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\"A high stakes dystopian drama about finding humanity in a world torn apart by violence.\"--Back cover.
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Enhancing the Sustained Capability of Continual Test-Time Adaptation with Dual Constraints
Continuous Test-Time Adaptation aims to adapt a source model to continuously and dynamically changing target domains. However, previous studies focus on adapting to each target domain independently, treating them as isolated, while ignoring the interplay of interference and promotion between domains, which limits the model’s sustained capability, often causing it to become trapped in local optima. This study highlights this critical issue and identifies two key factors that limit the model’s sustained capability: (1) The update of parameters lacks constraints, where domain-sensitive parameters capture domain-specific knowledge, leading to unstable channel representations and interference from old domain knowledge and hindering the learning of domain-invariant knowledge. (2) The decision boundary lacks constraints, and distribution shifts, which carry significant domain-specific knowledge, cause features to become dispersed and prone to clustering near the decision boundary. This is particularly problematic during the early stages of domain shifts, where features are more likely to cross the boundary. To tackle the two challenges, we propose a Dual Constraints method: First, we constrain updates to domain-sensitive parameters by minimizing the representation changes in domain-sensitive channels, alleviating the interference among domain-specific knowledge and promoting the learning of domain-invariant knowledge. Second, we introduce a constrained virtual decision boundary, which forces features to move away from the original boundary, and with a virtual margin to prevent features from crossing the decision boundary due to domain-specific knowledge interference caused by domain shifts. Extensive benchmark experiments show our framework outperforms competing methods.
Journal Article
Intestinal Response to Acute Intragastric and Intravenous Administration of Phosphate in Rats
Phosphate (Pi) homeostasis is controlled by the intestine and kidneys whose capacities to transport Pi are under endocrine control. Several studies point to intestinal absorption as a therapeutic target to modulate Pi homeostasis. The small intestine is responsible for almost all Pi absorption in the gut, a process involving Na
-dependent and independent mechanisms. Three Na
-dependent Pi cotransporters have been described in the gastrointestinal tract: NaPi-IIb (a SLC34 member) and Pit-1 and Pit-2 (SLC20 transporters). We recently analysed the acute hormonal and renal response to intragastric (i.g) and intravenous (i.v) Pi-loading. This study demonstrated that the kidney quickly adapts to Pi-loading, with changes manifesting earlier in the i.v than i.g intervention. The aim of this work was to extend the previous studies in order to investigate the acute adaptation of intestinal transport of Pi and expression of intestinal Na
/Pi-cotransporters in response to acute Pi-loading.
Duodenal and jejunal mucosa was collected 40 minutes and/or 4 hours after administration (i.g and i.v) of either NaCl or Pi to anaesthetized rats. Uptakes of Pi and protein expression of Na
/Pi cotransporters were measured in brush border membrane vesicles (BBMV); the cotransporters' mRNA abundance was quantified by real-time PCR in total RNA extracted from whole mucosa.
Pi-loading did not modify transport of Pi in duodenal and jejunal BBMV 4 hours after treatment. Administration of Pi did not alter either the intestinal expression of NaPi-IIb and Pit-2 mRNAs, whereas Pit-1 mRNA expression was only regulated (diminished) in duodenum collected 4 hours after i.g Pi-loading. NaPi-IIb protein expression was decreased in duodenum 4 hours upon i.v Pi infusion, whereas the duodenal and jejunal abundance of the cotransporter was unaffected by i.g administration of Pi.
Together, these data suggest that the intestine responds acutely to Pi-loading, though this response seems slower than the renal adaptation.
Journal Article
A Semi-Supervised Domain Adaptation Method for Sim2Real Object Detection in Autonomous Mining Trucks
In open-pit mining, autonomous trucks are essential for enhancing both safety and productivity. Object detection technology is critical to their smooth and secure operation, but training these models requires large amounts of high-quality annotated data representing various conditions. It is expensive and time-consuming to collect these data during open-pit mining due to the harsh environmental conditions. Simulation engines have emerged as an effective alternative, generating diverse labeled data to augment real-world datasets. However, discrepancies between simulated and real-world environments, often referred to as the Sim2Real domain shift, reduce model performance. This study addresses these challenges by presenting a novel semi-supervised domain adaptation for object detection (SSDA-OD) framework named Adamix, which is designed to reduce domain shift, enhance object detection, and minimize labeling costs. Adamix builds on a mean teacher architecture and introduces two key modules: progressive intermediate domain construction (PIDC) and warm-start adaptive pseudo-label (WSAPL). PIDC builds intermediate domains using a mixup strategy to reduce source domain bias and prevent overfitting, while WSAPL provides adaptive thresholds for pseudo-labeling, mitigating false and missed detections during training. When evaluated in a Sim2Real scenario, Adamix shows superior domain adaptation performance, achieving a higher mean average precision (mAP) compared with state-of-the-art methods, with 50% less labeled data required, achieved through active learning. The results demonstrate that Adamix significantly reduces dependence on costly real-world data collection, offering a more efficient solution for object detection in challenging open-pit mining environments.
Journal Article
Nine Maxims for the Ecology of Cold-Climate Winters
Frozen winters define life at high latitudes and altitudes. However, recent, rapid changes in winter conditions have highlighted our relatively poor understanding of ecosystem function in winter relative to other seasons. Winter ecological processes can affect reproduction, growth, survival, and fitness, whereas processes that occur during other seasons, such as summer production, mediate how organisms fare in winter. As interest grows in winter ecology, there is a need to clearly provide a thought-provoking framework for defining winter and the pathways through which it affects organisms. In the present article, we present nine maxims (concise expressions of a fundamentally held principle or truth) for winter ecology, drawing from the perspectives of scientists with diverse expertise. We describe winter as being frozen, cold, dark, snowy, less productive, variable, and deadly. Therefore, the implications of winter impacts on wildlife are striking for resource managers and conservation practitioners. Our final, overarching maxim, “winter is changing,” is a call to action to address the need for immediate study of the ecological implications of rapidly changing winters.
Journal Article
A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition
Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle).
Journal Article
Autopolyploidy-driven range expansion of a temperate-originated plant to pan-tropic under global change
Angiosperms are believed to have emerged initially in the tropics and expanded their distribution range poleward through diverse mechanisms, for example polyploidization-driven cold tolerance evolution. Reversed expansion from temperate to pan-tropic climates through a polyploidization-driven shift in heat tolerance remains largely unknown. Here, we found autopolyploidy in relation to the global expansion of Solidago canadensis from its temperate-climate native range in North American to hot-summer climate in an introduced range. Our cytogeographical study of 2,062 accessions from 471 locations worldwide demonstrates that ploidy levels correlate negatively with latitude and positively with average temperature. An isotherm-dependent shift of the climate niches at the threshold of 20°–24°C between geo-cytotypes can be attributed mainly to autopolyploidy-driven differentiation of heat tolerance; only polyploids and not diploids are able to complete sexual reproduction, germinate, and grow in the hot-summer climate of low latitudes. Ploidy-dependent fertility appears to play a key role in the hot-summer introduced range in the northern hemisphere through both pre-adaptation and rapid post-introduction adaptive evolution of delayed flowering and improved heat tolerance during embryo development. The MaxEnt model predicts continued expansion of this plant species under global change. These results provide new insights into the mechanisms governing autopolyploidy-driven backward range expansion of plant species from temperate origins.
Journal Article
Natural variation in the HAN1 gene confers chilling tolerance in rice and allowed adaptation to a temperate climate
Rice (Oryza sativa L.) is a chilling-sensitive staple crop that originated in subtropical regions of Asia. Introduction of the chilling tolerance trait enables the expansion of rice cultivation to temperate regions. Here we report the cloning and characterization of HAN1, a quantitative trait locus (QTL) that confers chilling tolerance on temperate japonica rice. HAN1 encodes an oxidase that catalyzes the conversion of biologically active jasmonoyl-L-isoleucine (JA-Ile) to the inactive form 12-hydroxy-JA-Ile (12OH-JA-Ile) and fine-tunes the JA-mediated chilling response. Natural variants in HAN1 diverged between indica and japonica rice during domestication. A specific allele from temperate japonica rice, which gained a putative MYB cis-element in the promoter of HAN1 during the divergence of the two japonica ecotypes, enhances the chilling tolerance of temperate japonica rice and allows it to adapt to a temperate climate. The results of this study extend our understanding of the northward expansion of rice cultivation and provide a target gene for the improvement of chilling tolerance in rice.
Journal Article
Estimation of Fast and Slow Adaptions in the Tactile Sensation of Mechanoreceptors Mimicked by Hybrid Fluid (HF) Rubber with Equivalent Electric Circuits and Properties
In order to advance engineering applications of robotics such as wearable health-monitoring devices, humanoid robots, etc., it is essential to investigate the tactile sensations of artificial haptic sensors mimicking bioinspired human cutaneous mechanoreceptors such as free nerve endings, Merkel’s cells, Krause end bulbs, Meissner corpuscles, Ruffini endings, and Pacinian corpuscles. The generated receptor’s potential response to extraneous stimuli, categorized as slow adaption (SA) or fast adaption (FA), is particularly significant as a typical property. The present study addressed the estimation of SA and FA by utilizing morphologically fabricated mechanoreceptors made of our proposed magnetically responsive intelligent fluid, hybrid fluid (HF), and by applying our proposed electrolytic polymerization. Electric circuit models of the mechanoreceptors were generated using experimental data on capacitance and inductance on the basis of the electric characteristics of impedance. The present results regarding equivalent firing rates based on FA and SA are consistent with the FA and SA findings of vital mechanoreceptors by biomedical analysis. The present investigative process is useful to clarify the time of response to a force on the fabricated artificial mechanoreceptor.
Journal Article
Response of Plants to Water Stress: A Meta-Analysis
Plants are key to the functionality of many ecosystem processes. The duration and intensity of water stress are anticipated to increase in the future; however, a detailed elucidation of the responses of plants to water stress remains incomplete. For this study, we present a meta-analysis derived from the 1,301 paired observations of 84 studies to evaluate the responses of plants to water stress. The results revealed that although water stress inhibited plant growth and photosynthesis, it increased reactive oxygen species (ROS), plasma membrane permeability, enzymatic antioxidants, and non-enzymatic antioxidants. Importantly, these responses generally increased with the intensity and duration of water stress, with a more pronounced decrease in ROS anticipated over time. Our findings suggested that the overproduction of ROS was the primary mechanism behind the responses of plants to water stress, where plants appeared to acclimatize to water stress, to some extent, over time. Our synthesis provides a framework for better understanding the responses and mechanisms of plants under drought conditions.
Journal Article