Digitala Vetenskapliga Arkivet - Academic Archive On-line
Not a member yet
734120 research outputs found
Sort by
Future projections of wet and dry spells in southern Sweden : The impact of climate model resolution
No full textNeurocognitive function in schizophrenia spectrum disorders : A 20-year prospective study of a community sample
No full textLongitudinal studies of neurocognition in schizophrenia spectrum disorders (SSD) usually follow relatively young first-episode patients across several years. Comparatively little is known about the neurocognitive trajectory of samples also consisting of older patients. This is a 20-year follow-up study of participants who performed the baseline assessment at different ages and utilizes data from the Swedish Clinical Long-Term Psychosis Study (CLIPS). At baseline, 61 SSD patients were included and available for clinical assessment after 20 years. Of these, 28 performed neurocognitive assessment at both baseline and 20 years later. The test results from this group were used for this study. After 20 years, the participants exhibited significantly worsening cognitive flexibility, verbal learning, verbal retention memory, and verbal intellectual function compared to baseline. All the statistically significant differences from baseline to follow-up had large effect sizes. The other cognitive domains showed no statistically significant changes from baseline for either group. We conclude that although the overall picture was one of neurocognitive stability across 20 years, our participants showed signs of accelerated ageing in the verbal domain specifically
Robot digital twin systems in manufacturing : Technologies, applications, trends and challenges
No full textThe manufacturing industry is undergoing a profound transformation toward smart, digital, and flexible production systems under the Industry 4.0 framework. Within this paradigm, Digital Twin (DT) serves as a key enabler, bridging physical and digital domains to simulate, analyse, and optimise manufacturing operations. Concurrently, robotic systems, enhanced by smart sensor perception, Industrial Internet of Things connectivity, and adaptive control mechanisms, are increasingly deployed to handle complex and dynamic tasks. However, the evolving demands of the modern manufacturing industry require a high degree of flexibility and responsiveness, necessitating more intelligent solutions. The Robot Digital Twin (RDT) has emerged as a transformative approach, facilitating dynamic adaptation and continuous operational improvement. This review offers a comprehensive examination of the literature on RDT in manufacturing from both technology and application perspectives, aiming to provide insight for researchers and practitioners in Industry 4.0. The paper introduces a four-layer RDT system architecture and summarises how Industry 4.0 technologies, e.g., the Industrial Internet of Things, Cloud/Edge Computing, 5 G, Virtual Reality, Modelling and Simulation, and Artificial Intelligence, converge and influence the RDT system based on this architecture. Furthermore, the review covers domain-specific and system-level applications, such as assembly, machining, grasping, material handling, human-robot interaction, predictive maintenance, and additive manufacturing systems, with an analysis of their development status. Finally, the trends, practical challenges, and future research directions for RDT systems in manufacturing are summarised at different levels.CC BY 4.0© 2025 The Author(s)Correspondence Address: X.V. Wang; Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, 10044, Sweden; email: [email protected]; CODEN: RCIMEThis research was supported by the EU Horizon Europe NEPTUN project (Grant Agreement: 101079398), the Swedish Digital Futures project: Towards Safe Smart Construction (VF 2020-0315), Swedish research centre of eXcellence in PRoduction RESearch (XPRES), China Scholarship Council (CSC 202308430011).</p
Position specific isotope analysis of diethylamine by 2H and 13C NMR : dual nucleus analysis in forensic investigation of illegal use of chemical weapons
No full textDiethylamine (DEA) is a known precursor to some of the most toxic chemical warfare agents (CWA) as both V-agents and Fourth Generation Agents (FGAs) contain the dialkylamine functionality. DEA is also a readily available commercial substance with extensive use in the chemical industry for legitimate purposes. Because of this potential dual use, it is desirable to develop methods to trace the origin of dialkylamines if they are used for illicit purposes. We herein demonstrate that it is possible to differentiate six commercial batches of DEA using position-specific isotope analysis (PSIA) by both 2H and 13C NMR. Using a high-field NMR spectrometer together with a cryogenic 2H probe, we have produced 2H-{1H} NMR data with high accuracy and precision. The PSIA by NMR results show that the intramolecular 2H ratios of all six DEAs are significantly different while two of the six DEAs have unique 13C ratios. Further, the intramolecular isotopic variations can be used to link the DEAs to different suppliers. The two nuclei separately contribute to isotopic profiles of the DEAs. However, combining the two techniques provides a higher-resolved isotopic profile that can differentiate all DEAs and thus be useful in forensic investigations of illegal use of chemical weapons
Experimental and theoretical study on ion association in [Hmim][halide] + methanol/dimethyl sulfoxide mixtures
No full textThe electrical conductivities of 1-hexyl-3-methylimidazolium halides ([Hmim][halide], halide = Cl–, Br–, I–) were measured in methanol (MeOH) and dimethyl sulfoxide (DMSO) at dilute concentrations from 293.15 to 313.15 K, alongside liquid density measurements for parametrization. Molar conductivity (Λ) decreased with increasing IL concentration and decreasing temperature, with solvent effects predominating over those of anion size. Λ was higher in MeOH than in DMSO due to lower viscosity and greater ion dissociation of MeOH. Comparison with a previous study involving H2O, MeOH, DMSO, and isopropanol confirmed that solvent viscosity is the dominant factor influencing Λ at infinite dilution. At higher IL concentrations, Λ in MeOH fell below that in H2O, likely due to a reduced number of free ions and the formation of larger solvated ion complexes.To analyze conductivity behavior, the Debye-Huckel-Onsager model was employed to determine the limiting molar conductivity (Λ0), which was subsequently used in the Shedlovsky equation to calculate the association constant (KA). For comparison, simultaneous regression of Λ0 and KA was also performed. The results indicated that, within the same solvent, Λ0 increased with temperature, while KA exhibited irregular trends. Across different solvents, Λ0 correlated with solvent viscosity, and KA was influenced by dielectric constant and polarity. Solvent effects on both Λ0 and KA were more pronounced than those of anion size, suggesting the dominant role of the solvent environment. Positive Eyring activation enthalpies showed the endothermic ion-pairing process. Additionally, the Walden product suggested stronger ion-solvent interactions and larger solvated ions in MeOH compared to DMSO. These findings provide deeper insight into IL conductivity in diverse solvent environments.Validerad;2025;Nivå 2;2025-10-17 (u8);Full text license: CC BY;Funder: State Key Laboratory of Material-Oriented Chemical Engineering; </p
Advances in MoS2 composites for electrocatalytic energy conversion: Synthesis, applications, and future perspectives in hydrogen, oxygen, nitorgen, and CO2 reactions
No full textThe significant increase in energy demand and environmental challenges requires sustainable technologies to preserve the climate and minimize CO2 emissions. Electrocatalysis for energy conversion applications, such as hydrogen evolution reaction (HER), oxygen evolution reaction (OER), nitrogen reduction reaction (NRR), and CO2 reduction reactions (CCR), are essential in renewable energy technologies. State-of-the-art catalysts are highly needed to enhance energy conversion efficiencies. Recently, Molybdenum disulfide (MoS2) with its distinguished physiochemical properties has been verified as a potential energy conversion material for catalyzing electrochemical reactions, ensuring excellent performance.Aside from graphene, which is unsuitable in some fields due to its zero-energy bandgap, alternative 2D materials like MoS2 have been developed and investigated. MoS2 nanostructures, with a relatively brief history, are emerging as suitable candidates in several applications, especially in electrocatalysis. Enhancing charge transfer and combining MoS2 with other materials can improve energy and environmental application performance.The excellent electrocatalytic progress of MoS2-based composites has been reported alongside enhanced and tunable properties like rich active edges, high density of structural defects, excellent conductivity, well-defined size dispersion, good electrode contact, favorable exposed crystal facets, and maximized phases. These properties, critical in electrocatalysis, are reviewed herein.We describe different methodologies for preparing MoS2 composite materials, illustrating their advantages and limitations for catalysis applications. We discuss the figure of merit of MoS2 composite nanostructures in electrocatalysis and present the challenges and outlooks for this new material class based on recent developments and potential applications in energy and the environment, suggesting promising research directions for the future.Validerad;2025;Nivå 2;2025-11-25 (u4);Funder: Pakistan Science Foundation and the National Natural Science Foundation of China (PSF-NSFC/202307/427); UK Carbon Capture and Storage Research Centre (UKCCSRC);Fulltext license: CC BY</p
Bisection width, discrepancy, and eigenvalues of hypergraphs
No full textA celebrated result of Alon from 1993 states that any d-regular graph on n vertices (where d=O(n1/9)) has a bisection with at most [Formula presented.] edges, and this is optimal. Recently, this result was greatly extended by Räty, Sudakov, and Tomon. We build on the ideas of the latter, and use a semidefinite programming inspired approach to prove the following variant for hypergraphs: every r-uniform d-regular hypergraph on n vertices (where d≪n1/2) has a bisection of size at most [Formula presented.] for some c=c(r)>0. This bound is the best possible up to the precise value of c. Moreover, a bisection achieving this bound can be found by a polynomial-time randomized algorithm. The minimum bisection is closely related to discrepancy. We also prove sharp bounds on the discrepancy and so called positive discrepancy of hypergraphs, extending results of Bollobás and Scott. Furthermore, we discuss implications about Alon-Boppana type bounds. We show that if H is an r-uniform d-regular hypergraph, then certain notions of second largest eigenvalue λ2 associated with the adjacency tensor satisfy λ2≥Ωr(d), improving results of Li and Mohar
Biofuel bottlenecks and synthetic fuels : Leveraging aviation for global climate action
No full textBiogenic hydrocarbons occupy a central place in transition narratives across multiple sectors, from transport and energy to chemicals and consumer goods. Yet their inherent scarcity creates unavoidable dilemmas of prioritization. This article examines aviation as a case study of these dilemmas. While the industry has tied its hopes for decarbonization to biofuels, their large-scale use risks crowding out other sectors, undermining both climate and biodiversity goals. To guide policymakers, the article proposes three evaluative principles – global scalability, transformational leverage, and ability-to-pay – arguing that aviation is uniquely positioned to accelerate investment in synthetic electrofuels derived from carbon capture. Such fuels offer compatibility with existing infrastructure while simultaneously commercializing technologies that are essential for achieving net-negative emissions. By situating aviation within wider ethical and political debates, the article suggests that, with democratic steering, the sector could shift from climate villain to driver of globally meaningful climate action. © 2025 The Author
Efficient finite difference modeling of infrasound propagation in realistic 3D domains: Validation with wind turbine measurements
No full textWe present a high-fidelity simulation tool for accurate acoustic modeling across a wide range of applications. The numerical method is based on diagonal-norm Summation-By-Parts (SBP) finite-difference operators, which guarantee linear stability on piecewise curvilinear multi-block grids. Realistic three-dimensional atmospheric and topographic data are directly incorporated into the simulations, and the solver is implemented in CUDA to achieve high computational efficiency. Verification is performed through convergence studies against highly resolved benchmark problems in both two and three spatial dimensions, while validation is carried out using high-quality infrasound measurements from two modern wind farms in Sweden. The results show that modern, large-scale wind turbines generate infrasound levels significantly higher than those reported for older, smaller turbines. These findings advance the understanding of the acoustic characteristics of contemporary wind turbines and provide important guidance for assessing their potential environmental and societal impacts