139585 research outputs found
Sort by
Subinvariant Metric Functionals for Nonexpansive Mappings
No full textPublisher Copyright: © 2025 Taylor & Francis Group, LLC.We investigate the existence of subinvariant metric functionals for commuting families of nonexpansive mappings in noncompact subsets of Banach spaces. Our findings underscore the practicality of metric functionals when searching for fixed points of nonexpansive mappings. To demonstrate this, we additionally investigate subsets of Banach spaces that have only nontrivial metric functionals. We particularly show that in certain cases every metric functional has a unique minimizer; thus, subinvariance implies the existence of a fixed point.Peer reviewe
Minimizing extractivism through 3D printing with law and policy support
No full textThe concept of ‘extractivism’ refers to the mindset and processes that facilitate for-profit large-scale exploitation of natural resources. Extractivism has a strong connection with how the markets work in this era of factory mass-production. This article seeks to understand if and how 3D printing (3DP), guided by effective legislation and policy, could help reduce overproduction practices and minimize resource extraction, thereby limiting the consumeristic attitude on which the concept of extractivism is based. The research utilized scenario building, following a multiphased-qualitative approach involving literature review, an expert workshop, and two focus group interviews. The primary outcome includes four scenarios for the year 2032, which are from most-likely, normative, optimistic, and pessimistic perspectives. Since the normative scenario calls for action to reach a preferable future, further analysis involved mapping out the strategies for utilizing 3DP to reduce extractivism. The findings support positioning 3DP as a low-volume production tool for prolonging product lifecycle and material value, highlighting the strategic areas of ‘material circulation’ and ‘product upgrade and repair-reuse systems’. Key legal and policy actions that could support these approaches are also identified, which primarily pertain to the fields of IPR and environmental legislation.Peer reviewe
Online Memetic Engagement and Collective Memory: The Case of “Lying Flat”
No full textThis article explores the “Lying Flat Movement”, a burgeoning online socio-cultural trend that is in its process of historization as a memetic engagement in Chinese cyberspace. This movement challenges the glorification of relentless societal competition in China, symbolized by the pervasive “Eating Bitterness” (吃苦) and “Spirit of Hard Work” (艰苦奋斗精神) ideologies. We aim to decipher the online discourse surrounding this movement, focusing on its semiotic and modal potentials in (re)shaping collective memory. Our theoretical framework draws from concepts like re-semiotization, media modality, and mediated social action. We gathered 11,555 comments from prominent Chinese social media platforms, such as Sina Weibo and Toutiao, representing the movement’s discourse with meaningful symbols and internet memes. Employing mediated discourse analysis (MDA), we examine these comments to uncover their semiotic, modal, and discursive implications in shaping collective memory. Our findings highlight three key concepts: (1) memetic engagement as a multimodal framework to aid memory concretization, (2) memetic engagement as an ideological cluster interlinking opinions and memetic intertextualities to enrich memory construction and narrative coherence, and (3) memetic engagement as an entangled social action with discourse in place, interaction order, and historical body.Peer reviewe
Economic viability of large-scale solar PV implementation in the Nordic power market : Case Finland
No full textPublisher Copyright: © 2025 The Author(s)This study analyses how the rapid growth of utility-scale solar PV in the Nordic region will impact its economic viability by 2030, using Finland as a case study. The analysis is based on modelling the Nordic electricity market. Solar energy is crucial for the energy transition in the Nordic region; however, high penetration levels pose significant economic challenges. The lack of feed-in tariffs for solar PV, limited energy system flexibility, high shares of nuclear and wind power and ambitious solar expansion plans make Finland a topical case study. Using PLEXOS advanced electricity market simulation tool, this study models the Nordic and Baltic multinational electricity system in detail and its connections to the Central Western European power market. The study includes significant electricity demand changes from rapid increases in electric vehicles, district heating electrification, and hydrogen production. Multiple scenarios representing different solar PV levels across the Nordic regions are analysed by 2030, including one scenario with various shares of vertically mounted, east-west-oriented bifacial solar PV. Results indicate that large-scale solar PV integration in the Nordic region could collapse Finnish electricity prices, specifically in the summer months. This expansion would reduce solar capture rates to 40% by 2030, highlighting the solar cannibalisation in Finland. These findings indicate the potential economic risks of extensive solar PV deployment and the need for market adaptation. Integrating vertical bifacial panels to adjust the PV production profile and optimising the electric vehicle charging are found to be important to improve the economic viability of solar generation.Peer reviewe
Giant Multiphoton Luminescence and Band Renormalization with Hot Electron–Hole Plasma in Multilayer GaSe
No full textPublisher Copyright: © 2025 Wiley-VCH GmbH.Efficient photoluminescence (PL) of layered semiconductors is crucial for advancing next-generation photonic devices. However, thermal effect-induced destruction typically hinders the practical applications, such as biosensing and imaging. Here, the upconversion PL of multilayer GaSe is reported, which circumvents thermal damage. A high-order multiphoton (up to 8-photon) PL is first reported in multilayer GaSe. Both experimental and theoretical results reveal a power-dependent redshift of the PL peak (≈40 meV, equivalent to 2% of the bandgap) and PL spectral broadening (full width at half maximum increased by ≈2 times), attributed to the hot electron–hole plasma. Time-resolved PL resolves the multistage of carrier relaxation, revealing an ultrafast transition (≈58 ps) from electron–hole plasma to excitonic states, which establishes hot electron–hole plasma engineering as a critical mechanism for manipulating PL processes in Group-III–VI chalcogenides. Furthermore, wavelength-dependent two- and three-photon PL spectra are explored. These results establish a microscopic framework connecting hot electron–hole plasma dynamics with macroscopic optoelectronic phenomena, providing critical insights for designing ultrafast photonic modulators and nonlinear optical devices based on 2D layered semiconductors.Peer reviewe
Design Principles for Immersive Virtual Safety Training : An Action Design Research Project
No full textPublisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.To tackle emerging challenges related with traditional safety training for practitioners that work onboard trains in society; for this research, we developed an immersive virtual safety training environment with Immersive Virtual Reality technology. We employed the Action Design Research (ADR) approach to design an Alpha prototype in close cooperation with end-users and software developers. The end-users were train operators and safety trainers at a train operating company in Sweden known as SJ. Two research cycles were executed to develop and evaluate the prototype. Consequently, by following the ADR method, we developed and proposed four design principles for immersive virtual safety training environments: (1) Design for Virtual Safety Realism, (2) Design for Virtual Boundary Crossing, (3) Design for Virtual Multimodal Feedback, and (4) Design for Virtual Touchpoints and Collaborative Reflection.Peer reviewe
Quantum computing for discrete optimization : A highlight of three technologies
No full textPublisher Copyright: © 2025 The AuthorsQuantum optimization has emerged as a promising frontier of quantum computing, providing novel numerical approaches to mathematical optimization problems. The main goal of this paper is to facilitate interdisciplinary research between the Operations Research (OR) and quantum computing communities by helping OR scientists to build initial intuition for-, and offering them a hands-on gateway to quantum-powered methods in the context of discrete optimization. To this end, we consider three quantum-powered optimization approaches that make use of different types of quantum hardware available on the market. To illustrate these approaches, we solve three classical optimization problems: the Traveling Salesperson Problem, Weighted Maximum Cut, and Maximum Independent Set. With a general OR audience in mind, we attempt to provide an intuition behind each approach along with key references, describe the corresponding high-level workflow, and highlight crucial practical considerations. In particular, we emphasize the importance of problem formulations and device-specific configurations, and their impact on the amount of resources required for computation (where we focus on the number of qubits). These points are illustrated with a series of experiments on three types of quantum computers: a neutral atom machine from QuEra, a quantum annealer from D-Wave, and gate-based devices from IBM.Peer reviewe
TinyTripleNet: A lightweight architecture for solar photo voltaic fault detection optimized for edge tensor processing unit hardware deployment
No full textPublisher Copyright: © 2025 The Author(s)The growing adoption of solar energy underscores the need for efficient and accurate fault detection in photovoltaic (PV) systems to minimize energy loss and maintenance overhead. This study introduces TinyTripleNet, a lightweight convolutional neural network optimized for real-time solar panel fault classification on edge devices. The model integrates three convolutional layers with Residual and Squeeze-and-Excitation (SE) blocks to enhance feature extraction while maintaining a compact size of only 0.9 million parameters. TinyTripleNet is trained using binary cross-entropy loss and the Adam optimizer on a thermographic PV dataset, achieving class-wise accuracies of 96.71 % (2-class), 92.16 % (8-class), 90.25 % (11-class), and 93.07 % (12-class). It also achieved a mean Average Precision (mAP) of 92.4 % on the 12-class dataset. Compared to 29 baseline models, including VGG16, ResNet50, and MobileNet, TinyTripleNet demonstrated a 75 % reduction in inference time and over 80 % savings in memory usage, with an inference latency of 4.8 ms/image on the Coral Edge TPU and a runtime memory footprint of 1.7 MB. These results position TinyTripleNet as a robust solution for drone-based PV fault detection, offering a practical trade-off between accuracy, model size, and real-time deployment efficiency.Peer reviewe
On the Sense of Convergence in the Dyadic Representation Theorem
No full textPublisher Copyright: © Springer-Verlag GmbH Germany & The Editorial Office of AMS 2025.The dyadic representation of any singular integral operator, as an average of dyadic model operators, has found many applications. While for many purposes it is enough to have such a representation for a “suitable class” of test functions, we show that, under quite general assumptions (essentially minimal ones to make sense of the formula), the representation is actually valid for all pairs (f,g) ∈ Lp(ℝd) × Lp′(ℝd), not just test functions.Peer reviewe
Experimental thermal performance intensification of gravitational water vortex heat exchanger using hexagonal boron nitride-water nanofluid
No full textPublisher Copyright: © 2024One of the main concerns presently is the rapid improvement of thermal technology for widespread heat exchanger applications involving energy conservation and intensification of heat transfer process. For the enhancement of heat exchange processes, nanofluids have been considered as a potential substitute for conventional fluids, which in general have subpar thermal characteristics. Therefore, the present study focusses on the heat transfer enhancement and the intensification of overall thermal performance of the developed gravitational water vortex heat exchanger (GWVHE). The experimental investigation first involves the preparation and characterization of water-based hexagonal-boron nitrides (h-BN) nanofluids as well as the computation of thermophysical properties of different volume fractions of h-BN nanofluids. Subsequently, a comparative analysis evaluating the thermal energy exchange capabilities of water-to-water and water-to-h-BN nanofluids combination of two fluids has been conducted to investigate the intensification in thermal performance of the developed GWVHE. The experimental investigation is primarily based on calculating the thermal energy balance, overall heat transfer coefficient, log-mean temperature difference (LMTD) and the effectiveness of the developed GWVHE using effectiveness-NTU method. The experimental results reported that 0.02 % volume fraction of water-based h-BN nanofluids is more suitable for further testing of the developed GWVHE to mitigate the stability concerns at higher concentrations. The minimal thermal losses, that lie within the 10 % confirms the thermal energy balance and by using the h-BN nanofluids −to-water strategy for two fluids. The maximum value of heat exchange rate significantly increased from 8490 W to 9998 W with the utilization of h-BN nanofluids-to-water as compared to water-to-water combination. Furthermore, the maximum values of LMTD employing h-BN nanofluids are found to be reduced from 21.15 K to 17.53 K compared to the water-to-water combination confirming the intensification in thermal performance of GWVHE. The overall heat transfer coefficient values are also found higher when h-BN nanofluids are substituted instead of water. The maximum value of overall heat transfer coefficient for h-BN nanofluids-to-water combination is improved from 874 W/m2K to 1142 W/m2K compared to water-to-water combination. Moreover, by utilizing the h-BN nanofluids-to-water combination, the values of effectiveness are intensified by an average of 13.5 % and 9 % in both sets of testing parameters, respectively. All these maximum improvement in findings for heat exchange, overall heat transfer coefficient, effectiveness, and reduction in LMTD values are obtained by maintaining the inlet mass flow rate of cold fluid at 0.142 kg/s, while the inlet mass flow rate of hot fluid was varied in the range from 0.092 kg/s to 0.133 kg/s. Additionally, the inlet temperatures of hot and cold fluids are kept at 330 K and 296 K, respectively. Hence, the utilization of h-BN nanofluids is proven to be highly effective for boosting thermal energy exchange and enhancing the overall thermal performance of the developed GWVHE.Peer reviewe