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Particle transport from first principles in the early heliosphere: κ1 Ceti as a case study for the young Sun
(IOP Publishing, 2026) Engelbrecht, N. Eugene; Herbst, Konstantin; Scherer, Klaus; Oughton, Sean; Airapetian, Vladimir S.
Several studies of Galactic cosmic-ray (GCR) modulation within the astrospheres of stars deemed to be proxies for the young Sun have concluded that the intensities of these particles would, at early stages of the Sun’s evolution, be negligible at 1 au. These studies, however, do not take into account the varying interstellar conditions the young Sun would have encountered as it traversed its Galactic orbit, nor do they realistically model the transport of GCRs. The present study, for the first time, examines the influence of various interstellar parameters in the Galactic spiral arms on the astrosphere of κ1 Ceti, a young Sun proxy, through magnetohydrodynamic modelling. We demonstrate that these conditions lead to an astrosphere with considerably smaller dimensions than previous estimates. We also model the transport of turbulence parameters within said astrosphere for the first time, demonstrating that turbulence levels could be significantly higher than observed in the heliosphere. Finally, these insights are implemented in a 3D, ab initio GCR transport model to compute GCR intensities at 1 au, demonstrating the importance of drift effects in astrospheric modulation: full drift effects lead to GCR intensities comparable to modern observations, while turbulence-reduced drift coefficients lead to significantly smaller intensities.
Towards sustainable IoT: A digital signature‐enhanced federated learning approach
(Wiley, 2025) Qureshi, Shahida Hafeezan; Malik, Saif Ur Rehman; Haseeb, Junaid; Moqurrab, Syed Atif; Bukht, Tanvir Fatima Naik; Srivastava, Gautam
Federated Learning (FL) is emerging as a premier paradigm for privacy‐preserved Machine Learning (ML), enabling devices to train models without central data pooling collaboratively. In the contemporary Internet of Things (IoT) landscape, characterized by escalating energy consumption and associated carbon footprint, FL is recognized not merely for its privacy features. Intrinsic to decentralized architectures such as FL, secure communication is based on digital signatures to guarantee integrity. This is particularly evident in sensitive sectors such as the Internet of Vehicles (IoV), banking, and healthcare. Integrating FL becomes imperative and intricate as these sectors are intertwined with the IoT fabric. Our study unveils “Secure Federated Learning Framework (SecFL),” a pioneering decentralized framework combining FL and sustainable computing. SecFL offers defences against adversarial attacks such as data poisoning and label flipping. Utilizing the Rivest‐Shamir‐Adleman (RSA) asymmetric encryption algorithm for securing digital communications and transactions, combined with ElGamal encryption and a private Ethereum blockchain, ensures enhanced client‐specific security. Our research emphasizes the formal modeling of adversarial dynamics using High‐Level Petri nets (HLPN) within the FL‐IoT ecosystem, balancing system dynamics and energy conservation. Our model consistently outperforms contemporary solutions in accuracy and time efficiency after validation. As IoT burgeons into domains like environmental monitoring, smart cities, and energy grids, the SecFL framework, fostering FL, optimizes energy utilization and bolsters resource efficiency. In our comparative analysis, the Elliptic Curve Digital Signature Algorithm (ECDSA) algorithm demonstrates superior transaction latency and verification time compared to RSA and Elliptic Curve Cryptography (ECC).
Cultural dimensions of Indigenous trade: A summary of te ao Māori value frameworks
(Te Kotahi Research Institute, University of Waikato, 2026-01) Sterling, Rogena; Hudson, Maui; Kusabs, Natalie; Forde, Xavier
This working paper, part of the MBIE-funded ‘Tauhokohoko’ research project, investigates how Māori frameworks for wellbeing and economic development can inform the creation of a transformative Indigenous trade model. The project seeks to define Indigenous trade and its potential to reshape trade policy, enabling mana motuhake (self-determination) and fostering climate-resilient, holistic wellbeing (waiora). Key Context and Approach Global economic systems often prioritise profit over cultural and environmental values. In contrast, Māori trade integrates cultural principles to support community and ecological flourishing. This paper analyses thirteen distinct Māori wellbeing and economic development frameworks—from government, academic, and iwi sources—to identify common values, outcomes, and indicators. These are mapped against the project’s three core outcome areas: Mana Motuhake, Huanga (benefits), and Waiora. Core Findings: A Coherent, Values-Based Paradigm Despite diverse origins, the frameworks reveal a remarkably consistent and robust philosophical foundation that challenges conventional economics. Key recurring principles include: • Rangatiratanga / Mana Motuhake: The right and responsibility for self-determination is central. This extends beyond political autonomy to Māori-led governance of economic, social, and cultural pathways, ensuring trade policies are by and for Māori. • Holistic Huanga (Benefits): Success is defined multi-dimensionally, encompassing cultural vitality, social cohesion, environmental health, and spiritual wellbeing alongside economic prosperity. Models like the Economy of Mana emphasise reciprocity and wealth distribution for the collective good, contrasting with individualistic, profitmaximising paradigms. • Kaitiakitanga (Guardianship): The economy is embedded within an ecological context. Sustainability is an ethical imperative at the core of economic practice, demanding trade that protects natural resources for future generations. • Relationality (e.g., Whanaungatanga): Economic activity is seen as a means to build and strengthen respectful, long-term relationships and kinship networks, moving beyond purely transactional partnerships. Implications for an Indigenous Trade Framework The analysis demonstrates that a transformative Indigenous trade framework must be built on this values-based foundation. It requires: 1. Māori Leadership: Policies must be driven by Māori to actualise mana motuhake. 2. Broad Measurement: New systems are needed to capture the full spectrum of cultural, social, environmental, and economic benefits (huanga). 3. Values-Based Practice: Trade must operationalise principles like kaitiakitanga and whanaungatanga to ensure sustainability and foster respectful partnerships. Conclusion The reviewed frameworks provide a proven philosophical guide and practical indicators for building an alternative trade system. They show that an economically viable, culturally affirming, and environmentally sustainable model is not only possible but deeply rooted in te ao Māori. The Tauhokohoko project’s challenge and opportunity is to translate this rich knowledge into actionable trade policy that delivers holistic wellbeing for Indigenous peoples and offers a constructive alternative for the global community.
Salvador Urban Network Transportation (SUNT): A landmark spatiotemporal dataset for public transportation
(Springer, 2025) Ferreira, Marcos V.; Souza, Matheus; Rios, Tatiane N.; Fernandes, Islame F. C.; Nery, Jorge; Gama, João; Bifet, Albert; Rios, Ricardo A.
Efficient public transportation management is essential for the development of large urban centers, providing several benefits such as comprehensive coverage of population mobility, reduction of transport costs, better control of traffic congestion, and significant reduction of environmental impact limiting gas emissions and pollution. Realizing these benefits requires a deeply understanding the population and transit patterns and the adoption of approaches to model multiple relations and characteristics efficiently. This work addresses these challenges by providing a novel dataset that includes various public transportation components from three different systems: regular buses, subway, and BRT (Bus Rapid Transit). Our dataset comprises daily information from about 700,000 passengers in Salvador, one of Brazil’s largest cities, and local public transportation data with approximately 2,000 vehicles operating across nearly 400 lines, connecting almost 3,000 stops and stations. With data collected from March 2024 to March 2025 at a frequency lower than one minute, SUNT stands as one of the largest, most comprehensive, and openly available urban datasets in the literature.
Estimation of effective viscosity to quantify collisional behavior in collisionless plasma
(IOP Publishing, 2025) Adhikari, Subash; González, Carols A.; Yang, Yan; Oughton, Sean; Pecora, Francesco; Bandyopadhyay, Riddhi; Matthaeus, William H.
While dissipation in collisional plasma is defined in terms of viscosity and resistivity, the exact functional form of dissipation, i.e., the so-called dissipation function in nearly collisionless plasma, is unknown. Nevertheless, previous studies have suggested that there exists viscous-like energy conversion in collisionless plasma with scaling characteristics analogous to collisional plasma, and in particular that the average dissipation is proportional to the square of the rate of strain as in hydrodynamics. In this study, using 2.5D kinetic particle-in-cell (PIC) simulation of collisionless plasma turbulence, we provide an estimate of effective viscosity at each scale, obtained via a scale-filtering approach. We then compare the turbulent dynamics of the PIC simulation with that from MHD and two-fluid simulations in which the viscosity is equal to the effective viscosity estimate obtained from the PIC simulation. We find that the global behavior in these MHD and two-fluid simulations has a striking similarity to that in their kinetic/PIC counterpart. In addition, we explore the scale dependence of the effective viscosity and discuss implications of this approach for space plasmas.