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The study aims to explore high‐carbon steel's behavior during cold drawing, focusing on the link between microstructural changes, texture, and mechanical properties at different strain levels. Using X‐ray diffraction, scanning electron microscopy–electron backscatter diffraction, micro‐ and nanoindentation, and wear analysis, findings show that grain size and interlamellar spacing decrease as strain increases, and pearlitic colonies become more compact and aligned. This refinement leads to significant hardening, from 333.8 HV in the wire rod to 470.4 HV at 2.05 strain, aligning with the Hall–Petch law. The <110> fiber texture develops linearly, and a higher dislocation density is noted at lower strain rates, with low‐angle grain boundaries increasing from 65.2% to 76.5%. The cold drawing process is thus divided into two phases, marked by a shift from low‐angle grain boundaries dominance and a notable reduction in wear rate compared to severely deformed states. [ABSTRACT FROM AUTHOR]

Managing the metal's texture throughout the entire processing procedure is imperative for controlling the final properties of metal alloys. In the aerospace industry, α‐Ti alloys have been successfully utilized in applications such as aircraft skins, heat shields, and heat exchangers. However, inherent mechanical strength, fatigue sensitivity, and fracture toughness limitations have significantly restricted their wider adoption. On the other hand, β‐Ti alloys have received increasing attention in the biomedical field due to their lower elastic modulus. However, their actual application has been primarily restricted by the inability to match natural bone's Young's modulus sufficiently. Among these application limitations for both α‐Ti and β‐Ti alloys, texture is an essential factor affecting mechanical properties. Elucidating texture evolution on α‐Ti and β‐Ti alloys is crucial for enabling the expansion of their applications. This review summarizes detailed analyses of the intertwined evolution of texture and microstructure in α‐Ti and β‐Ti alloys during cold rolling, hot rolling, and annealing. Furthermore, based on these fundamental materials science insights, the resultant impact of texture and microstructure on achieving targeted mechanical properties is discussed. Finally, potential pathways are proposed to further guide texture and microstructure evolution in α‐Ti and β‐Ti alloys to meet application requirements. [ABSTRACT FROM AUTHOR]

A classic finding reported in Beck (1966a) is that observers tend to indicate a more natural texture break between a set of T's and tilted T's than between a set of T's and backward L's. This finding has played a prominent role in discussions about the properties of texture segmentation and in the development of computational theories of texture segmentation. Due to the small sample size of the original study, we replicated the original experiment with a larger sample. Regrettably, we discovered that the description in Beck (1966a) is insufficient to allow us to reproduce the stimuli. For our replication, we created stimuli that seem consistent with the spirit of the original study. The results of the replication study partly match Beck's original data ( r =. 59 ), but conclusions indicated by these results deviate from some of Beck's key conclusions. We also further explored the influential claim derived from a second experiment in Beck (1966a) that texture segmentation was not related to the perceived similarity of elements. Contrary to this claim, a re-analysis of Beck's data indicates the counterintuitive conclusion that observers tend to indicate stronger texture segmentation between regions that are rated as being more similar. In a replication of the second experiment, this relation flipped so that the replication observers indicated stronger texture segmentation for regions with lower similarity ratings. Despite being influential, we conclude that there are substantial problems with the stimuli, analyses, and conclusions in Beck (1966a). [ABSTRACT FROM AUTHOR]

This study analyzes the influence of nine distinct texture geometries on a convergent oil film gap using a simulation model. The geometrical dimensions of the textures are characterized by the texture area density, S t e x. , A and the ratio of the textured-to-untextured area ( A t e x. / A 0) . The results show that different texture geometries optimize the tribological performance depending on the value of S t e x. , A . Rectangular textures with variable widths (85% of the texture length a t e x. ) significantly enhance lifting and the drag force across a broad range of S t e x. , A . Furthermore, rectangular textures with a constant width (85% of the global width b 0 ) show the best improvement within this study. The investigation also reveals that a small texture pitch angle, α t e x , further enhances tribological performance. [ABSTRACT FROM AUTHOR]

This research investigates the generation and evaluation of various geometric surface textures on PLA components produced via fused filament fabrication (FFF). Textures, including grooves, pyramids, and cylinders, were created at different depth levels on the PLA surfaces. The surface quality of these textures was assessed using a 3D optical system, focusing on area parameters such as Sa and Sz. The wettability of each texture was evaluated through contact angle and sliding angle tests, revealing the ability to modulate contact angles and achieve either hydrophobic or hydrophilic surfaces depending on the texture type. Subsequently, pairs of textured PLA pieces were bonded using a cyanoacrylate adhesive following standardised protocols, and shear tests were conducted to determine the maximum shear stress at bond (τmax) of each texture. Notably, textured surfaces generally exhibited hydrophobic properties that reduce the adhesion between the adhesive and the piece, leading to reduced maximum shear stress at bond values compared to non-textured surfaces. However, groove textures notably increased τmax values. The results were analysed to establish correlations between surface quality, wettability, and shear strength. This comprehensive evaluation aims to elucidate the influence of surface texture on the mechanical performance and adhesive properties of FFF-manufactured PLA components. [ABSTRACT FROM AUTHOR]

Material selection is important yet difficult in interior design, as designers need to consider technical factors beyond aesthetics, such as maintenance, sustainability, and costs that are often considered in later stages of the design process. As a result, making design changes due to unanticipated technical constraints in the later stages can be costly. We attempt to approach this problem by anticipating these as early as the conceptualization stage, where designers model and assign textures to their 3D scenes. To this end, our study explores the use of generative AI tools, namely ChatGPT and DALLE-2, in both texturing 3D scenes and selecting materials for interior design projects. Through a prototype, we evaluated the generative AI tools by conducting a user study with professional designers and students (n = 11). Based on creativity support (CSI), participants averaged a score of 72.82/100, while in task load (NASA-TLX), they scored 47.36/100. Based on qualitative feedback, designers could easily search and explore textures and materials while also receiving informative and contextually relevant suggestions on materials and colors from ChatGPT. However, these tools can be improved by fine-tuning on domain-specific datasets. Lastly, we analyze how designers interacted with these tools and reflect on how they can benefit from using generative AI in texturing and material selection in the interior design process.

Rodents rely on their whiskers as vital sensory tools for tactile perception, enabling them to distinguish textures and shapes. Ensuring the reliability and constancy of tactile perception under varying stimulus conditions remains a fascinating and fundamental inquiry. This study explores the impact of stimulus configurations, including whisker movement velocity and object spatial proximity, on texture discrimination and stability in rats. To address this issue, we employed three distinct approaches for our investigation. Stimulus configurations notably affected tactile inputs, altering whisker vibration's kinetic and kinematic aspects with consistent effects across various textures. Through a texture discrimination task, rats exhibited consistent discrimination performance irrespective of changes in stimulus configuration. However, alterations in stimulus configuration significantly affected the rats' ability to maintain stability in texture perception. Additionally, we investigated the influence of stimulus configurations on cortical neuronal responses by manipulating them experimentally. Notably, cortical neurons demonstrated substantial and intricate changes in firing rates without compromising the ability to discriminate between textures. Nevertheless, these changes resulted in a reduction in texture neuronal response stability. Stimulating multiple whiskers led to improved neuronal texture discrimination and maintained coding stability. These findings emphasize the importance of considering numerous factors and their interactions when studying the impact of stimulus configuration on neuronal responses and behavior. [ABSTRACT FROM AUTHOR]

The present study encompasses petrographic variations in simple Deccan basaltic lava flows of the Rajura volcanics, central India. The Deccan basalt lava flows entirely covered the area and exposed in the form of moderate hillocks. During geological fieldwork, flows are identified and differentiated based on mineral content, relative grain size, presence of phenocrysts, and red bole horizons. Flow mapping reveals three basalt lava flows: mafic plagioclase microphyric basalt, phyric basalt, and plagioclase mafic microphyric basalt. The petrographic study of the lava flows was carried out to understand the mineralogy, textural patterns, crystallization, and genetic significance of the lava flows. The result indicates dominant plagioclase and clinopyroxene minerals with opaques exhibit porphyritic, glameroporphyritic, ophitic, and sub-ophitic textures. The petrographic variations are due to the combination of several factors like gravitational sinking of phenocryst, low viscosity, and slow rate of effusion of lava flows, as described by earlier workers. Plagioclase occurs as phenocrysts and in the groundmass phase, indicating early crystallization of phenocryst followed by crystallization of groundmass. The petrographic studies are further useful to correlate the lava flows exposed in different hillocks of the area. [ABSTRACT FROM AUTHOR]

An attempt has been made to discuss some of the developments, in a personalized historical perspective, regarding a viable answer to the 'Flavor Riddle' through a minor addition to the Fritzsch's original proposal about texture zero mass matrices. [ABSTRACT FROM AUTHOR]

This research aims to examine the compound impact of adding rectangular textures to various zones on the surface of the bearing and nanoparticles in the lubricant on the properties of journal bearing. A lubrication models with various texture depths and eccentricity ratios of journal bearing are created and simulated using CFD-FSI method to get static properties like load capacity and frictional force. Aluminum oxide nanoparticles were added in weight ratios ranging from 0.1 to 0.5 %, and the change in viscosity due to these additives in the lubricant was considered. Cavitation and the dependence of viscosity on temperature effects are also considered. The validation results show that the acquired results from the current simulation method agree well with the experimental results in the reference. The outcomes indicated that the highest load capacity and the lowest frictional force are found in the high-pressure region. It was noted that the maximum rise in load capacity was 16.51% without nanoparticles at a texture depth of 0.5 mm and eccentricity ratio of 0.1, and with the adding of 0.5 wt. % of nanoparticles to the lubricant in the same region, the load carrying capacity increased to 40.87 % compared to a bearing without textures. [ABSTRACT FROM AUTHOR]

The monitoring of crop growth, particularly the estimation of Leaf Area Index (LAI) using optical remote sensing techniques, has been a continuous area of research. However, it has become a challenge to accurately and rapidly interpret the spatial variation of LAI under nitrogen stress. To tackle these issues, this study aimed to explore the potential for precise LAI estimation by integrating multiple features, such as average spectral reflectance (ASR), vegetation index, and textures, obtained through an unmanned aerial vehicle (UAV). The study employed the partial least squares method (PLS), extreme learning machine (ELM), random forest (RF), and support vector machine (SVM) to build the LAI estimation model under nitrogen stress. The findings of this study revealed the following: (i) texture features generally exhibited greater sensitivity to LAI compared to ASR and VIs. (ii) Utilizing a multi-source feature fusion strategy enhanced the model's accuracy in predicting LAI compared to using a single feature. The best RP2 and RMSEP of the estimated LAI were 0.78 and 0.49, respectively, achieved by RF through the combination of ASR, VIs, and textures. (iii) Among the four machine learning algorithms, RF and SVM displayed strong potential in estimating LAI of rice crops under nitrogen stress. The RP2 of the estimated LAI using ASR + VIs + texture, in descending order, were 0.78, 0.73, 0.67, and 0.62, attained by RF, SVM, PLS, and ELM, respectively. This study analyzed the spatial variation of LAI in rice using remote sensing techniques, providing a crucial theoretical foundation for crop management in the field. [ABSTRACT FROM AUTHOR]

Lake Van, the world's largest alkaline lake, hosts some of the largest microbialite towers worldwide, which are considered as modern analogues of ancient stromatolites. This study investigates the links between microbialite evolution, geology, climate and hydrology, and the role of biotic and abiotic processes in microbialite growth and morphology. For these objectives, the northern shelf of Lake Van was surveyed by sub‐bottom seismic profiling and diving, and two 9 m and 15 m high microbialite chimneys were sampled at 25 m water depth. Samples were analysed for stable oxygen and carbon isotopes, X‐ray diffractometry, scanning electron microscopy and U/Th age dating. Lake Van microbialites precipitate wherever focused Ca‐rich groundwater flows onto the lake floor to mix with alkaline lake water. Variable columnar, conical and branching morphologies of the microbialites indicate various processes of formation by groundwater channelling within the chimneys. Collectively, our data suggest that the microbialite chimneys have formed within the last millennium, most likely starting during the warm and humid Medieval Climate Anomaly (caad 800–1300), when lake level rose approximately to the present level due to enhanced Inputs of riverine Ca‐rich freshwater and groundwater. Our new scanning electron microscopy observations indicate that the internal structure of the microbialites below the outer cyanobacteria‐covered crust is constructed by calcified filaments, globular aggregates and nanocrystals of algal, cyanobacterial and heterobacterial origins and inorganically precipitated prismatic calcite crystals. These textural features, together with dive observations, clearly demonstrate the important role of inorganic carbonate precipitation at sites of groundwater discharge, followed by cyanobacteria and algal mucilage deposition and microbially meditated calcification in the photic zone in the rapid growth of the microbialite chimneys. Considering the close similarities of some textures with those of ancient stromatolites and meteorites, the results of this study provide new insights into the environmental conditions associated with stromatolite formation and extra‐terrestrial life evolution. [ABSTRACT FROM AUTHOR]

To avoid cracks during hot rolling, a short process of direct cold rolling following solution treatment of the casting billet for preparing lean duplex stainless steel plates is proposed. The effect of cold rolling reduction on the microstructure, texture, and mechanical properties of UNS S32101 is investigated. The results show that dislocation slip is the main character in ferrite, which leads to dislocation tangles, dislocation cells, high‐density dislocation walls, and deformed microbands. However, twinning and strain‐induced martensite transformation (SIMT) occur in austenite, and the SIMT mechanism of austenite follows the classical model γ → ε → α′ and γ → α′, with the orientation relationship of Kurdjumov–Sachs ({111}γ || {0001}ε || {110}α′$\left(\text{{111}}\right)_{\gamma} \text{ || } \left(\left{\right. 0001 \left.\right}\right)_{\epsilon} \left(\text{ || {110}}\right)_{\text{&amp;amp;amp;amp;amp;amp;amp;alpha;&amp;amp;amp;amp;amp;amp;amp;aposx;}}$ and <101¯>γ || <112¯0>ε || <11¯1>α′$\text{&amp;amp;amp;amp;amp;amp;lt;10} \overset{\cdot}{1} \left(\text{&amp;amp;amp;amp;amp;amp;gt;}\right)_{\gamma} \text{ || &amp;amp;amp;amp;amp;amp;lt;11} \overset{\cdot}{2} \left(\text{0&amp;amp;amp;amp;amp;amp;gt;}\right)_{\epsilon} \text{ || &amp;amp;amp;amp;amp;amp;lt;1} \overset{\cdot}{1} \left(\text{1&amp;amp;amp;amp;amp;amp;gt;}\right)_{\text{&amp;amp;amp;amp;amp;amp;amp;alpha;&amp;amp;amp;amp;amp;amp;amp;aposx;}}$) and Nishyama–Wassermann (N–W) ({111}γ || {110}α′$\left(\text{{111}}\right)_{\gamma} \left(\text{ || {110}}\right)_{\text{&amp;amp;amp;amp;amp;amp;amp;alpha;&amp;amp;amp;amp;amp;amp;amp;aposx;}}$ and <11¯0>γ || <001>α′$\text{&amp;amp;amp;amp;amp;amp;lt;1} \overset{\cdot}{1} \left(\text{0&amp;amp;amp;amp;amp;amp;gt;}\right)_{\gamma} \left(\text{ || &amp;amp;amp;amp;amp;amp;lt;001&amp;amp;amp;amp;amp;amp;gt;}\right)_{\text{&amp;amp;amp;amp;amp;amp;amp;alpha;&amp;amp;amp;amp;amp;amp;amp;aposx;}}$). Meanwhile, at 50%, there is a transition from Cu texture to Brass texture in the austenite phase. At 12.5%, the yield strength is 344 MPa higher than that of the traditional hot rolling process, and the elongation remains about 35%. With the increasing cold rolling reduction, the elongation decreases while the strength rises significantly. Strengthening dislocations, fine‐tuning grains, and SIMT are the primary contributors to the improvement in strength. [ABSTRACT FROM AUTHOR]

The aim of this Tutorial is to give a pedagogical introduction into realizations of Majorana fermions, usually termed as Majorana bound states (MBSs), in condensed matter systems with magnetic textures. We begin by considering the Kitaev chain model of "spinless" fermions and show how two "half" fermions can appear at chain ends due to interactions. By considering this model and its two-dimensional generalization, we emphasize intricate relation between topological superconductivity and possible realizations of MBS. We further discuss how "spinless" fermions can be realized in more physical systems, e.g., by employing the spin-momentum locking. Next, we demonstrate how magnetic textures can be used to induce synthetic or fictitious spin–orbit interactions, and, thus, stabilize MBS. We describe a general approach that works for arbitrary textures and apply it to skyrmions. We show how MBS can be stabilized by elongated skyrmions, certain higher order skyrmions, and chains of skyrmions. We also discuss how braiding operations can be performed with MBS stabilized on magnetic skyrmions. This Tutorial is aimed at students at the graduate level. [ABSTRACT FROM AUTHOR]

The kinetics of fluid-driven metamorphic reactions are challenging to study in nature because of the tendency of metamorphic systems to converge towards chemical equilibrium. However, in cases where mineral textures that reflect incomplete reactions are preserved, kinetic processes may be investigated. Atoll garnet, a texture formed by the dissolution of a garnet's core, has been described in 2D from thin sections of rocks worldwide. Quantifying the extent of this dissolution reaction requires a sample-wide examination of hundreds of individual grains in 3D. In this study, we quantified the distribution of atoll garnet using micro-computed tomography and grain shape analysis. A convolutional neural network was trained on human-labeled garnet grains for automated garnet classification. This approach was applied to a retrogressed mafic eclogite from the Zermatt–Saas Zone (Western Alps). Pervasive atoll-like resorption preferentially affected the larger porphyroblasts, suggesting that compositional zoning patterns exert a first-order control on dissolution rates. A kinetic model shows that the reactivity of metastable garnet to form atolls is favored at pressure–temperature conditions of 560 ± 30°C and 1.6 ± 0.2 GPa. These conditions coincide with the release of water when lawsonite breaks down during the exhumation of mafic eclogites. The model predicts dissolution rates that are three to five times faster for the garnet core than for the rim. This study shows that deep learning algorithms can perform automated textural analysis of crystal shapes in 3D and that these datasets have the potential to elucidate petrological processes, such as the kinetics of fluid-driven metamorphic reactions. [ABSTRACT FROM AUTHOR]

During tactile sensation in rodents, the whisker movements across surfaces give rise to intricate whisker motions that encompass discrete and transient stick-slip events, effectively conveying valuable information regarding surface properties. These surface characteristics are transformed into cortical neuronal responses. This study examined the coding strategies underlying these transformations in rat whiskers. We found that changes in surface coarseness modified the number and magnitude of stick-slip events, which in turn both modulated properties of neuronal responses. Global changes in the number of stick-slip events primarily affected neuronal discharge rates and the degree of neuronal synchronization. In contrast, local changes in the magnitude of stick-slip events affected the transformation of these kinematic and kinetic characteristics into neuronal discharges. Most cortical neurons exhibited surface coarseness selectivity through global and local stick-slip event properties. However, this selectivity varied across coding strategies in the same neurons, given that each coding strategy reflected different aspects of changes in whisker-surface interactions. The degree of spatial similarity in surface coarseness preference in adjacently recorded neurons differed among these coding strategies. Adjacently recorded neurons exhibited the same surface coarseness preference in their firing rates but not through other coding strategies. Through these results, we were able to show that local stick-slip event properties contribute to texture discrimination, complementing and surpassing global coding in this context. These findings suggest that the representation of surface coarseness in the cortex may rely on concurrent coding strategies that integrate tactile information across different spatiotemporal scales. [ABSTRACT FROM AUTHOR]

Eucalyptus constitutes one of the most common tree genera used in forest plantations worldwide. In Europe, Eucalyptus trees are especially common in the Northwest of the Iberian Peninsula, E. nitens and E. globulus being the most commonly cultivated species. Each species presents particularities that lend to different exploitation strategies and industrial usages. Therefore, updated knowledge about the abundance and spatial distribution of the different species is important for forest planning. This is a special challenge for areas where forest land is highly fragmented. Remote sensing has been used to efficiently monitor the distribution of the Eucalyptus genera, however little research has been able to map specific Eucalyptus species. This study evaluates the efficiency of Sentinel-2 data, Worldview-3 images, and Airborne LiDAR data in the differentiation of E. nitens and E. globulus. Supervised classifications were performed using neural networks for these data sets both individually and in combination. The highest accuracies were obtained when using Sentinel-2 data in combination with LiDAR point clouds and when using Sentinel-2 data in a multitemporal approach. The best time of year to differentiate between the two species is during the emergence of spring shoots. Worldview-3 images have a moderate capacity to differentiate between the two species, although this is increased when textural metrics are included. This study can serve as the basis for generating Eucalyptus species distribution maps, which will allow for improved forest management and planning. [ABSTRACT FROM AUTHOR]

Rodents rely on their whiskers as vital sensory tools for tactile perception, enabling them to distinguish textures and shapes. Ensuring the reliability and constancy of tactile perception under varying stimulus conditions remains a fascinating and fundamental inquiry. This study explores the impact of stimulus configurations, including whisker movement velocity and object spatial proximity, on texture discrimination and stability in rats. To address this issue, we employed three distinct approaches for our investigation. Stimulus configurations notably affected tactile inputs, altering whisker vibration’s kinetic and kinematic aspects with consistent effects across various textures. Through a texture discrimination task, rats exhibited consistent discrimination performance irrespective of changes in stimulus configuration. However, alterations in stimulus configuration significantly affected the rats’ ability to maintain stability in texture perception. Additionally, we investigated the influence of stimulus configurations on cortical neuronal responses by manipulating them experimentally. Notably, cortical neurons demonstrated substantial and intricate changes in firing rates without compromising the ability to discriminate between textures. Nevertheless, these changes resulted in a reduction in texture neuronal response stability. Stimulating multiple whiskers led to improved neuronal texture discrimination and maintained coding stability. These findings emphasize the importance of considering numerous factors and their interactions when studying the impact of stimulus configuration on neuronal responses and behavior.

This study analyzes the influence of nine distinct texture geometries on a convergent oil film gap using a simulation model. The geometrical dimensions of the textures are characterized by the texture area density, Stex.,A and the ratio of the textured-to-untextured area (Atex./A0). The results show that different texture geometries optimize the tribological performance depending on the value of Stex.,A. Rectangular textures with variable widths (85% of the texture length atex.) significantly enhance lifting and the drag force across a broad range of Stex.,A. Furthermore, rectangular textures with a constant width (85% of the global width b0) show the best improvement within this study. The investigation also reveals that a small texture pitch angle, αtex, further enhances tribological performance.

Tree diversity in the tropical forests face escalating threats from wildfires. This study assessed post-fire impacts and recovery patterns in Tanzanian Eastern Arc Mountains forests from 2017 to 2022 using field measurements and remote sensing techniques. Tree species diversity, composition, and forest stand parameters were compared between burned and unburned forest plots across two reserves. A predictive model utilizing 14 key variables derived from multispectral satellite data was developed to accurately map burned areas and spatial fire patterns. Results revealed significantly lower tree density, aboveground biomass, species richness, and Shannon diversity in burned areas compared to unburned forests. However, compositional analysis showed extensive species overlap between burned and unburned sites, with burned areas containing more indicative pioneer and disturbance-adapted species such as Apodytes dimidiata. Over time since fire events, tree density, basal area, aboveground biomass, species richness, evenness, and diversity increased markedly, evidencing active tree recovery. The remote sensing model effectively delineated approximately 1430 hectares of burned areas concentrated near villages, suggesting prevalent anthropogenic fire ignitions. Although wildfires substantially impacted forest structure and biodiversity, the limited compositional shifts point to resilience of these tropical montane forests. Integration of diverse spectral bands and textural metrics from multispectral satellite data can support precise mapping of fire effects and forest recovery dynamics in these ecologically vital yet threatened ecosystems, aiding conservation and management. Overall, this study provides novel insights into post-fire responses in Eastern Arc Mountain forests using a synergistic field and remote sensing approaches.

During tactile sensation in rodents, the whisker movements across surfaces give rise to intricate whisker motions that encompass discrete and transient stick–slip events, effectively conveying valuable information regarding surface properties. These surface characteristics are transformed into cortical neuronal responses. This study examined the coding strategies underlying these transformations in rat whiskers. We found that changes in surface coarseness modified the number and magnitude of stick–slip events, which in turn both modulated properties of neuronal responses. Global changes in the number of stick–slip events primarily affected neuronal discharge rates and the degree of neuronal synchronization. In contrast, local changes in the magnitude of stick–slip events affected the transformation of these kinematic and kinetic characteristics into neuronal discharges. Most cortical neurons exhibited surface coarseness selectivity through global and local stick–slip event properties. However, this selectivity varied across coding strategies in the same neurons, given that each coding strategy reflected different aspects of changes in whisker-surface interactions. The degree of spatial similarity in surface coarseness preference in adjacently recorded neurons differed among these coding strategies. Adjacently recorded neurons exhibited the same surface coarseness preference in their firing rates but not through other coding strategies. Through these results, we were able to show that local stick–slip event properties contribute to texture discrimination, complementing and surpassing global coding in this context. These findings suggest that the representation of surface coarseness in the cortex may rely on concurrent coding strategies that integrate tactile information across different spatiotemporal scales.

Herein, the effect of annealing time on the texture evolution in Fe–3.4 wt% Si non‐oriented electrical steel is investigated. Strip samples are cast using a vacuum sampling method, which simulate the solidification conditions of an industrial twin roll thin strip casting (TRSC) process. As‐cast samples with different carbon and sulfur (C&S) levels are hot rolled (HR) with varying levels of hot deformation, cold rolled (CR) to 0.35 mm thickness, and then annealed at 1050 °C for different holding times (1, 6, 24 h). To Fe–3.4 wt% Si nonoriented electrical steel, the observed texture evolution can be divided into different stages as annealing time is increased from 1 to 24 h. With increasing annealing time, the fraction of Goss texture decreases initially and then increases again through the consumption of grains with other textures. With additional time, a decrease of pinning force due to precipitate coarsening results in normal grain growth, resulting in an increase of grain size. In this step, Cube grains can form from rotated Goss grains. A model for core loss is presented and used to explain the core loss results. [ABSTRACT FROM AUTHOR]

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Copyright of Materials & Technologies / Materiali in Tehnologije is the property of Institute of Metals & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Despite a high degree of knowledge about Cambrian–Ordovician sandy sequence in the northwestern flank of the Moscow syneclise, some of its subdivisions are still poorly studied. The article provides first comprehensive lithological analysis of the textural and mineral–structural composition of the Novolutsk sand member, which is common in the western Leningrad region. This member conditionally belongs to the Middle Cambrian Sablin Formation. Significant differences between the studied sands and the sands in other units of the formation are shown, and their analogues in the eastern sections of the Baltic–Ladoga glint are found. The lenticular morphology, peculiar textural complex and coarse- to medium-grained composition of the Novolutsk sands made it possible to prove their continental alluvial genesis and link them with the sedimentary environments in the earlier identified Putilovsky sands of the Sablin Formation. [ABSTRACT FROM AUTHOR]

Ti–Nb–Fe–Sn alloys with relatively low Nb content, located near the phase boundary of (β + ω)/β, are designed on the basis of electron‐to‐atom (e/a) ratio, d‐electron alloy design concept, and Mo equivalent (Moeq) aiming at low Young's modulus comparable to human bone. The effect of Sn content and Nb content on the microstructure and the mechanical properties is investigated in Ti–5Nb–3Fe–(0–6)Sn (at%) and Ti–(3–9)Nb–3Fe–4Sn (at%) alloys. The composition dependence of Young's modulus and tensile strength of Ti–Nb–Fe–Sn alloys is analyzed in terms of the phase stability, ω phase, and recrystallization texture. Both Nb and Sn are effective in suppressing the athermal ω phase and stabilizing the β phase. The recrystallization texture is strongly influenced by the content of Sn and Nb. A strong {110}β<001>β Goss texture is formed in the Ti–5Nb–3Fe–(2–4)Sn and Ti–(3–5)Nb–3Fe–4Sn alloys. The Ti–5Nb–3Fe–4Sn alloy exhibits an exceptionally low Young's modulus of 30 GPa due to the combined effects of low stability of the β phase, a small amount of ω phase, and a strong Goss texture. [ABSTRACT FROM AUTHOR]

Recent years are showing a rapid adoption of digital manufacturing techniques to the construction industry, with a focus on additive manufacturing. Although 3D printing for construction (3DPC) has notably advanced in recent years, publications on the subject are recent and date a growth in 2019, indicating that it is a promising technology as it enables greater efficiency with fair consumption of material, minimization of waste generation, encouraging the construction industrialization and enhancing and accelerating the constructive process. This new building system not only gives an optimization of the building process but provides a new approach to the building design materiality. The direct connection between design and manufacturing allows the reduction in the number of the various construction phases needed. It is opening a new and wide range of options both formal and chromatic in customization, avoiding complex formworks, reducing costs and manufacturing time. The creative process has a strict and direct link with the constructive process, straightening design with its materiality. Cement-based materials lead the way, but new alternatives are being explored to further reduce its carbon footprint. In order to leverage its sustainability and enhance the system capacity, initiatives are being pursued to allow the reduction of the use of PC. Geopolimers are taking the first steps in 3DPC. Construction and Demolition Waste (CDW) materials are used to substitute natural aggregates. Even soil is being explored has a structural and aesthetic material. These research trends are opening a wider range of possibilities for architecture and design, broadening the spectrum of color, texture, and formal variations. The concern about textures and colours is not yet evident in many the structures already printed, opening the opportunity for future research. More can be done in the mixture and formal design of this building system, “discovering” other raw materials in others waste. This article aims to make a critical review of technologies, materials and methodologies to support the development of new sustainable materials to be used as a plastic element in the printed structure. A roadmap of 3D printing for construction is presented, and an approach on mix design, properties in the fresh and hardened state, highlighting the possibilities for obtaining alternative materials are pointed. With this review possible directions are presented to find solutions to enhance the sustainability of this system discovering “new” materiality for architecture and design.

Inverse formulas for the energy potential level and the effective electron mass within an unknown quantum material are obtained, solely based on the transmission probabilities of obliquely incident beams through a thin lamellar sample. The estimator is robust-to-noise and does not require phase unwrapping of the wave functions; importantly, it is very reliable for low-contrast samples and high impinging energies. Even when the proposed method fails to deliver an accurate prediction, it can serve well the purpose of disclosing the identity of the medium in the case it has been picked from a well-known list. The introduced scheme may constitute the first step toward flawless generic estimation of quantum texture if implemented multiple times for various energies or incidence angles, and the collected data are post-processed by suitable algorithmic routines. [ABSTRACT FROM AUTHOR]

Trial production of 0.25 mm‐thick thin‐gauge high‐grade nonoriented silicon steel with a Si content of 3.5% by the secondary cold rolling process is studied. The recrystallization microstructure and magnetic properties are systematically studied by the microstructure, texture evolution, and the effect of two‐stage cold rolling reduction ratios (37.5–70.5%) during the whole process. The results show that the magnetic induction intensity B5000 first increases and then decreases; the iron loss first decreases and then increases at the frequencies of 50 and 400 Hz with the reduction of the cold rolling reduction rate in the second stage. The cubic and Goss texture of the finished annealed sheet has the highest strength when the reduction ratio of the second stage cold rolling is 58.3%. The highest magnetic induction intensity, B5000 = 1.671 T. Lowest iron loss, P1.0/50 = 0.83 W kg−1, P1.5/50 = 1.98 W kg−1, and P1.0/400 = 11.94 W kg−1, respectively. [ABSTRACT FROM AUTHOR]

Ferrite/martensite steel is an important material candidate for nuclear reactor claddings owing to its excellent mechanical properties and radiation resistance. In particular, the hot deformation behavior of 12Cr‐ferritic/martensitic (12Cr‐F/M) steel is crucial for the fabrication of cladding tubes, and experiments performed in a wide temperature range could reveal the possible thermal deformation behavior of 12Cr‐F/M steel during tube fabrication. Herein, hot compression experiments of 12Cr‐F/M steel are conducted with strain rates and deformation temperatures ranging from 0.005 to 5 s−1 and 750 to 1200 °C, respectively. According to the thermal deformation flow and thermal expansion curves of the alloy, the Arrhenius‐type constitutive equations before and after the phase transformation of 12Cr‐F/M steel are established, taking 950 °C as the critical point. The results show that for a strain rate of 0.5 s−1, the cooling intensity increases gradually with the deformation temperature. The ferrite transforms into a mixed structure of ferrite and pearlite and finally transforms into martensite. At 950 °C, the degree of austenitization of the alloy increases with the strain rate, and the texture changes from cubic to brass. [ABSTRACT FROM AUTHOR]

Mineral replacement reactions mediated by fluids are common in sedimentary basins, where they influence geochemical cycles. Phosphorous (P) pollution of soils, sediments and water bodies is currently a widespread problem. Some apatite accumulations in sediments may have formed through the interaction of P-bearing aqueous solutions with mineral surfaces that result in mineral replacement reactions. Here, we investigate the pseudomorphic replacement of anhydrite single crystals by aggregates of β-tricalcium phosphate and hydroxyapatite upon interaction with a P-bearing solution at temperatures between 120 and 200 °C. SEM imaging is used to study the texture of the aggregates. Rietveld refinement of the X-ray diffraction patterns and Raman spectra analysis of the reacted samples provide information on the kinetics of the replacement. At all temperatures β-tricalcium phosphate forms alongside hydroxyapatite at early stages of the replacement reaction. At T ≥ 180 °C, hydroxyapatite/β-tricalcium phosphate ratio rapidly increases, and hydroxyapatite is the only phase in fully replaced samples. At T < 180 °C hydroxyapatite/β-tricalcium phosphate ratio increases slowly and fully replaced samples still contain significant amounts of β-tricalcium phosphate. The progress of the replacement is facilitated by the formation of porosity. The evolution of the hydroxyapatite/β-tricalcium phosphate ratio and the crystal habit of both phases strongly influence the arrangement of this porosity. The empirical activation energy Ea (kJ/mol) of the replacement reaction is determined by the Avrami and the iso-conversion methods. Both approaches yield an Ea of ~40 kJ/mol. Anhydrite dissolution appears as the rate-limiting process and the overall kinetics of the replacement reaction is controlled by the rate diffusion of dissolved species through the porosity network. The ripening of the metastable β-tricalcium phosphate into hydroxyapatite affects the characteristics of the porosity network and further modulates the kinetics of the replacement. These results may improve the understanding of the mechanisms of P-sequestration by mineral surfaces through coupled dissolution–precipitation reactions and shed light on the origin of apatite accumulations associated to evaporitic sedimentary rocks. [ABSTRACT FROM AUTHOR]

Herein, dynamic and postdynamic recrystallization behaviors of GWZ magnesium are investigated. Toward this end, the single‐hit and double‐hit hot compression tests are conducted under strain rate of 0.001 s−1 at 400 °C. The prestrains of 0.1 and 0.5 are considered to investigate the effect of interpass time (5–300 s) on the compressive strength level. At the low strain level of 0.1, the contribution of Hall–Petch effect is considerable due to the occurrence of static recrystallization. In addition, the rare earth texture component is eliminated during interpass annealing. This causes increasing the strength of the material during second pass of hot compression. In contrast, at higher imposed strain, the strength level decreases with increasing the interpass time of annealing. The high amount of strain is completely consumed and the remaining stored energy is not high enough to trigger the occurrence of static recrystallization. The occurrence of metadynamic recrystallization and subsequent growth are characterized. In addition, the texture does not change in respect of the intensity or numbers/types of components. Accordingly, the observed decreasing trend of the strength is justified relying on the occurrence grain growth. [ABSTRACT FROM AUTHOR]

Focal research has been conducted on medium-entropy alloys (MEAs) that exhibit a balanced combination of strength and plasticity. In this study, the microstructure, dynamic mechanical properties, and texture evolution of an as-cast medium-entropy CoCr0.4NiSi0.3 alloy were investigated through dynamic compression tests at strain rates ranging from 2100 to 5100 s−1 using the Split Hopkinson Pressure Bar in order to elucidate the underlying dynamic deformation mechanism. The results revealed a significant strain rate effect with dynamic compressive yield strengths of 811 MPa at 2100 s−1, 849 MPa at 3000 s−1, 919 MPa at 3900 s−1, and 942 MPa at 5100 s−1. Grains were dynamically refined from 19.73 to 3.35 μm with increasing strain rates. The correlation between adiabatic temperature rise induced by dynamic compression and dynamic recrystallization was examined, revealing that the latter is not associated with adiabatic heating but rather with phase transition triggered by the dynamic stress during compression. The proportion of Σ3n (1 ≤ n ≤ 3) grain boundaries in deformation specimens increases with increasing strain rates during dynamic compression. The formation of specific three-node structures enhances both strength and plasticity by impeding crack propagation and resisting higher mechanical stress. In the as-cast state, significant anisotropy was observed in the MEA. As strain rates increased, it transited into a stable {111}<112> F texture. The exceptional dynamic properties of strength and plasticity observed in the as-cast state of the MEA can be attributed to a deformation mechanism involving a transition from dislocation slip to the formation of intricate arrangements, accompanied by interactions encompassing deformation nanotwins, stacking faults, Lomer–Cottrell locks, stair-rods, and displacive phase transformations at elevated strain rates. [ABSTRACT FROM AUTHOR]

The dense and accurate measurement of 3D texture is helpful in evaluating the pavement function. To form dense mandatory constraints and improve matching accuracy, the traditional binocular reconstruction technology was improved threefold. First, a single moving laser line was introduced to carry out global scanning constraints on the target, which would well overcome the difficulty of installing and recognizing excessive laser lines. Second, four kinds of improved algorithms, namely, disparity replacement, superposition synthesis, subregion segmentation, and subregion segmentation centroid enhancement, were established based on different constraint mechanism. Last, the improved binocular reconstruction test device was developed to realize the dual functions of 3D texture measurement and precision self-evaluation. Results show that compared with traditional algorithms, the introduction of a single laser line scanning constraint is helpful in improving the measurement's accuracy. Among various improved algorithms, the improvement effect of the subregion segmentation centroid enhancement method is the best. It has a good effect on both overall measurement and single point measurement, which can be considered to be used in pavement function evaluation. [ABSTRACT FROM AUTHOR]

Currently, climate change requires the quantification of carbon stored in forest biomass. Synthetic aperture radar (SAR) data offers a significant advantage over other remote detection measurement methods in providing structural and biomass-related information about ecosystems. This study aimed to develop non-parametric Random Forest regression models to assess the changes in the aboveground forest biomass (AGB), basal area (G), and tree density (N) of Mediterranean pine forests by integrating ALOS-PALSAR, Sentinel 1, and Landsat 8 data. Variables selected from the Random Forest models were related to NDVI and optical textural variables. For 2015, the biomass models with the highest performance integrated ALS-ALOS2-Sentinel 1-Landsat 8 data (R2 = 0.59) by following the model using ALS data (R2 = 0.56), and ALOS2-Sentinel 1-Landsat 8 (R2 = 0.50). The validation set showed that R2 values vary from 0.55 (ALOS2-Sentinel 1-Landsat 8) to 0.60 (ALS-ALOS2-Sentinel 1-Landsat 8 model) with RMSE below 20 Mg ha−1. It is noteworthy that the individual Sentinel 1 (R2 = 0.49). and Landsat 8 (R2 = 0.47) models yielded equivalent results. For 2020, the AGB model ALOS2-Sentinel 1-Landsat 8 had a performance of R2 = 0.55 (validation R2 = 0.70) and a RMSE of 9.93 Mg ha−1. For the 2015 forest structural variables, Random Forest models, including ALOS PAL-SAR 2-Sentinel 1 Landsat 8 explained between 30% and 55% of the total variance, and for the 2020 models, they explained between 25% and 55%. Maps of the forests' structural variables were generated for 2015 and 2020 to assess the changes during this period using the ALOS PALSAR 2-Sentinel 1-Landsat 8 model. Aboveground biomass (AGB), diameter at breast height (dbh), and dominant height (Ho) maps were consistent throughout the entire study area. However, the Random Forest models underestimated higher biomass levels (>100 Mg ha−1) and overestimated moderate biomass levels (30–45 Mg ha−1). The AGB change map showed values ranging from gains of 43.3 Mg ha−1 to losses of −68.8 Mg ha−1 during the study period. The integration of open-access satellite optical and SAR data can significantly enhance AGB estimates to achieve consistent and long-term monitoring of forest carbon dynamics. [ABSTRACT FROM AUTHOR]

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Ti6Al4V alloy has been widely used in aerospace and medical fields due to its advantages in superb high strength-to-weight ratio and biocompatibility. However, the hard machinability of Ti6Al4V alloy seriously affects the surface integrity and performance of components. This paper adopts a hybrid process of picosecond laser ablation and micro-milling to fabricate a high-quality U-shape groove on a Ti6Al4V alloy surface. Material removal mechanisms under a single micro-milling process and hybrid process are obtained through experiments and simulations. Picosecond laser ablation with material removal is utilized to produce different textures on the workpiece surface prior to the micro-milling process, and the effect of surface textures on the subsequent micro-milling process is revealed. Furthermore, simulation results show that surface textures ablated by picosecond laser can directly reconstruct the axial cutting depth of micro-milling, thus converting continuous chip forming into an intermittent process and effectively reducing the cutting force. This study offers a promising process to effectively improve the machining performance of hard-to-machine materials. [ABSTRACT FROM AUTHOR]

Active contour models (ACMs) are popular and widely used for many image segmentation applications and obtain promising results. However, these methods are unable to achieve the highest performance in the presence of intensity inhomogeneity. To address this issue, this paper presents an ACM based on the combination of a convolutional neural network (CNN) and a texture descriptor approach. This study uses a CNN model to generate parameter maps more effectively for ACM. Compared to conventional global techniques, these parameter maps increase the speed of movement of the contour into the target. In this approach, the Local Word Directional Pattern (LWDP) is applied as the texture descriptor. LWDP is a texture descriptor that uses the angle between two gradients for exploring the texture structure inside the image. In the proposed method both the original image and the new image obtained by the LWDP texture descriptor (encoded image) are provided as inputs to the CNN. The experimental outcomes show that the proposed strategy consistently outperforms the state-of-the-art in accuracy and robustness for segmenting images with fuzzy boundaries and intensity inhomogeneity. [ABSTRACT FROM AUTHOR]