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It is well known that most of the cadastral maps and property plans in Iraq are preserved in paper form, with the majority dating back to the 1930s. These maps are widely used for various purposes, such as urban planning, sewage networks, and electricity networks. However, most of these maps suffer from some distortion and wear, with some being torn and taped due to the nature of the paper material and its handling, resulting in severe physical distortion. To address these issues, it is necessary to convert these maps into a digital format and perform corrective processing to mitigate the effects of past errors. Scanning alone is insufficient as it introduces many errors. Recently, fast and accurate computer software has become available that can process data from these maps and paper drawings, including addressing the wear they have undergone, and update them to meet the needs of local authorities developing and investing in these maps and implementing development projects. This process is also essential for establishing a digital foundation for the database. Geographic Information System (GIS) applications are widely used to enhance and assist decision-makers in making decisions that align with their purposes and application scenarios. [ABSTRACT FROM AUTHOR]

Design randomizations and spatial corrections have increased understanding of genotypic, spatial, and residual effects in field experiments, but precisely measuring spatial heterogeneity in the field remains a challenge. To this end, our study evaluated approaches to improve spatial modeling using high-throughput phenotypes (HTP) via unoccupied aerial vehicle (UAV) imagery. The normalized difference vegetation index was measured by a multispectral MicaSense camera and processed using ImageBreed. Contrasting to baseline agronomic trait spatial correction and a baseline multitrait model, a two-stage approach was proposed. Using longitudinal normalized difference vegetation index data, plot level permanent environment effects estimated spatial patterns in the field throughout the growing season. Normalized difference vegetation index permanent environment were separated from additive genetic effects using 2D spline, separable autoregressive models, or random regression models. The Permanent environment were leveraged within agronomic trait genomic best linear unbiased prediction either modeling an empirical covariance for random effects, or by modeling fixed effects as an average of permanent environment across time or split among three growth phases. Modeling approaches were tested using simulation data and Genomes-to-Fields hybrid maize (Zea mays L.) field experiments in 2015, 2017, 2019, and 2020 for grain yield, grain moisture, and ear height. The two-stage approach improved heritability, model fit, and genotypic effect estimation compared to baseline models. Electrical conductance and elevation from a 2019 soil survey significantly improved model fit, while 2D spline permanent environment were most strongly correlated with the soil parameters. Simulation of field effects demonstrated improved specificity for random regression models. In summary, the use of longitudinal normalized difference vegetation index measurements increased experimental accuracy and understanding of field spatio-temporal heterogeneity. [ABSTRACT FROM AUTHOR]

With rapid economic development, the size of urban land in China is expanding dramatically. The Urban Growth Boundary (UGB) is an expandable spatial boundary for urban construction in a certain period in order to control the urban sprawl. Reasonable delineation of UGB can inhibit the disorderly spread of urban space and guide the normal development of the city. It is of practical significance for the construction of green urban space. The study utilizes GIS technology to establish a land construction suitability evaluation system for Nankang city, which is experiencing rapid urban expansion, and outlines the preliminary UGB under the future land use simulation (FLUS) model. At the same time, considering the coupled coordination of "Production-Living-Ecological Space", and based on the suitability evaluation, we revised the preliminary UGB by combining the advantages of the patch-generating land use simulation (PLUS) model and the convex hull model to delineate the final UGB. The results show that: 1) the comprehensive score of the evaluation of the suitability of the construction of land from high to low shows the distribution of the center of the city to the surrounding circle type spread, the center of the city has the highest suitability score. The results of convex hull model show that the urban expansion type of Nankang is epitaxial. In the future, the urban expansion will mainly occur in the northern part of the city. The PLUS model predicts an increase of 3359.97 hm2 of construction land in Nankang by 2035, of which 2022.97 hm2 is urban construction land. 2) The FLUS model has a prediction accuracy of 86.3% and delineates a preliminary UGB area of 9215.07 hm2. 3) We used the results of the construction suitability evaluation, PLUS model simulation results, and convex hull model predictions to revise the originally delineated UGB. The final delineated UGB area is 8895.67 hm2 and it is capable of meeting the future development of the study area. The results of the delineation can promote sustainable urban development, and the delineation methodology can provide a reference basis for the preparation of territorial spatial planning. [ABSTRACT FROM AUTHOR]

Premise: Digitized biodiversity data offer extensive information; however, obtaining and processing biodiversity data can be daunting. Complexities arise during data cleaning, such as identifying and removing problematic records. To address these issues, we created the R package Geographic And Taxonomic Occurrence R‐based Scrubbing (gatoRs). Methods and Results: The gatoRs workflow includes functions that streamline downloading records from the Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio). We also created functions to clean downloaded specimen records. Unlike previous R packages, gatoRs accounts for differences in download structure between GBIF and iDigBio and allows for user control via interactive cleaning steps. Conclusions: Our pipeline enables the scientific community to process biodiversity data efficiently and is accessible to the R coding novice. We anticipate that gatoRs will be useful for both established and beginning users. Furthermore, we expect our package will facilitate the introduction of biodiversity‐related concepts into the classroom via the use of herbarium specimens. [ABSTRACT FROM AUTHOR]

The ecosystem services in an area are quite dependent on its ambient land use and land cover (LULC) attributes. Here we assess the spatio-temporal distribution of Ecosystem Services Value (ESV) for the years 1990, 2000, 2010, 2020, based on the then existing LULC aspects of the Kolkata Urban Agglomeration in eastern India. Further, these are simulated for 2030, 2040 and 2050 to determine the future potential ESV. The respective LULC layers were extracted from Landsat images using the support vector machine method and future projections were done using Markov Chain-Cellular Automata models. Results reveal that all LULC aspects are likely to significantly decrease except built-up tracts. The available ESV shall concomitantly decline by 29.7%, especially due to wetland loss. The ESV patterns also showed strong spatial correlation/clustering, with higher ESV patches locating along rivers/wetlands. These results can better inform management of high-value EVS components for sustaining/improving the urban environmental quality. [ABSTRACT FROM AUTHOR]

Faster-than-Nyquist (FTN) technology can improve the spectral efficiency of Optical Wireless Communications (OWC). However, it is affected by the artistically introduced Inter-Symbol Interference (ISI) and atmospheric turbulence, which leads to the degradation of BR Error Rate (BER) performance. To deal with this issue, a PAM modulated Multiple In¬put Multiple Output (MIMO)-FTN-OWC system is proposed, and MIMO technology is utilized to suppress the influence of atmospheric turbulence. Furthermore, the theoretical BER in log-normal fading channel Is deduced, and the influence of chan¬nel correlation on the BER performance Is analyzed. The simulation results show that the BER performance of 2 X 2 MIMO- FTN system is 9. 5 dB higher than that of SingC-Input SingC-Output (SISO)-FTN system when BER is 10-4. In addition, the MIMO-FTN system has better BER performance than that of SISO-FTN system when the channel spatial correction coeffi¬cient is lower than 0. 6. [ABSTRACT FROM AUTHOR]

The context for this article is the statistical fusion of several pollutant measurement networks: a reference one of fixed sensors of high quality and others of fixed or mobile micro‐sensors of heterogeneous quality. The challenge is to use together the measurements of such different networks to obtain a better air quality map. Since pollution maps are often obtained from the correction of numerical model outputs by the measurements provided by the monitoring stations of air quality networks, the quality of the reconstructed map may be improved by increasing the density of sensors by adding low‐cost micro‐sensors. A geostatistical approach is very often used for the fusion of measurements. But the first step is to correct micro‐sensors measures using those given by the reference sensors. Usually, this preprocessing is performed during an offline preliminary study for which reference and micro‐sensor are located at the same position, which does not allow to adapt quickly to changes and to cope with time‐related nonstationarities. We propose in this article to complement these approaches by a simple online spatial correction of micro‐sensors. The principle is to use the reference measurements to correct the network of micro‐sensors. More precisely, by kriging only the measurements from micro‐sensors, the reference measurements are estimated; allowing to calculate a correction by kriging the differences, finally applied to the micro‐sensors. Then one can iterate this fundamental sequence of steps. Numerical experiments exploring the proposed algorithm by simulation and an application to a real‐world dataset are provided. [ABSTRACT FROM AUTHOR]

Controlling spatial variation in agricultural field trials is the most important step to compare treatments efficiently and accurately. Spatial variability can be controlled at the experimental design level with the assignment of treatments to experimental units and at the modeling level with the use of spatial corrections and other modeling strategies. The goal of this study was to compare the efficiency of methods used to control spatial variation in a wide range of scenarios using a simulation approach based on real wheat data. Specifically, classic and spatial experimental designs with and without a two-dimensional autoregressive spatial correction were evaluated in scenarios that include differing experimental unit sizes, experiment sizes, relationships among genotypes, genotype by environment interaction levels, and trait heritabilities. Fully replicated designs outperformed partially and unreplicated designs in terms of accuracy; the alpha-lattice incomplete block design was best in all scenarios of the medium-sized experiments. However, in terms of response to selection, partially replicated experiments that evaluate large population sizes were superior in most scenarios. The AR1 × AR1 spatial correction had little benefit in most scenarios except for the medium-sized experiments with the largest experimental unit size and low GE. Overall, the results from this study provide a guide to researchers designing and analyzing large field experiments. Supplementary materials accompanying this paper appear online. [ABSTRACT FROM AUTHOR]

Canopy temperature (CT) has been related to water-use and yield formation in crops. However, constantly (e.g., sun illumination angle, ambient temperature) as well as rapidly (e.g., clouds) changing environmental conditions make it difficult to compare measurements taken even at short time intervals. This poses a great challenge for high-throughput field phenotyping (HTFP). The aim of this study was to i) set up a workflow for unmanned aerial vehicles (UAV) based HTFP of CT, ii) investigate different data processing procedures to combine information from multiple images into orthomosaics, iii) investigate the repeatability of the resulting CT by means of heritability, and iv) investigate the optimal timing for thermography measurements. Additionally, the approach was v) compared with other methods for HTFP of CT. The study was carried out in a winter wheat field trial with 354 genotypes planted in two replications in a temperate climate, where a UAV captured CT in a time series of 24 flights during 6 weeks of the grain-filling phase. Custom-made thermal ground control points enabled accurate georeferencing of the data. The generated thermal orthomosaics had a high spatial accuracy (mean ground sampling distance of 5.03 cm/pixel) and position accuracy [mean root-mean-square deviation (RMSE) = 4.79 cm] over all time points. An analysis on the impact of the measurement geometry revealed a gradient of apparent CT in parallel to the principle plane of the sun and a hotspot around nadir. Averaging information from all available images (and all measurement geometries) for an area of interest provided the best results by means of heritability. Correcting for spatial in-field heterogeneity as well as slight environmental changes during the measurements were performed with the R package SpATS. CT heritability ranged from 0.36 to 0.74. Highest heritability values were found in the early afternoon. Since senescence was found to influence the results, it is recommended to measure CT in wheat after flowering and before the onset of senescence. Overall, low-altitude and high-resolution remote sensing proved suitable to assess the CT of crop genotypes in a large number of small field plots as is required in crop breeding and variety testing experiments.

Canopy temperature (CT) has been related to water-use and yield formation in crops. However, constantly (e.g., sun illumination angle, ambient temperature) as well as rapidly (e.g., clouds) changing environmental conditions make it difficult to compare measurements taken even at short time intervals. This poses a great challenge for high-throughput field phenotyping (HTFP). The aim of this study was to i) set up a workflow for unmanned aerial vehicles (UAV) based HTFP of CT, ii) investigate different data processing procedures to combine information from multiple images into orthomosaics, iii) investigate the repeatability of the resulting CT by means of heritability, and iv) investigate the optimal timing for thermography measurements. Additionally, the approach was v) compared with other methods for HTFP of CT. The study was carried out in a winter wheat field trial with 354 genotypes planted in two replications in a temperate climate, where a UAV captured CT in a time series of 24 flights during 6 weeks of the grain-filling phase. Custom-made thermal ground control points enabled accurate georeferencing of the data. The generated thermal orthomosaics had a high spatial accuracy (mean ground sampling distance of 5.03 cm/pixel) and position accuracy [mean root-mean-square deviation (RMSE) = 4.79 cm] over all time points. An analysis on the impact of the measurement geometry revealed a gradient of apparent CT in parallel to the principle plane of the sun and a hotspot around nadir. Averaging information from all available images (and all measurement geometries) for an area of interest provided the best results by means of heritability. Correcting for spatial in-field heterogeneity as well as slight environmental changes during the measurements were performed with the R package SpATS. CT heritability ranged from 0.36 to 0.74. Highest heritability values were found in the early afternoon. Since senescence was found to influence the results, it is recommended to measure CT in wheat after flowering and before the onset of senescence. Overall, low-altitude and high-resolution remote sensing proved suitable to assess the CT of crop genotypes in a large number of small field plots as is required in crop breeding and variety testing experiments. [ABSTRACT FROM AUTHOR]

Reactimeter algorithms enable real-time evaluation of the reactivity of a near-critical reactor from the signal of a neutron detector. They only depend on a few parameters defined by the inverse point kinetic equations, and which can be calculated by most neutron transport codes. However, the neutron population measured locally by a detector may not always lead to a good estimate of the reactivity. For example, this would be the case for an in-core detector placed just next to a moving control rod. In such special cases – or when measurement precision is an issue – costly simulations are needed to provide correction factors that account for variations in the spatial distribution of the neutron flux. This paper aims to provide an auto-corrected reactimeter algorithm (ACRA) in the special cases where rapid perturbations are applied to a core close to criticality. Such perturbations were successfully performed in the MINERVE reactor using a dedicated control rod to alternatively insert and withdraw a small sample of material under study. ACRA has been validated against 3D Monte Carlo neutron transport calculations using the signals of four in-core detectors located just next to the moving sample. • An Auto-Corrected Reactimeter Algorithm was developed and successfully validated. • The validation process using experimental data yielded conclusive results. • The precision of the algorithm for the experiments studied was limited to 1. 2 × 1 0 − 3 due to noise. [ABSTRACT FROM AUTHOR]

Recognizing changes in ecosystem services (ES) and their relationships is the basis of achieving sustainable regional development. Regional collaborative development has become the core strategy of the development of the Beijing--Tianjin--Hebei (BTH) region. However, sub regions have different ecological changes and relationships. Here, we quantify and map ES, including water yield, sediment retention, carbon sequestration and grain productive capacity in 2000, 2005, 2010 and 2015, using several biophysical models and explore the relationships of spatial correction, trade-offs and synergies among multiple ES in different spatial scales. Results across the four years show that the quality and variation tendency of ES from each region are spatially heterogeneous. The relationship between ES that are not significant in the entire region shows different correlations in individual ecological--functional zones. From the perspective of regional disparity, the effect of land use factor and correlative mechanisms among ES are analyzed. To observe the spatiotemporal variations and relationships of ES in individual regions, land use management policies are proposed on the basis of the results of the relationships among ES. [ABSTRACT FROM AUTHOR]

There are various applied electro-optical devices, which utilize light emitting didoe (LED) chip array for applications to displays and opto-electronic sensors. In those devices, it is the one of the critical technical issues to minimize uncertain fluctuations including optical power and optical density. Due to variation in operating environment of a device, those are not corrected precisely by controlling parameters based on simple relation between parameters and resultant abovementioned outputs. Therefore, there is essential need to correct outputs in real-time based on correction function generated from the consideration on various operation condition. In this article, we introduce an output correction method through reporting real-time image noise reduction in the application to electro-photography with LED print head. In the technology of LED print head, as differences in optical characteristics between each LED cause vertical image noise, it should be corrected in order to obtain images that are comparable or better in quality compared to those produced by the conventional laser scanning method. Even though it seems that the method used to obtain uniform light power from each LED can solve this problem, it does not work well for high-resolution printing. Therefore, a scan method involving correction by a printed and scanned pattern is introduced through this work. The scan method is composed of correction patterns to minimize printing noise by its shape, the correction algorithm to calculate the optimized value and the printing algorithm to control gray levels in real-time precisely. We believe that the developed correction method upgrades the printing quality of the LPH printer better than commercial printers. The developed correction method can also be applied to various application areas that use an array-type light source such as display systems and lighting systems. [ABSTRACT FROM AUTHOR]

Introduction. Supracondylar fractures of the humerus represent a current concern in the child's and adolescent's osteo-articular pathology. Even though orthopedic reductions are made correctly, fractures can become displaced when managed only by cast immobilization and complications may arise. The most frequent complications encountered in "Prof. Dr. Alexandru Pesamosca" Clinique, Bucharest, Romania, due to supracondylar humeral fractures, are valgus or varus deviations with angles that can sometimes exceed 40 degrees as a result of malunion. Varus or valgus deformations were rarely encountered after surgical treatment. The goal of this study is to present an alternative surgical technique to correct varus and valgus deformations as well as malrotation. Material and method. The study is a retrospective analysis of a 96 children study group surgically managed during 1985 and 2013. In the first period, various surgical techniques have been performed: cuneiform resections, step-cut osteotomies, open wedge osteotomies with external fixation, epiphysiodesis, hemichondrodiatasis and Pesamosca metaphyseal diaphyseal osteoplasty. Starting with 2005, all the cases that presented such complications - 28 out of 96 (29.1%) - were managed with the Pesamosca procedure. Due to the malunion of supracondylar humeral fractures only varus or valgus deformities were admitted in the study. The malunion due to the pathologic fractures encountered in osteogenesis imperfecta or fibrous dysplasia was precluded. The experience accumulated with the other surgical techniques used in 68 out of 96 patients (70.9%) determined us to exclusively use the Pesamosca osteoplasty following the year 2005, seeing the simplicity and the efficiency of this procedure. Results. The outcome was very good. In 5 cases out of the 28 (17%) an apparent residual elbow was encountered and one case of relapse (3%) was noted due to inadequate term of cast immobilization. The elbow's mobility was completely recovered, the thoracic member's axis was appropriate and the metaphyseal diaphyseal osteotomy site healed completely in 3 months' time. Conclusions. Compared to other surgical techniques, the Pesamosca technique offers to the surgeon the possibility of correcting the varus or the valgus deformity as well as the malrotation in a simple, secure and efficient manner. [ABSTRACT FROM AUTHOR]

The spread of citrus canker has become one of the most important challenges faced by Florida Fresh Market citrus is affecting the export of citrus fruits to several international markets including European countries. Previous studies have shown that automated detection systems can help detect citrus canker infected fruit and could assist in eliminating the detected fruit from shipment to closed markets. Most automated detection systems use some form of machine vision with artificial light sources. However, when capturing images of spherical objects, non-uniform illumination results in an edge blackening effect resulting in higher misclassification rate. The basic objective of this research was to implement a compensation algorithm to eliminate the edge effect when capturing hyperspectral image of citrus fruits. The algorithm originally developed by Gomez et al. 2007, was adapted for the purpose of canker detection. The image was corrected for spatial variations (flat field correction) caused by intensity of light source as well as geometrical variation caused by the spherical geometry of the citrus fruit. In this study, the geometric correction was accomplished by constructing a 3-D digital elevation model (DEM) of the fruit from its 2-D image. This DEM provided the geometric properties of the fruit X, Y, and Z coordinates which were exploited in the course of estimating the geometric correction factor for each pixel. The corrected image portrayed a more uniform brightness of the citrus fruit surface throughout. Tests were conducted on 10 orange samples (five marketable and five cankerous) to validate the results of the algorithm which demonstrated that the geometric correction resulted in uniform intensity of radiation throughout the fruit surface thus reducing the within class variation. [ABSTRACT FROM AUTHOR]

In crop breeding, the interest of predicting the performance of candidate cultivars in the field has increased due to recent advances in molecular breeding technologies. However, the complexity of the wheat genome presents some challenges for applying new technologies in molecular marker identification with next-generation sequencing. We applied genotyping-by-sequencing, a recently developed method to identify single-nucleotide polymorphisms, in the genomes of 384 wheat (Triticum aestivum) genotypes that were field tested under three different water regimes in Mediterranean climatic conditions: rain-fed only, mild water stress, and fully irrigated. We identified 102,324 single-nucleotide polymorphisms in these genotypes, and the phenotypic data were used to train and test genomic selection models intended to predict yield, thousand-kernel weight, number of kernels per spike, and heading date. Phenotypic data showed marked spatial variation. Therefore, different models were tested to correct the trends observed in the field. A mixed-model using moving-means as a covariate was found to best fit the data. When we applied the genomic selection models, the accuracy of predicted traits increased with spatial adjustment. Multiple genomic selection models were tested, and a Gaussian kernel model was determined to give the highest accuracy. The best predictions between environments were obtained when data from different years were used to train the model. Our results confirm that genotyping-by-sequencing is an effective tool to obtain genome-wide information for crops with complex genomes, that these data are efficient for predicting traits, and that correction of spatial variation is a crucial ingredient to increase prediction accuracy in genomic selection models.