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See detailActive reconfiguration of cytoplasmic lipid droplets governs migration of nutrient-limited phytoplankton
Sengupta, Anupam UL; Dhar, Jayabrata UL; Danza, Francesco et al

E-print/Working paper (2021)

As open oceans continue to warm, modified currents and enhanced stratification exacerbate nitrogen and phosphorus limitation, constraining primary production. The ability to migrate vertically bestows ... [more ▼]

As open oceans continue to warm, modified currents and enhanced stratification exacerbate nitrogen and phosphorus limitation, constraining primary production. The ability to migrate vertically bestows motile phytoplankton a crucial–albeit energetically expensive–advantage toward vertically redistributing for optimal growth, uptake and resource storage in nutrient-limited water columns. However, this traditional view discounts the possibility that the phytoplankton migration strategy may be actively selected by the storage dynamics when nutrients turn limiting. Here we report that storage and migration in phytoplankton are coupled traits, whereby motile species harness energy storing lipid droplets (LDs) to biomechanically regulate migration in nutrient limited settings. LDs grow and translocate–directionally–within the cytoplasm to accumulate below the cell nucleus, tuning the speed, trajectory and stability of swimming cells. Nutrient reincorporation reverses the LD translocation, restoring the homeostatic migratory traits measured in population-scale millifluidic experiments. Combining intracellular LD tracking and quantitative morphological analysis of red-tide forming alga, Heterosigma akashiwo, along with a model of cell mechanics, we discover that the size and spatial localization of growing LDs govern the ballisticity and orientational stability of migration. The strain-specific shifts in migration which we identify here are amenable to a selective emergence of mixotrophy in nutrient-limited phytoplankton. We rationalize these distinct behavioral acclimatization in an ecological context, relying on concomitant tracking of the photophysiology and reactive oxygen species (ROS) levels, and propose a dissipative energy budget for motile phytoplankton alleviating nutrient limitation. The emergent resource acquisition strategies, enabled by distinct strain-specific migratory acclimatizing mechanisms, highlight the active role of the reconfigurable cytoplasmic LDs in guiding vertical movement. By uncovering the mechanistic coupling between dynamics of intracellular changes to physiologically-governed migration strategies, this work offers a tractable framework to delineate diverse strategies which phytoplankton may harness to maximize fitness and resource pool in nutrient-limited open oceans of the future. [less ▲]

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See detailStudy into In-orbit Servicing of the Rosetta Mission
Rana, Loveneesh UL; Menzio, Davide UL; Ellwood, John

in International Astronautical Congress, Dubai, 25-29 October 2021 (2021, October)

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See detailAnti-seizure activity of African medicinal plants: The identification of bioactive alkaloids from the stem bark of Rauvolfia caffra using an in vivo zebrafish model
Chipiti, Talent; Viljoen M., Alvaro; Cordero Maldonado, Maria Lorena UL et al

in Journal of Ethnopharmacology (2021), 28(279),

Epilepsy is one of the major chronic diseases that does not have a cure to date. Adverse drug reactions have been reported from the use of available anti-epileptic drugs (AEDs) which are also effective in ... [more ▼]

Epilepsy is one of the major chronic diseases that does not have a cure to date. Adverse drug reactions have been reported from the use of available anti-epileptic drugs (AEDs) which are also effective in only two-thirds of the patients. Accordingly, the identification of scaffolds with promising anti-seizure activity remains an important first step towards the development of new anti-epileptic therapies, with improved efficacy and reduced adverse effects. Herbal medicines are widely used in developing countries, including in the treatment of epilepsy but with little scientific evidence to validate this use. In the search for new epilepsy treatment options, the zebrafish has emerged as a chemoconvulsant-based model for epilepsy, mainly because of the many advantages that zebrafish larvae offer making them highly suitable for high-throughput drug screening. [less ▲]

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See detailA life-course perspective on cognitive ageing: Explaining gendered trajectories in memory functioning
Bertogg, Ariane; Leist, Anja UL

Scientific Conference (2021, October)

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See detailProgressive Web-Apps: Die Dos and Dont's im UX-Design
Christ, Hendrik; Rohles, Björn UL

Article for general public (2021)

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See detailTask Offloading and Resource Allocation for IoV Using 5G NR-V2X Communication
Raza, Salman; Wang, Shangguang; Ahmed, Manzoor et al

in IEEE Internet of Things Journal (2021)

Vehicular edge computing (VEC) is an innovative computing paradigm with an exceptional ability to improve the vehicles’ capacity to manage computation-intensive applications with both low latency and ... [more ▼]

Vehicular edge computing (VEC) is an innovative computing paradigm with an exceptional ability to improve the vehicles’ capacity to manage computation-intensive applications with both low latency and energy consumption. Vehicles require to make task offloading decisions in dynamic network conditions to obtain maximum computation efficiency. In this article, we analyze computation efficiency in a VEC scenario, where a vehicle offloads its tasks to maximize computation efficiency as a tradeoff between computation time and energy consumption. Although, it is quite a challenge to ensure the quality of experience of the vehicle due to diverse task requirements and the dynamic wireless conditions caused by vehicle mobility. To tackle this problem, a computation efficiency problem is formulated by jointly optimizing task offloading decision and computation resource allocation. We propose a mobility-aware computational efficiency-based task offloading and resource allocation (MACTER) scheme and develop a distributed MACTER algorithm that provides the near-optimal solution. We further consider the fifth-generation new-radio vehicle-to-everything communication model, i.e., cellular link and millimeter wave, to enhance the system performance. The simulation outcomes demonstrate that the proposed algorithm can efficiently enhance computation efficiency while satisfying computing time and energy consumption constraints. [less ▲]

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See detailDATA DISTRIBUTION API SPECIFICATION
Blanco, Braulio UL; Brorsson, Mats Hakan UL

Report (2021)

The second deliverable for the Script Project: API Specification

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See detailErnährungssouveränität: Katzentisch statt Mitbestimmung
Adami, Joël; Reckinger, Rachel UL

Article for general public (2021)

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See detailEnablers for Matching Demand in GEO Multi-Beam Satellites: Dynamic Beamforming, Precoding, or Both?
Chaker, Haythem UL; Maturo, Nicola UL; Chatzinotas, Symeon UL et al

Scientific Conference (2021, September 30)

In trending satellite communication applications, the traffic demand is not only rapidly increasing, it is also spatiotemporally evolving. This motivates the deployment of high throughput satellite ... [more ▼]

In trending satellite communication applications, the traffic demand is not only rapidly increasing, it is also spatiotemporally evolving. This motivates the deployment of high throughput satellite systems with flexible radio resource management and transmission techniques. In contrast to regular beam layout plans (RBLP) currently used in GEO payloads, future flexible payloads are capable of dynamic beamforming (DBF) in order to illuminate the coverage area using highly-directive and traffic-adaptive beampatterns. The beampatterns in an adaptive beam layout plan (ABLP) can have irregular shapes and mutual overlaps, potentially causing excessive inter-beam interferences (IBI) compared to the RBLP case. In this work, we evaluate the combination of DBF and precoding as the latter promises high throughputs in interference-limited conditions and is supported by the recent DVB-S2X norm. Under realistic non-uniform traffic patterns, we compare a typical RBLP against an ABLP in terms of their traffic matching performances with and without precoding. Through the comparisons, we show that DBF enables to significantly reduce the capacity mismatches using an ABLP that uniformly balances the demand distribution across beams. Noting that the ABLP is IBI agnostic, an unpredictable interference environment is built. In such conditions, precoding enables to reliably provide high throughputs through full frequency reuse. [less ▲]

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See detailGetting Creative - AI and Arts
Schommer, Christoph UL

Speeches/Talks (2021)

Keynote Talk "Getting Creative - AI and Arts"; AIFA - Artificial Intelligence and the Future of Arts

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See detailEssays on Human Capital, Inequality, and Income
Menta, Giorgia UL

Doctoral thesis (2021)

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See detailPredictive Assistance for Security Risk Assessment
Bettaieb, Seifeddine UL

Doctoral thesis (2021)

In many domains such as healthcare and banking and most notably the Fintech industry, IT systems can be exposed to breaches or attacks and need to fulfill various requirements related to security to ... [more ▼]

In many domains such as healthcare and banking and most notably the Fintech industry, IT systems can be exposed to breaches or attacks and need to fulfill various requirements related to security to prevent such scenarios from happening while limiting any potential exposure. In order to demonstrate or establish that compliance, risk assessments are conducted to determine potential threats and vulnerabilities that a system might be exposed to, as well as potential security controls to implement in order to counter those breaches and fulfill the requirements.An important difficulty that analysts have to contend with during that process is sifting through a large number of vulnerabilities and security controls and determining which ones have a bearing on a given system. This challenge is often exacerbated by the scarce security expertise available in most organizations. In addition, risk assessments are conducted manually in a traditional approach and rely heavily on the expertise of available risk assessors. This turns manually eliciting the applicable vulnerabilities and controls into a lengthy, costly, tedious, and error-prone activity. Our goal is to develop an automated approach to provide decision support during that process by allowing the system to assist in the identification of vulnerabilities and security controls that are relevant to a particular context. Our approach, which is based on Machine Learning (ML), leverages historical data from security assessments performed over past systems in order to recommend applicable vulnerabilities and controls for a new system. Natural Language Processing (NLP) techniques are used in combination with ML to extract any useful information from those previous records e.g.: data from a project's internal and external environment including its scope, involved assets, collaborators,etc. We operationalize and empirically evaluate our approach using real historical data from the banking domain.The automation of such a process raises several challenges: Understanding the specifics of risk assessments is the first one and using the right tools to obtain the desired results is a second one. In fact, in addition to requiring the right data and features in combination with the proper ML techniques, existing NLP techniques are not built to handle the textual data in risk assessments with its technicalities or multilingualism. An additional challenge is to find a suitable knowledge representation for risk assessments that would enable the automation of decision-support while maintaining both cohesiveness and understandability from all involved stakeholders. In this dissertation, we investigate to which extent one can automatically provide recommendations during a risk assessment. We focus exclusively on Vulnerabilities and Security Controls. All our technical solutions have been developed and empirically evaluated in close collaboration with our industrial partner. [less ▲]

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See detailA new brain organoid model to study Parkinson’s Disease
Bolognin, Silvia UL; Smits, Lisa UL; Nickels, Sarah Louise UL et al

in Biomedical Science and Engineering (2021)

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See detailNanopore Single-Molecule Sequencing for Mitochondrial DNA Methylation Analysis: Investigating Parkin-Associated Parkinsonism as a Proof of Concept
Lüth, Theresa; Wasner, Kobi UL; Klein, Christine et al

in Frontiers in Aging Neuroscience (2021)

Objective: To establish a workflow for mitochondrial DNA (mtDNA) CpG methylation using Nanopore whole-genome sequencing and perform first pilot experiments on affected Parkin biallelic mutation carriers ... [more ▼]

Objective: To establish a workflow for mitochondrial DNA (mtDNA) CpG methylation using Nanopore whole-genome sequencing and perform first pilot experiments on affected Parkin biallelic mutation carriers (Parkin-PD) and healthy controls. Background: Mitochondria, including mtDNA, are established key players in Parkinson's disease (PD) pathogenesis. Mutations in Parkin, essential for degradation of damaged mitochondria, cause early-onset PD. However, mtDNA methylation and its implication in PD is understudied. Herein, we establish a workflow using Nanopore sequencing to directly detect mtDNA CpG methylation and compare mtDNA methylation between Parkin-related PD and healthy individuals. Methods: To obtain mtDNA, whole-genome Nanopore sequencing was performed on blood-derived from five Parkin-PD and three control subjects. In addition, induced pluripotent stem cell (iPSC)-derived midbrain neurons from four of these patients with PD and the three control subjects were investigated. The workflow was validated, using methylated and unmethylated 897 bp synthetic DNA samples at different dilution ratios (0, 50, 100% methylation) and mtDNA without methylation. MtDNA CpG methylation frequency (MF) was detected using Nanopolish and Megalodon. Results: Across all blood-derived samples, we obtained a mean coverage of 250.3X (SD ± 80.5X) and across all neuron-derived samples 830X (SD ± 465X) of the mitochondrial genome. We detected overall low-level CpG methylation from the blood-derived DNA (mean MF ± SD = 0.029 ± 0.041) and neuron-derived DNA (mean MF ± SD = 0.019 ± 0.035). Validation of the workflow, using synthetic DNA samples showed that highly methylated DNA molecules were prone to lower Guppy Phred quality scores and thereby more likely to fail Guppy base-calling. CpG methylation in blood- and neuron-derived DNA was significantly lower in Parkin-PD compared to controls (Mann-Whitney U-test p < 0.05). Conclusion: Nanopore sequencing is a useful method to investigate mtDNA methylation architecture, including Guppy-failed reads is of importance when investigating highly methylated sites. We present a mtDNA methylation workflow and suggest methylation variability across different tissues and between Parkin-PD patients and controls as an initial model to investigate. [less ▲]

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See detailInvesting in Crises
Penasse, Julien UL

Presentation (2021, September 28)

Detailed reference viewed: 19 (0 UL)