Variety Of Textures Research Articles

SymSwin: Multi-Scale-Aware Super-Resolution of Remote Sensing Images Based on Swin Transformers

Despite the successful applications of the remote sensing image in agriculture, meteorology, and geography, its relatively low spatial resolution is hindering the further applications. Super-resolution technology is introduced to conquer such a dilemma. It is a challenging task due to the variations in object size and textures in remote sensing images. To address that problem, we present SymSwin, a super-resolution model based on the Swin transformer aimed to capture a multi-scale context. The symmetric multi-scale window (SyMW) mechanism is proposed and integrated in the backbone, which is capable of perceiving features with various sizes. First, the SyMW mechanism is proposed to capture discriminative contextual features from multi-scale presentations using corresponding attentive window size. Subsequently, a cross-receptive field-adaptive attention (CRAA) module is introduced to model the relations among multi-scale contexts and to realize adaptive fusion. Furthermore, RS data exhibit poor spatial resolution, leading to insufficient visual information when merely spatial supervision is applied. Therefore, a U-shape wavelet transform (UWT) loss is proposed to facilitate the training process from the frequency domain. Extensive experiments demonstrate that our method achieves superior performance in both quantitative metrics and visual quality compared with existing algorithms.

Estimation of dynamic soil properties for geotechnical analysis in the Niger Delta using index testing and empirical correlations

This study investigated geotechnical properties of subsurface soils from Mbiama town in Rivers State, Niger Delta region through laboratory index testing and development of empirical correlations to estimate dynamic soil parameters. Grain size analyses revealed heterogeneous stratigraphy transitioning from upper clayey sands to lower gravelly sands deposited under changing fluvio-deltaic conditions. Atterberg limits exhibited decreasing plasticity trends with depth confirming the textural variations. Laboratory data conforms to layering architecture inferred from depositional facies analyses. Predictive models were developed relating Standard Penetration Test blow counts (SPT-N) and shear wave velocity (Vs) to depth, moisture content and percentage sand. High regression coefficients validated models' accuracy in reproducing over 90% of field measurements. Factor of safety against liquefaction was correlated to SPT-N, accounting for density-dependent properties. Index-based characterizations aligned well with trends predicted by the empirical correlations. This research demonstrated robust indirect estimation of dynamic geotechnical indices for foundation design and seismic risk analysis in data-scarce Niger Delta through standardized field and laboratory index testing integrated with depositionally-linked predictive models.

Influence of Textural and Compositional Heterogeneities on the Staining of Silicate Ornamental Rocks

Objective: This study aims to compare the results of staining tests carried out on natural silicate ornamental stone samples. The staining test was applied to different regions of the same slab of rock, assessing the behavior of a staining agent, oil, in relation to the textural variations and compositional characteristics of the natural rocks investigated. From this analysis, we hope to better understand how these properties influence the interaction with the staining agent, contributing to knowledge about the durability and aesthetic maintenance of ornamental stones in commercial use. Theoretical background: Ornamental stones, as well as being beautiful, must be durable and functional, maintaining their aesthetic, physical and chemical properties (ASTM, 2005). However, cleaning products, food and environmental factors can alter these characteristics. Aires-Barros (1991) defines this “alterability” as a function of intrinsic factors (material and porosity), extrinsic factors (environment) and time, which together determine the durability of stone. Method/project/approach: A study compared the behavior of three types of stone exposed to oil as a staining agent, applying a stain resistance test methodology. The procedure followed Document 20 of the ABIROCHAS Technical Documents Collection on the technological characterization of cladding stones and the practices described by Castilho (2018) in Technological Characterization of Ornamental Stones: Laboratory Practices. Results and conclusion: The study carried out in this work showed that the same slab of natural ornamental stone can have areas that are more susceptible to oil staining than other areas on the same slab. The areas with the finest crystalline texture and consequently the least expressive cracking were the areas least affected by oil staining. Another observation based on the results obtained was the loss of shine associated with the areas subjected to staining, even those where the stain was visually removed. In addition to these observations, the color of the ornamental stone, as well as the type of surface finish on the slabs, may also be important variables in the effect of oil staining, since the Anthracite stone with a black color and brushed surface finish was the lithotype that did not show stains after contact with oil. Implications of the research: Natural ornamental stone comprises materials with textural, compositional and structural heterogeneities observed even in a single slab, so the work seeks, through comparisons, to observe areas of greater susceptibility in natural ornamental stone slabs that can interact with oil staining agents. Originality/value: to contribute to the improvement of technologies that contribute to the best performance of natural ornamental stones, taking into account the type of resin and associated finishes.

The Petrochemistry and Origin of Precambrian Gneisses around Madaka and Kwana-Bala Area, North Central Nigeria

This paper discusses the petrochemistry and origin of gneisses within basement complex of Nigeria around Madaka and Kwana-Bala area. The lithological units of rocks from Madaka and Kwana-Bala area comprises of gneisses (migmatitic, banded, granitic), kyanite-sillimanite schist, semi-pelitic schist, amphibolites, talcose rock, quartzite, phyllite, granodiorite, fine-medium-grained granites and porphyritic granite. Seven samples of gneisses were analyzed for major element oxides using (ICM-MS). The gneisses are often variable in colour which depending on the nature and proportion of the feldspar and the ferromagnesian minerals. The variation in textures of these rocks from study area is due to varying size and amount of the K-feldspar porphyroblasts couple with varying degree of foliation. In thin section, the characteristics granoblastic textures were observed in migmatitic and granitic gneisses. The mineral compositions of the gneisses rocks are variable, the common minerals assemblage includes: migmatitic gneiss quartz + plagioclase +microcline +biotite + chlorite +garnet, banded gneiss: quartz + plagioclase+ muscovite +biotite+sphene +chlorite+ garnet and granitic gneiss contain quartz +plagioclase+microcline + muscovite+ biotite + chlorite +garnet + opaque minerals. The gneisses of the study area are product of reworked rocks during the Pan-African with a positive DF values, this suggests igneous sources for the protoliths of these rocks in the study area. The chemistry of the gneissic rock also show a variable proportion of Na2O and K2O with alkali-calcic affinity, which suggests, a closed system behaviour during metamorphism on one hand, and possibly a co-magmatic origin of the igneous protolith on the other hand.

Textural and chemical variation of apatite from Ziyang-Zhuxi alkaline rocks (Central China): Implications for REE migration during magmatic and hydrothermal processes

Textural and chemical variation of apatite from Ziyang-Zhuxi alkaline rocks (Central China): Implications for REE migration during magmatic and hydrothermal processes

Effects of mineral mode and textural variation on the seismic anisotropy in lithospheric mantle: an example from Horoman peridotites

We performed a numerical analysis of seismic velocities in mantle peridotite using the elastic constants and crystallographic preferred orientations (CPOs) of olivine, orthopyroxene, and clinopyroxene. Proportions of olivine in the samples ranged from 50 to 100% mechanically, whereas the two pyroxenes ranged from 0 to 50%. We utilized three lherzolite samples from the Horoman peridotite complex for this study. As the quantity of pyroxene increased, the P-wave velocities in the X-direction (8.35–9.14 km/s) and P-wave anisotropies (5.51–14.50%) decreased in all samples. However, the S1-wave velocities remained relatively consistent, with Vs1 ranging from 4.79 to 5.15 km/s and Vs2 from 4.55 to 4.92 km/s. The maximum S-wave anisotropies decreased as orthopyroxene contents increased. As a consequence, non-negligible effects of pyroxenes resulted in the variation of seismic velocities, suggesting the orthopyroxene/clinopyroxene contents and their CPOs could be one of critical factors for evaluating seismic anisotropy within the upper mantle.Graphical abstract

Insights into transglutaminase on structural and rheological properties of gels from adzuki bean protein pretreated by electric fields

The demand for protein is increasing as the global population continues to grow. The plant protein has been favored and plant-based food has become a research hotspot for healthy diet, environmental protection, animal ethics and other issues. Adzuki bean protein (ABP) is a quality source with complete amino acids, abundant essential amino acids and beanless flavour. ABP is rich in glutamine and lysine which are good substrates for transaminase (TGase) induced gelation. The pulsed electric field (PEF), alternating current EF (ACEF), direct current EF (DCEF) were applied to pretreat ABP aiming at improving the efficacy of TGase induced crosslinking. The results showed that the TGase decreased the free amino amount significantly and increased the molecular weight of ABP. The EF pretreatments significantly influenced the secondary and tertiary structures of ABP with a decrease in β-sheets, increase in random coils, β-turns, and α-helices, also decrease in fluorescence intensity with blueshift. The content of disulfide bond increased with the decrease of free sulfhydryl groups. The ionic bonds decreased and hydrophobic actions surpassed significantly hydrogen bonds. The hydrophobicity increased. The electric field intensity corresponded to variation of microstructure, texture and rheological behaviour of the ABP gel according to the type of the EF.

Impact of Cooking on Tuber Color, Texture, and Metabolites in Different Potato Varieties.

Potatoes are a globally important crop with high nutritional value. Different potato varieties display notable variations in color, texture, and nutrient composition. However, the influence of cooking on tuber color, texture, and metabolites has not been comprehensively explored. This study evaluated the color and texture of five potato varieties before and after cooking. Cooking significantly altered tuber color, decreased hardness and adhesiveness, and increased springiness, particularly after steaming. The metabolomic analysis of Zhongshu 49 (ZS49) and Shishu 3 (SH3) tubers was conducted using gas chromatography-mass spectrometry (GC-MS) and ultra-high performance liquid chromatography (UHPLC)-MS/MS. GC-MS identified 122 volatile metabolites, with 42 significantly varying between cooking treatments, while UHPLC-MS/MS detected 755 nonvolatile metabolites, 445 of which showed significant differences. Compared to ZS49, SH3 exhibited a marked increase in umami- and flavor-related metabolites, especially after cooking. This study provides new insights into how cooking affects the quality, texture, and metabolite profiles of potato tubers.

Investigating Anode Structural Characteristics with Multistage Data Quantification: Influence of Extrinsic Properties of Anodes for Oxidation Evolution Reaction in Alkaline Water Electrolysis

Tackling climate change demands the deployment of sustainable technologies, among which alkaline water electrolysis (AWE) emerges as one of the pivotal solutions. In AWE, anode morphology plays a critical role in facilitating the oxygen evolution reaction (OER), which is a key step in splitting water molecules into oxygen and hydrogen gas. OER performance can be enhanced by fine-tuning the morphology of the anodes [1, 2]. Therefore, there is a critical need to quantitatively comprehend surface morphology or coating quality quantitatively and define the relationships between these surface features and the activity of anodes. We have observed that conducting a quantitative analysis of the nanoscale structure of anodes produced via ultrasonic spray coating provides a reliable metric, serving as a descriptor to evaluate the quality of particle-based catalyst coatings [3, 4]. For this quantitative analysis, it is crucial to characterize the structure with high resolution. However, high-resolution techniques commonly employed such as atomic force microscopy (AFM) have a significant limitation. They cover only a small measurement area that may not represent the entire surface area. In response to this need, we have introduced multistage data quantification (MSDQ) technique as a full-scale surface extrapolation method. The MSDQ technique is a statistical approach that facilitates an impartial characterization of surfaces by optimizing the process of region selection (ROS) and feature extraction, as exemplified in Figure 1. We validated MSDQ through the characterization of anodes produced utilizing different spray coating processing parameters. AFM was employed to capture surface morphology. Through MSDQ, the following surface characteristics are extracted: the surface roughness indicates the variations of surface texture, measuring the peaks and valleys on the surface, the roughness factor refers to the total area covered by the electrode surface to the projected area, and the homogeneity score quantifies the uniformity of the surface structure, essential for assessing the consistency of catalyst coatings were extracted. For validation, in a first proof of principle, extrinsic surface features were correlated to electrocatalytic activity for the oxygen evolution reaction (OER), as quantified through scanning droplet cell (SDC) measurements. The anode that showed a consistent surface topography yielded uniform electrochemical activity, while the anode that displayed irregular surface characteristics also lead to a more wide-spread electrochemical activity. To validate the reliability of the MSDQ technique, we conducted independent ROS measurements and found that the measured features were consistent with the ranges previously predicted by MSDQ. This consistency underscores the effectiveness of MSDQ in accurately characterizing surface features of anode, further establishing its credibility as a robust tool for surface analysis. Taken together, the developed strategy exhibits high potential for adaptability across diverse electrochemical systems and their components. Moreover, it acts as a powerful approach for linking statistically backed-up surface characteristics, also beyond AFM, with electrochemical activity. This capability enhances our understanding of how surface nuances influence the overall electrochemical performance, offering valuable insights into optimizing material compositions and processing techniques for improved functionality.

An integrated approach to characterize diabase sills in Parnaíba Basin, based on geochemical data, cuttings description, and well logs interpretation

Igneous rocks play a fundamental role in the formation and evolution of petroleum systems in several basins around the world. In the Parnaíba Basin, northestern Brazil, the diabase sills and dikes, which compound the Mosquito and Sardinha formations, contribute as a thermal source for an unconventional hydrocarbon generation, as well as providing trap and seal for the petroleum system. To understand these intrusions, we propose a methodology to identify the igneous intrusions in well-logs and interpret their compositional variations. The methodology is based on detailed descriptions of cuttings, X-ray fluorescence (XRF), X-ray diffractometry (XRD) and well logs, such as Gamma Ray (GR), Density (RHOZ) and Photoelectric Factor (PEFZ), from six exploratory wells drilled in the main gas-producing area of the Parnaíba Basin. The intrusions present in these wells were identified through the Igneability Feature and classified based on the GR curve as either “Barriguda” or “Caixote” patterns. The “Barriguda” intrusions show variations in the well logs (GR, RHOZ and PEFZ) along their vertical section, as well as variations in aluminum, calcium, potassium, zirconium, iron, titanium, magnesium, nickel and chromium values, evidencing a great textural and mineralogical variation, confirmed by the mineralogical results of XRD. Data interpretation suggests that the “Barriguda” intrusions are characterized in distinct electrofacies- and chemiofacies that represent an internal variation from top to base, related to magmatic differentiation processes.

Exploring the multispectral acoustic response of reef habitats

In recent decades, the value and utility of multibeam bathymetry and backscatter data has been increasingly recognized within the field of seascape ecology (the ocean-centric equivalent of landscape ecology) to map the bio- and geodiversity of the ocean floor. More recently, multispectral multibeam backscatter has emerged as a promising endeavor in seabed classification, and its acoustic response across multiple frequencies has been studied in a range of substrates. Coral reef systems are an under-represented seabed type within this research, as these shallow water ecosystems are more commonly mapped with optical remote sensing techniques. Further investigation is necessary to determine the extent to which backscatter data can contribute to the characterization of these habitats–especially for reef systems that are beyond the reach of optical remote sensing approaches. This study investigates the multifrequency acoustic response of coral reefs in two study areas on the Abrolhos Shelf, Brazil. Backscatter mosaics and angular response curves (ARC) are investigated to explore the potential applications of these data for enhanced reef seascape characterization. In both survey areas, the acoustic mapping revealed extensive reef features, and the assessment of acoustic response was influenced by reef surface roughness and biological attributes (algal cover). Results contribute significantly to the understanding of multi-frequency signatures in reef seascapes and highlight the potential of backscatter for mapping and monitoring the health of these ecosystems. Herein, the higher frequencies were found to be fundamental for detection of subtle variations in texture in the inter-reef region of both study areas; this underscores the value of employing these frequencies in a multispectral framework for discerning heterogeneities in coarse substrate types. Furthermore, the lower frequencies were indispensable for more precise delineation of reef characteristics in the Abrolhos Channel area, whereas the higher frequencies were the most effective in identifying reefs with epibiotic cover (those characterized by flatter ARC associated with lower backscatter values) in the Forgotten Reefs region.

Midge Paleo-Communities (Diptera Chironomidae) as Indicators of Flood Regime Variations in a High-Mountain Lake (Italian Western Alps): Implications for Global Change

Sediments of alpine lakes serve as crucial records that reveal the history of lacustrine basins, offering valuable insights into the effects of global changes. One significant effect is the variation in rainfall regimes, which can substantially influence nutrient loads and sedimentation rates in lacustrine ecosystems, thereby playing a pivotal role in shaping biotic communities. In this study, we analyze subfossil chironomid assemblages within a sediment core from an alpine lake (western Italian Alps) to investigate the effects of rainfall and flood regime variations over the past 1200 years. Sediment characterization results highlight changes in sediment textures and C/N ratio values, indicating phases of major material influx from the surrounding landscape into the lake basin. These influxes are likely associated with intense flooding events linked to heavy rainfall periods over time. Flooding events are reflected in changes in chironomid assemblages, which in our samples are primarily related to variations in sediment texture and nutrient loads from the surrounding landscape. Increased abundances of certain taxa (i.e., Brillia, Chaetocladius, Cricotopus, Psectrocladius, Cricotopus/Orthocladius Parorthocladius) may be linked to higher organic matter and vegetation inputs from the surrounding landscape. Biodiversity decreased during certain periods along the core profile due to intense flood regimes and extreme events. These results contribute to our understanding of alpine lake system dynamics, particularly those associated with intense flooding events, which are still understudied.

NIMG-79. A RADIOMIC-RISK SCORE FOR SURVIVAL PREDICTION IN GLIOMA: A LARGE MULTI-INSTITUTIONAL RETROSPECTIVE VALIDATION STUDY

Abstract Gliomas have dismal survival. Recently, radiomics has demonstrated success in developing non-invasive image-based biomarkers for survival prediction in gliomas. However, clinical applicability of radiomics-based biomarkers will ultimately require rigorous validation on large, multi-institutional data. This work attempts to evaluate a radiomic-based survival risk-assessment prognostic score on a multi-institutional cohort of Glioma patients. Our rationale is that optimizing and validating radiomic features that capture intensity-based textural variations and morphology-based changes (e.g., local curvature and global contour) on large multi-institutional cohorts can allow for robust risk assessment in Glioma. n=668 pre-operative T1w MRI scans for Glioma patients from 4 cohorts: University of California San Francisco “UCSF” (n=495), LUMIERE (n=86)), xCures (n=13), and Cleveland Clinic (CCF) (n=74) were analyzed. Subjects from UCSF, CCF, and xCures were used for training, whereas the LUMIERE cohort was used for hold-out testing. Following pre-processing, expert-vetted tumor segmentation into Edema (ED) and Enhancing tumor (ET) regions was performed. A total of n=1558 radiomic features were extracted from the tumor regions (779 per region), namely, 31 global contour, 20 curvature-based, 624 gradient co-occurrence statistics, and 104 Collage features. Cox regression model was employed to create a radiomic risk score (RRS) for every subject, which included radiomics features as well as on clinical and demographic variables (IDH, MGMT, sex, age), for survival analysis. RRS incorporated a total of 43 radiomic features, and the associated clinical and demographic variables (CDS), yielding significant differences between high and low risk groups in the training (RRS: p=0.043, HR = 2, CSD: p=0.0031, HR = 2.8) and testing sets (RRS: p=0.0096, HR = 1.8, CSD: p=0.0071, HR = 1.8). Combining RRS and CDS improved the OS prediction at group level (p=3.6e-6, 0.0011, HR=5.4, 2, for training and testing, respectively). Radiomics-based risk-stratification may be promising for reliable risk-stratification in glioma.

LSSF-Net: Lightweight segmentation with self-awareness, spatial attention, and focal modulation

Accurate segmentation of skin lesions within dermoscopic images plays a crucial role in the timely identification of skin cancer for computer-aided diagnosis on mobile platforms. However, varying shapes of the lesions, lack of defined edges, and the presence of obstructions such as hair strands and marker colors make this challenge more complex. Additionally, skin lesions often exhibit subtle variations in texture and color that are difficult to differentiate from surrounding healthy skin, necessitating models that can capture both fine-grained details and broader contextual information. Currently, melanoma segmentation models are commonly based on fully connected networks and U-Nets. However, these models often struggle with capturing the complex and varied characteristics of skin lesions, such as the presence of indistinct boundaries and diverse lesion appearances, which can lead to suboptimal segmentation performance. To address these challenges, we propose a novel lightweight network specifically designed for skin lesion segmentation utilizing mobile devices, featuring a minimal number of learnable parameters (only 0.8 million). This network comprises an encoder–decoder architecture that incorporates conformer-based focal modulation attention, self-aware local and global spatial attention, and split channel-shuffle. The efficacy of our model has been evaluated on four well-established benchmark datasets for skin lesion segmentation: ISIC 2016, ISIC 2017, ISIC 2018, and PH2. Empirical findings substantiate its state-of-the-art performance, notably reflected in a high Jaccard index.

A synthesis of the REE-Fe-polymetallic mineral system of the REE-line, Bergslagen, Sweden: New mineralogical and textural-paragenetic constraints

Rare earth elements (REE) have gained increasing significance for numerous technologies, particularly in today’s rapidly expanding “green transition” applications such as wind generators and electric vehicle traction engines. Among the more well-known REE mineralisation types in Sweden, together with alkaline intrusions and apatite-iron oxide ores, is the classic yet enigmatic REE-Fe-polymetallic mineral system of Bastnäs-type. The mineralisation type is regional in context and occurs in a discontinuous SW-NE-striking belt (the REE-line) in the west-central part of the Palaeoproterozoic Bergslagen ore province, Sweden. This contribution is aimed at integrating and synthesising existing geological mineralogical, and textural features with new observations from both well-known and several lesser-known, underexplored or previously unrecognised REE-enriched occurrences within this belt, and to discuss key features within the context of mineral systems modelling. A considerable diversity in both the style and abundance of REE mineralisation as well as in discrete REE mineralogy is evident both regionally across the entire REE-line and locally within different ore districts or mine fields. These variations also extend laterally within or across different stratigraphic levels, and within different host rocks, primarily skarn-altered metacarbonates but also variably altered felsic metavolcanic rocks. Many of the mineralisations share similar textural features, which record a protracted evolution with multiple stages of formation or replacement of REE-minerals. The earliest recognised REE assemblages feature fine-grained cerite-(CeCa) with minor bastnäsite-(Ce) – bastnäsite-(La) or fluorbritholite-(Ce) – fluorbritholite-(Y) or locally britholite-(Ce) – britholite-(Y) minerals. Such assemblages typically display anhedral-granoblastic textures appearing in folded assemblages, all suggesting recrystallisation and ductile deformation during regional metamorphism of REE-minerals that had formed during an early stage of the Svecokarelian orogeny. Overprinting overgrowths and cross-cutting vein-like features of allanite-group minerals likely represent different stage(s) of REE mineralisation and (re)-mobilisation during this orogenic evolution. Several of the REE-enriched occurrences contain variably abundant and diverse polymetallic Cu-Mo-Bi-(Co) sulphide mineralisation that typically occur in late paragenetic positions and show a prevalence to REE-rich assemblages, often dominated by different allanite-group minerals. Sulphide and REE mineralisation are locally strongly associated with metamorphic minerals formed during metamorphism of variably Mg-(Fe)-altered metavolcanic rocks. The diversity in style and intensity of the REE mineralisations, along with variations in textures and specific mineralogy, suggest slight differences in the ore-forming conditions or environment at the time of mineralisation. Additionally, these differences may also reflect variations in the preservation or modification processes that operated later in the evolution of the Svecokarelian orogeny, also featuring remobilisation of REEs and sulphidic minerals. The insights gained from all available evidence synthesised herein, from micro-scale to province-scale, help define key proxies for prospectivity mapping. The combined evidence supports that the primary ore-forming stages in the mineral system coincided with felsic volcanism and associated sub-volcanic to plutonic processes at around 1.9 Ga.

Reconstructing urban vegetation evolution in China using multimodal deep learning and 30-years Landsat archive

To retrospect the impact of urbanization on vegetation, consistent and reliable maps that provide urban vegetation estimates are required. In this study, we make the first attempt to employ deep learning for urban vegetation mapping of 2120 cities in China using a 30-years Landsat archive (UV-30). We present a multimodal deep learning (MDL) model to combine features from 5 categories, namely reflective bands, remote sensing indices, texture variables, topographical variables, and time labels. We normalized elevation data locally to remove the inter-city differences, while retaining topographic details. We used time labels to account for spectral variability over time and Landsat sensors. The performance of the MDL models was compared with a vanilla deep neural network, random forest, and support vector regression. Results indicated that the fusion of different categories of features improved the prediction accuracy. The MDL performed best in most validation cities, and our results were superior to the fractional maps aggregated from high-resolution datasets in homogeneous urban landscapes. We further analyzed urban vegetation dynamics across the urban core-new town-outskirt gradients of different geographical regions and city sizes. We found a gradually diminishing de-greening trend in urban China, especially in urban cores and new towns. Nevertheless, we observed a more pronounced degradation of urban vegetation in the south regions of China compared to the north, and smaller cities show no evident urban vegetation increase. The suggested framework is valuable for urban vegetation assessments and facilitates a thorough understanding and management of urban ecosystems.

The role of mouse tails in response to external and self-generated balance perturbations on the roll plane.

Chordate tails exhibit considerable morphological and functional diversity, with variations in length, diameter and texture adapted to various ecological roles. While some animals, including humans, have lost or reduced their tails, many vertebrates retain and use their tails for activities such as balancing, climbing and escaping predators. This study investigates how laboratory mice (Mus musculus) use their tails to maintain balance when dealing with external and self-generated perturbations. Mice crossed platforms of different widths, while responding to roll-plane tilts. Our findings show that mice swing their tails to counteract external roll perturbations, generating angular momentum to stabilize themselves. Mice were also found to use active (dynamic stabilizer) and passive (counterweight) tail movement strategies when locomoting on narrow platforms. The results suggest that the tail is a core component of mouse locomotion, especially in challenging balancing conditions.

Nucleation delay controlling the formation of mafic enclaves and banded pumice

The presence of mafic enclaves and banded pumice reveals key physical processes associated with volcanic eruptions. Here, through the textural and geochemical analyses of the 3550 B.P. Waimihia deposits in Taupō, New Zealand, we demonstrate how disequilibrium crystallization controls the way magmas mix. Andesitic enclaves in pyroclastic deposits from this predominantly rhyolitic eruption consist of microlites that crystallized rapidly during mafic injection into rhyolitic host magma. The variation of microlite textures depends on enclave size, implying that mafic enclaves crystallized as discrete blobs within a host rhyolitic magma. However, gray pumice and dark bands in banded pumice are characterized by a lack of or less plagioclase microlites that should be present if equilibrium crystallization occurred. Our textural and chemical data suggest that the lack of plagioclase in gray pumice and dark bands resulted from the nucleation delay arising from the mixing with rhyolitic magma. After mafic magma broke up in a magma chamber as discrete mafic blobs, the plagioclase-free rim of the blobs was disaggregated by shear flow. The eroded mafic blobs form a hybrid magma by mixing with rhyolitic magma, which further delays the plagioclase nucleation. This hybrid magma eventually erupted as gray pumice or banded pumice, depending on the intensity of magma mingling in the conduit. We use a plagioclase nucleation delay model to calculate residence times of hours to tens of hours prior to eruption. Our mixing model with nucleation delay enables small volumes of mafic magma to mix with large amounts of silicic magma.

Understanding the effects of livestock grazing on dryland plant communities within the context of abiotic variability

AbstractDrylands, which cover more than 40% of the Earth's terrestrial surface, face rising agricultural demand and the influence of climate change. Understanding how livestock grazing pressure and local climate affect these environments is pivotal for informed land management. We studied big sagebrush plant communities in southwestern Wyoming over grazing gradients created by artificial livestock watering points. To explore the role of abiotic factors in shaping plant community response to grazing, we assessed the response of plant functional groups to grazing while accounting for soil texture variability across a precipitation gradient. Our models estimated that sagebrush cover responded positively to grazing intensity, with a 6% increase in cover with intensity when comparing the heaviest grazing treatment with the lowest grazing intensity. Perennial bunchgrass cover, the primary forage component, had a small negative response, a 3% decrease in cover from the lowest grazing intensity to the highest. Grazing intensity had no effect on bunchgrass density, perennial forbs, or rhizomatous grasses. Compared with abiotic factors, grazing intensity had a small effect on perennial bunchgrass and bare ground. We found that precipitation explained a 13% increase in perennial bunchgrass cover and a 34% decrease in bare ground cover compared with a 6% increase with increasing intensity across our grazing gradients. Sand content also had a larger effect on perennial bunchgrass cover and density than grazing. Increased sand content was associated with increased bunchgrass cover and density, supporting the inverse texture hypothesis. Our results show that while livestock grazing impacts sagebrush plant communities, its effect is small when compared with the effects of climate and soil. Our study contributes to a growing body of research emphasizing the need to contextualize plant community responses to grazing within specific climatic and edaphic conditions, which will promote effective land management in dryland ecosystems.

Remote Sensing Identification and Information Extraction Method of Glacial Debris Flow Based on Texture Variation Characteristics

The formation mechanism of glacial debris flows in alpine gorge mountain areas is complex, with varying characteristics across different regions. Due to the influence of mountain shadows and the accumulation and ablation of ice and snow, accurately identifying and rapidly extracting glacial debris flows using optical images remains challenging. This study utilizes the Random Forest method to develop a multi-feature spatiotemporal information extraction model based on Landsat-8 images and a glacial debris flow gully identification model. These models were applied to the Songzong–Tongmai section of the Sichuan–Tibet Highway to identify glacial debris flows. The results showed that (1) the multi-feature spatiotemporal extraction model effectively eliminated the interference of mountain shadows and ice–snow phase changes, resulting in a higher accuracy for identifying and extracting glacial debris flows in areas with significant information loss due to deep shadows. The total accuracy was 93.6%, which was 8.9% and 4.2% higher than that of the Neural Network and Support Vector Machine methods, respectively. (2) The accuracy of the glacial debris flow gully identification model achieved 92.6%. The proposed method can accurately and rapidly identify glacial debris flows in alpine gorge mountain areas, facilitating remote sensing dynamic monitoring. This approach reduces the damage caused by debris flows to both transportation and the environment, ensuring the safe passage of highways and promoting the sustainable development of the region.