On Improving Slant Wet delays for Tracking Severe Weather Events: An evaluation During Two Storms in Europe

Scientific Conference (2022, December 14)

Climate change has led to an increase in the frequency and severity of weather events with intense precipitation and, subsequently, a greater susceptibility of communities around the world to flash ... [more ▼]

Climate change has led to an increase in the frequency and severity of weather events with intense precipitation and, subsequently, a greater susceptibility of communities around the world to flash flooding. Networks of ground-based Global Navigation Satellite System (GNSS) stations enable the measurement of integrated water vapor along slant pathways, providing three-dimensional (3D) water vapor distributions at low-cost and in real-time. This makes these data a valuable complementary source of information for tracking storm events and predicting their paths. However, it is well established that residual modelling errors and multipath (MP) effects at GNSS stations do impact incoming signals, especially at low elevations and during storms when the atmospheric conditions change rapidly. Until now, the bulk of GNSS products for meteorology are estimates of the more conventional zenith total delays and horizontal gradients, but these products may not be most appropriate for determining 3D distributions of water vapor during convective storm events. In this study we investigate the impact of residual-phase-corrected and multipath-corrected slant wet delay (SWD) estimates on tracking extreme weather events using two events in Europe that led to flooding, damage to property and loss of life. We employed Precise Point Positioning (PPP) with integer ambiguity resolution to generate station-specific MP correction maps. The spatial stacking was carried out in congruent cells with an optimal resolution in elevation and azimuth at the local horizon but with decreasing azimuth resolution as the elevation angle increases. This permits an approximately equal number of observations allocated to each cell. In our analysis we recovered the one-way SWD by adding GNSS post-fit phase residuals, representing the non-isotropic component of the SWD, i.e., the higher-order inhomogeneity. Using the derived MP maps in a final step, the one-way SWD were improved to employ them for the analysis of the weather event. Moreover, we validated the SWD between ground-based water-vapor radiometry and GNSS-derived SWD for different elevation angles. Furthermore, the spatio-temporal fluctuations in the SWD as measured by GNSS closely mirrored the moisture field from the ERA5 re-analysis associated with this severe weather event [less ▲]

MiRNAs from serum-derived extracellular vesicles as biomarkers for uveal melanoma progression

in Frontiers in Cell and Developmental Biology (2022)

Uveal melanoma (UM) is a rare type of malignancy that originates from melanocytes located in the choroid, iris and the ciliary body of the eye. UM has a very high mortality upon metastatic spread to the ... [more ▼]

Uveal melanoma (UM) is a rare type of malignancy that originates from melanocytes located in the choroid, iris and the ciliary body of the eye. UM has a very high mortality upon metastatic spread to the liver, the prime target organ for UM metastasis. The lack of effective therapies for advanced stages of the disease aggravate the prognosis further. Moreover, biomarkers for early detection and progression of UM, especially the molecular traits governing the development of metastasis, are still not available in clinical practice. One extensively studied components of liquid biopsies are exosomes, a subtype of extracellular vesicle. Due to their unique molecular cargo, they could be used as carriers of early markers of cancer development and progression. For characterisation of the miRNA profiles present in circulating serum-derived exosomes of patients with diagnosed primary and metastatic UM, we have analysed the miRNA cargos using next-generation sequencing followed by RT-qPCR validation in a cohort of patients (control n=20; primary n=9; metastatic n=11). Nine miRNAs clearly differentiating these patient groups have been established. We show that hsa-miR-223 and hsa-miR-203a are the most promising biomarker candidates, allowing categorization of patients into local and advanced UM. Additionally, the comparison of miRNA expression levels in exosomes derived from UM patients with those derived from healthy donors, revealed that hsa-miR-144 has the potential to be used as an early marker for presence of UM. Taken together, this pilot study reveals that miRNAs extracted from circulating exosomes could be exploited as potential biomarkers in UM diagnosis and, more importantly, for indicating metastatic spread. [less ▲]

Towards an Efficient and Coherent Regulatory Framework on Cybersecurity in the EU: The Proposals for a NIS 2.0 Directive and a Cyber Resilience Act

in Applied Cybersecurity & Internet Governance (2022), 1(1),

Cybersecurity regulation in the EU has long been implemented in a piece- meal fashion resulting in a fragmented regulatory landscape. Recent developments triggered the EU to review its approach which has ... [more ▼]

Cybersecurity regulation in the EU has long been implemented in a piece- meal fashion resulting in a fragmented regulatory landscape. Recent developments triggered the EU to review its approach which has not resulted in the envisaged high level of cyber resilience across the Union. The paper addresses the EU’s limited mandate to regulate cybersecurity and outlines how the internal market rationale serves as a basis to harmonise cybersecurity legislation in the EU Member States. In that regard, the recent Proposal for a NIS 2.0 Directive (adopted by the European Parliament in November 2022) and the Proposal for a Cyber Resilience Act (published in September 2022) highlight how the EU seeks to align legislation and reduce complexity between different, often sectoral regulatory approaches to cybersecurity, while at the same time extending regulation in a view to achieve a high level of cybersecurity across the EU. As regards the latter, the paper also outlines how the Cyber Resilience Act will complement the NIS 2.0 Directive in order to close existing regulatory gaps. [less ▲]

Compressive Instabilities Enable Cell-Induced Extreme Densification Patterns in the Fibrous Extracellular Matrix: Discrete Model Predictions

E-print/Working paper (2022)

Interpretation and distinction between labour exploitation in the context of trafficking in human beings and particularly exploitative working conditions under the Employers Sanctions Directive

Scientific Conference (2022, December 01)

This presentation presents the findings of the EMN Luxembourg inform entitled Interpretation and distinction between labour exploitation in the context of trafficking in human beings and particularly ... [more ▼]

This presentation presents the findings of the EMN Luxembourg inform entitled Interpretation and distinction between labour exploitation in the context of trafficking in human beings and particularly exploitative working conditions under the Employers Sanctions Directive and the conclusions of the Benelux thematic day entitled "Human Trafficking" on 11 October 2022 that took place under the Luxembourgish presidency of the Benelux. [less ▲]

Crex: Predicting patch correctness in automated repair of C programs through transfer learning of execution semantics

in Information and Software Technology (2022), 152

Non-Geostationary Satellite Communications Systems

Book published by The Institution of Engineering and Technology (IET) (2022)

Lightweight Permutation-Based Cryptography for the Ultra-Low-Power Internet of Things

in Bella, Giampaolo; Doinea, Mihai; Janicke, Helge (Eds.) Innovative Security Solutions for Information Technology and Communications 15th International Conference, SECITC 2022, Virtual Event, December 8-9, 2022, Revised Selected Papers (2022, December)

The U.S. National Institute of Standards and Technology is currently undertaking a process to evaluate and eventually standardize one or more "lightweight" algorithms for authenticated encryption and ... [more ▼]

The U.S. National Institute of Standards and Technology is currently undertaking a process to evaluate and eventually standardize one or more "lightweight" algorithms for authenticated encryption and hashing that are suitable for resource-restricted devices. In addition to security, this process takes into account the efficiency of the candidate algorithms in various hardware environments (e.g. FPGAs, ASICs) and software platforms (e.g. 8, 16, 32-bit microcontrollers). However, while there exist numerous detailed benchmarking results for 8-bit AVR and 32-bit ARM/RISC-V/ESP32 microcontrollers, relatively little is known about the candidates' efficiency on 16-bit platforms. In order to fill this gap, we present a performance evaluation of the final-round candidates Ascon, Schwaemm, TinyJambu, and Xoodyak on the MSP430 series of ultra-low-power 16-bit microcontrollers from Texas Instruments. All four algorithms were explicitly designed to achieve high performance in software and have further in common that the underlying primitive is a permutation. We discuss how these permutations can be implemented efficiently in Assembly language and analyze how basic design decisions impact their execution time on the MSP430 architecture. Our results show that, overall, Schwaemm is the fastest algorithm across various lengths of data and associated data, respectively. Xoodyak has benefits when a large amount of associated data is to be authenticated, whereas TinyJambu is very efficient for the authentication of short messages. [less ▲]

Alterations of oral microbiota and impact on the gut microbiome in type 1 diabetes mellitus revealed by integrated multi-omic analyses

in Microbiome (2022)

Background: Alterations to the gut microbiome have been linked to multiple chronic diseases. However, the drivers of such changes remain largely unknown. The oral cavity acts as a major route of exposure ... [more ▼]

Background: Alterations to the gut microbiome have been linked to multiple chronic diseases. However, the drivers of such changes remain largely unknown. The oral cavity acts as a major route of exposure to exogenous factors including pathogens, and processes therein may affect the communities in the subsequent compartments of the gastrointestinal tract. Here, we perform strain‑resolved, integrated meta‑genomic, transcriptomic, and proteomic analyses of paired saliva and stool samples collected from 35 individuals from eight families with multiple cases of type 1 diabetes mellitus (T1DM). Results: We identified distinct oral microbiota mostly reflecting competition between streptococcal species. More specifically, we found a decreased abundance of the commensal Streptococcus salivarius in the oral cavity of T1DM individuals, which is linked to its apparent competition with the pathobiont Streptococcus mutans. The decrease in S. salivarius in the oral cavity was also associated with its decrease in the gut as well as higher abundances in facultative anaerobes including Enterobacteria. In addition, we found evidence of gut inflammation in T1DM as reflected in the expression profiles of the Enterobacteria as well as in the human gut proteome. Finally, we were able to follow transmitted strain‑variants from the oral cavity to the gut at the individual omic levels, highlighting not only the transfer, but also the activity of the transmitted taxa along the gastrointestinal tract. Conclusions: Alterations of the oral microbiome in the context of T1DM impact the microbial communities in the lower gut, in particular through the reduction of “mouth‑to‑gut” transfer of Streptococcus salivarius. Our results indicate that the observed oral‑cavity‑driven gut microbiome changes may contribute towards the inflammatory processes involved in T1DM. Through the integration of multi‑omic analyses, we resolve strain‑variant “mouth‑to‑gut” transfer in a disease context. [less ▲]

A Survey on Machine Learning-based Misbehavior Detection Systems for 5G and Beyond Vehicular Networks

in IEEE Communications Surveys and Tutorials (2022)

Advances in Vehicle-to-Everything (V2X) technology and onboard sensors have significantly accelerated deploying Connected and Automated Vehicles (CAVs). Integrating V2X with 5G has enabled Ultra-Reliable ... [more ▼]

Advances in Vehicle-to-Everything (V2X) technology and onboard sensors have significantly accelerated deploying Connected and Automated Vehicles (CAVs). Integrating V2X with 5G has enabled Ultra-Reliable Low Latency Communications (URLLC) to CAVs. However, while communication performance has been enhanced, security and privacy issues have increased. Attacks have become more aggressive, and attackers have become more strategic. Public Key Infrastructure (PKI) proposed by standardization bodies cannot solely defend against these attacks. Thus, in complementary of that, sophisticated systems should be designed to detect such attacks and attackers. Machine Learning (ML) has recently emerged as a key enabler to secure future roads. Various V2X Misbehavior Detection Systems (MDSs) have adopted this paradigm. However, analyzing these systems is a research gap, and developing effective ML-based MDSs is still an open issue. To this end, this paper comprehensively surveys and classifies ML-based MDSs as well as discusses and analyses them from security and ML perspectives. It also provides some learned lessons and recommendations for guiding the development, validation, and deployment of ML-based MDSs. Finally, this paper highlighted open research and standardization issues with some future directions. [less ▲]