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Food-Embedded Cold Energy Flows in Decentralised Solar Cold Chains
Authors:
Hange Lao,
Binjian Nie,
Wei He
Abstract:
Reliable cold storage is needed to reduce meat loss in informal food systems, but conventional cold-chain expansion is difficult where electricity supply is weak and battery-based solar refrigeration is costly. This study develops an hourly techno-economic optimisation framework for decentralised solar-powered cold storage in interconnected open-air meat markets. Using five meat markets in Abuja,…
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Reliable cold storage is needed to reduce meat loss in informal food systems, but conventional cold-chain expansion is difficult where electricity supply is weak and battery-based solar refrigeration is costly. This study develops an hourly techno-economic optimisation framework for decentralised solar-powered cold storage in interconnected open-air meat markets. Using five meat markets in Abuja, Nigeria, the model combines field-derived cooling demand, solar photovoltaic generation, refrigeration, battery storage, phase change material thermal storage, and directed inter-market meat flows. A key feature is that pre-chilled meat is represented as a carrier of product-embodied cooling credit, while phase change material storage remains a stationary cold-side storage component at each market. This allows cooling supplied at one market to reduce the sensible cooling load required at another market. Results show that shifting part of the storage function from battery storage to phase change material thermal storage reduces battery capacity by approximately 67\% and lowers total system cost by up to 15\% compared with battery-only systems. Allowing inter-market cooling-credit exchange further reduces total system cost by 8\% and aggregate phase change material storage capacity by 35\%, mainly by reallocating refrigeration and storage requirements across connected markets. The findings show that product flows can change where cooling services are required, allowing refrigeration and storage capacity to be coordinated across connected sites. Accounting for the product-mediated redistribution of cooling demand extends decentralised energy-system planning beyond isolated demand nodes and may inform cluster-level cooling infrastructure design in other infrastructure-constrained food networks.
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Submitted 27 July, 2026; v1 submitted 7 May, 2026;
originally announced May 2026.
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Alloying Controlled Tuning of Interfacial Spin Orbit Interaction and Magnetic Damping in Crystalline FeCo Alloys
Authors:
Hongrui Lao,
Matthias Kronseder,
Zhe Yuan,
Thomas Narr,
Thomas N. G. Meier,
Nadine Mundigl,
Christian H. Back,
Lin Chen
Abstract:
The discovery of intrinsic spin orbit fields in noncentrosymmetric ferromagnets has attracted considerable interest for both fundamental studies and technological applications. However, once such materials are synthesized, the strength of the spin orbit fields is difficult to tune because it is primarily a bulk property. Here, we demonstrate that the interfacial spin orbit interaction (SOI) in sin…
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The discovery of intrinsic spin orbit fields in noncentrosymmetric ferromagnets has attracted considerable interest for both fundamental studies and technological applications. However, once such materials are synthesized, the strength of the spin orbit fields is difficult to tune because it is primarily a bulk property. Here, we demonstrate that the interfacial spin orbit interaction (SOI) in single crystalline FeCo thin films grown on GaAs(001) can be continuously tuned via alloying. Using spin orbit ferromagnetic resonance, we find that the Lande g factor, the Gilbert damping (alpha), and the interfacial spin orbit fields exhibit a common nonmonotonic dependence on Co concentration. A pronounced minimum occurs near x ~ 0.2 where an ultra low damping alpha ~ 0.0015 is achieved. Furthermore, we observe linear scaling between alpha and (g-2)^2, establishing a direct correlation between interfacial SOI and magnetic relaxation. These results identify alloying as an effective knob to engineer interfacial SOI and damping in single crystalline ferromagnet semiconductor heterostructures.
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Submitted 28 March, 2026;
originally announced March 2026.
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A Frenet frame analysis of protein geometry: hints for secondary structure assignments
Authors:
M. Prados,
M. D. Hernández de la Torre,
F. de Soto
Abstract:
This paper deepens into the analysis of the protein secondary structure using Frenet frame to describe the curvature and torsion of the discrete curve formed by the protein $α$-carbons. We show how a simple criterion based on the evaluation of the curvature and torsion of the discrete curve can be useful to pinpoint the presence of some secondary and supersecondary structures in proteins. Moreover…
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This paper deepens into the analysis of the protein secondary structure using Frenet frame to describe the curvature and torsion of the discrete curve formed by the protein $α$-carbons. We show how a simple criterion based on the evaluation of the curvature and torsion of the discrete curve can be useful to pinpoint the presence of some secondary and supersecondary structures in proteins. Moreover, the description of proteins as fixed points of an effective action inspired by an $U(1)$ gauge model is strongly supported by the curvature and torsion observed over a large dataset of proteins in the Protein Data Bank.
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Submitted 5 December, 2025;
originally announced December 2025.
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A Neural Network approach to reconstructing SuperKEKB beam parameters from beamstrahlung
Authors:
S. Di Carlo,
G. Bonvicini,
N. A. Althubiti,
R. Ayad,
E. De La Cruz-Burelo,
I. Domínguez,
B. O. El Bashir,
H. Farhat,
J. Flanagan,
R. Gillard,
S. Izaguirre Gamez,
K. Kanazawa,
K. Kumara,
D. Liventsev,
P. L. M. Podesta-Lerma,
D. Ricalde-Herrmann,
D. Rodriguez Perez,
G. Tejeda-Muñoz,
M. Tobiyama I. Heredia de la Cruz
Abstract:
This work shows how it is possible to reconstruct SuperKEKB's beam parameters using a Neural Network with beamstrahlung signal from the Large Angle Beamstrahlung Monitor (LABM) as input. We describe the device, the model, and discuss the results.
This work shows how it is possible to reconstruct SuperKEKB's beam parameters using a Neural Network with beamstrahlung signal from the Large Angle Beamstrahlung Monitor (LABM) as input. We describe the device, the model, and discuss the results.
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Submitted 10 September, 2022; v1 submitted 23 June, 2022;
originally announced June 2022.
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Denoising Convolutional Networks to Accelerate Detector Simulation
Authors:
Sunanda Banerjee,
Brian Cruz Rodriguez,
Lena Franklin,
Harold Guerrero De La Cruz,
Tara Leininger,
Scarlet Norberg,
Kevin Pedro,
Angel Rosado Trinidad,
Yiheng Ye
Abstract:
The high accuracy of detector simulation is crucial for modern particle physics experiments. However, this accuracy comes with a high computational cost, which will be exacerbated by the large datasets and complex detector upgrades associated with next-generation facilities such as the High Luminosity LHC. We explore the viability of regression-based machine learning (ML) approaches using convolut…
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The high accuracy of detector simulation is crucial for modern particle physics experiments. However, this accuracy comes with a high computational cost, which will be exacerbated by the large datasets and complex detector upgrades associated with next-generation facilities such as the High Luminosity LHC. We explore the viability of regression-based machine learning (ML) approaches using convolutional neural networks (CNNs) to "denoise" faster, lower-quality detector simulations, augmenting them to produce a higher-quality final result with a reduced computational burden. The denoising CNN works in concert with classical detector simulation software rather than replacing it entirely, increasing its reliability compared to other ML approaches to simulation. We obtain promising results from a prototype based on photon showers in the CMS electromagnetic calorimeter. Future directions are also discussed.
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Submitted 10 February, 2022;
originally announced February 2022.
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Möbius Strip Microlasers: a Testbed for Non-Euclidean Photonics
Authors:
Yalei Song,
Yann Monceaux,
Stefan Bittner,
Kimhong Chao,
Héctor M. Reynoso de la Cruz,
Clément Lafargue,
Dominique Decanini,
Barbara Dietz,
Joseph Zyss,
Alain Grigis,
Xavier Checoury,
Melanie Lebental
Abstract:
We report on experiments with Möbius strip microlasers which were fabricated with high optical quality by direct laser writing. A Möbius strip, i.e., a band with a half twist, exhibits the fascinating property that it has a single nonorientable surface and a single boundary. We provide evidence that, in contrast to conventional ring or disk resonators, a Möbius strip cavity cannot sustain whisperi…
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We report on experiments with Möbius strip microlasers which were fabricated with high optical quality by direct laser writing. A Möbius strip, i.e., a band with a half twist, exhibits the fascinating property that it has a single nonorientable surface and a single boundary. We provide evidence that, in contrast to conventional ring or disk resonators, a Möbius strip cavity cannot sustain whispering gallery modes (WGM). Comparison between experiments and 3D finite difference time domain (FDTD) simulations reveals that the resonances are localized on periodic geodesics.
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Submitted 30 November, 2021; v1 submitted 24 November, 2020;
originally announced November 2020.
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Quantum Effects on the Free Energy of Ionic Aqueous Clusters Evaluated by Non-equilibrium Computational Methods
Authors:
Lisandro Hernández de la Peña,
Gilles H. Peslherbe
Abstract:
This paper has been withdrawn by the authors due to a copyright conflict with the Journal of Physical Chemistry B, to which it has been submitted.
This paper has been withdrawn by the authors due to a copyright conflict with the Journal of Physical Chemistry B, to which it has been submitted.
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Submitted 4 May, 2010; v1 submitted 10 September, 2009;
originally announced September 2009.