Search Results (47)

Electrochromic devices (ECDs) capable of modulating both visible color and infrared (IR) emissivity are promising for applications in smart thermal camouflage and multifunctional displays. However, conventional transmissive ECDs suffer from limited IR modulation due to the low IR transmittance of transparent electrodes. Here, we report a reflection-type electrochromic zinc-ion battery (HWEC-ZIB) using a self-doped polyaniline nanorod film (SP(ANI-MA)) as the active layer. By positioning the active material at the device surface, this structure avoids interference from transparent electrodes and enables broadband and efficient IR emissivity tuning. To prevent electrolyte-induced IR absorption, a thermal lamination encapsulation method is employed. The optimized device achieves emissivity modulation ranges of 0.28 (3–5 μm) and 0.19 (8–14 μm), delivering excellent thermal camouflage performance. It also exhibits a visible color change from earthy yellow to deep green, suitable for various natural environments. In addition, the HWEC-ZIB shows a high areal capacity of 72.15 mAh cm⁻² at 0.1 mA cm⁻² and maintains 80% capacity after 5000 cycles, demonstrating outstanding electrochemical stability. This work offers a versatile device platform integrating IR stealth, visual camouflage, and energy storage, providing a promising solution for next-generation adaptive camouflage and defense-oriented electronics. Full article

Introduction: Genetic plasticity and adaptive camouflage in critical pathogens have contributed to the global surge in multidrug-resistant (MDR) infections, posing a serious threat to public health and therapeutic efficacy. Antimicrobial resistance, now a leading cause of global mortality, demands urgent action through diagnostics, vaccines, and therapeutics. In India, the Indian Council of Medical Research’s surveillance network identifies Escherichia coli as a major cause of urinary tract infections, with increasing prevalence in human gut microbiomes, highlighting its significance across One Health domains. Methods: Whole-genome sequencing of E. coli strain ECG015, isolated from a human gut sample, was performed using the Illumina NextSeq platform. Results: Genomic analysis revealed multiple antibiotic resistance genes, virulence factors, and efflux pump components. Phylogenomic comparisons showed close relatedness to pathovars from both human and animal origins. Notably the genome encoded protein tyrosine kinases (Etk/Ptk and Wzc) and displayed variations in the envelope stress-responsive CpxAR two-component system. Promoter analysis identified putative CpxR-binding sites upstream of genes involved in resistance, efflux, protein kinases, and the MazEF toxin–antitoxin module, suggesting a potential regulatory role of CpxAR in stress response and persistence. Conclusions: This study presents a comprehensive genomic profile of E. coli ECG015, a gut-derived isolate exhibiting clinically significant resistance traits. For the first time, it implicates the CpxAR two-component system as a potential central regulator coordinating antimicrobial resistance, stress kinase signaling, and programmed cell death. These findings lay the groundwork for future functional studies aimed at targeting stress-response pathways as novel intervention strategies against antimicrobial resistance. Full article

Camouflaged object detection (COD) aims to detect objects that seamlessly integrate with their surrounding environment and are thereby intractable to distinguish from the background. Existing approaches face difficulties in dynamically adapting to scenarios where the foreground closely resembles the background. Additionally, these methods primarily rely on single-domain boundary supervision while overlooking multi-dimensional constraints, leading to indistinct object boundaries. Inspired by the hawk’s visual predation mechanism, namely, global perception and local refinement, we design an innovative two-stage boundary-aware network, namely, SFNet, which relies on supervision in the spatial-frequency domains. In detail, to simulate the global perception mechanism, we design a multi-scale dynamic attention module to capture contextual relationships between camouflaged objects and surroundings and to enhance key feature representation. In the local refinement stage, we introduce a dual-domain boundary supervision mechanism that jointly optimizes boundaries in frequency and spatial domains, along with an adaptive gated boundary guided module to maintain global semantic consistency. Extensive experiments on four camouflaged object detection datasets demonstrate that SFNet surpasses state-of-the-art methods by 4.1%, with lower computational overhead and memory costs. Full article

Target detection in resource-constrained environments faces multiple challenges such as the use of camouflage, diverse target sizes, and harsh environmental conditions. Moreover, the need for solutions suitable for edge computing environments, which have limited computational resources, adds complexity to the task. To meet these challenges, we propose MSCDNet (Multi-Scale Context Detail Network), an innovative and lightweight architecture designed specifically for efficient target detection in such environments. MSCDNet integrates three key components: the Multi-Scale Fusion Module, which improves the representation of features at various target scales; the Context Merge Module, which enables adaptive feature integration across scales to handle a wide range of target conditions; and the Detail Enhance Module, which emphasizes preserving crucial edge and texture details for detecting camouflaged targets. Extensive evaluations highlight the effectiveness of MSCDNet, which achieves 40.1% mAP50-95, 86.1% precision, and 68.1% recall while maintaining a low computational load with only 2.22 M parameters and 6.0 G FLOPs. When compared to other models, MSCDNet outperforms YOLO-family variants by 1.9% in mAP50-95 and uses 14% fewer parameters. Additional generalization tests on VisDrone2019 and BDD100K further validate its robustness, with improvements of 1.1% in mAP50 on VisDrone and 1.2% in mAP50-95 on BDD100K over baseline models. These results affirm that MSCDNet is well suited for tactical deployment in scenarios with limited computational resources, where reliable target detection is paramount. Full article

Thermochromic materials have attracted interest in textile applications, particularly in printing and dyeing processes. However, their thermochromic properties and impact on fabric comfort remain underexplored. This study aimed to investigate the thermochromic properties of printed fabrics with green-to-brown transitions and evaluates their comfort attributes. In the present study, a thermochromic dye paste was applied to nylon/cotton medium-weight fabric via screen printing process. The brown pigment paste was applied first, followed by the thermochromic olive green dye. The printed fabrics were tested for thermochromism, morphology, Fourier Transform Infrared Spectroscopy (FTIR), and comfort properties. Comfort properties were assessed via air permeability, water vapour permeability, and moisture management tests. The results show reversible colour changes from green (25 °C) to brown (40 °C), with increasing lightness (L*) and shifting green–red coordinates (−a*). The scanning electron microscopy (SEM) confirmed uniform dye dispersion, and the FTIR validated the presence of thermochromic pigments. The printed fabrics showed a reduction in air permeability from 40.2 mm/s to 0 mm/s, while water vapour permeability decreased by 62.50% compared to the pristine fabric due to the coating layers. The overall moisture management properties of the printed fabric remained similar to those of the unprinted fabric, with a grade of 1. These findings highlight the potential of thermochromic textiles for adaptive camouflage, particularly in military uniforms, contributing to the advancement of intelligent textiles with enhanced thermal responsiveness. Full article

The decline in mental health among workers in Japan has become a serious concern. Autism spectrum disorder (ASD) traits are increasingly recognized as a potential risk factor for mental health issues, yet few individuals receive a formal ASD diagnosis. This study aims to examine whether undiagnosed but working individuals with strong ASD characteristics differ in factors related to presenteeism (low productivity) compared to their counterparts with fewer ASD traits. In particular, we investigated the impact of social camouflaging—the behavioral adaptation used to mask ASD traits—especially on workers with strong ASD characteristics. An online survey was conducted among white-collar workers aged 20 to 60. The survey included items collecting demographic information (gender, age, marital status, highest level of education completed, employment status, job title, length of employment, and working hours) and included the Japanese versions of four validated instruments to measure aspects of autism traits, social camouflaging, work functioning, and occupational stress. Of the 543 respondents, 139 (25.6%) exhibited strong ASD characteristics. These individuals reported lower productivity than their counterparts. While social camouflaging was observed across all ASD trait levels, it was specifically linked to poorer mental health and reduced productivity among workers with strong ASD characteristics. To support workplace well-being and productivity, it is crucial to increase awareness and understanding of ASD traits in professional settings and create an environment that accommodates diverse work styles. Full article

The variability in shape and coloration patterns associated with strategies of crypsis increases the environmental entropy and makes it more difficult for a potential predator to learn a certain prey to locate. To demonstrate this concept, we composed images of the wings of two Hemerobiidae species (Gayomyia falcata and Megalomus stangei) on a leaf background and then optically analyzed them by calculating the entropy of the images (in color as well as grayscale). For comparison, we colored the wings of Hemerobiidae artificially, and the analysis was repeated with these non-cryptic wings. The results indicate that the artificially colored wings reduce the entropy of the image, facilitating the location of the specimen, while the natural wings increase the entropy, thus hiding the presence of the specimen. In this context, the more morphological and chromatic diversity that the wings show, the greater the increase in entropy. Full article

Small-Structure Camouflaged Object Detection (SSCOD) is a highly promising yet challenging task, as small-structure targets often exhibit weaker features and occupy a significantly smaller proportion of the image compared to normal-sized targets. Such data are not only prevalent in existing benchmark camouflaged object detection datasets but also frequently encountered in real-world scenarios. Although existing camouflaged object detection (COD) methods have significantly improved detection accuracy, research specifically focused on SSCOD remains limited. To further advance the SSCOD task, we propose a detail-preserving multi-scale adaptive network architecture that incorporates the following key components: (1) An adaptive scaling strategy designed to mimic human visual perception when observing blurry targets. (2) An Attentive Atrous Spatial Pyramid Pooling (A2SPP) module, enabling each position in the feature map to autonomously learn the optimal feature scale. (3) A scale integration mechanism, leveraging Haar Wavelet-based Downsampling (HWD) and bilinear upsampling to preserve both contextual and fine-grained details across multiple scales. (4) A Feature Enhancement Module (FEM), specifically tailored to refine feature representations in small-structure detection scenarios. Extensive comparative experiments and ablation studies conducted on three camouflaged object detection datasets, as well as our proposed small-structure test datasets, demonstrated that our framework outperformed existing state-of-the-art (SOTA) methods. Notably, our approach achieved superior performance in detecting small-structured targets, highlighting its effectiveness and robustness in addressing the challenges of SSCOD tasks. Additionally, we conducted polyp segmentation experiments on four datasets, and the results showed that our framework is also well-suited for polyp segmentation, consistently outperforming other recent methods. Full article

Electrochromic fabrics (ECFs) can be applied to wearable displays and military camouflage clothing, and they have great potential in developing wearable products. Current ECFs are often bulky, involve complicated processes, and have high production costs. In this study, we report a novel strategy for preparing electrochromic fabrics that require only a three-layer structure: cotton fabric as the substrate, poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) as the electrochromic layer and the electrodes, and an ion-conducting film (ICF) bonded to the fabric by hot pressing. Compared with conventional ECFs, this method does not require the extra preparation of electrode layers on the fabric, as these layers affect the color-changing effect. Hot pressing eliminates the need for a complex sealing process and is more suitable for fabrics with poor wicking effects, which increases the method’s applicability. Cotton fabrics offer the value of biodegradability and are more environmentally friendly. Meanwhile, unlike carbon cloth, the fabric’s color does not interfere with the electrochromic effect. The ICF is non-liquid and can maintain the dryness of the fabric. Additionally, the ICF provides high-temperature protection up to 150 °C. The ECFs exhibit exceptional thinness at 161 µm and a lightweight construction with a 0.03 g/cm² weight. Furthermore, the ECFs exhibit a relatively long sustain time of 115 min without voltage, demonstrating impressive performance. Improved peel strength to 7.11 N is achieved through an improved hot-pressing process. The development strategy for ECFs can also be applied to other electrochromic substances, potentially advancing intelligent applications such as wearable fabrics and military camouflage while promoting rapid progress in electrochromic fabrics. Full article

Camouflaged Object Detection (COD) aims to identify objects that are intentionally concealed within their surroundings through appearance, texture, or pattern adaptations. Despite recent advances, extreme object–background similarity causes existing methods struggle with accurately capturing discriminative features and effectively modeling multiscale patterns while preserving fine details. To address these challenges, we propose Iterative Refinement Fusion Network (IRFNet), a novel framework that mimics human visual cognition through progressive feature enhancement and iterative optimization. Our approach incorporates the following: (1) a Hierarchical Feature Enhancement Module (HFEM) coupled with a dynamic channel-spatial attention mechanism, which enriches multiscale feature representations through bilateral and trilateral fusion pathways; and (2) a Context-guided Iterative Optimization Framework (CIOF) that combines transformer-based global context modeling with iterative refinement through dual-branch supervision. Extensive experiments on three challenging benchmark datasets (CAMO, COD10K, and NC4K) demonstrate that IRFNet consistently outperforms fourteen state-of-the-art methods, achieving improvements of 0.9–13.7% across key metrics. Comprehensive ablation studies validate the effectiveness of each proposed component and demonstrate how our iterative refinement strategy enables progressive improvement in detection accuracy. Full article

Background: This study investigates the complex relationship between accentuation and attention in visual perception, extending classical Gestalt principles by introducing dissimilarity as a complementary mechanism to similarity in perceptual organization. Objectives and Methods: Through a series of phenomenological experiments, we demonstrate how accentuation, driven by dissimilarity, plays a crucial role in shaping visual experience and guiding attention. Results: Our findings reveal that accentuation serves as a pre-attentive mechanism for highlighting salient features, influencing initial perceptual organization, and modulating the apparent shape and orientation of visual elements. We show that while accentuation operates rapidly and automatically, attention acts as a flexible, selective mechanism that can either reinforce or override accentuation-based percepts. This interplay suggests a two-stage process of visual perception, with implications for theories of consciousness and information processing in biological systems. This study also explores the evolutionary significance of accentuation in camouflage and sexual selection, providing insights into how perceptual mechanisms may have evolved to enhance adaptive fitness. Conclusions: Our results have broad implications for understanding visual cognition, design, and clinical applications related to attentional disorders. Full article

To enhance the capabilities of UAV platforms in recognizing and tracking hostile targets on the battlefield, advanced feature extraction and image segmentation are required. In response, the Depse Unet++ model was developed. By introducing Squeeze-and-Excitation, the model’s ability to discriminate camouflaged targets in high-similarity backgrounds is improved; by incorporating a depth-separated convolutional design, the parameters and computational requirements for embedded device applications are significantly reduced; and employing Dropout technique to prevent overfitting with limited sample sizes, thus boosting the model’s adaptability and generalization across environments. Evaluations were conducted using a custom-built dataset to test the model’s segmentation accuracy and performance. The experimental results show that the Depse Unet++ model surpasses existing state-of-the-art models in critical metrics such as Mean Inter-section and Union Ratio, Dice coefficient and pixel accuracy. Additionally, the specific contributions of each technical component to the model’s performance were confirmed through ablation studies, ensuring the method’s validity and reliability. Overall, the Depse Unet++ model offers a more effective tool for target recognition and semantic segmentation for UAVs operating in complex battlefield scenarios. Full article

This paper presents a modularized reconfigurable functional electromagnetic surface (MRFES) for broadband absorption and polarization conversion by using tightly coupled dipole antennas (TCDA) and back-loaded radio frequency (RF) circuits (BLRFC). A dual-polarized antenna array with tight coupling and wide angular scanning characteristics is designed. By loading different RF circuits on the back side of the antenna array’s ground plane, switchable broadband absorption and polarization conversion functions are achieved. The design adopts modularization to facilitate the replacement of back-loaded RF circuits for diverse electromagnetic (EM) control functions. The final design of the tightly coupled antenna array has a thickness of 13.437 mm and a size of 119.5 mm × 119.5 mm. It works in a bandwidth range of 4.14–13 GHz. Upon loading the absorption circuit board, a broadband absorbing electromagnetic (EM) surface is formed, achieving dual-polarization absorption within a bandwidth of 4.14–12.4 GHz. With the polarization conversion circuit board attached, polarization conversion effects are realized within a bandwidth of 4.4–12.9 GHz. Both simulations and experiments verify that the designed EM surface possesses modular reconfigurable functions for broadband absorption/polarization conversion. The proposed design scheme holds promising prospects for applications in active stealth, adaptive camouflage, intelligent communication and other fields. Full article

Background color matching is essential for camouflage and thermoregulation in ectothermic vertebrates, yet several key cellular-level questions remain unresolved. For instance, it is unclear whether the number of chromatophores or the activity of individual chromatophores plays a more critical role in this process. Using single-cell RNA sequencing (scRNA-seq), we investigated the cellular and molecular mechanisms underlying color change in Rhacophorus dugritei, which adapted to its background by displaying light-green skin on white and black skin on black within two days. We identified two types of chromatophores in their skin, both responsible for the observed color differences. Our findings reveal that morphological color change (MCC) is the dominant process, with the number of chromatophores being more influential in driving color change than the transcriptional activity of melanogenesis in individual cells. Additionally, melanophores from darker individuals exhibited increased activity in energy metabolism pathways, while those from lighter individuals showed stronger immune-related gene expression, suggesting that background adaptation involves more than just morphological changes. Overall, this study successfully applied single-cell sequencing technology to investigate skin pigmentation in a non-model organism. Our results suggest that MCC driven by chromatophore proliferation is a key mechanism of background adaptation, offering new insights into amphibian color adaptation and environmental adaptation in other vertebrates. Full article

Yellow-to-green electrochromic color switching plays a key role in the intelligent adaptive camouflage under the visible light environment in future military camouflage applications. Here, we designed and synthesized a soluble electrochromic conjugated pDPTD polymer, mainly based on perylo[1,12-bcd]thiophene and the novel ProDOT groups. The pDPTD polymer displayed a yellow-to-green electrochromism with large optical contrast and fast switching times. Based on the pDPTD polymer film, a yellow-to-green electrochromic device was achieved, showing an orange-yellow color at −0.4 V with L*a*b* color coordinates of 88.5, 18.5, and 34.2 and a pale green color at 0.7 V with L*a*b* color coordinates of 85.6, −4.8, and 11.5, together with a large optical contrast of 43.5% and fast switching times of 2.4/3.2 s. These results indicated that the pDPTD polymer could serve as a potential electrochromic material for yellow/green system camouflage applications. Full article