- genDS2(List, List) - Method in class DataMergingMatlabUtils.DatasetGenerator
-
Provides the interface for calling the genDS2
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- genDS2(Object[], Object[]) - Method in class DataMergingMatlabUtils.DatasetGenerator
-
Provides the interface for calling the genDS2
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- genDS2(int, Object...) - Method in class DataMergingMatlabUtils.DatasetGenerator
-
Provides the standard interface for calling the genDS2
MATLAB function with
5 comma-separated input arguments.
- genDS2(int, Object...) - Method in interface DataMergingMatlabUtils.DatasetGeneratorRemote
-
Provides the standard interface for calling the genDS2
MATLAB
function with 5 input arguments.
- genRot(List, List) - Method in class DataMergingMatlabUtils.DatasetRotator
-
Provides the interface for calling the genRot
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- genRot(Object[], Object[]) - Method in class DataMergingMatlabUtils.DatasetRotator
-
Provides the interface for calling the genRot
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- genRot(int, Object...) - Method in class DataMergingMatlabUtils.DatasetRotator
-
Provides the standard interface for calling the genRot
MATLAB function with
2 comma-separated input arguments.
- genRot(int, Object...) - Method in interface DataMergingMatlabUtils.DatasetRotatorRemote
-
Provides the standard interface for calling the genRot
MATLAB
function with 2 input arguments.
- genRot2D(List, List) - Method in class DataMergingMatlabUtils.DatasetRotator
-
Provides the interface for calling the genRot2D
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- genRot2D(Object[], Object[]) - Method in class DataMergingMatlabUtils.DatasetRotator
-
Provides the interface for calling the genRot2D
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- genRot2D(int, Object...) - Method in class DataMergingMatlabUtils.DatasetRotator
-
Provides the standard interface for calling the genRot2D
MATLAB function with
2 comma-separated input arguments.
- genRot2D(int, Object...) - Method in interface DataMergingMatlabUtils.DatasetRotatorRemote
-
Provides the standard interface for calling the genRot2D
MATLAB
function with 2 input arguments.
- genRot2D(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the genRot2D
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- genRot2D(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the genRot2D
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- genRot2D(int, Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the genRot2D
MATLAB function with
2 comma-separated input arguments.
- genRot2D(int, Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the genRot2D
MATLAB
function with 2 input arguments.
- genRot2DDrift(List, List) - Method in class DataMergingMatlabUtils.DatasetRotator
-
Provides the interface for calling the genRot2DDrift
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- genRot2DDrift(Object[], Object[]) - Method in class DataMergingMatlabUtils.DatasetRotator
-
Provides the interface for calling the genRot2DDrift
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- genRot2DDrift(int, Object...) - Method in class DataMergingMatlabUtils.DatasetRotator
-
Provides the standard interface for calling the genRot2DDrift
MATLAB function with
3 comma-separated input arguments.
- genRot2DDrift(int, Object...) - Method in interface DataMergingMatlabUtils.DatasetRotatorRemote
-
Provides the standard interface for calling the genRot2DDrift
MATLAB
function with 3 input arguments.
- genRot2DDrift(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the genRot2DDrift
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- genRot2DDrift(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the genRot2DDrift
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- genRot2DDrift(int, Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the genRot2DDrift
MATLAB function with
3 comma-separated input arguments.
- genRot2DDrift(int, Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the genRot2DDrift
MATLAB
function with 3 input arguments.
- pca2(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the pca2
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- pca2(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the pca2
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- pca2(int, Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the pca2
MATLAB function with
4 comma-separated input arguments.
- pca2(int, Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the pca2
MATLAB function
with 4 input arguments.
- pca2originalgenerated(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the pca2originalgenerated
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- pca2originalgenerated(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the pca2originalgenerated
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- pca2originalgenerated(int, Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the pca2originalgenerated
MATLAB function with
8 comma-separated input arguments.
- pca2originalgenerated(int, Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the pca2originalgenerated
MATLAB function with 8 input arguments.
- plotBoxApproachStreamSizeAll(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotBoxApproachStreamSizeAll
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotBoxApproachStreamSizeAll(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotBoxApproachStreamSizeAll
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotBoxApproachStreamSizeAll(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotBoxApproachStreamSizeAll
MATLAB function with
13 comma-separated input arguments.
- plotBoxApproachStreamSizeAll(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the
plotBoxApproachStreamSizeAll
MATLAB function with 13 input arguments.
- plotDS(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotDS
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotDS(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotDS
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotDS(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotDS
MATLAB function with
3 comma-separated input arguments.
- plotDS(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the plotDS
MATLAB
function with 3 input arguments.
- plotOverlapped(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotOverlapped
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotOverlapped(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotOverlapped
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotOverlapped(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotOverlapped
MATLAB function with
6 comma-separated input arguments.
- plotOverlapped(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the plotOverlapped
MATLAB
function with 6 input arguments.
- plotOverlappedGradientBoxes(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotOverlappedGradientBoxes
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotOverlappedGradientBoxes(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotOverlappedGradientBoxes
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotOverlappedGradientBoxes(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotOverlappedGradientBoxes
MATLAB function with
6 comma-separated input arguments.
- plotOverlappedGradientBoxes(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the
plotOverlappedGradientBoxes
MATLAB function with 6 input arguments.
- plotOverlappedGradientBoxesGrayAreas(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotOverlappedGradientBoxesGrayAreas
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotOverlappedGradientBoxesGrayAreas(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotOverlappedGradientBoxesGrayAreas
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotOverlappedGradientBoxesGrayAreas(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotOverlappedGradientBoxesGrayAreas
MATLAB function with
6 comma-separated input arguments.
- plotOverlappedGradientBoxesGrayAreas(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the
plotOverlappedGradientBoxesGrayAreas
MATLAB function with 6 input
arguments.
- plotStrEvals(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvals
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotStrEvals(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvals
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotStrEvals(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotStrEvals
MATLAB function with
4 comma-separated input arguments.
- plotStrEvals(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the plotStrEvals
MATLAB
function with 4 input arguments.
- plotStrEvalsComp2(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsComp2
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotStrEvalsComp2(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsComp2
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotStrEvalsComp2(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotStrEvalsComp2
MATLAB function with
8 comma-separated input arguments.
- plotStrEvalsComp2(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the plotStrEvalsComp2
MATLAB function with 8 input arguments.
- plotStrEvalsComp2Split(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsComp2Split
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotStrEvalsComp2Split(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsComp2Split
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotStrEvalsComp2Split(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotStrEvalsComp2Split
MATLAB function with
8 comma-separated input arguments.
- plotStrEvalsComp2Split(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the
plotStrEvalsComp2Split
MATLAB function with 8 input arguments.
- plotStrEvalsComp3(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsComp3
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotStrEvalsComp3(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsComp3
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotStrEvalsComp3(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotStrEvalsComp3
MATLAB function with
12 comma-separated input arguments.
- plotStrEvalsComp3(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the plotStrEvalsComp3
MATLAB function with 12 input arguments.
- plotStrEvalsComp3Split(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsComp3Split
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotStrEvalsComp3Split(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsComp3Split
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotStrEvalsComp3Split(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotStrEvalsComp3Split
MATLAB function with
12 comma-separated input arguments.
- plotStrEvalsComp3Split(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the
plotStrEvalsComp3Split
MATLAB function with 12 input arguments.
- plotStrEvalsComp3SplitDTSize(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsComp3SplitDTSize
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotStrEvalsComp3SplitDTSize(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsComp3SplitDTSize
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotStrEvalsComp3SplitDTSize(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotStrEvalsComp3SplitDTSize
MATLAB function with
12 comma-separated input arguments.
- plotStrEvalsComp3SplitDTSize(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the
plotStrEvalsComp3SplitDTSize
MATLAB function with 12 input arguments.
- plotStrEvalsComp3SplitTag(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsComp3SplitTag
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotStrEvalsComp3SplitTag(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsComp3SplitTag
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotStrEvalsComp3SplitTag(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotStrEvalsComp3SplitTag
MATLAB function with
12 comma-separated input arguments.
- plotStrEvalsComp3SplitTag(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the
plotStrEvalsComp3SplitTag
MATLAB function with 12 input arguments.
- plotStrEvalsCompBar(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsCompBar
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotStrEvalsCompBar(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotStrEvalsCompBar
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotStrEvalsCompBar(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotStrEvalsCompBar
MATLAB function with
6 comma-separated input arguments.
- plotStrEvalsCompBar(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the plotStrEvalsCompBar
MATLAB function with 6 input arguments.
- Plotter - Class in DataMergingMatlabUtils
-
The Plotter
class provides a Java interface to MATLAB functions.
- Plotter() - Constructor for class DataMergingMatlabUtils.Plotter
-
Constructs a new instance of the Plotter
class.
- Plotter(String) - Constructor for class DataMergingMatlabUtils.Plotter
-
- Plotter(MWComponentOptions) - Constructor for class DataMergingMatlabUtils.Plotter
-
Constructs a new instance of the Plotter
class.
- PlotterRemote - Interface in DataMergingMatlabUtils
-
The PlotterRemote
class provides a Java RMI-compliant interface to MATLAB
functions.
- plotWithRuleBoundaries(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotWithRuleBoundaries
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- plotWithRuleBoundaries(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the plotWithRuleBoundaries
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- plotWithRuleBoundaries(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the plotWithRuleBoundaries
MATLAB function with
5 comma-separated input arguments.
- plotWithRuleBoundaries(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the
plotWithRuleBoundaries
MATLAB function with 5 input arguments.
- printPctCorrectStream(List, List) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the printPctCorrectStream
MATLAB function
where the first argument, an instance of List, receives the output of the MATLAB function and
the second argument, also an instance of List, provides the input to the MATLAB function.
- printPctCorrectStream(Object[], Object[]) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the interface for calling the printPctCorrectStream
MATLAB function
where the first argument, an Object array, receives the output of the MATLAB function and
the second argument, also an Object array, provides the input to the MATLAB function.
- printPctCorrectStream(Object...) - Method in class DataMergingMatlabUtils.Plotter
-
Provides the standard interface for calling the printPctCorrectStream
MATLAB function with
3 comma-separated input arguments.
- printPctCorrectStream(Object...) - Method in interface DataMergingMatlabUtils.PlotterRemote
-
Provides the standard interface for calling the printPctCorrectStream
MATLAB function with 3 input arguments.


To further investigate the proposed two-step teleconnection, and additionally verify that sea-ice-induced tropical convection changes are forcing the circulation changes in the North Pacific, we explore the impacts of another source of remote forcing: Antarctic sea-ice loss. Antarctic sea-ice decline will result in a warming at mid- to high latitudes of the southern hemisphere. One consequence of this warming is a southward shift of tropical precipitation, with convection increase in the southern and central tropical Pacific 40. This is the opposite to the precipitation response accompanying Arctic sea-ice loss. In accord with previous studies 13, 35, 36 and the mechanism advanced here, increased convection should in turn drive a northward-propagating Rossby wavetrain consisting of an anticyclonic anomaly in the tropical Pacific and a cyclonic anomaly in the North Pacific. This cyclonic flow is associated with negative geopotential height anomalies over the North Pacific (geopotential low) leading to wetter conditions over California. Simulations in which the sea-ice physics parameter perturbations are prescribed in the Southern hemisphere only (“low Antarctic ice” simulations, Fig. 1b and Supplementary Fig. 1b, d) show a response that is consistent with these expectations. Tropical precipitation shifts southward (Fig. 5a), anticyclonic flow is established over the northern tropical Pacific, and cyclonic flow is formed over the North Pacific (Fig. 5c). The geopotential ridge in the North Pacific is replaced with a geopotential trough, favoring the propagation of tropical storms across California (Fig. 5b). As a result, precipitation over California increases (Fig. 5a).
Atmospheric impacts of Antarctic sea-ice loss. a Precipitation anomalies. b 500 hPa geopotential distribution changes. c Stream function changes. Shown are the ensemble mean differences (“low Arctic ice” minus control) for December–February (DJF) season. Stippling indicates anomalies that are statistically significant at the 90% confidence level
The “low Antarctic ice” simulations show that the proposed mechanism can be triggered by sea-ice changes in either hemisphere. Since Antarctic sea-ice loss involves northward propagation in both teleconnection steps (i.e., Antarctic sea-ice affecting the tropical Pacific, which in turn affects the North Pacific) and no high northern latitude changes, it provides additional support for our conjecture that the sea-ice changes can influence North Pacific geopotential height through tropical convection changes. More generally, any high-latitude perturbation (northern or southern hemispheric warming or cooling) that impacts the position of the tropical Pacific ITCZ, will have an impact on California’s rainfall.


The little chicken that was so happy to have a place of its own in the coopdrooped with sadness when its feathers were coated in a thick layer of goop. [G|D]
She grabbed the old hoop and excitedly leapt into a huge scoop of poop, hoping to find something cool inside. [G|D]
She cautiously crept up to the old sloop and, while she was trying not to stoop, she used her nose to snoop around to figure out what was inside. [G|D]
The triumphant army of brave troops whooped with joy as they swooped in and conquered their enemy. [G|D]


About
Resume
Research
Contact
Labib Imam Chowdhury
<EMAIL_ADDRESS>Labib Chowdhury
+8801724538432


# -*- coding: utf-8 -*- # Copyright 2017 Elisey Zanko # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import sys from pip._vendor.tenacity import BaseRetrying from pip._vendor.tenacity import DoAttempt from pip._vendor.tenacity import DoSleep from pip._vendor.tenacity import RetryCallState from tornado import gen class TornadoRetrying(BaseRetrying): def __init__(self, sleep=gen.sleep, **kwargs): super(TornadoRetrying, self).__init__(**kwargs) self.sleep = sleep @gen.coroutine def __call__(self, fn, *args, **kwargs): self.begin(fn) retry_state = RetryCallState(retry_object=self, fn=fn, args=args, kwargs=kwargs) while True: do = self.iter(retry_state=retry_state) if isinstance(do, DoAttempt): try: result = yield fn(*args, **kwargs) except BaseException: # noqa: B902 retry_state.set_exception(sys.exc_info()) else: retry_state.set_result(result) elif isinstance(do, DoSleep): retry_state.prepare_for_next_attempt() yield self.sleep(do) else: raise gen.Return(do)


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Hello,
In my emoncms, i cant create a parameter to divide by 100 my Vrms. I chose x (calibration) and put 0.01 in parameter.
when i add it, nothing happened. I can see in inputs "x log" but undefined. Nothing else. I must kill input to recreate it.
What happened ?
Re: Impossible to multiply by 0.01
you need to add an input x0.001 and then a log to feed input afterwards. Working fine for me
Re: Impossible to multiply by 0.01
Yes but it is not working for me. I dont know why...
OK Found. It is a language problem.
I use fr_FR and it is not working. I must commute to en_EN to proceed.
Is there any solution ?
Re: Impossible to multiply by 0.01
Doesn't fr_FR set the number separator from a decimal point to a comma?
Re: Impossible to multiply by 0.01
Probably.
Re: Impossible to multiply by 0.01
I can confirm this on a old version of emoncms.
With en_EN I can enter 0.01
With fr_FR it seems to be read 0, and a second processing line is created with null null as arguments. If I enter 0,01, then I get an error message: a number is required.
With fr_FR, the 0.01 entered in en_EN is used correctly.
I opened an issue: https://github.com/emoncms/emoncms/issues/154
Re: Impossible to multiply by 0.01
Thank you for your report.
My emoncms is up to date. Y did it 5 days ago and i used last version of it.
Re: Impossible to multiply by 0.01
Hello,
Got another problem with my emoncms 8.2.6.
When connected and language selected to en_EN, i can see my zoom graph correctly.
When not connected, emoncms switch to fr_FR (i am french in France...)
Graph appears but empty. nan values everywhere.
Ex :
Total: 0 kWh : 0€ | Average: NaN kWh : NaN€ | NaN€ a week, NaN€ a year | Unit price: 0.14€
Is there any solution ?


Author: {{quote.author}}
This quote was submitted {{quote.submitDate|dayCount| number : '1.0-0'}} days ago


Neuroplasticity and Growth Mindset
NEUROPLASTICITY
How does understanding the principals of neuroplasticity benefits people?
I learned that engaging in new activites helps stimulate and grow the brain as well as repeating activites helps harden those
activites into your psyche which makes those activites much easier to perform in the future.
How you might engage with the principals of neuroplasticity for your own benefit?
Through things such as drumming or doing weight lifting/muscle building, this is a concept that I have known to exist
just to do the fact of actually seeing the results, although not putting a scientific name or doing any research into.
After learning this I will look to use this concept to keep my brain active in the activites I do as well as to push
or break through walls/barriers that are holding my growth or development back with computer coding/drumming or anything
I look to do going forward.
What are some of the ways to increase your neuroplasticity
To try different activites that are related into what you are doing to help you develop more effectively as well as
repeatition on these activites to help engrave them into your psyche to perform more easily. Learning new activites,
developing on weaknesses and to continue to learn or challenge your mind through all the years of your life help to
increase your neuroplasicity.
 It is relevant
because it can help you from not achieveing goals or learning topics/subjects to actually being able to do so, all with
the right positive mindset.
In this exploration, did anything surprise you? Change for you?
This is something I have been familar with, although similar to neuroplasticity I will be intergrating into my mindset more
prominently when I look to learn something new and challening to get the most out of it in the shortest amount of time.
How will you integrate growth mindset into your learning journey?
I will look to take on any challenges or 'hard tasks' on with a positive mindset as well as not worry to compare my
shortcomings if any to anyone else around me. Deep breaths, deep focus and the will to achieve will help me persevere
through anything I encounter going forward.


Burnie is principally a commercial port about 25nm Northwest of Devonport on Tasmania's norther coast.
Only useful for yachts as a port of refuge.
Position 41° 03'07"S, 145° 55'03"E
See Australia/Formalities for details.
There few facilities for yachts here.
Contact Port Control on VHF channel 16.
Last updated April 2016.


So this is my blog. I've spent a lot of time thinking about starting one, wondering what I would share, and how I would go about saying it. Mostly, though, this exists for my sanity, and anything I write will be for the purpose of preserving my sanity.
- Anxiety - May 19, 2018
- Grief - March 27, 2018
- Losing My Religion - December 17, 2017
- Hair - December 05, 2017
- Day 7 Depression - November 07, 2017
- Day 5 Secrets of a Postmates Delivery Driver - November 05, 2017
- Day 3 The Story of Amy Part 2 - November 03, 2017
- Day 2 The Story of Amy - November 02, 2017
- Day 1 NaNo Wri Mo Writing and Other Issues - November 01, 2017
- Happiness - October 08, 2017
- Weight - September 18, 2017
- Denial - August 16, 2017
- Self Love - August 03, 2017
- What Makes Life Worth Living - July 18, 2017
- I Am Disabled - June 28, 2017
- How Are You - June 13, 2017
- For Pounce - June 02, 2017
- Dreams - April 24, 2017
- A Letter to my Gastroparesis - April 03, 2017
- On My Current Body Image - March 31, 2017
- Things I Cant Do - February 26, 2017
- In Defense of Rage - February 10, 2017
- In Which I Offend all of my Well Wishers - January 05, 2017
- Fetzig and Milkshakes - December 06, 2016
- A Little Unsteady - November 28, 2016
- It Gets Better - November 20, 2016
- A Day in the Life - November 16, 2016
- Living on Borrowed Time - November 11, 2016
- About Me - November 08, 2016


Module pl.lexer
Lexical scanner for creating a sequence of tokens from text.
`lexer.scan(s)` returns an iterator over all tokens found in the string `s`. This iterator returns two values, a token type string (such as 'string' for quoted string, 'iden' for identifier) and the value of the token.
Versions specialized for Lua and C are available; these also handle block comments and classify keywords as 'keyword' tokens. For example:
> s = 'for i=1,n do' > for t,v in lexer.lua(s) do print(t,v) end keyword for iden i = = number 1 , , iden n keyword do
See the Guide for further ???
Functions
| scan (s, matches[, filter[, options]]) | create a plain token iterator from a string or file-like object. |
| insert (tok, a1, a2) | insert tokens into a stream. |
| getline (tok) | get everything in a stream upto a newline. |
| lineno (tok) | get current line number. |
| getrest (tok) | get the rest of the stream. |
| get_keywords () | get the Lua keywords as a set-like table. |
| lua (s[, filter[, options]]) | create a Lua token iterator from a string or file-like object. |
| cpp (s[, filter[, options]]) | create a C/C++ token iterator from a string or file-like object. |
| get_separated_list (tok[, endtoken=')'[, delim=']]) | get a list of parameters separated by a delimiter from a stream. |
| skipws (tok) | get the next non-space token from the stream. |
| expecting (tok, expected_type, no_skip_ws) | get the next token, which must be of the expected type. |
Functions
- scan (s, matches[, filter[, options]])
-
create a plain token iterator from a string or file-like object.
Parameters:
- s string or file a string or a file-like object with `:read()` method returning lines.
- matches tab an optional match table - array of token descriptions. A token is described by a `{pattern, action}` pair, where `pattern` should match token body and `action` is a function called when a token of described type is found.
- filter tab a table of token types to exclude, by default `{space=true}` (optional)
- options tab a table of options; by default, `{number=true,string=true}`, which means convert numbers and strip string quotes. (optional)
- insert (tok, a1, a2)
-
insert tokens into a stream.
Parameters:
- tok a token stream
- a1 a string is the type, a table is a token list and a function is assumed to be a token-like iterator (returns type & value)
- a2 string a string is the value
- getline (tok)
-
get everything in a stream upto a newline.
Parameters:
- tok a token stream
Returns:
-
a string
- lineno (tok)
-
get current line number.
Parameters:
- tok a token stream
Returns:
-
the line number.
if the input source is a file-like object,
also return the column.
- getrest (tok)
-
get the rest of the stream.
Parameters:
- tok a token stream
Returns:
-
a string
- get_keywords ()
-
get the Lua keywords as a set-like table.
So `res["and"]` etc would be `true`.
Returns:
-
a table
- lua (s[, filter[, options]])
-
create a Lua token iterator from a string or file-like object.
Will return the token type and value.
Parameters:
- s string the string
- filter tab a table of token types to exclude, by default `{space=true,comments=true}` (optional)
- options tab a table of options; by default, `{number=true,string=true}`, which means convert numbers and strip string quotes. (optional)
- cpp (s[, filter[, options]])
-
create a C/C++ token iterator from a string or file-like object.
Will return the token type type and value.
Parameters:
- s string the string
- filter tab a table of token types to exclude, by default `{space=true,comments=true}` (optional)
- options tab a table of options; by default, `{number=true,string=true}`, which means convert numbers and strip string quotes. (optional)
- get_separated_list (tok[, endtoken=')'[, delim=']])
-
get a list of parameters separated by a delimiter from a stream.
Parameters:
- tok the token stream
- endtoken string end of list. Can be '\n' (default ')')
- delim string separator (default ')
Returns:
-
a list of token lists.
- skipws (tok)
-
get the next non-space token from the stream.
Parameters:
- tok the token stream.
- expecting (tok, expected_type, no_skip_ws)
-
get the next token, which must be of the expected type.
Throws an error if this type does not match!
Parameters:
- tok the token stream
- expected_type string the token type
- no_skip_ws bool whether we should skip whitespace


{% load i18n %} {% load staticfiles %} {% language lang_code %} {% comment %} NOTE: This template is only used when initializing the database during set-up of a new site. All modifications to the content from that point onwards shall be done using the CMS tool found in admin/ section of the site. {% endcomment %}


Security Camera Footage
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i don't know what's going on
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SOS SAVE US
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at least i won't need to take midterms
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why meeee :(


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Coraline flexing her spelling and love of noodles: "Can we go out for F-U?" Long pause from us. "You know, pho."
4/25/2014, 3:52:13 PM
Favs: 4
Retweets: 0
link--- layout: tweet ---
Coraline flexing her spelling and love of noodles: "Can we go out for F-U?" Long pause from us. "You know, pho."
4/25/2014, 3:52:13 PM
Favs: 4
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link


All Classes
-
All Classes Class Summary Exception Summary Class Description Connect4 GameBoard This class represents the game board containing the game pieces.GameBoard.InvalidMoveException Custom Exception for Illegal moves selected by players.GameHandler This class holds the different game elements and provides methods for the game flow.InvalidStateException Player This class represents a player and is responsible for generating move information.


Table
Table
<question_variable_name> Transformation
Prefix
Last Prefix
Suffix
Default Text
Select Child Question
Transformation Type
Insert
Cancel
Please add one entry for each overseas deployment in support of a combat operation for more than 30 days.
Question:
Why we need to show the option of "Number of Entries"
Step 1
delimit_var_xyz
<question_variable_name> Transformation
Prefix
Last Prefix
Suffix
Default Text
Transformation Type
Insert
Cancel
Delimited
Custom Variable
(Var Appointments)
Free text
(Ex: With Date - demo_DOB)
<question_variable_name> Transformation
Transformation Type
Insert
Cancel
Multi Question??
<question_variable_name> Transformation
Prefix
Last Prefix
Suffix
Default Text
Transformation Type
Insert
Cancel
Delimited
Select One Matrix
or Select Multi Matrix
<question_variable_name> Transformation
Output Text
Insert
Cancel
In the past 1 week...
Transformation Type (Matrix to list)
Delimited
Have to select at least one column and one row
Columns (Answers)
Rows (Questions)
Output Text 2
Step 1
Step 1
Step 2
delimit_var_xyz
Step 2
Step 1
Step 2
delimit_var_xyz
Step 1
Step 2
delimit_var_xyz
Step 2
delimit_var_xyz


|
Bowling for Columbine: Race, the NRA And Gun Control
by Taunya Lovell Banks
Who would ever think that there
is a connection between the 1999 massacre at Columbine High School
and race. Initially, I resisted an underlying premise of Michael
Moore's latest documentary film, Bowling for Columbine,
that there is a connection between race and the National Rifle
Association's (NRA) opposition to gun control. So what if the
NRA was founded in 1871 the same year that the Ku Klux Klan was
outlawed, mere coincidence. So what if student witnesses at Columbine
claimed that the one black victim of the massacre was killed
just because he was black, mere speculation. So what if former
NRA spokesman Charlton Heston attributes the significantly higher
rate of gun violence in the United States than Canada to our
greater ethnic diversity, even Moore admits that Canada is pretty
diverse too.
Then
I remembered that the Virginia Colony in 1639 enacted a law providing
that "all persons except negroes to be provided with arms
and ammunition or be fined." Thus, one of the earliest laws
in English colonial America that distinguishes blacks from non-blacks
regulated gun possession. A year later a second law clarified
that "all persons" included any "capable"
unfree non-negro person (i.e., indentured servant). This mandate
to arm grew out of a well-founded fear by colonialists that local
hostile indigenous groups would massacre them. Understandably,
these Indians were hostile because the colonialists were taking
their land
Moore tries to convey the historical
connection between whites' fear of non-whites and the protection
of gun ownership using an eight minute cartoon. The cartoon starts
with the Mayflower, focuses on the colonists' fear of indigenous
people, and only links this fear to blacks as we approach the
civil rights era. Yet the Virginia colonial law illustrates how
these two fears combined from the beginning, suggesting that
European settlers feared armed black slaves or servants as much
as or more than attacking Indians.
In 1991 Robert Cottrol and
Raymond Diamond wrote a provocative article advancing what they
claimed to be an "African American perspective" on
the Second Amendment's right to bear arms language. They pointed
out that most colonies, while not prohibiting free blacks from
owning firearms prevented blacks, and often Indians, from serving
in the militia. After the Civil War black codes enacted by southern
states generally prohibited blacks from owning firearms. During
and after slavery blacks needed weapons to protect themselves
from white violence. The inability of blacks to protect themselves
from white violence, especially post emancipation, Cottrol and
Diamond assert, effectively undercut their constitutional and
statutory rights.
Once I opened my mind to Moore's
premise, I was reminded of more recent attempts to regulate gun
possession by blacks. Notable among them was the Chicago Housing
Authority's 1988 "Clean Sweep" policy authorizing warrantless
sweeps of public housing units and confiscation of unlicensed
or unauthorized weapons. The policy was instituted in response
to resident complaints about the unsafe living conditions resulting
from the widespread violence in the housing projects. Litigation
followed and the circumstances for conducting the searches restricted
until, in response to death of seven-year-old boy in fall of
1992, the housing authority instituted an even more aggressive
sweep program that resulted in further litigation. Although the
housing authority's policy was facially neutral, most of the
public housing residents affected by this policy were black.
Other cities, plagued by crime
and violence, instituted gun amnesty programs encouraging inner
city residents, most of whom are black, to turn in all unlicensed
guns, sometimes in exchange for money. Yet, no one would suggest
after the massacre at Columbine that police officials institute
a gun amnesty program or conduct clean sweeps of the houses in
Littleton Colorado. In fact, the response of many Americans might
be arm yourself to protect your family. Thus, Cottrol and Diamond
argue, black Americans who live in an environment where violence
is an everyday threat also should have access to weapons. Their
conclusion, while understandable, does not make the community
any safer. Just as selective access to and restrictions on guns
is not the answer to America's gun violence problem, neither
is arming everyone.
The consequences of unregulated
gun control are displayed in a chilling scene where we see the
actual tape of Eric Harris and Dylan Klebold, the Columbine shooters,
as they rampage through the school cafeteria. I kept wondering
whether the students in the cafeteria who survived the massacre
will ever fully recover from this trauma. Moore does not address
the psychic trauma of people and communities impacted by gun
violence. He simply questions American's love of guns.
Throughout the documentary
Moore, a life member of the NRA, carefully navigates the line
between being anti-gun and anti-gun regulation. His focus is
gun violence rather than gun use. Nowhere in the film is this
point conveyed so clearly as when he compares gun ownership and
gun violence in foreign countries, notably Canada (7 million
gun owners and fewer than 100 gun-related deaths), with gun ownership
and violence in the United States. Suggesting that there is not
necessarily a correlation between gun ownership and gun violence,
Moore effectively undercuts the traditional explanation for America's
gun violence.
In a funny, eureka-like moment,
Moore inserts a clip of comic Chris Rock questioning gun control
and asserting that bullets not guns kill people. Rock's solution
to America's gun violence -- make the cost of bullets so prohibitive
that people will think twice before shooting some one. The audience
laughed, but I bet some thought that Rock had a good idea. As
a follow-up, Moore accompanies two Columbine survivors to K-mart's
headquarter to ask the corporate officers to stop selling bullets
in their stores.
Whether you agree or disagree
with Michael Moore's point of view, Bowling for Columbine
raises provocative questions about the NRA, the prevalence of
gun violence in the United States and American's resistance to
gun control legislation. Occasionally Moore seems to stray far
a field alleging connections between gun violence and the Clinton
administration's "workfare" welfare reform policy.
There are other flaws as well such as the linking the Columbine
massacre to the presence of Lockheed Martin in Littleton. Moore's
self indulgence causes the movie to run about 30 minutes longer
than necessary. Nevertheless, Bowling for Columbine is
a must see film for the questions it raises about America's love
of guns and penchant for violence.
Posted November 25, 2002
|


DVSL (Declarative Velocity Style Language) is a tool modeled after XSLT and is intended for general XML transformations. DVSL steals two of the best features of XSLT:
DVSL's template language is Velocity, so conventional Velocity syntax is used to get and set data, to perform looping and flow control, etc. Anything that you can normally do in a Velocity template can be done in DVSL templates.
Before you use DVSL, you must get the source and build the tool. Currently, there is no release, so you must either get a nightly snapshot, or download directly from Subversion.
How to BuildBuilding DVSL is very simple. All dependency jars that are required are included in the distribution. However, we do require that Apache Ant is installed.
Once ant is installed, you simply need to change to the project root directory and invoke ant with the 'jar' target :
$ cd dvsl $ ant jar
This will build the dvsl jar in the project root directory.
Using DVSLWhile DVSL is also a tool that can be integrated into your applications, DVSL is able to be used without any programming.
The first way is via command line, where you can use it to transform a single file, or as a filter. The usage is :
java org.apache.dvsl.DVSL -STYLE stylesheet [-IN infile] [-OUT outfile ]
Note that the stylesheet is the only required element, and the input and output then default to
stdin
and stdout
.
By adding the appropriate stuff in your classpath (that would be all the jars in the project
lib
directory ), you can use it :
java org.apache.dvsl.DVSL -STYLE src/stylesheets/site.dvsl -IN xdocs/index.xml > out.stuff java org.apache.dvsl.DVSL -STYLE src/stylesheets/site.dvsl -OUT out.html < xdocs/index.html java org.apache.dvsl.DVSL -STYLE src/stylesheets/site.dvsl < xdocs/index.xml
You can also use DVSL right from ant using the included Ant task. The Ant task supports the toolbox.
<target name="docs"> <taskdef name="dvsl" classname="org.apache.dvsl.DVSLTask"> <classpath> <pathelement location="${project.name}-${project.version}.jar"/> <path refid="classpath"/> </classpath> </taskdef> <dvsl basedir="${docs.src}" destdir="${docs.dest}/" toolboxfile="${docs.src}/toolbox.props" extension=".html" style="${source.home}/stylesheets/site.dvsl" excludes="**/project.xml" includes="**/*.xml" /> </target>
For more information on using DVSL from Ant, please see the Ant Task Reference.
A few examples are provided with the current distribution, in the examples
directory in the distribution, and the examples that follow were originally taken
from there.
To begin, we will start with a simple example. Here is a basic XML document:
<?xml version="1.0"?> <document>

 Hello from section foo

 Hello from section bar

 </document>
A simple DVSL stylesheet to transform this into HTML might look like :
#match("document")   $context.applyTemplates()   #end #match("section")
 Section: $attrib.name $context.applyTemplates("p") #end #match("p")
 $node.copy($node.children())
 #end
With the resulting output of

 Section: foo
 Hello from section foo

 Section: bar
 Hello from section bar

This can be found in examples/simple and is example1.xml and example1.dvsl.
Now Add Some External ToolsA more interesting example involves specifying and using tools. We'll give an example and explain the toolbox later on.
A simple toolbox example is included, in examples/toolbox. First, you must define the tools and values in a properties file
toolbox.contextname = toolbox toolbox.tool.footool = Footool toolbox.string.mystring = Hello there! toolbox.integer.myint = 7
Here we do a couple of things :
toolbox.contextname = toolbox
:
defines 'toolbox' as the name we will use in the template
to access the tools.
toolbox.tool.footool = Footool
: defines that an instance
of the class 'Footool' will be placed in the context under the key 'footool'.
toolbox.string.mystring = Hello there!
: defines that a
java.lang.String
"Hello there!" will be placed in the context under the key 'mystring'
toolbox.integer.myint = 7
: defines that a
java.lang.Integer
will be placed in the context under the
key 'myint'.
You specify the toolbox in the <dvsl> task in the ant script as such :
<dvsl basedir="${docs.src}" destdir="${docs.dest}/" extension=".html" style="${docs.src}/site.dvsl" excludes="**/project.xml" toolboxfile="toolbox.props" includes="**/*.xml />
To use the tools, this is the stylesheet that has an example :
#match("document") Hello from the document node. From the toolbox : Method : $context.toolbox.footool.getFoo() String : $context.toolbox.mystring Int : $context.toolbox.myint #foreach( $data in $context.toolbox.footool.getList() ) Item $velocityCount : $data #end #end
With an input of :
<?xml version="1.0"?> <document value="5"> Data in <document> node </document>
And with the class Footool
import java.util.List; public class Footool { public String getFoo() { return "Hello from Foo!"; } public List getList() { List list = new java.util.ArrayList(); list.add("red"); list.add("blue"); list.add("green"); return list; } }
You get the output
Hello from the document node. From the toolbox : Method : Hello from Foo! String : Hello there! Int : 7 Item 1 : red Item 2 : blue Item 3 : green
This can be found in examples/toolbox
.
Also, the examples/velocitydocs
example shows how to grab
and use the HTMLEscape class from the Velocity jar as a tool to do
escaping.
Writing templates is very simple. The basic template definition uses the directive
#match(<XPath Expression >) < template content > #end
This directive declares that when a node matches the <XPath Expression >
then the body of the directive is to be rendered to the ouput.
In the body, you would place any static content you wish to go to
the output, and also get data from the XML document you are working in.
Future plans include a #name() directive, and optional arguments to the #match() and #name() directives to support modes and namsepaces.
The Node APIDuring processing, when a match occurs and a template is invoked, a few objects are placed in the Context for you to access. These elements are read-only and cannot be modified via #set().
The most important is the current Node, which is accessible via the reference
$node
. The $node
is the current node that matched
the template XPath expression (or name).
You can use the $node object two ways. First, you can use the Velocity property formalism to access child nodes in the document tree rooted at the current node. So with a document such as :
<?xml version="1.0"?> <document>

 foo

 bar

 </document>
you could use references like
$node.section.p.code
to access elements and atributes in the subtree, assuming that $node was the 'document' element. Further, you can of course call methods on the sub-elements :
$node.section.children()
As for methods, $node
has the following API
for you to use :
| Reference | Methods | Description |
|---|---|---|
| $node | Current node for this template match. | |
| $node.name() | Element name of node - ex 'table' | |
| $node.value() | Text content of node | |
| $node.attrib("name") | Returns attribute of node if appropriate. | |
| $node.selectNodes(xpathexpr) | Returns an iteratable list of nodes that satisfy the XPath expression | |
| $node.selectSingleNode(xpathexpr) | Returns the first node that satisfies the XPath expression | |
| $node.get(xpathexpr) | Returns the first node that satisfies the XPath expression | |
| $node.children() | Returns a List of all children of this node | |
| $node.copy() | Does a 'deep copy' of this node's subtree to the output | |
| $node.copy(List) | Does a 'deep copy' of the specified nodelist to the output. | |
| $node.valueOf(xpathexpr) | Returns the result of the specified XPath as a Object |
The next node-specific reference is $attrib
. This
corresponds to a collection of the current nodes attributes (if appropriate - for
example, an attribute doesn't itself have attributes) which you can use
to quickly get the values using Velocity's property reference formalism.
So with the example above, if you matched the 'section' node
you could find the value of the 'name' attribute via
$attrib.name
Which would return 'first'.
The final reference available is $context
. This object offers the
following API :
| Reference | Methods | Description |
|---|---|---|
| $context | Utility context. | |
| $context.applyTemplates() | Applies all templates in the subtree against the ruleset. | |
| $context.applyTemplates(xpathexpr) | Applies templates to all nodes in the subtree
that match the given XPath expression. Ex. $context.applyTemplates("*|@*") |
|
| $context.applyTemplates(Node) | Applies templates to the specified node. First match is applied. | |
| $context.applyTemplates(Node, xpathexpr) | Applies the XPath expression to the specified node, and applies templates to the resulting nodeset. | |
| $context.applyTemplates(Node, xpathexpr) | Applies the XPath expression to the specified node, and applies templates to the resulting nodeset. | |
| $context.getAppValue(Object key) | Returns the application value for this key. For example, Ant will place the current input file name under the key "infilename". |
DVSL has default patterns to drive the transformation engine just like XSLT does. These patterns currently are modeled after the XSLT default behavior. DVLS differs in that it will offer you the abillity to override the default patterns w/o having to change your stylesheet. The patterns are :
#match("/")$context.applyTemplates()#end #match("*")$context.applyTemplates()#end
These patterns are registered in the matching engine first, so any patterns specified in the stylesheet will override these definitions.
What this means for the user is that DVSL will automatically start with the root of the document (in the XSL sense, the the 'properly formed document sense') and try to match each element that it finds. Because it has a default rule for elements ("*") it will appply templates to all nodes in each element that it finds. Further it will print out the value of each text ndoes, and each attribute node.
These rules are copied from the XSLT spec. There are two more rules that have been commented out :
#match("text()")$node.value()#end #match("@*")$node.value()#end
which should be there for XSLT spec compliance. If you want them, just
uncomment in org.apache.dvsl.resource.defaultroot.dvsl
and rebuild the jar.
They are currently left out as they don't seem to be desireable, and it doesn't appear that xalan respects the rules either.


--- layout: page title: NOCSI — Careers eleventyNavigation: key: Careers --- {% from "macros/typography.njk" import tagline, title %} {% from "macros/buttons.njk" import view_open_opportunities %} {% from "macros/tag.njk" import tag %}
| Role | Type | Status | Skills |
|---|---|---|---|
| {{ currentJobListing.role }} | {% for type in currentJobListing.type %} {{ tag(type.name, type.color) }} {% endfor %} | {% for status in currentJobListing.status %} {{ tag(status.name, status.color) }} {% endfor %} | {% for skill in currentJobListing.skills %} {{ tag(skill.name, skill.color) }} {% endfor %} |
If anything interests you, see the contact details in the post or send an email to<EMAIL_ADDRESS>and introduce yourself. We'd love to meet you.
Oh, and one more thing. If you could really see yourself at NOCSI but don't see a role that fits what you're looking for... please still let us know.


if access any following 3 pages, always show page03.html
http://nginx-training-03.local:18080/redirect_chain02/page01.html
↓ redirect
http://nginx-training-03.local:18080/redirect_chain02/page02.html
↓ redirect
http://nginx-training-03.local:18080/redirect_chain02/page03.html
access with "no-redirect" parameter, show original request page.
http://nginx-training-03.local:18080/redirect_chain02/page01.html?no-redirect
http://nginx-training-03.local:18080/redirect_chain02/page02.html?no-redirect
http://nginx-training-03.local:18080/redirect_chain02/page03.html?no-redirect


This simple risk analysis method provides data on hard to measure risks. This method is geared towards security teams who want to reduce risks, and measure those reductions.
It can be explained briefly:
Far more digestable explanations exist in this slideshow, and this medium article, if you are looking for less intimidating introductions to probabilistic risk.
This is based on the Probabilistic Risk Assessment methodology used in aerospace, nuclear, oil, and other environmental industries. This document simplifies these practices and focuses on the available research to improve collaborative forecasting.
When you are done with this document, you might own a forecast that looks something like this.
A remote adversary will access a production server in Q2.
This is not an example of fortune telling. Instead, we are measuring uncertainty about a risk. Uncertainty is part of what drives our intuition about risk, and is the basis for most of the decisions we make.
For example, total uncertainty about the above scenario would result in a 33%/33%/33% forecast. If you wouldn't agree with those probabilities, it's because you have a measurable uncertainty that differs from them.
This document suggests ways to reduce cognitive bias, introduce skepticism, develop evidence gathering, and find consensus in prioritizing risk.
A scenario is influenced by any combination of a threat, vulnerability, or an impact. Choose a scenario that best reflects your concerns and mitigation efforts. Make sure it is time specific, so it can expire in a reasonable time. Here are some examples:
Choose a scenario that best represents the risk you're concerned about, and how you are organizing your effort to reduce that risk.
Here's an example of how this differs, with small variances on a similar risk:
The first scenario is influenced by reducing the odds that a bank robber could get to the vault. Any risk mitigation effort will be centered around the bank robber's ease of access to the vault.
The second scenario is most influenced by limiting the overall amount of funds that are needed in the vault. It assumes that a bank robber,
The third scenario implies aspects of both. Mitigation efforts for the third scenario will be influenced by reducing the probility of the attack, but also anything that would slow the attacker down or limit their capacity to succeed. By being more vague about the threat actor, it also consider something like an insider threat into calculation.
The fourth scenario is related to a specific vulnerability. This would encourage efforts to mitigate the vulnerability entirely, or add compensating controls focused on a specific problem.
You can see that being intentionally specific or vague in developing a scenario allows you to include or exclude known and unknown risks. This concept is developed further here. Skillfully crafting the right scenario can attract mitigation techniques that are properly scoped to your expectations, while allowing and attracting creative solutions.
The scenario needs two qualities for us to forecast it. The first, is a reasonable timeframe the event could occur (months, quarter, year). Second, is a structured set of outcomes for the forecast, which we can build in many ways.
The following forecast examples measure these various aspects of probability and / or impact. Someone could forecast the probabilities involved with any one, or multiple, of these outcomes.
If we choose to use the third example, the forecasts would look like this:
A remote adversary gains a foothold on a production server in Q2.
Some events happen so infrequently, you are simply forecasting if it will happen at all. A nice structure for that is divvying up the probability of something happening once, more than once, or not at all.
85%: Won't happen. 10%: Will happen. 5%: Will happen more than once.
Scenarios related to impact do well with estimating a range of values that you are mostly sure the correct result will fall into. For instance:
I am 90% confident I will lose $0-100
You can also estimate whether an incident will become an initiating event for a larger attack.
10% chance the adversary will go on to pivot throughout our network.
Identify the events that lead up to this larger event. This process looks very similar to threat modeling.
What events might take place before the big event occurs? There are likely very many. Some examples:
The research done around human estimation suggests that forecasters who decompose a problem will have improved forecasts. This is sometimes referred to as the "Fermi Problem".
This is why it's sometimes valuable to substitute relevant scenarios for ones we are lacking data around. For instance, you can better estimate the average height of an apple tree by knowing the average hight of an orange and pear tree. It helps bring you into a ballpark with "outside" information, to which you'll apply your own estimation skills.
You may discover that the risk you have identified already has a "kill chain", or an "attack matrix" defined.
In probability risk assessments in the nuclear industry, these are often called "Initiating Events".
NASA also calls these initating events, and has documented this process here (3.3.1).
Research suggests that training will drastically improve the reliability of our forecasts. This online training resembles the training used in that research. Our ultimate goal is to calibrate the Brier score of people involved with this process. Established biases should be taught to forecasters in this training, as well as concepts like the "overconfidence effect".
We want participants to resemble a weather forecasters as much as possible. That is, someone who is constantly held accountable for the outcomes of their forecasts.
Humans are wildly overconfident, and experts can be even worse. Research strongly suggests this to be the case.
This poor quality can be measured easily in any person. The Brier score is a dead simple method used to measure how calibrated a person's sense of confidence is with their actual knowledge. It can be fixed quickly.
The most important aspect of forecasting is the Brier Score. A feedback loop that holds you accountable for your miscalibration will rapidly improve it. By being constantly tested and accountable for our forecasts, we can quickly prevent ourselves from becoming overconfident.
There are plenty of online materials to recreate the training used in the above cited research. The aim of training is to make individuals self aware of common sources of cognitive bias, our natural reactions to new information, and overconfidence.
This research shows that calibration against
In general, training and awareness of cognitive bias, combined with practice, are critical.
Now your forecasters should have opinions and demands for evidence that influence the potential outcomes of these scenarios. We want to get forecasters decision making data.
Do not limit your imagination to whatever frequency based historical statistics you can pull together.
During training, a forecaster should be hyper aware about their tendancy to overvalue certain types of data, and our process will limit the volatility introduced by a drastic bias. This allows us to introduce all forms of information.
Audit results, interviews, opinion briefs, and cross industry data are all useful and the forecaster will observe them with measure.
Forecaster demand is important. Don't bother collecting data that a forecaster won't find useful. No need to overdo it on collection.
Nobel prize winning research describes effective forecasting as using "outside" and "inside" data. For instance, industry data that says it takes eight months to discover a breach would be considered "outside" data. If you have data to make you believe you are better or worse than industry standard, that would be considered "inside" data. Seek out both outside data, as well as inside data, and make sure your forecasters understand the difference.
As forecasts occur over time, previous forecasts themselves can be useful as "stand-in" data where no other data exists.
However, data collection that is useful for statistical modeling will quickly replace a forecast, or better inform a forecaster than a previous forecast alone. Always prefer better data.
The Blockchain Graveyard is an example of postmortem data with a low signal of truth. It relies on expert estimation of root cause based on unreliable data. It is still extremely useful as data for forecasting.
If forecasting methods become more common, it will be simple to share forecasts and data for similar scenarios with companies within your industry. Or, for instance, higher risk scenarios or industries. If a university network can produce data that ~%50 of hosts on a dormitory wireless network exhibit signs of compromise over the course of a year, a forefcaster can use that data to narrow their estimations of a managed and invested network.
This is as simple as recording your forecasts into a spreadsheet. A group of forecasters should get a chance to discuss their forecasts and modify them. This will help reveal scenario misunderstandings, or dramatic differences in how evidence was interpreted per person.
Record the average of forecasted values to create a representative forecast.
There is a lot of flexibility in how often you measure forecasts over time, as these are numeric values and you can track their progress very simply. You may want to trigger measurement at certain milestones to ensure that the team still feels progress will be made.
Our database is dumped and exfiltrated during an infrastructure breach this year.
Forecast: Percentage of never happening, happening once, or more than once.
| Forecaster | Never | Only once | More than once |
|---|---|---|---|
| 1 | 75% | 20% | 5% |
| 2 | 80% | 18% | 2% |
| 3 | 40% | 25% | 35% |
| Average | 65% | 21% | 14% |
Should new information come to the forecasters at any time, they may update these scenarios. For instance, let's say your team receives scary results from penetration test. This may cause probability to reduce from the "never" column and move to the "once" column.
Alternatively, a deployment of second factor authentication may move probability to the left, into the "never" column.
This example shows the use of multiple forecasters. A simple average of multiple forecasts has been shown to help smoothen out biases and misunderstandings across multiple people.
Panels of forecasters with expertise in their subject area are a very common risk assessment tool used in many high risk industries.
Diversifying a panel with asset owners, leadership, technical experts, or even outside consultation will help add integrity to the forecast.
Of note, teams of less informed forecasters were used to compete with intelligence agencies armed with classified information, and won by a broad margin. Alternatively, when intelligence agencies that employ these forecasting methods with tight feedback loops see very positive results when forecasting complex scenarios.
For great information on why ordinal scales should not be used, see research done by Sherman Kent which suggested improvements to the National Intelligence Estimate process. The value of estimates made by the entire intelligence community were diminished because of misunderstandings in the words used to express confidence, which were fixed by a quantitative system.
Additionally, see the "Delphi" method, developed by RAND in the 50's, which suggests a "forecast, talk, forecast" approach to a forecast using a panel.
Lastly, you may want to train individuals on different ways to interpret to probabilities they assign in frames of time. For instance, a 10% annual probability should occur every ten years on average. 50% probability will occur once every other year on average. Someone may quickly say 5% without also reasoning that it means a probability of once every 20 years. You can confront a forecaster with that realization and it will help them settle their forecast into a place that makes more sense to them.
When the forecast timeframe "closes", discuss with the team if the event occurred. You can discuss the root cause, update any scenario decomposition, and begin maintaining the event as a form of historical data for future forecasting.
It is critical to hold a review and observe the correctness of forecasts. Reward accurate forecasts and post-mortem forecasts that were high confidence and incorrect.
For example, if an individual or panel states 90% confidence that a system will be breached within the next quarter and is clearly not breached... then this is a topic for discussion and course correction. These misses will damage a panel or individual's Brier score over time.
This method is highly reliant on "hunting", audit logs, and detection. It may warrant a secondary effort to thoroughly review a backlog of activity for a specific type of compromise, thus providing you with confidence that a hard-to-detect event didn't occur.
Whether or not your detection capability or log reliability will be useful in a future incident is also a forecastable scenarios that can be improved through this process.
It's perfectly OK to be skeptical that your efforts to detect an issue weren't thorough. Sometimes we aren't in a place where we can truly rely on our detection capability. In fact, this skepticism is common, and can be tracked by yet another forecast:
We have detected a malicious process running on our bastion server.
Forecast: Yes (55%)
If there is a massive drop off in confidence about your detection capability, you can then pivot and decide if trust needs to be built, or if a different approach altogether is necessary.
In this document, we've measured the outcomes related to an invidual scenario. This is considered to be a single risk analysis.
Eventually, you'll desire having a broader enumeration of scenarios that you'll forecast. This is how risk assessments work at their core, across many scenarios.
Deciding on which risks to tackle first can be as simple a cumulative vote, which represents group estimation as well. When enough resource appears to measure or forecast impact, you can then mature to a numeric approach to prioritization.
This is an draft risk management approach for teams who have outgrown checklists and maturity models. There are plenty of known problems, so please use an indoor voice when pointing them out.


Sales & Account Manager
Global Delivery
Operations
Consulting
Delivery
Technology
Creative
PM
Business
Technology
Creative
PM
Business


Start by selecting a runtime or mission. Secondary selection will be narrowed based on your primary selection.


--- title: Twitter Tools date: '2009-09-27 19:15:55 +0200' date_gmt: '2009-09-27 17:15:55 +0200' categories: - Webdev ---
Trying out Twitter Tools plugin for WordPress.


Emmerdale viewers fed up of Charity Dingle as she lashes out at her family
Charity left Moses with Cain!
by Charlotte RodriguesViewers of Emmerdale are fed up with Charity Dingle after she has lashed out at her family, including cousins Cain and Aaron.
Last week, after the break down of their relationships, Cain and Aaron stole cars with the plan to sell them on, but things went haywire when Sean, the man who stole the cars originally, tracked them down.
In last night's episode (November 12 2019) Charity was also struggling after her fiancée Vanessa Woodfield ended their relationship due to her involvement in the casino scam.
Read More: Emmerdale SPOILERS: Lydia find out she could have Huntington's disease
Struggling to look after her son Moses, Charity left him with Cain, despite him telling her he was busy that day.
When Aaron's sister Liv returned home, Cain left Moses with her.
As they were at the park, Liv was distracted by a woman asking for directions, meanwhile little Moses was kidnapped.
Read More: Emmerdale SPOILERS: Sarah risks her life by taking drugs
When Cain and Aaron were forced to come clean to Charity about what happened and the car theft, Charity freaked out, especially as Sean threatened to burn the car with Moses inside.
As she continued to blame her cousins for Moses' kidnapping, viewers got fed up as she palmed him off on Cain in the first place.
Luckily, Nate found Moses wandering round the village and brought the little boy home to his mum.
Tonight, Charity let rip at Cain and Aaron again, insisting 'sorry' wasn't enough.
Chas went into defend her son and Charity has been left totally at war with her family.
Emmerdale airs weeknights at 7pm on ITV, with an extra episode at 8pm on Thursdays.
Leave us a comment on our Facebook page @EntertainmentDailyFix and let us know what you think!


5.1 Start position / 5.2 Header / 5.3 First instruction / 5.4 Main routine (V6) / 5.5 Initial execution point (other versions)
A routine is required to begin at an address in memory which can be represented by a packed address (for instance, in Version 5 it must occur at a byte address which is divisible by 4).
A routine begins with one byte indicating the number of local variables it has (between 0 and 15 inclusive).
In Versions 1 to 4, that number of 2-byte words follows, giving initial values for these local variables. In Versions 5 and later, the initial values are all zero.
Execution of instructions begins from the byte after this header information. There is no formal 'end-marker' for a routine (it is simply assumed that execution eventually results in a return taking place).
In Version 6, there is a "main" routine (whose packed address is stored in the word at $06 in the header) called when the game starts up. It is illegal to return from this routine.
In all other Versions, the word at $06 contains the byte address of the first instruction to execute. The Z-machine starts in an environment with no local variables from which, again, a return is illegal.
Note that it is permissible for a routine to be in dynamic memory. Marnix Klooster suggests this might be used for compiling code at run time!
In Versions 3 and 4, Inform always stores 0 as the initial values for local variables.
Section 1 / 2 / 3 / 4 / 5 / 6 / 7 / 8 / 9 / 10 / 11 / 12 / 13 / 14 / 15 / 16
Appendix A / B / C / D / E / F


WITNESS LIST Higher Education Committee April 23, 2003-2:30P HB 613 Against: Harris, Dwight (Texas Federation of Teachers) Hempstead, Chuck (Texas Association of College Teachers) Zucker, Dr. Charles (Texas Faculty Association) HB 796 On: Flack, Teri E. (Texas Higher Education Coordinating Board) HB 838 For: Stevens, John (Texas Business and Education Coalition) HB 1058 For: Mittelstet, Dr. Stephen K. (President Mittelstet Richland College) On: Castillo, Professor Darrell (Richland College of the Dallas County Community College District) HB 1746 For: Landry, Todd A. (Spaulding for Children) On: Benham, Rose (Child Protective Services) HB 2117 For: Zucker, Dr. Charles (Texas Faculty Association) HB 2633 On: Flack, Teri E. (Texas Higher Education Coordinating Board) HB 2802 For: Gavras, John C. (Dallas-Fort Worth Hospital Council) On: Blanck D.O., Ronald R. (UNT- Health Science Center) McQueen, Greg (UNT- Health Science Center) HB 2862 On: Goldsmith, Clair W. (University of Texas System) Kennedy, Kerry (U.T. System Adminstration) HB 3015 For: Zafereo, Mark (Self) Against: de la Torre III, Pedro (Self) Dobbs, Andrew W. (Legislative Relations Agency) Eichenbaum, Marc (Student Body) Haley, Brian (UT Student Body) Hodgkin, Mark (Young Conservatives of Texas) Jiang, Wei (Self) Kinghorn, Austin (Young Conservatives of Texas) Majid, Slyman (Student Government - The University of Texas at Austin) Nation, John (Self) Neumann, Zach (Student Body) Pravda, Bryan (College Republicans, University Democrats, UT&A&M Young Conservatives of Texas, Student Government) Pruett, John (Self) Reinlie, Lauren (Self) Schwellenbach, Nicholas (Self) Stolhandske, Matt (Self and Young Conservatives of Texas) Taylor, Will (Self) Van Zant, Austin (Self) Walden, Justin (Self) Wilder, Forrest (Self) On: Ruth, Andrew (Comptroller's Ofc - Texas Tomorrow Fund) HB 3262 On: Doblin, Steve (Lamar University) Martin, Gabriel A. (Tony) (Lamar University) Schultz, Russ (Lamar University) Simmons, James (Lamar University) HB 3321 On: Moore, Richard S. (The University of Texas Medical Branch) HB 3331 For: Cryan, Charles (Self and City of College Station) McDonald, Carol (Independent Colleges and Universities of Texas, Inc) Ramsey, Dr. Curtis P. (Self and Texas School's Tax Base Defense Coalition) Sims, Randy (Self and Brazos Co.) Woolfolk, Rick (Self and Denton Independent School District) Against: Bul, Stewart (JPI) Moon, Thomas Allen (Texas Student Housing Corporation - Denton Project) Smyth, Henry C. (Hank) (Texas Student Housing)


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Preparation time
less than 30 mins
Cooking time
no cooking required
Serves
Makes 6 sandwiches
These sandwiches take no time to make and are great for a school packed lunch.
Each sandwich provides 347 kcal, 30g protein, 29g carbohydrate (of which 2.2g sugars), 12.5g fat (of which 2.5g saturates), 3g fibre and 1g salt per portion.
Mix the mayonnaise and pesto together in a bowl. Gently stir in the shredded chicken.
Fill the rolls with the chicken mixture and top with some rocket.


var receiptEmail: String?
Email address that the receipt for the resulting payment will be sent to.
See receipt_email.


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Hyundai Aura engine, gearbox options revealed
by Amaan AhmedThe successor to the Xcent, the Hyundai Aura will get BS6-compliant versions of the 1.2-litre petrol, 1.2-litre diesel and 1.0-litre turbo-petrol engine; manual and AMT options will be on offer.
Having confirmed the name of its all-new compact sedan a few days ago, Hyundai has now revealed the engine options for the Aura. A total of three BS6-compliant engines will be available for the Hyundai Aura – two petrols and a diesel.
All three engines are units we’re familiar with – there’s a 1.2-litre, four-cylinder petrol, a 1.2-litre three-cylinder diesel, and a 1.0-litre turbo-petrol. In BS4 guise, the 1.2 petrol produces 83hp and 114Nm, the 1.2 diesel makes 75hp and 190Nm, so expect the BS6-compliant versions to have roughly the same power outputs. Going forward, tese upgraded engines will also be introduced on the updated Xcent, which will continue as an offering for commercial-use buyers.
The Aura’s 1.0-litre turbo-petrol is also available with the Hyundai Venue but is expected to run in a lower state of tune in the compact sedan. Much like the sportier Grand i10 Nios (set to be launched early-2020), the Hyundai Aura turbo-petrol is likely to produce 100hp.
Hyundai has also stated it has employed a Lean NOx Trap (LNT) to help the 1.2-litre diesel engine meet BS6 emission norms, instead of a more complex (and costly) selective catalytic reduction system seen on some expensive diesel cars and SUVs.
Also revealed are the gearbox options for each version of the Hyundai Aura. A 5-speed manual is available on the 1.2-litre petrol and diesel models, accompanied by the option of an automated manual transmission (AMT). The 1.0-litre turbo-petrol variant, however, will only come with a 5-speed manual. Interestingly, this is the same engine-gearbox combination you’ll see on the sportier Grand i10 Nios.
In terms of design, the Aura will share most of its body panels and interior with the Grand i10 Nios, and will be in line with Hyundai’s sedan family. The Nios’ 8.0-inch touchscreen infotainment system with Apple CarPlay and Android Auto connectivity will also be carried over, and it’ll be interesting to see if Hyundai chooses to spec the Aura with its BlueLink connected-car tech.
When it is launched in the coming months, the Hyundai Aura will battle the Maruti Suzuki Dzire, Honda Amaze, Ford Aspire, Tata Tigor, and Renault’s upcoming LBA compact sedan.
Which engine-gearbox combo for the Hyundai Aura do you think will be the most appealing? Let us know in the comments.
Also see:
Grand i10 Nios vs Swift vs Figo petrol comparison
Now, book your service appointment on Whatsapp: Hyundai India
Hyundai Grand i10 now sold as petrol-only