Surface Changes Research Articles

Runoff Variation in Midstream Hei River, Northwest China: Characteristics and Driving Factors Analysis

Study regionThe midstream of the Hei River Basin (HRB). Study focusThe study investigated the changes in hydrological elements at different time scales in the basin from 1982 to 2020. We used the Budyko coupled balance equation to quantitatively assess the contributions of climate change and human activity-induced land surface changes to runoff during different periods. In addition, the driving factors of flow consumption within the basin were analyzed using wavelet coherence and generalized additive model (GAM). New hydrological insights for the regionPrior to 2001, there was a significant decrease in annual-scale runoff in the midstream. After that, a partial recovery was observed due to the influence of the Ecological Water Transfer Project (EWTP), while the NDVI trend exhibited an opposite pattern. The study indicates that human-induced modification of the underlying surface is the primary driving factor for the decrease in runoff, with land surface factors contributing 84.69% and 65.27% to the runoff reduction during two periods of change, respectively. Further research on the driving forces of runoff consumption reveals that vegetation cover and climate factors jointly regulate the variations in runoff consumption in the midstream, with multifactor effects surpassing those of individual factors, and NDVI emerges as the predominant controlling factor for runoff consumption. Moreover, all anthropogenic factors exhibit a high explanatory power for runoff consumption.

Modeling and Locating the Wind Erosion at the Dry Bottom of the Aral Sea Based on an InSAR Temporal Decorrelation Decomposition Model

The dust originating from the extinct lake of the Aral Sea poses a considerable threat to the surrounding communities and ecosystems. The accurate location of these wind erosion areas is an essential prerequisite for controlling sand and dust activity. However, few relevant indicators reported in this current study can accurately describe and measure wind erosion intensity. A novel wind erosion intensity (WEI) of a pixel resolution unit was defined in this paper based on deformation due to the wind erosion in this pixel resolution unit. We also derived the relationship between WEI and soil InSAR temporal decorrelation (ITD). ITD is usually caused by the surface change over time, which is very suitable for describing wind erosion. However, within a pixel resolution unit, the ITD signal usually includes soil and vegetation contributions, and extant studies concerning this issue are considerably limited. Therefore, we proposed an ITD decomposition model (ITDDM) to decompose the ITD signal of a pixel resolution unit. The least-square method (LSM) based on singular value decomposition (SVD) is used to estimate the ITD of soil (SITD) within a pixel resolution unit. We verified the results qualitatively by the landscape photos, which can reflect the actual conditions of the soil. At last, the WEI of the Aral Sea from 23 June 2020, to 5 July 2020 was mapped. The results confirmed that (1) based on the ITDDM model, the SITD can be accurately estimated by the LSM; (2) the Aral Sea is experiencing severe wind erosion; and (3) the middle, northeast, and southeast bare areas of the South Aral Sea are where salt dust storms may occur.

A Comparative Evaluation of Surface and Elemental Changes in Stainless Steel and Titanium Orthodontic Mini-screw Implants: A Multi-arm Randomized Control Trial.

The present study aimed to compare and quantify the surface changes seen in two most commonly used orthodontic miniscrew implants (MSI) materials; titanium and stainless steel after their clinical use. 40 MSIs (20 titanium and 20 stainless steel) were retrieved from the maxillary arch of 20 subjects (13 females and 7 males) in the age group of 18 - 27 years (mean age=22.4 ± 3.83 years) after their intended use. 40 (20 titanium and 20 stainless steel) asreceived MSIs were used as control. All the MSIs were analyzed under a Scanning Electron Microscope (SEM) for the characterization of their morphological condition (blunting of tip, surface defects and corrosion). Furthermore, Energy Dispersive X-ray (EDX) microanalysis was carried out to study the changes in surface characterization. When imaged using SEM, as-received Titanium and Stainless Steel MSIs demonstrated a relatively smooth surface with no surface defects. However, the retrieved titanium and stainless-steel implants showed increased surface defects (both corrosion and cracks) with the difference being statistically significant. The retrieved Titanium MSIs (115.31±24.38μm) showed 4 times more blunting compared to the retrieved Stainless-steel MSIs (29.74±8.56 μm), with the latter showing 2-3 times more surface corrosion. Clinical usage had pronounced effects on both Titanium and Stainless steel MSI alloys in terms of changes in the surface characteristics. While stainless steel MSIs are more susceptible to surface corrosion, Titanium MSIs exhibit greater alterations in the form of tipblunting and cracks in screw threads.

Cross‐attention neural network for land cover change detection with remote sensing images

AbstractLand cover change detection (LCCD) with remote sensing images (RSIs) is important for observing the land cover change of the Earth's surface. Considering the insufficient performance of the traditional self‐attention mechanism used in a neural network to smoothen the noise of LCCD with RSIs, in this study a novel cross‐attention neural network (CANN) was proposed for improving the performance of LCCD with RSIs. In the proposed CANN, a cross‐attention mechanism was achieved by employing another temporal image to enhance attention performance and improve detection accuracies. First, a feature difference module was embedded in the backbone of the proposed CANN to generate a change magnitude image and guide the learning progress. A self‐attention module based on the cross‐attention mechanism was then proposed and embedded in the encoder of the proposed network to make the network pay attention to the changed area. Finally, the encoded features were decoded to obtain binary change detection with the ArgMax function. Compared with five methods, the experimental results based on six pairs of real RSIs well demonstrated the feasibility and superiority of the proposed network for achieving LCCD with RSIs. For example, the improvement for overall accuracy for the six pairs of real RSIs improved by our proposed approach is about 0.72–2.56%.

Enhanced Detection of Artisanal Small-Scale Mining with Spectral and Textural Segmentation of Landsat Time Series

Artisanal small-scale mines (ASMs) in the Amazon Rainforest are an important cause of deforestation, forest degradation, biodiversity loss, sedimentation in rivers, and mercury emissions. Satellite image data are widely used in environmental decision-making to monitor changes in the land surface, but ASMs are difficult to map from space. ASMs are small, irregularly shaped, unevenly distributed, and confused (spectrally) with other land clearance types. To address this issue, we developed a reliable and efficient ASM detection method for the Tapajós River Basin of Brazil—an important gold mining region of the Amazon Rainforest. We enhanced detection in three key ways. First, we used the time-series segmentation (LandTrendr) Google Earth Engine (GEE) Application Programming Interface to map the pixel-wise trajectory of natural vegetation disturbance and recovery on an annual basis with a 2000 to 2019 Landsat image time series. Second, we segmented 26 textural features in addition to 5 spectral features to account for the high spatial heterogeneity in ASM pixels. Third, we trained and tested a Random Forest model to detect ASMs after eliminating irrelevant and redundant features with the Variable Selection Using Random Forests “ensemble of ensembles” technique. The out-of-bag error and overall accuracy of the final Random Forest was 3.73 and 92.6%, which are comparable to studies mapping large industrial mines with the normalized difference vegetation index (NDVI) and LandTrendr. The most important feature in our study was NDVI, followed by textural features in the near and shortwave infrared. Our work paves the way for future ASM regulation through large area monitoring from space with free and open-source GEE and operational satellites. Studies with sufficient computational resources can improve ASM monitoring with advanced sensors consisting of spectral narrow bands (Sentinel-2, Environmental Mapping and Analysis Program, PRecursore IperSpettrale della Missione Applicativa) and deep learning.

Reproductive biology of Capparis decidua (Kair): A potential underutilized multipurpose plant of arid and semi arid region

Foliation and flowering of Capparis decidua occurs three times a year i.e. from January to November months. Flowers are bracteate, pedicellate, complete, hermaphrodite, zygomorphic, hypogynous with slender pedicel, usually light red, scarlet red and yellow in colour. Anthesis was maximum between 4.00 p.m. to 8.00 PM and 6.00 to 10.00 AM. Pollen grains are prolate, tricolporate, trilobed, with costae, colpal membrane sparsely granulated. Anther dehiscence takes place after 20–30 minutes of anthesis at 6.00 to 8.00 PM by the time the flowers starts antehsizing, the anthers are almost mature. The viability of pollen grains ranges from 38–52%, and starts decreasing in the stored pollen. The percentage fruit set decreases with the collection time of the pollen grains and plant type. According to visual observation stigmatic surface change in the appearance i.e. green coloured stigma was considered receptive while dull and brown was accounted non-receptive. Pollen germination in-vivo showed 80 per cent stigma receptive and 90 percent of fruit set in the flowers pollinated on the time of anthesis. Pollen grains per anther were ranging from 331–369, fully developed and mature anthers differing significantly among the plant types. The mean number of pollen grains per ovule was 4309 thus the pollen-ovule ratio was 431:1. There is 17–23% fruit set observed under self pollination (autogamy and geitonogamy) and 52–72% as a result of cross pollination. The cross pollinated nature of C. decidua is due to entomophilic nature of flowers, insect visitors which play the main role of pollination are from Apidae and Papilionidae.

Durability of Japanese-earth cob walls subjected to accelerated rain simulation

Earthen materials are increasingly being recognized in architecture for their low embodied energy, recyclability, and hygrothermal properties. However, the common use of manufactured stabilizers, while enhancing weathering resistance, compromises these merits. Japan, known for its typhoons, has used unstabilized earth in construction for centuries, suggesting the viability of this construction material. While architecture around the world attests to its resilience, in-depth research into unstabilized earthen material is limited. This study examines unstabilized earth durability through 90-min accelerated rain simulation tests, totaling over 6500 mm of “rain” exposure on each of twelve test surfaces (eight representing rural Japanese cob-ball construction and four, monolithic cob walls). Surface changes were monitored by 3D scans performed at seven intervals. The test walls were built using two common materials in Japanese earthen wall craft, sourced from the areas of Kashiba and Fukakusa. It was clear from 3D-scan analysis that the base-layer material, Kashiba, is remarkably resistant to weathering. The four monolithic Kashiba test surfaces, constructed on four different foundation types, respectively eroded just 1 mm, 2.6 mm, 3.8 mm, and 3.9 mm. These results corroborate traditional building practices. Thus, our study also underscores the value of incorporating knowledge from vernacular earthen architecture professionals in expediting academic research. Additionally, our results suggest the potential of hose-showerhead tool use for research, and for on-site testing of earthen material erosion levels for material adequacy.

Study on the effects of inorganic salts and ionic surfactants on the wettability of coal based on the experimental and molecular dynamics investigations

Through the evaluation and preparation of a novel inorganic salt composite solution consisting of sodium dodecyl benzene sulfonate (SDBS), the nonionic surfactants polyethylene glycol pisooctyl phenyl ether (Triton X-100), and inorganic salt Na2SO4, based on surface tension, contact angle, settling time, wetting rate, and changes in the surface microstructure and functional groups of coal, this study analyzed the wetting behavior of the solution on coal dust and its adsorption capacity on the surface of coal particles. The results demonstrate that the composite solution of inorganic salts can significantly enhance the wettability of coal samples, reducing the contact angle to 21.54° and lowering the surface tension to 26.10 mN/m. After treatment with the solution, the relative content of oxygen-containing functional groups in the microscopic structure of the coal sample increased to 59.6 % and pores more prominent than 25 nm increased to 34.63 %. Molecular dynamics (MD) simulations of the water-inorganic salt composite solution-coal system are conducted using Materials Studio software, revealing that after the addition of the composite solution, the self-diffusion coefficient (D) of water molecules is 6.3 × 10-9 m2/s, the starting point of the composite solution is 15 Å, and the system's interaction energy increase to 14000 kcal/mol. It further elucidated the modification of the surface molecular structure of coal dust by the inorganic salt composite solution, increasing hydrogen bonds, enhancing wetting, and demonstrating a solid adsorption capability of the inorganic salt composite solution on the surface of coal dust.

Interpretable baseflow segmentation and prediction based on numerical experiments and deep learning

Baseflow is a crucial water source in the inland river basins of high-cold mountainous region, playing a significant role in maintaining runoff stability. It is challenging to select the most suitable baseflow separation method in data-scarce high-cold mountainous region and to evaluate effects of climate factors and underlying surface changes on baseflow variability and seasonal distribution characteristics. Here we attempt to address how meteorological factors and underlying surface changes affect baseflow using the Grey Wolf Optimizer Digital Filter Method (GWO-DFM) for rapid baseflow separation and the Long Short-Term Memory (LSTM) neural network model for baseflow prediction, clarifying interpretability of the LSTM model in baseflow forecasting. The proposed method was successfully implemented using a 63-year time series (1958–2020) of flow data from the Tai Lan River (TLR) basin in the high-cold mountainous region, along with 21 years of ERA5-land meteorological data and MODIS data (2000–2020). The results indicate that: (1) GWO-DFM can rapidly identify the optimal filtering parameters. It employs the arithmetic average of three methods, namely Chapman, Chapman-Maxwell and Eckhardt filter, as the best baseflow separation approach for the TLR basin. Additionally, the baseflow significantly increases after the second mutation of the baseflow rate. (2) Baseflow sources are mainly influenced by precipitation infiltration, glacier frozen soil layers, and seasonal ponding. (3) Solar radiation, temperature, precipitation, and NDVI are the primary factors influencing baseflow changes, with Nash-Sutcliffe efficiency coefficients exceeding 0.78 in both the LSTM model training and prediction periods. (4) Changes in baseflow are most influenced by solar radiation, temperature, and NDVI. This study systematically analyzes the changes in baseflow and response mechanisms in high-cold mountainous region, contributing to the management of water resources in mountainous basins under changing environmental conditions.

The development of sensitive graphene-based surface acoustic wave sensors for NO2 detection at room temperature

Bilayer graphene (Bl-Gr) and sulphur-doped graphene (S-Gr) have been integrated with LiTaO3 surface acustic wave (SAW) sensors to enhance the performance of NO2 detection at room temperature. The sensitivity of the Bl-Gr SAW sensors toward NO2, measured at room temperature, was 0.29º/ppm, with a limit of detection of 0.068 ppm. The S-Gr SAW sensors showed 0.19º/ppm sensitivity and a limit of detection of 0.140 ppm. The origin of these high sensitivities was attributed to the mass loading and elastic effects of the graphene-based sensing materials, with surface changes caused by the absorption of the NO2 molecules on the sensing films. Although there are no significant differences regarding the sensitivity and detection limit of the two types of sensors, the measurements in the presence of interferent gases and various humidity conditions outlined much better selectivity and sensing performances towards NO2 gas for the Bl-Gr SAW sensors.Graphical

Strengthening the fiber-cement matrix interface by introducing functional groups on fiber surface

Polypropylene (PP) fiber is widely used for reinforcing cement matrix to improve its cracking resistance, but the poor interaction between two materials caused localized cracks along the fiber thus adverse effect on the fiber reinforced composites. Thus, novel methods for strengthening the fiber-cement matrix interface were proposed in this study. Amidoxime and amine functional groups were successfully grafted onto PP fiber surface through a two-step chelating procedure. XPS, FTIR, iGC-SEA and TG were employed to characterize the modified fibers, and the results verified that the surface treatment significantly improved the surface roughness, specific surface area, hydrophily and thermostability of PP fiber. Moreover, single fiber pullout, uniaxial tensile and three-point bending were conducted to assess the efficiency of surface treatment in enhancing the bonding between fiber and cement matrix, as well as the tensile and flexural strength of composites incorporating PP fibers. The bonding strength was increased by 84.15%–90.08 % and the flexural strength at 28 days was increased by 23.7%–26.4 %. The change in PP fiber surface led to densified fiber-cement matrix ITZ, enhanced chemical bonding and mechanical interlocking thus stronger interaction between fiber and cement matrix. Overall, the proposed surface treatment method is of great potential to be used in producing high performance concrete due to its easy of application and high efficiency.

Global structure graph mapping for multimodal change detection

ABSTRACT Multimodal change detection (MCD) combines multiple remote sensing data sources to realize surface change monitoring, which is essential for disaster evaluation and environmental monitoring. However, due to the ‘incomparable’ features in multimodal data, traditional change detection methods for unimodal (homogenous) data no longer apply. To address this issue, this paper proposes a novel MCD method with global structure graph mapping (GSGM) which extracts the ‘comparable’ structural features between multimodal datasets and constructs a global structure graph (GSG) to express the structure information for each of the multi-temporal images, which are then cross-mapped to the other data domain. The change intensity (CI) is determined by measuring the change of GSGs after mapping and the differences between GSGs and mapped GSGs. The forward and backward CI maps (CIMs) are then fused with the latent low-rank representation method (LLRR), and the change map (CM) is obtained by threshold segmentation. Experiments on five multimodal and four unimodal datasets demonstrate the effectiveness and robustness of the proposed method (source code is made available at https://github.com/rshante0426/GSGM).

Multi-Scale Fusion Siamese Network Based on Three-Branch Attention Mechanism for High-Resolution Remote Sensing Image Change Detection

Remote sensing image change detection (CD) is an important means in remote sensing data analysis tasks, which can help us understand the surface changes in high-resolution (HR) remote sensing images. Traditional pixel-based and object-based methods are only suitable for low- and medium-resolution images, and are still challenging for complex texture features and detailed image detail processing in HR images. At present, the method based on deep learning has problems such as inconsistent fusion and difficult model training in the combination of the difference feature information of the deep and shallow layers and the attention mechanism, which leads to errors in the distinction between the changing region and the invariant region, edge detection and small target detection. In order to solve the above problems of inconsistent fusions of feature information aggregation and attention mechanisms, and indistinguishable change areas, we propose a multi-scale feature fusion Siamese network based on attention mechanism (ABMFNet). To tackle the issues of inconsistent fusion and alignment difficulties when integrating multi-scale fusion and attention mechanisms, we introduce the attention-based multi-scale feature fusion module (AMFFM). This module not only addresses insufficient feature fusion and connection between different-scale feature layers, but also enables the model to automatically learn and prioritize important features or regions in the image. Additionally, we design the cross-scale fusion module (CFM) and the difference feature enhancement pyramid structure (DEFPN) to assist the AMFFM module in integrating differential information effectively. These modules bridge the spatial disparity between low-level and high-level features, ensuring efficient connection and fusion of spatial difference information. Furthermore, we enhance the representation and inference speed of the feature pyramid by incorporating a feature enhancement module (FEM) into DEFPN. Finally, the BICD dataset proposed by the laboratory and public datasets LEVIR-CD and BCDD are compared and tested. We use F1 score and MIoU values as evaluation metrics. For AMBMFNet, the F1 scores on the three datasets are 77.69%, 81.57%, and 77.91%, respectively, while the MIoU values are 84.65%, 85.84%, and 84.54%, respectively. The experimental results show that ABMFNet has better effectiveness and robustness.

Experimental Investigation of the Effects of Grooves in Fe2O4/Water Nanofluid Pool Boiling

In this study, we systematically explored how changing groove surfaces of iron oxide/water nanofluid could affect the pool boiling heat transfer. We aimed to investigate the effect of three types of grooves, namely rectangular, circular, and triangular, on the boiling heat transfer. The goal was to improve heat transfer performance by consciously changing surface structure. Comparative analyses were conducted with deionized water to provide valuable insights. Notably, the heat transfer coefficient (HTC) exhibited a significant increase in the presence of grooves. For deionized water, the HTC rose by 91.7% and 48.7% on circular and rectangular grooved surfaces, respectively. Surprisingly, the triangular-grooved surface showed a decrease of 32.9% in HTC compared to the flat surface. On the other hand, the performance of the nanofluid displayed intriguing trends. The HTC for the nanofluid diminished by 89.2% and 22.3% on rectangular and triangular grooved surfaces, while the circular-grooved surface exhibited a notable 41.2% increase in HTC. These results underscore the complex interplay between groove geometry, fluid properties, and heat transfer enhancement in nanofluid-based boiling. Hence, we thoroughly examine the underlying mechanisms and elements influencing these observed patterns in this research. The results provide important insights for further developments in this area by shedding light on how surface changes and groove geometry may greatly affect heat transfer in nanofluid-based pool boiling systems.

Surface roughness and optical characteristics evaluations after chairside adjustment of different zirconia types.

Limited evidence is available for the effect of chairside adjustment using rotary cutting instruments on the surface roughness and optical properties of different zirconia types. To evaluate the effect of simulated adjustments on surface roughness and optical properties of different zirconia types. Three Partially Stabilized Zirconia (PSZ) types based on mole percent yttria (Y) concentration from the same manufacturer (Katana; Kuraray) were used: 3Y-PSZ, 4Y-PSZ, and 5Y-PSZ. Thirty disk-shaped specimens (Ø14 × 1.2 mm) from different zirconia types (N = 90) were prepared. Specimens were either left without adjustment (NA), adjusted with Dialite ZR finishing and polishing system (Brasseler) (APol), or adjusted with course diamond instruments only (ADia). The specimens were distributed into 9 groups (n = 10): Group 3Y-PSZ/NA, Group 3Y-PSZ/APol, Group 3Y-PSZ/ADia, Group 4Y-PSZ/NA, Group 4Y-PSZ/APol, Group 4Y-PSZ/ADia, Group 5Y-PSZ/NA, Group 5Y-PSZ/APol, and Group 5Y-PSZ/ADia. The surface roughness of specimen was analyzed using an Atomic Force Microscope (AFM) (Bruker's Dimension Icon, Bruker) and Root Means Square (RMS) were recorded (nm). Surface Gloss (SG), Translucency Parameter (TP), and Contrast Ratio (CR) values of all groups were recorded using an integrating sphere spectrophotometer. Statistical analysis was performed using analysis of variance (ANOVA) and Tukey's multiple comparison tests for pairwise comparisons at p < 0.05 and 95% confidence interval. APol had no effect on the surface roughness (p = 0.88) while ADia had a significant negative effect (p < 0.05) despite the type of zirconia. Out of the three testes optical properties, only SG was negatively affected by ADia for all types of zirconia (p < 0.05). The two adjustment types did not affect the TP of all the tested zirconia (p = 0.91). The CR was not affected by the tested adjustments for all zirconia types (p = 0.726). Proper zirconia adjustment following a sequence of burs and polishers can maintain acceptable roughness and optical properties. Adjustment of zirconia with rough diamond can lead to deleterious effects and should be avoided. Chairside adjustment of zirconia could lead to rougher surface and unpredictable changes of surface gloss. Therefore, zirconia adjustment should be minimized to the greatest extent possible and a proper protocol should be followed if had to be done.

Towards Modelling Mechanical Shaking Using Potential Energy Surfaces: A Toy Model Analysis

In this work, we formalize the effect of mechanical shaking by using various forms of an externally exerted force, which may be constant or may be position-dependent, and we examine the changes in the potential energy surfaces that quantify the chemical reaction. We use a simple toy model to model the potential energy surfaces of a chemical reaction, and we study the effect of a constant or position-dependent externally exerted force for various forms of the force. As we demonstrate, the effect of the force can be quite dramatic on the potential energy surfaces, which acquire new stationary points and new Newton trajectories that are distinct from the original ones that were obtained in the absence of mechanochemical effects. We also introduce a new approach to mechanochemical interactions, using a dynamical systems approach for the Newton trajectories. As we show, the dynamical system attractor properties of the trajectories in the phase space are identical to the stationary points of the potential energy surfaces, but the phase space contains much more information regarding the possible evolution of the chemical reaction—information that is quantified by the existence of unstable or saddle fixed points in the phase space. We also discuss how an experimental method for a suitable symmetric liquid solution substance might formalize the effect of shaking via various forms of external force, even in the form of an extended coordinate-dependent force matrix. This approach may experimentally quantify the Epstein effect of shaking in chemical solutions via mechanochemistry methods.

Study of Mechanical and Surface Properties of Multi-Walled Carbon Nanotube Grafted Flax Fiber and Its Composites

ABSTRACT The modification method of grafting multi-walled carbon nanotubes (MWCNT, abbreviated as CNT in this paper) on the surface of flax fibers was investigated, i.e. CNT were grafted onto the surface of flax fibers by silane coupling agent under the action of ultrasonic waves to form covalent bonding. The tensile strength of CNT grafted flax fiber is 22% higher than that of untreated flax fiber monofilament. The tensile strength of FFRP composites after CNT grafting treatment increased by 14.2%; however, the tensile modulus of single fiber and composites did not show a significant increase, the interfacial shear strength of the fiber-resin is 38.3% higher than that of untreated filament. The improvement of the contact angle after grafting was investigated by observing the surface morphology, and the surface of flax filament was characterized by scanning electron microscopy and atomic force microscopy. Also the elemental changes of the flax single fiber surface before and after the treatment were analyzed using X-ray photoelectron spectroscopy. The results showed that the tensile strength of flax single fibers, its composites, and interfacial shear strength of fiber-matrix was improved after CNT grafting treatment but the increase of modulus was not obvious.

Intra-Individual Paired Mass Spectrometry Dataset for Decoding Solar-Induced Proteomic Changes in Facial Skin

Photoaging is the premature aging of the skin caused by prolonged exposure to solar radiation. The visual alterations manifest as wrinkles, reduced skin elasticity, uneven skin tone, as well as other signs that surpass the expected outcomes of natural aging. Beyond these surface changes, there is a complex interplay of molecular alterations, encompassing shifts in cellular function, DNA damage, and protein composition disruptions. This data descriptor introduces a unique dataset derived from ten individuals, each with a minimum of 18 years of professional experience as a driver, who are asymmetrically and chronically exposed to solar radiation due to their driving orientation. Skin samples were independently collected from each side of the face using a microdermabrasion-like procedure and analyzed on an Exploris 240 mass spectrometer. Our adapted proteomic statistical framework leverages the sample pairing to provide robust insights. This dataset delves into the molecular differences in exposed skin and serves as a foundational resource for interdisciplinary research in photodermatology, targeted skincare treatments, and computational modelling of skin health.

A 2012–2021 high‐resolution glacier mass balance estimate for Icelandic ice caps based on ArcticDEM and ICESat‐2

AbstractIce caps are important water resources for Iceland and are threatened by climate change. Despite their importance and vulnerability, the geodetic glacier mass balance estimate for the recent decade lacks a high‐resolution result. To address this gap, we first co‐registered the 2012–2021 ArcticDEM (v4) strips with ICESat‐2 points acquired over off‐ice areas and evaluated the accuracy of the co‐registered DEMs. We then applied a per‐pixel weighted liner regression to the multi‐temporal ArcticDEM strips and generated a high‐resolution (2 m) glacier surface elevation change rate for six major Icelandic ice caps. Based on these estimates we calculated the geodetic mass balance. Additionally, we estimated the seasonal relative surface elevation changes using ICESat‐2 ATL06 data for the 2019 to 2021 period. The results showed the co‐registered ArcticDEM strips exhibit good accuracy, with a standard deviation of 1.15 m across the Icelandic ice cap regions. Between 2012 and 2021, Icelandic ice caps experienced a state of mass loss, with a surface elevation change rate of −0.57 ± 0.21 m/a, corresponding to a mass loss of −0.51 ± 0.02 m w.e/a. Spatial variability in glacier surface elevation changes among different Icelandic ice caps ranges −0.19 m/a to −0.75 m/a. The Langjökull ice cap exhibited the most severe glacier mass loss at −0.68 ± 0.006 m w.e/a. Furthermore, our observations indicate a change in seasonal trends occurred across all six ice caps from 2019 to 2021. Specifically, the glacier surface thickening decreased during the accumulation period, while the thinning rate increased during the ablation period. These findings highlight that ArcticDEM v4 strips provide new insights into the mass balance of Icelandic glaciers and will aid in making future water management decisions. Moreover, the high‐resolution surface elevation topography and change rates provided in this study may contribute to an improved understanding of the influence of glacier dynamics on glacier change.

Effects of surfactant types on anthracite dust wettability: Experimental and molecular simulations

To study the wetting mechanism of surfactants at the solid–liquid interface of anthracite, a combination of experiments and molecular simulation was used to explore the adsorption and wetting processes of four surfactants, namely, fatty alcohol polyoxyethylene ether N = 9 (AEO9), Triton X-100, rapid penetrant T (PRT), and sodium alkyl ether sulfate (AES) on anthracite. The wetting mechanism of surfactants on anthracite was analyzed at both macroscopic and microscopic levels by surface tension, contact angle, settling time, and changes in surface morphology and functional groups on the anthracite surface. The presence of OH-π and C = O was determined to significantly enhance anthracite wettability. The anthracite/surfactant/water system was constructed from a microscopic perspective, and the interaction energies, relative concentration distributions along the Z-axis, diffusion coefficient (D) of water molecules, radial distribution functions (RDF) of hydrophilic groups and water molecules, and coordination numbers of the components were analyzed. The results show that the wetting effect depends on the adsorption state of the surfactant at the anthracite/water interface and the strength of the interaction between the surfactant and water molecules. The addition of surfactants enhances the adsorption thickness of water molecules along the Z-axis and generates more hydrogen bonds, which play a role in fixing water molecules and lead to a decrease in the D of water molecules. RPT forms the highest number of hydrogen bonds with water molecules and has the lowest D of 0.479 × 10-5 cm2/s, indicating strong wetting ability. The RDF of O atoms in surfactants and water molecules shows a similar trend, with two peaks one strong and one weak. The coordination numbers are 1.356, 1.057, 1.003, and 0.903, respectively. The final wettability of the surfactant on the anthracite depends on the synergistic interaction between the oxygen functional groups (OGs) as compared to the coordination number of the individual OGs.