Definition at line 27 of file MultiAppInterpolationTransfer.h.
Definition at line 54 of file MultiAppInterpolationTransfer.C.
Generate a unified error message if the underlying libMesh mesh is a DistributedMesh.
Definition at line 77 of file MultiAppInterpolationTransfer.C.
202 // The zero only works for LAGRANGE!
260 // Only works with a serialized mesh to transfer to!
387 // The zero only works for LAGRANGE!
Referenced by MultiAppPostprocessorInterpolationTransfer::execute(), MultiAppVariableValueSampleTransfer::execute(), MultiAppUserObjectTransfer::execute(), execute(), MultiAppDTKInterpolationTransfer::execute(), MultiAppNearestNodeTransfer::execute(), DTKInterpolationAdapter::get_values_to_fill(), DTKInterpolationAdapter::get_variable_evaluator(), MultiAppMeshFunctionTransfer::transferVariable(), DTKInterpolationAdapter::update_variable_values(), and MultiAppTransfer::variableIntegrityCheck().
Return the nearest node to the point p.
p The point you want to find the nearest node to.
The Node closest to point p.
Definition at line 432 of file MultiAppInterpolationTransfer.C.
Definition at line 68 of file MultiAppInterpolationTransfer.C.
Referenced by GridPartitioner::_do_partition(), PetscExternalPartitioner::_do_partition(), FEProblemBase::addConstraint(), FEProblemBase::addInitialCondition(), FEProblem::addLineSearch(), FEProblemBase::addLineSearch(), FEProblemBase::addOutput(), DiracKernel::addPointWithValidId(), FEProblemBase::addPostprocessor(), MooseMesh::addQuadratureNode(), FEProblemBase::addVectorPostprocessor(), ADPiecewiseLinearInterpolationMaterial< compute_stage >::ADPiecewiseLinearInterpolationMaterial(), Output::advancedExecuteOn(), AnnularMesh::AnnularMesh(), AnnularMeshGenerator::AnnularMeshGenerator(), MultiApp::appPostprocessorValue(), MultiApp::appProblem(), MultiApp::appProblemBase(), MultiApp::appUserObjectBase(), DerivativeParsedMaterialHelper::assembleDerivatives(), Function::average(), Axisymmetric2D3DSolutionFunction::Axisymmetric2D3DSolutionFunction(), BicubicSplineFunction::BicubicSplineFunction(), BoundingValueElementDamper::BoundingValueElementDamper(), BoundingValueNodalDamper::BoundingValueNodalDamper(), BoundsAux::BoundsAux(), BreakMeshByBlockGenerator::BreakMeshByBlockGenerator(), BreakMeshByBlockGeneratorBase::BreakMeshByBlockGeneratorBase(), MooseMesh::buildCoarseningMap(), Piecewise::buildFromFile(), Piecewise::buildFromXandY(), Piecewise::buildFromXY(), TiledMesh::buildMesh(), FileMesh::buildMesh(), SpiralAnnularMesh::buildMesh(), DistributedGeneratedMesh::buildMesh(), GeneratedMesh::buildMesh(), ImageMeshGenerator::buildMesh3D(), ImageMesh::buildMesh3D(), MooseMesh::buildMeshBaseObject(), MooseMesh::buildRefinementMap(), MooseMesh::buildSideList(), CartesianMeshGenerator::CartesianMeshGenerator(), ChangeOverTimePostprocessor::ChangeOverTimePostprocessor(), EigenExecutionerBase::chebyshev(), SubProblem::checkBlockMatProps(), SubProblem::checkBoundaryMatProps(), FEProblemBase::checkCoordinateSystems(), FEProblemBase::checkDependMaterialsHelper(), FEProblemBase::checkDisplacementOrders(), Material::checkExecutionStage(), BreakMeshByBlockBase::checkInputParameter(), Steady::checkIntegrity(), EigenExecutionerBase::checkIntegrity(), ActuallyExplicitEuler::checkLinearConvergence(), FEProblemBase::checkProblemIntegrity(), Material::checkStatefulSanity(), FEProblemBase::checkUserObjects(), LibmeshPartitioner::clone(), MooseMesh::clone(), ComparisonPostprocessor::comparisonIsTrue(), CompositeFunction::CompositeFunction(), ElementLpNormAux::compute(), ElementH1ErrorFunctionAux::compute(), NodalPatchRecovery::compute(), KernelBase::computeADOffDiagJacobian(), InterfaceKernel::computeElemNeighJacobian(), TimeSequenceStepperBase::computeFailedDT(), IterationAdaptiveDT::computeFailedDT(), TimeStepper::computeFailedDT(), HistogramVectorPostprocessor::computeHistogram(), EqualValueEmbeddedConstraint::computeQpJacobian(), EqualValueEmbeddedConstraint::computeQpOffDiagJacobian(), KernelValue::computeQpResidual(), FEProblemBase::computeResidualInternal(), FEProblemBase::computeResidualTag(), FEProblemBase::computeResidualType(), StatisticsVectorPostprocessor::computeStatValue(), Material::computeSubdomainProperties(), ExplicitEuler::computeTimeDerivatives(), ImplicitEuler::computeTimeDerivatives(), BDF2::computeTimeDerivatives(), NewmarkBeta::computeTimeDerivatives(), CrankNicolson::computeTimeDerivatives(), ActuallyExplicitEuler::computeTimeDerivatives(), LStableDirk2::computeTimeDerivatives(), LStableDirk3::computeTimeDerivatives(), ImplicitMidpoint::computeTimeDerivatives(), ExplicitTVDRK2::computeTimeDerivatives(), AStableDirk4::computeTimeDerivatives(), LStableDirk4::computeTimeDerivatives(), ExplicitRK2::computeTimeDerivatives(), PenetrationAux::computeValue(), ConcentricCircleMesh::ConcentricCircleMesh(), ConditionalEnableControl::ConditionalEnableControl(), TimeStepper::constrainStep(), CoupledForce::CoupledForce(), DebugResidualAux::DebugResidualAux(), FunctorRelationshipManager::delete_remote_elements(), BicubicSplineFunction::derivative(), DerivativeSumMaterial::DerivativeSumMaterial(), DGKernelBase::DGKernelBase(), FunctorRelationshipManager::dofmap_reinit(), FEProblemBase::duplicateVariableCheck(), EigenProblem::EigenProblem(), Eigenvalues::Eigenvalues(), ElementalVariableValue::ElementalVariableValue(), ElementQualityAux::ElementQualityAux(), MooseMesh::errorIfDistributedMesh(), SolutionUserObject::evalMeshFunction(), SolutionUserObject::evalMeshFunctionGradient(), SolutionUserObject::evalMultiValuedMeshFunction(), SolutionUserObject::evalMultiValuedMeshFunctionGradient(), MultiAppPostprocessorTransfer::execute(), DiscreteElementUserObject::execute(), MultiAppPostprocessorInterpolationTransfer::execute(), MultiAppVariableValueSamplePostprocessorTransfer::execute(), ElementQualityChecker::execute(), NodalValueSampler::execute(), InterfaceQpValueUserObject::execute(), PointValue::execute(), MultiAppPostprocessorToAuxScalarTransfer::execute(), MultiAppScalarToAuxScalarTransfer::execute(), MultiAppVariableValueSampleTransfer::execute(), execute(), MultiAppUserObjectTransfer::execute(), FindValueOnLine::execute(), MultiAppNearestNodeTransfer::execute(), TimeExtremeValue::execute(), VectorPostprocessorComparison::execute(), LeastSquaresFit::execute(), LeastSquaresFitHistory::execute(), FEProblemBase::executeControls(), MultiAppVectorPostprocessorTransfer::executeFromMultiapp(), MultiAppVectorPostprocessorTransfer::executeToMultiapp(), Exodus::Exodus(), FileOutput::FileOutput(), CentroidMultiApp::fillPositions(), MultiApp::fillPositions(), VerifyElementUniqueID::finalize(), VerifyNodalUniqueID::finalize(), DiscreteElementUserObject::finalize(), ElementQualityChecker::finalize(), MemoryUsage::finalize(), PointSamplerBase::finalize(), Transfer::find_sys(), BreakMeshByBlockBase::findFreeBoundaryId(), BreakMeshByBlockGeneratorBase::findFreeBoundaryId(), FunctionDT::FunctionDT(), FunctionMaterialBase::FunctionMaterialBase(), ParsedMaterialHelper::functionParse(), FunctionScalarAux::FunctionScalarAux(), FunctionScalarIC::FunctionScalarIC(), GapValueAux::GapValueAux(), ElementSubdomainIDGenerator::generate(), ExtraNodesetGenerator::generate(), RenameBlockGenerator::generate(), RenameBoundaryGenerator::generate(), GeneratedMeshGenerator::generate(), MeshExtruderGenerator::generate(), SideSetsFromBoundingBoxGenerator::generate(), StackGenerator::generate(), SpiralAnnularMeshGenerator::generate(), PatternedMeshGenerator::generate(), BoundingBoxNodeSetGenerator::generate(), GeneratedMesh::GeneratedMesh(), GeneratedMeshGenerator::GeneratedMeshGenerator(), RandomICBase::generateRandom(), GenericConstantMaterial::GenericConstantMaterial(), GenericFunctionMaterial::GenericFunctionMaterial(), MooseMesh::getBoundaryID(), MultiApp::getBoundingBox(), MooseMesh::getCoarseningMap(), Control::getControllableParameterByName(), FEProblemBase::getCoordSystem(), PiecewiseConstant::getDirection(), FEProblemBase::getDistribution(), GhostingUserObject::getElementalValue(), ElementGenerator::getElemType(), MultiApp::getExecutioner(), FEProblemBase::getFunction(), SolutionUserObject::getLocalVarIndex(), SubProblem::getMatrixTagID(), AnnularMesh::getMaxInDimension(), DistributedGeneratedMesh::getMaxInDimension(), GeneratedMesh::getMaxInDimension(), FEProblemBase::getMaxQps(), FEProblemBase::getMaxShapeFunctions(), AnnularMesh::getMinInDimension(), DistributedGeneratedMesh::getMinInDimension(), GeneratedMesh::getMinInDimension(), MooseMesh::getMortarInterface(), MooseMesh::getMortarInterfaceByName(), MooseMesh::getNodeBlockIds(), MooseMesh::getNodeList(), FEProblemBase::getNonlinearSystem(), MooseMesh::getPairedBoundaryMapping(), ImageMeshGenerator::GetPixelInfo(), ImageMesh::GetPixelInfo(), InterfaceQpValueUserObject::getQpValue(), MaterialStdVectorAux::getRealValue(), MooseMesh::getRefinementMap(), FEProblemBase::getSampler(), DisplacedProblem::getScalarVariable(), FEProblemBase::getScalarVariable(), DisplacedProblem::getStandardVariable(), FEProblemBase::getStandardVariable(), MooseMesh::getSubdomainBoundaryIds(), MooseMesh::getSubdomainID(), DisplacedProblem::getSystem(), FEProblemBase::getSystem(), FEProblemBase::getUserObject(), FEProblemBase::getUserObjectBase(), Residual::getValue(), PerformanceData::getValue(), PerfGraphData::getValue(), LineValueSampler::getValue(), FindValueOnLine::getValueAtPoint(), SubProblem::getVariableHelper(), SubProblem::getVectorTagID(), DisplacedProblem::getVectorVariable(), FEProblemBase::getVectorVariable(), GhostingAux::GhostingAux(), MultiApp::globalAppToLocal(), MooseParsedVectorFunction::gradient(), AdvancedOutput::hasOutputHelper(), CrankNicolson::init(), CSVTimeSequenceStepper::init(), IterationAdaptiveDT::init(), EigenExecutionerBase::init(), Transient::init(), MooseMesh::init(), FEProblemBase::init(), NumPicardIterations::initialize(), FullSolveMultiApp::initialSetup(), PiecewiseBase::initialSetup(), SolutionAux::initialSetup(), Axisymmetric2D3DSolutionFunction::initialSetup(), SolutionFunction::initialSetup(), Exodus::initialSetup(), SolutionUserObject::initialSetup(), FEProblemBase::initialSetup(), AdvancedOutput::initOutputList(), AdvancedOutput::initShowHideLists(), Material::initStatefulProperties(), Function::integral(), InterfaceKernel::InterfaceKernel(), InterfaceTimeKernel::InterfaceTimeKernel(), EigenExecutionerBase::inversePowerIteration(), InversePowerMethod::InversePowerMethod(), IterationAdaptiveDT::IterationAdaptiveDT(), LayeredSideIntegral::LayeredSideIntegral(), LeastSquaresFit::LeastSquaresFit(), LibmeshPartitioner::LibmeshPartitioner(), LinearCombinationFunction::LinearCombinationFunction(), LinearCombinationPostprocessor::LinearCombinationPostprocessor(), LinearNodalConstraint::LinearNodalConstraint(), LineMaterialSamplerBase< Real >::LineMaterialSamplerBase(), LineSearch::lineSearch(), LineValueSampler::LineValueSampler(), MaterialRealTensorValueAux::MaterialRealTensorValueAux(), MaterialRealVectorValueAux::MaterialRealVectorValueAux(), MaterialStdVectorRealGradientAux::MaterialStdVectorRealGradientAux(), MaterialVectorPostprocessor::MaterialVectorPostprocessor(), Distribution::median(), FunctorRelationshipManager::mesh_reinit(), SubProblem::meshChanged(), MeshExtruder::MeshExtruder(), MeshExtruderGenerator::MeshExtruderGenerator(), MeshSideSetGenerator::MeshSideSetGenerator(), SideSetsFromPoints::modify(), SideSetsFromNormals::modify(), BreakMeshByBlockBase::modify(), MeshExtruder::modify(), AddExtraNodeset::modify(), AssignElementSubdomainID::modify(), SmoothMesh::modify(), AddAllSideSetsByNormals::modify(), ElementDeleterBase::modify(), ParsedSubdomainMeshModifier::modify(), RenameBlock::modify(), ImageSubdomain::modify(), OrientedSubdomainBoundingBox::modify(), BoundingBoxNodeSet::modify(), AddSideSetsFromBoundingBox::modify(), SubdomainBoundingBox::modify(), MooseGhostPointNeighbors::MooseGhostPointNeighbors(), MooseMesh::MooseMesh(), MultiAppMeshFunctionTransfer::MultiAppMeshFunctionTransfer(), MultiAppPostprocessorTransfer::MultiAppPostprocessorTransfer(), NearestNodeDistanceAux::NearestNodeDistanceAux(), NearestNodeValueAux::NearestNodeValueAux(), RenameBlockGenerator::newBlockID(), RenameBlock::newBlockID(), RenameBlockGenerator::newBlockName(), RenameBlock::newBlockName(), NewmarkBeta::NewmarkBeta(), NodalConstraint::NodalConstraint(), NodalScalarKernel::NodalScalarKernel(), NodalVariableValue::NodalVariableValue(), NumDOFs::NumDOFs(), NumNonlinearIterations::NumNonlinearIterations(), NumVars::NumVars(), FunctorRelationshipManager::operator()(), RelationshipManager::operator==(), XDA::output(), SolutionHistory::output(), Exodus::output(), AdvancedOutput::outputElementalVariables(), AdvancedOutput::outputInput(), AdvancedOutput::outputNodalVariables(), AdvancedOutput::outputPostprocessors(), AdvancedOutput::outputScalarVariables(), AdvancedOutput::outputSystemInformation(), Console::outputVectorPostprocessors(), AdvancedOutput::outputVectorPostprocessors(), MooseObject::paramError(), PiecewiseBilinear::parse(), ParsedAddSideset::ParsedAddSideset(), ParsedAux::ParsedAux(), ParsedGenerateSideset::ParsedGenerateSideset(), ParsedODEKernel::ParsedODEKernel(), ParsedSubdomainMeshGenerator::ParsedSubdomainMeshGenerator(), ParsedSubdomainMeshModifier::ParsedSubdomainMeshModifier(), PetscExternalPartitioner::PetscExternalPartitioner(), PhysicsBasedPreconditioner::PhysicsBasedPreconditioner(), Piecewise::Piecewise(), PiecewiseBilinear::PiecewiseBilinear(), PiecewiseLinearInterpolationMaterial::PiecewiseLinearInterpolationMaterial(), PiecewiseMulticonstant::PiecewiseMulticonstant(), PiecewiseMultiInterpolation::PiecewiseMultiInterpolation(), SolutionUserObject::pointValueGradientWrapper(), SolutionUserObject::pointValueWrapper(), LStableDirk2::postResidual(), LStableDirk3::postResidual(), ImplicitMidpoint::postResidual(), ExplicitTVDRK2::postResidual(), LStableDirk4::postResidual(), AStableDirk4::postResidual(), ExplicitRK2::postResidual(), Predictor::Predictor(), Transient::preExecute(), SolutionUserObject::readExodusII(), SolutionUserObject::readXda(), FunctorRelationshipManager::redistribute(), EqualValueEmbeddedConstraint::reinitConstraint(), RelativeSolutionDifferenceNorm::RelativeSolutionDifferenceNorm(), RenameBlock::RenameBlock(), RenameBlockGenerator::RenameBlockGenerator(), RenameBoundaryGenerator::RenameBoundaryGenerator(), RinglebMesh::RinglebMesh(), RinglebMeshGenerator::RinglebMeshGenerator(), ScalarComponentIC::ScalarComponentIC(), BicubicSplineFunction::secondDerivative(), FEProblemBase::setCoordSystem(), PiecewiseBase::setData(), EigenProblem::setEigenproblemType(), FEProblemSolve::setInnerSolve(), Sampler::setNumberOfRequiedRandomSeeds(), Exodus::setOutputDimensionInExodusWriter(), Split::setup(), TransientMultiApp::setupApp(), TimeSequenceStepperBase::setupSequence(), Transient::setupTimeIntegrator(), SideSetsFromBoundingBoxGenerator::SideSetsFromBoundingBoxGenerator(), SideSetsFromNormals::SideSetsFromNormals(), SideSetsFromNormalsGenerator::SideSetsFromNormalsGenerator(), SideSetsFromPoints::SideSetsFromPoints(), SideSetsFromPointsGenerator::SideSetsFromPointsGenerator(), SolutionTimeAdaptiveDT::SolutionTimeAdaptiveDT(), SolutionUserObject::SolutionUserObject(), PicardSolve::solve(), ActuallyExplicitEuler::solve(), FullSolveMultiApp::solveStep(), SpatialAverageBase::SpatialAverageBase(), UserObject::spatialValue(), SpiralAnnularMesh::SpiralAnnularMesh(), SpiralAnnularMeshGenerator::SpiralAnnularMeshGenerator(), StitchedMesh::StitchedMesh(), NodalUserObject::subdomainSetup(), GeneralUserObject::subdomainSetup(), Constraint::subdomainSetup(), Console::systemInfoFlags(), Terminator::Terminator(), TestSetupPostprocessorDataActionFunction::TestSetupPostprocessorDataActionFunction(), ThreadedGeneralUserObject::ThreadedGeneralUserObject(), ThreadedGeneralUserObject::threadJoin(), DiscreteElementUserObject::threadJoin(), GeneralUserObject::threadJoin(), TiledMeshGenerator::TiledMeshGenerator(), Function::timeDerivative(), TimeExtremeValue::TimeExtremeValue(), TimePeriod::TimePeriod(), VectorPostprocessorVisualizationAux::timestepSetup(), MultiAppCopyTransfer::transfer(), MultiAppMeshFunctionTransfer::transferVariable(), FEProblemBase::uDotDotOldRequested(), FEProblemBase::uDotOldRequested(), EqualValueBoundaryConstraint::updateConstrainedNodes(), SolutionUserObject::updateExodusBracketingTimeIndices(), Axisymmetric2D3DSolutionFunction::value(), ValueRangeMarker::ValueRangeMarker(), ValueThresholdMarker::ValueThresholdMarker(), MultiAppTransfer::variableIntegrityCheck(), VariableTimeIntegrationAux::VariableTimeIntegrationAux(), VectorNodalBC::VectorNodalBC(), VectorOfPostprocessors::VectorOfPostprocessors(), VectorPostprocessorFunction::VectorPostprocessorFunction(), MooseParsedGradFunction::vectorValue(), MooseParsedFunction::vectorValue(), VectorVariableComponentAux::VectorVariableComponentAux(), VolumeHistogram::VolumeHistogram(), VTKOutput::VTKOutput(), DOFMapOutput::writeStreamToFile(), and Console::writeStreamToFile().
Referenced by GridPartitioner::_do_partition(), FEProblemBase::addADJacobianMaterial(), FEProblemBase::addADResidualMaterial(), Executioner::addAttributeReporter(), DumpObjectsProblem::addAuxKernel(), FEProblemBase::addAuxKernel(), DumpObjectsProblem::addAuxScalarKernel(), FEProblemBase::addAuxScalarKernel(), DumpObjectsProblem::addBoundaryCondition(), FEProblemBase::addBoundaryCondition(), DumpObjectsProblem::addConstraint(), FEProblemBase::addConstraint(), FEProblemBase::addDamper(), DumpObjectsProblem::addDGKernel(), FEProblemBase::addDGKernel(), DumpObjectsProblem::addDiracKernel(), FEProblemBase::addDiracKernel(), FEProblemBase::addDistribution(), DumpObjectsProblem::addFunction(), FEProblemBase::addFunction(), FEProblemBase::addIndicator(), DumpObjectsProblem::addInitialCondition(), FEProblemBase::addInitialCondition(), DumpObjectsProblem::addInterfaceKernel(), FEProblemBase::addInterfaceKernel(), DumpObjectsProblem::addKernel(), FEProblemBase::addKernel(), FEProblemBase::addMarker(), DumpObjectsProblem::addMaterial(), FEProblemBase::addMaterial(), FEProblemBase::addMaterialHelper(), MooseMesh::addMortarInterface(), FEProblemBase::addMultiApp(), DumpObjectsProblem::addNodalKernel(), FEProblemBase::addNodalKernel(), FEProblemBase::addPostprocessor(), FEProblemBase::addPredictor(), CreateDisplacedProblemAction::addProxyAlgebraicRelationshipManagers(), CreateDisplacedProblemAction::addProxyGeometricRelationshipManagers(), FEProblemBase::addSampler(), DumpObjectsProblem::addScalarKernel(), FEProblemBase::addScalarKernel(), FEProblemBase::addTimeIntegrator(), FEProblemBase::addTransfer(), FEProblemBase::addUserObject(), FEProblemBase::addVectorPostprocessor(), Output::advancedExecuteOn(), MultiApp::appPostprocessorValue(), MultiApp::appProblem(), MultiApp::appProblemBase(), MultiApp::appUserObjectBase(), DerivativeParsedMaterialHelper::assembleDerivatives(), AStableDirk4::AStableDirk4(), Function::average(), MultiApp::backup(), BreakMeshByBlockGenerator::BreakMeshByBlockGenerator(), ChangeOverTimePostprocessor::ChangeOverTimePostprocessor(), FEProblemBase::checkDependMaterialsHelper(), Damper::checkMinDamping(), Material::checkStatefulSanity(), CompositeFunction::CompositeFunction(), Material::computeSubdomainProperties(), VectorPostprocessorVisualizationAux::computeValue(), MultiApp::createApp(), FEProblemBase::declareVectorPostprocessorVector(), DOFMapOutput::demangle(), DerivativeSumMaterial::DerivativeSumMaterial(), DGKernelBase::DGKernelBase(), DumpObjectsProblem::dumpObjectHelper(), ElementValueSampler::ElementValueSampler(), MooseMesh::errorIfDistributedMesh(), AB2PredictorCorrector::estimateTimeError(), SolutionUserObject::evalMeshFunction(), SolutionUserObject::evalMeshFunctionGradient(), SolutionUserObject::evalMultiValuedMeshFunction(), SolutionUserObject::evalMultiValuedMeshFunctionGradient(), MultiAppPostprocessorTransfer::execute(), MultiAppPostprocessorInterpolationTransfer::execute(), MultiAppVariableValueSamplePostprocessorTransfer::execute(), StatisticsVectorPostprocessor::execute(), MultiAppPostprocessorToAuxScalarTransfer::execute(), MultiAppScalarToAuxScalarTransfer::execute(), MultiAppVariableValueSampleTransfer::execute(), PointValue::execute(), MultiAppMeshFunctionTransfer::execute(), execute(), MultiAppUserObjectTransfer::execute(), MultiAppNearestNodeTransfer::execute(), MultiAppProjectionTransfer::execute(), MultiAppVectorPostprocessorTransfer::execute(), HistogramVectorPostprocessor::execute(), MultiAppCopyTransfer::execute(), Exodus::Exodus(), FileOutput::FileOutput(), MultiApp::fillPositions(), PointSamplerBase::finalize(), DerivativeParsedMaterialHelper::findMatPropDerivative(), FunctionDT::FunctionDT(), GeneralUserObject::GeneralUserObject(), LowerDBlockFromSidesetGenerator::generate(), StitchedMeshGenerator::generate(), Material::getADMaterialProperty(), MultiApp::getBoundingBox(), MooseObject::getCheckedPointerParam(), Control::getControllableParameterByName(), Control::getControllableValue(), Control::getControllableValueByName(), DistributionInterface::getDistribution(), FEProblemBase::getDistribution(), DistributionInterface::getDistributionByName(), MultiApp::getExecutioner(), OutputWarehouse::getFileNumbers(), FEProblemBase::getFunction(), SolutionUserObject::getLocalVarIndex(), Marker::getMarkerValue(), FEProblemBase::getMaterial(), NodalPatchRecovery::getMaterialProperty(), Material::getMaterialProperty(), AuxKernelTempl< ComputeValueType >::getMaterialProperty(), SubProblem::getMaterialPropertyBlockNames(), SubProblem::getMaterialPropertyBoundaryNames(), NodalPatchRecovery::getMaterialPropertyOld(), AuxKernelTempl< ComputeValueType >::getMaterialPropertyOld(), Material::getMaterialPropertyOld(), NodalPatchRecovery::getMaterialPropertyOlder(), AuxKernelTempl< ComputeValueType >::getMaterialPropertyOlder(), Material::getMaterialPropertyOlder(), MeshGenerator::getMesh(), MooseMesh::getMortarInterfaceByName(), OutputWarehouse::getOutput(), MooseObject::getParam(), GeneralUserObject::getPostprocessorValue(), FEProblemBase::getPostprocessorValue(), GeneralUserObject::getPostprocessorValueByName(), FEProblemBase::getPostprocessorValueOld(), FEProblemBase::getPostprocessorValueOlder(), FEProblemBase::getSampler(), FEProblemBase::getScatterVectorPostprocessorValue(), FEProblemBase::getScatterVectorPostprocessorValueOld(), Transient::getTimeStepperName(), InitialConditionBase::getUserObject(), FEProblemBase::getUserObject(), InitialConditionBase::getUserObjectBase(), FEProblemBase::getUserObjectBase(), InitialConditionBase::getUserObjectByName(), GeneralUserObject::getVectorPostprocessorValue(), FEProblemBase::getVectorPostprocessorValue(), GeneralUserObject::getVectorPostprocessorValueByName(), FEProblemBase::getVectorPostprocessorValueOld(), FEProblemBase::hasFunction(), AdvancedOutput::hasOutputHelper(), FEProblemBase::hasPostprocessor(), FEProblemBase::hasUserObject(), FEProblemBase::hasVectorPostprocessor(), FEProblemBase::init(), AdvancedOutput::initExecutionTypes(), AttribName::initFrom(), CSVReader::initialize(), StatisticsVectorPostprocessor::initialize(), HistogramVectorPostprocessor::initialize(), MultiAppProjectionTransfer::initialSetup(), DerivativeFunctionMaterialBase::initialSetup(), SolutionUserObject::initialSetup(), AdvancedOutput::initOutputList(), FEProblemBase::initPostprocessorData(), AdvancedOutput::initPostprocessorOrVectorPostprocessorLists(), Material::initStatefulProperties(), FEProblemBase::initVectorPostprocessorData(), Function::integral(), InterfaceKernel::InterfaceKernel(), Registry::isADObj(), MooseObject::isParamValid(), Registry::isRegisteredObj(), LinearCombinationFunction::LinearCombinationFunction(), Marker::Marker(), MatDiffusionBase< Real >::MatDiffusionBase(), MaterialDerivativeTestKernelBase< Real >::MaterialDerivativeTestKernelBase(), MaterialVectorPostprocessor::MaterialVectorPostprocessor(), Distribution::median(), MemoryUsageReporter::MemoryUsageReporter(), MeshSideSetGenerator::MeshSideSetGenerator(), ElementDeleterBase::modify(), MooseVariableInterface< Real >::MooseVariableInterface(), NearestPointBase< LayeredAverage >::NearestPointBase(), NodalValueSampler::NodalValueSampler(), NodalVariableValue::NodalVariableValue(), Registry::objData(), DOFMapOutput::output(), Output::Output(), AdvancedOutput::outputElementalVariables(), AdvancedOutput::outputInput(), AdvancedOutput::outputNodalVariables(), ConsoleUtils::outputOutputInformation(), Nemesis::outputPostprocessors(), Exodus::outputPostprocessors(), AdvancedOutput::outputPostprocessors(), AdvancedOutput::outputScalarVariables(), AdvancedOutput::outputSystemInformation(), AdvancedOutput::outputVectorPostprocessors(), ParsedAddSideset::ParsedAddSideset(), ParsedAux::ParsedAux(), ParsedGenerateSideset::ParsedGenerateSideset(), ParsedODEKernel::ParsedODEKernel(), ParsedSubdomainMeshGenerator::ParsedSubdomainMeshGenerator(), ParsedSubdomainMeshModifier::ParsedSubdomainMeshModifier(), PointSamplerBase::PointSamplerBase(), Registry::registerObjectsTo(), FEProblemBase::registerRandomInterface(), Material::resetQpProperties(), MultiApp::restore(), Sampler::Sampler(), ScalarComponentIC::ScalarComponentIC(), MooseMesh::setBoundaryName(), Control::setControllableValue(), Control::setControllableValueByName(), OutputWarehouse::setFileNumbers(), MooseMesh::setSubdomainName(), Split::setup(), TransientMultiApp::setupApp(), SideSetsFromNormalsGenerator::SideSetsFromNormalsGenerator(), SideSetsFromPointsGenerator::SideSetsFromPointsGenerator(), SideValueSampler::SideValueSampler(), TransientMultiApp::solveStep(), SpatialAverageBase::SpatialAverageBase(), UserObject::spatialValue(), StitchedMesh::StitchedMesh(), SubProblem::storeBoundaryDelayedCheckMatProp(), SubProblem::storeBoundaryMatPropName(), SubProblem::storeBoundaryZeroMatProp(), SubProblem::storeSubdomainDelayedCheckMatProp(), SubProblem::storeSubdomainMatPropName(), SubProblem::storeSubdomainZeroMatProp(), TaggingInterface::TaggingInterface(), ThreadedGeneralUserObject::ThreadedGeneralUserObject(), Function::timeDerivative(), VectorPostprocessorVisualizationAux::timestepSetup(), TransientMultiApp::TransientMultiApp(), MultiAppTransfer::variableIntegrityCheck(), and AdvancedOutput::wantOutput().
Referenced by MultiAppVariableValueSampleTransfer::initialSetup(), MultiAppMeshFunctionTransfer::initialSetup(), initialSetup(), MultiAppUserObjectTransfer::initialSetup(), MultiAppNearestNodeTransfer::initialSetup(), and MultiAppCopyTransfer::initialSetup().
Referenced by IterationAdaptiveDT::acceptStep(), SetupRecoverFileBaseAction::act(), Adaptivity::adaptMesh(), FEProblemBase::adaptMesh(), SimplePredictor::apply(), MultiApp::backup(), FEProblemBase::backupMultiApps(), FEProblemBase::checkProblemIntegrity(), IterationAdaptiveDT::computeAdaptiveDT(), Transient::computeConstrainedDT(), NonlinearSystemBase::computeDamping(), IterationAdaptiveDT::computeDT(), IterationAdaptiveDT::computeFailedDT(), IterationAdaptiveDT::computeInterpolationDT(), FEProblemBase::computeResidualTags(), IterationAdaptiveDT::constrainStep(), TimeStepper::constrainStep(), MultiApp::createApp(), FEProblemBase::execMultiApps(), FEProblemBase::execMultiAppTransfers(), MultiAppPostprocessorTransfer::execute(), MultiAppPostprocessorInterpolationTransfer::execute(), MultiAppVariableValueSamplePostprocessorTransfer::execute(), MultiAppPostprocessorToAuxScalarTransfer::execute(), MultiAppScalarToAuxScalarTransfer::execute(), MultiAppVariableValueSampleTransfer::execute(), execute(), MultiAppMeshFunctionTransfer::execute(), MultiAppUserObjectTransfer::execute(), MultiAppVectorPostprocessorTransfer::execute(), MultiAppNearestNodeTransfer::execute(), MultiAppProjectionTransfer::execute(), MultiAppCopyTransfer::execute(), Steady::execute(), MultiAppDTKUserObjectTransfer::execute(), ActionWarehouse::executeActionsWithAction(), ActionWarehouse::executeAllActions(), FEProblemBase::FEProblemBase(), ElementQualityChecker::finalize(), FEProblemBase::finishMultiAppStep(), MultiApp::globalAppToLocal(), InversePowerMethod::init(), NonlinearEigen::init(), Steady::init(), FEProblemBase::initialAdaptMesh(), FEProblemBase::initialSetup(), EigenExecutionerBase::inversePowerIteration(), Transient::keepGoing(), IterationAdaptiveDT::limitDTByFunction(), IterationAdaptiveDT::limitDTToPostprocessorValue(), EigenExecutionerBase::makeBXConsistent(), Console::meshChanged(), MooseObject::mooseDeprecated(), MooseObject::mooseInfo(), MooseObject::mooseWarning(), PerfGraphOutput::output(), DOFMapOutput::output(), VariableResidualNormsDebugOutput::output(), Console::output(), ControlOutput::outputActiveObjects(), ControlOutput::outputChangedControls(), ControlOutput::outputControls(), Console::outputInput(), Console::outputPostprocessors(), Console::outputScalarVariables(), Console::outputSystemInformation(), FEProblemBase::possiblyRebuildGeomSearchPatches(), EigenExecutionerBase::postExecute(), AB2PredictorCorrector::postSolve(), ActionWarehouse::printActionDependencySets(), EigenExecutionerBase::printEigenvalue(), MaterialPropertyDebugOutput::printMaterialMap(), SolutionTimeAdaptiveDT::rejectStep(), DT2::rejectStep(), MultiApp::restore(), FEProblemBase::restoreMultiApps(), SimplePredictor::shouldApply(), NonlinearSystem::solve(), PicardSolve::solve(), LStableDirk2::solve(), LStableDirk3::solve(), ImplicitMidpoint::solve(), ExplicitTVDRK2::solve(), LStableDirk4::solve(), AStableDirk4::solve(), ExplicitRK2::solve(), TransientMultiApp::solveStep(), PicardSolve::solveStep(), DT2::step(), AB2PredictorCorrector::step(), NonlinearEigen::takeStep(), Console::writeTimestepInformation(), Console::writeVariableNorms(), and FEProblemBase::~FEProblemBase().
Referenced by MultiAppTransfer::direction(), MultiAppPostprocessorTransfer::execute(), MultiAppVariableValueSamplePostprocessorTransfer::execute(), MultiAppPostprocessorInterpolationTransfer::execute(), MultiAppScalarToAuxScalarTransfer::execute(), MultiAppVariableValueSampleTransfer::execute(), MultiAppPostprocessorToAuxScalarTransfer::execute(), MultiAppUserObjectTransfer::execute(), execute(), MultiAppDTKInterpolationTransfer::execute(), MultiAppMeshFunctionTransfer::execute(), MultiAppNearestNodeTransfer::execute(), MultiAppVectorPostprocessorTransfer::execute(), MultiAppProjectionTransfer::execute(), MultiAppCopyTransfer::execute(), MultiAppTransfer::getAppInfo(), MultiAppTransfer::getFromsPerProc(), MultiAppTransfer::getTransferVector(), MultiAppMeshFunctionTransfer::initialSetup(), initialSetup(), MultiAppUserObjectTransfer::initialSetup(), MultiAppNearestNodeTransfer::initialSetup(), MultiAppPostprocessorTransfer::MultiAppPostprocessorTransfer(), and MultiAppMeshFunctionTransfer::transferVariable().
Referenced by execute(), MultiAppUserObjectTransfer::execute(), MultiAppTransfer::getAppInfo(), and MultiAppMeshFunctionTransfer::transferVariable().
Referenced by execute(), MultiAppUserObjectTransfer::execute(), and MultiAppTransfer::getAppInfo().
Referenced by MultiAppInterpolationTransfer(), and MultiAppUserObjectTransfer::MultiAppUserObjectTransfer().
Definition at line 51 of file MultiAppInterpolationTransfer.h.
Referenced by execute(), and initialSetup().
Definition at line 55 of file MultiAppInterpolationTransfer.h.
Referenced by MultiAppPostprocessorTransfer::execute(), MultiAppPostprocessorInterpolationTransfer::execute(), MultiAppVariableValueSamplePostprocessorTransfer::execute(), MultiAppScalarToAuxScalarTransfer::execute(), MultiAppVariableValueSampleTransfer::execute(), MultiAppPostprocessorToAuxScalarTransfer::execute(), execute(), MultiAppDTKInterpolationTransfer::execute(), MultiAppUserObjectTransfer::execute(), MultiAppCopyTransfer::execute(), MultiAppDTKUserObjectTransfer::execute(), MultiAppVectorPostprocessorTransfer::executeFromMultiapp(), MultiAppVectorPostprocessorTransfer::executeToMultiapp(), MultiAppTransfer::getAppInfo(), MultiAppTransfer::getFromsPerProc(), MultiAppTransfer::getMultiApp(), MultiAppTransfer::getTransferVector(), MultiAppVariableValueSampleTransfer::initialSetup(), MultiAppTransfer::MultiAppTransfer(), and MultiAppTransfer::variableIntegrityCheck().
Definition at line 53 of file MultiAppInterpolationTransfer.h.
Definition at line 54 of file MultiAppInterpolationTransfer.h.
Definition at line 56 of file MultiAppInterpolationTransfer.h.
Definition at line 50 of file MultiAppInterpolationTransfer.h.


Two cells of E.M.F. 10 V and 2 V and internal resistances 10 ohm and ohm resp are connected in parallel as shown. Find the effective voltage across R.
What is the electric flux through a cube of side 'a' if a charge q is placed in its centre. Derive an expression by gauss law.
How to solve the word problem question into equation based on linear equation?
Which of the following substance have a tendency to move from stronger to the weaker part of an external magnetic field.
A circus player placed in a wheel on a suspended bridge slips down, causing a landing in a wheel followed by a rise. At one point it breaks off and begins to land. At what altitude does the player break off?
A convex lens makes a real image 4 cm long on a screen.When the lens is shifted to a new position without disturbing the object, we again get a real image on the screen which is 16 cm tall.The length of the object must be a) 1/4 cm. b)8 cm. c)12 cm. d020 cm.
a convex lens makes a real image 4cm long on a screen. When the lens is shifted to a new position without disturbing the object, we again get a real image on the screen which is16 cm tall.


The company's definition of a truly open wireless network is in conflict with how wireless operators do business today.
The idea is that depending on where a wireless user is at any given time, he could be on any number of networks. For example, if coverage is better from Verizon Wireless at home, a subscriber might connect to that network to make phone calls. But he might use AT&T while at work, where the signal is stronger. Price would also be a factor, and operators would constantly be vying in a sort of auction to provide the most competitive pricing for the call.
Meanwhile, users could also access other free or low-cost networks. So if, for example, someone wanted to surf the Web from their phone they could connect via a Wi-Fi or WiMax network. Or people may even be able to connect to a network that uses yet-to-be available "white space" spectrum.
This notion of a device connecting to any network is quite different from how the wireless industry operates today. When people buy cell phones today, they're essentially locked to one provider. A particular provider may have roaming agreements with other cell phone operators, but customers have a contract and billing relationship with one cell phone operator. And if they decide to switch carriers, they usually have to pay a penalty for breaking a contract, and they must purchase a phone that will work on the new network.
Of course, consumers don't have the same issues in the broadband market, where people can connect to any broadband network using any computer, whether it be a Wi-Fi, cable or DSL connection.
Carriers are beginning to offer consumers some alternatives. Apple's iPhone, which is sold exclusively in the U.S. on AT&T's network, also has Wi-Fi. And users regularly choose to surf the Net on Wi-Fi connections. T-Mobile has a service that allows subscribers with Wi-Fi enabled phones to switch between the T-Mobile cellular network and a home Wi-Fi connection.
Verizon Wireless also recently announced it would not require contracts in exchange for consumers paying full retail price for devices. And all four of the major mobile carriers in the U.S. have begun pro-rating contracts so that the penalty for leaving a service before the contract expires decreases over time.
But wireless operators have stopped short of offering truly open networks that would allow consumers to bring any device onto their networks. For instance, Verizon Wireless' Open Network Initiative announced last year isn't really open. The company isn't allowing any device to connect to its network. It's simply speeding up the certification process.
Executives at these companies argue that they need to certify devices to ensure service quality. Recently, T-Mobile CEO Robert Dotson told an audience at the CTIA tradeshow in San Francisco that "even though on the outside (an open device network) looks enticing, there still needs to be a minimum level of control to safeguard security and privacy."
For the meantime, it looks like Google is being forced to play by these carrier rules. Earlier this week, T-Mobile USA launched the G1, the first smartphone to use Google's Android operating system. The phone is set to go on sale in October, but it will be locked to T-Mobile's network.
Google has high hopes for changing the market, whether carriers like it or not.
That said, Google has high hopes for changing the market, whether carriers like it or not. It has been lobbying the Federal Communications Commission and Congress for well over a year to adopt policies that reflect its vision of an open network. Last year it convinced the FCC to agree to add an open network provision in the rules for the 700MHz spectrum auction. And then it helped ensure the provision would take effect by bidding on the spectrum so that it reached a predetermined threshold. It's also been pushing the FCC to open up the so-called white spaces between TV channels for unlicensed use.
Google has also been investing in alternative wireless technology and networks. It's investing $500 million in the new Sprint/ClearwireWiMax joint venture, which is trying to build a nationwide network using WiMax. The company has dabbled in citywide Wi-Fi. It's already attempted to buy wireless spectrum. And it's been investing in its own fiber infrastructure as well in the form of undersea cable deployments, which could eventually be used to create high-speed backhaul networks.
Still, there are several challenges to making Google's open network a reality. For one, device manufacturers would have to cram in more radios into devices to handle all the potential wireless networks that consumers might encounter. While this is not impossible, it does complicate device design and could drive costs up and battery life down. Also, designing devices to seamlessly switch among all those networks is not a trivial task. In fact, users have complained about the iPhone 3G's ability to switch between 2.5G and 3G networks.
What's more, a real-time wireless auction system would have to be in place to manage network usage in Google's ideal wireless world. This actually could be an opportunity for Google, according to a blog on Wired News. The patent explicitly outlines "a transparent auction marketplace with wireless providers bidding in real time to provide the communication services to users." And the blog notes that Google may be well-suited to establish such a marketplace because of its experience with AdWords and AdSense.
One thing is certain, Google has a long way to go before its vision is realized. But as wireless networks handle more data and become more Internet-enabled, it's only a matter of time before openness is forced onto carriers whether they like it or not.


"The aim of the paper is to discuss how the knowledge of the landscape architect can be used to create sustainable school grounds. The paper also looks critically at the professional role and identity of the landscape architect in a participative context. School grounds in Sweden are still, in spite of many campaigns and projects, places with few incentives for pupils and teachers to use other than as a place to run about in and get some fresh air. The demand for developing different methods for involving pupils in all stages of school ground use, planning, building and maintenance, as a means for a long term sustainable solution has noticeably increased over the last few years according to a survey conducted in 2002. Who can help out on this? Landscape architects belong to a profession that has knowledge about places and how they can be used and managed. They are also educated to see and visualize for others how places can change and be developed. These qualities are a potential for new thinking that is today not fully realized in the development of children's environments. In a case study at a secondary school in northern Sweden a new method for participatory planning was tried, so called "knowledge workshops". This method is in part based on Future Workshops, a method for visionary planning developed in Germany, but "knowledge workshops" includes the place itself as an actor and as a base for joint learning. Pupils, teachers, landscape architects and the project leaders from the community worked together over time. This resulted in a proposal for change which was then built. The paper will also address the findings from a focus group of landscape architects in Sweden discussing the role of the landscape architect in general, with a starting-point in school ground development. In what manner does the paradigm of the landscape architect (the first aesthetical standpoint she or he takes) have importance for the final design of school grounds? How much does a common language mean in this context? The "knowledge workshops" which included both children and adults showed that this last question is important. Working together with the place itself as an actor made a difference in how the process evolved, and to some extent in what was built. The question of whose aesthetic preference takes precedence was shown to be a point of debate. Another question of interest was how such newly-won knowledge can, together with different actors be a part of communal learning about a physical, tangible change to a place. Seeing what the obstacles are today against using the knowledge of landscape architects in school ground development and the significance of landscape architects in that process can be a basis for change in teaching landscape architecture. This critical analysis can also be of importance to planners and schools who can then put new and more relevant questions to landscape architects when developing school grounds."
Paget, Susan. "Creating Sustainable Places for Children." In Environment, Health and Sustainable Development (IAPS 19 Conference Proceedings on CD-Rom). IAPS. Alexandria, Egypt, 2006.
Lieberg, M., C. Wingren, A. Pettersson, and S. Jallow. "Spiritual Places in the Urban Contemporary Landscape." In Urban Diversities, Biosphere and Well-Being: Designing and Managing Our Common Environment (IAPS 20 Conference Proceedings on CD-Rom). IAPS. Rome, Italy: Aula Magna Sapienza University of Rome, 2008.
Lieberg, Mats. "Spontaneous Memorials in the Urban Contemporary Landscape." In Vulnerability, Risk and Complexity: Impacts of global Change on Human Habitats (IAPS 21 Conference, Abstracts of Presentations). IAPS. Leipzig, Germany: Helmholtz Centre for Environmental Research - UFZ, 2010.


How can you fabricate a huge number of nanostructures in a split second? Self-assembly is a fast technique for the mass production of materials and complex structures. But before self-assembly is ready for prime time, scientists need to establish ways to control this process, so that desired nanostructures emerge from the unstructured soup of basic building blocks that are fast-moving atoms and molecules.
There are many ways atoms can arrange microscopically to form crystalline materials. Interestingly, materials created from different arrangements of the same atoms may exhibit completely different physical and chemical properties. A method called thin film epitaxy allows scientists not only to fine-tune the properties of known materials, but also to generate completely new materials with structures and properties not found in nature.
Scientists have developed a way to engineer new forms of matter by stacking different types of layers, each only one atom thick, on top of one another.


This chapter discusses the initiation of the process of systematic research synthesis. Without a systematic approach to defining, obtaining, and collating data, meta-analyses may yield precise but erroneous results, with different types of sampling error (biases) and excess subjectivity in choice of methods and definition of thresholds; these devalue the rigor of any statistical approaches employed. The chapter considers exactly the same issues that face an ecologist designing a field experiment. What's the question? How can I define my sampling universe? How should I collect my data? What analyses should I undertake? How should I interpret my results robustly? These questions are considered in the context of research synthesis.


I started off my making some observational notes on the image: The steps have areas of dark/light. The colours include shades of grey, cream, black, brown and blue. Then there is a tiled piece of ground which consists of an even pattern of lines, criss-crossing. Shadows of the trees form silhouettes on the tiles. There is another section of rocks which form a mosaic of white, grey and blue. There is another section of steps but these are made up of small round pebbles, forming an orderly pattern of grey, blue, white and black. Leading down to the water, there are huge rock boulders, which in contrast to the smaller more even rocks and pebbles are uneven, with bumpy surfaces and sharp edges. The water is a great contrast to the rocks, with the reflections of the rocks softening the textures and the light catching the water in swirly patterns of green, blue and white.
i) Starting off using a charcoal pencil, I chose a small section of the steps, boulders and water. I tried to draw simple lines to catch the feel of the different textures. I started imagining how this would translate to a fabric collage with swirly stitching representing the reflections in the water.
ii) I then did another charcoal study of a close-u f several boulders and the water. I was able to use a variety of lines to represent the texture of the boulders and their uneven surface.
iii) Next I looked closer at the section where the stone steps meet the tiled area. I used charcoal pencil again to draw the shapes but this time added silver pen to portray the light catching the stone.
iv) I then continued using calligraphy ink and cocktail stick – materials which I greatly enjoyed using int he previous mark-making exercises. I found it easy to use the cocktail stick with differing amounts of ink to show the texture. By letting the ink run out, I was able to vary the thickness and strength of the lines. This worked particularly well when studying the reflections.
v) I then worked on a small study to try to capture the contrast between four different layers of the photo., using the techniques above.
vi) Lastly, I decided to add some colour and carried out a study of the boulders and water, using watercolour pencils and candle-wax resist to capture the reflections in the water. I was very pleased with the way this worked out and feel the wax-resist was a useful technique to create the watery effect.
The next image selected is a photo of a wall. The top section of the wall is made up of huge rock boulders, tessellating but uneven. The rocks change from grey/black to orange, brown, with speckled patches of light/dark. Then there is a step of painted concrete. The vertical drop of the step had flaking paint forming an interesting texture and a variety of colours. Some areas are smooth, others gritty, or sand-like. The paint forms a dripping effect with various shades of brown, yellow and orange.
I started off using graphite pencil. I chose a small area of the photo and worked hard to show the different textures. I was able to show the contrast between the heavy boulders and lighter texture of the concrete area by using heavy/light strokes of the pencil.
Next I made a study of the same area using my favourite materials – Black calligraphy ink applied using a cocktail stick. The cocktail stick worked well as I was able to portray the feel of the grittiness by making small dots and circles.
I then started to think about colour.
Continuing with a technique tried with the last image, I used candle wax resist to show the areas of light/dark. I then added watercolour pencil to show the areas of changing colour and then applied water on a small brush over some of the areas. this worked quite well but I felt I had not shown the contrast between the two main textures very well.
Next, I tried acrylic gouache to make a bolder drawing. I applied the paint with polystyrene packing pieces for the boulders and the end of a brush for the flaking paint. I then highlighted areas with calligraphy ink using the same printing implements. I was pleased with the way this study worked out and wanted to see how it would translate into a collage.
Using pieces of black tissue, previously bleached, white paper sponged with heavily diluted ink and beige paper sponged with ink, I made a collage on a background of black paper. I was really pleased with the way this worked out.
I enjoyed working on this image and can think of some ways I can further develop my design ideas. I pulled out an earlier exercise I did of graphite pencil shaded over rough textured watercolour pencil and rectangles of graphite rubbed out in places – and thought this would be a great way to represent rocks.
The last image I worked on was of the rusty boat. This was my favourite and I kept wanting to try new ideas. I really had to reign myself in as I could spend weeks on developing ideas from this image!
The photograph was taken by me of a rusty boat in a boatyard in Ito, Japan at New Year. I was drawn to the colours and texture of the layering effect of the peeling paint which revealed the layers underneath. The blending colours created an interesting effect and I was immediately inspired, thinking of different ways in which the image could be developed into collage, printed fabric and stitch.
I first of all, I made some written observations of the effects in the image. Pink turning to blue, dark shadows revealing the layers beneath. Pink, blue, green, dark blue and brown rusty smears.Speckled colours blending to green, green turning to yellow and to orange. Brittle, crispy, crunchy, fragile, delicate and crumbly.
I started by drawing a sketch of a section of the image, using ink and cocktail stick. I then applied watercolour pencil, adding water by brush to blend some areas.
I did not look too closely at the photo as I did not want to be tempted into attempting a close observation drawing. Rather , I wanted to create the ‘feel’ of the image as instructed in the manual and I think I achieved my aim! The colours I used were inspired by the photo but not ‘true’ to the photo.
ii) I then took very small sections of the drawing and did some ‘studies of corrosion’ in ink and water-colour. These did not relate directly to the original image but from my drawing.
iii) I then attempted collage inspired by the image. I layered tissue paper, rough silk tops, and bleached paper napkins onto kitchen roll. I added some tea-stained tissue, some twine and then added highlights in black pen. I was attempting to portray the fragile layers of the flaking paint and was pleased with the result.
Until now, all the exercises have involved materials, media and techniques already familiar to me and I am ready to come out of my ‘comfort zone’ and try some new techniques and materials.
I have been browsing through a lot of blogs, books and watching several podcasts on various textile techniques and was inspired to have a go at ‘slashing’ to create the layered effect with fabric. I layered pieces of fabrics, paper, old cut-up tights and bits of thread inside a folded piece of white calico and machine-stitched all around the edge and then up and down all the way across the fabric. I then cut through all the layers (being careful not to cut through the bottom layer of calico to achieve the slashed effect. This was great fun and though I am in danger of veering off-course, I am so pleased that I feel inspired enough to try these techniques after many years of suppressing my creative tendencies!


News update: I have been confirmed as a judge at this year’s (2015) “Golden Target Awards”, the “Oscars” of the Public Relations Institute of Australia (PRIA), with judging commencing in mid-July.
I have no doubt that if Australian-Jewish director Ariel Kleiman’s film “Partisan” was produced in a central or eastern European language such as Russian, Ukrainian or Georgian rather than English, it would be touted as a hot prospect for Best Foreign Language film at next year’s Academy Awards. It’s that good.
Shot partly in Melbourne (at a Mount Eliza winery) and partly in Georgia – yes, the country of Georgia, located between Russia, Turkey, Armenia and Azerbaijan, “Partisan” is set in a mythical “middle Europe”. It features a multicultural cast headed by French actor Vincent Cassel, whose breakthrough role was the rage-filled Jewish character of “Vinz” in Mathieu Kassovitz’s “La Haine”. Here he plays Gregori, the charismatic leader of a cult-like sect where he is the alpha (and only adult) male, part Pied Piper, part saviour and part unquestioned intimidating master to a number of needy and vulnerable women and their children, who he both protects and preys upon.
If viewers are put off by the language, it would be a shame, for Kleiman has created one of this year’s most haunting and disturbing films, one that starts slowly and gradually accretes to create a picture of emotional horror. With its creeping sense of dread, “Partisan” has much in common with “Ex_Machina” (currently screening), Alex Garland’s Frankenstein-like meditation on the potential horror of artificial intelligence. This is not classic horror like last year’s acclaimed “Babadook”, but something that – for me at least – operates far more effectively.
Part of the power of “Partisan” is in our experiencing much of the story through the increasingly less innocent eyes of a young boy, Alexander (Jeremy Chabriel). This perspective operates in the same way that we viewed the world through the eyes of Kodi Smit-McPhee’s character in “The Road” (also by an Australian director, John Hillcoat), a film that haunted me for months afterwards. Gregori has raised Alexander from birth, and the tension in “Partisan” arises when Alexander begins to question his upbringing and role. Because here is the catch (minor spoiler alert): Gregori has trained his young charges for a particular mission: to conduct assassinations, reminiscent of the film “Hanna”.
“Partisan” falls squarely in the category of films about cults; its closest recent neighbours are “Martha Marcy May Marlene” and “The Master”. Because I lived in California during the times of Jim Jones’ People’s Temple massacre and the Charles Manson murders, I find any strong evocation of cults particularly chilling. “Partisan” captures this claustrophobia.
The beauty of “Partisan” – and it is physically stunning, shot by Germain McMicking, who won a special award for cinematography for this work on “Partisan” at this year’s Sundance Film Festival, also lies in its ability to illustrate its emotions through simple visuals.
Director Kleiman – at the tender age of 30 and working with his co-writing partner Sarah Cyngler – has full control of all the elements of his film. Aside from the cinematography, he even commissioned three original songs for karaoke sequences in the film. The film’s themes are universal – parenting, mentoring, human need – but “Partisan” has a dark core that will not appeal to everyone: it is rated MA15+ “for strong themes and violence”, for good reason. Kleiman is a director to watch, an assured auteur with a powerful imagination whose future accomplishments are likely to be many.
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TAMPA, Fla. -- Two preseason games into the 2018 season, the Tampa Bay Buccaneers starting running back is Peyton Barber. That's despite the fact the Bucs used a second-round draft pick on Ronald Jones II.
"I'm the starter and I plan on keeping it that way," said Barber, an undrafted free agent out of Auburn in 2016. He started four games last season for the Bucs, and coach Dirk Koetter has praised him for his ability to finish runs.
"Peyton has done an excellent job. He's hungry," running backs coach Tim Spencer said. "I like his mindset this year. I've always liked his mindset, but I just think that this year -- he has a goal and his goal is to be the No. 1 cat -- and so far, I haven't seen anything different."
Barber is averaging 5.3 yards per carry this preseason and scored a touchdown against Miami in Week 1. He also entered camp at 222 pounds after dropping 10 pounds in the offseason. The lighter frame has made Barber quicker, yet he's still able to fight for tough yardage inside and isn't going down after contact, something he showed a knack for last season.
"It's important," Barber said. "That lets the defense know that I'm going to be coming all day. Setting the tone."
Barber will be the guy the Bucs turn to on first and second down and in short yardage. Though the Bucs have gotten away from using a bell-cow back, believing it results in too much wear-and-tear, they do feel Barber is capable of being on the field for every down if needed.
"That was one of the things he needed to improve on obviously," Spencer said. "He's at that point now where I feel comfortable and we all feel comfortable that he can get it done."
Like Barber, Jones also scored a touchdown in the first preseason game, but has produced 11 rushing yards on 12 carries this preseason. Aside from Barber simply outperforming him, Jones' biggest obstacle would be his hands. He's had several noticeable drops in practices and hasn't caught a pass in the preseason, either.
"In college, there was probably a reason why he was only thrown the ball 17 times," Spencer said. "But I think he's worked on his game, he's worked on his hands, his eyes. To me, [the thing] I see with him, is eye-hand coordination and following the ball, concentrating and believing you can get the job done.
"He's never going to be the best catching guy on the team, but he certainly can improve on catching the balls that we want to throw to him -- especially the routes that we have," said Spencer. "With his speed, we need him to be able to catch the balls down the field."
During joint practices with the Tennessee Titans, Jones did have multiple catches on go-routes, about 25 yards downfield, hauling them in over his shoulder -- a step in the right direction.
"Just reps and absorbing contact, just coming down with it. Like Coach [Spencer] was helping me with my hand placement. It's really more your eyes," Jones said, adding he's also growing more comfortable with the playbook. "It's becoming more natural, but not enough natural. I'm still working on it."
Veterans Jacquizz Rodgers and Charles Sims are battling it out for the third-down role with Rodgers having the most versatility. Rodgers, despite standing at 5-foot-6, can line up on first and second down and contribute as a rock-solid pass protector.
"Be a guy they can plug in anywhere, and go out there when your number is called and make plays -- I live by that," said Rodgers, who can also line up most anywhere on special teams.
Though Rodgers is more of a chameleon, Sims, who suffered a knee injury against the Titans, is strictly a third-down back. Sims has in the past gotten looks as a starter. A converted wide receiver in college, he's a great route runner, has natural hands and works best in space.
It's tough to say how many running backs the Bucs will keep on their 53-man roster, especially with injuries at cornerback and defensive tackle. But rookie Shaun Wilson, an undrafted free agent out of Duke, has made a memorable impression.
"He's got great hands," Spencer said. "Shaun's a tough kid. Shaun's one of those guys where if you told him he can't do it, he's gonna do it. He's gonna get in there and he's gonna fight tooth and nail, arms and legs -- whatever it takes, he's gonna throw it in there."
Wilson, who at 5-foot-9 and 185 pounds is not an in-between-the-tackles player on every play, runs with good leverage.
"He's small in height, but he's got really good quickness, really good vision. He can burst and he's smart," Koetter said. "He also makes guys miss. He's been an impressive guy in camp."
Wilson missed the first preseason game, but did see a lot of action on kickoff and punt returns in the second. He also rushed for 17 yards on five carries, including a 9-yard run.
It's unlikely the Bucs would carry five running backs (they had four last season). Barber and Jones should be 1-2. The No. 3 spot will come down to Rodgers or Sims. At this point, Rodgers looks to have the upper hand, and Sims' injury could make that decision easier.
If Wilson shows enough on special teams, he could earn a 53-man roster spot. The Bucs could sign him to the practice squad, assuming he cleared waivers and didn't sign elsewhere.


There are many opinions and techniques for recording the snare drum. Some engineers prefer the standard two SM57 approach while others may aim for using the overheads for the snare sound. In addition other engineers may use a single LDC (large diaphragm condenser) microphone for a snare.
In truth anyone of these techniques could work and just about any combination of the techniques could work. What matters is what context is the snare being played? If you are going for a hard hitting rock track then you would mostly use the microphones placed right up in the snare. If however you are doing jazz then you may use mostly the overheads with only a tiny bit of the snare accent mics blended in.
However before we can really decide which technique is better for a given situation we first need to understand the techniques themselves!
When recording the snare you have to at least look at the most widely used snare drum technique of a mic on top and a mic on bottom; usually a SM57. When in doubt this will be the go to technique for any engineer recording a snare drum.
The core of this technique is that a microphone placed on the top and bottom of the snare, aimed either down into the rim of the snare or aimed across the head. You will always use a dynamic microphone for this job, period; the sheer volume produced by a snare will overload most condensers. Because you need a dynamic and you are putting your mics right in the firing line of the drummers sticks, you usually will reach for and SM57 or equivalent microphone that could take the potential abuse.
What makes this technique so wonderful is how easy it is to tweak and how many sound options you can get for mixing. Very small adjustments on the mic placement can have huge audible differences with this technique. If you aim the top mic directly into the batter head near the rim then you will end up with a lot of focus on the harmonics while aiming more across or pulling away from the edge a little bit will balance out the harmonics and fundamental pitch.
This same idea also goes for the resonant head underneath as well but there is another consideration that you need to take into account with the resonant head; the snares. Depending on where you aim the underside mic you can either get a lot of snare crackle or not much at all.
While the crack of the snares can be nice, if the snares are cheap ones that ring too long or are easily excited by the toms, you will end up with a fizzy annoying high end ring in your snare sound. Generally speaking, the cheaper the drum the more you will not want to directly mic the snares themselves.
One final note, phase. You have to be very careful with this technique in regards to the phase of the two microphones. Chances are the mics will be almost 180 degrees out of phase and one of the mics will need phase inverted before you can properly mix them. Always be on the lookout (hear out?) for phasing problems!
While the previous technique is great for a whole wide array of situations, it doesn’t always sound the most natural. The reason it tends to sound a little less true to the drum itself is because the sound has less time to develop. We never listen to a snare drum with our ears right up in the drum but we usually place a microphone there.
Simply pulling the microphone back will render a much more natural sound hence why we usually use the overheads for this situation. The drawback of course is that we do not have anywhere near as much processing control of the snare. However we can choose a wide array of microphones for this job since we are far enough back to now utilize ribbon and condenser microphones.
The trick with technique is balancing out the rest of drum kit. If you need a really tight stereo image and want a slightly more present snare sound then you need to get the overhead lower and closer to the kit. If you are ok with a little more bleed and want a more roomy sound then pull your overheads back.
This technique is more of an overall drum kit technique but can be an awesome alternate technique and bears mentioning. This technique was invented by engineer Glyn Johns and requires a tape measure to ensure perfect phase.
Essentially you need to place an overhead microphone directly over the center of the kick pedal and another aimed directly across the kit at the drummer’s right side.
The top mic needs to be 40 inches from the pedal and the side mic needs to be 40 inches from the center of the snare. Once you have these aligned you add a single snare accent mic in the place of your choosing.
While it simply is just a variation of the overhead technique, it has very specific guidelines which is why I believe it deserves its own place. I would highly recommend condensers or ribbons if you have a matched pair for this job and use more colored microphones if the kit is less than adequate sounding on its own.
You do need to be careful with the panning in this situation, as we do not have an even stereo field. I would suggest panning the top microphone halfway to the right and the side mic all the way to the left; adjust to taste.
This technique is a wonderful option for those of you who want an up close snare sound but maybe are not digging the old reliable. Essentially what we do here is mic the snare drum from the side to get more of the sound of the drum as a whole and not just the heads.
having troubles with hi-hat bleed then use a hyper cardiod pattern since it has good side rejection.
Generally with this technique you control the tone by where the microphone is aiming and how high or low it is relative to the drum. If you aim your mic directly at the shell you will get bright sound and more full balanced tone when moving it up towards the rim. If you move the mic either closer or further from the snare then you can control how much room and drum bleed you have in the snare mic and shape the tone a little as well.
Keep in mind of the porthole on the snare so when the air escapes the drum it does not blow right into the diaphragm.
Snares are somewhat like distorted guitars when it comes to their harmonic content and what space it takes up in the audio spectrum; they take up a lot! However unlike a distorted guitar, they decay quickly and do not change pitch mid song (usually).
drum is since they only last for a fraction of second. Now you cannot re-pitch a snare too drastically, but if it isn’t sitting tight in a mix you can adjust the perceived pitch enough to make it sit a little nicer.
If you have too much kick leakage high pass everything below 100 Hz (usually a good idea anyways).
For a thicker or thinner snare play around in the 120-250 Hz region depending on the drum. This the region where you generally can re-pitch the drum to some extent.
When dealing with harmonic ringing look around the 300-1000 Hz range to either accentuate the ring or try and tame it.
If you need more or less attack examine the 2-5 kHz region. Reducing this range will give you a smoother fatter sound while boosting this range will give you more crack and punch.
If you need more sizzle or air to the snare look at boosting around 10k and up. Obviously if you have too much then just reduce this range instead.
cleaner more clinical style EQ, probably one that is linear phase. If however you think it really needs some color to cover up its blemishes then a program EQ like a Pultec clone would be a good choice. If you need more color or material to work with then perhaps some harmonic saturation is in order.
Harmonic saturation can be killer on a snare for either fattening up the low end or really bringing out the crack. There are many harmonic saturation plugins out there to choose from but to be careful. Some of these plugins are essentially just static EQs and waveshapers that don’t sound all that pleasing.
If you place your saturator before the EQ it will give you more harmonic content to work with inside your EQ where as if you place it after the EQ you will accentuate your EQ a little more. I highly recommend using a non-linear stateful style saturator that only adds harmonics based on what kind of content is put in it.
What this means is it will only add harmonics relative to what is already there and not just add the same kind of harmonics regardless of whether it is a bass guitar or a flute. A very good free VST for this is Variety of Sounds ThrillseekerLA compressor, which has a separate harmonic stage. Simply turn off the compressor portion and you have beautiful stateful saturation.
bring the gain up and make the snares sustain more pronounced.
For a sharp crack and very little sustain set the attack to somewhere around 10ms or so and give it a slower release of around 10-20ms; this will compress the signal after the initial attack has already happened. By doing this you end up compressing the sustain and place more emphasis on the attack.
◦ When using the above techniques make sure your Threshold setting does not cover the entire range of the snare; you only want the compressor to react to the peaks for the above techniques. If however you really need to smash the heck out of the snare then drop the Threshold so that your compressor will be more sensitive to incoming audio.
◦ If you need more gentle leveling as opposed to hard compressing or limiting then make sure you do not overdue it on the ratio. While a simple 2:1 ratio might seem small, it is in fact still a pretty decent amount of compression. For jazz and other lighter music I would highly recommend keeping an eye on the ratio if you really feel the need to compress.
which while may say they can react around 5ms, may still be a little slower to the nature of optical compressors. I would highly recommend a VCA or FET style compressor for snares since they are so transient in nature and need something that can react to them.
While we have gone over compressors there are still one more volume and dynamic style effect we can use to our advantage, the transient shaper. These tools analyze the incoming audio and either accentuate the peaks or dull the peaks volume so that the attack appears either sharper or smoother.
For a tight smooth room sound use a fairly diffuse ambience (if using a convolution reverb a wood room works well) and set a tiny bit of predelay; only a few ms if that. Excellent for pop rock, funk, etc.
If you need a tight but more live sounding room use a ambience that replicates a concrete room. These generally are less diffusive and have more high-end content than the wood room. This can work excellent for metal drums that are not blazing fast.
For a bigger but still roomy sound use the above techniques but add just a tiny bit of delay before the ambience plugin. This will make the room sound large but not hall sized. This setup can work well if you trying to get a sound somewhere between a studio and a small stage.
If you need a soft pad like reverb in the background then add a nice long diffuse reverb, probably a second or two long. Next bring it down in volume so it blends into the back ground; good for modern pop ballads which still need a fairly dry drum sound.
When you need a reverb for a rock ballad then add a nice large tailed reverb and adjust the top end content to make it sound either more like wood or like stone (less high content vs more high content). Also be sure to adjust the diffusion between highly diffuse and barely diffuse to make it sound either more wood or more stone.
Finally for a big stadium sound you will need a long fairly diffuse reverb with a decent bit of delay before hand to replicate the shear size of a stadium or arena.
If you have any questions please feel free to email us at Alpine Mastering through the Contact page on this website – we are always happy to help you maximize the sonic potential in your art and records.


1. The woman is friendly who lives next to me.
1. The woman who lives next to me is friendly.
2. The man stole from the houses was arrested by the police.
2. The man who/that stole from the houses was arrested by the police.
3. The girl was friendly whom I met.
3. The girl whom I met was friendly.
4. The book is mine that is on the table.
4. The book which/that is on the table is mine.
5. The man whom I saw him was Mr. Jones.
5. The man whom I saw was Mr. Jones.
6. The dog bit me was a stray dog.
6. The dog which/that bit me was a stray dog.
7. She is the woman about who I told you.
7. She is the woman about whom I told you. / She is the woman whom I told you about.
8. The music to that we listened last night was good.
8. The music to which we listened last night was good.
9. The person who talking to me was my former office colleague.
9. The person who/that was talking to me was my former office colleague.
10. The books are on that shelf are mine.
10. The books that are on that shelf are mine.


Why work hard to collect good seed?
In agriculture, collecting seed from superior parent stock has been practiced for thousands of years. This technique results in higher yields and environmentally durable plants. This concept, however, has yet to gain widespread acceptance in forestry practice. To maximize yields and quality of trees for plantations, agroforestry, and other uses, the following principles for collecting seed should be observed.
In forestry, as in agriculture, the quality of offspring plants improved populations will result if the seed used to produce them was collected from superior individuals, stands or orchards. Seed quality is measured in two ways. One, by the physical quality of the seed and secondly by the desired physical traits of the resultant mature tree. The benefits of using quality seeds, chosen from selected parent trees, are twofold: improved survival and greater economic returns.
Seeds from healthy, well-formed trees provide greater assurance that resulting stock will have good form, survive and better resist stressed conditions due to marginal sites, frequent cutting, or harsh climates. These adverse conditions typically weaken all but the strongest trees, making them vulnerable to insects, fungi, parasitic plants, and diseases. More important, because of the long-term resource investment and land and labor commitment in forestry, high survival rates of good quality trees is a must. In agriculture, farmers can recoup their loses after a poor season, or even two. Trees, however, occupy a site for years. Therefore, any reduction in growth or quality from planting inferior stock represents a lost opportunity, which can be measured in time and capital, for as long as a tree occupies a particular site.
For the second benefit, economic return, the investment in selection will be more than compensated for by higher product yields over shorter rotations. Better yields result in more building materials, higher fruit production and quality, faster fuelwood growth, and quicker and more prolific regrowth after lopping.
Effective seed selection can create success, even though sophisticated techniques may not be used. Any attention given to seed source will be a measured improvement over current practices. In addition, careful seed handling practices must be included as part of the seed collection program. Such practices include transport, seed preparation, handling, cleaning, grading, and seed testing. Disregarding these practices will result in damaged seed or allow the inclusion of unwanted or excessive amounts of foreign materials, which may hinder germination and plant production.
The following sections in this bulletin describe how to develop a system of proper seed collection and handling practices.
Too often in large planting programs the task of seed collection is an afterthought, typically left until the last minute and done hurriedly by unskilled or untrained labor while final nursery preparations are being made. Small-scale planters usually have access to left-over seeds from large programs. In either case, little consideration is given to seed quality, form, or location of the parent stock. Sometimes, to satisfy the requisite seed volume, nursery managers purchase bulked seed from villagers. However, villagers tend to collect from the nearest trees or stands, which generally include immature, diseased, distressed and otherwise inferior seed. And, if seeds need to be collected from the crown, villagers will choose the easy-to-climb trees, which are typically small and misshapen. Such trees would not normally be chosen as prime seed source candidates. Also, in some species a single tree will produce a large amount of seed in some years. Such a harvest may satisfy the bulk requirement, but would be genetically dangerous because only one phenotype is represented. This technique causes problems for both large- and small-scale planters.
Either approach, using untrained labor or collecting seed from a single tree, can be a critical mistake. Such practices often result in low survival, substandard trees, and a poor economic return for the time and work invested, for example, nursery and site preparation costs. Instead of an impromptu search or purchase from unknown sources, any seed collection, both large-scale and small-scale, should be a developed program of scheduled activities overseen by knowledgeable individuals. This is especially true for those involved in large-scale planting programs. Those involved in small-scale plantings can often request advice from nearby large-scale planters. These essential activities include selection of preferable parent trees; preparation of equipment including provisions for handling, transport, extraction, testing, grading, and storage; recruitment and training of workers and; seed sampling and quality monitoring. A timeline and workplan for the collection itself must be developed in conjunction with overall nursery operations. More important of these is the selection of preferable parent stock. This can be accomplished by an able person who can distinguish between desired and inferior seed sources. This person, in turn, can supervise field collection crews during harvest. Incorporating many of these activities often requires the level of funding available to large-scale operations. Nevertheless, even the small-scale planter should apply the principles as best possible whenever collecting seed.
"The choice of seed source is one of the most important decisions faced by the forest manager. An error in judgment can lead to crops with poor stem and branch form or prone to pests and diseases. Within the genetic constitution of the seed is the potential for either good or poor tree growth, and since even small increases in growth rate or improved timber quality can lead to a much enhanced return on investment, the advantages of using the best available seed from which to grow the planting stock are considerable." Hibberd, P.G. (Forestry Commission Handbook 6: Forestry Practice) HMSO London, 1991.
Why is it necessary to collect only from certain preferable trees?
Tree improvement programs worldwide have shown that seed collected from trees with particular traits tends to produce trees with similar traits. One can correctly assume that if good parent trees are selected, then most of the resultant offspring will be of desirable quality. Yet despite this concept's proven value and wide understanding, it is seldom applied in the field. To correct this shortcoming, simple parent tree selection guidelines should be developed. These would identify the desired traits and specify the parent trees that reflect those traits. Such traits might include straight trunks, fast growth, and better form. These guidelines are normally met in national or company research programs, but following them will benefit all planters who are careful about the source of their seeds. The traits in turn are chosen to reflect the ultimate desired use of the tree, including building materials, windbreaks, shade, fuelwood, or erosion control. At the same time, these guidelines should not be made cumbersome. For the benefit of those individuals collecting seeds, the guidelines could be a condensed set of simple criteria. Indeed, immediate benefits can be derived from using even the most basic concepts, such as selecting trees of good form and vigor and avoiding trees that are poorly developed, diseased, dying, or are isolated from others of the same species. These simple methods should be applied to large and small programs.
Collection strategy includes area, number, and spacing.
While it is important to collect seed from the best parent trees it is also important to gather seed from several parent trees. Collecting seed from several parent trees assures a diversity among seedlings being planted. Whether the program is large or small, maintaining diversity is important and will help guard against pest epidemics. To obtain adequate diversity, seedlots should be collected from a number of trees within a species' range. Researchers have yet to determine an ideal number of trees per seedlot.
In plantations and along roads more emphasis should be placed on collecting from the best trees. In all cases care should be taken to collect seed from several trees representative of the best parent stock. Researchers have yet to determine an ideal number of trees per seedlot, i.e., those seeds that will be used in one planting. However, most agree that collection should not rely on only one or two individual trees. According to some sources, a minimum of 15 to 25 mother trees per bulked seed source is preferred. Furthermore, collection should cover a broad geography, including the environmental extremes at the edge of the range. Seed selected from a narrow sampling of trees should be avoided as this will limit genetic diversity. Keeping a proper distance between selected parent trees is also vital. During natural regeneration of some species, seeds fall near the parent stock. In time, inbreeding may occur, which will result in lower quality individuals. To reduce the chance of collecting a seedlot predominated by half-siblings, a 100-meter distance between collection trees of the same species is recommended. This practice is especially critical to species that are lopped or coppiced as a method of harvest and regeneration. The temptation to forego a minimum number and spacing strategy is perhaps greatest during years of abundant seed production. Here, a large seed quantities are available from relatively few trees. At such times, an even greater effort should be made to ensure genetic variety. Even better, abundant seed years can be opportune. When properly cleaned and prepared, seeds can be stored for several years. Stored volumes of good seed will help ensure supplies during leaner production cycles. Where possible, all large-scale planting programs should have at least two years' seed supply in storage. Conversely, leaner seed years present other challenges. During such years shortfalls will occur and the urge will be to collect for quantity, without regard to quality. If at all possible, seed collection during lean production years should be minimized.
Aside from genetic and site qualities, other considerations must be factored into the collection strategy. For instance, only mature seed from ripened fruits should be gathered. Harvest schedules must account for the different times at which fruits from various species ripen. Depending on species, maturation can last between two to six months. To help determine ripening, periodic surveys of the selected stands is suggested. Surveys should begin after flowering, as is the practice with cocoa. To prevent any false readings, specific sample trees should be marked and used throughout the process. The surveys will also serve as an early indication of the season's expected seed volume and quality. In addition, field surveyors can detect early infestations of insects, disease, or other seed predators. With such information, the harvesting strategy and schedules can be adjusted to accommodate any foreseen hindrances.
Aside from desired end-use traits, the tree must adapt to its growing site. In particular, it must withstand periodic harsh conditions, such as drought, and be able to grow in poor soils. Physical traits alone may yield few clues as to site adaptability. Here, environmental distinctions may help.
The collection staff should note even the slightest variation throughout a species' range. Topography, soils, microclimate, associated vegetation, and man-caused factors such as perennial grazing may all influence how a species conforms to its surroundings. In overall location, a species typically grows best in the middle of its range and fares less well at the edges. However, seedlots should reflect all site variations, thus assuring that no one habitat is relied on too heavily. But some cautions are needed when sampling for habitat. When associated plants are used as site indicator species, one must discern between natural conditions and man-made alterations. For example, continual grazing can heavily degrade a site, even to the point where it changes the vegetative makeup. In addition, extreme dry or wet areas should be excluded if not within the normal bounds of a species' requirements. During collection of particular stands, efforts should concentrate on trees that comprise the stand's perimeter. These individuals produce better quality seed. Aside from natural areas, man-made stands should be reviewed carefully before selection as a seed source. For example, early reforestation efforts may have given little thought to seed collection, thus producing inferior parent trees to those found in natural stands. Or, the species planted on the site may not be well suited for the area. Whenever possible, historical data or records should be referred to for such stands.
Collect seedlots from between 15 and 25 individuals that are spaced at least 100 meters distance from any other collection tree of the same species.
Choose trees in vigorous health and avoid any that are diseased, suppressed, deformed, environmentally stressed, or in otherwise poor health.
Collect from trees that are well formed and either dominant or co-dominant in the canopy.
Avoid individuals that are isolated from others of the same species.
Harvest only mature seed from ripened fruits.
To ensure genetic variation, collect fruits equally from all parts of the crown--top, sides, and bottom--as these parts may have been pollinated at varying times from different sources.
Collect throughout a species' normal habitat, noting variations in site.
Man-made stands, including live fencing, plantations, or windbreaks, should be carefully reviewed as to their establishment before being selected as a seed source.
Parent tree selection in the field is best done as a planned team effort coordinated by a trained person. This selection of preferred trees serves to eliminate errors that would otherwise be produced by last-minute collection efforts. In addition, a planned, timely program allows for the full use of available people and resources. Development of the collection strategy includes a series routine screenings of potential parent stock. The series is broken into three progressive phases.
Phase one is done well before the onset of flowering. Given simple guidelines for site selection and appearance, general laborers search for appropriate stands. Locations of such are recorded, along with general descriptive information.
Phase two involves technical staff. Here, the identified stands are reviewed for their potential as a seed source. The review includes analysis of the site makeup including soils and topography, species composition, volume and spacing, and age, size and health of the trees. Initial selections are made as to potential parent stock. These trees are marked for further study in phase three.
In phase three, trained professionals examine the marked individuals for a final selection. The trees are analyzed for their physical characteristics, including their form, branching, growth rate, dominance, crown cover, health, and any clues as to their seed productive capabilities. Before the final candidates are chosen, additional criteria are again considered. This includes the previous mentioned spacing preference of at least 100 meters between individuals of the same species. And, preference will be given to those trees located in the stand's perimeter. Finally, selected trees are marked and their location noted. Monitoring will increase as flowering begins and continue through the seed harvest period. Monitoring includes volume and quality of the seed as it matures, in addition to any indications of pest infestations including insects and disease.
Seeds are rarely taken directly from the collection site for immediate planting in the nursery.
Instead, they must first undergo a preparation that will ensure proper germination and help eliminate bad or damaged seed. Preparation includes all activities from collection to sowing. These activities cover transport, sorting, extracting, cleaning, testing, and grading. In addition, seed harvesting and sowing periods are often months apart, which requires adequate storage facilities. The facilities must protect the seed stock from the weather and intrusive pests such as animals, insects or molds. In some instances, proper temperature control may also be required. This is especially true if seed is to be kept over a number of years.
Once the fruits are picked or collected, they must be transported directly for seed processing. Any lag time in the field could cause desiccation or predation by various seed pests. The seeds must also be well-protected from the weather to prevent excessive contact with moisture, which may prompt early germination. In addition, because of the variation in harvested fruits, handling techniques must flexible. Those in charge of collection must have adequate knowledge as to each species' requirements and limitations during transport. For example, while the hard coated seeds of most leguminous species travel well, other seeds are more fragile and require greater handling care.
The nursery manager must have facilities readied for seed preparation at the time of collection. Such facilities should be located at the nursery site, thus eliminating the need for further transport before sowing. Seed extraction should occur as the fruits arrive from the field. Again, any lag between collection and preparation will cause the seed to degrade or spoil. Depending on species, equipment for both dry and moist extraction may be needed. Dry extraction requires appropriate sorting and drying areas, tumblers, and screens for sieving. Moist extraction calls for a method of macerating the fleshy fruits, followed by drying and cleaning of any remaining foreign materials.
In either case, all inert materials must be removed as these can result in poor germination or hamper storage ability. Also, the rate of drying and moisture content must be carefully monitored during the drying process. Seeds dried too quickly may become damaged. While small-scale planters may not have access to sophisticated equipment for drying and cleaning seeds, they should aim to remove as much foreign material as possible. After extraction, the pure seed is then graded. Grading helps ensure a more homogenous seed set, which in turn will produce more uniform growth in the nursery. Grading is done either by seed size, weight, or a combination of both. Actual seed size within the same species will vary due to a number of factors. The goal is to eliminate undersized, immature, or deformed seed. This usually can be done by hand if great quantities are not required. However, graders must be provided samples of the desired well-graded product to use as a guide. In addition to grading, seeds are tested for germination rates, and are examined for phytosanitary concerns and species purity. Using these factors, the forester must develop criteria for consistent seed certification. No matter how carefully done, collection efforts in the field will be nullified if inconsistent methods of grading and testing are used from one seed lot to the next.
If the prepared seed is not used within a reasonable amount of time, adequate storage must be provided. As noted, most leguminous seeds store well in normal conditions, provided they are properly cleaned, dried, and protected. Such prepared, intact seed can be handled and stored without fear of damage. However, if storage is required for several years, special facilities, such as cold storage, may be needed for some species. On the other hand, if germination begins, different measures must be taken. Here, the seed ceases dormancy and begins to use stored nutrients for survival. At this point, its shelf life is drastically reduced. Thus, it is important to closely observe the condition of the stored seed and monitor it periodically to ensure the storage environment remains intact.
Why collect seed from several provinces?
Differences in how trees adapt to environments is often more important with a species than among species. There can be important differences in growth between seed sources from different geographical areas and environments. The areas and environments in which stands have developed through natural selection are call provenances. The growth, measured in height, in tropical hardwoods of the most vigorous provenances can be 30 to 50 percent greater than the growth in the least vigorous provenances. Unfortunately, there are very few tree species that have been adequately explored in their center of origin and studied in provenance and progeny tests on multiple sites, leaving much uncertainty about provenances which are intended to represent an entire species. Perhaps the most striking example of this comes form the use of Acacia mangium in Sabah, Malaysia, where ultimately thousands of hectares were planted from seed collected from one tree. As a result, growth rates of third generation were one-half those of the first generation.


Let X be a real Banach space and G1; G2 two nonempty, open and bounded subsets of X such that 0 \in G2 and G2 \subset G1. The problem (*) Tx + Cx = 0 is considered, where T : X \supset D(T) \rightarrow X is an accretive or monotone operator with 0 \in D(T) and T(0) = 0, while C : X \supset D(C) \rightarrow X can be, e.g., one of the following types: (a) compact; (b) continuous and bounded with the resolvents of T compact; (c) demicontinuous, bounded and of type (S+) with T positively homogeneous of degree one; (d) quasi-bounded and satisfies a generalized (S+)-condition w.r.t. the operator T; while T is positively homogeneous of degree one. Solutions are sought for the problem (*) lying in the set D(T + C) \cap (G1 \ G2). Nontrivial solutions of (*) exist even when C(0) = 0. The degree theories of Leray and Schauder, Browder, and Skrypnik as well as the degree theory by Kartsatos and Skrypnik for densely defined operators T; C are used.
The last three degree theories do not assume any compactness conditions on the operator C. The excision and additivity properties of these degree theories are employed, and the main results are significant extensions or generalizations of previous results by Krasnoselskii, Guo, Ding and Kartsatos involving the relaxation of compactness conditions and/or conditions on the boundedness of the operator T. Moreover, a new degree theory developed by Kartsatos and Skrypnik has been used to prove a similar result for operators of type T + C, where T : X \supset D(T) \rightarrow 2X* is a multi-valued maximal monotone operator, with 0 \in D(T) and 0 \in T(0), and C : X \supset D(C) \rightarrow X* is a densely defined quasi-bounded and finitely continuous operator of type (~S+). The problem of existence of nonzero solutions for Tx + Cx + Gx \ni 0 is also considered. Here, T is maximal monotone, C is bounded demicontinuous of type (S+), and G is of class (P).
Eigenvalue and invariance of domain results have also been established for the sum L + T + C : G \cap D(L) \rightarrow 2X* , where G \subset X is open and bounded, L : X \supset D(L) \rightarrow X* densely defined linear maximal monotone, T : X \rightarrow 2X* bounded maximal monotone, and C : G \rightarrow X* bounded demicontinuous of type (S+) w. r. t. D(L).
Adhikari, Dhruba R., "Applications of degree theories to nonlinear operator equations in Banach spaces" (2007). Graduate Theses and Dissertations.