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Several global high-resolution built-up surface products have emerged over the last five years, taking full advantage of open sources of satellite data such as Landsat and Sentinel. However, these data sets require validation that is independent of the producers of these products. To fill this gap, we designed a validation sample set of 50 K locations using a stratified sampling approach independent of any existing global built-up surface products. We launched a crowdsourcing campaign using Geo-Wiki (https://www.geo-wiki.org/) to visually interpret this sample set for built-up surfaces using very high-resolution satellite images as a source of reference data for labelling the samples, with a minimum of five validations per sample location. Data were collected for 10 m sub-pixels in an 80 × 80 m grid to allow for geo-registration errors as well as the application of different validation modes including exact pixel matching to majority or percentage agreement. The data set presented in this paper is suitable for the validation and inter-comparison of multiple products of built-up areas.

Several global high-resolution built-up surface products have emerged over the last five years, taking full advantage of open sources of satellite data such as Landsat and Sentinel. However, these data sets require validation that is independent of the producers of these products. To fill this gap, we designed a validation sample set of 50 K locations using a stratified sampling approach independent of any existing global built-up surface products. We launched a crowdsourcing campaign using Geo-Wiki (https://www.geo-wiki.org/) to visually interpret this sample set for built-up surfaces using very high-resolution satellite images as a source of reference data for labelling the samples, with a minimum of five validations per sample location. Data were collected for 10 m sub-pixels in an 80 × 80 m grid to allow for geo-registration errors as well as the application of different validation modes including exact pixel matching to majority or percentage agreement. The data set presented in this paper is suitable for the validation and inter-comparison of multiple products of built-up areas.

Several global high-resolution built-up surface products have emerged over the last five years, taking full advantage of open sources of satellite data such as Landsat and Sentinel. However, these data sets require validation that is independent of the producers of these products. To fill this gap, we designed a validation sample set of 50 K locations using a stratified sampling approach independent of any existing global built-up surface products. We launched a crowdsourcing campaign using Geo-Wiki (https://www.geo-wiki.org/) to visually interpret this sample set for built-up surfaces using very high-resolution satellite images as a source of reference data for labelling the samples, with a minimum of five validations per sample location. Data were collected for 10 m sub-pixels in an 80 × 80 m grid to allow for geo-registration errors as well as the application of different validation modes including exact pixel matching to majority or percentage agreement. The data set presented in this paper is suitable for the validation and inter-comparison of multiple products of built-up areas.

This collection contains data that were collected during a crowdsourcing campaign using Geo-Wiki (https://www.geo-wiki.org/). The campaign involved visual interpretation of a sample that is designed for validating any existing global built-up surface product. A zipped shapefile (ValidationGrids.zip) contains the random stratified sample of 50K locations, which consist of 80x80m grids further sub-divided into 10m cells so there are 64 cells per grid. These locations were provided to the crowd, who used very high-resolution satellite images to label the grids as built-up (i.e., containing a building), non-built-up or unsure. The file (Geo-WikiBuilt-upCentroidsAll.csv) contains the data collected in the campaign summarized by the centroid (or central point of each 80m grid location). It also contains fields for quality control, one that indicates if the change information matches the control points (see below) or the majority answer from the crowd, and another that indicates whether the presence/absence of built-up matches the control points (see below) or the majority answer from the crowd. The data collected for all 64 cells per grid can be found in Geo-WikiBuilt-upCellsAll.csv. The Geo-Wiki campaign uses visually interpreted grid locations called control points as part of the scoring mechanism of Geo-Wiki for quality control. These control points are provided by centroid (Geo-WikiBuilt-upCentroidsControls.csv) and for all cells in the 80m grid (Geo-WikiBuilt-upCellsControls.csv). In addition to the raw data, two additional quality-controlled files have been produced. The first file (Geo-WikiBuilt-upCentroidsChangeQualityControlled.csv) provides a single record for each location on change in built-up (if built-up is present) that lists either the control point answer or the majority answer from the crowd. The second file (Geo-WikiBuilt-upCellsQualityControlled.csv) contains a single record for each of the 64 cells in each grid, listing either the control point answer

This collection contains data that were collected during a crowdsourcing campaign using Geo-Wiki (https://www.geo-wiki.org/). The campaign involved visual interpretation of a sample that is designed for validating any existing global built-up surface product. A zipped shapefile (ValidationGrids.zip) contains the random stratified sample of 50K locations, which consist of 80x80m grids further sub-divided into 10m cells so there are 64 cells per grid. These locations were provided to the crowd, who used very high-resolution satellite images to label the grids as built-up (i.e., containing a building), non-built-up or unsure. The file (Geo-WikiBuilt-upCentroidsAll.csv) contains the data collected in the campaign summarized by the centroid (or central point of each 80m grid location). The data collected for all 64 cells per grid can be found in Geo-WikiBuilt-upCellsAll.csv. The Geo-Wiki campaign uses visually interpreted grid locations called control points as part of the scoring mechanism of Geo-Wiki for quality control. These control points are provided by centroid (Geo-WikiBuilt-upCentroidsControls.csv) and for all cells in the 80m grid (Geo-WikiBuilt-upCellsControls.csv). Finally, the file Strata.csv contains the mapping between the grid location and the sampling stratum used in the design of the sample.

This collection contains data that were collected during a crowdsourcing campaign using Geo-Wiki (https://www.geo-wiki.org/). The campaign involved visual interpretation of a sample that is designed for validating any existing global built-up surface product. A zipped shapefile (ValidationGrids.zip) contains the random stratified sample of 50K locations, which consist of 80x80m grids further sub-divided into 10m cells so there are 64 cells per grid. These locations were provided to the crowd, who used very high-resolution satellite images to label the grids as built-up (i.e., containing a building), non-built-up or unsure. The file (Geo-WikiBuilt-upCentroidsAll.csv) contains the data collected in the campaign summarized by the centroid (or central point of each 80m grid location). The data collected for all 64 cells per grid can be found in Geo-WikiBuilt-upCellsAll.csv. The Geo-Wiki campaign uses visually interpreted grid locations called control points as part of the scoring mechanism of Geo-Wiki for quality control. These control points are provided by centroid (Geo-WikiBuilt-upCentroidsControls.csv) and for all cells in the 80m grid (Geo-WikiBuilt-upCellsControls.csv). Finally, the file Strata.csv contains the mapping between the grid location and the sampling stratum used in the design of the sample.

This collection contains data that were collected during a crowdsourcing campaign using Geo-Wiki (https://www.geo-wiki.org/). The campaign involved visual interpretation of a sample that is designed for validating any existing global built-up surface product. A zipped shapefile (ValidationGrids.zip) contains the random stratified sample of 50K locations, which consist of 80x80m grids further sub-divided into 10m cells so there are 64 cells per grid. These locations were provided to the crowd, who used very high-resolution satellite images to label the grids as built-up (i.e., containing a building), non-built-up or unsure. The file (Geo-WikiBuilt-upCentroidsAll.csv) contains the data collected in the campaign summarized by the centroid (or central point of each 80m grid location). It also contains fields for quality control, one that indicates if the change information matches the control points (see below) or the majority answer from the crowd, and another that indicates whether the presence/absence of built-up matches the control points (see below) or the majority answer from the crowd. The data collected for all 64 cells per grid can be found in Geo-WikiBuilt-upCellsAll.csv. The Geo-Wiki campaign uses visually interpreted grid locations called control points as part of the scoring mechanism of Geo-Wiki for quality control. These control points are provided by centroid (Geo-WikiBuilt-upCentroidsControls.csv) and for all cells in the 80m grid (Geo-WikiBuilt-upCellsControls.csv). In addition to the raw data, two additional quality-controlled files have been produced. The first file (Geo-WikiBuilt-upCentroidsChangeQualityControlled.csv) provides a single record for each location on change in built-up (if built-up is present) that lists either the control point answer or the majority answer from the crowd. The second file (Geo-WikiBuilt-upCellsQualityControlled.csv) contains a single record for each of the 64 cells in each grid, listing either the control point answer

We examine the implications of a recently proposed theory of fermion masses and mixings in which an A4 family symmetry emerges from orbifold compactification. We analyze two variant schemes concerning their predictions for neutrino oscillations, neutrinoless double-beta decay, and the golden quark-lepton unification mass relation. We find that upcoming experiments DUNE as well as LEGEND and nEXO offer good chances of exploring a substantial region of neutrino parameters.

Eukaryotic algae rose to ecological relevance after the Neoproterozoic Snowball Earth glaciations, but the causes for this consequential evolutionary transition remain enigmatic. Cap carbonates were globally deposited directly after these glaciations, but they are usually organic barren or thermally overprinted. Here we show that uniquely-preserved cap dolostones of the Araras Group contain exceptional abundances of a newly identified biomarker: 25,28-bisnorgammacerane. Its secular occurrence, carbon isotope systematics and co-occurrence with other demethylated terpenoids suggest a mechanistic connection to extensive microbial degradation of ciliate-derived biomass in bacterially dominated ecosystems. Declining 25,28-bisnorgammacerane concentrations, and a parallel rise of steranes over hopanes, indicate the transition from a bacterial to eukaryotic dominated ecosystem after the Marinoan deglaciation. Nutrient levels already increased during the Cryogenian and were a prerequisite, but not the ultimate driver for the algal rise. Intense predatory pressure by bacterivorous protists may have irrevocably cleared self-sustaining cyanobacterial ecosystems, thereby creating the ecological opportunity that allowed for the persistent rise of eukaryotic algae to global importance.

Eukaryotic algae rose to ecological relevance after the Neoproterozoic Snowball Earth glaciations, but the causes for this consequential evolutionary transition remain enigmatic. Cap carbonates were globally deposited directly after these glaciations, but they are usually organic barren or thermally overprinted. Here we show that uniquely-preserved cap dolostones of the Araras Group contain exceptional abundances of a newly identified biomarker: 25,28-bisnorgammacerane. Its secular occurrence, carbon isotope systematics and co-occurrence with other demethylated terpenoids suggest a mechanistic connection to extensive microbial degradation of ciliate-derived biomass in bacterially dominated ecosystems. Declining 25,28-bisnorgammacerane concentrations, and a parallel rise of steranes over hopanes, indicate the transition from a bacterial to eukaryotic dominated ecosystem after the Marinoan deglaciation. Nutrient levels already increased during the Cryogenian and were a prerequisite, but not the ultimate driver for the algal rise. Intense predatory pressure by bacterivorous protists may have irrevocably cleared self-sustaining cyanobacterial ecosystems, thereby creating the ecological opportunity that allowed for the persistent rise of eukaryotic algae to global importance.

Bi-large patterns for the leptonic mixing matrix are confronted with current neutrino oscillation data. We analyse the status of these patterns and determine, through realistic simulations, the potential of the upcoming long-baseline experiment DUNE in testing bi-large ansatze and discriminating amongst them.

A major concern for the Australian grain industry in recent years is the constant threat of resistance to the key disinfectant phosphine in a range of stored grain pests. The need to maintain the usefulness of phosphine and to contain the development of resistance are critical to international market access for Australian grain. Strong levels of resistance have already been established in major pests including the lesser grain borer, Rhyzopertha dominica (F.), the red flour beetle, Tribolium castaneum (Herbst), and most recently in the rusty grain beetle Cryptolestes ferrugineus (Stephens). As a proactive integrated resistance management strategy, new fumigation protocols are being developed in the laboratory and verified in large-scale field trials in collaboration with industry partners. To aid this development, we have deployed advanced molecular diagnostic tools to accurately determine the strength and frequency of key phosphine resistant insect pests and their movement within a typical Australian grain value chain. For example, two major bulk storage facilities based at Brookstead and Millmerran in southeast Queensland, Australia, were selected as main nodes and several farms and feed mills located in and around these two sites at a scale of 25 to 100 km radius were selected and surveyed. We determined the type, pattern, frequency as well as the distribution of resistance alleles accurately for two major pests, R. dominica and T. castaneum. Overall, this information along with the phenotypic data, provide a basis for designing key intervention strategies in managing resistance problems in the study area.

A major concern for the Australian grain industry in recent years is the constant threat of resistance to the key disinfectant phosphine in a range of stored grain pests. The need to maintain the usefulness of phosphine and to contain the development of resistance are critical to international market access for Australian grain. Strong levels of resistance have already been established in major pests including the lesser grain borer, Rhyzopertha dominica (F.), the red flour beetle, Tribolium castaneum (Herbst), and most recently in the rusty grain beetle Cryptolestes ferrugineus (Stephens). As a proactive integrated resistance management strategy, new fumigation protocols are being developed in the laboratory and verified in large-scale field trials in collaboration with industry partners. To aid this development, we have deployed advanced molecular diagnostic tools to accurately determine the strength and frequency of key phosphine resistant insect pests and their movement within a typical Australian grain value chain. For example, two major bulk storage facilities based at Brookstead and Millmerran in southeast Queensland, Australia, were selected as main nodes and several farms and feed mills located in and around these two sites at a scale of 25 to 100 km radius were selected and surveyed. We determined the type, pattern, frequency as well as the distribution of resistance alleles accurately for two major pests, R. dominica and T. castaneum. Overall, this information along with the phenotypic data, provide a basis for designing key intervention strategies in managing resistance problems in the study area.

A major concern for the Australian grain industry in recent years is the constant threat of resistance to the key disinfectant phosphine in a range of stored grain pests. The need to maintain the usefulness of phosphine and to contain the development of resistance are critical to international market access for Australian grain. Strong levels of resistance have already been established in major pests including the lesser grain borer, Rhyzopertha dominica (F.), the red flour beetle, Tribolium castaneum (Herbst), and most recently in the rusty grain beetle Cryptolestes ferrugineus (Stephens). As a proactive integrated resistance management strategy, new fumigation protocols are being developed in the laboratory and verified in large-scale field trials in collaboration with industry partners. To aid this development, we have deployed advanced molecular diagnostic tools to accurately determine the strength and frequency of key phosphine resistant insect pests and their movement within a typical Australian grain value chain. For example, two major bulk storage facilities based at Brookstead and Millmerran in southeast Queensland, Australia, were selected as main nodes and several farms and feed mills located in and around these two sites at a scale of 25 to 100 km radius were selected and surveyed. We determined the type, pattern, frequency as well as the distribution of resistance alleles accurately for two major pests, R. dominica and T. castaneum. Overall, this information along with the phenotypic data, provide a basis for designing key intervention strategies in managing resistance problems in the study area.

Phosphine resistance monitoring typically involves bioassays of beetles from population samples collected from grain storage facilities. Insects are classified into susceptible or resistant phenotypes based on mortality or survival at one or more discriminating doses. Although valuable, phenotype testing has several drawbacks. First, phenotype testing needs live insects, and considerable effort is required to collect and maintain them before testing. Second, population samples may contain multiple genotypes expressing different levels of resistance that may not be distinguishable using discriminating dose bioassays. Third, collections are likely to be focussed around grain storages to maximise sampling success. Recent research shows that several key pests are actively dispersing through flight. The availability of commercial pheromone lures and recent advances in molecular screening provide an opportunity to provide information on resistance gene frequencies more broadly across the landscape. This approach is proving to be a valuable adjunct to traditional resistance testing in Australia.

Phosphine resistance monitoring typically involves bioassays of beetles from population samples collected from grain storage facilities. Insects are classified into susceptible or resistant phenotypes based on mortality or survival at one or more discriminating doses. Although valuable, phenotype testing has several drawbacks. First, phenotype testing needs live insects, and considerable effort is required to collect and maintain them before testing. Second, population samples may contain multiple genotypes expressing different levels of resistance that may not be distinguishable using discriminating dose bioassays. Third, collections are likely to be focussed around grain storages to maximise sampling success. Recent research shows that several key pests are actively dispersing through flight. The availability of commercial pheromone lures and recent advances in molecular screening provide an opportunity to provide information on resistance gene frequencies more broadly across the landscape. This approach is proving to be a valuable adjunct to traditional resistance testing in Australia.

A major concern for the Australian grain industry in recent years is the constant threat of resistance to the key disinfectant phosphine in a range of stored grain pests. The need to maintain the usefulness of phosphine and to contain the development of resistance are critical to international market access for Australian grain. Strong levels of resistance have already been established in major pests including the lesser grain borer, Rhyzopertha dominica (F.), the red flour beetle, Tribolium castaneum (Herbst), and most recently in the rusty grain beetle Cryptolestes ferrugineus (Stephens). As a proactive integrated resistance management strategy, new fumigation protocols are being developed in the laboratory and verified in large-scale field trials in collaboration with industry partners. To aid this development, we have deployed advanced molecular diagnostic tools to accurately determine the strength and frequency of key phosphine resistant insect pests and their movement within a typical Australian grain value chain. For example, two major bulk storage facilities based at Brookstead and Millmerran in southeast Queensland, Australia, were selected as main nodes and several farms and feed mills located in and around these two sites at a scale of 25 to 100 km radius were selected and surveyed. We determined the type, pattern, frequency as well as the distribution of resistance alleles accurately for two major pests, R. dominica and T. castaneum. Overall, this information along with the phenotypic data, provide a basis for designing key intervention strategies in managing resistance problems in the study area.

A major concern for the Australian grain industry in recent years is the constant threat of resistance to the key disinfectant phosphine in a range of stored grain pests. The need to maintain the usefulness of phosphine and to contain the development of resistance are critical to international market access for Australian grain. Strong levels of resistance have already been established in major pests including the lesser grain borer, Rhyzopertha dominica (F.), the red flour beetle, Tribolium castaneum (Herbst), and most recently in the rusty grain beetle Cryptolestes ferrugineus (Stephens). As a proactive integrated resistance management strategy, new fumigation protocols are being developed in the laboratory and verified in large-scale field trials in collaboration with industry partners. To aid this development, we have deployed advanced molecular diagnostic tools to accurately determine the strength and frequency of key phosphine resistant insect pests and their movement within a typical Australian grain value chain. For example, two major bulk storage facilities based at Brookstead and Millmerran in southeast Queensland, Australia, were selected as main nodes and several farms and feed mills located in and around these two sites at a scale of 25 to 100 km radius were selected and surveyed. We determined the type, pattern, frequency as well as the distribution of resistance alleles accurately for two major pests, R. dominica and T. castaneum. Overall, this information along with the phenotypic data, provide a basis for designing key intervention strategies in managing resistance problems in the study area.

Phosphine resistance monitoring typically involves bioassays of beetles from population samples collected from grain storage facilities. Insects are classified into susceptible or resistant phenotypes based on mortality or survival at one or more discriminating doses. Although valuable, phenotype testing has several drawbacks. First, phenotype testing needs live insects, and considerable effort is required to collect and maintain them before testing. Second, population samples may contain multiple genotypes expressing different levels of resistance that may not be distinguishable using discriminating dose bioassays. Third, collections are likely to be focussed around grain storages to maximise sampling success. Recent research shows that several key pests are actively dispersing through flight. The availability of commercial pheromone lures and recent advances in molecular screening provide an opportunity to provide information on resistance gene frequencies more broadly across the landscape. This approach is proving to be a valuable adjunct to traditional resistance testing in Australia.

We present an analysis of the $xF_3(x,Q^2)$ structure function and Gross-Llewellyn Smith(GLS) sum rule taking into account the nuclear effects and higher twist correction. This analysis is based on the results presented in "N. M. Nath et al., Indian J Phys 90(1), 117 (2016)". The corrections due to nuclear effects predicted in several earlier analysis are incorporated to our results of $xF_3(x,Q^2)$ structure function and GLS sum rule for free nucleon, corrected upto next-next-to-leading order (NNLO) perturbative order and calculate the nuclear structure function as well as sum rule for nuclei. In addition, by means of a simple model we have extracted the higher twist contributions to the non-singlet structure function $xF_3(x,Q^2)$ and GLS sum rule in NNLO perturbative orders and then incorporated them to our results. Our NNLO results along with nuclear effect and higher twist corrections are observed to be compatible with corresponding experimental data and other phenomenological analysis., Comment: 17 pages, 4 figures. arXiv admin note: text overlap with arXiv:0911.2254 by other authors

We present an analysis of the $xF_3(x,Q^2)$ structure function and Gross-Llewellyn Smith(GLS) sum rule taking into account the nuclear effects and higher twist correction. This analysis is based on the results presented in "N. M. Nath et al., Indian J Phys 90(1), 117 (2016)". The corrections due to nuclear effects predicted in several earlier analysis are incorporated to our results of $xF_3(x,Q^2)$ structure function and GLS sum rule for free nucleon, corrected upto next-next-to-leading order (NNLO) perturbative order and calculate the nuclear structure function as well as sum rule for nuclei. In addition, by means of a simple model we have extracted the higher twist contributions to the non-singlet structure function $xF_3(x,Q^2)$ and GLS sum rule in NNLO perturbative orders and then incorporated them to our results. Our NNLO results along with nuclear effect and higher twist corrections are observed to be compatible with corresponding experimental data and other phenomenological analysis., Comment: 17 pages, 4 figures. arXiv admin note: text overlap with arXiv:0911.2254 by other authors

Neutrino-nucleon scattering, which produces the parity violating term, xF3(x,Q2) the non-singlet hadron structure function in their weak interaction has significant contribution towards the understanding of valence quark distribution for low-Q2 and small-x region inside hadrons. Here x is the fractional momentum of partons and Q2 is the four momentum transfer in a deep inelastic scattering process. In this paper, the xF3(x,Q2) structure function has been obtained by solving the Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution equation in leading order and next-to-leading order at small-x limit by using the method to get unique solution. The results are compared with recent experimental data and parametrizations. Also a qualitative discussion of nuclear effect in xF3(x,Q2) is done in this regards., Comment: 8 pages, 3 figures This paper has been withdrawn due to the reason that it has been improved and some texts and equations will be replaced

Neutrino-nucleon scattering, which produces the parity violating term, xF3(x,Q2) the non-singlet hadron structure function in their weak interaction has significant contribution towards the understanding of valence quark distribution for low-Q2 and small-x region inside hadrons. Here x is the fractional momentum of partons and Q2 is the four momentum transfer in a deep inelastic scattering process. In this paper, the xF3(x,Q2) structure function has been obtained by solving the Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution equation in leading order and next-to-leading order at small-x limit by using the method to get unique solution. The results are compared with recent experimental data and parametrizations. Also a qualitative discussion of nuclear effect in xF3(x,Q2) is done in this regards., Comment: 8 pages, 3 figures This paper has been withdrawn due to the reason that it has been improved and some texts and equations will be replaced

Continuum or hyper-redundant robots are robots which exhibit behavior similar to biological trunks, tentacles and snakes. Unlike traditional robots, continuum robot manipulators do not have rigid joints, hence the manipulators are compliant, extremely dexterous, and capable of dynamic, adaptive manipulation in unstructured environments; however, the development of high-performance control algorithms for these manipulators is a challenging problem. In this paper, we present an approach to whole arm grasping control for continuum robots. The grasping controller is developed in two stages; high level path planning for the grasping objective, and a low level joint controller using a neural network feedforward component to compensate for dynamic uncertainties. These techniques are used to enable whole arm grasping without using contact force measurements and without using a dynamic model of the continuum robot. Experimental results using the OCTARM, a soft continuum robotic manipulator are included to illustrate the efficacy of the proposed low level joint controller., Sponsored in part by ARO Automotive Center, the Department of Commerce and the Department of Energy. The original document contains color images.