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Cladocerans can produce dormant stages to avoid unfavorable environments, such as predation pressure and population crowding. However, only a few studies evaluated the influences of the biochemical signals of predation risk and population crowding on the termination of dormant stages of cladocerans. This study aimed to investigate the influences of predation risk signals from different predators and crowding signals from high‐density populations on the hatching of cladoceran resting eggs and the anti‐predation defensive traits of hatched offspring. We collected resting eggs of Ceriodaphnia cornuta from the surface of lake sediments and incubated them under different biochemical signals (fish kairomones, Chaoborus kairomones, alarm signals, and crowding signals) in the laboratory. In response to fish kairomones, Chaoborus kairomones, and alarm signals, the hatching time of resting eggs was delayed to a certain extent, and the body length of the offspring hatched from resting eggs increased at their birth and decreased at their first reproduction. This indicated that the offspring hatched from C. cornuta resting eggs possibly can sense predation risk signals but cannot distinguish the type of signals. In addition, the effects of crowding signals on the resting eggs were similar to those of fish kairomones, both of which can increase the body length of hatched offspring at birth, but these influences would not be further enhanced in the simultaneous presence of fish kairomones and crowding signals. This study will contribute to a better understanding of the perception of resting eggs to environmental biochemical signals and the corresponding hatching strategies of cladocerans. [ABSTRACT FROM AUTHOR]

Both predation risk and crowding can induce sexual reproduction in Daphnia, and predator kairomones can also cause population crowding. It is, however, unclear as to whether sexual reproduction is caused by kairomone per se or indirectly by kairomone‐induced crowding.In this study, we cultured Daphnia pulex in the presence of fish kairomone, with newborn offspring being retained (increasing population density) or removed (constant population density). The relationships among fish kairomone, population density, and indicators of sexual reproduction were assessed using structural equation models.The results showed that when offspring were retained in the population, the population density and sexual reproduction by Daphnia simultaneously increased in response to the presence of the fish kairomone, whereas sexual reproduction was not directly affected in the presence of fish kairomones alone. Conversely, when maintaining a constant population density, the number of ephippia and ratio of male to female of Daphnia increased with increasing population density, but the presence of fish kairomone did not promote sexual reproduction. Structural equation model analysis indicated that population density, rather than the fish kairomone, was the significant factor promoting sexual reproduction.The findings of this study indicate that population density directly triggers sexual reproduction in Daphnia populations. Our observations provide new insights into environmentally induced sexual reproduction, and on this basis, we suggest that a more thorough consideration of the interactions among environmental factors in determining sexual reproduction is necessary. [ABSTRACT FROM AUTHOR]

Daphnia can develop a VARIETY of inducible defensive traits when they sense predator kairomone and transmit the predation risk information from females to their offspring. However, limited research has focused on how Daphnia females transmit predation risk information across multiple broods when the mothers and offspring are respectively exposed or not exposed to predation pressure.Here we conducted a prolonged predation risk transmission experiment, where three generations of Daphnia pulex individuals were cultured with or without fish kairomone until they produce six broods of offspring. Life history traits and morphological defensive traits were measured to investigate how inducible defensive traits were transmitted across generations and multiple broods.Our results demonstrated that (1) inducible defensive traits of offspring were mainly determined by the offspring's environment rather than their mothers' experience; and (2) as the mothers produced more broods of offspring, inducible defensive traits of the offspring were gradually increased and then decreased.The present study highlights the reversibility and differences among generations and broods of the transmission of predation risk information via transgenerational effects, which provides a basis for further understanding of transgenerational plasticity across broods. [ABSTRACT FROM AUTHOR]

Terrestrial water storage (TWS) is an essential element of the water cycle and a key state variable for land surface–atmosphere interaction. This study investigates the changes of TWS in Xinjiang of China in response to climate change, using Gravity Recovery and Climate Experiment (GRACE)-derived data and ground hydrological/meteorological observations in 2003–2015. The results show that the TWS has an overall significant decreasing trend of −2.8 mm per year. TWS is in a state of surplus in the first half year (from February to July), while it is in a state of deficit in the second half year (from August to next January). The change rates in TWS exhibit strong regional disparities, with profound decreasing trends in Tianshan Mountains and increasing in Kunlun Mountains. Further analyses suggest that the spatial-temporal change of TWS was closely related to the variations in seasonal snow melt and glacier retreat due to temperature and precipitation changes. [ABSTRACT FROM AUTHOR]

Taylor diagram has been frequently used to evaluate climate or hydrology models or data. A Taylor diagram summarizes three frequently used metrics including correlation coefficient (CC), standard deviation (STD), and centred root mean square error (RMSEc). Although these three metrics are relevant metrics for some applications, in some cases, additional indicators are needed, which calls for a new method. This study firstly addressed the short comments about the distance between indices of simulation and observation (DISO) described in a previous study. Secondly, the number of statistical metrics of DISO is extended from 3 to more than 3. The statistical metrics of the expanded DISO are more flexible than the Taylor diagram which uses the three fixed metrics. Thirdly, the current work compares the Taylor diagram with the expanded DISO in terms of their theoretical bases, revealing the advantage of DISO in terms of its flexibility in the selection of different types of metrics, and its suitability as an effective single metric to express a model's or dataset's overall quality. The power and flexibility of the expanded DISO are discussed. [ABSTRACT FROM AUTHOR]

• A spatial cognitive learning method for vectorized building extraction is proposed. • Enriched topological embedding of graph nodes increases model generalization ability. • Pooling and up-sampling augmenting feature reuse in graph convolution is introduced. • Obtain-and-play extraction with accurate coordinates of shapely boundary is accessed. Traditional approach from source image to application vectors in building extraction needs additional complex regularization of converted intermediate raster results. While in conversion, the lost detailed artifacts, unnecessary nodes, and messy paths would be labor-intensive to repair errors and topological issues, even aside the inherent problems of blob-like objects and blurry, jagged edges in first-stage extraction. This research explores new graph convolution-driven solution, the spatial-cognitive shaping model (SCShaping), to directly access vectorization form of individual buildings through spatial cognitive approximation to coordinates that form building boundaries. To strengthen graph nodes expressivity, this method enriches topological feature embedding travelling along the model architecture along with features contributed from convolutional neural network (CNN) extractor. To stimulate the neighboring aggregation in graphs, Graph-Encoder-Decoder mechanism is introduced to augment feature reuse integrating complementary graph convolution layers. The strong embedding guarantees effective feature tapping and the robust structure guarantees the feature mining. Comparative studies have been conducted between the proposed approach with five other methods on three challenging datasets. The results demonstrate the proposed approach yields unanimous and significant improvements in mask-wise metrics, which evaluate object integrity and accuracy, as well as edge-wise metrics, which assess contour regularity and precision. The outperformance also indicates better multi-scale object adaptability of SCShaping. The obtain-and-play SCShaping commands a pleasurable implementation way to advance ideal man – machine collaboration. [ABSTRACT FROM AUTHOR]

Immunotherapy directed against cancer-specific neoantigens derived from non-silent mutants is a promising individualized strategy for cancer treatment. Neoantigens shared across patients could be used as a public resource for developing T cell-based therapy. To identify potential public neoantigens for therapy in gastric cancer (GC), 74 GC patients were enrolled in this study. Combined with the TCGA cohort and other published studies, whole exome sequencing data from 942 GC patients were used to detect somatic mutations and predict neoantigens shared by GC patients. The mutations pattern between our study and the TCGA cohort is comparable, and C > T is the most common substitution. The number of neoantigens was significantly higher in older patients (age ≥60) compared to younger patients (age <60), both in this study and the TCGA cohort. Recurrent neoantigens were found in eight genes (TP53, PIK3CA, PGM5, ERBB3, C6, TRIM49C, OR4C16, and KRAS) in this study. The neoantigen-associated mutations PIK3CA (p.H1047R) and TP53 (p.R175H) are common across several cancer types, indicating their potential usage. Overall, our study illustrates a comprehensive genomic landscape of GC and provides the recurrent neoantigens to facilitate further immunotherapy. [ABSTRACT FROM AUTHOR]

High-performance simulation of flow dynamics remains a major challenge in the use of physical-based, fully distributed hydrologic models. Parallel computing has been widely used to overcome efficiency limitation by partitioning a basin into sub-basins and executing calculations among multiple processors. However, existing partition-based parallelization strategies are still hampered by the dependency between inter-connected sub-basins. This study proposed a particle-set strategy to parallelize the flow-path network (FPN) model for achieving higher performance in the simulation of flow dynamics. The FPN model replaced the hydrological calculations on sub-basins with the movements of water packages along the upstream and downstream flow paths. Unlike previous partition-based task decomposition approaches, the proposed particle-set strategy decomposes the computational workload by randomly allocating runoff particles to concurrent computing processors. Simulation experiments of the flow routing process were undertaken to validate the developed particle-set FPN model. The outcomes of hourly outlet discharges were compared with field gauged records, and up to 128 computing processors were tested to explore its speedup capability in parallel computing. The experimental results showed that the proposed framework can achieve similar prediction accuracy and parallel efficiency to that of the Triangulated Irregular Network (TIN)-based Real-Time Integrated Basin Simulator (tRIBS). [ABSTRACT FROM AUTHOR]

Gaining a comprehensive understanding of the characteristics and propagation of precipitation-based meteorological drought to terrestrial water storage (TWS)-derived hydrological drought is of the utmost importance. This study aims to disentangle the frequency–time relationship between precipitation-derived meteorological and TWS-based hydrological drought from June 2002 to June 2017 based on the Standardized Precipitation Index (SPI) and Standardized Terrestrial Water Storage Index (STI) by employing wavelet coherence rather than a traditional correlation coefficient. The possible influencing factors on drought propagation in 28 regions across the world are examined. The results show that the number of drought months detected by the STI is higher than that detected by the SPI worldwide, especially for slight and moderate drought. Generally, TWS-derived hydrological drought is triggered by and occurs later than precipitation-based meteorological drought. The propagation characteristics between meteorological and hydrological droughts vary by region across the globe. Apparent intra-annual and interannual scales are detected by wavelet analysis in most regions, but not in the polar climate region. Drought propagation differs in phase lags in different regions. The phase lag between hydrological and meteorological drought ranges from 0.5 to 4 months on the intra-annual scale and from 1 to 16 months on the interannual scale. Drought propagation is influenced by multiple factors, among which the El Niño–Southern Oscillation, North Atlantic Oscillation, and potential evapotranspiration are the most influential when considering one, two, or three factors, respectively. The findings of this study improve scientific understanding of drought propagation mechanisms over a global scale and provide support for water management in different subregions. [ABSTRACT FROM AUTHOR]

Accurate atmospheric correction is decisive for ocean color remote sensing applications. Near infrared (NIR)-based algorithm performs well for clear waters; while shortwave infrared (SWIR)-based algorithm can obtain good results for turbid waters, however, it tends to produce noisy patterns for clear waters. A practical strategy is to apply NIR- and SWIR-based algorithm for clear and turbid waters, respectively, which is called NIR-SWIR combined atmospheric correction algorithm. However, the currently applied switching scheme for the NIR-SWIR algorithm undermines the atmospheric correction performance. This study aimed to find an applicable switching scheme for NIR-SWIR algorithm. Four MODIS land bands were used to switch the NIR- and SWIR-based algorithms. A simulated dataset was used to evaluate atmospheric performance of NIR- and SWIR-based algorithm. The switching threshold for each MODIS land band was determined as an R rs value at which SWIR-based algorithm performed better than NIR-based algorithm. The switching scheme was evaluated using matchups of simultaneous MODIS Aqua images and AERONET-OC data, and then tested with a MODIS Aqua image over the western Pacific Ocean. Results showed that the switching threshold for R rs (469), R rs (555), R rs (645) and R rs (859) were 0.009, 0.016, 0.009 and 0.0006 sr−1, respectively; R rs (645) with a threshold of 0.009 sr−1 and R rs (555) with a threshold of 0.016 sr−1 worked well for NIR-SWIR algorithm, while R rs (469) and R rs (859) produced worse performance. Therefore, R rs (555) > 0.016 sr−1 or R rs (645) > 0.009 sr−1 was recommended as the switching scheme for NIR-SWIR algorithm. Considering contrasted estuarine, coastal and some inland waters, combining NIR- and SWIR-based atmospheric correction algorithm with the proposed switching scheme should be useful for remote sensing monitoring over these waters. [ABSTRACT FROM AUTHOR]

The accuracies of gridded precipitation data sets are important for regional climate studies and hydrological models. In this study, the performances of Global Precipitation Climatology Centre (GPCC) V7, Climatic Research Unit (CRU) TS 3.22 and Willmott and Matsuura (WM) precipitation data sets were examined over central Asia by comparing them against observed precipitation records (OBS) from 586 meteorological stations during 1901–2010. The results show that all the three gridded data sets underestimated the observed precipitation at annual and monthly scales, especially in mountainous areas. Both GPCC and WM underestimated seasonal precipitation, especially for spring precipitation. Among the three gridded data sets, GPCC had the highest correlation and lowest bias compared with CRU and WM when against the OBS. WM had a higher correlation than that of CRU, and its bias was larger than that of CRU. In terms of the drought and heavy rainfall events, CRU had the best performance in capturing drought events, and GPCC was best at representing heavy rainfall events. These differences in the performances between the three gridded data sets were primarily induced by their different interpolation methods and the numbers of available meteorological stations used in the interpolations of the three gridded data sets. Therefore, compared to the other two data sets, GPCC is more suitable for studies of long‐term precipitation variations over central Asia. [ABSTRACT FROM AUTHOR]

Abstract: The accuracy and efficiency of the simulations in distributed hydrological models must depend on the proper estimation of flow directions and paths. Numerous studies have been carried out to delineate the drainage patterns based on gridded digital elevation models (DEMs). The triangulated irregular network (TIN) has been increasingly applied in hydrological applications due to the advantages of high storage efficiency and multi‐scale adaptive performance. Much of the previous literature focuses mainly on filling the depressions on gridded DEMs rather than treating the special cases in TIN structures, which has hampered its applications to hydrological models. This study proposes a triangulation‐based solution for the removal of flat areas and pits to enhance the simulation of flow routing on triangulated facet networks. Based on the drainage‐constrained TIN generated from only a gridded DEM by the compound point extraction (CPE) method, the inconsistent situations including flat triangles, V‐shape flat edges and sink nodes are respectively identified and rectified. The optimization algorithm is an iterative process of TIN reconstruction, in which the flat areas are generalized into their center points and the pits are rectified by embedding break lines. To verify the proposed algorithm and investigate the potential for flow routing, flow paths of steepest descent are derived by the vector‐based tracking algorithm based on the optimized TIN. A case study of TIN optimization and flow path tracking was performed on a real‐world DEM. The outcomes indicate that the proposed approach can effectively solve the problem of inconsistencies without a significant loss in accuracy of the terrain model. [ABSTRACT FROM AUTHOR]

The purpose of this study was to evaluate the accuracy of diffusion-weighted imaging (DWI) for predicting locoregional failure of chemoradiotherapy in patients with head and neck squamous cell carcinoma (HNSCC). A comprehensive search was conducted through the EMBASE, PubMed and Cochrane Library databases for relevant publications. Stata software was used to calculate the pooled sensitivity, specificity, likelihood ratios and diagnostic odds ratios, and to construct a summary receiver operating characteristics (sROC) curve for DWI. A total of 9 studies comprising 421 patients were included. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio were 0.82 [95% confidence interval (CI): 0.72-0.88], 0.70 (95% CI: 0.62-0.77), 2.7 (95% CI: 2.1-3.6), 0.26 (95% CI: 0.17-0.41), and 10.48 (95% CI: 5.35-20.53), respectively. The area under the sROC curve was 0.84 (95% CI: 0.81-0.87). Therefore, DWI appears to be a promising imaging modality for predicting local failure of chemoradiotherapy in patients with HNSCC. [ABSTRACT FROM AUTHOR]

ABSTRACT This study examines the temporal variations and spatial distributions of annual precipitation over Central Asia during the periods of 1901-2013, 1951-2013, and 1979-2013 using the latest version of Global Precipitation Climatology Centre (GPCC) full data reanalysis version 7 ( GPCC V7) data set. The linear trend and multiperiods of the precipitation over the entire region and plain and mountainous area separately are analysed by linear least square method and ensemble empirical mode decomposition method. An overall increasing trend [0.66 mm (10 years)−1] is found for the entire region during 1901-2013, which is smaller than that of 1951-2013. The regional annual precipitation exhibits multi-decadal variations, with a sharp decline during 1901-1944, followed by an increase until 1980s, and a fluctuation thereafter. During 1979-2013, the mountainous area shows a greater increasing trend than the entire region. Furthermore, the regional annual precipitation has exhibited high-frequency variations with 3-year and 6-year quasiperiods and a low-frequency variation with 28-year quasiperiods. In terms of the spatial distribution, increasing trend in the annual precipitation is found in Xinjiang and decreasing trends appear over the five countries of Central Asia during 1951-2013. Empirical orthogonal function results show that the mountainous area is the large variability centre of the annual precipitation. The dominant mode of interannual variability in Central Asia annual precipitation is related to El Niño-Southern Oscillation, which explains about 17% of the interannual variance during 1951-2013. The results of this study describe the long-term variation in the annual precipitation over Central Asia as well as its relationship with some key climate indices in great detail, which will benefit the understanding and the prediction of the climate variations in this region. [ABSTRACT FROM AUTHOR]

Trigger factor (TF) is one of the multiple bacterial chaperone proteins interacting with nascent peptides and facilitating their folding in bacteria. While TF is well-characterized in E. coli , HP0795 , a TF-like homologue gene identified earlier in the pathogenic Helicobacter pylori ( H. pylori ), has not been studied biochemically to date. To characterize its function as a chaperone, we performed 3D-modeling, cross-linking and in vitro enzyme assays to HP0795 in vitro . Our results show that HP0795 possesses peptidyl prolyl cis-trans isomerase activity and exhibits a dimeric structure in solution. In addition, stable expression of HP0795 in a series of well-characterized E. coli chaperone-deficient strains rescued the growth defects in these mutants. Furthermore, we showed that the presence of HP0795 greatly reduced protein aggregation caused by deficiencies of chaperones in these strains. In contrast to other chaperone genes in H. pylori , gene expression of HP0795 displays little induction under acidic pH conditions. Together, our results suggest that HP0795 is a constitutively expressed TF-like protein of the prokaryotic chaperone family that may not play a major role in acid response. Given the pathogenic properties of H. pylori , our insights might provide new avenues for potential future medical intervention for H. pylori -related conditions. [ABSTRACT FROM AUTHOR]

Identifying, recording and monitoring land cover change on the Earth's surface is a complex procedure. Spatio-temporal modelling is an effective approach to simplifying and simulating the process. Existing spatio-temporal modelling methods are typically based on either, an overlay of multi-temporal land cover maps, or temporal trend analysis of spatial pattern indices. Consequently, an understanding of the spatial dynamics of any changes is either fragmental in the former case, or invisible in the latter case, due to the lack of adequate geographical location information. In the arid zone of western China, a widely accepted belief is that rapid farmland expansion and the subsequent abandonment of the farms, or their mis-management, would lead to soil salinisation and desertification. In order to better understand the spatio-temporal pattern of farmland change, this paper proposes an integrated approach that combines the two methods of pixel-based trajectory analysis and class-level spatial pattern metrics. Multi-temporal remote sensing images were collected beginning in 1994, a year that captured the initial effects of the period of rapid farmland expansion. Historical change trajectories were established for each pixel and categorized according to change types ( i.e . expanding or shrinking). The spatial dynamics of farmland change can then be illustrated by mapping the change trajectory classes. Spatial patterns of farmland change were quantified by employing distribution-related landscape metrics, such as indices of interspersion (IJI), connectivity (COHESION) and isolation (ENN), to analyse farmland development models of the two river basins in the study area. Shape indices, including overall shape (nLSI) and edge shape (FRAC), were applied to appraise the structural stability of the farmlands over time. Results indicate that, over the past two decades, the area subject to farmland expansion was significantly larger than that experiencing farmland abandonment. The relatively rapid expansion of farmland exhibited a concentrated pattern, and generally followed a layer-based development model. The study showed that the proposed research method effectively visualized and quantified the spatio-temporal dynamics of farmland change. [ABSTRACT FROM AUTHOR]

Landslides are one of the most destructive disasters that cause damage to both property and life every year. The mountainous terrain, heavy and prolonged rainfall and dense development near steep hillsides make Hong Kong as one of the most vulnerable metropolitans to the risk of landslides. Therefore, regional-specific landslide susceptibility assessment in Hong Kong is necessary for hazard management and effective land use planning. Various methodologies have been proposed for landslide susceptibility mappings. By applying the statistically based frequency ratio and logistic regression models in Lantau Island, Hong Kong, this study attempts to add extra value to the literature of evaluating their ‘prediction rate’ (rather than ‘success rate’) for landslide susceptibility mapping in a temporal context. The spatial relationship among landslide occurrence and nine causative factors (elevation, slope, aspect, plan curvature, profile curvature, normalized difference vegetation index (NDVI), distance to river, distance to fault and lithology) were examined, and landslide susceptibility maps were generated by frequency ratio and logistic regression model. Validations of the mapping results were performed by calculating relative operating characteristics (ROC). Virtually all previous studies randomly extracted and reserved a portion of historical landslide records to perform the model evaluation. In contrast, in this study, 1864 (70%) landslide records in the Enhanced Natural Terrain Landslide Inventory from 2000 to 2008 are utilized to train the model, while the subsequent 799 (30%) landslides occurred from 2008 to 2009 are used for model validation. The validation result shows that logistic regression model (84.05%) possesses a better prediction power than frequency ratio model (76.64%) for the study area. This study attempts to offer a new model assessment strategy for landslide susceptibility mapping. The resultant maps also provide a scientific assessment of the risk areas with respect to landslides on Lantau Island and could serve as a basis for decisions or justification of the Lantau development planning. [ABSTRACT FROM PUBLISHER]

Accurate high-spatial-resolution precipitation is significantly important in hydrological and meteorological modelling, especially in rain-gauge-sparse areas. Some methods and strategies have been applied for satellite-based precipitation downscaling, residual correction and precipitation calibration. However, which downscaling scheme can provide reliable high-resolution precipitation efficiently remains unanswered. To address this issue, this study aimed to present a framework combining the machine learning downscaling algorithm and post-process procedures. Firstly, four ML-based models, namely support vector regression, random forest, spatial random forest (SRF) and eXtreme gradient boosting (XGBoost), were tested for downscaling and compared with conventional downscaling methods. Then, the effectiveness of the residual correction process using ordinary Kriging and the calibration process using the geographical difference analysis (GDA) method was investigated. The results showed that the ML-based methods had better performance than the conventional regression and interpolation approaches. The SRF and XGBoost outperformed others in generating accurate precipitation estimation with a high resolution. The GDA calibration process significantly improved the downscaled results. However, the residual correction process decreased the downscaling performance of the ML-based models. Combining the SRF or XGBoost downscaling algorithm with the GDA calibration method could be a promising downscaling scheme for precipitation data. The scheme could be used to generate high-resolution precipitation, especially in areas urgently requiring data, which would benefit regional water resource management and hydrological disaster prevention. [ABSTRACT FROM AUTHOR]

In engineering ceramic grinding, the wheel wear states have an important influence on the processing efficiency and grinding quality. To address the difficulty of online monitoring of wheel wear states, a signal reconstruction method based on parameter-adaptive variational modal decomposition was proposed. Experiments on the entire life cycle of the grinding wheel were performed, and the wear states were classified based on the observed surface morphologies of the wheel and workpiece. Subsequently, acoustic emission signals were collected by nodes, and high correlation frequency bands were chosen and reconstructed. The signal features were extracted, and the wear states were identified based on a random forest optimization feature combination, finally. In this study, taking alumina ceramic as an example, eight groups of single-factor experiments were designed based on cumulative grinding depth to determine the optimal linear speed of the grinding wheel, worktable moving rate, and other process parameters. A total of 160 groups of AE signal samples were obtained. The results show that feature extraction by frequency bands can better reflect the changes in the grinding wheel wear states than the overall signal. In addition, optimization feature combinations based on the bands after decomposition, filtering, and reconstruction can divide and identify the various wear states more effectively. The comprehensive identification accuracy reached 90.6%. The accuracy of identifying the severe wear state reached 100%. Thus, the proposed method provides theoretical guidance for the practical industrial applications of online monitoring of wheel wear states. [ABSTRACT FROM AUTHOR]

High-resolution images of the crust were obtained along two high-density temporary seismic arrays that cross tectonic blocks in the southwest boundary of the Ordos block and its adjacent regions. Dense stations with <1-km station spacings allowed teleseismic receiver functions to unveil the unprecedented details of crustal structures from the northeast margin of the Tibetan Plateau and the Qinling orogenic belt to the southwest Ordos block. The observations from nearby broadband seismic stations and two-dimensional numerical simulation were used to verify the reliability and validity of our results from the temporary dense array data. The receiver function profiles and the migration images revealed the contrasting crustal structures beneath the southwest Ordos block and the adjacent regions. Liupanshan mountain is a boundary that resists the lateral growth of the Tibetan Plateau; however, the slight bending of the Moho indicates absence of large-scale deformation in west Liupanshan. The Moho transition zone beneath the Weihe graben and southwest corner of the Ordos block represented by the complicated P-to-S converted phases can be contributed to the eastward extrusion of hot uppermost mantle from the Tibetan Plateau driven by the mantle flow. [Display omitted] • High density seismic array revealed the crustal structures beneath the southwest Ordos block and its adjacent regions. • The results indicate the contrasting crustal structures in the southwest boundary region of Ordos block. • The mantle flow from Tibetan Plateau caused the complicated Mohobeneath Weihe Graben and Southwest corner of Ordos block. • No large-scale deformation beneath the Liupanshan imply the strong-strong convergence of the Longxi basin and Ordos block. [ABSTRACT FROM AUTHOR]

The article lists individuals who reviews the papers for the periodical including Ola Ahlqvist, Jared Aldstradt, and Claudia Almeida.

This paper proposes a flow-path network (FPN) model to simulate complex surface flow based on a drainage-constrained triangulated irregular network (TIN). The TIN was constructed using critical points and drainage lines extracted from a digital terrain surface. Runoff generated on the surface was simplified as ‘water volumes’ at constrained random points that were then used as the starting points of flow paths (i.e. flow source points). The flow-path for each ‘water volume’ was constructed by tracing the direction of flow from the flow source point over the TIN surface to the stream system and then to the outlet of the watershed. The FPN was represented by a set of topologically defined one-dimensional line segments and nodes. Hydrologic variables, such as flow velocity and volume, were computed and integrated into the FPN to support dynamic surface flow simulation. A hypothetical rainfall event simulation on a hilly landscape showed that the FPN model was able to simulate the dynamics of surface flow over time. A real-world catchment test demonstrated that flow rates predicted by the FPN model agreed well with field observations. Overall, the FPN model proposed in this study provides a vector-based modeling framework for simulating surface flow dynamics. Further studies are required to enhance the simulations of individual hydrologic processes such as flow generation and overland and channel flows, which were much simplified in this study. [ABSTRACT FROM PUBLISHER]

Due to the coarse spatial resolution of imagery and heterogeneity of snow physical parameters, the currently available snow depth data sets derived from passive microwave sensors have shown significant accuracy variations in different parts of the world. This study aims to analyse the reliability of existing remote sensing snow depth products for the arid zone of China. Two long-term products were compared and evaluated including the GlobSnow Snow Water Equivalent product (‘the GlobSnow product’) and the Long-term Snow Depth Dataset of China (‘the WestDC product’). Nine-year ground measurements from 35 sampling sites with diverse topographical conditions were used as ground references for the accuracy assessment. Statistical analysis methods such as intra-class correlation coefficient and root mean square error (RMSE) were adopted for the consistency test and accuracy assessment. Analysis of variance (ANOVA) was employed to examine whether the data reliability varied by seasonal or locational factors. The results show that the two products in general do not agree well in the study region. However, the generalized data with different temporal resolutions tend to yield better results in terms of data consistency and accuracy. Compared to the GlobSnow product, the WestDC product has shown a better accuracy with the RMSE of 8.23, 7.43, and 6.56 cm for the original daily, and generalized weekly, and monthly data, respectively. According to the ANOVA test, season and latitude show statistically significant impacts on data reliability, while altitude and terrain complexity do not. Data reliability declines with higher latitude and it rapidly falls down to an unacceptable level in snow melting periods. This study provides a quantitative assessment on the quality of the snow depth products and raises the awareness of data consistency issues of these products for regional applications. [ABSTRACT FROM AUTHOR]

A scale-adaptive digital elevation model (S-DEM) method is proposed for multi-scale terrain analysis using a single high-resolution digital elevation model (DEM) database. The motivation is to construct a DEM that is self-adaptive to a given scale of an application, rather than letting the application fit into the built-in scale of the DEM. The method is based on an adaptive compound point extraction (CPE) algorithm that extracts surface ‘significant points’ from a high-resolution DEM according to their degree of importance (DOI) to the scale of an application. A data structure can be established to match the demand from an application at a coarser scale. Based on the data structure, a triangulated irregular network (TIN) model can be generated to support the terrain analysis at the desired scale. The aim of the S-DEM is to support multi-scale applications in three aspects, namely, ‘one database for all scales and scale-adaptive’ (i.e. matching any application scale using a single high-resolution DEM), ‘consistent measurement’ (i.e. delivering more constant measurements of terrain parameters with changing scales), and ‘skeleton preservation’ (i.e. preserving basic streamlines with changing scales). Compared with the raster resampling algorithm and the maximum z-tolerance algorithm, we find that the proposed method offers better performance, providing values that meet the accuracy requirements set by DEM data standards for different scales, and producing analytical derivatives that retain terrain features with consistent measurements of terrain parameters. [ABSTRACT FROM PUBLISHER]

The urban fringe is the transition zone between urban land use and rural land use. It represents the most active part of the urban expansion process. Change detection using multi-temporal imagery is proven to be an efficient way to monitor land-use/land-cover change caused by urban expansion. In this study, we propose a new multi-temporal classification method for change detection in the urban fringe area. The proposed method extracts and integrates spatio-temporal contextual information into multi-temporal image classification. The spatial information is extracted by object-oriented image segmentation. The temporal information is modelled with temporal trajectory analysis with a two-step calibration. A probabilistic schema that employs a global membership function is then used to integrate the spectral, spatial and temporal information. A trajectory accuracy measurement is proposed to assist the comparison on the performances of the integrated spatio-temporal method and classical pixel- and ‘snapshot’-based classification methods. The experiment shows that the proposed method can significantly improve the accuracies of both single scene classification and temporal trajectory analysis. [ABSTRACT FROM PUBLISHER]

This study investigates environmental change over a 30-year period and attempts to gain a better understanding of human impacts on an arid environment and their consequences for regional development. Multi-temporal remotely sensed imagery was acquired and integrated to establish the basis for change detection and process analysis. Land cover changes were investigated in two categories, namely categorical change using image classification and quantitative change using a vegetation index. The results show that human-induced land cover changes have been minor in this remote area. However, the pace of growth of human-induced change has been accelerating since the early 1990s. The analysis of the multi-temporal vegetation index also shows no overall trend of rangeland deterioration, although local change of vegetation cover caused by human activities was noticeable. The results suggest that the current trend of rapid growth may not be sustainable and that the implementation of effective counter-measures for environmentally sound development is a rather urgent matter. [ABSTRACT FROM AUTHOR]

Abstract: This paper reports an investigation into the generalization of a grid-based digital elevation model (DEM) for the purpose of terrain analysis. The focus is on the method of restructuring the grid-based surface elevation data to form a triangulated irregular network (TIN) that is optimized to keep the important terrain features and slope morphology with the minimum number of sample points. The critical points of the terrain surface are extracted from the DEM based on their significance, measured not only by their local relief, but also by their importance in identifying inherent geomorphological and drainage features in the DEM. A compound method is proposed by integrating the traditional point-additive and feature-point methods to construct a drainage-constrained TIN. The outcome is then compared with those derived from other selected methods including filtering, point-additive or feature-point algorithms. The results show that the compound approach is capable of taking advantage of both point-additive and feature-point algorithms to maximally keep the terrain features and to maintain RMSE at an acceptable level, while reducing the elevation data points by over 99%. The analytical result also shows that the proposed method outperforms the compared methods with better control in retaining drainage features at the same level of RMSE. [ABSTRACT FROM AUTHOR]

This study develops a practical methodology to assess the accuracy of multi-temporal change detection using a trajectory error matrix (TEM). In this error matrix one axis represents the land-cover change trajectory categories derived from single-date classified images, and the other represents the land-cover change trajectories identified from reference data. The overall accuracies of change trajectories and states of change/no-change are used as indices for accuracy assessment. As the number of possible land-cover change trajectories can be enormous, a practical processing flow for computing accuracy assessment indices has also been developed to avoid listing all possible change trajectories in the error matrix. A case study using this method was conducted to assess the accuracy of land-cover change over a period with five observations in a study area in China's arid zone. This method simplifies the process of estimating overall accuracy in the change trajectory analysis, and provides a more realistic and detailed assessment of the results of multi-temporal change detection using post-classification comparison methods. [ABSTRACT FROM AUTHOR]

This study attempts to develop a methodology to quantify spatial patterns of land cover change using landscape metrics. First, multitemporal land cover types are derived based on a unified land cover classification scheme and from the classification of multitemporal remotely sensed imagery. Categorical land cover change trajectories are then established and reclassified according to the nature and driving forces of the change. Finally, spatial pattern metrics of the land cover change trajectory classes are computed and their relationships to human activities and environmental factors are analysed. A case study in the middle reach of Tarim River in the arid zone of China from 1973 to 2000 shows that during the 30-year study period, the natural force is dominant in environmental change, although the human impact through altering water resources and surface materials has increased dramatically in recent years. The human-induced change trajectories generally show lower normalized landscape shape index (NLSI), interspersion and juxtaposition index (IJI) and area-weighted mean patch fractal dimension (FARC_AM), indicating greater aggregation, less association with others and simpler and larger patches in shape, respectively. The results suggest that spatial pattern metrics of land cover change trajectories can provide a good quantitative measurement for better understanding of the spatio-temporal pattern of land cover change due to different causes. [ABSTRACT FROM AUTHOR]

The objective of this research is to study the relationship between terrain complexity and terrain analysis results from grid‐based digital elevation models (DEMs). The impact of terrain complexity represented by terrain steepness and orientation on derived parameters such as slope and aspect has been analysed. Experiments have been conducted to quantify the uncertainties created by digital terrain analysis algorithms. The test results show that (a) the RMSE of derived slope and aspect is negatively correlated with slope steepness; (b) the RMSE of derived aspect is more sensitive to terrain complexity than that of derived slope; and (c) the uncertainties in derived slope and aspect tend to be found in flatter areas, and decrease with increasing terrain complexity. The study shows that although primary surface parameters can be well defined mathematically, the implementation of those mathematical models in a GIS environment may generate considerable uncertainties related to terrain complexity. In general, when terrain is rugged with steep slopes, the uncertainty of derived parameters is quite minimal. While in flatter areas, the DEM‐based derivatives, particularly the aspect, may contain a great amount of uncertainty, causing significant limitation in applying the analytical results. [ABSTRACT FROM AUTHOR]

Abstract: Landuse change in metropolitan areas is largely focused on the dynamic nature of urban landuse change. In this research, a spatial statistical model was used to support decision-making with regard to urban growth predictions in the urban fringe of Beijing, China. The model adopted in this study was based on the integration of remote sensing, geographical information systems, and multivariate mathematical models. The model emphasises the spatial distribution of the landuse/cover units and the spatio-temporal patterns, which were modelled by landuse/cover change trajectories over a series of observation years. The main trajectories for the landuse/cover change model were based on five sets of multitemporal landuse/cover data derived from remotely sensed images. Using the integrated GIS, several spatial variables were derived, including the proximity to major roads and built-up areas. A multivariate model was established to establish relationships between urban expansion and above spatial variables. The landuse/cover change trajectories and the multivariate model were then integrated to construct a multivariate spatial model that is capable of estimating the spatial probability of the urban expansion. [Copyright &y& Elsevier]

One of the obvious sources of errors in digital terrain analysis (DTA) algorithms is that introduced by raster data structure employed by a digital elevation model (DEM). Because of its regular sample space and orientation, the DTA results often show significant octant ‘bias’, presenting obvious visual and numerical error patterns. Moreover, other DEM data properties may also introduce errors in slope and aspect computation, such as data precision and spatial resolution (i.e. grid interval). This paper reports an investigation on the accuracy of algorithms that derive slope and aspect measures from grid DEM. A quantitative methodology has been developed for objective and data-independent assessment of errors generated from the algorithms that extract surface morphological parameters such as slope and aspect from grid DEM.The generic approach is to use artificial surfaces that can be described by a mathematical model, thus the ‘true’ output value can be pre-determined to avoid uncertainty caused by uncontrollable data errors. Two mathematical surfaces were generated based on ellipsoid (representing convex slopes) and Gauss synthetic surface (representing complex slopes), and the theoretical ‘true’ value of the slope and aspect at any given point on the surfaces could be computed using mathematical inference. Based on these models, tests were made on the results from a number of algorithms for slope and aspect computation. Analysis has been undertaken to find out the spatial and statistical patterns of error distribution so that the influence of data precision, grid resolution, grid orientation and surface complexity can be quantified. [Copyright &y& Elsevier]

This paper reports an investigation on the accuracy of grid-based routing algorithms used in hydrological models. A quantitative methodology has been developed for objective and data-independent assessment of errors generated from the algorithms that extract hydrological parameters from gridded DEM. The generic approach is to use artificial surfaces that can be described by a mathematical model, thus the 'true' output value can be pre-determined to avoid uncertainty caused by uncontrollable data errors. Four mathematical surfaces based on an ellipsoid (representing convex slopes), an inverse ellipsoid (representing concave slopes), saddle and plane were generated and the theoretical 'true' value of the Specific Catchment Area (SCA) at any given point on the surfaces could be computed using mathematical inference. Based on these models, tests were made on a number of algorithms for SCA computation. The actual output values from these algorithms on the convex, concave, saddle and plane surfaces were compared with the theoretical 'true' values, and the errors were then analysed statistically. The strengths and weaknesses of the selected algorithms are also discussed. [ABSTRACT FROM AUTHOR]

At present, application of GIS network analysis for agricultural drainage management is limited, although the nature of water flow within a drainage network is by and large in a similar way to that of, for example, the traffic flow over a road network. This is due to the limitation of the current GIS network model, which has difficulties in handling the complexity and event-based dynamic nature of the drainage network. This research therefore focuses on drainage management problems in a floodplain where drainage is controlled by the natural and artificial drainage networks. GIS network capabilities were employed, with enhancements of specific needs for the drainage simulation. A specialized three-dimensional network model was developed to allow computation of important parameters for network analysis, making dynamic simulation of drainage corresponding to individual rainfall events possible. Test simulation results indicate that the simulation tends to overestimate the discharge volume and pollutant, but the relative error level is low with an average of 7.3% and maximum of 12.7%. [ABSTRACT FROM AUTHOR]

In the real estate business, it is a common understanding that the value and potential of a property are fundamentally determined by its location. This emphasises the significance of spatial factors in decision making in real estate. A geographical information system (GIS) is undoubtedly useful in this decision making. This paper reports on the development of a prototype real estate GIS (REGIS) by integrating fuzzy set (FZ) theory, a rule-based system (RBS) and GIS. The role of this system in the real estate business is in assisting decision makers for sellers and buyers, as well as property managers. For real estate agencies, the system can be used as an aid to selling and managing properties. For the buyers, the REGIS can function as a consultant in their decision making in purchasing properties. Methodologies are demonstrated using case studies. Developed as a generic tool with capabilities to deal with uncertainties, this prototype REGIS can also be applied to other fields, which involves optimal spatial decision making. [ABSTRACT FROM AUTHOR]

Evaluating, ranking, and clustering (ERC) stand as fundamental tasks in scientific research, each requiring a mathematical foundation. This study presents an ERC system anchored in the CCHZ-DISO (Chen, Chen, Hu, and Zhou-Distance between Indices of Simulation and Observation) system. Previous research underscores the optimality achieved by the CCHZ-DISO system (Hu et al., 2022). Since the inception of CCHZ- DISO-series research by Hu et al. (2019), DISO has found extensive applications across various domains including geography, hydrology, and economics. Analogous to the CCHZ-DISO system's construction, the ERC system employs the Euclidean distance to perform evaluating, ranking, and clustering tasks. Furthermore, illustrative examples are provided to elucidate the application of the ERC system. In fact, the ERC system unified the evaluating, ranking, and clustering tasks in one simple equation which is more flexible and simpler than the present system. It will have a more widely application than CCHZ-DISO in diverse scientific domains. [ABSTRACT FROM AUTHOR]

The fine-scale insights of existing cropland trends and their nexus with agrometeorological parameters are of paramount importance in assessing future food security risks and analyzing adaptation options under climate change. This study has analyzed the seasonal cropland trends in the Indus River Plain (IRP), using multi-year remote sensing data. A combination of Sen's slope estimator and Mann–Kendall test was used to quantify the existing cropland trends. A correlation analysis between enhanced vegetation index (EVI) and 9 agrometeorological parameters, derived from reanalysis and remote sensing data, was conducted to study the region's cropland-climate nexus. The seasonal trend analysis revealed that more than 50% of cropland in IRP improved significantly from the year 2003 to 2018. The lower reaches of the IRP had the highest fraction of cropland, showing a significant decreasing trend during the study period. The nexus analysis showed a strong correlation of EVI with the evaporative stress index (ESI) during the water-stressed crop season. Simultaneously, it exhibited substantial nexus of EVI with actual evapotranspiration (AET) during high soil moisture crop season. Temperature and solar radiation had a negative linkage with EVI response. In contrast, a positive correlation of rainfall with EVI trends was spatially limited to the IRP's upstream areas. The relative humidity had a spatially broad positive correlation with EVI compare to other direct climatic parameters. The study concluded that positive and sustainable growth in IRP croplands could be achieved through effective agriculture policies to address spatiotemporal AET anomalies. [ABSTRACT FROM AUTHOR]

Investigation of urban expansion can provide a better understanding of the urbanization process and its driving forces, which is critical for environmental management and land use planning. Total of 514 sampling points from the aerial photos and field sampling were applied to assess the image accuracy. A Conversion of Land Use and its Effect at Small Region Extent (CLUE-S) model was established to simulate the urbanization process at the township level in the North Xinjiang Economic Zone (NXEZ) of western China. Historical land use and land cover changes with multi-temporal remote sensing data were retrieved, and the underlying driving forces were explored by training the CLUE-S model. Moreover, future changes in urban development were simulated under different scenarios. Results showed that the overall accuracy reaches larger than 80% for the years of 2002, 2005, and 2007, and the corresponding kappa coefficient is bigger than 0.8. The NXEZ is at a premature development stage compared with urban clusters in eastern China. Before 1999, the driving force in this region was primary industry development. In recent years, secondary industries started to show significance in urbanization. These findings indicate that the industrial base and economic development in the NXEZ are still relatively weak and have not taken a strong leading role. When industry and population become the main driving factors, the regional economy will enter a new stage of leap-forward development, which in turn will stimulate a new round of rapid urbanization. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including digital terrain analysis and modeling, the definition of the third-order geomorphometric variables, and the expert knowledge-based approach to landslide susceptibility mapping.

With the increasing demand for accurate and reliable hydrological information, geo-spatial analysis plays a more and more important role in hydrological studies. The development of the geo-spatial technique advances our understanding of the complex and spatially heterogeneous hydrological systems. Meanwhile, how to efficiently and effectively process and analyze multi-source geo-spatial data has become more challenging in the fields of hydrology. In this editorial, we first review the development and application of geo-spatial analysis in three major topics in hydrological studies, namely the scaling issue, extraction of basin characteristics, and hydrological modelling. We hence introduce the articles of the Special Issue. These studies present the latest results of geo-spatial analysis in different topics in hydrology, and improve geo-spatial analytic methods for better accuracy and reliability. [ABSTRACT FROM AUTHOR]

Under climate change and increasing water demands, groundwater depletion has become regional and global threats for water security, which is an indispensable target to achieving sustainable developments of human society and ecosystems, especially in arid and semiarid regions where groundwater is a major water source. In this study, groundwater depletion of 2003–2016 over Xinjiang in China, a typical arid region of Central Asia, is assessed using the gravity recovery and climate experiment (GRACE) satellite and the global land data assimilation system (GLDAS) datasets. In the transition of a warm-dry to a warm-wet climate in Xinjiang, increases in precipitation, soil moisture and snow water equivalent are detected, while GRACE-based groundwater storage anomalies (GWSA) exhibit significant decreasing trends with rates between-3.61 ± 0.85 mm/a of CSR-GWSA and −3.10 ± 0.91 mm/a of JPL-GWSA. Groundwater depletion is more severe in autumn and winter. The decreases in GRACE-based GWSA are in a good agreement with the groundwater statistics collected from local authorities. However, at the same time, groundwater abstraction in Xinjiang doubled, and the water supplies get more dependent on groundwater. The magnitude of groundwater depletion is about that of annual groundwater abstraction, suggesting that scientific exploitation of groundwater is the key to ensure the sustainability of freshwater withdrawals and supplies. Furthermore, GWSA changes can be well estimated by the partial least square regression (PLSR) method based on inputs of climate data. Therefore, GRACE observations provide a feasible approach for local policy makers to monitor and forecast groundwater changes to control groundwater depletion. [ABSTRACT FROM AUTHOR]

I Toosi University of Technology i Jonathan Tan I University i I of Southern California i Guoan Tang I Nanjing i I Normal University i Jinjun Tang I Central i I South University i Wenwu Tang I University i I of North Carolina at Charlotte i Hakan Tanyas I University i I of Twente i Hu Tao I Harvard i I University i Ran Tao I University i I of South Florida i Simone Tarquini I Istituto i I Nazionale di Geofisica e Vulcanologia Sezione di Pisa, Pisa, Italy i Nicholas Tate I Leicester i I University i Malissa Taylor I University i I of Massachusetts Amherst i Hugo Teixeira I University i I of Porto i Sudeep Thakuri I Tribhuvan i I University i Jean-Claude Thill I University i I of North Carolina, Charlotte i Sabine Timpf I University i I of Augsburg i Giacomo Titti I Istituto i I di Ricerca per la Protezione Idrogeologica i Brian Todd I Natural i I Resources Canada, i I Dartmouth, i I NS, Canada i Eleni Tomai I National i I Technical University of Athens i Hrvoje Tomi'c I University i I of Zagreb i Daoqin Tong I University i I of Arizona i Agnieszka Trystula I University i I of Warmia i Ming-Hsiang Tsou I San i I Diego State University i Naru Tsutsumida I Kyoto i I University i Wei Tu I Shenzhen i I University i Lynn Usery I U.S i . I Toosi University of Technology i Jeff Allen I University i I of Toronto i Jesús Almendros-Jiménez I University i I of Almería i Massimiliano Alvioli I CNR i I - IRPI, Perugia, Italy i Jennings Anderson I University i I of Colorado Boulder i Paul Anderson I Texas i I A&M University i Taylor Anderson I George i I Mason University i Witold Andrzejewski I Poznan i I University of Technology i Francisco Ariza I University i I of Jaén i Sandra Arlinghaus I University i I of Michigan i Samantha Arundel I U.S i . [Extracted from the article]

Background: Hybridization capture-based targeted next generation sequencing (NGS) is gaining importance in routine cancer clinical practice. DNA library preparation is a fundamental step to produce high-quality sequencing data. Numerous unexpected, low variant allele frequency calls were observed in libraries using sonication fragmentation and enzymatic fragmentation. In this study, we investigated the characteristics of the artifact reads induced by sonication and enzymatic fragmentation. We also developed a bioinformatic algorithm to filter these sequencing errors. Results: We used pairwise comparisons of somatic single nucleotide variants (SNVs) and insertions and deletions (indels) of the same tumor DNA samples prepared using both ultrasonic and enzymatic fragmentation protocols. Our analysis revealed that the number of artifact variants was significantly greater in the samples generated using enzymatic fragmentation than using sonication. Most of the artifacts derived from the sonication-treated libraries were chimeric artifact reads containing both cis- and trans-inverted repeat sequences of the genomic DNA. In contrast, chimeric artifact reads of endonuclease-treated libraries contained palindromic sequences with mismatched bases. Based on these distinctive features, we proposed a mechanistic hypothesis model, PDSM (pairing of partial single strands derived from a similar molecule), by which these sequencing errors derive from ultrasonication and enzymatic fragmentation library preparation. We developed a bioinformatic algorithm to generate a custom mutation "blacklist" in the BED region to reduce errors in downstream analyses. Conclusions: We first proposed a mechanistic hypothesis model (PDSM) of sequencing errors caused by specific structures of inverted repeat sequences and palindromic sequences in the natural genome. This new hypothesis predicts the existence of chimeric reads that could not be explained by previous models, and provides a new direction for further improving NGS analysis accuracy. A bioinformatic algorithm, ArtifactsFinder, was developed and used to reduce the sequencing errors in libraries produced using sonication and enzymatic fragmentation. [ABSTRACT FROM AUTHOR]

Background: Most of the current progression of immune checkpoint inhibitors for malignant melanoma is based on data from Caucasians in Western countries, but the benefit of Chinese patients is limited, mainly due to different pathological subtypes. The patients in western countries are mainly skin melanoma (about 90%), while the acral and mucosal types are dominant in China, accounting for 41.8% and 22.6% respectively. Acral and mucosal melanoma have lower response rates to immunotherapy and chemotherapy. Objective: Whether immune checkpoint inhibitors can improve the survival of Chinese patients with malignant melanoma, therefore, we conducted a retrospective analysis. Methods: We analyzed 53 patients with metastatic melanoma treated in our hospital to evaluate the efficacy and safety of PD‐1 mAb in Chinese patients with metastatic melanoma, and performed univariate and multivariate analyses of prognostic factors that may affect overall survival (OS). Results: In a study of 125 patients with advanced malignant melanoma, 53 patients participated, with a median follow‐up of 16 months. Among these, 69.8% died, and 30.2% remained on treatment. Median progression‐free survival (PFS) was 6 months, and median OS was 19 months. Patients treated with immune checkpoint inhibitors had improved outcomes, with a median PFS of 7 months and a median OS of 24 months. Patients with bone metastasis and aberrant Lactate dehydrogenase (LDH) post‐treatment had worse prognoses, while immunotherapy was a protective factor. Subgroup analysis showed the benefits of immunotherapy across various patient characteristics. No unexpected toxicities were observed. Conclusion: The study highlights the efficacy of immune checkpoint inhibitors, particularly PD‐1 mAb, in improving survival outcomes for Chinese patients with metastatic melanoma. [ABSTRACT FROM AUTHOR]

A quarter finite element model of 3 mol% yttria stabilized tetragonal zirconia polycrystal (3Y-TZP) ceramics undergoing Vickers indentation was established to simulate the evolution of stress and the propagation of cracks inside a sample. The indentation experiment was carried out on the Micro Vickers Hardness Tester. The results of the geometric characteristic parameters, such as the indentation diagonal half-length a , the crack length c and the maximum indent depth h m , from the indentation simulation and experiment were similar. The types of indentation cracks under various loads were determined according to the Lawn-Evan model, which exactly correspond to the simulation results. In addition, the propagation of indentation cracks was discussed based on the maximum principal stress contour plots at various stages, and the conclusions were verified by the indentation analysis model proposed by Yoffe. As a result, the model developed in this paper can be used in indentation studies to solve the related problem. [ABSTRACT FROM AUTHOR]

Background: Mulberry (Morus spp.) is an economically important woody plant, which has been used for sericulture (silk farming) for thousands of years. The genetic background of mulberry is complex due to polyploidy and frequent hybridization events. Results: Comparative genomic in situ hybridization (cGISH) and self-GISH were performed to illustrate the chromosome constitution and genetic relationships of 40 mulberry accessions belonging to 12 species and three varietas in the Morus genus and containing eight different ploidy levels. We identified six homozygous cGISH signal patterns and one heterozygous cGISH signal pattern using four genomic DNA probes. Using cGISH and self-GISH data, we defined five mulberry sections (Notabilis, Nigra, Wittiorum, and Cathayana, all contained only one species; and Alba, which contained seven closely related species and three varietas, was further divided into two subsections) and proposed the genetic relationships among them. Differential cGISH signal patterns detected in section Alba allowed us to refine the genetic relationships among the closely related members of this section. Conclusions: We propose that GISH is an efficient tool to investigate the chromosome constitution and genetic relationships in mulberry. The results obtained here can be used to guide outbreeding of heterozygous perennial crops like mulberry. [ABSTRACT FROM AUTHOR]

Highlights • Variation patterns of turbidity index with aerosol size distributions, aerosol optical thickness, relative humidity and observing geometry, are investigated. • The effectiveness of the turbidity index for the NIR-SWIR ocean color atmospheric correction algorithm is tested using simulated aerosol reflectance and Aqua MODIS images. • Turbidity index does not work well as expected, and more effective switching scheme should be developed for the NIR-SWIR algorithm. Abstract Accurately removing atmospheric interferences and retrieving water-leaving reflectance are decisive for subsequent ocean color applications. Over turbid waters, the black pixel assumption at the near-infrared (NIR) spectral region does not hold, and shortwave infrared (SWIR)-based atmospheric correction algorithm should be applied. Turbidity index is proposed to detect turbid waters and worked as a criterion for NIR-SWIR combined algorithm. However, studies demonstrated that turbidity index did not work well as expected. This study, using simulated data and satellite images, aimed to revisit the effectiveness of turbidity index for the switching scheme of NIR-SWIR algorithm. The simulated data were obtained from aerosol look-up tables, and the Aqua MODIS images were used. The variations of turbidity index calculated from aerosol reflectance and Rayleigh-corrected reflectance were explored. Results showed that turbidity index did not obey the assumption that it should be close to one over clear waters with negligible NIR water-leaving reflectance; its value calculated from simulated aerosol reflectance ranged from 0.7 to 2.2; and the turbidity index values varied depending on fine-mode fraction, aerosol optical thickness, relative humidity and observing geometries. Therefore, more effective switching scheme should be developed for the NIR-SWIR combined atmospheric correction algorithm. [ABSTRACT FROM AUTHOR]

Climate models use quantitative methods to simulate the interactions of the important drivers of climate system, to reveal the corresponding physical mechanisms, and to project the future climate dynamics among atmosphere, oceans, land surface and ice, such as regional climate models and global climate models. A comprehensive assessment of these climate models is important to identify their different overall performances, such as the accuracy of the simulated temperature and precipitation against the observed field. However, until now, the comprehensive performances of these models have not been quantified by a comprehensive index except the existed single statistical index, such as correlation coefficient (r), absolute error (AE), and the root‐mean‐square error (RMSE). To address this issue, therefore, in this study, a new comprehensive index Distance between Indices of Simulation and Observation (DISO) is developed to describe the overall performances of different models against the observed field quantitatively. This new index DISO is a merge of different statistical metrics including r, AE, and RMSE according to the distance between the simulated model and observed field in a three‐dimension space coordinate system. From the relationship between AE, RMSE, and RMS difference (RMSD) (i.e., standard deviation [SD] of bias time series), the new index also has the information of RMSD which is the statistical index in Taylor diagram. An example is applied objectively to display the applications of DISO and Taylor diagram in identifying the overall performances of different simulated models. Overall, with the strong physical characteristic of the distance in three dimensional space and the strict mathematical proof, the new comprehensive index DISO can convey the performances among different models. It can be applied in the comparison between different model data and in tracking changes in their performances. [ABSTRACT FROM AUTHOR]