Walking is well known for its societal benefits, including promoting sustainability, health, and environmental well-being. In recent years, urban planners and traffic designers have increased their focus on creating pedestrian-friendly zones. The 15-minute city concept, which gained recognition in recent years, emphasizes proximity, aiming to keep daily amenities close to residents to reduce travel time and encourage walking and cycling as modes of transport. This literature review, using an abductive qualitative approach, examines how the factors influencing planning for walking are addressed within the 15-minute city concept. The goal is to compile the state of knowledge and identify critical issues and priorities in the field of walking as a mode of transport. The findings are predominantly from China and Italy, and indicate a global concern about urban centres’ accessibility within the 15-minute city concept and highlight that walking is a multidisciplinary topic. However, the review reveals under-researched areas such as individual factors, smaller settlements, and lack of standardized methods. This stresses the need for further research to encourage walking and its multiple benefits.

The c. 1.89 Ga Garpenberg Zn-Pb-Ag-(Cu-Au) deposit is hosted by dolomite marble, skarn and felsic metavolcanic rocks. Extensive marble units host part of the mine infrastructure, including sections of bright-colored, chemically pure marble. Assessing the potential of carbonates as by-products to base metal mining is of interest for a sustainable and efficient use of resources and for securing a domestic supply of carbonates. This study characterizes marble units proximal to the Dammsjön and Lappberget ore bodies at Garpenberg based on their optical, chemical, mineralogical, and textural properties to delineate controls on their brightness, color, and purity. Methods employed include drill core logging, whole-rock lithogeochemistry, petrography, SEM-EDS, μXRF, spectrophotometric brightness measurements, and tests of AIR and magnetic separation. The marble units are divided into bright calcite marble (white, gray, and green varieties), dark calcite marble (salmon pink, spotted, brecciated, and ophicalcite varieties) and dolomite marble. Brightness and purity of the marbles are highly correlated, with Fe having a particularly detrimental effect on brightness, both via substitution in the dolomite and calcite lattices, but also via presence of accessory minerals that grind to dark powders. Ore-proximal dolomite marble shows a hydrothermal signature, with elevated base metals, Fe, S and Mn content, whereas impurities in calcite marble seem to mainly be of detrital origin, reflecting co-settled volcaniclastic and siliciclastic material in the limestone precursors. Mainly the bright calcite marble varieties are of potential industrial quality and are present in Garpenberg in significant volumes, but the technoeconomic feasibility of by-product valorization requires further analysis.

Lifelong learning can be indispensable for the adaptation to continuously evolving labor markets and societal demands. In the current study, we examined psychological factors, notably aspects of personality (personality traits in the five-factor model and trait curiosity), self-reflection and motivation in relation to attitudes to lifelong learning. A specific aim was to examine the relative importance of these factors in their contribution to attitudes to lifelong learning. The study was carried out by use of a digital survey and included 717 adults (Mage = 47.93) within working life. The results showed that self-reflection and trait curiosity were the strongest predictors of attitudes to lifelong learning but work intrinsic motivation and openness to experience (a personality trait in the five-factor model) also contributed with unique explanatory power, although to a lesser degree. The results can inform individualized accessibility strategies for lifelong learning.

Improving the accuracy of reference evapotranspiration (RET) estimation is essential for effective water resource management, irrigation planning, and climate change assessments in agricultural systems. The FAO-56 Penman-Monteith (PM-FAO56) model, a widely endorsed approach for RET estimation, often encounters limitations due to the lack of complete meteorological data. This study evaluates the performance of eight empirical models and four machine learning (ML) models, along with their hybrid counterparts, in estimating daily RET within the Gharb and Loukkos irrigated perimeters in Morocco. The ML models examined include Random Forest (RF), M5 Pruned (M5P), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), with hybrid combinations of RF-M5P, RF-XGBoost, RF-LightGBM, and XGBoost-LightGBM. Six input combinations were created, utilizing Tmax, Tmin, RHmean, Rs, and U2, with the PM-FAO56 model serving as the benchmark. Model performance was assessed using four statistical indicators: Kling-Gupta efficiency index (KGE), coefficient of determination (R2), mean squared error (RMSE), and relative root squared error (RRSE). Results indicate that the Valiantzas 2013 (VAL2013b) model outperformed other empirical models across all stations, achieving high KGE and R2 values (0.95–0.97) and low RMSE (0.32–0.35 mm/day) and RRSE (8.14–10.30%). The XGBoost-LightGBM and RF-LightGBM hybrid models exhibited the highest accuracy (average RMSE of 0.015–0.097 mm/day), underscoring the potential of hybrid ML models for RET estimation in subhumid and semi-arid regions, thereby enhancing water resource management and irrigation scheduling.

While vegetable uptake of traditional metal contaminants is a well-studied pathway to human exposure and risk, a paucity of information exists on the uptake of emerging metal contaminants. This study evaluated the uptake of the Technology-critical elements (TCEs) gallium (Ga), germanium (Ge), niobium (Nb), tantalum (Ta), thallium (Tl), and rare earth elements (REEs) into lettuce cultivated in 21 European urban soils. For comparison, the uptake of cadmium (Cd) was also analysed. First, the uptake was predicted by multiplying soil concentrations with previously established bioconcentration factors (BCFs). Subsequently, multiple regression models incorporating geochemical variables as predictors were used to determine whether prediction accuracy could be improved. A "3-predictor model" incorporated soil TCE concentration, pH, and organic matter (OM), and a "7-predictor model" added data on clay content and the soil concentrations of Fe, Al, and Mn as well. With the exception of Cd, Ge, and Tl, the BCF approach provided unsatisfactory predictions (R2 < 0.5), while the 7-predictor models yielded the best predictions, even when accounting for the greater number of predictors. While the most important predictors of uptake varied somewhat between the TCEs, the concentrations of TCEs in the soil generally explained the largest proportion of the variation. The least influential predictors in our dataset were [Mnsoil], [Fesoil], and soil OM. Incorporating geochemical data generally improved the predictions of uptake by lettuce, and these findings underscore the need for more detailed characterisations of the uptake potential of TCEs by food plants and subsequent consequences for human health.

An extensive plasticity model base useful to predict stresses in thermo-mechanical processes where the microstructure changes has been established. The densities of mobile and immobile dislocations are the basic ingredients in the model. The motion of the former corresponds to plastic strain rate. The interaction between moving dislocations and various obstacles contributes to the material resistance. The focus is on the developed recrystallization model that is based on dislocation densities. The results show that recrystallization at high strain rates leads to a large number of nuclei that grow after the test. This means that most of the recrystallization occurs after the test

Background: Alzheimer’s disease (AD) leads to severe cognitive impairment and functional decline in patients, and its exact cause remains unknown. Early diagnosis of AD is imperative to enable timely interventions that can slow the progression of the disease. This research tackles the complexity and uncertainty of AD by employing a multimodal approach that integrates medical imaging and demographic data. Methods: To scale this system to larger environments, such as hospital settings, and to ensure the sustainability, security, and privacy of sensitive data, this research employs both deep learning and federated learning frameworks. MRI images are pre-processed and fed into a convolutional neural network (CNN), which generates a prediction file. This prediction file is then combined with demographic data and distributed among clients for local training. Training is conducted both locally and globally using a belief rule base (BRB), which effectively integrates various data sources into a comprehensive diagnostic model. Results: The aggregated data values from local training are collected on a central server. Various aggregation methods are evaluated to assess the performance of the federated learning model, with results indicating that FedAvg outperforms other methods, achieving a global accuracy of 99.9%. Conclusions: The BRB effectively manages the uncertainty associated with AD data, providing a robust framework for integrating and analyzing diverse information. This research not only advances AD diagnostics by integrating multimodal data but also underscores the potential of federated learning for scalable, privacy-preserving healthcare solutions.

Research regarding the geochemistry of beryllium (Be) in terrestrial environments is hindered by its high toxicity to humans and the low concentrations normally occurring in the environment. Although Be is considered an immobile element, extremely high dissolved concentrations have been detected in groundwater in the legacy Tailings Storage Facility (TSF) of Smaltjärnen, Sweden. Therefore, a detailed study was conducted to determine physiochemical parameters affecting the speciation of Be in the groundwater. Groundwater was sampled from 2016 to 2024 and filtered through 0.2 μm filters, whereas truly dissolved fraction (<1 kDa) samples were collected with dialysis membrane tubes in situ at groundwater wells. Secondary minerals on the tailings shore were studied by mineralogical methods and sequential extraction to trace the pathway whereby Be entered the downstream surface water. In part of the tailings, dissolved Be was detected in very high concentrations (average: 4.8 mg/L) in suboxic groundwater with pH from 6.0 to 6.4. Dialysis sampling in 2024 showed that more than 90% occurred as truly dissolved Be (<1 kDa). A significant correlation between Be and S was found, suggesting that sulfate complexes kept Be mobile in these pH conditions. Dissolved Be increased with decreased pH, and there is risk that the concentrations will increase further since sulfide oxidation with subsequent decrease in pH will continue for 100 of years in the TSF. In another part of the TSF, the pH was >6.4 and dissolved Be was below the detection limit, possibly due to formation of Al(OH)3 (>0.2 μm) together with F and Zn. Secondary minerals on the shore of the tailings functioned as a temporary chemical barrier, scavenging Be primarily by secondary gypsum when present and otherwise by Fe-(hydr)oxides.

Understanding of carbon nanomaterials oxidation is useful in many different applications, e.g., for soot emission abatement, or in defect engineering aiming to improve material properties. In this work, the oxidative behavior of three substantially different qualities of carbon black, multiwall carbon-nanotubes, and few-layer graphene, was studied using a combination of macroscale quantification (using thermogravimetric analysis) and nanoscale imaging of their structural evolution (using environmental transmission electron microscopy, ETEM). The materials were investigated both with and without the addition of a nanoparticulate iron oxide catalyst. Catalyst addition clearly lowered the conversion temperature during oxidation. The ETEM revealed that the catalyst nanoparticles induced primary surface damages in the carbon nanostructure at relatively low temperatures. From there, oxidation could proceed more rapidly at recently exposed edge sites due to their higher propensity for oxidation. Thus, the enhanced oxidation was not solely linked to the interface between catalyst and carbon.

Depression is one of the most common psychiatric conditions. Given its high prevalence and disease burden, accurate diagnostic procedures and valid instruments are warranted to identify those in need of treatment. The Patient Health Questionnaire-9 (PHQ-9) is one of the most widely used self-report measures of depression, and its validity and reliability has been evaluated in several languages. However, the Swedish translation has yet not been subject to psychometric evaluation, and no previous psychometric evaluation of the instrument have used both Rasch analysis and classic test theory. The aim of this study was to investigate validity and reliability of the PHQ-9 in a Swedish sample of individuals with self-reported current or past mental health problems using Rasch analysis and confirmatory factor analysis. A sample of 4958 participants was recruited from an online survey covering different aspects of covid-19 and mental health targeted towards individuals with mental health problems. Results showed that a one-factor solution fit the data after removing one item and that some items had a different response pattern for older respondents. Furthermore, after removing item 2 and merging the two middle response categories for item 9, the Swedish translation of PHQ-9 showed adequate psychometric properties. The findings suggests that the Swedish translation of PHQ-9 may need to be adapted in order to make adequate interpretations of an individual score and to differentiate between populations. Further tests of its validity and reliability in other Swedish samples are needed to fully understand the properties of the Swedish version of PHQ-9. 

Shallow waterways such as rapids, tributaries and smaller streams can have important ecological functions in both free-flowing and regulated rivers. As more intermittent renewable energy is introduced to the energy system to reduce CO2 emissions, the operational conditions of hydropower plants are changing. This implies various flow scenarios that can lead to more locations with shallow depths and larger variations in water levels and velocities, resulting in increased impact on the riverine ecosystem. Accurate predictions of these impacts require an understanding of the flow dynamics near large roughness elements such as boulders or trees in shallow river regions. This study uniquely investigates the effect of relative submergence, i.e., water depth relative to boulder size, on the flow field, turbulence, and potential fish habitats around idealized stone shapes (hemispheres) in shallow open channel flow using time-resolved 3D particle tracking velocimetry. The results indicate that varying relative submergence significantly affects recirculation zones, velocity and vorticity distribution, as well as turbulent kinetic energy. Notably, larger regions of lower velocity downstream of the roughness elements were generated at lower submergences, which might be favorable for fish energy conservation. Valuable insights into ecohydraulic engineering and habitat restoration in shallow waterways can be gained by understanding the fundamental flow mechanisms at low submergence for the flow around large roughness elements.

This paper investigates the current landscape of multiscale studies in concrete composites incorporating molecular dynamics (MD) methods. Through a thorough literature analysis, it was determined that finite element, discrete element, homogenization, microphysical characterization, and machine learning methods are better suited for integration with MD in multiscale studies of concrete composites. The paper delves into MD's application characteristics and the selection of force fields in multiscale studies and provides a summary of the combined applications between MD and various methods. Challenges identified include the optimization of MD simulations and the appropriate selection of combined methods. The conclusions underscore the growing recognition of MD's significance, advocating for rational multi-method integration in multiscale approaches to effectively advance research on concrete composites.

Syftet med denna delrapport är att dels beskriva byggprocessens mest centrala delar, dels beskriva platschefernas arbetssituation i bygg- och anläggningsindustrin.

Den första delen av delrapporten redovisar byggprocessens generella delar utifrån den beskrivning som görs av denna i Hansson, m.fl. bok ”Byggledning Produktion” (2021). Den andra delen där två platschefers arbetssituation redovisas bygger på två intervjuer med en platschef från ett byggprojekt och en platschef från ett anläggningsprojekt. Resultaten visar att platscheferna uppvisar ett stort intresse för sina respektive arbeten men att det samtidigt ställs höga krav på dem som individer i fråga om arbetsprestation och till viss del arbetstid och tillgänglighet.

Syftet med litteraturstudien är att undersöka organisatoriska och sociala faktorer som påverkar arbetsmiljön för produktionsnära chefer och tjänstepersoner i den internationella bygg- och anläggningsindustrin.

Resultaten visar att även om många studier fokuserar på individers upplevda psykosociala arbetsmiljö finns problemen och möjligheterna att hitta i termer av handlingsutrymme, krav, resurser och stöd, det vill säga i den organisatoriska och sociala arbetsmiljön. Litteraturen kan delas in i tre övrgripande teman: copingsstrategier för stress, utbrändhet, och balans mellan arbete och privatliv. Forskningen om copingstrategier visar att organisatoriska förutsättningar i form av feedback och resurstilldelning för beslutstagande är viktigt för individers hantering av stressrelaterade problem. Studier om utbrändhet eller utmattningssyndrom som det numera benämns i svensk kontext pekar på att handlingsutrymme är en viktig faktor för att inte drabbas av utmattning. Slutligen, studier om balansen mellan arbete och privatliv visar på att organisatoriska omständigheter spelar en stor roll för att hitta just en balans, exempelvis genom att införa rutiner för hur tillgänglig en chef ska vara utanför normal arbetstid och se över chefers arbetstid så att det inte blir frågan om övertidsarbete under långa perioder.

En slutsats som kan dras är att arbetsgivare behöver ta hänsyn till den sammantagna bilden av kraven för dessa grupper då deras omständigheter kan kräva särskilda insatser i arbetsmiljöarbetet.

The detailed ash transformation process during the combustion of agricultural biomass containing moderate to high amounts of P was studied in entrained flow conditions. The selected fuels were grass and brewer’s spent grain (BSG) containing a moderate and high amount of P in the fuel, respectively. The experiments were conducted in a lab-scale drop tube furnace at 1200 and 1450 °C. The residual chars, ashes, and particulate matter (PM) were collected and analyzed by scanning electron microscopy-energy-dispersive X-ray spectroscopy (SEM-EDS), X-ray diffraction (XRD), inductively coupled plasma atomic emission spectroscopy (ICP-AES) and ion chromatography (IC), and CHN-analysis. Additionally, the obtained results were interpreted through thermodynamic equilibrium calculations (TECs). For both fuels, P was primarily identified in the residual coarse ash (>1 μm) fractions. In contrast, a minor to moderate amount of fuel inherent P was detected in the fine particulate (<1 μm) fraction at 1200 and 1450 °C, respectively. For grass, the retained P in the residual coarse ash fractions was mainly identified as amorphous K–Ca–Mg-rich phosphosilicate melt. These phosphosilicates were most likely formed through the initial formation of molten K-rich silicates, with subsequent incorporation of Ca, P, and Mg. For BSG, a P–Si-rich fuel with moderate to minor amounts of Ca, Mg, and K, most P was retained in a Ca–Mg-rich phosphosilicate melt, likely originating from phytate-derived Ca–Mg phosphates interacting with fuel-inherent Si-rich particles. The results obtained from this study could be used to address the ash-related challenges and potential P-recovery routes during pulverized fuel combustion of P-containing biomass.

Background: Physical activity (PA) after stroke has significant health benefits if it is conducted regularly, with sufficient intensity and duration. Because of the health benefits, it is important to identify those below the World Health Organization (WHO) recommended level of PA. However, few studies have assessed the level of PA after stroke in relation to the WHO recommendations and which sociodemographic factors and stroke characteristics are associated with those below the WHO recommendations.

Objective: To assess survivors of stroke at least 1 year after onset and (1) describe their self-reported level of PA; (2) explore the association between PA, sociodemographics, and stroke characteristics, and (3) determine the characteristics of those below the WHO recommended level of PA.

Design: Cross-sectional descriptive survey.

Setting: Community settings.

Participants: Data were collected from 160 survivors of stroke (mean age 73 years, 46% women, mean time since stroke onset 35 months).

Interventions: Not applicable.

Main outcome measures: The Swedish National Board of Health and Welfare Physical Activity Questionnaire and the following sociodemographics and stroke characteristics: gender, age, marital status, vocational situation, need for home help, use of mobility devices, time since stroke onset, first-time stroke, type of stroke, location of stroke, and stroke treatment.

Results: Two thirds (66.3%) of the participants were below the WHO recommendations. The hierarchical regression analysis explained 13% of the variance in PA with need for home help as a single significant contributor. Those who did not meet the WHO recommendations were significantly older, more likely to live alone, and in need of home help and mobility devices.

Conclusions: A majority of survivors of stroke do not meet the WHO recommended level of PA. Future studies should assess how other factors characterize those who are physically inactive. This knowledge could help rehabilitation professionals to target interventions and self-management programs to promote PA among survivors of stroke.

Digitalization drives societal transformation to reform existing practices in the evolving environment. Central to this transformation is the creation of interoperable digital public services across diverse organizations, increasingly guided by human-centric principles and life-event orientation. This paper explores the complex process of achieving digital service innovation, emphasizing the need for inter-organizational balancing between radical transformation and efficiency through collective ambidexterity, where multiple ecosystem actors coordinate to balance innovation and efficiency simultaneously. While previous research predominantly studied ambidexterity at the organizational level, focusing on its antecedents, mechanisms, and outcomes, our study extends this inquiry to the broader ecosystem. Via a single-case study, we investigate how collective ambidexterity can be governed in a large-scale digital service ecosystem. To address the research question, we developed a multi-level conceptual model of governing mechanisms, antecedents, and outcomes of collective ambidexterity across three analytical levels: the ecosystem, organization group, and organization. Our theoretical contribution is twofold. First, we enhance conceptual clarity on collective ambidexterity and show how Modes of Collaboration (MoC) can facilitate innovation and efficiency of human-centric digital services throughout the three levels of governance. Second, the resulting governance model emphasizes the need to connect centralized, decentralized, and group-level governance strategies for developing digital services—to achieve and govern collective ambidexterity in the development of digital services in the public sector.

Sensorimotor difficulties are common in children with autism spectrum disorder, and it has been suggested that motor planning problems underlie their atypical movements. At early school-age, motor planning development typically involves changes in visuomotor integration, a function known to be affected in autism spectrum disorder. However, there is a lack of detailed characterization of typical motor planning development during this stage, and how motor planning develops in children with autism spectrum disorder is largely unknown. This longitudinal kinematic study examined goal-directed sequential manual movements in children with autism spectrum disorder and in typically developing children across ages 7, 8, and 9 years. We manipulated goal-difficulty and availability of initial visual information to investigate visuomotor integration and chaining of subparts during movement performance. The results revealed emerging group differences at older age, suggesting atypical motor planning development in children with autism spectrum disorder. Notably, unlike the typically developing group, availability of initial visual information did not facilitate motor planning for the autism spectrum disorder group. The results show that motor planning differences in autism spectrum disorder appear related to atypical visuomotor integration and global processing of sensorimotor information. The findings also emphasize the importance of considering developmental aspects in research and practice related to motor problems in children with autism spectrum disorder.

Using Sweden as a study case, this article explores the polarized opinions to wind and nuclear energy, two low carbon energy options that have been shown to be politically controversial. In a wide-scale survey (N = 5200), general attitudes to wind and nuclear energy are captured, as well as to projects in the proximity of people's homes. The study demonstrates a deep polarization of energy preferences in Sweden, finding strong associations between worldviews, political orientation, environmental concern, and support for or resistance to wind and nuclear energy. The study concludes that support for both energy options is reduced when wind or nuclear power is constructed near people's home, but also suggests that the proximity effect is particularly strong for individuals with strong TAN (traditional, authoritarian, nationalistic) values and right leaning political ideology. The article argues that politically motivated reasoning might explain the polarization of attitudes, yet this effect seems to become less relevant when people are asked to judge potential energy infrastructure located close them.

Den urbana utvecklingen har resulterat i alltmer hårdgjorda ytor och förekomst av konstruerat material i städer, och som följd finns det en stor variation av material som kan bidra till föroreningar till kringliggande miljöer. Dagvatten, såsom regn och smältvatten, har visat sig vara en bidragande faktor till att föroreningar sprids inom urbana områden. Kemikalierna per- och polyfluorerade alkylsubstanser (PFAS) har under det senaste årtiondet hamnat mer i fokus då det framkommit att de är toxiska och svårnedbrytbara i miljön. Trots att dagvatten kan vara en faktor som påverkar spridning av PFAS i urbana områden är det ett forskningsområde med få studier. Denna rapport syftar därför till att öka kunskapen om förekomst av PFAS i dagvattensystem i urbana områden, utifrån ett svenskt perspektiv. 47 prover tagna i dagvattensystem från fyra urbana områden i Östersund under år 2012–2013, analyserades med avseende på 55 olika PFAS-ämnen inklusive beräkningar för summaparametrarna ∑PFAS55 ∑PFAS4, och ∑PFAS24. Proverna bestod av dagvatten från regn och smältvatten samt vissa basflöden tagna i dagvattenledningar. Resultaten visar att i 45 av de 47 proverna förekom minst en av de analyserade PFAS-ämnena. Främst förekommande var PFOS, PFOA, PFNA, 6:2FTS samt PFHpA. Det mest heterogena urbana området, innefattande stora delar av centrala staden och campusområde, hade högst halter av ∑PFAS55 med en median på 144 ng/l i jämförelse med de andra områdena med mediankoncentrationer på 12,6–20,6 ng/l i dagvatten och 4,4–15,1 i basflöden. Resultaten indikerar att PFAS förekommer i urbana dagvattensystem samt att det finns många faktorer i urbana miljöer som bidrar till källor samt spridning av PFAS. 

The reuse and recycling of timber are crucial for a circular economy, but barriers like insufficient information and concerns about material quality hinder their industrial-scale implementation. Uncertainty about mechanical properties often leads to downcycling and CO2 release. Circular practices involve cascading reuse of timber, but downcycling occurs at each step, leading to waste. To maintain carbon storage, reclaimed timber should be used with maximum integrity, like in load-bearing beams. Non-destructive assessment methods for reclaimed timber face challenges due to variations in origin, age, and wear conditions. X-ray computed tomography (CT) scanning in conjunction with computational mechanics provides a means to structurally assess wood based on its internal density distribution. In this paper, a modelling pipeline is proposed using CT-based finite element analysis to assess the quality of reclaimed timber elements. The pipeline is part of an ongoing investigation where timber stiffness and strength are evaluated both destructively and non-destructively using various measurement modalities. Accurate non-destructive assessment of the mechanical properties of reclaimed timber could optimize its use and enable repeated reuse. In subsequent research, the pipeline will be validated and simplified to aim for practical application. 

Entropy-stabilized Ultra High-Temperature Ceramics (UHTC) offer a groundbreaking solution to the challenges of extreme environments, showcasing enhanced mechanical properties, thermal stability, and resistance to oxidation at high temperatures. The consolidation of UHTC by ultra-fast high-temperature sintering (UHS) significantly reduces processing times and temperature and can produce dense high-performance ceramics with superior mechanical properties. This study reports the pressureless synthesis and consolidation of the entropy-stabilized (Hf0.25Zr0.25Ti0.25V0.25)B2-B4C composite through UHS within 1 minute, starting from transition metal diboride powders. B4C acts as an effective sintering aid, promoting the densification of the system and the formation of a nearly single-phase hexagonal diboride with a diboride-eutectic phase. Furthermore, a secondary minor hexagonal phase rich in V and Zr is formed close to the eutectic regions. Sintering currents of 40 A were necessary to reach densities higher than 90 % under pressureless conditions, achieving nano hardness higher than 27.3 GPa, comparable with high-entropy diborides produced by Spark Plasma Sintering. The study highlights the entropy-stabilized phase formation, diffusion, densification, and grain growth mechanisms involved during UHS. The work contributes to the understanding of entropy-stabilized ceramics produced by UHS as a faster and less energy-consuming process than conventional sintering methods.

Global warming is caused by anthropogenic carbon dioxide (CO2) emissions in the atmosphere, and different options have been proposed to mitigate CO2 emissions, where CO2 separation plays an important role. To develop cost-effective technologies for CO2 separation, immobilizing ionic liquids (ILs) into porous materials demonstrates potential. Different ILs are strategically immobilized into different porous materials like MOFs, activated carbons, pops, and silica, resulting in IL-porous composites with the functional properties of the pristine porous materials and the peculiar physicochemical of the immobilized ILs. These progressive developments reveal novel opportunities in separation science.In this review, we discuss the functionalization of ILs for CO2 separation. We also highlight several porous materials, such as MOFs, carbon nanotubes, zeolites, carbonaceous materials, and graphene. Finally, we demonstrate the development of hybrid ionic materials composed of ILs and porous materials, especially MOFs, to provide a perspective on the potential of ILs/porous material composites for CO2 separation. The most significant opportunities and challenges in ILs/porous materials as well as their synthesis methods, characterization techniques, applications, and future possibilities are thoroughly explored to develop a roadmap for CO2 separation. Considering future developments in this field, the design and development of these innovative hybrid materials and their potential to replace conventional materials are also carefully evaluated.

Over the years, fretting has been a leading cause of fuel failures for water cooled nuclear reactors. Implementation of liquid lead coolant increases the need for fretting and corrosion-resistant materials. Fe–10Cr–4Al alloy has shown good resistance to thermal aging, oxidation, liquid metal corrosion, and embrittlement in liquid lead environment. The performance of Fe-10Cr-4Al under fretting wear conditions has not been studied previously. This work aims to investigate the fretting wear and friction behaviour of self-mated Fe-10Cr-4Al alloy at varying temperatures, in the presence of a reducing gas environment and liquid lead. The results show that an increase in test temperature from RT to 550 °C decreases the coefficient of friction and promotes the formation of Cr and Fe oxide third body layer. At high temperature in reducing gas atmosphere, the initial plastic deformation and severe adhesion leads to early seizure. Presence of liquid lead has a lubricating effect and allows a third body layer to form on worn surfaces. A detailed description of the initial wear mechanisms of Fe-10Cr-4Al alloy and friction levels under various conditions provides a base for further investigation of this alloy for long-duration fretting wear.

Electron microscopy (EM) is a key tool for studying the microstructure of wood; however, observing uncoated samples poses a challenge due to surface charging. This study aims to identify the critical voltage that allows for the effective observation of uncoated wood samples without significant loading. As part of the experiment, samples of different wood species were tested, including Acacia (Robinia pseudoacacia L.), Oak (Quercus robur L.), Maple (Acer pseudoplatanus spp.), Ash (Fraxinus excelsior L.), Spruce (Picea abies (L.) Karst.), Thermowood (Thermal modifed Spruce), Garapa (Apuleia leiocarpa), Ipé (Handroanthus spp.), Merbau (Intsia bijuga), and Massaranduba (Manilkara spp.). Several methods were tested for surface preparation for SEM analysis, including the use of a circular saw, a hand milling machine, and a microtome. The results show that the optimal voltage for observing uncoated wood samples varied depending on the wood species. Regarding the selection of wood species and the results obtained, it was found that uncoated samples could be effectively observed. This finding suggests that practical observations can be accelerated and more cost-effective, as all wood species exhibited the required voltage range of 1 kV to 1.6 kV. Additionally, it was determined that using a secondary electron detector was optimal for such observations, as it provided a sufficiently strong signal even at relatively low voltages. Conversely, when using a backscattered electron detector, it was more beneficial to use coated samples to achieve a sufficient signal at higher voltages. This study brings new knowledge that will facilitate further research and applications of electron microscopy in the study of other wood species or wood-based materials.

Per- and polyfluoroalkyl substances (PFAS) are extensively used in urban environments and are, thus, found in urban stormwater. However, the relevance of stormwater as a pathway for PFAS to urban streams is largely unknown. This study evaluated the impact of urban stormwater runoff on PFAS concentrations and spatial distribution in three urban streams affected by stormwater discharges from separate sewer systems. River water was sampled during dry (DW) and wet weather (WW) upstream, immediately downstream, and further downstream of three urbanized areas with separate sewer systems and with and without point sources (i.e. waste water treatment plant, airports). Water samples were analyzed for 34 targeted PFAS compounds and sediment samples for 35 targeted PFAS and 30 PFAS compounds using a total oxidizable precursor assay. The sum of the quantified PFAS concentrations ranged from the reporting limit (RL) to 84.7 ng/L during DW and increased as the streams were affected by WW discharges (0.87 to 102.3 ng/L). The highest PFAS concentrations were found downstream of urban areas and/or point sources (i.e. airports) during WW, indicating a clear contribution from stormwater discharges. A consistent PFAS contribution from the WWTP was observed under both DW and WW conditions. During WW events, concentrations of perfluorooctanesulfonic acid (PFOS) and total PFAS (PFOA equivalents) exceeded the annual average environmental quality standards, which are an established limit of 0.65 ng/L for PFOS and a proposed limit of 4.4 ng/L for total PFAS. Notably, except for the legacy PFAS, PFOS and perfluorooctanoic acid (PFOA), the most frequently quantified PFAS during DW were short-chain. For WW, long-chain perfluorocarboxylic acids (PFCAs) and a precursor, 6:2 Fluorotelomer sulfonic acid (6:2 FTS), were more frequently quantified, suggesting stormwater is a source of these longer-chain and particle-associated PFAS. The detection of unregulated fluorotelomer sulfonates (FTSs) such as 6:2 and 8:2 FTS during WW suggests a need for regulatory action, as these compounds can degrade into more stable PFAS. In sediment, higher concentrations, and a greater variety of PFAS were found at sites with known point sources i.e. airports. Long-chain PFCAs (C7–C13), perfluoroalkyl sulfonates (PFSAs) (C6), and precursors (i.e. N-Ethyl perfluorooctane sulfonamidoacetic acid), were more prevalent in sediments than in the water. Notably, PFOS concentrations in sediment exceeded the lowest Predicted No-Effect Concentration (PNEC) across sites, posing a potential long-term environmental risk, though current PNECs for other PFAS may underestimate such risks. The findings of the study highlight urban stormwater as a source of PFAS to urban streams indicating the need to minimize PFAS sources in the urban environment and to effectively treat stormwater to protect receiving water bodies.

Recent advances in the tribology of polymer composites in water-lubricated conditions have focused on achieving a synergistic effect by incorporating multiple fillers into the polymer matrix. This approach requires a comprehensive understanding of how each filler interacts with the other components, something that remains unknown for hard fillers. This study investigates the tribological performance and tribological mechanisms of a hard filler, nano-titanium dioxide, in a short-carbon-fibre-reinforced, ultra-high-molecular-weight-polyethylene (UHMWPE) composite when combined with microfillers that include graphite, hexagonal boron nitride and silicon dioxide. The results reveal that, while composites with nano-titanium dioxide and microfillers improve the friction by 30–53 % compared to basic fibre-reinforced UHMWPE, the nano-titanium dioxide reduced the friction only with boron nitride and silicon dioxide. In these cases, the nano-titanium dioxide contributes to transferred material onto the steel surface where it embeds in a relatively softer layer of material composed of other components transferred from the composite and thereby reduces the friction. In contrast, all the composites have lower wear rates than the basic carbon-fibre-reinforced composite. We present how the nano-titanium dioxide interacts synergistically with all the microfillers, with each filler contributing in its own way to improving the load-bearing capacity and hindering the fibre pullout. Surprisingly, the combination with the graphite microfiller did not reduce the friction, but had the lowest wear rate in this study of 5–8 × 10⁻8 mm³ /Nm. The impact of the contact pressure on the fillers’ interactions and the tribological performance is also highlighted in this study.

The Late Cretaceous obduction of the Semail Ophiolite onto the rifted passive Arabian margin and the Cenozoic collisional tectonics with the final closure of the Neo-Tethys Ocean, are major contributors to the present-day crustal architecture of the northern United Arab Emirates (UAE). We acquired the first 3D grid magnetotelluric observations from 73 stations in the northern UAE in order to image deep crustal electrical structures associated with the two significant compressional episodes. Inversion of the broadband magnetotelluric data reveals the subsurface geometry of the high-resistivity ophiolite blocks, the underlying conductive thrust sheet (Haybi-Hawasina nappe), a “wedge-shaped” conductive foreland basin flanking the Hajar mountain ranges, and at depth, a high-resistivity structure associated with a fold-thrust belt adjacent to the allochthonous units, or Proterozoic crystalline basement. The ophiolite along the eastern coast (from cities Khor Fakkan to Fujairah) is more than 20 km thick and dips eastward. Across the Wadi Ham fault, the resistive ophiolite lies against less resistive materials that may represent Bani Hamid metamorphic rocks. The thin-skinned thrust sheets of the proximal-distal Tethyan sedimentary units (Haybi-Hawasina complexes) exhibit low resistivity in the Dibba zone. In contrast to its gently east-dipping geometry in the Dibba zone, the conductive Haybi-Hawasina structure in the southern portion of the study area appears nearly vertically (>20 km) beneath the dense Khor Fakkan and Aswad ophiolite blocks. This result suggests extensive deformation of the thrust sheets beneath the southerly dense ophiolite blocks.

Al/Cu bimetal components (BMCs) possess higher thermal conductivity, better wear resistance and corrosion resistance than Al and Al alloys. It is a big challenging task to fabricate a high-performance Al/Cu BMC by a conventional infrared (IR) laser-directed energy deposition (L-DED) process due to the crack formation and high IR laser reflectivity. A novel high-speed L-DED process was proposed to successfully fabricate a crack-free Al/Cu BMC by controlling the residual stress distribution and brittle intermetallic compounds (IMCs) formation. The damaging effect of the reflective IR laser rays on the laser equipment can also be suppressed. Compared with the Al base metal, the microhardness, wear and electrochemical corrosion performances of the Al/Cu BMC were significantly improved. The residual stress distribution was predicted and measured. The IMC formation mechanism was revealed based on element distributions, the formation energy and the effective heat of formation of each IMC. The study would provide the basis for manufacturing crack-free and high-performance multi-material components in many applications in different industries.

Despite the increasing sophistication of autonomous vehicles (AVs) and promises of increased safety, accidents will occur. These will corrode public trust and negatively impact user acceptance, adoption and continued use. It is imperative to explore methods that can potentially reduce this impact. The aim of the current paper is to investigate the efficacy of informational assistants (IAs) varying by anthropomorphism (humanoid robot vs. no robot) and dialogue style (conversational vs. informational) on trust in and blame on a highly autonomous vehicle in the event of an accident. The accident scenario involved a pedestrian violating the Highway Code by stepping out in front of a parked bus and the AV not being able to stop in time during an overtake manoeuvre. The humanoid (Nao) robot IA did not improve trust (across three measures) or reduce blame on the AV in Experiment 1, although communicated intentions and actions were perceived by some as being assertive and risky. Reducing assertiveness in Experiment 2 resulted in higher trust (on one measure) in the robot condition, especially with the conversational dialogue style. However, there were again no effects on blame. In Experiment 3, participants had multiple experiences of the AV negotiating parked buses without negative outcomes. Trust significantly increased across each event, although it plummeted following the accident with no differences due to anthropomorphism or dialogue style. The perceived capabilities of the AV and IA before the critical accident event may have had a counterintuitive effect. Overall, evidence was found for a few benefits and many pitfalls of anthropomorphising an AV with a humanoid robot IA in the event of an accident situation.

This study evaluated the tribological performance of a glycerol-based hydraulic fluid as a green alternative to conventional mineral-based hydraulic lubricants under low-temperature conditions, down to −20 °C. The performance of the glycerol hydraulic fluid (GHF) was compared against that of a mineral hydraulic fluid (MHF) using an SRV tribometer for steel-to-steel sliding contact under boundary lubrication conditions. Comparisons were also made at a moderate temperature to assess the fluids’ performance across different thermal conditions. The results show that the GHF demonstrated up to 55% lower friction coefficients under various test conditions than the MHF. With wear volumes up to 90% lower, the GHF produced thinner and less intense wear scars on the test discs compared to the deeper and more pronounced scars observed with the MHF. We conducted rheological tests which also revealed the green fluid’s stable viscosity transition with temperature changes and its Newtonian behaviour under the measured shear conditions, which may indicate its ability to maintain consistent lubrication.

Current advances and trends in the fields of mechanical, material, and software engineering have allowed mining technology to undergo a significant transformation. Aiming to maximize the efficiency and safety of the mining process, several enabling technologies, such as the recent advances in artificial intelligence, IoT, sensor fusion, computational modeling, and advanced robotics, are being progressively adopted in mining machine manufacturing while replacing conventional parts and approaches that used to be the norm in the rock ore extraction industry. This article aims to provide an overview of research trends and state-of-the-art technologies in face exploration and drilling operations in order to define the vision toward the realization of fully autonomous mining exploration machines of the future, capable of operating without any external infrastructure. As the trend of mining at large depths is increasing and as the re-opening of abandoned mines is gaining more interest, near-to-face mining exploration approaches for identifying new ore bodies need to undergo significant revision. This article aims to contribute to future developments in the use of fully autonomous and cooperative smaller mining exploration machines.

The United Nations Sustainable Development Goal 11 aims to make cities and human settlements inclusive, safe, resilient and sustainable. Smart cities have been studied extensively as an overarching framework to address the needs of increasing urbanisation and the targets of SDG 11. Digital twins and artificial intelligence are foundational technologies that enable the rapid prototyping, development and deployment of systems and solutions within this overarching framework of smart cities. In this paper, we present a novel AI approach for hypervector approximation of complex manifolds in high-dimensional datasets and data streams such as those encountered in smart city settings. This approach is based on hypervectors, few-shot learning and a learning rule based on single-vector operation that collectively maintain low computational complexity. Starting with high-level clusters generated by the K-means algorithm, the approach interrogates these clusters with the Hyperseed algorithm that approximates the complex manifold into fine-grained local variations that can be tracked for anomalies and temporal changes. The approach is empirically evaluated in the smart city setting of a multi-campus tertiary education institution where diverse sensors, buildings and people movement data streams are collected, analysed and processed for insights and decisions.

Background: Healthy lifestyle behaviors in pregnancy are important for maternal and offspring health. Mobile health (mHealth) tools have potential to provide support for lifestyle behaviors at scale but such tools are commonly developed only in native languages, limiting reach in migrant populations. 

Objectives: This qualitative study, in two of the largest migrant populations in Sweden (Arabic- and Somali-speaking women), aimed to explore (a) perceptions and needs of knowledge and support related to pregnancy and lifestyle behaviors and (b) needs of and attitudes towards a pregnancy app and how features and content in the app can be adapted to support healthier lifestyle behaviors in migrant women.

Method: Individual semi-structured interviews were conducted with Arabic (n = 10) and Somali-speaking women (n = 9). Data was analyzed using content analysis (inductive latent approach).

Results: Arabic- and Somali-speaking women described an increased need of knowledge regarding pregnancy and lifestyle behaviors. The social environment could both motivate behavior change and be a source of misinformation. Women expressed great trust in maternity healthcare but requested more information related to lifestyle behaviors. A pregnancy app was perceived as a helpful tool to support healthy lifestyle behaviors. Mere translations were suggested to be valuable, however, audio- and video-format to deliver content and inclusion of women's partners in the app were described as desirable adaptations.

Conclusion: Our findings can guide maternity healthcare on what support migrant women need and inform future development of mHealth tools for pregnant migrant populations. Future research should disentangle the degree of cultural adaptations required for mHealth lifestyle interventions provided by healthcare.

Scene text image super-resolution (STISR) aims to enhance the resolution of text images while simultaneously improving their readability by reducing noise, blur, and other degradations. Existing diffusion-based approaches for STISR primarily rely on text-prior information but often overlook the importance of explicitly modeling the visual structure of the text. In this paper, we propose a novel Skeleton-Aware Diffusion Method (SADM) for STISR, which introduces text skeletons as structural guidance to the diffusion process. The text skeleton serves as a critical visual cue, helping the model to better restore the fine details of text, even in severely degraded low-resolution images. Generating high-quality skeletons from low-resolution scene text is a challenging task due to the inherent blurring and noise present in such images. To tackle this, we introduce a diffusion-based Skeleton Correction Network (SCN), which refines the initial skeletons produced by a convolutional neural network-based skeletonization model. The SCN effectively improves the accuracy of the skeletons, allowing for more precise structural guidance during the diffusion process. Our extensive experiments demonstrate the significant benefits of incorporating skeleton information into the STISR pipeline. The proposed SADM achieves state-of-the-art performance on the TextZoom dataset, with accuracies of 81.4%, 64.9%, and 49.6% on the easy, medium, and hard subsets, respectively, compared to the previous best results by ASTER text recognizer. Through detailed analysis, we also show that improving the quality of skeletons from low-resolution images leads to better super-resolution outcomes and enhances the performance of text recognizers.

Our study explores governing of European eel in Sweden. The paper aims to analyze and tentatively explain the degree of policy coherence between different political levels and discuss implications for management. The study focuses on the Advocacy Coalition Framework and a qualitative methodology. Results show that EU and Swedish eel fishery policies are based on partly different beliefs about prioritized groups, problem descriptions, and policy preferences. Swedish policy is more considerate of fishery, attentive to the problems of hydropower, and hesitant toward fishery closures, than is the EU. These differences can be understood by the positions and power of the two advocacy coalitions competing for influence at the national level. National decisions align more with the coalition that includes fishery organizations, the Swedish Board of Agriculture, and coastal municipalities than with the beliefs of the coalition involving environmental-and sport fishing organizations and the Swedish Environmental Protection Agency.

The long-term intelligent machine condition monitoring system is essential in improving maintenance costs and decision-making. Triboelectric nanogenerator (TENG) has a great advantage in developing self-powered machine condition monitoring. The main issues preventing TENG for such applications are poor integration to machine components, limited operational range, and weak durability. In this work, durable non-contact TENG energy harvester adaptive is designed to mechanical shafts for harvesting rotational energy. The harvester is designed to automatically switch to the non-contact mode by using centrifugal force to avoid manual switching while operating over a wide range of speeds of 0–2000 rpm. The designed TENG generates a high output of up to 25 mW with excellent stability for >20 days of continuous operation and exhibits a high-power density of 286 W m−3. Moreover, a self-powered long-term continuous condition monitoring system is developed from a TENG sensor, energy harvester, and wireless module. The developed system successfully sends possible machine fault frequency every 74 min to the cloud and accessible anywhere. This is the only TENG design reported in the literature that can fully power a Wi-Fi module to send data. Hence, the result promises the practical application of the system in developing internet of things (IoT) in the Industry.

The paper discusses Structural Health Monitoring (SHM) based on ultrasonic guided waves for damage detectionin structures. Guided waves allow inspection over long distances and inaccessible features, but are also sensitiveto changes in environmental and operating conditions (EOC). The focus of this paper is on temperaturecompensation methods for guided waves. The compensation techniques include Baseline Signal Stretch (BSS),Optimal Baseline Selection (OBS), OBS+BSS, and Dynamic Time-Warping (DTW). In particular, a new, fastapproximation of DTW is evaluated and compared with conventional but computationally expensive DTW. TheFDTW algorithm utilizes a multilevel approach inspired by graph bisection principles to achieve precise warpingpath determination with linear computational complexity.The study evaluates the compensation performance of FDTW using a single baseline at a single temperature, thusaddressing the complexity and inaccessibility issues of obtaining an extensive database of baseline signals inpractical applications. The Open Guided Wave (OGW) dataset is employed for a fair comparison with othercompensation methods.Results indicate that FDTW performs well, demonstrating comparable warping performance to DTW but withsignificantly reduced computational complexity. The analysis also includes comparisons with BSS, OBS+BSS,and DTW across a range of temperatures, highlighting the effectiveness of FDTW in mitigating errors introducedby larger temperature variations.

Crystalline thermoelectric materials, especially SnSe crystals, have emerged as promising candidates for power generation and electronic cooling. In this study, significant enhancement in ZT is achieved through the combined effects of lattice distortions and band convergence in multiple electronic valence bands. Density functional theory (DFT) calculations demonstrate that cation vacancies together with Pb substitutional doping promote the band convergence and increase the density of states (DOS) near the Fermi surface of SnSe, leading to a notable increase in the Seebeck coefficient (S). The complex defects formed by Sn vacancies and Pb doping not only boost the Seebeck coefficient but also optimize carrier concentration (nH) and enhance electrical conductivity (σ), resulting in a higher power factor (PF). Furthermore, the localized lattice distortions induced by these defects increase phonon scattering, significantly reducing lattice thermal conductivity (κlat) to as low as 0.29 W m−1 K−1at 773 K in Sn0.92Pb0.03Se. Consequently, these synergistic effects on phonon and electron transport contribute to a high ZT of 1.8. This study provides a framework for rational design of high-performance thermoelectric materials based on first-principles insights and experimental validation.

Over the last century, intensification of human movement has resulted in a large-scale redistribution of species worldwide. In recent decades, this phenomenon has been further compounded by climate change, creating complex challenges in the management of non-native species. As effective management can be hampered by gaps in communication and understanding between scientific researchers, natural resource managers and the wider public, assessing consensus between these groups is crucial.

Here, we adopt an explorative approach to analyse three key groups concerned with the management of freshwater ecosystems – recreational fishers, natural resource managers and scientific researchers. Our objective is to better understand the level of consensus regarding the interaction between non-native species and climate change.

We found that, while scientific researchers and managers had varying opinions on the management of non-native species as driven by climate change, recreational fishers were almost unanimously opposed to the potential presence of non-native species, regardless of the nature of their introduction. Additionally, definitions of what constitutes a non-native species varied greatly between and within the groups.

Our results underline both the current lack of consensus on the definition and management of non-native species and gaps in understanding between and within the three groups regarding both the nature of non-native species and the range-shifting effects of climate change.

Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer’s disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2–7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer’s Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age ~50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.

The potential of recycling carbon fiber reinforced polymers (CFRP) as a sustainable solution for waste management is yet to be fully understood. This study reports on the evolution of mechanical, and chemical properties of reclaimed carbon fibers when recycled multiple times via pyrolysis and partial oxidation. The performed work aims at filling the knowledge gap related to repetitive recycling when moving towards a circular flow of resources. A recycling process existing at industrial scale is used to ensure the relevance and usefulness of the results in the current industry scene. Two sets of three identical model composites are recycled using distinct recycling parameters, and their properties are characterized at the end of each recycling cycle. Results show that recycling can lead to an increase in stiffness but can have a negative impact on strength of recovered fibers. Mechanical behaviour shows recovered fibers suitable for secondary applications with medium performance requirements after two recycling cycles. The findings highlight the importance of understanding the material properties evolution during recycling processes. This research contributes to the development of sustainable waste management strategies and a more environmentally friendly future.

This study aims to expand the understanding of public acceptance of carbon taxes by exploring the role of habits. Habits play a pivotal role in guiding our behaviors and reasoning and can even influence our self perception and identity but remain an underexplored variable in relation to public policy acceptance. We employed a large scale (N > 5200) national survey to measure public acceptance of higher carbon taxation in Sweden, also capturing car driving habits, car usage, and other relevant variables. The findings show that habit strength is negatively correlated with policy acceptance, regardless of self reported driving distance, while also appearing to moderate the relationship between policy acceptance and environmental concern and political leaning, variables previously shown to be of relevance. The study suggests that the influence of habits needs to be recognized to better understand the formation of climate policy acceptance, and exploring this perspective paves the way for future research.