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Ion-Mediated Tearing and Kink Instabilities in the Earth's Magnetosphere:Hybrid-Vlasov Simulations
No full textWe explore the three-dimensional structure of ion-kinetic instabilities in a thin current layer using a hybrid-Vlasov simulation of the Earth's magnetosphere. The simulation shows the simultaneous growth of tearing and kinking instabilities, which develop in the Sun-Earth and dawn-dusk directions, respectively, within the magnetotail current sheet. The formation of flux ropes indicates the development of the tearing instability, while flapping-type cross-tail oscillations arise from the kink instability. We consider both instabilities as independent polarizations, albeit sharing a common source: demagnetized ions forming crescent-shape distributions at the center of the current layer. These oscillations exhibit spatiotemporal characteristics within the proton-scale range, featuring a growth time on the order of 40–80 proton gyroperiods and a wavelength of approximately 15–30 proton skin depths
The effect of feedstock concentration on the crystal phase, morphology, and optical properties of WO<sub>3</sub> nanostructures
No full textIn this study, the effect of feedstock concentration on the synthesis of WO3 nanostructures in a one-step hydrothermal process was investigated. According to our experiments, when titrating aqueous Na2WO4$2H2O with HCl solutions of different concentrations to a constant pH of 1.5, after identical hydrothermal treatments at 180 °C, the morphology, crystal size and phase composition as well as the optical properties of the products could be tuned. Furthermore, by applying Na2SO4 in the precursor solution, we get a further degree of freedom to alter the structural and optical properties of the products. The precursor concentration dependent optical band gap energy values (that vary from ∼2.5 eV to ∼2.9 eV) are in good agreement with the associated hexagonal (from 32.7% to 65.5%) and orthorhombic (from 67.3% to 34.5%) phases of nanostructured tungsten oxide products. The calculated Urbach energies can be well explained by the oxygen deficient crystals. The latter is also coherent with measured photoluminescence (multiple peaks between 400 and 580 nm) that indicate abundant defect states in the tungsten oxide products.</p
Adding Emotional Intelligence to Physical Spaces:Data-Driven Solutions for Measuring, Analysing, and Responding to User Needs and Expectations
No full textAlthough emotions can influence our living, experiences, and performance in different contexts, current immersive services in physical environments are failing to read, interpret and respond to our emotions. This study aims to provide understanding of how to enhance physical spaces with emotionally aware, intelligent, and integrated services meeting the expectations of the users. It focuses on three different environments (office, public space and transport) and defines the high-level requirements for the technologies needed for the implementation of emotionally intelligent services, as well as identifies the stakeholders involved in service creation and data processing. Service concepts were generated in collaboration with experts from academia and industry using co-creation methods. The industrial partners of this study see that the novel sensing capabilities and artificial emotional intelligence-based solutions for behaviour analysis and situational awareness have the potential to enable new services, for both the space operators and the users. For such services, the pipeline from data to information and actions must be streamlined and modular, which requires research on technologies, analytics methods, service, and business model design. Ultimately, such services will enable businesses to provide experiences that understand and respond to human behaviour and emotional responses in everyday life, while interacting with technology.</p
Factors improving dry fractionation of Bambara groundnut aiming at production of protein-rich ingredients with elevated nutritional and technological quality
Get PDFBambara groundnut is a nutritious African grain legume with potential to be refined into a high-protein ingredient. This work aimed to develop protein-rich ingredients from Bambara via dry processing. Due to Bambara's high fat content, two dry fractionation approaches were developed. In the first one, Bambara was defatted using supercritical CO 2 extraction, milled and air classified producing ingredients with 48 % protein, achieving 74 % of total protein separation efficiency. Without defatting, the efficiency stood at 16.7 %. A second attempt, incorporating a flow aid during air classification, yielded ingredients with 38.2 % protein and protein separation efficiency of 33 %. These protein-rich ingredients exhibited higher protein solubility, total extractability, and water and oil absorption capacities compared to the raw materials. Phytic acid content increased in the protein-rich ingredients, but tannin was significantly reduced. The essential amino acid score of Bambara protein-rich ingredients was higher than 1 and the degree of protein hydrolysis was 31 %. </p
Accurate SOP prediction of supercapacitor using fractional calculus framework
No full textReal-time information of state of power (SOP) of a supercapacitor (SC) is crucial for determining its capability about power delivery or absorption. The dynamics of SOP is intricately coupled with the present state of charge (SOC), and depends on various operating limits including voltage limits. In essence, better SOP prediction is highly dependent on the estimated value of SOC as well as the physical model that captures the electrical dynamics of SC. In this context, this paper proposes an accurate SOP prediction scheme which utilizes an accurate device model and SOC estimation scheme based on fractional order calculus. Within this proposed framework, SOP has been predicted in real-time based on the derived value of maximum possible input/output current without violating the device voltage, current, and SOC limits. This maximum current is derived by using instantaneous voltage estimated through a fractional order model (FOM) and instantaneous SOC estimated through fractional order extended Kalman filter (FOEKF), along with the aforementioned device constraints. The FOM is identified based on the experimental data obtained using a commercial Maxwell 5F SC. As SC performance suffers from the leakage current, especially in low duty cycle applications, the effect of leakage current variation on the SOP prediction is investigated. Furthermore, the impact of prediction horizon on SOP prediction has been studied. Overall, these studies collectively show that the effectiveness of the proposed framework.</p
Inverse-Free Hybrid Spatial-Temporal Derivative Neural Network for Time-Varying Matrix Moore-Penrose Inverse and Its Circuit Schematic
No full textThis brief introduces the Inverse-free hybrid spatial-temporal derivative neural network (IHSTDNN), a novel neural network that integrates principles from gradient neural networks (GNN) and zeroing neural networks (ZNN) to address the time-varying matrix Moore-Penrose inverse. The IHSTDNN features an explicit dynamic structure, eliminating the need for inverse operations. The design of its circuit is outlined, and the model's convergence and robustness are examined theoretically. Numerical simulations and experimental data demonstrate that the IHSTDNN outperforms other existing models, achieving a faster convergence rate and reduced steady-state error.</p
Scrape-off layer and divertor physics:Chapter 5 of the special issue: on the path to tokamak burning plasma operation
No full textSince the publication of the review Progress in the ITER Physics Basis (PIPB) in 2007, significant progress has been made in understanding the processes at the plasma-material interface. This review, part of the ITPA Nuclear Fusion Special Issue On the Path to Burning Plasma Operation, presents these developments, focusing on key areas such as the physics of plasma exhaust, plasma-material interactions, and the properties of plasma-facing materials and their evolution under plasma exposure. The coordinated efforts of the ITPA Topical Group on Scrape-Off Layer and Divertor Physics (DivSOL) have been instrumental in identifying and addressing critical research and development issues in numerous collaborative experimental and modelling projects.</p
Kestävää kasvua solumaatalouden arvoketjuista:Toimenpidesuunnitelma Suomelle
Get PDFTämän selvityksen tavoitteena on luoda askelmerkit solumaatalouteen perustuvan kasvun mahdollistamiseksi ja toteuttamiseksi Suomessa. Työssä kartoitettiin solumaatalouden nykytila Suomessa ja maailmalla, sekä tarkasteltiin toimintaympäristön kehitystä Suomessa ja kansainvälisillä markkinoilla. Lisäksi määriteltiin useita toimijoita yhdistävät muutospolut solumaatalouden juurruttamiseen ja edistämiseen kohti kestävää ja kannattavaa tulevaisuuden ruokajärjestelmää. Kartoitusten, sidosryhmähaastattelujen, työpajojen ja asiantuntijatiedon perusteella määriteltiin askelmerkit Suomelle solumaatalouden integroimiseksi kansalliseen ruokajärjestelmään ja kasvupotentiaalin lunastamiseksi
New Kinematic Control Scheme for Redundant Robotic Manipulators Perturbed by Harmonic Noise
No full textKinematic control is one of the fundamental issues in the study of redundant robotic manipulators, and various schemes that utilize the pseudoinverse of the Jacobian have been crafted in this field.However, these schemes may be ineffective due to the lack of suppressing additive noise, especially the harmonic noise widely encountered in practice. This article proposes a new kinematic control scheme for redundant robotic manipulators affected by harmonic noise, aiming to overcome the identified limitations. Such a scheme, which incorporates the adaptive learning mechanism based on harmonic frequency, can simulate the harmonic noise, suppress its disturbance, and eventually realize the effective control purpose. It is then theoretically proven that the Cartesian error generated by the proposed scheme exhibits the convergence property, thus guaranteeing the control performance on redundant robotic manipulators even in the presence of harmonic noise. Simulation and experiment results under PA10 and Panda robotic manipulators further verify the efficacy and superiority of the proposed kinematic control scheme.</p
Prompting to Gather Object Categories in NeRF Scenes Related to Manufacturing
No full textDespite the effectiveness of closed-set object detectors, recent advancements have introduced zero-shot detectors that can recognize a wide range of object categories across different environments. These detectors rely on text prompts, such as object tags. This study explores using multimodal large language models (MLLMs) to gather and refine object information from NeRF scenes into tags. We propose a training-free pipeline for extracting object-specific details, such as category, color, material, and functionality, from 3D scenes via prompting. Subsequently, we investigate how to apply the object tagging problem to NeRF-reconstructed scenes, particularly in a manufacturing context. This pipeline is evaluated in manufacturing environments for object recognition, with the resulting categories serving as inputs for zero-shot object detection and other tasks