Recurrent Neural Network Model for On-Board Estimation of the Side-Slip Angle in a Four-Wheel Drive and Steering Vehicle

A valuable quantity for analyzing the lateral dynamics of road vehicles is the side-slip angle, that is, the angle between the vehicle’s longitudinal axis and its speed direction. A reliable real-time side slip angle value enables several features, such as stability controls, identification of understeer and oversteer conditions, estimation of lateral forces during cornering, or tire grip and wear estimation. Since the direct measurement of this variable can only be done with complex and expensive devices, it is worth trying to estimate it through virtual sensors based on mathematical models. This article illustrates a methodology for real-time on-board estimation of the side-slip angle through a machine learning model (SSE—side-slip estimator). It exploits a recurrent neural network trained and tested via on-road experimental data acquisition. In particular, the machine learning model only uses input signals from a standard road car sensor configuration. The model adaptability to different road conditions and tire wear levels has been verified through a sensitivity analysis and model testing on real-world data proves the robustness and accuracy of the proposed solution achieving a root mean square error (RMSE) of 0.18 deg and a maximum absolute error of 1.52 deg on the test dataset. The proposed model can be considered as a reliable and cheap potential solution for the real-time on-board side-slip angle estimation in serial cars

Programming Light-Harvesting Efficiency Using DNA Origami.

The remarkable performance and quantum efficiency of biological light-harvesting complexes has prompted a multidisciplinary interest in engineering biologically inspired antenna systems as a possible route to novel solar cell technologies. Key to the effectiveness of biological "nanomachines" in light capture and energy transport is their highly ordered nanoscale architecture of photoactive molecules. Recently, DNA origami has emerged as a powerful tool for organizing multiple chromophores with base-pair accuracy and full geometric freedom. Here, we present a programmable antenna array on a DNA origami platform that enables the implementation of rationally designed antenna structures. We systematically analyze the light-harvesting efficiency with respect to number of donors and interdye distances of a ring-like antenna using ensemble and single-molecule fluorescence spectroscopy and detailed Förster modeling. This comprehensive study demonstrates exquisite and reliable structural control over multichromophoric geometries and points to DNA origami as highly versatile platform for testing design concepts in artificial light-harvesting networks.A. W. C. acknowledges support from the Winton Programme for the Physics of Sustainability. U. F. K. was partly supported by an ERC starting grant (PassMembrane, EY 261101). E. A.H. acknowledges support from Janggen-Pöhn Stiftung and the Schweizerischer Nationalfonds (SNF). P. T. acknowledges support by a starting grant (SiMBA, EU 261162) of the European Research Council (ERC). B. W. gratefully acknowledges support by the Braunschweig International Graduate School of Metrology B-IGSM and the DFG Research Training Group GrK1952/1 ‘Metrology for Complex Nanosystems’. P. M. thankfully acknowledges the support of the EPSRC Centre for Doctoral Training in Sensor Technologies and Applications EP/L015889/1.This is the final version of the article. It first appeared from ACS via https://doi.org/10.1021/acs.nanolett.5b0513

Multiomic profiling of medulloblastoma reveals subtype-specific targetable alterations at the proteome and N-glycan level

Abstract Medulloblastomas (MBs) are malignant pediatric brain tumors that are molecularly and clinically heterogenous. The application of omics technologies—mainly studying nucleic acids—has significantly improved MB classification and stratification, but treatment options are still unsatisfactory. The proteome and their N-glycans hold the potential to discover clinically relevant phenotypes and targetable pathways. We compile a harmonized proteome dataset of 167 MBs and integrate findings with DNA methylome, transcriptome and N-glycome data. We show six proteome MB subtypes, that can be assigned to two main molecular programs: transcription/translation (pSHHt, pWNT and pG3myc), and synapses/immunological processes (pSHHs, pG3 and pG4). Multiomic analysis reveals different conservation levels of proteome features across MB subtypes at the DNA methylome level. Aggressive pGroup3myc MBs and favorable pWNT MBs are most similar in cluster hierarchies concerning overall proteome patterns but show different protein abundances of the vincristine resistance-associated multiprotein complex TriC/CCT and of N-glycan turnover-associated factors. The N-glycome reflects proteome subtypes and complex-bisecting N-glycans characterize pGroup3myc tumors. Our results shed light on targetable alterations in MB and set a foundation for potential immunotherapies targeting glycan structures

The political dynamics of portfolio design in European democracies

Austrian Research Association (ÖFG) and the Austrian Science Fund (FWF) under grant P25490

Nucleic Acid-based Detection of Bacterial Pathogens Using Integrated Microfluidic Platform Systems

The advent of nucleic acid-based pathogen detection methods offers increased sensitivity and specificity over traditional microbiological techniques, driving the development of portable, integrated biosensors. The miniaturization and automation of integrated detection systems presents a significant advantage for rapid, portable field-based testing. In this review, we highlight current developments and directions in nucleic acid-based micro total analysis systems for the detection of bacterial pathogens. Recent progress in the miniaturization of microfluidic processing steps for cell capture, DNA extraction and purification, polymerase chain reaction, and product detection are detailed. Discussions include strategies and challenges for implementation of an integrated portable platform

Elena+ Care for COVID-19, A Pandemic Lifestyle Care Intervention: Intervention Design and Study Protocol

Background: The current COVID-19 coronavirus pandemic is an emergency on a global scale, with huge swathes of the population required to remain indoors for prolonged periods to tackle the virus. In this new context, individuals’ health-promoting routines are under greater strain, contributing to poorer mental and physical health. Additionally, individuals are required to keep up to date with latest health guidelines about the virus, which may be confusing in an age of social-media disinformation and shifting guidelines. To tackle these factors, we developed Elena+, a smartphone-based and conversational agent (CA) delivered pandemic lifestyle care intervention.Methods: Elena+ utilizes varied intervention components to deliver a psychoeducation-focused coaching program on the topics of: COVID-19 information, physical activity, mental health (anxiety, loneliness, mental resources), sleep and diet and nutrition. Over 43 subtopics, a CA guides individuals through content and tracks progress over time, such as changes in health outcome assessments per topic, alongside user-set behavioral intentions and user-reported actual behaviors. Ratings of the usage experience, social demographics and the user profile are also captured. Elena+ is available for public download on iOS and Android devices in English, European Spanish and Latin American Spanish with future languages and launch countries planned, and no limits on planned recruitment. Panel data methods will be used to track user progress over time in subsequent analyses. The Elena+ intervention is open-source under the Apache 2 license (MobileCoach software) and the Creative Commons 4.0 license CC BY-NC-SA (intervention logic and content), allowing future collaborations; such as cultural adaptions, integration of new sensor-related features or the development of new topics.Discussion: Digital health applications offer a low-cost and scalable route to meet challenges to public health. As Elena+ was developed by an international and interdisciplinary team in a short time frame to meet the COVID-19 pandemic, empirical data are required to discern how effective such solutions can be in meeting real world, emergent health crises. Additionally, clustering Elena+ users based on characteristics and usage behaviors could help public health practitioners understand how population-level digital health interventions can reach at-risk and sub-populations

Age of the Mt. Ortles ice cores, the Tyrolean Iceman and glaciation of the highest summit of South Tyrol since the Northern Hemisphere Climatic Optimum

In 2011 four ice cores were extracted from the summit of Alto dell'Ortles (3859 m), the highest glacier of South Tyrol in the Italian Alps. This drilling site is located only 37 km southwest from where the Tyrolean Iceman, similar to 5.3 kyrs old, was discovered emerging from the ablating ice field of Tisenjoch (3210 m, near the Italian-Austrian border) in 1991. The excellent preservation of this mummy suggested that the Tyrolean Iceman was continuously embedded in prehistoric ice and that additional ancient ice was likely preserved elsewhere in South Tyrol. Dating of the ice cores from Alto dell'Ortles based on Pb-210, tritium, beta activity and C-14 determinations, combined with an empirical model (COPRA), provides evidence for a chronologically ordered ice stratigraphy from the modern glacier surface down to the bottom ice layers with an age of similar to 7 kyrs, which confirms the hypothesis. Our results indicate that the drilling site has continuously been glaciated on frozen bedrock since similar to 7 kyrs BP. Absence of older ice on the highest glacier of South Tyrol is consistent with the removal of basal ice from bedrock during the Northern Hemisphere Climatic Optimum (6-9 kyrs BP), the warmest interval in the European Alps during the Holocene. Borehole inclinometric measurements of the current glacier flow combined with surface ground penetration radar (GPR) measurements indicate that, due to the sustained atmospheric warming since the 1980s, an acceleration of the glacier Alto dell'Ortles flow has just recently begun. Given the stratigraphic-chronological continuity of the Mt. Ortles cores over millennia, it can be argued that this behaviour has been unprecedented at this location since the Northern Hemisphere Climatic Optimum