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The geological structure affects the occurrence of coalbed methane (CBM), and identifying its structural characteristic boundaries is significant for CBM development. Based on the 3# coal seam top elevation observation data of the South Shizhuang CBM district in Qinshui Basin, this study comprehensively used trend surface analysis, curvature analysis and multi-element overlay analysis to study the geological structure characteristics of this area and identify its geological structure boundaries. First of all, through the analysis of the fitting degree test and significance test, it was proved that the fourth-order trend surface can be better used to identify the geological structure characteristics in this area. On this basis, the geological structural units of the study area were identified on a regional scale, and the study area was divided into the northwest depression zone, the middle fold area and the eastern slope zone. Then, by using the contour curvature analysis method, the fold geological structure boundaries were identified on a local scale, and combined with the coal seam roof elevation model for optimization and adjustment, 73 fold structural boundaries were finally identified, including 37 anticlines and 36 synclines. The results showed that: (1) The fold structures of the 3# coal seam in the South Shizhuang CBM district are primarily wide and gentle secondary folds, with symmetrical wings and a roughly NNE trend. (2) The northwest depression zone is dominated by syncline structure. (3) In the middle fold zone, anticlines and synclines are evenly distributed. (4) The eastern slope zone is dominated by anticline structure and has small terrain fluctuations, making it a favourable area for CBM development. The identification results can provide a reference for the exploration, planning and development site selection of CBM resources in the study area. [ABSTRACT FROM AUTHOR]

Aggressive cultivation practised across the Indian subcontinent to meet the growing food demands results in the groundwater at many places being severely affected by salinity, and this is a recognised hazard of agricultural belts. Evaluating spatial variations of salinity hazards is important for managing agricultural activity and implementing suitable and timely remedial measures. A precise representation of spatial variations of groundwater salinity using electrical conductivity (EC) can help identify potential sources and evaluate their severity and spatial impact. Simple spatial interpolation schemes, viz., inverse distance weighted (IDW) and trend surface analysis (TSA) are evaluated with over 250 EC measurements in groundwater during two seasons from saline-impacted regions of northwest India. Considering the three performance metrics, namely, correlation coefficient, root mean square error and mean absolute error, IDW scheme was adjudged better than TSA for both seasons. Interpolation by TSA and contour plot using OriginLab® software resulted in unrealistic (negative) values of EC, whereas IDW was free from such limitations. Errors associated with IDW-based interpolated EC values for this site would be 320–415 μS/cm for pre-monsoon and 630–800 μS/cm during post-monsoon seasons. Refined EC map generated using seasonal IDW interpolation scheme would facilitate timely and cost-effective remediation of salinity hazard, impact assessment of point and non-point sources on salinity hazard. Research highlights: Simple algorithms were examined for spatial interpolation of groundwater EC; IDW was adjudged better over TSA. Seasonal influence on interpolation parameters for EC was highlighted. IDW parameters ascertained from systematic search in this study are different from reported default values in commercially available software. Whereas TSA or default interpolation with OriginLab® resulted in negative(unrealistic) EC values, IDW results were consistent. Refined EC map generated using seasonal IDW interpolation scheme would facilitate: timely and cost-effective remediation of salinity hazard; impact assessment of point and non-point sources on salinity hazard. [ABSTRACT FROM AUTHOR]

With the increase in global economic integration, high-quality economic development (HQED) has become a common goal of all countries. Based on these five development concepts, this paper uses the Gini coefficient, trend surface analysis, geographically weighted regression (GWR), the entropy weighting method, and standard deviation ellipse analysis to study the spatio-temporal pattern and driving mechanism of HQED in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). This paper examines the spatial and temporal patterns and driving mechanisms of HQED in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) based on five development concepts. The study revealed that (1) HQED is on the rise overall, but at the same time, it highlights the uneven development of multiple dimensions, especially in terms of significant differences in innovation, openness, and sharing. (2) HQED shows a clear center-periphery structure, with Guangzhou, Shenzhen, and Hong Kong as the core high-value areas; the growth rate of HQED capacity in the internal areas is significantly greater than that in the external areas, and HQED is prominent in the cities around Guangzhou, Shenzhen, and Hong Kong. (3) Factors such as agglomeration level, human capital, foreign investment, infrastructure development, financial and environmental protection expenditures, and financial inputs, and scientific, and technological inputs have a significant positive effect on HQED, and their interactions are further strengthened. This study reveals the importance of the realization of HQED in the GBA and the promotion of the overall development of the region.

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In order to gain a comprehensive understanding of land system changes and regional sustainable development, it is crucial to explore the spatiotemporal distributions of multiple land use functions (LUFs). Therefore, herein, considering the Yangtze River Delta urban agglomeration (YRDUA) as the research object, we constructed an evaluation system based on the perspective of production–living–ecological (PLE) land functions. Furthermore, the coupling coordination model, kernel density curve, trend surface analysis, and spatial autocorrelation model were used to examine the spatial and temporal characteristics of LUFs and their coupling coordination and analyze the spatial clustering of the coupling coordination effect in the urban agglomeration from 2005 to 2020. The following results were obtained: The level of PLE functions and its coupling coordination degree in the YRDUA have been improved in the study period, and the distribution of high value areas of different functions is diverse. In terms of the spatial distribution of the coupling coordination degree, the high value areas of production function (PF)–living function (LF) is distributed in "clusters", the PF–ecological function (EF) demonstrated a single-polarized development structure, and the LF-EF exhibited a multi-core structure. The coupling coordination of the LUFs demonstrated a "high in the east and low in the west" pattern in the east–west direction and an inverted "U" shape in the north–south direction. Moreover, both high-value and low-value areas exhibited a clustering phenomenon, with an evident spatial positive correlation. The results of this study can serve as a reference for the integrated socioeconomic development of the Yangtze River Delta region and the sustainable development of urban land use. [ABSTRACT FROM AUTHOR]

Interpolation parameters are the basic elements of an interpolation algorithm in terrain environmental modeling. Different interpolation parameters produce different interpolation precisions, and the differences can be substantial. They are divided into deterministic parameters and uncertainty parameters. The optimization of uncertainty interpolation parameters is studied in this article. First, the methods of cross-validation, correlation analysis, and trend surface analysis are systematically used to identify and determine the optimal interval of interpolation parameters, which is helpful to solve the “black box” problem of parameter selection. Second, the significance degree of different parameters on the interpolation accuracy is given by using analysis of variance, which indicated that the high influence parameters are more helpful to improve the accuracy. This is an innovative conclusion.

The main targets of this were to screen the factors that may influence the distribution of cholinesterase (CHE) reference value in healthy people, and further explored the geographical distribution differences of CHE reference value in China. In this study, we collected the CHE data of 17,601 healthy people from 173 cities in China to analyse the correlation between CHE and 22 geography secondary indexes through spearman regression analysis. Six indexes with significant correlation were extracted, and a ridge regression model was built, and the country's urban CHE reference value of healthy Chinese was predicted. By using the disjunctive kriging method, we obtained the geographical distribution of CHE reference values for healthy people in China. The reference value of CHE for healthy Chinese was significantly correlated with the 6 secondary indexes, namely, latitude (°), altitude (m), annual average temperature (°C), annual average relative humidity (%) and annual precipitation (mm), and topsoil sand gravel percentage (% wt). The geographical distribution of CHE values of healthy Chinese showed a trend of being higher in southeast China and lower in northwest. This study lays a foundation for further research on the mechanism of different influencing factors on the reference value of CHE index. A ridge regression model composed of significant influencing factors has been established to provide the basis for formulating reference criteria for the treatment factors of the liver damage diseases and liver cancer using CHE reference values in different regions. [ABSTRACT FROM AUTHOR]

The Bainiuchang Ag polymetallic deposit is located at the junction between the Cathaysia, Yangtze, China and Indosinian blocks. It has experienced many geological events, and records excellent conditions for multiple mineralization. In this paper, elemental correlation analysis, cluster analysis, factor analysis, a semivariogram of Zn/Pb values, mineralization distribution and trend surface analysis have been carried out based on the prospecting database and ore body model. Our results show that Ag–Pb–Zn were mineralized at moderate temperatures. Tin was mineralized at high temperatures, and Sn and Zn/Pb values are well correlated. The Zn/Pb values can be used for tracing the ore-forming fluid. The semivariogram revealed that the Zn/Pb values are moderately spatially dependent, with good mineralization continuity in the 100° and 10° directions. The spatial pattern of the elemental grade correlates with mineralization enrichment. The trend surface analysis shows that the Ag, Pb, Zn, and Cu mineralization is weak in the south and strong in the north of the deposit, and the Sn grades and Zn/Pb values are high in the south and low in the north. High-temperature Sn, medium-temperature Cu, and medium-temperature Ag–Pb–Zn mineralization have occurred in a south-to-north trend. Therefore, the source of the ore-forming fluid was in the southern part of the mining area. During the migration of the ore-forming fluid from south to north, different minerals were precipitated due to changes in the physicochemical environment. The spatial patterns of mineralization may provide a basis for studying the formation of the ore deposit, and can guide ore exploration and mining in the mine area and similar ore deposits elsewhere. [ABSTRACT FROM AUTHOR]

Understanding the biogeography of species in space and time is essential for the development of evidence‐based conservation and management plans. In this paper we propose a biogeographical spatial modelling approach based on the favourability function, and developed under a fuzzy logic framework, to unravel the historical biogeography of the two European wild rabbit subspecies, Oryctolagus cuniculus algirus (Oca) and Oryctolagus cuniculus cuniculus (Occ), in the Iberian Peninsula (IP).We first reviewed published and unpublished information (PhD theses, scientific papers, technical reports, etc.) on the occurrence of each rabbit subspecies throughout the IP. We compiled data from 201 Iberian rabbit populations and from genetic information of 4348 rabbits that was used to identify subspecies. Only populations in which all rabbits surveyed belonged to one subspecies were considered in the modelling procedure.We modelled rabbit subspecies' distribution separately for populations in which nuclear and mitochondrial DNA sequences were available. We employed a trend surface analysis developed by logistic regressions, which applied the favourability function and fuzzy logic operations.Using our approach we indentify the expansion cores from which both rabbit subspecies would have expanded after isolation during the last glaciations. Furthermore, we reveal the possible existence of a competitive exclusion zone between both rabbit subspecies that may have prevented their further expansion. Finally, our study shows that the Oca subspecies is distributed in north‐western areas previously attributed to Occ.This assessment of the actual and historical distribution of each rabbit subspecies may allow more specific conservation interventions, as the two subspecies are not just genetically distinct but also ecologically and behaviourally different. Our methodological approach could be useful in unravelling the historical biogeography of other lesser‐known species. [ABSTRACT FROM AUTHOR]

An origin-destination (OD) flow is the movement of objects from an origin to a destination. Determining how the flows vary across geographic locations helps understand the mechanism of flow distributions; however, it has rarely been studied. Here, we propose a trend surface model with polynomial functions to quantify the flow distribution with coordinates in the flow space. This model assumes that an observed data-record is composed of the trend value and the residual, and is represented by the orthogonal polynomial with O and D coordinates as independent variables and flow properties as dependent variables. The simulation experiments based on the linear and quadratic models indicated that the trend surface function could reflect the increasing/decreasing variation of flows with OD locations (i.e. flow trends) in different patterns. Applying this model to a case study of taxi OD flows in the broad Central Business District of Beijing, we found that the flows exhibited a rising trend toward the southwest. The trend surface characteristics are associated with the distributions of urban functional patches, where the workplaces and residences increased toward the southwest in the study area. Notably, the spatial deviations of trend surface model can help in identifying site pairs that attract flows at a high density (e.g. commerce centers and big communities), facilitating the planning of public transportation to mitigate the congestion. [ABSTRACT FROM AUTHOR]

Pervious concrete is a special type of concrete designed to allow water to pass through by omitting fine aggregates from the mix, or by using special techniques to create interconnected voids within the concrete. The current study investigates a novel method of cultivating calcium silicate hydrate (CSH) precipitates on a supplementary cementitious material (SCM), Rice husk ash (RHA), substrate and integrating the RHA substrate into pervious concrete to improve mechanical and durability properties. Scanning electron microscopy (SEM) images indicates the formation of precipitates of calcium silicate hydrates on the surface of RHA particles. The silica to RHA (Si/RHA) ratio and curing age of pervious concrete specimens serve as focal points for assessing the mechanical characteristics. Trend surface analysis is utilized to analyse the results, using a polynomial equation to identify underlying trends or patterns within the dataset. The analysis reveals that the Si/RHA ratio and curing days have minimal impact on permeability, while an increase in RHA substrate volume reduces permeability, indicating microstructure densification rather than macro void filling. For compressive strength, the results show that higher Si/RHA ratios and longer curing times positively correlate with strength, with accelerated hydration suggested by the quadratic coefficients of curing age. In terms of split tensile strength, increasing substrate volume enhances strength, while linear terms of Si/RHA ratio and curing age also exhibit positive correlations, although quadratic terms indicate minimal change in strength gain rates. Flexural strength correlates positively with both Si/RHA ratio and curing age, while abrasion resistance negatively correlates with Si/RHA ratio and substrate volume, suggesting enhanced resistance with increased values. CSH seeds grown on RHA enhances the microstructure of concrete, resulting in a denser material facilitating rapid strength development and improved durability. [Display omitted] • Increasing RHA substrate volume reduces permeability, indicating microstructure densification. • Silica to RHA ratio and curing days minimally affect permeability. • Higher Si/RHA ratios and longer curing times improve compressive strength. • Enhanced split tensile strength with increased substrate volume • Abrasion resistance improved with increased Si/RHA ratio and substrate volume [ABSTRACT FROM AUTHOR]

The channel multipath and non-line-of-sight (NLOS) reflections introduce a bias on the time difference of arrival (TDOA) observations, which reduce the accuracy of the ultra-wideband (UWB) positioning performance in an indoor environment. In previous research, the multipath map (MPM) method is based on spatial domain modeling principle in the reverse positioning framework and is used to mitigate the multipath effect. Utilizing the mean value of the multipath residuals as the calibration value will inevitably lead to insufficient or excessive multipath modification in the grid. By combining the trend surface analysis method, this paper proposes an advanced multipath mitigation method named trend surface analysis based multipath map (TMPM). Meanwhile, this paper propose an adaptive wavelet denoise (AWD) method in order to eliminate the noise of data set in advance. We mainly demonstrate the effect of TMPM in reverse positioning scenarios, analyze the multipath correction effect of TMPM. The experimental results show that the accuracy of the tag positioning is 16.0 cm with TMPM, which is improved by 22.7% compared to that of MPM. In dynamic positioning case, results with TMPM also show benefit over MPM. [ABSTRACT FROM AUTHOR]

The Bainiuchang Ag polymetallic deposit is located at the junction between the Cathaysia, Yangtze, China and Indosinian blocks. It has experienced many geological events, and records excellent conditions for multiple mineralization. In this paper, elemental correlation analysis, cluster analysis, factor analysis, a semivariogram of Zn/Pb values, mineralization distribution and trend surface analysis have been carried out based on the prospecting database and ore body model. Our results show that Ag–Pb–Zn were mineralized at moderate temperatures. Tin was mineralized at high temperatures, and Sn and Zn/Pb values are well correlated. The Zn/Pb values can be used for tracing the ore-forming fluid. The semivariogram revealed that the Zn/Pb values are moderately spatially dependent, with good mineralization continuity in the 100° and 10° directions. The spatial pattern of the elemental grade correlates with mineralization enrichment. The trend surface analysis shows that the Ag, Pb, Zn, and Cu mineralization is weak in the south and strong in the north of the deposit, and the Sn grades and Zn/Pb values are high in the south and low in the north. High-temperature Sn, medium-temperature Cu, and medium-temperature Ag–Pb–Zn mineralization have occurred in a south-to-north trend. Therefore, the source of the ore-forming fluid was in the southern part of the mining area. During the migration of the ore-forming fluid from south to north, different minerals were precipitated due to changes in the physicochemical environment. The spatial patterns of mineralization may provide a basis for studying the formation of the ore deposit, and can guide ore exploration and mining in the mine area and similar ore deposits elsewhere.

This work constructs an evaluation index system and quantitatively explores the coupling coordination relationship between the tourism development system and the medical services system in China. Results show that the degree of coupling coordination between the tourism development system and the medical services system showed a good upward trend in China during the period 2012–2019. However, the relationship was barely balanced, with tourism development lagging. The overall layout shows a spatial pattern of “high in the north and low in the south, high in the east and low in the west.” The degree of coupling coordination tends to be randomly distributed from clustered distribution, and the cold–hot spots show a spatial development pattern of “cold in the northwest and hot in the southeast” as time passes. The power of government to regulate has always been an important mechanism affecting the degree of coupling coordination. The study aims to provide reference for the rationalization of medical tourism layout and sustainable development.

The interaction between livelihood means and land use pattern of households is the core of the interactive coupling of the human-land system. This study focuses on Qinba mountainous area in southern Shaanxi province, a typical poverty-alleviated mountainous area. With the help of the coupling coordination degree model, kernel density estimation, and trend surface analysis, this study constructs the coupling coordination degree of livelihood efficiency and land use for households, and analyzes the differences between households' livelihood efficiency and land use level, as well as the coupling coordination relationship between households livelihood efficiency and land use in different types and regions. The research conclusions are as follows. (1) For households in the Qinba mountainous area, southern Shaanxi province, the livelihood efficiency is at a medium level of 0.681, the land use is at a low level of 0.127, while the coupling coordination degree 0.526 is at the primary coordination state. (2)With the increase of nonagricultural degree, the coupling coordination degree of households increases first, and then decreases. (3) The coupling coordination degree for households east-to-west is "sagging", while south-to-north diagram is "hogging". (4) The distribution of the coupling coordination degree for agriculture-dependent households east-to-west (the "sagging" diagram) is opposite to the other types of households. By analogy, the distribution of the coupling coordination degree for nonagriculture and agriculture-dependent households north-to-south (the "hogging" diagram) is opposite to the other types of households. The coupling coordination between the households' livelihood efficiency and land use level is affected by the households' regional development level, natural resources, geographic location, infrastructure availability and many other factors. Making appropriate livelihood development plans based on the types of households and regional space can both effectively improve the livelihood conditions, as well as offer guidance in promoting regional human-land activity coordination and ensuring sustainable development. [ABSTRACT FROM AUTHOR]

Groundwater is a precious source in arid and semi-arid regions of the world. Potentiometric level data show a non-stationary behavior due to the trend component. Consequently, it renders difficult to delineate groundwater-surface, i.e., spatial estimation. The staple objectives of this study are three-fold: (1) to diagnose trend component in potentiometric data by utilizing experimental semivariograms, (2) to model trend surface, (3) to remove trend component from groundwater elevation and demonstrate the effectiveness of the method by using experimental semivariograms of residuals. The study was conducted in the region of Mahdia, located in central-eastern Tunisia. Point-wisely scattered groundwater level data from 69 observation sites were used in the study. Data of the rainy period in 2008 and 2018 were utilized in order to elude negative anthropogenic impacts on potentiometric levels. Omnidirectional experimental semivariograms (OESs) were obtained from elevation data by using the minimum feasible lag interval. Experimental semivariograms helped us diagnose trend component, i.e., non-stationarity. Trend surface analysis was conducted through using the ANOVA technique. A very significant proportion of the variation in the observed data could be "explained" by a quadratic trend surface model. Comparing the partial cubic trend surface model with the quadratic one resulted in "statistically-not-significant" F value. Consequently, there was no real evidence that the partial cubic surface model was actually any better than the quadratic one. OESs of residuals indicated that the quadratic trend was effectively removed from the data. [ABSTRACT FROM AUTHOR]

With the increase in global economic integration, high-quality economic development (HQED) has become a common goal of all countries. Based on these five development concepts, this paper uses the Gini coefficient, trend surface analysis, geographically weighted regression (GWR), the entropy weighting method, and standard deviation ellipse analysis to study the spatio-temporal pattern and driving mechanism of HQED in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). This paper examines the spatial and temporal patterns and driving mechanisms of HQED in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) based on five development concepts. The study revealed that (1) HQED is on the rise overall, but at the same time, it highlights the uneven development of multiple dimensions, especially in terms of significant differences in innovation, openness, and sharing. (2) HQED shows a clear center-periphery structure, with Guangzhou, Shenzhen, and Hong Kong as the core high-value areas; the growth rate of HQED capacity in the internal areas is significantly greater than that in the external areas, and HQED is prominent in the cities around Guangzhou, Shenzhen, and Hong Kong. (3) Factors such as agglomeration level, human capital, foreign investment, infrastructure development, financial and environmental protection expenditures, and financial inputs, and scientific, and technological inputs have a significant positive effect on HQED, and their interactions are further strengthened. This study reveals the importance of the realization of HQED in the GBA and the promotion of the overall development of the region., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

This study retrospectively analyzed the spatio-temporal distribution and spatial clustering of scarlet fever in mainland China from 2004 to 2017. In recent years, the incidence of scarlet fever is increasing. Previous studies on the spatial distribution of scarlet fever in China are mainly focused at the provincial and municipal levels, and there is few systematic report on the spatial and temporal distribution characteristics of scarlet fever on the national level. Based on the incidence information of scarlet fever in mainland China between 2004 and 2017 collected from the China Center for Disease Control, this paper systematically explored the Spatio-temporal distribution of scarlet fever by three methods, contains spatial autocorrelation analysis, Spatio-temporal scanning analysis, and trend surface analysis. The results demonstrate that the incidence of scarlet fever varies by seasons, which is in line with double-peak distribution.The first peak generally occurs from May to June and the second one from November to December, while February and August is the lowest period of incidence. Trend surface analysis indicates that the incidence of scarlet fever in northern China is higher than the south, slightly higher in western compared to the east, and lower in the central part. Additionally, the results show that the clustering regions of scarlet fever centrally distributed in the northeast, northwest, north china and some provinces in the east, such as Zhejiang, Shanghai, Shandong, and Jiangsu.

We explored the variation and spatial distribution of the activated partial thromboplastin time (APTT) reference values of healthy people at different altitudes in China in order to develop a scientific basis for a unified standard. The APTT reference values of 49,020 healthy males (41–75 years old) and 32,447 healthy females (41–75 years old) were collected from 601 work units and 546 work units in China, respectively. The relationship between the APTT reference values and altitude was tested by correlation analysis. Linear regression analysis and curve analysis were employed to predict the APTT reference values in the whole country. Trend surface analysis, the variation function, kriging interpolation, and Getis-Ord Gi* statistic were utilized to reveal the spatial characteristics of the values. The result showed a significant positive correlation between the APTT reference values and altitude. The APTT values for females were prolonged for a greater amount of time than the males in several same areas in China. The spatial contact forms of the APTT reference values of healthy Chinese were mainly "high-high" and "low-low," which was in accord with the first law of geography. The APTT reference values still showed spatial autocorrelation and regional variation. The values were higher in the western and northern areas than in the eastern and southern areas of China. The APTT reference values of people aged 41–75 in China showed regional differences. The APTT reference values in one area can be estimated by using the best prediction model or can be obtained by the geographical distribution. [ABSTRACT FROM AUTHOR]

Trading area and market penetration maps are used extensively in retail chares for the evaluation of existing and potential retail locations Mapping procedures are many and vaned, but most depend upon rather a sample of consumers [1] or a measurement of store characteristics [8] for their input Procedures based upon the sampling of consumers are more direct, but their application has not proceeded far beyond the subjective blending of descriptive statistics and managerial intuition. Development of models based upon store characteristics is more advanced, but their empirical reliability is questionable.[2] Finally, there is the problem of statistical evaluation A visual analysis of the market penetration and trading area maps by management is still the best determinant of the success of the procedure. It is possible to have very different maps which have the same degree of statistical success by simply changing the trend surface model. The quadratic polynomial used here seems to work the best for single store locations Going to higher order polynomials usually results in only minor changes Evaluating multiple stores is more complex With multiple stores there are a number of viable models to choose from Outcomes of different models can be substantial. Results of the one store model so far are promising, but more is needed m both methodological development and empirical application before the proposed techniques can be extended to more complex situations. [ABSTRACT FROM AUTHOR]

Modeling complex geological interfaces is a common task in geosciences. Many data sources are available for geological interface modeling, including borehole data and geophysical surveys. Geological knowledge, such as the delineation from geologists, is difficult to quantify but likely adds value to geological interface modeling. To integrate all information, we present a data-knowledge-driven trend surface analysis method to construct stochastic geological interfaces. We design a Metropolis–Hastings sampling framework to sample stochastic trend interfaces and quantify the uncertainty of geological interfaces given all information sources. This method is suitable for both explicit and implicit representations of geological interfaces. We demonstrate our method in three different test cases: modeling stochastic interfaces of Greenland subglacial topography, magmatic intrusion, and buried river valleys in Australia. • This new trend surface analysis method integrates various data types and geological knowledge. • A Markov chain Monte Carlo sampler is used for explicit and implicit geological interfaces. • Stochastic geological interfaces are sampled in three studies: subglacial topography, magmatic intrusion, and palaeovalley modeling. [ABSTRACT FROM AUTHOR]

Abstract: Aim: To assess if geographical and/or environmental factors are driving skull morphology and genetic structure in the cosmopolitan bat species, Tadarida brasiliensis. Location: North, Central and South America, Greater and Lesser Antilles. Methods: We analysed morphometric, genetic and environmental data from the entire distribution of T. brasiliensis. Individuals were genotyped at nine nuclear loci, and clustering analyses were used to detect genetic groups and test correlations between genetic, geographical, and environmental distances. Museum specimens were photographed and 111 two‐dimensional landmarks were digitized per individual. Multivariate analyses were applied to explore whether factors such as sex, genetic group, subspecies, biogeographical regions, latitude, longitude and/or environment contribute to the morphometric variation of this species. We also applied a novel approach based on trend surface analyses and model selection to compare models of spatial and environmental dependence and to predict size, shape, and allometry‐free variation across the Americas. Results: Genetic and morphometric differences among populations coincide with major biogeographical and climatic breaks in Nearctic, Neotropical and Antillean regions. Trend surface analyses showed that skull size variation can be explained by spatial factors (latitude and longitude), whereas skull shape can be explained by the interaction of spatial and environmental factors. However, allometry‐free shape variation might respond to complex interactions not captured by our models. Main conclusion: Our explicit testing of spatial and environmental dependence using geostatistical model selection approaches allowed us to identify extrinsic factors that shape genetic and phenotypic responses in a cosmopolitan bat species. Our findings suggest that skull size is primarily driven by geographical factors (genetic drift), whereas shape variation is driven by adaptive responses to environmental conditions. [ABSTRACT FROM AUTHOR]

A quantitative interpretation of gravity and magnetic anomalies in west of Tikrit city and surroundings, has been completed utilizing Grav2dc and Mag2dc (2D, 2.5D) forward techniques. The modeling has been carried out along four profiles, two NW-SE profiles along the distinct gravity residual anomalies and two NE-SW profiles along the magnetic residual anomalies. The most geologic plausible model that matches the data was picked. The model along the gravity profile (A-A') reveal faulting of the basement, whereas along the profiles B-B', C-C' and D-D' did not present faulting. The models comprise of two rock units, the first is the sedimentary cover and the second unit is the basement rock. According to the results of modeling, thickness of the sedimentary cover and basement depth values are in good agreement with the results of previous studies. The upper part of sedimentary cover exhibited different density and susceptibility contrasts. These contrasts may be interpreted in term of lithological lateral variation. [ABSTRACT FROM AUTHOR]

We study the role of geography in R&D networks by means of a quantitative, micro-geographic approach. Using a large database that covers international R&D collaborations from 1984 to 2009, we localize each actor precisely in space through its latitude and longitude. This allows us to analyze the R&D network at all geographic scales simultaneously. Our empirical results show that despite the high importance of the city level, transnational R&D collaborations at large distances are much more frequent than expected from similar networks. This provides evidence for the ambiguity of distance in economic collaboration which is also suggested by the existing literature. In addition we test whether the hypothesis of local buzz and global pipelines applies to the observed R&D network by calculating well-defined metrics from network theory. [ABSTRACT FROM AUTHOR]

Spatial interpolation methods which are one of most commonly applied functions of Geographic information systems (GIS) provide prediction values for unmeasured coordinates. Reliability and robustness of all spatial interpolation methods depend on the total amount of data collected in the interested region. Obtaining such valuable spatial data may require a vast of amount time and budget. In some situations, institutions even competing ones may collect data from the same region. If data collected by such organizations can be integrated, they will have more accurate prediction models. However, they may not to share such valuable information with other institutions or companies due to privacy concern. Additionally, in some countries there are laws against sharing private data especially health and financial records. Therefore, a privacy-preserving solution which offers confidentiality of both parties’ data may induce them to collaborate. Furthermore, our solution protects the client’s privacy who requests predictions from such institutions. In this study, we propose a privacy-preserving Trend surface analysis method that provides privacy of both clients and data holders. In addition to this, our solution will produce more accurate and reliable predictions on combined data of two data holders without violating their privacy. We analyses our solution in terms of performance, privacy and accuracy. Although privacy-preserving solution may bring extra storage, computation and communication costs, we will present that they do not affect overall performance of the interpolation process. [ABSTRACT FROM AUTHOR]

The detection and attribution of long-term patterns in hydrological time series have been important research topics for decades. A significant portion of the literature regards such patterns as ‘deterministic components’ or ‘trends’ even though the complexity of hydrological systems does not allow easy deterministic explanations and attributions. Consequently, trend estimation techniques have been developed to make and justify statements about tendencies in the historical data, which are often used to predict future events. Testing trend hypothesis on observed time series is widespread in the hydro-meteorological literature mainly due to the interest in detecting consequences of human activities on the hydrological cycle. This analysis usually relies on the application of some null hypothesis significance tests (NHSTs) for slowly-varying and/or abrupt changes, such as Mann-Kendall, Pettitt, or similar, to summary statistics of hydrological time series (e.g., annual averages, maxima, minima, etc.). However, the reliability of this application has seldom been explored in detail. This paper discusses misuse, misinterpretation, and logical flaws of NHST for trends in the analysis of hydrological data from three different points of view: historic-logical, semantic-epistemological, and practical. Based on a review of NHST rationale, and basic statistical definitions of stationarity, nonstationarity, and ergodicity, we show that even if the empirical estimation of trends in hydrological time series is always feasible from a numerical point of view, it is uninformative and does not allow the inference of nonstationarity without assuming a priori additional information on the underlying stochastic process, according to deductive reasoning. This prevents the use of trend NHST outcomes to support nonstationary frequency analysis and modeling. We also show that the correlation structures characterizing hydrological time series might easily be underestimated, further compromising the attempt to draw conclusions about trends spanning the period of records. Moreover, even though adjusting procedures accounting for correlation have been developed, some of them are insufficient or are applied only to some tests, while some others are theoretically flawed but still widely applied. In particular, using 250 unimpacted stream flow time series across the conterminous United States (CONUS), we show that the test results can dramatically change if the sequences of annual values are reproduced starting from daily stream flow records, whose larger sizes enable a more reliable assessment of the correlation structures. [ABSTRACT FROM AUTHOR]

Karst reservoir has great hydrocarbon potential, however karst reservoir prediction is inhibited by the strong lateral and vertical heterogeneity of karstification which in turn results in recognition difficulty when geological and geophysical methods are used in isolation. Combined geological and geophysical methods, including core observation, thin section analysis, well log interpretation, seismic attributes and seismic inversion are applied to understand the depositional environment, types of karstification, the geophysical response and distribution of karst reservoir and the controls over and evolution model of karst reservoir in Permian Yuanba gas field, northern Sichuan Basin. The results show that there are four types of major seismic facies recognized in the study area, which correspond to platform margin reef, carbonate platform, platform margin inter-bay and platform margin slope. Karstification can be divided into three zones: the supergene karst zone, the vertical seepage zone and the horizontal underflow zone, among which the supergene karst zone have the strongest karstification. Karstification is highlighted with low seismic impedance, low Poisson's ratio, and high seismic attenuation on seismic inversion as well as micro scale paleo geomorphology recognized by trend surface analysis. By comparing the distribution of karstification with paleo geomorphology, fault distribution and gas contents, it can be observed that the karstification have a good matching relationship with these factors. The dominant type of karstification is epigenic karst, which is strongly influenced by depositional facies and paleo geomorphology. Fracture networks have contributed to karstification but are not the dominant factor of karst formation. The integration of geological and geophysical methods can predict karst reservoir with high accuracy within large area and can be applied to karst reservoir hydrocarbon exploration of similar geological setting. • Karst reservoir distribution is predicted in the NE Sichuan basin using an integrated geological and geophysical method. • Karstification is mainly represented by pores and fractures filled with large-grain calcite. Areas of high karstification observed in wells correlate strongly with areas of high attenuation in seismic data. • The primary type of karstification is epigenetic karst and is mainly controlled by paleo geomorphology and sedimentary facies. [ABSTRACT FROM AUTHOR]

The regional variation of the blood concentration of alanine aminotransferase (ALT), a sensitive predictor of liver damage, was studied in the People’s Republic of China with reference to its potential association with environmental variables and geographic location. The research results presented are based on 121,977 blood samples from healthy adults in 93 cities in the country using correlation analysis, ridge regression estimation and trend surface analysis that were applied to explore if there was any tendency of spatial variation. A regression formula using a simulation equation under the condition of known local geographic factors was used. Statistical significance was set at P

When striving for the ordination methods best predicting independently measured site factors, the following questions arise: does the optimal choice depend on the kind of biological community analysed? Are there different ordination methods needed to address different site factors? Simultaneously, I explore alternative similarity approaches of entire ordinations, as well as the role of the transformations applied to the scale used in measuring species performance. The combination of methods and data transformations results in 96 alternative solutions for any one data set. These are compared by a graphical display, that is, an ordination of ordinations. The goodness-of-fit of independently measured site factors is assessed by two alternative methods. The resulting 96 performance values serve as independent variables in trend surfaces overlaid to the ordination of ordinations. The results from two real-world data sets indicate that some ordination methods greatly vary with data transformation. Scores close to a binary scale perform best in almost all ordination methods. Methods that intrinsically constrain the range of species scores, such as principal components analysis based on correlation, correspondence analysis (including its detrended version), nonmetric multidimensional scaling, as well as principal coordinates analysis based on the Bray-Curtis distance, always figure among the most successful methods, irrespective of data used.

In sedimentary basin studies, gravity data are typically used to estimate the basement topography. Gravity inversion methods are expected to be able to discriminate between continuous and discontinuous sedimentary basins. Most 3D gravity inversion methods require intensive computational resources (computer memory and processing time). MDR3D, a variant of the well-known Bott method, was transformed into the Gauss-Newton inversion approach for extension flexibility. Integration of trend surface analysis (TSA) into the inversion scheme for regional anomaly estimation allows basement depth estimation from the Bouguer anomaly data. The aim of the additional total variation regularization is to stabilize the inversion algorithm and to achieve a geologically feasible model, especially for discontinuous basin types. Evaluation of the proposed method led to satisfactory results both for the synthetic and the field data set. It was found that the regularization parameter can improve the stability of the algorithm and also the depth estimation from noisy data up to ±0.5 mGal. [ABSTRACT FROM AUTHOR]

The investigation of the potential natural and anthropogenic contribution to atmospheric aerosol particles by using lichen-bag technique was performed in the Agri Valley (Basilicata region, southern Italy). This is an area of international concern since it houses one of the largest European on-shore reservoirs and the biggest oil/gas pre-treatment plant (i.e., Centro Olio Val d'Agri (COVA)) within an anthropized context. In particular, the concentrations of 17 trace elements (Al, Ca, Cd, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, P, Pb, S, Ti, and Zn) were measured in lichen bags exposed in 59 selected monitoring points over periods of 6 months (from October 2011 to April 2012) and 12 months (from October 2011 to October 2012). The general origin of the main air masses affecting the sampling site during the study period was assessed by the back trajectories clustering calculated using the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The results allowed the identification and characterization of the crustal material, smoke, sea salt, sulfate, and anthropogenic trace element contributions to the atmospheric aerosol particles in the study area. Finally, the application of the trend surface analysis (TSA) allowed the study of the spatial distribution of the considered contributions highlighting the existence of a continuous broad variation of these contributions in the area of interest. [ABSTRACT FROM AUTHOR]

Trend surface analysis is a geological term for a mathematical technique which separates a given map set into a regional component and a local component. This work has extended the steps for the derivation of the constants in the trend surface analysis equation from the popularly known matrix and simultaneous form to a more simplified and easily achievable format. To achieve this, matrix inversion was applied to the existing equations and the outcome was tested for suitability using a large volume of gravity data set acquired from the Anambra Basin, south-eastern Nigeria. Tabulation of the field data set was done using the Microsoft Excel spread sheet, while gravity maps were generated from the data set using Oasis Montaj software. A comparison of the residual gravity map produced using the new equations with its software derived counterpart has shown that the former has a higher enhancing capacity than the latter. This equation has shown strong suitability for application in the separation of gravity data sets into their regional and residual components. [ABSTRACT FROM AUTHOR]

The geomorphological understanding may lead to the evolution understanding and the processes that characterize the fluvial view at the Quaternary. Changes that happened in the fluvial systems are registered at the terraces and fluvial areas. In this way, the confluence stretch of theBrancoandGranderivers has paleochannels, abandoned meanders and lakes that denote the evolution of both channels. Therefore, this study aims to understand how these geomorphologies are placed in the area using as a resource provided by the remote sensing. It was used then the Shuttle Radar Topography Mission image in order to apply the trend surface model, which shows the light flotation of the area, in other words, positive values – high spots in the relief, and negative values – low spots. Through this observation, it was possible to identify the terraces and the areas of the low plain. The results were also described by the morphostratigraphic analysis that is important in order to validate the data applied by the geoprocessing analysis. Besides, the data inferred in the elaboration of a morphologies base chat placed in the fluvial portion. [ABSTRACT FROM PUBLISHER]