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Traffic-related diesel pollution particles impair the lysosomal functions of human iPSC-derived microglia
No full textExposure to air pollution is associated with neurological diseases. Traffic is a major source of air pollution, consisting of a complex mixture of ultrafine particles, that can invade the brain and induce a microglia-mediated inflammatory response. However, the exact mechanisms of how traffic-related particles impact human microglia remain poorly understood. This study investigates the effects of diesel exhaust particles (DEPs) on human induced pluripotent stem cell-derived microglia-like cells (iMGL). We exposed iMGLs to three different DEPs and studied the impact on the iMGL transcriptome and functionality, focusing on cytokine secretion, mitochondrial respiration, lysosomal function, and phagocytosis. A20 particles were collected from a heavy-duty engine run with petroleum diesel. For A0, the same engine was run with renewable diesel. E6 was produced with a modern 2019 model diesel passenger car run with renewable diesel. RNAseq revealed activation of the cytokine storm pathway and inhibition of the autophagy pathway in iMGLs after exposure to particles derived from older diesel emission technology (A20, A0). Particles from the modern diesel engine technology (E6) did not alter microglial transcriptome after 24 h exposure. A20 and A0 exposure led to impaired lysosomal functions in iMGLs. In contrast, E6 did not cause major alterations in microglia functions. In addition, we show that response to particles is more pronounced in human iMGLs compared to mouse primary microglia. To conclude, particles from older emission technology impair phago-lysosomal functions of iMGLs, but modern alternatives with filtration do not induce drastic changes in the functionality of iMGLs.</p
Predicting cargo handling and berthing times in bulk terminals:A neural network approach
No full textThis paper presents a comprehensive study on the development of a neural network model aimed at predicting the cargo handling time and berthing time. Utilizing physical ship data (length, beam, draught, DWT, and GT), cargo type, daily weather conditions, cargo handling equipment data, and historical operation times, the model aims to enhance the operational efficiency of bulk terminals. A case study conducted at a bulk terminal, leveraging a three-year dataset, serves as the foundation of this research. The outcomes of the neural network analysis highlight the average cargo handling capacity under various conditions, providing crucial insights for port operation optimizations such as determining the optimal number of gangs, calculating berth occupancy ratios, and improving berth planning strategies. The implications of these findings are significant, offering a pathway toward more efficient and predictive port management strategies, with the potential to substantially reduce operational costs and increase throughput efficiency. This study not only contributes to the existing body of knowledge by integrating diverse data types into a predictive model but also proposes practical applications that can lead to more informed decision-making in port and terminal operations.</p
Regulation of Sugar Metabolism During Fermentation of Brewers' Spent Grain by Leuconostoc pseudomesenteroides DSM20193
No full textRe-utilising brewers' spent grain (BSG) through LAB fermentation can enable its broad use in the food industry, enhancing its nutritional and functional properties and offering a clear example of a sustainable approach in the valorisation of food side streams. Despite extensive research on LAB fermentation, the regulation of metabolism during the growth in complex food-industry-relevant environments remains unclear. This study investigates the metabolic processes in Leuconostoc pseudomesenteroides DSM20193 during 24 h fermentation of BSG with and without 4% sucrose (w/w) supplementation, allowing in situ dextran synthesis. Besides dextran synthesis, the presence of sucrose led to faster acidification, especially due to the increased formation of acetic acid. Furthermore, differences in the utilisation of sucrose, fructose, glucose, and maltose and the formation of diverse oligosaccharides were observed. Transcriptome analysis comparing expression profiles during 0 h and 16 h growth in BSG with sucrose revealed differences in the expression of genes involved in carbohydrate utilisation pathways, including higher activity of sucrose and maltose metabolism and lower activity of metabolism related to alternative carbon sources. Transcription analysis of selected relevant genes in a time-course comparison between BSG with and without sucrose provided more detailed indications of responses of the metabolic network in this complex environment. This analysis provided a deeper understanding of the dynamic regulatory mechanism that drives sugar metabolism and dextran synthesis and how the presence of sucrose can alter the metabolic flux towards different fermentation products.</p
Towards industrial autonomy: a four-dimensional Level of Autonomy (LoA) Framework
No full textIndustrial systems are transitioning towards greener, digital, and autonomous solutions, resulting in significant changes to their design and operation. This path to full autonomy faces several challenges, especially in integrating modern and legacy equipment at industrial sites, causing incompatible communication standards and diverse software systems. Each site presents unique requirements, necessitating close cooperation between technology providers and site operators.Site operators need a thorough understanding of the opportunities, limitations, and safety risks associated with increased autonomy. Additionally, the physical design of sites must be suitable for the integration of autonomous machines, alongside potential combinations of autonomous, semi-autonomous, and manual equipment. Communication challenges can arise when certain machines rely on manual operation, complicating overall system's functionality. Beyond technical hurdles, increased autonomy requires adjustments in business-wide operations, including safety management, logistics, product and document management, fleet management, and the refinement of operator skillsets.To address these complexities, we propose a four-dimensional Level of Autonomy (LoA) framework that helps in identifying and prioritizing key areas for enhancing autonomy. Unlike existing models that focus solely on system-wide or individual machine autonomy, our LoA framework integrates dimensions for machine driving, machine manipulation, system operation, and system mission. The operational dimension considers the orchestration of autonomous driving and manipulation of both individual machines and entire fleets, while the mission dimension emphasizes the management of multiple connected mixed fleets working towards a unified system goal.Dimensions of autonomy are crucial because they highlight areas where human involvement is necessary and provide insights into strategies needed to enhance autonomy or assess the current level of system autonomy. A comprehensive LoA framework benefits stakeholders, including original equipment manufacturers (OEMs), suppliers, and system integrators, by providing a unified approach for implementing autonomous systems
Dual crosslinked poly(vinyl alcohol)/starch/oxidized-cellulose nanofiber hydrogels with self-healing and antibacterial effects
No full textHydrogels composed of polyvinyl alcohol (PVA), Pehuen Starch (PS), and TEMPO-oxidized cellulose nanofibrils (TO-CNF) were prepared by the use of a one-pot method that consisted of sonication and freeze-thawing cycles without intermediate separation. Field Emission Scanning Electron Microscopy (FE-SEM), Atomic Force Microscopy (AFM), and Micro-Computed Tomography (micro-CT) analyses confirmed that PVA/PS/TO-CNF hydrogels had dynamic behavior (reversible ester bonds and hydrogen bonds), resulting in homogeneous porous architectures. FTIR spectra highlighted chemical structure changes because of the dual cross-linking reaction. Along the same line, rheological measurements indicated a predominantly elastic nature and incremented storage modulus by 20–50%, promoted by the addition of 1 wt.% TO-CNF. Light optical microscopy revealed a fast self-healing behavior within 2 min post-incision, and thermal gravimetry (TGA) confirmed that the inclusion of borax improved thermal stability. Biocompatibility tests with MSCs and HepG2 cells showed non-toxicity, with 1:1 mass ratio PVA/PS-TOCNF hydrogels exhibiting superior dimensional stability, viable cell recovery rates (20–40%), and antimicrobial activity against E. coli. These results demonstrates the potential of biobased polymers (PS-TOCNF) to improve the properties of PVA/borax hydrogels for next-generation healthcare applications, offering a promising solution with competitive mechanical strength, biocompatibility, and antibacterial properties.</p
Impact of storage of oat bran flour and dispersion on lipid oxidation, odour profile, and oxidative degradation of beta-glucan
No full textLipid oxidation induced oxidative degradation of beta-glucan could lead to technological, sensory, and nutritional challenges during food storage. This study aimed to explore the impact of storage of oat bran concentrate (OBC) flours and aqueous oat dispersions on lipid, beta-glucan, and odour properties. Formation of free fatty acids was observed in non-heat treated OBC flour during storage (12 weeks at 4–40 °C), indicating the activity of endogenous hydrolytic enzymes, while lipid oxidation was highest in heat-treated (HT) OBC flour. The molecular weight of beta-glucan remained the same, indicating that lipid oxidation did not induce oxidative degradation of beta-glucan in the flours. Fresh and 8 weeks at 40 °C stored HT OBC flours were used for the preparation of aqueous oat dispersions with and without 3 % rapeseed oil. No difference in the odour characteristics of dispersions prepared from fresh and stored OBC flours was found. However, 4 weeks at 22 °C storage of HT OBC dispersions had a significant effect on the odour in comparison to the freshly prepared dispersions. During the storage of the dispersions, oxidation of lipids was mild and degradation of beta-glucan was not detected. This study provides new insights into the impact of storage on dry and aqueous oat products.</p
VSMI2-PANet:Versatile Scale-Malleable Image Integration and Patch Wise Attention Network With Transformer for Lung Tumour Segmentation Using Multi-Modal Imaging Techniques
No full textLung cancer (LC) is a major cancer which accounts for higher mortality rates worldwide. Doctors utilise many imaging modalities for identifying lung tumours and their severity in earlier stages. Nowadays, machine learning (ML) and deep learning (DL) methodologies are utilised for the robust detection and prediction of lung tumours. Recently, multi modal imaging emerged as a robust technique for lung tumour detection by combining various imaging features. To cope with that, we propose a novel multi modal imaging technique named versatile scale malleable image integration and patch wise attention network ((Formula presented.)) which adopts three imaging modalities named computed tomography (CT), magnetic resonance imaging (MRI) and single photon emission computed tomography (SPECT). The designed model accepts input from CT and MRI images and passes it to the (Formula presented.) module that is composed of three sub-modules named image cropping module, scale malleable convolution layer (SMCL) and PANet module. CT and MRI images are subjected to image cropping module in a parallel manner to crop the meaningful image patches and provide them to the SMCL module. The SMCL module is composed of adaptive convolutional layers that investigate those patches in a parallel manner by preserving the spatial information. The output from the SMCL is then fused and provided to the PANet module. The PANet module examines the fused patches by analysing its height, width and channels of the image patch. As a result, it provides an output as high-resolution spatial attention maps indicating the location of suspicious tumours. The high-resolution spatial attention maps are then provided as an input to the backbone module which uses light wave transformer (LWT) for segmenting the lung tumours into three classes, such as normal, benign and malignant. In addition, the LWT also accepts SPECT image as input for capturing the variations precisely to segment the lung tumours. The performance of the proposed model is validated using several performance metrics, such as accuracy, precision, recall, F1-score and AUC curve, and the results show that the proposed work outperforms the existing approaches.</p
Security, Privacy, and Resilience Controls for the 6G End-to-End System Developed in Hexa-X-II
No full textThe sixth generation (6G) of mobile networks is being developed to overcome limitations in previous generations and meet emerging user demands. As spearhead of the European research and development effort on 6G, the Smart Networks and Services Joint Undertaking (SNS JU) 6G Flagship project Hexa-X-II has a leading role for developing the technologies and anchoring 6G end-toend (E2E) system. This paper summarizes the security, privacy, and resilience (SPR) controls identified by the Hexa-X-II project and their validation activities. Moreover, we share the SPR view on the 6G E2E system with the SPR features which are necessary to ensure the trustworthiness of 6 G.</p
DEVELOPMENT OF AN INNOVATIVE STRUCTURAL SYSTEM FOR MULTISTOREY TIMBER BUILDINGS WITH INCREASED SERVICE LIFE - THE CRESTIMB PROJECT
No full textCRESTIMB aims to develop an innovative timber system for multi-storey buildings with open spaces. The system includes softwood or hardwood glued-laminated timber (glulam) columns and beams connected with innovative moment resisting connections, and dowel-cross laminated floors. This paper focuses on the description and identification of the structural system, in addition to the experimental programme that aims to assess the short- and long-term performance of the system components, which includes mechanical tests on small wood samples, and full-scale tests. Test results will serve as input to advanced numerical modelling to investigate the long-term behaviour of the selected components considering the complex rheological behaviour of wood under variable indoor climates, with the objective to ensure an increased service life and also the possibility of reuse of components.</p
Two novel harmonic-resistant zeroing neural networks for time-varying problems in robotic manipulators
No full textThis paper presents two novel harmonically disturbance-resistant zeroing neural network (ZNN) models: the known frequency harmonic-resistant ZNN (KFHRZNN) and the unknown frequency harmonic-resistant ZNN (UFHRZNN). These models are designed to tackle the pseudoinverse of time-varying matrices and inverse kinematics challenges in robotic manipulators. By precisely accounting for the derivatives of harmonic disturbances, they significantly mitigate these interferences, thereby improving the control efficacy of robots in high-speed, dynamic settings. The study elucidates the design rationale, convergence characteristics, and stability assessments for both KFHRZNN and UFHRZNN. Numerical simulations and physical experiments validate the effectiveness and advantages of these models in resolving time-varying issues within robotic manipulators, highlighting their precision and robustness against harmonic disturbances.</p