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Influencing Alertness Through Remote Coaching for Professional Drivers
No full textThis paper presents a focused look at findings related to driver fatigue from Use Case A (UCA) of EU project PANACEA (grant agreement number 953426). UCA considers safety drivers of autonomous shuttles. For safety and regulation reasons all shuttles have a driver present ready to intervene if needed. In practice, this means that the safety driver is responsible for ensuring the safety of both passengers and surrounding road users. 8 shuttle safety drivers (100% of those available) participated. Subjective driver sleepiness was reported daily at the start and end of each shift using the Karolinska Sleepiness Scale. Potential risk for driver sleepiness was calculated using the Bordeaux Sleepiness Scale (BOSS). Overall, sleepiness was a rare experience (mean KSS start shift = 3, mean KSS end shift = 3.1). However, those identified as potentially at-risk using BOSS had some experiences of sleepiness (KSS = 7) on some shifts. The PANACEA system uses input from sensors in the vehicle, workplace depot and on the driver, creating a holistic monitoring and assessment system. This detects professional drivers who are not fit to drive and supports them and their employers to manage the situation and adopt preventive measures. PANACE
From analysis to findings: How do process mining analysts discover results?
No full textProcess mining involves analyzing event data from business process executions to uncover valuable insights. Although obtaining meaningful results is crucial for any process mining initiative, there is still little understanding of how process analysts derive these insights. In this paper, we fill this gap by characterizing findings of process mining analysis, the processes that lead to these findings, and the role of process mining expertise in guiding these processes. To this end, we leverage empirical data from a study with process mining analysts, including user interactions from process mining tools and inference steps from think-aloud protocols. Our empirical insights provide a comprehensive understanding of how analysts interact with process mining tools, highlighting approaches that lead to valuable findings. The results of our analysis lay the groundwork for the design of tools and visualizations that can support process analysts in their analysis and reasoning processes.Funding Agencies|Swiss National Science Foundation, Switzerland [2000 21_197032]</p
Spectral and stiffness characterization of whole prostate gland to assist superficial cancer detection during radical prostatectomy
No full textProstate cancer treatment depends on whether the cancer exists only inside the gland or within the prostate capsule or on the outside surface of the gland. The presence on the outside surface indicates migration of the cancer to adjacent organs. This study presents a novel method for detecting prostate cancer (PCa) on the surface of excised prostate glands using Raman spectroscopy and stiffness measurements. The workflow involves assessing the location and extent of PCa via MRI before surgery, followed by 3D scanning of the excised prostate. Key positions on ten excised prostates, 211 positions with 56 deemed as cancer, are measured using Raman spectroscopy and stiffness probes. The results are mapped onto a digital representation of the prostate to aid surgical decision-making. Statistical analysis of the Raman data indicates that spectra could be divided into two components, one more related to cancer and one more related to normal tissue. A stiffness parameter was calculated from resonance measurements from the stiffness probe. The Raman components and stiffness parameters were converted to z-scores. Logistic generalized linear mixed modelling revealed that the stiffness parameter was statistically associated with cancer presence in prostate regions (p = 0.009). The scanning equipment is easy to handle and makes further larger studies possible. This method holds promise for providing real-time support during surgery, reducing the need for post-surgical therapies and minimizing patient distress
The role of pressure and steam on pyrolysis of biogenic waste : Value-added commodity products
No full textThe global concerns regarding climate change and the steep increase in greenhouse gas emissions, driving the society to transform biogenic waste into renewable value-added products. Thermal depolymerization of biomass is regarded as the most promising thermochemical conversion technology to produce bio-oil, biochar and syngas. To date, previously published review articles revolve around various biomass pyrolysis aspects, such as the chemistry of biomass, application of pyrolysis products, effects of pyrolysis parameters and kinetics, effect of various catalysts on product yield, upgradation strategies, and process technologies. The commercialization of conventional pyrolysis technology is challenging due to the inferior oil properties (oxygenates nearly 40 wt%), agglomeration, feeding constraints, ash content in the biomass, heat and mass transfer limitations, pressure build-up due to tar formation and thermal distribution across the reactor. Pressurized steam pyrolysis of biomass improves the product quality (oil, char and gas) with a production of value-added chemicals. Despite this, studies regarding the combined effect of steam and pressure on product quality from pyrolysis technology are not available in the literature. This study offers a comprehensive overview of the state-of-the-art on the effect of pressure and steam on biogenic pyrolysis. Additionally, the study also explains how pressure and steam can be utilized to improve the properties of the pyrolysis products. The review examine the fundamentals of biomass conversion, the effect of pressure and steam, with interlaid mechanisms on biomass conversion and challenges with pressurized steam pyrolysis. Finally, the benefits of products in various applications and a conceptual process perspective of pressurized steam pyrolysis are briefly outlined.QC 20251028</p
Vegetation change in dry grasslands in Northeast Germany over two decades : A resurvey
No full textSemi-natural dry grasslands in Central Europe harbor many rare and specialized species and face threats due to altered management practices and environmental change. However, more studies on vegetation change and management effects in dry grasslands are needed, especially with consideration of non-vascular taxa. Here we used a resurvey approach to analyze vegetation change in dry grasslands on loamy and sandy soils (Festuco-Brometea, Trifolio-Geranietea sanguinei and Koelerio-Corynephoretea canescentis) in Brandenburg, Northeastern Germany. We surveyed 157 plots (10m2) at each of two time points, 1993-1997, and 20-25 years later, 2017-2018. We recorded a total of 362 vascular plants and 84 non-vascular taxa. Species richness per plot remained stable across surveys. We detected, on average, 32.2 and 21.9 species per plot in dry grasslands on loamy and sandy soils, respectively, including 3.25 and 4.8 non-vascular taxa and 7.6 and 2.2 endangered species according to the regional Red List. We found evidence for vegetation homogenization and a reduction in Shannon diversity and Shannon evenness in the recent survey, suggesting early signs of biodiversity decline. Analyses of mean ecological indicator values and plant traits, as well as of winner and loser species, revealed that changes in vegetation composition were accompanied by an increase in competitive, mesophytic species and a decline in disturbance-tolerant specialists. We further show that the highest diversity in dry grasslands on loamy soils was associated with intermediate levels of grazing. Our findings highlight the conservation significance of dry grasslands and suggest intermediate grazing pressure as a suitable management strategy
Climate impacts of timber-frame buildings in a life cycle perspective : Implications of static and dynamic modelling approaches for biogenic carbon accounting
No full textThis study explores the climate change effects of building with wood structural frames in a life cycle perspective, with a focus on biogenic carbon. Analyses of a timber-frame building are carried out considering fossil and biogenic carbon flows during the production, construction, use, and end-of-life stages of the building. Both static and dynamic life cycle modelling are used and compared, to understand the implications of different biogenic carbon accounting methods, including a simplified approach and an entire chain approach integrating biogenic carbon flows from forestry, construction, and energy sectors. The findings show significant differences between the modelling approaches. Over a 100-year analysis period, the static modelling with simplified biogenic carbon accounting indicates a building life cycle climate impact of 164 kgCO2e/m2, and is the same when excluding and including biogenic carbon flows. The dynamic modelling with simplified biogenic carbon accounting indicates a life cycle climate impact at year 100 of 199 and 91 kgCO2e/m2 when excluding and including biogenic carbon flows, respectively. The corresponding life cycle climate impact for dynamic modelling with entire chain accounting of biogenic carbon flows is 51 kgCO2e/m2. The production stage dominates the building's life cycle climate impact, with insulation contributing the most. Overall, the dynamic modelling of biogenic carbon flows across the entire chain results in a significantly lower life cycle climate impact for the building. This study underscores the importance of robust accounting for GHG emissions, including biogenic carbon, to optimize the climate impacts of wood-based buildings
Label-free and real-time synchronized monitoring of extracellular matrix proteolysis using quartz crystal microbalance and nanoplasmonic sensing with morphological validation by atomic force microscopy
No full textAim: Understanding the interactions between extracellular matrix (ECM) proteins and proteases is essential for elucidating the mechanisms of ECM remodeling in both health and disease. The integration of real-time, label-free, and surface-sensitive techniques based on distinct physical principles enables detailed characterization of protease activity at the ECM substrate-liquid interface. Based on these kinds of techniques, this study focuses on investigating the dynamic interactions between protein adlayers and proteases, offering new insights into complex ECM remodeling processes. Experiments: The adsorption behavior and resulting adlayer properties of collagen and elastin, used as ECM model substrates, and the proteolytic activity of collagenase and elastase, were studied using synchronized quartz crystal microbalance with dissipation monitoring (QCM-D) and localized surface plasmon resonance (LSPR). Changes in adsorbed mass, viscoelastic properties, and near-surface dielectric environment were monitored via shifts in frequency (Δf), energy dissipation (ΔD), and plasmon resonance peak (∆λ), respectively. Atomic force microscopy (AFM) was employed to validate film morphology and mechanical alterations before and after proteolytic digestion. Findings: While the QCM-D/LSPR signals both detect mass uptake during protein adsorption and mass loss during proteolysis, synchronized measurements, complemented with AFM imaging, reveal more complex responses arising from the differing surface sensitivities of the techniques. Our integrated analysis show substantial differences in adlayer morphology and proteolytic degradation. Collagen forms a vertically heterogeneous adlayer with a dense near-surface layer and a highly viscoelastic outer layer of protruding fibrils (Δf ≈ −100 to −240 Hz, ΔD ≈ 40–70 ppm, and ∆λ ≈ 0.7 nm), whereas elastin adsorbs as a thinner, more rigid film (Δf ≈ −36 to −40 Hz, ΔD ≈ 2–3 ppm, and ∆λ ≈ 0.4 nm). Real-time monitoring reveals that collagenase primarily degrades the protruding collagen fibrils, significantly affecting all QCM-D and LSPR signals—particularly showing a clear overtone dependence in ΔD and Δf shifts—while elastase digestion of elastin occurs without overtone dependence and results in more pronounced changes in Δf and ∆λ, with comparatively low effect on ΔD. Cross-reactivity experiments confirm substrate specificity; however, both proteases show non-specific activity. Inhibition studies demonstrate that QCM-D can detect both true enzymatic inactivity and substrate-inhibitor interactions that mimic inhibition in conventional assays, for example by physically adsorbing to the substrate and thereby shielding it from proteolysis
Food-related sensory activities for children in educational settings : a scoping review
No full textHands-on activities, where children explore food with their senses, are of interest for their potential to promote healthy eating. Various food-related sensory activities (FRSA) have been developed as interventions, but design, delivery and outcome variation challenge a robust evaluation of programs. Some argue that a focus on health is narrow and that FRSA could foster other competences, including non-health dimensions of sustainability. The objective of this scoping review was therefore to examine insights from the scientific literature regarding types, aims, perceived benefits, outcome measures and connections to sustainability of FRSA targeting children in educational settings. PRISMA-ScR was used. Three databases were searched in Spring 2024, resulting in 25 included articles. The FRSA were categorized into two main types and four subtypes. The most common aims, perceived benefits, and outcome measures were related to improving children's healthy eating. It has also been suggested that FRSA might foster critically conscious consumers and socially competent individuals, and support product development. Yet, these aspects were only partially evaluated in the studies reviewed. While environmental dimensions of sustainable eating were recognized, some of the competences related to being critically conscious and socially competent may also be important for sustainable development. Future research may explore FRSA's potential contributions to outcomes other than physical health
Ultrasound-driven formation of defects and radicals in contact-electro-catalysis: a DFT and AIMD investigation
No full textThis study reveals the critical chemical and physical roles of ultrasound in enhancing contact-electro-catalysis (CEC), using the methane (CH4) oxidation process as a model system. By integrating density functional theory (DFT), ab initio molecular dynamics (AIMD), and targeted experiments, we demonstrate for the first time that ultrasonic treatment significantly modifies the solid material’s (i.e. CEC catalyst) surface chemistry and morphology, leading to enhanced catalytic performance. FTIR and Raman spectroscopy analyses reveal distinct molecular-level changes in the tested solid material (i.e. fluorinated ethylene propylene (FEP)) following ultrasonication, specifically the formation of C–H bonds, aligning closely with theoretical spectra predictions. Additionally, ultrasound induces substantial physical alterations, tripling the surface roughness of FEP, and significantly elevating fluoride ion concentrations in the surrounding solution, indicating pronounced C–F bond cleavage. AIMD simulations further elucidate that ultrasound-generated radicals initiate homogenous catalytic pathways by cleaving C–H bonds in CH4, identifying this as a critical mechanistic step previously unclarified. Those induced structural defects in FEP could also simultaneously enhance heterogeneous catalytic activity. Our findings establish a comprehensive mechanistic framework that resolves prior ambiguities in ultrasound-assisted CEC processes, offering robust theoretical and experimental foundations for advancing CEC catalytic efficiency and guiding future CEC catalyst development.Validerad;2025;Nivå 2;2025-11-25 (u5);Full text license: CC BY 4.0;Funder: U.S. National Science Foundation (2422927)</p
Sustainability challenges in the value chains of battery minerals
No full textTo address the climate change issue, a global transition from the current “brown economy” to a “green economy” is imperative. The realization of this worldwide ambition necessitates large-scale electrification which leads to a growing demand for lithium-ion batteries as energy storage technologies. The developing market of batteries requires significant mineral and metal inputs. However, there are diverse challenges, rooted in different stages of a battery value chain, in meeting the escalating demand for battery metals and minerals. These challenges consist of, for example, various uncertainties; the need for building institutional and knowledge capacity; environmental, social, economic, and governance issues; and geopolitical tensions. These challenges can hinder the uninterrupted supply of battery raw materials and propagate through the whole battery value chain affecting all involved stakeholders. This fact reinforces the global concern over how to enhance the resilience of supply for each battery raw material, while upholding sustainable development goals. The aim of this research work is to contribute to the development of the knowledge domains that are considered prerequisites to the supply sustainability of battery minerals and a real green transition. Here, considering the entire value chain of a lithium-ion battery, the approaches adopted by regulatory agencies, governments, mining companies, and vehicle and battery manufacturers are evaluated. The objectives of this evaluation are to discern and categorize gaps and opportunities in the implemented strategies, to identify key criteria for resilient and sustainable battery mineral value chain, and to analyze the roles of various actors in global mineral supply chains during the transition to a green economy. These assessments are accompanied by the analyses of the factors threatening the primary supply of the selected battery raw materials including lithium, cobalt, graphite, and nickel. The purpose of these in-depth analyses is to comprehend the interplay between mine production of each individual battery raw material and a multitude of risks and uncertainties, which is a valuable asset to supply chain management. Moreover, another objective of this work is to predict the future mining production of the selected battery raw materials in twenty years ahead. To achieve this, three time series forecasting techniques namely Seasonal Autoregressive Integrated Moving Average, Holt’s linear trend methods, and Holt-Winters techniques are Utilized. Predicting the future regional and global mining production of battery raw materials provides decision makers with a knowledge platform about the dynamics of supply security in the future. This platform can also help the stakeholders engaged in the different stages of a battery value chain to adopt sound strategies to minimize the probability of demand and supply imbalance in the future