Journals
2026 EN
Zhang Weihao · Yan Zihan · Tu Yifeng
+4 more
Abstract Micro‐fluidized beds significantly enhance mass and heat transfer efficiency in gas–liquid–solid catalytic reaction systems due to their high specific surface area characteristics. However, scale effects often induce bubble coalescence and promote slugging tendencies. To address these limitations, this study utilizes a microporous distributor with apertures smaller than the particle size to compartmentalize conventional miniaturized fluidized beds, accordingly constructing a novel miniaturized confined fluidized bed. Furthermore, by employing a triple analysis framework integrating power spectral density, wavelet decomposition, and K ‐means clustering, the bubble dynamics within the confined gas–liquid–solid micro‐fluidized bed are quantitatively characterized. Based on the extracted bubble dynamics characteristics, thresholds for classing bubble motion states in the confined micro‐fluidized bed are summarized. Additionally, K ‐means clustering is utilized to objectively analyze geometric and operational parameters on bubble dynamics features, enabling the partitioning of operating gas‐velocity regimes corresponding to different bubble motion states without subjective human influence.
Journals
2026 EN
Thomas Andrew · Yates Matthew · Osborne Oliver
ABSTRACT Reinforcement learning (RL) has shown to be effective for simple automated cyber defence (ACD) type tasks. However, there are limitations to these approaches that prevent them from being deployed onto real‐world hardware. Trained RL policies will often have limited transferability across even small changes to the environment setup. Instability during training can prevent optimal learning, a problem that only increases as the environment scales and grows in complexity. This work looks at addressing these limitations with a zero‐shot transfer approach based on multi‐agent RL. This is achieved by partitioning the task into smaller network machine subtasks, where agents learn the solution to the local problem. These local agents are independent of the network scale and can therefore be transferred to larger networks by mapping the agents to machines in the new network. Initial experiments show that this transfer method is effective for direct application to a number of ACD tasks. It is also shown that its performance is robust to changes in network activity, attack scenario and reduces the effects of network scale on performance.
Journals
2026 EN
Seck Dame · Yanes Samuel · Perales Manuel
+2 more
Plastic pollution in water bodies threatens and disrupts aquatic life, requiring effective cleanup solutions. This paper proposes a strategy for plastic cleanup using a fleet of autonomous surface vehicles in a multitask scenario, with a focus on both exploration and cleaning tasks. The mission is decoupled into two phases: an exploration phase for locating trash and a cleaning phase for collection. A Multitask Deep Q‐Network with two heads estimates Q ‐values for each task, and all ASVs share the same policy through an egocentric state formulation to enhance scalability. A multiobjective learning approach is applied, resulting in distinct policies that balance the duration of the exploration and cleaning phases, leading to the construction of a Pareto front, which provides a visual representation of trade‐offs between task priorities. The framework adapts to various environmental conditions, demonstrated in both the larger Malaga Port and the smaller Alamillo Lake. The study also highlights the importance of a dedicated exploration phase for larger areas, while minimal exploration is sufficient for smaller spaces. Compared to the decomposition weighting sum strategy, the approach consistently produces superior Pareto‐optimal policies, ensuring broader and more effective exploration of the objective space.
Journals
2026 EN
Ze Qiji · Huang Shuhao · Chang Yilong
+3 more
Insulin pumps typically use piston‐based mechanisms with bulky transmission components to convert rotary motion into the piston's forward motion. These mechanical transmission systems and insulin reservoirs occupy more than one‐third of pumps’ volume, significantly limiting miniaturization and making pumps cumbersome for daily use. Herein, a compact, magnetically actuated insulin pump is developed that is less than one‐quarter the size of piston‐based pumps. Instead of bulky mechanical components, the pump uses a magnetic soft actuator to directly compress the insulin chamber, controlled by a precisely tuned electromagnetic field. This innovative design eliminates the need for large transmission systems, enabling a notably smaller form factor. In addition, the fine‐tunable magnetic actuation enables a 0.01 μL delivery resolution, significantly surpassing the 0.25 μL resolution of piston‐based pumps. This high‐resolution mechanism facilitates further miniaturization by allowing the use of high‐concentration insulins, thereby reducing the reservoir size. By varying the magnetic field's waveform, amplitude, and duration, the pump's performance can be further enhanced. The reported magnetic insulin pump exhibits superior repeatability and accuracy across single‐pulse, basal, and bolus modes compared to commercial insulin pumps. This miniaturized, high‐resolution magnetic insulin pump is anticipated to substantially benefit people with diabetes by improving portability, precision, and cost efficiency.
Journals
2026 EN
MarinLlobet Arnau · SánchezManso Sergio · Manasanch Arnau
+7 more
This study investigates the application of Riemannian geometry‐based methods for brain decoding using invasive electrophysiological recordings. While Riemannian geometry has been successfully applied in noninvasive settings, its utility for invasive datasets, which are typically smaller and scarcer, remains less explored. Herein, a minimum distance to mean (MDM) classifier is proposed using a Riemannian geometry approach based on covariance matrices extracted from intracortical local field potential (LFP) recordings across various regions during different brain state dynamics. For benchmarking, the performance of the approach is evaluated against convolutional neural networks (CNNs) and Euclidean MDM classifiers. The results indicate that the Riemannian geometry‐based classification not only achieves a superior mean F1 macro‐averaged score across different channel configurations but also requires up to two orders of magnitude less computational training time. Additionally, the geometric framework reveals distinct spatial contributions of brain regions across varying brain states, suggesting a state‐dependent organization that traditional time series‐based methods often fail to capture. The findings align with previous studies supporting the efficacy of geometry‐based methods and extend their application to invasive brain recordings, highlighting their potential for broader clinical use, such as brain‐computer interface applications.
Journals
2026 EN
Sytsma Jack · Ricker Allison · Winters Helen
+4 more
Abstract Premise Understanding how plant populations adapt to water limitation through stomatal traits is key to predicting drought responses. The dominant C 4 grass Andropogon gerardi , distributed across sharp climate gradients in North America, offers an excellent focal species to study stomatal architecture (size and density). Using a common garden, we tested how stomatal architecture relates to home climate, how stomatal architecture influences gas exchange, and how experimental drought affects these responses in a greenhouse. We hypothesized that aridity drives stomatal architecture and that experimental drought reduces the size of stomata but increases their density to maintain photosynthesis. Methods We measured stomatal architecture and gas exchange in 25 populations sourced across temperature (4–21°C) and precipitation (350–1400 mm yr⁻¹) gradients under well‐watered conditions. Eight populations (precipitation: 472–1356 mm yr⁻¹) were then subjected to drought (~15% moisture) or were well‐watered (30% control) to assess trait plasticity. Stomatal traits were measured using epidermal peels and light microscopy, gas exchange with a LI‐COR 6400, and network analyses were used to characterize adaptive strategies. Results Arid populations exhibited smaller, denser stomata compared to wet populations, and networks demonstrated a trade‐off between stomatal size and density. In the experimental drought, stomatal size decreased. while density increased, with dry populations showing fewer changes than wet populations. Key traits in the network were stomatal size and water‐use efficiency. Conclusions Andropogon gerardi demonstrated adaptive changes in stomatal architecture. Our findings emphasize the interplay between adaptation and climate, providing important insights into how plants may respond to increased droughts.
Journals
2026 EN
Camargo Maria Gabriela Gutierrez · Arista Montserrat · Bergamo Pedro Joaquim
+2 more
Abstract Premise Flower color diversity within communities is shaped by biotic and abiotic factors. Pollinators often prefer specific colors, and floral pigments also help protect against abiotic factors such as ultraviolet (UV) radiation, precipitation, and temperature. Along altitudinal gradients, variations in biotic and/or abiotic conditions can drive the spatial distribution of flower color diversity at the community level. Methods Across five vegetation types in the Brazilian campo rupestre, a highly diverse tropical mountain grassland with an environmental mosaic of vegetation types, we surveyed floral color traits of 179 plant species from 180 plots distributed along an altitudinal gradient (808–1427 m). We related flower color traits to pollination systems, abiotic factors (soil type, temperature, and precipitation), and elevation to investigate their influence on flower color diversity. Results An association between flower colors and pollination systems was coupled with a functional divergence of color traits along the environmental mosaic, indicating that both, biotic and abiotic factors, shape color diversity in the campo rupestre. Despite this functional divergence, flower color diversity levels were similar across vegetation types and decreased slightly with elevation. Such maintenance of functional diversity contrasts with the sharp reductions in color diversity observed with elevation in temperate mountains. Conclusions Our results indicate that flower color diversity is maintained across environmental gradients when pollination systems are unconstrained by elevation, a characteristic of old tropical mountain systems.
Journals
2026 EN
Fryer Emma R. · O'Dell Ryan · Grossenbacher Dena L.
+3 more
Abstract Premise Plant species with affinity for harsh substrates often have well‐defined edaphic (soil) niches and are ideal for exploring questions of community assembly. Vertic clay soils are chemically and physically challenging to plant establishment and productivity, and annual plant communities associated with these soils of the San Joaquin Desert (California, USA) form a distinctive mosaic pattern of species that reflects differences in soil properties across the landscape. Methods We analyzed soil properties to determine how heterogeneous soils at two field sites in the San Joaquin Desert differed among the realized niches of 12 native annual forb species with an affinity for vertic clay soils. We then conducted a pot study with the same species to test if species differed in their realized and fundamental edaphic niches, and to examine the competition effects of an invasive annual grass ( Bromus rubens ) on these species’ edaphic niches. Results From our field study, we found some differences in the vertic clay soils between the realized niches of species at both sites. In our pot study, we found species had similar fundamental edaphic niche optima in our treatment soils and that several species’ competitive ability varied with the edaphic stress in our treatment soils. For some species, differences in competitive ability led to shifts in edaphic niche optima, likely contributing to more divergent realized niches. Conclusions The combination of competitive pressure and abiotic stress drove differences between the realized niche and fundamental niche for species in a novel, heterogeneous study system.
Journals
2026 EN
Hjelm Linnea L. · Brown Aishia A. · Fisher Benjamin W.
+2 more
Abstract As young people explore and reflect on the conditions of their neighborhoods and communities, they can forge a critical consciousness—merging their perspectives and analysis to direct both individual and collective actions. Photovoice is a methodological tool that allows participants to document their perspectives and analysis and discuss with peers what is needed for social change. In this study, members of a local government youth program engaged in Photovoice with the ultimate goal of exploring problems and possible solutions from their points of view. Through dialogue of their selected photos, participants name a variety of structural causes of neighborhood neglect and abandonment. However, when encouraged to consider the solutions to those issues, participants predominantly identify individual or community‐level actions. We discuss the implications of this discord in the context of literature on critical consciousness and social justice youth development, with the hope of informing policy and practice decisions that can facilitate the empowerment of young people and elevate community well‐being.
Journals
2026 EN
Shahin Hana · Patka Mazna · Smail Linda
Abstract This study analyzes the localization of a US‐designed Social Innovation course in the UAE as a contested site of knowledge production rather than a straightforward curricular adaptation. Using reflexive thematic analysis of lesson plans and faculty reflections, we identified two themes: Curricular Containment and Cultural Substitution Without Epistemic Transformation. These demonstrate how localization efforts simplified content and replaced cultural references without embedding local epistemologies or challenging dominant frameworks. Rather than increasing relevance, these adaptations risked reinforcing the coloniality of knowledge and contributed to what we label symbolic epistemicide, the structural erasure of non‐Western ways of knowing through institutional and curricular design. We argue that meaningful localization must go beyond surface‐level representation to center Arab, Islamic, and Emirati knowledge systems through sustained collaboration with local scholars and communities. This requires rethinking pedagogy, authorship, and authority to foster more just, pluralistic approaches to curriculum development in transnational educational settings.