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Determining the shape of plant cellulose microfibrils is critical for understanding plant cell wall molecular architecture and conversion of cellulose into biofuels. Only recently has it been determined that these cellulose microfibrils are composed of 18 cellulose chains rather than 36 polymers arranged in a diamond-shaped pattern. This study uses density functional theory calculations to model three possible habits for the 18-chain microfibril and compares the calculated energies, structures, 13 C NMR chemical shifts and WAXS diffractograms of each to evaluate which shape is most probable. Each model is capable of reproducing experimentally-observed data to some extent, but based on relative theoretical energies and reasonable reproduction of all variables considered, a microfibril based on 5 layers in a 34443 arrangement is predicted to be the most probable. A habit based on a 234432 arrangement is slightly less favored, and a 6 × 3 arrangement is considered improbable.

The mapping relationship was investigated between Color-Material-Finish (CMF) and style imagery, using Neo-Chinese armchairs as the research object. Within a Kansei Engineering (KE) framework, key style imagery features of Neo-Chinese armchairs were extracted by combining the Semantic Differential (SD) method and Principal Component Analysis (PCA), based on evaluations from a panel of design experts. Existing CMF configurations were systematically categorized and coded, with standardized digital samples generated using Rhino 3D and Keyshot software. Quantitative Theory Type I (QTTI) was then employed to establish the CMF-style imagery mapping framework. Results demonstrated that CMF significantly shapes style imagery: Different CMF combinations can shift stylistic perceptions toward “modern” or “traditional,” and modulate the intensity of “Zen-inspired” qualities—though they cannot eliminate such attributes entirely. Notably, individual CMF categories may exert contrasting effects on different imagery dimensions. This research addresses two core questions: (1) Which specific CMF components influence the style imagery of Neo-Chinese armchairs, and (2) How do these components operate mechanistically? Furthermore, qualitative CMF design strategies are proposed for Neo-Chinese furniture. The findings provide a theoretical basis for furniture designers to align CMF decisions with user cognitive expectations and a methodological reference for style mapping studies across broader design disciplines.

This study focuses on the wooden spandrel components of Ming-style furniture to explore the application potential of generative artificial intelligence in the digital preservation and redesign of traditional woodworking cultural heritage. Based on the Dreamina AI platform, a multidimensional Prompt model integrating furniture category, form-feature, and CMF (Colour-Material-Finish) semantics was constructed. From the perspectives of material cognition and ecological reuse, a three-stage experimental path was designed: “Traditional wooden component restoration experiment—Trend CMF semantic experiment—Innovative CMF integrated redesign.” The CMF semantic experiment showed that different material and process semantic combinations had a significant impact on aesthetic and innovative perception (p<0.01), with the combination of “bamboo + green silk + phoenix embroidery” showing the best performance in terms of ecological aesthetics and cultural expression. The study concluded that generative AI under semantic control can achieve scientific and high-fidelity restoration of traditional components and extend innovative redesign through CMF semantic cultural extension. The openness and semantic construction capabilities of general generative artificial intelligence have introduced new digital expression methods to cultural heritage items made of natural materials, such as bamboo and wood. These methods are forming an interdisciplinary research paradigm that combines sustainable material restoration, cultural semantic control, and AI-driven design.

Human visual cortex does not represent the whole visual field with the same detail. Changes in receptive field size, population receptive field (pRF) size and cortical magnification factor (CMF) with eccentricity are well established, and associated with changes in visual acuity with eccentricity. Visual acuity also changes across polar angle. However, it remains unclear how RF size, pRF size and CMF change across polar angle. Here, we examine differences in pRF size and CMF across polar angle in V1, V2 and V3 using pRF modeling of human fMRI data. In these visual field maps, we find smaller pRFs and larger CMFs in horizontal (left and right) than vertical (upper and lower) visual field quadrants. Differences increase with eccentricity, approximately in proportion to average pRF size and CMF. Similarly, we find larger CMFs in the lower than upper quadrant, and again differences increase with eccentricity. However, pRF size differences between lower and upper quadrants change direction with eccentricity. Finally, we find slightly smaller pRFs in the left than right quadrants of V2 and V3, though this difference is very small, and we find no differences in V1 and no differences in CMF. Moreover, differences in pRF size and CMF vary gradually with polar angle and are not limited to the meridians or visual field map discontinuities. PRF size and CMF differences do not consistently follow patterns of cortical curvature, despite the link between cortical curvature and polar angle in V1. Thus, the early human visual cortex has a radially asymmetric representation of the visual field. These asymmetries may underlie consistent reports of asymmetries in perceptual abilities. •PRFs are smaller in horizontal than vertical visual field quadrants of V1, V2 & V3.•Cortical magnification is correspondingly larger in these horizontal quadrants.•Cortical magnification is larger in the lower than the upper quadrant.•The size of these differences typically increases with visual field eccentricity.•Upper versus lower quadrant PRF size differences change direction with eccentricity.

CCT [for CONSTANS, CONSTANS-like (CO-like), and timing of CAB expression1 (TOC1)] domain-containing genes play important roles in regulating flowering, plant growth, and grain yield and are also involved in stress responses. The CMF (CCT motif family) genes, included in the CCT family, contain a single CCT domain as the only identifiable domain in their predicted protein sequence and are interesting targets for breeding programs. In this study, we identified 19 putative GmCMF genes, based on the latest soybean (Glycine max) genome annotation. The predicted GmCMF proteins were characterized based on conserved structural features, and a phylogenetic tree was constructed including all CMF proteins from rice and Arabidopsis as representative examples of the monocotyledonous (monocot) and dicotyledonous (dicot) plants, respectively. High similarities in the conserved motifs of the protein sequences and the gene structures were found. In addition, by analyzing the CMF gene family in soybean, we identified seven pairs of genes that originated from segmental chromosomal duplication events attributable to the most recent whole-genome duplication (WGD) event in the Glycine lineage. Expression analysis of GmCMF genes in various tissues and after specific treatments demonstrated tissue and stress-response specific differential expression. Gene expression analysis was complemented by the identification of putative cis-elements present in the promoter regions of the genes through a bioinformatics approach, using the existing soybean reference genome sequence and gene models. Co-functional networks inferred from distinct types of genomics data-including microarrays and RNA-seq samples from soybean-revealed that GmCMF genes might play crucial roles in metabolism and transport processes. The results of this study, the first systematic analysis of the soybean CCT gene family, can serve as a strong foundation for further elucidation of their physiological functions and biological roles.

Cellulose micro-fibrils (CMF), which are green, sustainable and are made from abundant renewable biomass, have attracted much attention in the research community for various applications. In this study, we presented a novel magnetic cellulose composite catalyst (HKUST-1/Fe 3 O 4 /CMF) for pollution remedy purpose. The main function of CMF is to improve the dispersion of metal organic framework (MOF) crystals (HKUST-1) and Fe 3 O 4 nanoparticles (NPs) so that the catalytic performance of resultant HKUST-1/Fe 3 O 4 /CMF composite is enhanced. The as-prepared HKUST-1/Fe 3 O 4 /CMF catalyst was characterized by TEM, EDX, BET, XRD, FTIR, TGA and VSM analytical techniques. Results have showed that HKUST-1 and Fe 3 O 4 NPs are anchored onto the surface of CMF. The adsorption efficiency of HKUST-1/Fe 3 O 4 /CMF composite has enhanced because of the porous MOF structures. Furthermore, the composite catalyst has a large surface area and exhibits good magnetic and catalytic properties in the Fenton system. When used as a catalyst in the degradation of dye model compound (methylene blue, MB), the composite catalyst shows a high catalytic activity. In addition, the composite catalyst reveals a good reusability, durability in the recycling and reuse testing. These results support to conclude that the as-prepared HKUST-1/Fe 3 O 4 /CMF composite is a green, sustainable, effective and potential catalyst system for pollutant remedy.

A highly sensitive pressure-sensitive sensor based on MXene was developed using the electrostatic self-assembly method, with carbide sponges as the elastic substrate and a rational design. Specifically, CTAB was used to treat the carbide triamine sponge and conduct the electrostatic self-assembly with MXene to achieve a tightly combined conductive filler and substrate. The resulting pressure sensor showed excellent performance, with a high sensitivity of 15.05 kPa −1 under a range of 0–20 kPa, a response time of 0.1 s, and high durability under 2000 loading–unloading cycles. The minimum detection limit of the sensor was as low as 0.3 Pa, demonstrating excellent monitoring performance. Additionally, finite-element simulation analysis showed that MXene@CTAB@CMF had even better sensing performance at the same stress level. Moreover, the pressure sensor exhibited good sensing performance for various physiological signals and daily work monitoring of the human body, indicating its potential application value.

While the raw material type and the production method of cellulose micro- and nanofibrils (CMNFs) strongly affect the absolute values of the rheological parameters of their aqueous suspensions, the dependence of these parameters on consistency, c, is found to be uniform. The consistency index and yield stress of CMNF suspensions follow generally the scaling laws K∼c2.43 and τy∼c2.26, respectively, and a decent approximation for flow index is n=0.30×c-0.43. The variability of reported scaling exponents of these materials is likely mainly due to experimental uncertainties and not so much due to fundamentally different rheology. It is suggested that the reason behind the apparently universal rheological behavior of CMNF suspensions is the strong entanglement of fibrils; the flow dynamics of typical CMNF suspensions is dominated by interactions between fibril flocs and not by interactions between individual fibrils.Graphic abstract

One of the most frequently used types of digital image forgery is copying one area in the image and pasting it into another area of the same image; this is known as the copy-move forgery. To overcome the limitations of the existing Block-based and Keypoint-based copy-move forgery detection methods, in this paper, we present an effective technique for copy-move forgery detection that utilizes the image blobs and keypoints. The proposed method is based on the image blobs and Binary Robust Invariant Scalable Keypoints (BRISK) feature. It involves the following stages: the regions of interest called image blobs and BRISK feature are found in the image being analyzed; BRISK keypoints that are located within the same blob are identified; finally, the matching process is performed between BRISK keypoints that are located in different blobs to find similar keypoints for copy-move regions. The proposed method is implemented and evaluated on the copy-move forgery standard datasets MICC-F8multi, MICC-F220, and CoMoFoD. The experimental results show that the proposed method is effective for geometric transformation, such as scaling and rotation, and shows robustness to post-processing operation, such as noise addition, blurring, and jpeg compression.