Occurrence and origin of thallium in mineral and thermal waters from the northern Upper Rhine Graben and adjacent regions, Germany

Although thallium is a widespread and highly toxic element, it is rarely investigated in environmental chemistry due to its typically low concentrations in water. Consequently, little is known about the occurrence of thallium in groundwater and its origin. Here we show that high thallium concentrations of 5 up to 99 µg/l occur in Hesse exclusively in Na-Cl-waters and are locally clustered within the Taunus Border Zone. These variable concentrations seem to result from different thallium sources, varying mixing ratios of brine components, and varying degrees of thallium incorporation in hydrothermal minerals. We present evidence for a thallium origin from Zechstein (Permian) and Oligocene evaporites. A third possible source are basement brines from the Rhenish Massif. As the evaporite deposits are located tens of kilometers away from thallium-bearing wells, high thallium concentrations appear to be a good indicator of deep and regionally circulating brines

Monitoring Tropical Forest Disturbance and Recovery: A Multi-Temporal L-Band SAR Methodology from Annual to Decadal Scales

Tropical forests harbor a significant portion of global biodiversity but are increasingly degraded by human activity. Assessing restoration efforts requires the systematic monitoring of tropical ecosystem status and recovery. Satellite-borne synthetic aperture radar (SAR) supports monitoring changes in vegetation structure and is of particular utility in tropical regions where clouds obscure optical satellite observations. To characterize tropical forest recovery in the Lowland Chocó Biodiversity Hotspot of Ecuador, we apply over a decade of dual-polarized (HH + HV) L-band SAR datasets from the Japanese Space Agency’s (JAXA) PALSAR and PALSAR-2 sensors. We assess the complementarity of the dual-polarized imagery with less frequently available fully-polarimetric imagery, particularly in the context of their respective temporal and informational trade-offs. We examine the radar image texture associated with the dual-pol radar vegetation index (DpRVI) to assess the associated determination of forest and nonforest areas in a topographically complex region, and we examine the equivalent performance of texture measures derived from the Freeman–Durden polarimetric radar decomposition classification scheme applied to the fully polarimetric data. The results demonstrate that employing a dual-polarimetric decomposition classification scheme and subsequently deriving the associated gray-level co-occurrence matrix mean from the DpRVI substantially improved the classification accuracy (from 88.2% to 97.2%). Through this workflow, we develop a new metric, the Radar Forest Regeneration Index (RFRI), and apply it to describe a chronosequence of a tropical forest recovering from naturally regenerating pasture and cacao plots. Our findings from the Lowland Chocó region are particularly relevant to the upcoming NASA-ISRO NISAR mission, which will enable the comprehensive characterization of vegetation structural parameters and significantly enhance the monitoring of biodiversity conservation efforts in tropical forest ecosystems

Decoding Cobalt’s Influence: An Analysis of Environmental Impacts in the Production of NMC Cathode Active Materials for Lithium-ion Batteries

The increased use of lithium-ion batteries has raised concerns about the sustainability of their usage, prompting the need for an environmental assessment. This study evaluates and compares the environmental impacts of NMC 111 and NMC 811 cathode active materials (CAMs) using Life Cycle Assessment (LCA). To improve the accuracy of the assessment, process simulation with HSC Chemistry was employed to model the production of cobalt sulfate (CoSO₄), a key precursor for NMC cathodes. Using the simulated process data, a custom Life Cycle Inventory (LCI) was generated and the environmental impacts of CoSO₄ production were assessed using the ReCiPe 2016, midpoint impact assessment method in OpenLCA were. This custom cobalt sulphate dataset is integrated into the Ecoinvent database by replacing the default CoSO₄ input in NMC 111 and NMC 811 inventories, allowing for a comparative LCA of both chemistries The results indicate that the modelled cobalt sulfate production route has a lower environmental impact than reported literature values, with a GWP of 12.1 kg CO₂-eq per kg of CoSO₄. The majority of emissions and resource use were found to stem from extraction and early processing stages, rather than final refining. When applied to NMC 111 and NMC 811, the results highlight key trade-offs: NMC 111 exhibits a higher GWP (22.4 kg CO₂-eq/kg) due to its greater cobalt content, while NMC 811, with lower cobalt dependency, has a slightly reduced footprint (21.8 kg CO₂-eq/kg). However, the increased nickel content in NMC 811 introduces additional environmental burdens, emphasizing the need for a balanced assessment when selecting cathode chemistries

Cyber Attack Prevention and Detection for Electric Vehicle Charging

The increasing adoption of Electric Vehicles (EVs) is transforming the automotive landscape, driven by the need for a more sustainable transportation sector. To support the widespread use of EVs, an efficient and reliable charging infrastructure is essential. For this, several related communication protocols and backend systems have been established to manage power delivery, authorization, and billing. The main goals are the security of charge session payments and a power grid-friendly scheduling of EV charging loads. The charging of EVs, however, also involves various security risks in associated use-cases. On the one hand, regarding the use-case of charge authorization and billing, existing protocols fail to protect against relevant adversaries. As a result, backend operators are exposed to the risk of significant financial damages and EV users are exposed to severe privacy risks. On the other hand, regarding the use-case of charge session power control and load balancing, existing processes can be manipulated by compromised systems. As a result, adversaries may be able to cause severe physical damage to involved systems and potentially harm power grid operations. In this dissertation, we address selected security risks. For charge authorization and billing, we present three solutions to enhance the preventive security of EV charging protocols. More specifically, we present concepts (i) for the integration of crypto-agility and the use of Post-Quantum Cryptography (PQC), (ii) for the use of Self-Sovereign Identities (SSIs) to enhance EV user privacy, and (iii) for the adoption of a standardized authorization framework to reduce existing complexity. Regarding manipulations of charge session control, we present several concepts for the analysis, detection, and mitigation of related attacks. More specifically, we present (i) a feasibility analysis of resulting attacks on grid stability and a related co-simulation framework, (ii) different anomaly detection concepts for either large-scale coordinated attacks on the grid or attacks in individual charging sessions, (iii) approaches for improving detection performance, including a Generative Adversarial Network (GAN)-based Intrusion Detection System (IDS) optimization and a combination of large-scale and session-based detection, and (iv) methods for attack mitigation based on IDS outputs. All presented concepts are implemented and evaluated with regard to relevant criteria. Concepts for EV charging protocol security are evaluated regarding performance/usability criteria based on proof-of-concept implementations and regarding security/privacy criteria based on formal protocol analyses using the Tamarin prover. Concepts for the analysis, detection, and mitigation of session control-related attacks are implemented with simulation-based approaches to evaluate their effect on involved systems and their detection/mitigation performance. Used Tamarin models and simulation data are published for reproducibility and future use in related studies. Overall, our results show the presented concepts can provide a significant benefit to the security of EV charging in the sector’s future

Algorithmic Maximization of Energy Productivity to Increase Energy Savings in Production Processes

The industrial sector accounts for 25 % of Germany's gross domestic product and 28 % of total final energy consumption in 2022. This sector is therefore both environmentally and economically significant. With renewables accounting for only 6.3 % of final energy production in this sector in 2022, the environmental need for transformation in industrial energy infrastructure is high. To remain globally competitive, the energy productivity of affected production processes must be maintained. This results in highly complex design and operation problems that require algorithmic support. Therefore, this article presents a mathematical programming approach to maximize energy productivity for surface hardening. The multi-objective optimization integrates process models with an evolutionary algorithm in a unified modeling and solution approach. The optimization provides viable solutions to derive adaption of process parameters capable of reducing the energy intensity of the related production process. The approach is validated by its application to the gas heated chamber oven of the ETA Research Factory

Rapid curing of polysilazane coatings at room temperature via chloride-catalyzed hydrolysis/condensation reactions

Moisture curing of polysilazane coatings at room temperature is of advantage to industrial applications, though it often takes a longer time than the other curing methods. To tackle this problem, tetrabutylammonium chloride (TBAC) is applied in this work as an efficient catalyst for the hydrolysis and condensation reactions of polymethyl(hydro)/polydimethylsilazane coatings under ambient conditions. In the suggested catalytic mechanism, the Si–H group is nucleophilically attacked by chloride ions to form a transient Si–Cl group, which is then nucleophilically substituted by a hydroxyl group from the moisture environment. It is found that by adding TBAC in the polysilazane coating, 1.6 times more of the reactive groups (Si–H, Si–NH) are consumed during the curing process in a shorter time (the dry-to-touch time for the uncatalyzed and the TBAC-catalyzed polysilazane coatings are ca. 19 h and 1 h, respectively), while 2 times more of the Si–O–Si groups are formed. Owing to the significantly enhanced crosslinking rate and degree, the coating quality and the mechanical properties are greatly improved. The hardness and the elastic modulus of the coating are increased by a factor of two and four, respectively

StatePol – Eine Datenbank zu den Mitgliedern von Regierungen und Parlamenten in den 16 Bundesländern

Diese Research Note stellt mit StatePol eine neue Datenbank vor, die Informationen über die Mitglieder der Landesparlamente und -regierungen enthält. Die Informationen umfassen sowohl soziodemografische Merkmale als auch Karrieredaten wie Mitgliedschaften und Ämter in Fraktionen, Ausschüssen, Parlamentspräsidien und Regierungskabinetten. Der Mehrwert von StatePol besteht insbesondere darin, dass diese Daten weitestgehend tagesgenau vorliegen und somit auch Dynamiken innerhalb von Legislaturperioden erfassen. Auf diese Weise umfasst StatePol Informationen zu 6946 individuellen Entscheidungsträger:innen in den deutschen Bundesländern und insgesamt 22.379.186 tagesweise Datenpunkte mit Informationen über ihre Ämter und Mandate in Legislative und Exekutive. Wir illustrieren das Potenzial von StatePol, indem wir uns explorativ der deskriptiven Repräsentation von Gender, Alter und regionaler Herkunft (Ost‑/Westdeutschland) widmen und hierbei Schlaglichter auf tagesgenaue Veränderungen werfen. Es zeigt sich, dass der Frauenanteil in den Länderparlamenten seit den 2000er-Jahren bei etwa 30 % stagniert, wobei erhebliche Unterschiede zwischen Parteien bzw. Fraktionen erkennbar sind. Die Daten konstatieren auch einen stetigen Anstieg des Durchschnittsalters der Abgeordneten, insbesondere bei Bündnisgrünen und Linken. Während Menschen ostdeutscher Herkunft zwar in den Landtagen und Regierungen der ostdeutschen Länder dominieren, sind sie in westdeutschen Landesparlamenten und -regierungen kaum vertreten. Demgegenüber stellen in Westdeutschland geborene Menschen in allen Landesregierungen kontinuierlich einen substanziellen Anteil der Entscheidungsträger:innen. Mithilfe der hochaufgelösten Daten, die mit der Veröffentlichung der Allgemeinheit zur Verfügung stehen, können künftig wichtige Fragen der Repräsentationsforschung im deutschen Kontext umfassend untersucht werden. Zur Research Note steht ein Onlineangebot bereit, das es ermöglicht, die präsentierten Daten eingehend zu erkunden und herunterzuladen

Addressing Multiple Responsibilities in the Early Stages of R&D with Provenance Assessment

A wealth of literature and best practices on Responsible Research and Innovation (RRI) document how it can be implemented in projects. However, each project is too specific to simply replicate existing patterns. Especially in early projects with a high degree of uncertainty, where indicators and measures cannot be applied, the so-called provenance assessment as a methodological change of perspective makes it possible to assess the procedural quality of research by means of narratives. A clear picture of the challenges for European bio-economy projects is sought by mapping the broader debate on "RRI in practice" in the context of biotechnology. The SUSPHIRE project is used as a case study to show how project-specific narratives integrate and signify RRI. By unpacking various concepts of "responsibility" that are already present in the project narrative at an early stage, I will show how this assessment differs significantly from other attempts to "do RRI". It is precisely in the absence of other criteria that the assessment of provenance can bring to the fore the specific form(s) of responsibility inherent in the development of projects

Recent advances in blood-brain barrier-on-a-chip models

The blood-brain barrier is a physiological barrier between the vascular system and the nervous system. Under healthy conditions, it restricts the passage of most biomolecules into the brain, making drug development exceedingly challenging. Conventional cell-based in vitro models provide valuable insights into certain features of the BBB. Nevertheless, these models often lack the three-dimensional structure and dynamic interactions of the surrounding microenvironment, which greatly influence cell functionality. Consequently, considerable efforts have been made to enhance in vitro models for drug development and disease research. Recently, microfluidic organ-on-a-chip systems have emerged as promising candidates to better mimic the dynamic nature of the BBB. This review provides a comprehensive overview of recent BBB-on-chip devices. The typical building blocks, chip designs, the perfusion infrastructure, and readouts used to characterize and evaluate BBB formation are presented, analyzed, and discussed in detail. Statement of Significance The blood-brain barrier (BBB) is a highly selective barrier that controls what can enter the brain. While it protects the brain from harmful substances, it also hinders the delivery of treatments for neurological diseases such as Alzheimer's and Parkinson's. Due to its complexity, studying the BBB in living organisms remains difficult. However, recent advances in “organ-on-a-chip” technology have allowed scientists to create small, engineered models that replicate the BBB. These models provide a powerful platform to study diseases and test potential drugs with greater accuracy than traditional methods. Organ-on-a-chip devices are designed to mimic the behavior of organs or tissues in the human body, offering a more realistic and controlled environment for research. This review highlights recent breakthroughs in BBB-on-a-chip technology, showing how these models enhance current research and have the potential to transform the way we study brain diseases and develop new drugs. By integrating biology and engineering, BBB-on-a-chip technology has the potential to transform neuroscience research, improve drug development, and enhance our understanding of brain disorders

Künstliche Intelligenz und Urheberrechte : Erzeugnisschutz und Rechtsverletzungen

Die vorliegende Arbeit widmet sich den aktuellen und komplexen Fragestellungen, die durch die künstliche Intelligenz (KI) im Bereich des Urheberrechts aufgeworfen werden. Im Zentrum steht die Frage, ob KI-Erzeugnisse urheberrechtlich geschützt werden können und welche Rechtsverletzungen durch sie entstehen können. Darüber hinaus wird untersucht, ob und inwieweit ein neues Leistungsschutzrecht erforderlich ist und sich in die Systematik des Urheberrechtsgesetzes einordnen lässt