Search

In the era of antiretroviral therapy (ART), mortality among people living with the human immunodeficiency virus (HIV) has significantly decreased, yet the population of people living with HIV remains substantial. Among people living with HIV (PLWH), HIV-associated lymphoma (HAL) has surpassed Kaposi’s sarcoma to become the most common tumor in this population in developed countries. However, there remains a dearth of comprehensive and systematic understanding regarding HIV-associated lymphomas. This review aims to shed light on the changes in the immune system among PLWH and the characteristics of the immune microenvironment in HIV-associated lymphoma, with a specific focus on the immune system’s role in these individuals. Additionally, it seeks to explore recent advancements in immunotherapy for the treatment of HIV-associated lymphoma, intending to enhance strategies for immunotherapy in this specific population.

Stripe noise is a general phenomenon in original remote sensing images that both degrades image quality and severely limits its quantitative application. While the classical statistical method is effective in correcting common stripes caused by inaccurately calibrating relative gains and offsets between detectors, it falls short in correcting other nonlinear stripe noises originating from subtle nonlinear changes or random contamination within the same detector. Therefore, this paper proposes a novel trend repair method based on two normal columns directly adjacent to a defective column to rectify the trend by considering the geospatial structure of contaminated pixels, eliminating residual stripe noise evident in level 0 (L0) remote sensing images after histogram matching. GF5-02 VIMI (Gaofen5-02, visual and infrared multispectral imager) images and simulated Landsat 8 thermal infrared sensor (TIRS) images deliberately infused with stripe noise are selected to test the new method and two other existing methods, the piece-wise method and the iterated weighted least squares (WLS) method. The effectiveness of these three methods is reflected by streaking metrics (Streaking), structural similarity (SSIM), peak signal-to-noise ratio (PSNR), and improvement factor (IF) on the uniformity, structure, and information content of the corrected GF5-02 VIMI images and by the accuracy of the corrected simulated Landsat 8 TIRS images. The experimental results indicate that the trend repair method proposed in this paper removes nonlinear stripe noise effectively, making the results of IF > 20. The remaining indicators also show satisfactory results; in particular, the mean accuracy derived from the simulated image remains below a digital number (DN) of 15, which is far superior to the other two methods.

The growing interest in renewable energy solutions for sustainable development has significantly advanced the design and analysis of floating offshore wind turbines (FOWTs). Modeling FOWTs presents challenges due to the considerable coupling between the turbine’s aerodynamics and the floating platform’s hydrodynamics. This review paper highlights the critical role of computational fluid dynamics (CFD) in enhancing the design and performance evaluation of FOWTs. It thoroughly evaluates various CFD approaches, including uncoupled, partially coupled, and fully coupled models, to address the intricate interactions between aerodynamics, hydrodynamics, and structural dynamics within FOWTs. Additionally, this paper reviews a range of software tools for FOWT numerical analysis. The research emphasizes the need to focus on the coupled aero-hydro-elastic models of FOWTs, especially in response to expanding rotor diameters. Further research should focus on developing nonlinear eddy viscosity models, refining grid techniques, and enhancing simulations for realistic sea states and wake interactions in floating wind farms. The research aims to familiarize new researchers with essential aspects of CFD simulations for FOWTs and to provide recommendations for addressing challenges.

Sarcopenia is an age-related syndrome characterized by the loss of skeletal muscle mass and function. Community screening, commonly used in early diagnosis, usually lacks features such as real-time monitoring, low cost, and convenience. This study introduces a promising approach to sarcopenia screening by dynamic plantar pressure monitoring. We propose a wearable flexible-printed piezoelectric sensing array incorporating barium titanate thin films. Utilizing a flexible printer, we fabricate the array with enhanced compressive strength and measurement range. Signal conversion circuits convert charge signals of the sensors into voltage signals, which are transmitted to a mobile phone via Bluetooth after processing. Through cyclic loading, we obtain the average voltage sensitivity (4.844 mV/kPa) of the sensing array. During a 6 m walk, the dynamic plantar pressure features of 51 recruited participants are extracted, including peak pressures for both sarcopenic and control participants before and after weight calibration. Statistical analysis discerns feature significance between groups, and five machine learning models are employed to screen for sarcopenia with the collected features. The results show that the features of dynamic plantar pressure have great potential in early screening of sarcopenia, and the Support Vector Machine model after feature selection achieves a high accuracy of 93.65%. By combining wearable sensors with machine learning techniques, this study aims to provide more convenient and effective sarcopenia screening methods for the elderly.

Clematis Florida (CF) is a folk medicinal herb in the southeast of China, which is traditionally used for treating osteoarticular diseases. However, the mechanism of its action remains unclear. The present study used network pharmacology and experimental validation to explore the mechanism of CF in the treatment of rheumatoid arthritis (RA). Liquid chromatography–mass spectrometry (LC-MS/MS) identified 50 main compounds of CF; then, their targets were obtained from TCMSP, ETCM, ITCM, and SwissTargetPrediction databases. RA disease-related targets were obtained from DisGeNET, OMIM, and GeneCards databases, and 99 overlapped targets were obtained using a Venn diagram. The protein–protein interaction network (PPI), the compound–target network (CT), and the compound–potential target genes–signaling pathways network (CPS) were constructed and analyzed. The results showed that the core compounds were screened as oleanolic acid, oleic acid, ferulic acid, caffeic acid, and syringic acid. The core therapeutic targets were predicted via network pharmacology analysis as PTGS2 (COX-2), MAPK1, NF-κB1, TNF, and RELA, which belong to the MAPK signaling pathway and NF-κB signaling pathway. The animal experiments indicated that topical application of CF showed significant anti-inflammatory activity in a mouse model of xylene-induced ear edema and had strong analgesic effect on acetic acid-induced writhing. Furthermore, in the rat model of adjuvant arthritis (AA), topical administration of CF was able to alleviate toe swelling and ameliorate joint damage. The elevated serum content levels of IL-6, COX-2, TNF-α, IL-1β, and RF caused by adjuvant arthritis were reduced by CF treatment. Western blotting tests showed that CF may regulate the ERK and NF-κB pathway. The results provide a new perspective for the topical application of CF for treatment of RA.

As an important way to realize the circular economy, remanufacturing faces the problem of low consumer recognition of remanufactured products. Given that factor, this study formulates a model that integrates offline direct sales with online distribution led by remanufacturers, assuming that consumers perceive differences between channels. We develop a Stackelberg game model to represent cases of remanufactured channel promotion and generic promotion and analyze the optimization of pricing and the level of promotion effort decisions for remanufactured products. Furthermore, considering the market conditions, such as the difference coefficient of consumer channel perception and the spillover effect in generic promotion, we investigate the selection of the optimal promotion strategy for remanufacturers. The research findings reveal the following: (i) Under channel promotion, the level of promotion effort and the prices of online and offline products are positively correlated with the difference coefficient of consumer value perception. Conversely, under generic promotion, the level of promotion effort and the prices of online and offline products initially decrease and then increase with the difference coefficient of consumer value perception. (ii) Under the generic promotion, the differences in prices between online and offline products are significantly smaller compared to channel promotion. (iii) The remanufacturer’s profit from channel promotion is higher when the difference in consumer channel perception is either small or large. Conversely, when the difference in consumer channel perception is moderate, the optimal strategy for remanufacturers is generic promotion, thereby achieving a mutually beneficial outcome with retailers. This study provides a theoretical foundation for remanufacturers to formulate effective pricing and promotion strategies in dual-channel marketing, thereby enhancing the market recognition and sales of remanufactured products.

Land surface temperature (LST) is a fundamental parameter in global climate, environmental, and geophysical studies. Remote sensing is an essential approach for obtaining large-scale and frequently updated LST data. However, due to the wide field of view of remote sensing sensors, the observed LST with diverse view geometries suffers from inconsistency caused by the thermal radiation directionality (TRD) effect, which results in LST products being incomparable, especially during daytime. To address this issue and correct current off-nadir LSTs to nadir LSTs, a semi-physical time-evolved kernel-driven model (TEKDM) is proposed, which depicts multitemporal TRD patterns during the daytime. In addition, we employ a Bayesian optimization method to calibrate seven unknown parameters in the TEKDM. Validation results using the U.S. Climate Reference Network (USCRN) sites show that the RMSE (MBE) for GOES-16 and MODIS off-nadir LST products is reduced from 3.29 K (−2.0 K) to 2.34 K (−0.02 K), with an RMSE reduction of 0.95 K (29%) and a significant reduction in systematic bias. Moreover, the proposed method successfully eliminates the angular and temporal dependence of the LST difference between the satellite off-nadir LST and in situ nadir LST. In summary, this study presents a feasible approach for estimating the high-accuracy nadir LST, which can enhance the applicability of LST products in various domains.

Surface upward longwave radiation (SULR) is one of the four components of surface net radiation. Geostationary satellites can provide high temporal but coarse spatial resolution SULR products. Downscaling coarse SULR to a higher resolution is important for fine-scale thermal condition monitoring. Statistical regression downscaling is widely used due to its simplicity and is built on the assumption that the thermal parameter like land surface temperature (LST) or SULR has a relationship with the related surface factors like the normalized difference vegetation index (NDVI), and the relationship remains unchanged in any scales. In this study, to establish the relationship between SULR and the related surface factors, we chose the multiple linear regression (MLR) model and five surface factors (i.e., the modified normalized difference water index (MNDWI), normalized difference built-up and soil index (NDBSI), NDVI, normalized moisture difference index (NMDI), and urban index (UI)) to drive the downscaling process. Additionally, a step-by-step downscaling strategy was applied to reach the 100-fold increase in spatial resolution, transitioning the estimated SULR from 4 km of the advanced geostationary radiation imager (AGRI) onboard FengYun-4B (FY-4B) satellite to 40 m of the visual and infrared multispectral imager (VIMI) in infrared spectrum onboard GaoFen5-02 (GF5-02). Finally, we evaluated the downscaling results by comparing the downscaled SULR values with the in situ measured SULR and GF5-02-calculated SULR, and the root mean square errors (RMSEs) were 19.70 W/m2 and 24.86 W/m2, respectively. Throughout this MLR-based step-by-step downscaling method (high-frequency data from FY-4B and high spatial resolution data from GF5-02), high spatiotemporal SULR (15 min temporal resolution, 40 m spatial resolution) were successfully generated instead of coarse spatial resolution ones from the FY-4B satellite or a coarse temporal resolution one from the GF5-02 satellite, relieving the above-mentioned conflict to some extent.

Rapeseed has the ability to absorb cadmium in the roots and transfer it to aboveground organs, making it a potential species for remediating soil cadmium (Cd) pollution. However, the genetic and molecular mechanisms underlying this phenomenon in rapeseed are still unclear. In this study, a ‘cadmium-enriched’ parent, ‘P1’, with high cadmium transport and accumulation in the shoot (cadmium root: shoot transfer ratio of 153.75%), and a low-cadmium-accumulation parent, ‘P2’, (with a cadmium transfer ratio of 48.72%) were assessed for Cd concentration using inductively coupled plasma mass spectrometry (ICP-MS). An F2 genetic population was constructed by crossing ‘P1’ with ‘P2’ to map QTL intervals and underlying genes associated with cadmium enrichment. Fifty extremely cadmium-enriched F2 individuals and fifty extremely low-accumulation F2 individuals were selected based on cadmium content and cadmium transfer ratio and used for bulk segregant analysis (BSA) in combination with whole genome resequencing. This generated a total of 3,660,999 SNPs and 787,034 InDels between these two segregated phenotypic groups. Based on the delta SNP index (the difference in SNP frequency between the two bulked pools), nine candidate Quantitative trait loci (QTLs) from five chromosomes were identified, and four intervals were validated. RNA sequencing of ‘P1’ and ‘P2’ in response to cadmium was also performed and identified 3502 differentially expressed genes (DEGs) between ‘P1’ and ‘P2’ under Cd treatment. Finally, 32 candidate DEGs were identified within 9 significant mapping intervals, including genes encoding a glutathione S-transferase (GST), a molecular chaperone (DnaJ), and a phosphoglycerate kinase (PGK), among others. These genes are strong candidates for playing an active role in helping rapeseed cope with cadmium stress. Therefore, this study not only sheds new light on the molecular mechanisms of Cd accumulation in rapeseed but could also be useful for rapeseed breeding programs targeting this trait.

Effectors are crucial for the interaction between endophytes and their host plants. However, limited attention has been paid to endophyte effectors, with only a few reports published. This work focuses on an effector of Fusarium lateritium, namely FlSp1 (Fusarium-lateritium-Secreted-Protein), a typical unknown secreted protein. The transcription of FlSp1 was up-regulated after 48 h following fungal inoculation in the host plant, i.e., tobacco. The inactivation of FlSp1 with the inhibition rate decreasing by 18% (p < 0.01) resulted in a remarkable increase in the tolerance of F. lateritium to oxidative stress. The transient expression of FlSp1 stimulated the accumulation of reactive oxygen species (ROS) without causing plant necrosis. In comparison with the wild type of F. lateritium (WT), the FlSp1 mutant of the F. lateritium plant (ΔFlSp1) reduced the ROS accumulation and weakened the plant immune response, which resulted in significantly higher colonization in the host plants. Meanwhile, the resistance of the ΔFlSp1 plant to the pathogenic Ralstonia solanacearum, which causes bacterial wilt, was increased. These results suggest that the novel secreted protein FlSp1 might act as an immune-triggering effector to limit fungal proliferation by stimulating the plant immune system through ROS accumulation and thus balance the interaction between the endophytic fungi and their host plants.

A model different from the traditional WEC, known as the flexible wave energy converter (fWEC), is numerically modeled in this paper. The fWEC is believed to be more efficient and has a greater range of operation when compared with the conventionally rigid WEC. A fully coupled fluid–structure interaction (FSI) tool is developed for the research performed in this paper. This tool is able to accommodate the dynamic interaction between the flexible membrane structure of the fWEC and the surrounding fluid. In this research, both linear-elastic and hyper-elastic materials are examined for their use in the fWEC. The fluid flow surrounding the fWEC is solved by a computational fluid dynamics (CFD) method. The deformation of the hyper-elastic structure within the fWEC is modeled using a finite element analysis method (FEA). Both the hyper-elastic material of the fWEC and the free surface wave contribute to the overall nonlinearity of the numerical simulation. To tackle this problem, a robust coupling scheme is implemented by an advanced coupling library. With this tool, the flexible deformations within the fWEC structure can be accurately captured. The degree of these deformations can then further be examined, allowing the overall effects on the fWEC energy output to be determined. The simulation results show that the peak deformation of the hyper-elastic material is four times that of the linear-elastic material. This suggests that the fWEC would perform better and generate greater power using the hyper-elastic material compared with the linear-elastic material. Additionally, because a wide range of wave conditions are studied, it can be concluded that unlike conventional WECs, the efficiency of energy harvesting of such an fWEC is not sensitive to certain wave periods. Such findings are supported by both the detailed flow fields captured and the structural stress–strain analysis results from this simulation.

The surface oxidation of chalcopyrite is one of the most important factors affecting its flotation performance. In this study, a critical oxidation degree is proposed to define “slight” and “significant” oxidation in terms of surface species and chalcopyrite flotation recovery. Slight oxidation enhanced chalcopyrite hydrophobicity, but significant oxidation reduced its recovery apparently. Microthermokinetic measurements indicated that the apparent activation energy (Ea) of chalcopyrite oxidation was reduced from around 173 kJ·mol−1 to 163 kJ·mol−1 when the reaction changed from slight oxidation to significant oxidation when applying H2O2. The surface oxidation degree was defined as the ratio of hydrophilic species to hydrophobic species. The highest recovery (94.8%) and contact angle (93°) were achieved at a concentration of 0.1 vol.% H2O2, with the lowest oxidation degree of 0.388 being observed. The oxidation degree was correlated to the flotation recovery, with a quantitative relationship (y = −298.81x + 213.05, y and x represent flotation recovery and oxidation degree, respectively, 0.388 ≤ x ≤ 0.618) being established, thereby giving a guideline to better manage chalcopyrite flotation by controlling its surface oxidation and SBX adsorption on chalcopyrite surfaces.

Land surface temperature (LST) is a vital parameter in the surface energy budget and water cycle. One of the most important foundations for LST studies is a theory to understand how to model LST with various influencing factors, such as canopy structure, solar radiation, and atmospheric conditions. Both physical-based and empirical methods have been widely applied. However, few studies have compared these two categories of methods. In this paper, a physical-based method, soil canopy observation of photochemistry and energy fluxes (SCOPE), and two empirical methods, random forest (RF) and long short-term memory (LSTM), were selected as representatives for comparison. Based on a series of measurements from meteorological stations in the Heihe River Basin, these methods were evaluated in different dimensions, i.e., the difference within the same surface type, between different years, and between different climate types. The comparison results indicate a relatively stable performance of SCOPE with a root mean square error (RMSE) of approximately 2.0 K regardless of surface types and years but requires many inputs and a high computational cost. The empirical methods performed relatively well in dealing with cases either within the same surface type or changes in temporal scales individually, with an RMSE of approximately 1.50 K, yet became less compatible in regard to different climate types. Although the overall accuracy is not as stable as that of the physical method, it has the advantages of fast calculation speed and little consideration of the internal structure of the model.

Anisotropic canopy reflectance plays a crucial role in estimating vegetation biophysical parameters, whereas soil reflectance anisotropy affects canopy reflectance. However, woodland canopy bidirectional reflectance distribution function (BRDF) models considering soil anisotropy are far from universal, especially for the BRDF models of mountain forest. In this study, a mountain forest canopy model, named geometric-optical and mutual shadowing and scattering from arbitrarily inclined-leaves model coupled with topography (GOSAILT), was extended to consider the soil anisotropic reflectance characteristics by introducing the simple soil directional (SSD) reflectance model. The modified GOSAILT model (named GOSAILT-SSD) was evaluated using unmanned aerial vehicle (UAV) field observations and discrete anisotropic radiative transfer (DART) simulations. Then, the effects of Lambertian soil assumption on simulating the vi-directional reflectance factor (BRF) were evaluated across different fractions of vegetation cover (Cv), view zenith angles (VZA), solar zenith angles (SZA), and spectral bands with the GOSAILT-SSD model. The evaluation results, with the DART simulations, show that the performance of the GOSAILT-SSD model in simulating canopy BRF is significantly improved, with decreasing RMSE, from 0.027 to 0.017 for the red band and 0.051 to 0.037 for the near-infrared (NIR) band. Meanwhile, the GOSAILT-SSD simulations show high consistency with UAV multi-angular observations (R2 = 0.97). Besides, it is also found that the BRF simulation errors caused by Lambertian soil assumption are too large to be neglected, with a maximum relative bias of about 45% for the red band. This inappropriate assumption results in a remarkable BRF underestimation near the hot spot direction and an obvious BRF overestimation for large VZA in the solar principal plane (PP). Meanwhile, this simulation bias decreases with the increase of fraction of vegetation cover. This study provides an effective technique to improve the capability of the mountain forest canopy BRDF model by considering the soil anisotropic characteristics for advancing the modeling of radiative transfer (RT) processes over rugged terrain.

Currently, the design of floating offshore wind systems is primarily based on mid-fidelity models with empirical drag forces. The tuning of the model coefficients requires data from either experiments or high-fidelity simulations. As part of the OC6 (Offshore Code Comparison Collaboration, Continued, with Correlation, and unCertainty (OC6) is a project under the International Energy Agency Wind Task 30 framework) project, the present investigation explores the latter option. A verification and validation study of computational fluid dynamics (CFD) models of the DeepCwind semisubmersible undergoing free-decay motion is performed. Several institutions provided CFD results for validation against the OC6 experimental campaign. The objective is to evaluate whether the CFD setups of the participants can provide valid estimates of the hydrodynamic damping coefficients needed by mid-fidelity models. The linear and quadratic damping coefficients and the equivalent damping ratio are chosen as metrics for validation. Large numerical uncertainties are estimated for the linear and quadratic damping coefficients; however, the equivalent damping ratios are more consistently predicted with lower uncertainty. Some difference is observed between the experimental and CFD surge-decay motion, which is caused by mechanical damping not considered in the simulations that likely originated from the mooring setup, including a Coulomb-friction-type force. Overall, the simulations and the experiment show reasonable agreement, thus demonstrating the feasibility of using CFD simulations to tune mid-fidelity models.

Temperature-sensitive male sterility is a heritable agronomic trait affected by genotype-environment interactions. In rapeseed (Brassica napus), Polima (pol) temperature-sensitive cytoplasmic male sterility (TCMS) is commonly used for two-line breeding, as the fertility of pol TCMS lines can be partially restored at certain temperatures. However, little is known about the underlying molecular mechanism that controls fertility restoration. Therefore, we aimed to investigate the fertility conversion mechanism of the pol TCMS line at two different ambient temperatures (16 °C and 25 °C). Our results showed that the anthers developed and produced vigorous pollen at 16 °C but not at 25 °C. In addition, we identified a novel co-transcript of orf224-atp6 in the mitochondria that might lead to fertility conversion of the pol TCMS line. RNA-seq analysis showed that 1637 genes were significantly differentially expressed in the fertile flowers of 596-L when compared to the sterile flower of 1318 and 596-H. Detailed analysis revealed that differentially expressed genes were involved in temperature response, ROS accumulation, anther development, and mitochondrial function. Single-molecule long-read isoform sequencing combined with RNA sequencing revealed numerous genes produce alternative splicing transcripts at high temperatures. Here, we also found that alternative oxidase, type II NAD(P)H dehydrogenases, and transcription factor Hsfs might play a crucial role in male fertility under the low-temperature condition. RNA sequencing and bulked segregant analysis coupled with whole-genome sequencing identified the candidate genes involved in the post-transcriptional modification of orf224. Overall, our study described a putative mechanism of fertility restoration in a pol TCMS line controlled by ambient temperature that might help utilise TCMS in the two-line breeding of Brassica crops.

The study evaluated the combined effect of high-pressure processing (HPP) and spice extracts on low-salt sausages during refrigerated storage. Physicochemical and microbiological characteristics of the sausages were determined. HPP treatment increased the thiobarbituric acid reactive substances (TBARS) value and the carbonyl content of the samples (p < 0.05), which meant lipid and protein oxidation was accelerated. Adding clove and cinnamon extracts can retard the oxidation caused by HPP (p < 0.05). The pH of the sausages treated with both the spice extracts and HPP maintained a higher pH value during the storage (p > 0.05). Compared with the samples treated with HPP or with the spice extracts alone, the combined treatment observably inhibited the growth of spoilage bacteria (p < 0.05) and improved the microbial community. The results demonstrated that the use of clove and cinnamon extracts in conjunction with HPP improved the storage quality and prolonged the shelf-life of the low-salt sausages. Thus, the combined use of spice extracts and HPP can be developed as a promising way to preserve low-salt meat products.

To reduce human risk and maintenance costs, Autonomous Underwater Vehicles (AUVs) are involved in subsea inspections and measurements for a wide range of marine industries such as offshore wind farms and other underwater infrastructure. Most of these inspections may require levels of manoeuvrability similar to what can be achieved by tethered vehicles, called Remotely Operated Vehicles (ROVs). To extend AUV intervention time and perform closer inspection in constrained spaces, AUVs need to be more efficient and flexible by being able to undulate around physical constraints. A biomimetic fish-like AUV known as RoboFish has been designed to mimic propulsion techniques observed in nature to provide high thrust efficiency and agility to navigate its way autonomously around complex underwater structures. Building upon advances in acoustic communications, computer vision, electronics and autonomy technologies, RoboFish aims to provide a solution to such critical inspections. This paper introduces the first RoboFish prototype that comprises cost-effective 3D printed modules joined together with innovative magnetic coupling joints and a modular software framework. Initial testing shows that the preliminary working prototype is functional in terms of water-tightness, propulsion, body control and communication using acoustics, with visual localisation and mapping capability.

A multi-body system model is proposed for the mimicking of swimming fish with coupled active and passive movements. The relevant algorithms of the kinematics and dynamics of the multi-body system and coupled fluid solver are developed and fully validated. A simplified three-body model is applied for the investigation of the hydrodynamic performance of both an active pitch motion and passive movement. In general, there is an optimal stiffness, under which the model swims with the fastest velocity. The effect of the damper can be drawn only when the stiffness is small. Comparing with the rigid tail, the flexible tail leads to a faster speed when the stiffness and damping coefficients are in a suitable range.

Introducing a duct along the perimeter of a rotor has been acknowledged to augment turbine performance. The outcome causation due to a bi-directional, cylindrical shroud, however, is uncertain. This study analyses the hydrodynamic swallowing capacity of a true-scale, vacant duct for tidal turbine applications in aligned and yawed inlet flow conditions by utilising three-dimensional unsteady computational fluid dynamics. The performance is investigated within free-stream magnitudes of 1 to 7 m.s−1, and a bearing angular range of 0° to 45° with the duct axis. In proportion to the free-stream magnitude, the normalised axial velocity through the duct increases as a result of a diminishment in pressure drag. Within yawed flow, the maximum capacity falls at a bearing of 23.2°, resulting in a performance increase of 4.13% above that at aligned flow conditions. The analysis concludes that the augmentation at yawed flow occurs due to the duct cross-sectional profile lift variation with angle-of-attack. Towards nominal yaw angle, the internal static pressure reduces, permitting a higher mass-flow rate. Beyond the nominal angle-of-attack, flow separation occurs within the duct, increasing pressure drag, thereby reducing the swallowing capacity.

In order to improve the simulation accuracy of directional brightness temperature (DBT) and the retrieval accuracy of component temperature, a model considering intra-row heterogeneity to simulate the DBT angular distribution over crop canopy is proposed. At individual scale, the probability of leaf appearance is inversely proportional to the distance from central stem. On the basis of this assumption, we formulated leaf area volume density (LAVD) spatial distribution at three hierarchical scales: individual scale, row scale, and scene scale. The equations for directional gap probability and bi-directional gap probability were modified to adapt the heterogeneity of row structure. Afterwards, a straightforward radiative transfer model was built based on the gap probabilities. A set of simulated data was generated by the thermal radiosity-graphics combined model (TRGM) as the benchmark to evaluate both forward simulation and inversion ability of the new model; we compared the new DBT model against an existing model assuming row as homogeneous box. With the growth of crops, the canopy structure of row crops will gradually change from row structure to continuous canopy. The new DBT model agreed with the TRGM model much better than the homogeneous row model at the middle stage of the crop growth season. The new model and the homogeneous row model achieve similar accuracy at early stage and end stage. At the middle growth stage, the new model can improve the accuracy of soil temperature retrieval. We recommend the new DBT model as an option to improve the DBT simulation and component temperature retrieval for row-planted crop canopy. In particular, the more accurate component temperatures during the middle growth stage are fundamentally important in characterizing crop water status, evapotranspiration, and soil moisture, which are subsequently critical for predicting crop productivity.

Surface upward longwave radiation (SULR) is a critical component in the calculation of the Earth’s surface radiation budget. Multiple clear-sky SULR estimation methods have been developed for high-spatial resolution satellite observations. Here, we comprehensively evaluated six SULR estimation methods, including the temperature-emissivity physical methods with the input of the MYD11/MYD21 (TE-MYD11/TE-MYD21), the hybrid methods with top-of-atmosphere (TOA) linear/nonlinear/artificial neural network regressions (TOA-LIN/TOA-NLIN/TOA-ANN), and the hybrid method with bottom-of-atmosphere (BOA) linear regression (BOA-LIN). The recently released MYD21 product and the BOA-LIN—a newly developed method that considers the spatial heterogeneity of the atmosphere—is used initially to estimate SULR. In addition, the four hybrid methods were compared with simulated datasets. All the six methods were evaluated using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Surface Radiation Budget Network (SURFRAD) in situ measurements. Simulation analysis shows that the BOA-LIN is the best one among four hybrid methods with accurate atmospheric profiles as input. Comparison of all the six methods shows that the TE-MYD21 performed the best, with a root mean square error (RMSE) and mean bias error (MBE) of 14.0 and −0.2 W/m2, respectively. The RMSE of BOA-LIN, TOA-NLIN, TOA-LIN, TOA-ANN, and TE-MYD11 are equal to 15.2, 16.1, 17.2, 21.2, and 18.5 W/m2, respectively. TE-MYD21 has a much better accuracy than the TE-MYD11 over barren surfaces (NDVI < 0.3) and a similar accuracy over non-barren surfaces (NDVI ≥ 0.3). BOA-LIN is more stable over varying water vapor conditions, compared to other hybrid methods. We conclude that this study provides a valuable reference for choosing the suitable estimation method in the SULR product generation.

As an essential climate variable (ECV), land surface albedo plays an important role in the Earth surface radiation budget and regional or global climate change. The Tibetan Plateau (TP) is a sensitive environment to climate change, and understanding its albedo seasonal and inter-annual variations is thus important to help capture the climate change rules. In this paper, we analyzed the large-scale spatial patterns, temporal trends, and seasonal variability of land surface albedo overall the TP, based on the moderate resolution imaging spectroradiometer (MODIS) MCD43 albedo products from 2001 to 2019. Specifically, we assessed the correlations between the albedo anomaly and the anomalies of normalized difference vegetation index (NDVI), the fraction of snow cover (snow cover), and land surface temperature (LST). The results show that there are larger albedo variations distributed in the mountainous terrain of the TP. Approximately 10.06% of the land surface is identified to have been influenced by the significant albedo variation from the year 2001 to 2019. The yearly averaged albedo was decreased significantly at a rate of 0.0007 (Sen’s slope) over the TP. Additionally, the yearly average snow cover was decreased at a rate of 0.0756. However, the yearly average NDVI and LST were increased with slopes of 0.0004 and 0.0253 over the TP, respectively. The relative radiative forcing (RRF) caused by the land cover change (LCC) is larger than that caused by gradual albedo variation in steady land cover types. Overall, the RRF due to gradual albedo variation varied from 0.0005 to 0.0170 W/m2, and the RRF due to LCC variation varied from 0.0037 to 0.0243 W/m2 during the years 2001 to 2019. The positive RRF caused by gradual albedo variation or the LCC can strengthen the warming effects in the TP. The impact of the gradual albedo variations occurring in the steady land cover types was very low between 2001 and 2019 because the time series was short, and it therefore cannot be neglected when examining radiative forcing for a long time series regarding climate change.

Thirty-six volatile compounds, composed of 18 esters, 10 terpenes, and 8 others, were detected by headspace-solid phase microextraction (HS-SPME) equipped with gas chromatography-mass spectrometry (GC-MS) in mango and vodka cocktail. Moreover, these compounds were detected by olfactometry using aroma intensities. Comparing these compounds revealed that the aroma intensities (AIs) of limonene, 3-carene, myrcene, β-caryophyllene, and citronellyl propanoate were higher than others (AIs ≥ 4). In this context, limonene was selected as the reference compound on the basis of the strongest component model. The aim of this study was to determine the perceptual interaction between limonene and 3-carene, myrcene, β-caryophyllene, citronellyl propanoate, respectively, in a binary mixture. In addition, feller’s addition model revealed that limonene presented an addition effect when combined with 3-carene, myrcene, β-caryophyllene, and citronellyl propanoate. It could be stated that these compounds played an important role in the aroma of mango and vodka cocktail. The results demonstrated that molecular structure and the ratio between compounds affected the synergistic effect, and compounds with similar structure and aroma were more prone to undergo addition and synergy.

To evaluate and improve the quality of land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. One of the essential steps for satellite albedo product validation is coarse scale observation technique development with long time ground-based measurements. In this paper, the optimal nodes were selected from the wireless sensor network (WSN) to perform observation at large scale and in longer time series for validation of albedo products. The relative difference is used to analyze the spatiotemporal representativeness of each node. The random combination method is used to assess the number of required sites (NRS) and then to identify the most representative combination (MRC). On this basis, an upscaling transform function with different weights for each node in the MRC, which are calculated with the ordinary least squares (OLS) linear regression method, is used to upscale WSN node albedo from point scale to the field scale. This method is illustrated by selecting the optimal nodes and upscaling surface albedo from point observation to the field scale in the Heihe River basin, China. Primary findings are: (a) The method of reducing the number of observations without significant loss of information about surface albedo at field scale is feasible and effective; (b) When only few sensors are available, the most representative locations in time and space should be the first priority; when a number of sensors are available in the heterogeneous land surface, it is preferable to install them in different land surface, rather than the most representative locations; (c) The most representative combination (MRC) combined with the upscaling weight coefficients can give a robust estimate of the field mean surface albedo. These efforts based on ground albedo observations promote the chance to use point information for validation of coarse scale albedo products. Moreover, a preliminary validation of the MODIS (Moderate Resolution Imaging Spectroradiometer) albedo product was performed as the tentative application for upscaling predictions.

High spatial resolution soil moisture (SM) data are crucial in agricultural applications, river-basin management, and understanding hydrological processes. Merging multi-resource observations is one of the ways to improve the accuracy of high spatial resolution SM data in the heterogeneous cropland. In this paper, the Bayesian Maximum Entropy (BME) methodology is implemented to merge the following four types of observed data to obtain the spatial distribution of SM at 100 m scale: soil moisture observed by wireless sensor network (WSN), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)-derived soil evaporative efficiency (SEE), irrigation statistics, and Polarimetric L-band Multi-beam Radiometer (PLMR)-derived SM products (~700 m). From the poor BME predictions obtained by merging only WSN and SEE data, we observed that the SM heterogeneity caused by irrigation and the attenuating sensitivity of the SEE data to SM caused by the canopies result in BME prediction errors. By adding irrigation statistics to the merged datasets, the overall RMSD of the BME predictions during the low-vegetated periods can be successively reduced from 0.052 m3·m−3 to 0.033 m3·m−3. The coefficient of determination (R2) and slope between the predicted and in situ measured SM data increased from 0.32 to 0.64 and from 0.38 to 0.82, respectively, but large estimation errors occurred during the moderately vegetated periods (RMSD = 0.041 m3·m−3, R = 0.43 and the slope = 0.41). Further adding the downscaled SM information from PLMR SM products to the merged datasets, the predictions were satisfactorily accurate with an RMSD of 0.034 m3·m−3, R2 of 0.4 and a slope of 0.69 during moderately vegetated periods. Overall, the results demonstrated that merging multi-resource observations into SM estimations can yield improved accuracy in heterogeneous cropland.

A land-cover-based linear BRDF (bi-directional reflectance distribution function) unmixing (LLBU) algorithm based on the kernel-driven model is proposed to combine the compact airborne spectrographic imager (CASI) reflectance with the moderate resolution imaging spectroradiometer (MODIS) daily reflectance product to derive the BRDF/albedo of the two sensors simultaneously in the foci experimental area (FEA) of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER), which was carried out in the Heihe River basin, China. For each land cover type, an archetypal BRDF, which characterizes the shape of its anisotropic reflectance, is extracted by linearly unmixing from the MODIS reflectance with the assistance of a high-resolution classification map. The isotropic coefficients accounting for the differences within a class are derived from the CASI reflectance. The BRDF is finally determined by the archetypal BRDF and the corresponding isotropic coefficients. Direct comparisons of the cropland archetypal BRDF and CASI albedo with in situ measurements show good agreement. An indirect validation which compares retrieved BRDF/albedo with that of the MCD43A1 standard product issued by NASA and aggregated CASI albedo also suggests reasonable reliability. LLBU has potential to retrieve the high spatial resolution BRDF/albedo product for airborne and spaceborne sensors which have inadequate angular samplings. In addition, it can shorten the timescale for coarse spatial resolution product like MODIS.

Validation is an essential and important step before the application of remote sensing products. This paper introduces a prototype of the validation network for remote sensing products in China (VRPC). The VRPC aims to improve remote sensing products at a regional scale in China. These improvements will enhance the applicability of the key remote sensing products in understanding and interpretation of typical land surface processes in China. The framework of the VRPC is introduced first, including its four basic components. Then, the basic selection principles of the observation sites are described, and the principles for the validation of the remote sensing products are established. The VRPC will be realized in stages. In the first stage, four stations that have improved remote sensing observation facilities have been incorporated according to the selection principles. Certain core observation sites have been constructed at these stations. Next the Heihe Station is introduced in detail as an example. The three levels of observation (the research base, pixel-scale validation sites, and regional coverage) adopted by the Heihe Station are carefully explained. The pixel-scale validation sites with nested multi-scale observation systems in this station are the most unique feature, and these sites aim to solve some key scientific problems associated with remote sensing product validation (e.g., the scale effect and scale transformation). Multi-year of in situ measurements will ensure the high accuracy and inter-annual validity of the land products, which will provide dynamic regional monitoring and simulation capabilities in China. The observation sites of the VRPC are open, with the goal of increasing cooperation and exchange with global programs.

High spatial resolution airborne data with little sub-pixel heterogeneity were used to evaluate the suitability of the temperature/vegetation (Ts/VI) space method developed from satellite observations, and were explored to improve the performance of the Ts/VI space method for estimating soil moisture (SM). An evaluation of the airborne ΔTs/Fr space (incorporated with air temperature) revealed that normalized difference vegetation index (NDVI) saturation and disturbed pixels were hindering the appropriate construction of the space. The non-disturbed ΔTs/Fr space, which was modified by adjusting the NDVI saturation and eliminating the disturbed pixels, was clearly correlated with the measured SM. The SM estimations of the non-disturbed ΔTs/Fr space using the evaporative fraction (EF) and temperature vegetation dryness index (TVDI) were validated by using the SM measured at a depth of 4 cm, which was determined according to the land surface types. The validation results show that the EF approach provides superior estimates with a lower RMSE (0.023 m3·m−3) value and a higher correlation coefficient (0.68) than the TVDI. The application of the airborne ΔTs/Fr space shows that the two modifications proposed in this study strengthen the link between the ΔTs/Fr space and SM, which is important for improving the precision of the remote sensing Ts/VI space method for monitoring SM.

This paper presents a study of FeNi-based thin film materials deposited with Mo, Al and B using a co-sputtering process. The existence of soft magnetic properties in combination with strong magneto-mechanical coupling makes these materials attractive for sensor applications. Our findings show that FeNi deposited with Mo or Al yields magnetically soft materials and that depositing with B further increases the softness. The out-of-plane magnetic anisotropy of FeNi thin films is reduced by depositing with Al and completely removed by depositing with B. The effect of depositing with Mo is dependent on the Mo concentration. The coercivity of FeNiMo and FeNiAl is reduced to less than a half of that of FeNi, and a value as low as 40 A/m is obtained for FeNiB. The surfaces of the obtained FeNiMo, FeNiAl and FeNiB thin films reveal very different morphologies. The surface of FeNiMo shows nano-cracks, while the FeNiAl films show large clusters and fewer nano-cracks. When FeNi is deposited with B, a very smooth morphology is obtained. The crystal structure of FeNiMo strongly depends on the depositant concentration and changes into an amorphous structure at a higher Mo level. FeNiAl thin films remain polycrystalline, even at a very high concentration of Al, and FeNiB films are amorphous, even at a very low concentration of B.

In this paper, we present numerical modelling for the investigation of dynamic responses of a floating offshore wind turbine subject to focused waves. The modelling was carried out using a Computational Fluid Dynamics (CFD) tool. We started with the generation of a focused wave in a numerical wave tank based on a first-order irregular wave theory, then validated the developed numerical method for wave-structure interaction via a study of floating production storage and offloading (FPSO) to focused wave. Subsequently, we investigated the wave-/wind-structure interaction of a fixed semi-submersible platform, a floating semi-submersible platform and a parked National Renewable Energy Laboratory (NREL) 5 MW floating offshore wind turbine. To understand the nonlinear effect, which usually occurs under severe sea states, we carried out a systematic study of the motion responses, hydrodynamic and mooring tension loads of floating offshore wind turbine (FOWT) over a range of wave steepness, and compared the results obtained from two potential flow theory tools with each other, i.e., Électricité de France (EDF) in-house code and NREL Fatigue, Aerodynamics, Structures, and Turbulence (FAST). We found that the nonlinearity of the hydrodynamic loading and motion responses increase with wave steepness, revealed by higher-order frequency response, leading to the appearance of discrepancies among different tools.

A novel decoupled XY compliant micro-positioning stage, based on a bridge-type amplification mechanism and parallelogram mechanisms, is designed in this paper. Analytical models of the bridge-type amplification mechanism and parallelogram mechanisms are developed by Castigliano’s second theorem and a Beam constrained model. The amplification ratio, input stiffness, and output stiffness of the stage are further derived, based on the proposed model. In order to verify the theoretical analysis, the finite element method (FEM) is used for simulation and modal analysis, and the simulation results indicate that the errors of the amplification ratio, input stiffness, and output stiffness of the stage between the proposed model and the FEM results are 2.34%, 3.87%, and 2.66%, respectively. Modal analysis results show that the fundamental natural frequency is 44 Hz, and the maximum error between the theoretical model and the FEM is less than 4%, which further validates the proposed modeling method. Finally, the prototype is fabricated to test the amplification ratio, cross-coupling error, and workspace. The experimental results demonstrate that the stage has a relatively large workspace, of 346.1 μm × 357.2 μm, with corresponding amplification ratios of 5.39 in the X-axis and 5.51 in the Y-axis, while the cross-coupling error is less than 1.5%.

Hydro-agricultural applications often require surface soil moisture (SM) information at high spatial resolutions. In this study, daily spatial patterns of SM at a spatial resolution of 1 km over the Babao River Basin in northwestern China were mapped using a Bayesian-based upscaling algorithm, which upscaled point-scale measurements to the grid-scale (1 km) by retrieving SM information using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived land surface temperature (LST) and topography data (including aspect and elevation data) and in situ measurements from a wireless sensor network (WSN). First, the time series of pixel-scale (1 km) representative SM information was retrieved from in situ measurements of SM, topography data, and LST. Second, Bayesian linear regression was used to calibrate the relationship between the representative SM and the WSN measurements. Last, the calibrated relationship was used to upscale a network of in situ measured SM to map spatially continuous SM at a high resolution. The upscaled SM data were evaluated against ground-based SM measurements with satisfactory accuracy—the overall correlation coefficient (r), slope, and unbiased root mean square difference (ubRMSD) values were 0.82, 0.61, and 0.025 m3/m3, respectively. Moreover, when accounting for topography, the proposed upscaling algorithm outperformed the algorithm based only on SM derived from LST (r = 0.80, slope = 0.31, and ubRMSD = 0.033 m3/m3). Notably, the proposed upscaling algorithm was able to capture the dynamics of SM under extreme dry and wet conditions. In conclusion, the proposed upscaled method can provide accurate high-resolution SM estimates for hydro-agricultural applications.

This study assessed accuracies of MCD43A3, Global Land-Surface Satellite (GLASS) and forthcoming Multi-source Data Synergized Quantitative Remote Sensing Production system (MuSyQ) albedos using ground observations and Huan Jing (HJ) data over the Heihe River Basin. MCD43A3 and MuSyQ albedos show similar high accuracies with identical root mean square errors (RMSE). Nevertheless, MuSyQ albedo is better correlated with ground measurements when sufficient valid observations are available or snow-free. The opposite happens when less than seven valid observations are available. GLASS albedo presents a larger RMSE than MCD43A3 and MuSyQ albedos in comparison with ground measurements. Over surfaces with smaller seasonal variations, MCD43A3 and MuSyQ albedos show smaller RMSEs than GLASS albedo in comparison with HJ albedo. However, for surfaces with larger temporal variations, both RMSEs and R2 of GLASS albedo are comparable with MCD43A3 and MuSyQ. Generally, MCD43A3 and MuSyQ albedos featured the same RMSEs of 0.034 and similar R2 (0.920 and 0.903, respectively), which are better than GLASS albedo (RMSE = 0.043, R2 = 0.787). However, when it comes to comparison with aggregated HJ albedo, MuSyQ and GLASS albedos are with lower RMSEs of 0.027 and 0.032 and higher R2 of 0.900 and 0.898 respectively than MCD43A3 (RMSE = 0.038, R2 = 0.836). Despite the limited geographic region of the study area, they still provide an important insight into the accuracies of three albedo products.

The academician Xiaowen Li devoted much of his life to pursuing fundamental research in remote sensing. A pioneer in the geometric-optical modeling of vegetation canopies, his work is held in high regard by the international remote sensing community. He codeveloped the Li⁻Strahler geometric-optic model, and this paper was selected by a member of the International Society for Optical Engineering (SPIE) milestone series. As a chief scientist, Xiaowen Li led a scientific team that made outstanding advances in bidirectional reflectance distribution modeling, directional thermal emission modeling, comprehensive experiments, and the understanding of spatial and temporal scale effects in remote sensing information, and of quantitative inversions utilizing remote sensing data. In addition to his broad research activities, he was noted for his humility and his dedication in making science more accessible for the general public. Here, the life and academic contributions of Xiaowen Li to the field of quantitative remote sensing science are briefly reviewed.

Seawater has been considered as an alternative to freshwater for flotation. However, many ions in seawater were reported to depress molybdenite (MoS2), with the depressing mechanisms being insufficiently understood. In this study, the influence of divalent ions (e.g., Ca2+ and Mg2+) and dispersant on MoS2 flotation was systematically investigated. It was found that the detrimental effects of Ca2+ and Mg2+ on the natural flotability of MoS2 were mainly due to the attachment of formed CaMoO4 precipitates and Mg(OH)2 colloids onto MoS2 surface. However, the addition of sodium hexametaphosphate (SHMP) reduced the negative effects. Various measurements, including contact angle, zeta potential, fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and atomic force microscope (AFM), were conducted to understand the influencing mechanisms of divalent ions and the beneficial effects of SHMP on MoS2 flotation. In addition, the Extended Derjguin–Landau–Verwey–Overbeek (EDLVO) theory was applied to investigate the total interaction energy between MoS2 particles and formed colloids, revealing that the reduced attraction force between MoS2 and Mg(OH)2 colloids in the presence of SHMP primarily resulted in the increased MoS2 recovery. In addition, SHMP combined with Mg2+ and Ca2+ to form dissolvable complexes, thereby reducing insoluble Mg2+ and Ca2+ compounds or precipitation. Thus, this study demonstrated for the first time two influencing mechanisms of SHMP in improving MoS2 recovery in the presence of Ca2+ and Mg2+.

Land surface temperatures (LSTs) obtained from remote sensing data are crucial in monitoring the conditions of crops and urban heat islands. However, since retrieved LSTs represent only the average temperature states of pixels, the distributions of temperatures within individual pixels remain unknown. Such data cannot satisfy the requirements of applications such as precision agriculture. Therefore, in this paper, we propose a model that combines a fast radiosity model, the Radiosity Applicable to Porous IndiviDual Objects (RAPID) model, and energy budget methods to dynamically simulate brightness temperatures (BTs) over complex surfaces. This model represents a model-based tool that can be used to estimate temperature distributions using fine-scale visible as well as near-infrared (VNIR) data and temporal variations in meteorological conditions. The proposed model is tested over a study area in an artificial oasis in Northwestern China. The simulated BTs agree well with those measured with the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The results reflect root mean squared errors (RMSEs) less than 1.6 °C and coefficients of determination (R2) greater than 0.7. In addition, compared to the leaf area index (LAI), this model displays high sensitivity to wind speed during validation. Although simplifications may be adopted for use in specific simulations, this proposed model can be used to support in situ measurements and to provide reference data over heterogeneous vegetation surfaces.

Sea water has been used in flotation plants, showing a promising way to save fresh water usage. Previous studies indicated that divalent salts in sea water played negative roles in chalcopyrite flotation, but not much work have been conducted to understand the eliminating mechanisms. This study systematically investigated the effects of divalent cations of Ca2+ and Mg2+ on natural flotability of chalcopyrite in the absence of collectors and frothers. The reduced recovery was mainly due to the adsorption of Mg and Ca hydroxyl complexes and precipitation on chalcopyrite surfaces, giving rise to a less hydrophobic surface. The addition of sodium hexametaphosphate (SHMP), however, significantly improved chalcopyrite recovery. Species calculation, contact angle, zeta potential, FTIR and XPS analyses were conducted to understand the influencing mechanisms of divalent ions and the beneficial effects of SHMP on chalcopyrite recovery. The primary mechanism was that SHMP prevented the adsorption of positively charged Mg and Ca compounds or precipitation with hydrophilic properties such as Mg(OH)2 on chalcopyrite surfaces, confirmed by the Derjguin-Landau-Verwey-Overbeek (DLVO) theory. Secondly, SHMP reacted with Mg2+ and Ca2+ to form dissolvable complexes, thereby declining the formation of insoluble Mg2+ and Ca2+ compounds or precipitation.

Rugged terrain, including mountains, hills, and some high lands are typical land surfaces around the world. As a physical parameter for characterizing the anisotropic reflectance of the land surface, the importance of the bidirectional reflectance distribution function (BRDF) has been gradually recognized in the remote sensing community, and great efforts have been dedicated to build BRDF models over various terrain types. However, on rugged terrain, the topography intensely affects the shape and magnitude of the BRDF and creates challenges in modeling the BRDF. In this paper, after a brief introduction of the theoretical background of the BRDF over rugged terrain, the status of estimating land surface BRDF properties over rugged terrain is comprehensively reviewed from a historical perspective and summarized in two categories: BRDFs describing solo slopes and those describing composite slopes. The discussion focuses on land surface reflectance retrieval over mountainous areas, the difference in solo slope and composite slope BRDF models, and suggested future research to improve the accuracy of BRDFs derived with remote sensing satellites.

Topography complicates the modeling and retrieval of land surface albedo due to shadow effects and the redistribution of incident radiation. Neglecting topographic effects may lead to a significant bias when estimating land surface albedo over a single slope. However, for rugged terrain, a comprehensive and systematic investigation of topographic effects on land surface albedo is currently ongoing. Accurately estimating topographic effects on land surface albedo over a rugged terrain presents a challenge in remote sensing modeling and applications. In this paper, we focused on the development of a simplified estimation method for snow-free albedo over a rugged terrain at a 1-km scale based on a 30-m fine-scale digital elevation model (DEM). The proposed method was compared with the radiosity approach based on simulated and real DEMs. The results of the comparison showed that the proposed method provided adequate computational efficiency and satisfactory accuracy simultaneously. Then, the topographic effects on snow-free albedo were quantitatively investigated and interpreted by considering the mean slope, subpixel aspect distribution, solar zenith angle, and solar azimuth angle. The results showed that the more rugged the terrain and the larger the solar illumination angle, the more intense the topographic effects were on black-sky albedo (BSA). The maximum absolute deviation (MAD) and the maximum relative deviation (MRD) of the BSA over a rugged terrain reached 0.28 and 85%, respectively, when the SZA was 60° for different terrains. Topographic effects varied with the mean slope, subpixel aspect distribution, SZA and SAA, which should not be neglected when modeling albedo.

The issue for the validation of land surface remote sensing albedo products over rugged terrain is the scale effects between the reference albedo measurements and coarse scale albedo products, which is caused by the complex topography. This paper illustrates a multi-scale validation strategy specified for coarse scale albedo validation over rugged terrain. A Mountain-Radiation-Transfer-based (MRT-based) albedo upscaling model was proposed in the process of multi-scale validation strategy for aggregating fine scale albedo to coarse scale. The simulated data of both the reference coarse scale albedo and fine scale albedo were used to assess the performance and uncertainties of the MRT-based albedo upscaling model. The results showed that the MRT-based model could reflect the albedo scale effects over rugged terrain and provided a robust solution for albedo upscaling from fine scale to coarse scale with different mean slopes and different solar zenith angles. The upscaled coarse scale albedos had the great agreements with the simulated coarse scale albedo with a Root-Mean-Square-Error (RMSE) of 0.0029 and 0.0017 for black sky albedo (BSA) and white sky albedo (WSA), respectively. Then the MRT-based model was preliminarily applied for the assessment of daily MODerate Resolution Imaging Spectroradiometer (MODIS) Albedo Collection V006 products (MCD43A3 C6) over rugged terrain. Results showed that the MRT-based model was effective and suitable for conducting the validation of MODIS albedo products over rugged terrain. In this research area, it was shown that the MCD43A3 C6 products with full inversion algorithm, were generally in agreement with the aggregated coarse scale reference albedos over rugged terrain in the Heihe River Basin, with the BSA RMSE of 0.0305 and WSA RMSE of 0.0321, respectively, which were slightly higher than those over flat terrain.

After publication of the research paper [1], it was found that funding information was missing from the Acknowledgment part [...]

The inversion of land surface component temperatures is an essential source of information for mapping heat fluxes and the angular normalization of thermal infrared (TIR) observations. Leaf and soil temperatures can be retrieved using multiple-view-angle TIR observations. In a satellite-scale pixel, the clumping effect of vegetation is usually present, but it is not completely considered during the inversion process. Therefore, we introduced a simple inversion procedure that uses gap frequency with a clumping index (GCI) for leaf and soil temperatures over both crop and forest canopies. Simulated datasets corresponding to turbid vegetation, regularly planted crops and randomly distributed forest were generated using a radiosity model and were used to test the proposed inversion algorithm. The results indicated that the GCI algorithm performed well for both crop and forest canopies, with root mean squared errors of less than 1.0 °C against simulated values. The proposed inversion algorithm was also validated using measured datasets over orchard, maize and wheat canopies. Similar results were achieved, demonstrating that using the clumping index can improve inversion results. In all evaluations, we recommend using the GCI algorithm as a foundation for future satellite-based applications due to its straightforward form and robust performance for both crop and forest canopies using the vegetation clumping index.

Much attention has been paid to the flotation of chalcopyrite using saline seawater. However, the influence of salt ions on mineral flotation is complex, and different salts may play various roles—either beneficial or detrimental. This study investigated the effects of common chlorides (Cl−) of Na+, K+, Mg2+, and Ca2+ in seawater on chalcopyrite floatability. The presence of Na+, K+, and Ca2+ resulted in greater chalcopyrite recovery, with this effect being more pronounced for the monovalent cations. In contrast, the addition of Mg2+ resulted in decreased chalcopyrite flotation efficiency. Contact angle measurements showed that the presence of monovalent cations increased the hydrophobicity of the chalcopyrite surface, while the presence of divalent cations reduced its hydrophobicity, depending on the concentration. Zeta potential, pulp species, and X-ray photoelectron spectroscopy (XPS) cross-confirmed the precipitation of Mg(OH)2 on the chalcopyrite surface when Mg concentration was 10−2 M and pulp pH was 10.

Narrowband-to-broadband conversion is a critical procedure for mapping land-surface broadband albedo using multi-spectral narrowband remote-sensing observations. Due to the significant difference in optical characteristics between soil and vegetation, NTB conversion is influenced by the variation in vegetation coverage on different surface types. To reduce this influence, this paper applies an approach that couples NTB coefficient with the NDVI. Multi-staged NDVI dependent NTB coefficient look-up tables (LUT) for Moderate Resolution Imaging Spectroradiometer (MODIS), Polarization and Directionality of Earth’s Reflectance (POLDER) and Advanced Very High Resolution Radiometer (AVHRR) were calculated using 6000 spectra samples collected from two typical spectral databases. Sensitivity analysis shows that NTB conversion is affected more by the NDVI for sensors with fewer band numbers, such as POLDER and AVHRR. Analysis of the validation results based on simulations, in situ measurements and global albedo products indicates that by using the multi-staged NDVI dependent NTB method, the conversion accuracies of these two sensors could be improved by 2%–13% on different NDVI classes compared with the general method. This improvement could be as high as 15%, on average, and 35% on dense vegetative surface compared with the global broadband albedo product of POLDER. This paper shows that it is necessary to consider surface reflectance characteristics associated with the NDVI on albedo-NTB conversion for remote sensors with fewer than five bands.

In order to selectively remove iron from copper laden solution after leaching but prior to electrowinning, equilibrium, kinetic, and thermodynamic studies have been conducted on an a chelating resin of Rexp-501 at pH 1.0 and at various temperatures. Both Langmuir and Freundlich models were investigated, with the Langmuir model proving to be more suitable for fitting iron removal performance, with little influence from copper concentration. Compared with the pseudo first order kinetic model, the pseudo second order kinetic model fitted the dynamic adsorption process better, indicating a chemisorption mechanism. Fourier transform infrared spectroscopy (FT-IR) results indicated that C=O from carbonyl group played a key role in combining with iron and can be regenerated and reused. However, the C=O of the acylamino group combining with iron was not able to be released after oxalic acid was applied.

Hydrometallurgical processing of chalcopyrite is hindered predominantly due to the passivation layers formed on the chalcopyrite surface. However, the effects of impurity cations released from the gangue are not yet well understood. Density functional theory (DFT) calculations were carried out to investigate monovalent cations of Na+ and K+ on chalcopyrite (001)-S surface using Materials Studio. The results show that the 3d orbital of Fe and 3p orbital of S predominantly contribute to their activities during chalcopyrite oxidation and dissolution processes. In addition, SO42− is more likely to be adsorbed on one Fe site in the presence of Na+, while it is preferentially adsorbed on two Fe sites in the presence of K+. However, the adsorption of both Na2SO4 and K2SO4 on the chalcopyrite (001)-S surface contributes to the breakage of S–S bonds, indicating that the impurity cations of Na+ and K+ are beneficial to chalcopyrite leaching in a sulfuric environment. The adsorption energy and partial density of states (PDOS) analyses further indicate that the adsorption of Na2SO4 on chalcopyrite (001)-S surface is favored in both -BB (bidentate binuclear ) and -BM (bidentate mononuclear) modes, compared to the adsorption of K2SO4.