, and reduced mental wellbeing among healthcare workers and informal caregivers. Leaders are crucial in promoting supportive working conditions but lack research-based measures to act upon these challenges.

Support4Resilience (S4R) will develop, implement, and evaluate a research-based Toolbox to support healthcare leaders in improving healthcare workers’ and informal caregivers’ resilience and mental wellbeing in elderly care. S4R will identify resilience and mental wellbeing factors among healthcare workers and informal caregivers; explore their perspectives and needs; develop new theory on the relationship between individual and organizational resilience, and mental wellbeing; and develop recommendations and cost-effective interventions. The Toolbox with tailormade resources for policy and practical use will be available through an open access S4R Resource Bank.

The S4R Toolbox includes three main tools: 1) Mapping and identification, 2) Reflection and education, and 3) Reorganization. Measures are initiated at the organizational level and effects on mental wellbeing and resilience transpire at the frontline of elderly care. The Toolbox covers different situational contexts, types of healthcare providers and health system levels. Elderly care settings in six European countries will implement and evaluate the Toolbox through a process evaluation, effectiveness evaluation, and cost-effectiveness evaluation. 

S4R provides policymakers, decisions-makers and leaders with solutions for taking action to solve specific risks for healthcare workers’ and informal caregivers’ resilience and mental wellbeing. Thus, pertinent to the work programme, S4R will support the development of resilient health systems in European elderly care through improved leadership capabilities, governance structures, and adaptive capacities.

NEXT GENERATION IMAGING FOR REAL-TIME DOSE VERIFICATION ENABLING ADAPTIVE PROTON THERAPY

The NOVO project will address a fundamental issue in proton radiotherapy (PT) of cancer, namely the lack of real-time dose verification (RDV) that significantly limits the potential of PT due to uncertainties in the precise delivery of the prescribed dose. In the NOVO project, we will develop the first proof-of-concept of an RDV technology adaptable to any PT treatment and bring the concept to TRL 4 by also considering integration into the PT clinical workflow. The RDV technology will be pivotal for enabling the next generation of adaptive PT therapy, i.e., dose-guided real-time adaptive therapy. Real-time measurement of the dose to targeted and non-targeted tissues will be the key to truly empower patient-centered, personalized cancer treatment, important to improve curation and quality-of-life post-treatment. As a high-risk/high-gain project, NOVO aims at a first-of-its-kind RDV technology through the unique synergy between (1) cutting-edge, inexpensive organic scintillator technology that can detect secondary radiation during treatment for non-invasive measurements, (2) novel and fast image reconstruction, artificial intelligence (AI)-accelerated models and AI-enhanced image reconstruction to allow simultaneous detection of multiple radiation species and tissue compositional analysis, (3) tumor-tracking and imaging of tissue radio-sensitivity based on oxygen levels, (4) intelligent automation of decision-making schemes for real-time dose-guided adaptive therapy. The project will essentially open a new era in PT that enables curing more cancer patients and reducing toxicity from treatment. The NOVO consortium covers the entire value chain of RDV development (technology providers, theory and modelling, technology integration and PT clinics) and optimally engages nuclear, medical, and high-energy physicists, chemists, mathematicians, computer scientists, oncologists, biologists, as well as European PT centers. 


Development of innovative proton and neutron therapies with high cancer specificity by 'hijacking' the intracellular chemistry of haem biosynthesis.

Deep-lying cancers, such as glioblastoma multiforme (GBM) brain cancer, are very difficult to access and incurable by the current standards of care. The fluorescence of photosensitive molecules (PSs) can precisely guide surgical resection of GBM. Nevertheless, photomedical treatments like photodynamic therapy (PDT) show limited efficacies due to the low penetration of light into tissue. Proton radiotherapy can reach deep-lying disease through therapeutic energy deposition in a spatially confined region called Bragg peak. Current neutron-based therapies, like Boron Neutron Capture Therapy (BNCT), have sufficient penetration depth but lack cancer specificity.
In NuCapCure, we propose to 'hijack' intracellular biosynthetic pathways and use them to produce custom-made drugs that will facilitate two genuinely new cancer treatments: i) "NuCapCure Proton", combining proton radiotherapy, protondynamic therapy through PS proton activation, and proton capture therapy (BPCT) through three produced alpha particles; and ii) "NuCapCure neutron", combining GBM specific BNCT and PS neutron activation as demonstrated in our FET-open project FRINGE.
The main scientific breakthroughs of NuCapCure will be to demonstrate the custom production of novel compounds through native intracellular biosynthesis but also to establish experimental proof-of-principle, both in vitro and in vivo, of the proposed two novel therapies. Our highly interdisciplinary project team comprises world-renowned experts from a unique combination of disciplines: proton and neutron physics, synthetic chemistry, photochemistry, photobiology, radiobiology, medical physics, nuclear reactor and particle accelerator technology and radio-oncology to lay the foundations for novel, targeted and curative therapies against currently fatal cancer indications like GBM.

Despites dental pulp capping materials should meet the certain requirements, the available materials have one or more shortcomings—poor biocompatibility and rheological properties, fail to maintain pulp vitality and to simulate reparative dentine formation and expensive etc. Mineral trioxide aggregate (MTA) is widely used material because of its beneficial properties. However, its composition bismuth oxide, which is suspectable to toxicity, has an impact on rheological properties. This emphasizes the necessity of looking for inexpensive alternatives to materials that meet the specifications. This project's goal and novelty are to investigate the potential processing of the dental pulp capping cement, which is made of strontium silicate (SrSiO3), strontium fluoride (SrF2), piezoelectric material (PZM) and tricalcium silicate (Ca3O5Si) and its rheological properties and hemocompatibility. Because SrSiO3, SrF2, PZM and Ca3O5Si have the promising properties. This project's work packages are split into four categories based on the interdisciplinary approach since it involves the synthesis and characterization of PZM, the processing and characterization of cement, the identification of rheological parameters utilizing ISO standardizations, and hemocompatibility, and acquiring new transferrable skills. Additionally, the interactions among the selected compounds will be determined. The scientific impact of this project is comprehending the physical properties and the immune system's response to evaluate the cement's suitability as a replacement for existing materials, as well as resulting in further uses in dentistry and medicine. The societal impact is providing millions of patients in Europe with predictable and outstanding treatment outcomes each year to maintain pulp vitality and health. Eventually, it will ease the financial load on millions of patients who need dental care, will be avoiding inflated medical expenses and misuse of the patent (economic impact).

SrSiO3-based Dental Pulp Capping Cement

Midlene fra PES2020-Prosj.etabl.støtte H2020 fordelt på år

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Midlene fra PES2020-Prosj.etabl.støtte H2020 fordelt på fagområde

CEO Pharma Holdings

Pharma Holdings (https://www.pharmaholdings.no) is developing eyedrops for the treatment of conjunctivitis caused by both bacteria and viruses based on LTX-109. LTX-109 is a novel antimicrobial synthetic peptide with a fast-acting membrane lysing mode of action. It is a short cationic synthetic peptide (peptidomimetic) which binds preferentially to negatively charged membrane components on microorganisms via electrostatic interactions, subsequently inducing their lysis and death . Pharma Holdings owns a patent family for LTX-109 and its use as a pharmaceutical drug (currently, EU Patent Office: EP2235041; Australia: 2008339611; USA: US8,598,114; Canada: 2,709,884; China: ZL200880126952.0; Japan: US8,598,114).

The clinicians have considerable difficulty in making a correct clinical distinction between bacterial and viral conjunctivitis. Currently, there is no medication targeting both bacterial and viral conjunctivitis – making our “all in one” innovative approach demanded by the market. Further, resistance against the current available treatment options is on the increase prompting pharmaceutical companies to develop new efficacious drugs with low propensity toward resistance development.

Further, the pathogen causing viral conjunctivitis is most often Adenovirus, for which there is no medication available and our innovative treatment may become the first on the market for this condition. 

Conjunctivitis Drugs Market is expected to register 3.1% CAGR during the forecast period of 2019 to 2025 and will be valued at USD 1.18 Billion in 2025.

Development of the first of its kind medication for combined treatment of viral and bacterial conjunctivitis.

Vindmiljøanalyser for fotgjengere er i ferd med å bli en kritisk faktor i utformingen av by- og bygningsplanlegging, gitt kompleksiteten i moderne byområder. Dette bidrar til å sikre generell trivsel, sikkerhet og komfort i gågater. Bruken av væskestrømssimuleringer gjør at arkitekter og ingeniører kan forutsi og optimalisere utformingen og ytelsen til bygninger i et tidlig stadium av designprosessen.

Særlig i tilfeller der rask iterasjonstid er ønsket, kan raskere datadrevne læringsbaserte surrogatmodeller gi en god tilnærming til simuleringen. Spesielt på grunn av deres evne til å lære komplekse spatiale mønstre og avhengigheter, representerer Deep Neural Network-baserte arkitekturer en rask og alternativ løsning for effektivt å nærme seg kartleggingsfunksjonen i høyere dimensjonale rom. De viktigste fordelene ved å bruke DNN-basert arkitektur som en surrogatmodell er: 1) ha en modell med høy grad av generalisering 2) relativt rask treningstid (i en annen størrelsesorden enn CFD-simulering) 3) raske slutninger som et resultat av interaksjon under designprosessen.

Oppsummert gir tradisjonelle CFD-metoder resultater med høy nøyaktighet, men de er beregningsmessig kostbare og fungerer ikke godt i designprosessen for nye prototyper i et gitt domene. For å oppnå resultater tar det ofte flere timer eller dager, avhengig av prototypens kompleksitet. Prosjektet har utforsket dyp læring med det formål å lage et interaktivt verktøy for å teste nye design, selv når det blir vanskelig å beregne fysiske løsninger. Spesielt har definert DL-baserte arkitekturer som kan generere vindstrømmer for vilkårlig utformede bygninger i scenarier av ulik kompleksitet (bykart), motivert av å bygge en surrogatmodell som kan brukes i et interaktivt verktøy for smarte bygningsvurderinger.

With the complexity of modern urban areas, the pedestrian wind environment analysis becomes a critical factor in urban and building planning design, helping to ensure the overall well-being, safety, and comfort in pedestrian zones. The usage of fluid flow simulation enables architects and engineers to predict and optimize the performance of buildings in the early stage of the design process. 

Especially for cases where fast iteration time is desired, the faster data-driven learning-based surrogate model can represent a reasonable approximation of the simulation. In particular, due to their capabilities in learning complex spatial patterns and dependencies, Deep Neural Network-based architectures represent a fast and alternative solution for efficiently approximating mapping function in high dimensional spaces. The main advantage of using DNN-based architecture as a surrogate model, will be 1) having a model with a high degree of generalization 2) relatively quick training time (different magnitude in comparison to CFD simulation) 3) quick inference with the advantage of interaction during the design process.

In summary, traditional CFD methods produce high-accuracy results, but they are computationally expensive and does not work well in the design process of new prototypes in a given domain. To obtain results, it often takes several hours or days, depending on the prototype’s complexity. We aim to explore deep learning with the objective of creating an interactive tool for testing new designs, even when they are getting computationally hard for physical solvers. In particular, we plan to go in a similar direction and define DL-based architectures that can generate wind flows for arbitrarily shaped buildings in scenario of different complexity (city maps) with the motivation of building a surrogate model that can be used in an interactive tool for smart building assessments.

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BIA-Brukerstyrt innovasjonsarena

LandSkape - Hybrid Physical-Based Deep Learning for Fast and Reliable Wind Flow Estimation

Tildelt: kr 4,9 mill.

Prosjektperiode: 2021-2023

Sted: Rogaland