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Tensor-to-tensor models with fast iterated sum features
Get PDFDesigning expressive yet computationally efficient layers for high-dimensional tensor data (e.g., images) remains a significant challenge. While sequence modeling has seen a shift toward linear-time architectures, extending these benefits to higher-order tensors is non-trivial. In this work, we introduce the Fast Iterated Sums (FIS) layer, a novel tensor-to-tensor primitive with linear time and space complexity relative to the input size. Theoretically, our framework bridges deep learning and algorithmic combinatorics: it leverages “corner tree” structures from permutation pattern counting to efficiently compute 2D iterated sums. This formulation admits dual interpretations as both a higher-order state-space model (SSM) and a multiparameter extension of the Signature Transform. Practically, the FIS layer serves as a drop-in replacement for standard layers in vision backbones. We evaluate its performance on image classification and anomaly detection. When replacing layers in a smaller ResNet, the FIS-based model achieves accuracy of a larger ResNet baseline while reducing both trainable parameters and multiply-add operations. When replacing layers in ConvNeXt tiny, the FIS-based model saves around 2% of parameters, has around 8% shorter time per epoch and improves accuracy by around 0.6% on CIFAR-10 and around 2% on CIFAR-100. Furthermore, on the texture subset of MVTec AD, it attains an average AUROC of 97.3%. The code is available at https://github.com/diehlj/fast-iterated-sums
Small-signal stability and inertia constrained optimal configuration method of grid-forming energy storage systems
Get PDFWith the increasing penetration of renewable energy sources and power electronic converters, the grid strength and inertia of modern power systems have significantly declined, potentially leading to various stability challenges, such as small-signal stability and frequency stability. It is widely recognized that the integration of grid-forming (GFM) energy storage systems (ESS) can mitigate these issues and enhance the stable operation of power systems from multiple perspectives. However, determining the optimal configuration of GFM ESS in hybrid systems to balance stability and economic efficiency remains an open research question. To bridge this gap, this paper proposes an optimization method for GFM ESS configuration considering stability constraints. First, based on the small-signal model of the multi-converter system, the relationship between system stability and the placement and capacity of GFM ESS is established, and stability criteria are derived. On this basis, both small-signal stability constraints and inertia constraints are incorporated, formulating the GFM ESS configuration problem as a mixed-integer programming problem. Finally, a relaxation method for eigenvalue constraints and a two-layer iterative algorithm are proposed to solve the optimization problem efficiently. Case studies conducted on the IEEE 39-bus system and the fully inverter-based system validate the accuracy and general applicability of the proposed configuration method
From barriers to gateways : leveraging institutional change for SMEs’ access to international markets
No full textThis paper examines the processes involved in leveraging institutional change to facilitate SMEs’ access to international markets. Drawing on institutional theory and rich qualitative data from 70 interviews in Kyrgyzstan across two time periods, it reveals a nuanced interplay between the reinforcement of formal institutions and the decline of outdated informal practices, as well as the influence of these changes on SMEs' actions. We find that SMEs’ successful access to international markets stems from their distinct adaptive responses to simultaneous improvements in formal institutions and the reshuffling of informal ones. This enables SMEs to channel institutional change through deliberate behavioral responses toward access to international markets. The study suggests that the evolution of formal institutions alone may not suffice; tackling entrenched, historically embedded, and detrimental informal institutions inherited from the Soviet past is crucial to overcoming barriers to accessing international markets. With more transparent formal and informal institutions and practices, exporting SMEs gain access to resources and capabilities, further enabling their progression from exporting to contracted participation in GVC. Our study, therefore, contributes to discussions in International Business literature on the role of context-specific institutions in local SMEs’ internationalization behavior. It highlights the importance of considering the combined role of formal and informal institutional change in providing adequate conditions for accessing international markets, particularly in transition countries, thereby providing policymakers and businesses operating in these contexts with empirically grounded practical insights
Deep learning identifies the climate warming signal in global ocean chlorophyll from satellite records
Get PDFSatellite remote sensing of chlorophyll-a (Chl-a) provides the only continuous global-scale monitoring of phytoplankton abundance for over two decades. While certain trends have been observed in the satellite Chl-a data, it remains uncertain whether the changes are attributable to climate warming, because the data is not long enough to separate the role of climate warming from natural variability. Here, using a deep-learning model trained with an ensemble of 10 Earth System Model (ESM) simulations, we identified the climate-warming signal in satellite-derived global Chl-a fields. By comparison, a null model trained on ESM simulations forced only by natural variability was unable to identify a warming signal, confirming the role of climate warming. The warming signal is primarily derived from the spatial pattern of global Chl-a trends, and eastern and western boundary regions are most sensitive to warming. Our results explicitly reveal the ongoing climate-warming effect on global marine phytoplankton this century
Effects of WEC geometry on the performance of a WEC array-VLFS integrated system
Get PDFThis study focuses on analysing the effects of wave energy converter (WEC) geometry on the performance of an integrated system comprising a WEC array and a very large floating structure (VLFS). A numerical model of the integrated system is established based on multi-body potential theory, the discrete-module-beam (DMB) method, and the Lagrange multiplier technique. After validating the accuracy of the simulation approach, the present study examines the energy capture efficiency and hydroelastic response of the integrated system with various WEC geometry parameters, including length, width, draft, and shape. Owing to the complexity of the physical model of the integrated system, it is difficult to determine the optimal Power Take-Off (PTO) damping coefficient analytically. Therefore, a numerical search method is employed to obtain the PTO damping coefficients corresponding to different WEC geometry parameters. After a series of numerical simulations, the results reveal that, compared to the other three geometry parameters, the power output of the integrated system is more sensitive to the WEC length. Moreover, the incorporation of the WEC array leads to a significant reduction in the hydroelastic response of the VLFS. In addition, the draft and shape of the WEC exhibit limited influence on the structural response of the VLFS. All in all, the analytical methodology and framework presented in this paper can offer some insights for the design of similar integrated systems
High-resolution atomic magnetometer-based imaging of integrated circuits and batteries
Get PDFOptically pumped magnetometers (OPMs) have emerged as a powerful technique for high-resolution magnetic field imaging. However, achieving sub-millimeter spatial resolution at sub-picotesla sensitivities (< 1 pT/ √ Hz) remains challenging, particularly under finite-field conditions. We present a high-resolution magnetic imaging system based on a free-induction-decay (FID) OPM integrated with a two-axis scanning micromirror for automated beam steering. The double-pass optical configuration allows millimeter-scale devices under test (DUTs) to be positioned directly behind the vapor cell. This enables a standoff distance of 2.7 mm between the magnetic source and the atomic vapor, improving practical imaging resolution by increasing the amplitude of near-field magnetic signals sampled within the sensitive volume. Spatial resolution is experimentally demonstrated by imaging a custom printed circuit board (PCB) containing antiparallel copper tracks spaced 2 mm apart, with measured field maps in close agreement with Biot–Savart predictions. The OPM achieves an optimal field sensitivity of 0.5 pT/ √ Hz, demonstrating the system’s capability for high-precision magnetic field measurements. The imaging system is further validated by resolving polarity-dependent asymmetries in a bridge rectifier integrated circuit (IC) and tracking current dynamics in a ceramic battery in situ. These results highlight the potential of OPM-based systems for noninvasive diagnostics of electronic circuits and batteries
Guidelines for evaluating endothelial function in vascular tissue
No full textThe endothelium plays a central role in maintaining vascular homeostasis by orchestrating vascular tone, inflammation, healing, permeability, and thrombosis. Assessing endothelial function in vascular tissue is essential for understanding the cellular and molecular mechanisms underlying cardiovascular physiology and pathology. Traditional approaches, such as wire and pressure myography, have been instrumental in defining endothelium-dependent responses and identifying key pharmacological targets. However, the complexity and heterogeneity of endothelial cells across vascular beds, and their dynamic phenotypic changes in health and disease, necessitate the incorporation of new investigative strategies. Emerging methodologies, including bulk and single-cell transcriptomics, proteomics, and advanced imaging, now provide unprecedented insights into endothelial cell diversity and function. A team of leading experts in the field, who collectively reached a consensus on the most widely used techniques to evaluate endothelial function, developed these guidelines. The document establishes best practices for assessing endothelial function, from endothelial cell cultures to isolated vascular tissues, integrating conventional functional assays with modern molecular approaches. By fostering methodological consistency and embracing innovation, our goal is to enhance rigor, reproducibility, understanding, and discovery in endothelial biology
Mechanism and dielectric performance of copper-doped activated carbon in natural rubber composites : combined experimental and DFT study
No full textThis research investigates the influence of copper-modified activated carbon (Cu-AC) on the structure, electrical properties, mechanical properties, thermal properties, and vulcanisation behaviour of natural rubber (NR) composite materials, aiming to clarify the role of copper in interfacial interactions and vulcanisation chemistry. Cu-AC containing 1% and 2% copper was introduced into NR at a fixed loading of 10 phr, and the resulting NR composites were analyzed using FTIR, XRD, SEM/EDX, mobile viscometer, TGA, DSC, and density functional theory (DFT) calculations. The incorporation of Cu-AC remarkably improved dielectric performance, with the dielectric permittivity increasing to ε' = 8.63 at 1 kHz for the 2% Cu-AC NR composite, compared with 3.92 for unmodified activated carbon and 1.72 for neat NR, while maintaining a low dielectric loss of 0.0006. Mechanical properties were also improved, as tensile strength increased from 5.97 MPa for neat NR to 12.34 MPa and 14.40 MPa for composites containing 1% and 2% Cu-AC, respectively. FTIR combined with DFT analysis indicates that copper participates in the curing process through Cusingle bondS coordination and preferential adsorption of mercaptobenzothiazole (MBT) (Eads = −2.18 eV), thereby influencing crosslink density and curing behaviour. In summary, the results show that copper-modified biomass-derived activated carbon can improve both the dielectric response and mechanical performance of NR composite materials, supporting their potential for use as sustainable and flexible multi-purpose materials, consistent with the Bio-Circular-Green (BCG) model
Form III of artemisinin: : discovery and crystallographic characterisation of a new high-pressure polymorph
No full textArtemisinin (ART) is mainly used for the treatment of malaria and exhibits polymorphism with two known crystalline forms. In this study, the high-pressure behaviour of these two polymorphs was investigated to evaluate their compressibility and identify if any pressure-induced phase transitions occur with a view to assessing the impact of manufacturing pressure on the active pharmaceutical ingredient (API). Form I, the orthorhombic polymorph, was found to be the most compressible of the three. Form II, a triclinic phase, undergoes a phase transition to a new polymorph that is observed at different pressures depending on the pressure transmitting medium used. The transition to Form III occurs at 0.75 GPa when compressed in petroleum ether, however, this transition is delayed to 2.02 GPa in silicone oil highlighting the influence of the pressure-transmitting medium on the stability of the crystal structure. The newly characterised, Form III, shares structural similarities with Form II but differs in symmetry where a pseudo-2₁ screw axis in Form II become a formal 2₁ screw axis in Form III, resulting in a change from triclinic to monoclinic crystal system and a reduction of the asymmetric unit from Z′ = 4 to Z′ = 2. These findings contribute to a deeper understanding of pressure-induced polymorphism in ART and underscores the importance of external factors such as pressure transmitting medium in influencing solid-state transitions relevant to pharmaceutical processing and formulation
Health and Social Care Workforce Survey : Experience, Opportunities and Attitudes to Digital Working – Summary Report
No full textThis report summarises findings from an anonymised digital skills and experience survey conducted by DHI in April 2025 across a rural integrated Health and Social Care partnership. Ninety six respondents from both local authority and health service teams provided insights into their access to digital tools, digital work habits, confidence levels, and training needs. While most staff reported positive attitudes toward digital working and recognised the benefits of digital tools for efficiency and convenience, significant challenges remain. These include inconsistent device quality, connectivity issues, limited time for training, and complex or outdated systems. Respondents expressed strong demand for practical, role specific learning opportunities, particularly in basic IT skills, data literacy, and specialist systems. Differences between NHS and local authority staff highlight the need for tailored approaches to capability building. The report offers recommendations to strengthen infrastructure, expand training, improve organisational support, and foster a culture of digital innovation to enable effective digital transformation
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