vignettes/articles/02_a_la_carte_workflow.Rmd
02_a_la_carte_workflow.Rmd
Single Cell Toolkit (singleCellTK, SCTK) is a package that works on single-cell RNA-seq (scRNAseq) dataset. SCTK allows users to import multiple datasets, perform quality control and a series of preprocessing, get clustering on cells and markers of clusters, and run various downstream analysis. Meanwhile, SCTK also wraps curated workflows for celda and Seurat.
This tutorial takes the real-world scRNAseq dataset as an example, which consists of 2,700 Peripheral Blood Mononuclear Cells (PBMCs) collected from a healthy donor, namingly PBMC3K. This dataset is available from 10X Genomics and can be found on the 10X website.
Before heading into the next steps, we assume that users have already loaded SCTK, imported and QC’ed the PBMC3K data, following the Import and QC Tutorial.
After removing cells of low quality, we next need to normalize the feature expression matrix. In this tutorial, we apply a global-scaling normalization method from scater, "logNormCounts"
. It normalizes the feature expression for each cell by the total expression, multiplies this by a scale factor, and log-transforms the result.
For detail about all normalization methods, please refer to the Normalization Documentation
"Scater - LogNormCounts"
from the left panel.SCTK has a generic wrapper function for various types of normalization, called runNormalization()
.
sce <- runNormalization(sce, useAssay = "counts", outAssayName = "logcounts",
normalizationMethod = "logNormCounts")
SCTK also supports a number of batch correction methods. Here we don’t present the workflow because PBMC3k dataset only has one batch. For examples, please refer to the document of batch correction.
We also recommend performing the scaling method to standardize the variance, and this results in a better PCA. The UI and console function allow users to perform scaling on the expression assay. However, we don’t recommend directly apply this to the full-sized expression matrix because the memory usage will be large. To accomplish this, we suggest finding the highly variable genes first in the next section, and only scaling the subset of the expression matrix as instructed.
Selecting highly variable genes (HVG) for downstream analyses is recommended, since a subset of variable features enhances the biological signal for community detection and reduces amount of data being used which hence speeds up the computation. SCTK wraps the methods used in Seurat and Scran. We recommend keeping at least 2,000-5,000 HVGs. In this tutorial, we use the “modelGeneVar” method from Scarn, and select the top 2,000 genes.
SCTK requires at least two steps to create the HVG subset. The first step performs variability calculation and stores the metrics, and the second step selects top genes basing on the ranking of the metrics.
After calculation, the panel for selecting the top features, “2. Select number of variable features” becomes enabled. A scatter plot of features, with axes of variance and mean, will also be shown on the right panel “Plot”.
After selection, the plot will be again updated, with highlighted red dots representing the selected features, texts labeling a smaller number (adjustable in the dropdown) of features with the top variability among the selected ones. The names of highlighted features are also updated in a text box at the bottom of the plotting region.
Note that:
For calculating the feature variablity, users can use either the wrapper function of each method (runSeuratFindHVG()
, runModelGeneVar()
) or using the generic wrapper runFeatureSelection()
with argument method
specified.
sce <- runModelGeneVar(sce, useAssay = "logcounts")
sce <- setTopHVG(sce, method = "modelGeneVar", hvgNumber = 2000, featureSubsetName = "hvg2000")
Users can also get the character vector of gene names:
## [1] "LYZ" "S100A9" "FTL" "HLA-DRA" "CD74" "CST3" "S100A8"
## [8] "FTH1" "NKG7" "TYROBP"
The variability metrics and the top variable feature selection can also be visualized:
plotTopHVG(sce, method = "modelGeneVar", hvgNumber = 2000, labelsCount = 10)
The next step is performing a principal component analysis (PCA), which creates new uncorrelated variables that successively maximize variance and finally increases the data interpretability and at the same time minimizes the information loss.
With the HVG selected from the previous step, we will perform PCA using the method from Scater. As mentioned in the Normalization section, we will also have the selected HVG scaled in this step.
SCTK also supports Seurat’s PCA and ICA method, which do a similar job. Please see: Seurat Curated Workflow, and Dimension Reduction Documentation.
What we actually set for the parameters:
Besides the scatter plot of the top two components for all cells, the switches also add an elbow plot and heatmap for visualization
After running, the plots will be updated on the right side. The elbow plot and heatmaps are internally calculated by Seurat functions.
The elbow plot is a heuristic method for determining the dimensionality to be used for downstream analysis. It is a ranking of principle components based on the percentage of variance explained by each one. In this example, we can observe an “elbow” around PC9-10, suggesting that the majority of true signal is captured in the first 10 PCs.
The heatmap allows for easy exploration of the primary sources of heterogeneity in a dataset, and can be useful when trying to decide which PCs to include for further downstream analyses. Both cells and features are ordered according to their PCA scores. Please refer to Seurat’s tutorial for more explanation on these two visualization approaches.
Here we use the wrapper function scaterPCA()
. The name of transformed normalized expression matrix can be passed to useAssay
(by default useAssay = "logcounts"
), and the name of the HVG subset should be passed to useFeatureSubset
. The scaling will be done by Scater by setting scale = TRUE
(default). The output PCs will be updated in the reducedDims
slot of the SCE object, named by "PCA"
by default.
sce <- scaterPCA(sce, useFeatureSubset = "hvg2000", seed = 12345)
Afterwards, users can make scatter plots to visualize the top dimensions that explains the most variance of the original data:
plotDimRed(sce, useReduction = "PCA")
Uniform Manifold Approximation and Projection (UMAP) and t-distributed Stochastic Neighbor Embedding (tSNE) are the most commonly used methods to visualize the relationships between the cells in a 2-D embedding. UMAP gives a better presentation of the global structure and is more efficient, while tSNE performs better in preserving the local structure.
In this tutorial, we calculate a UMAP embedding from the principal components generated in the previous step. We will use only 10 dimensions out of the 50 dimensions generated.
After done, a scatter plot of all cells on the UMAP dimension will be shown on the right panel.
A UMAP can be generated with the function runUMAP()
, which is a wrapper of calculateUMAP()
method in the scater
package. We will now use useReducedDim
argument to pass the PCA embedding just generated to the function. The result will be saved in reducedDim
slot.
Users can also create the tSNE embedding with runTSNE()
function, which works in a similar way as runUMAP()
sce <- runUMAP(sce, initialDims = 10, seed = 12345)
plotDimRed(sce, useReduction = "UMAP")
Note that we have another two functions runQuickUMAP()
and runQuickTSNE()
, which wrap the two functions mentioned above, respectively, and run directly from raw count matrix with all steps in the workflow automated internally. They can help with fast visualization at the beginning of an analysis.
SCTK supports clustering cells with Shared Nearest Neighbors (SNN) graph based methods and K-Means algorithm. For SNN graph based methods, we wrap the graph constructor from scran
library, and have options of algorithms from igraph
that can perform clustering on the graph. Alternatively, in the Seurat Curated Workflow, the Seurat’s SNN graph construction and community detection method are also wrapped as one method.
In this tutorial, we use the scran SNN graph approach, with the community detection algorithm set as Louvain. We will use the top 10 components for identifying the clusters. Though we have generated the UMAP representation in the previous section (also using 10 PCs), users are always allowed to test clustering with different numbers of PCs. In this case, we strongly suggest regenerating the UMAP with the consistent number of PCs, so that the UMAP can best reflect the information included in the PCs.
For the scran SNN graph approach, the parameter k
can always be tweaked as it affects the connectivity of the graph. When k
is larger, stronger connection will be constructed across the cells, thus larger and fewer clusters will be identified. Parameter weightType
allows for different shared neighbor weighting schemes. In this tutorial, we use "jaccard"
as it provides consistency with Seurat methods.
Upon completing clustering, a scatter plot of cells on a low-dimensional representation with cluster labeling colored on each cell will be shown on the right. However, we use the dimensions used for calculation as the default. For the best visualization, we suggest users change the dimensions to the 2D embedding obtained from the same components (of the same PCA matrix) as used for clustering.
With runScranSNN()
function, the dimension reduction matrix can be specified through argument useReducedDim
, and the cluster label assignment will be updated in the colData
slot, and the variable will be named by argument clusterName
. The default graph clustering algorithm is Louvain, while we also provide options including Leiden, Walktrap and etc. (from igraph
).
sce <- runScranSNN(sce, "PCA", clusterName = "cluster", nComp = 10,
weightType = "jaccard", k = 14, seed = 12345)
After getting the cluster labeling, we can then visualize it:
plotSCEDimReduceColData(sce, "cluster", "UMAP")
In the other curated workflow that SCTK wraps (Celda Curated Workflow), we use a Bayesian hierarchical model that can bi-cluster features into modules and observations into subpopulations. For detail of this method, please refer to the Celda Documentation.
Users can next perform marker detection process with the cluster labels, or any other types of reasonable grouping of similar biological state of cells stored in the cell metadata. SCTK iteratively finds markers for each cluster by running differential expression (DE) analysis on the cluster against all the other clusters.
Although we selected the variable features and reduced the dimensionality of the original expression matrix, here we will get back to the transformed normalized counts of all features.
After the analysis is done, the result would be presented in the right main panel, with a marker heatmap and the table of statistical metrics. Users can tweak the displaying parameters of each through the dropdown menu or filter module, respectively.
sce <- runFindMarker(sce, useAssay = "logcounts", method = "wilcox", cluster = "cluster")
By running runFindMarker()
, SCTK stores a data.frame
of marker table to the matadata
slot of the SCE object. The marker table will include all detected markers for each cluster and statistical values associated to each marker. To fetch the table, users can use the command below, and even add filtering parameters.
topMarkers <- getFindMarkerTopTable(sce, topN = 1, log2fcThreshold = 0,
fdrThreshold = 0.05, minClustExprPerc = 0.5,
maxCtrlExprPerc = 0.5, minMeanExpr = 0)
topMarkers
## Gene Log2_FC Pvalue FDR cluster clusterExprPerc
## 8764 IL7R 0.8117772 9.627633e-63 5.253157e-59 1 0.7500000
## 198011 CD3E 0.6404728 4.261088e-42 1.660708e-39 2 0.7769517
## 1956 S100A9 4.3853548 2.397248e-207 3.924055e-203 3 0.9977064
## 106781 HLA-DRA 3.2752984 1.682895e-182 2.754731e-178 4 1.0000000
## 26825 CCL5 3.0924934 1.691729e-148 5.538382e-144 5 0.9712644
## 106091 LST1 2.8683989 1.038405e-98 1.133177e-94 6 1.0000000
## 310761 NKG7 4.2398710 3.256027e-82 1.065958e-77 7 1.0000000
## 288182 CST3 3.2975861 2.221917e-16 1.039159e-12 8 1.0000000
## 7697 PPBP 5.9620589 9.423341e-07 2.504757e-03 9 1.0000000
## ControlExprPerc clusterAveExpr
## 8764 0.31156265 1.266208
## 198011 0.41455242 1.272202
## 1956 0.23094477 4.733569
## 106781 0.49538867 4.406597
## 26825 0.21676174 3.470436
## 106091 0.30477759 3.454109
## 310761 0.25687702 4.781861
## 288182 0.39113680 4.371755
## 7697 0.02406417 5.989445
For visualization, SCTK has a specific heatmap plotting function for detected markers. The heatmap will take the log-normalized feature expression matrix for the values (scaled when plotting), and subset the features to only the top markers of each cluster. For the organization of the heatmap, the function groups the markers by the belonging to the clusters, and groups the cells, obviously, by clusters.
plotFindMarkerHeatmap(sce, topN = 5, log2fcThreshold = 0.5,
fdrThreshold = 0.05, minClustExprPerc = 0.5,
maxCtrlExprPerc = 0.5, minMeanExpr = 0,
rowLabel = TRUE)
As we can observe from the marker heatmaps above, most of the clusters can be easily differentiated by the top marker genes of each cluster. However, “cluster 1” and “cluster 2”are seemingly having less difference between each other than compared to other cell clusters, in terms of the marker genes presented in the heatmap (top 5 markers for each cluster). To further explore the differential expression between them, we could do a cluster-by-cluster DE analysis in the next section.
Beyond finding the markers for each cluster, usually people are also interested in the differential expression between specific clusters and even groups of clusters. SCTK provides a relatively flexible way for conducting such analysis.
There are multiple ways to specify the groups of cells to be compared: by either directly specifying indices of cells, or selecting groups of cells with a categorical variable annotated in the cell metadata. However, when running DE analysis, SCTK requires a relatively sophisticated inputs for naming the analyses, including the names of the two groups, and the name of one analysis, though these are not necessary for calling the algorithms alone. By requiring these, the results of the analyses can be stored with human readable identifiers and within one single data container (SCE object), and can be more manageable. See the DE documentation for the detail.
Continued from the previous section, we will now set “cluster 1” and “cluster 2” as the two groups to perform the analysis.
After running, The visualization section at the bottom of this tab will be automatically updated. SCTK provides a heatmap, a table of statistic metrics, a volcano plot, a violin plot and a regression plot for visualization. Users can tweak the display option through the dropdown menu of a plot or the filtering module of the table.
runDEAnalysis()
is a generic function for performing differential expression (DE) analysis between two selected groups of cells. This is also used by runFindMarker()
. By running DE analysis, the function will take the expression assay with all features and perform statistical analysis to discover quantitative changes in expression levels between selected groups.
sce <- runDEAnalysis(inSCE = sce, method = "wilcox", useAssay = "logcounts",
class = "cluster", classGroup1 = c(1), classGroup2 = c(2),
groupName1 = "cluster1", groupName2 = "cluster2",
analysisName = "cluster1_VS_2")
Similarly to the marker detection section, SCTK also has a DE analysis specific heatmap plotting function, plotDEGHeatmap()
. Here, users can just easily enter the analysisName
specified for one run and the function will automatically arrange the output. The heatmap is also splitted into a “checker board”, by the “conditions” (i.e. the groups selected when running runDEAnalysis()
) and the “regulation” (i.e. “up” if the log2 fold change is positive in “group1” against “group2”).
plotDEGHeatmap(sce, useResult = "cluster1_VS_2", log2fcThreshold = 0.3, rowLabel = TRUE)
Besides using a feature expression assay for DE analysis, SCTK also allows using matrices stored in the low-dimensional representation slot of the data container (useReducedDim
argument of runDEAnalysis()
). For example, when users perform a pathway analysis and get a score matrix (stored in reducedDims
slot), DE analysis can be performed on this score matrix. See example.
SCTK adopts SingleR method for labeling the cell types. Briefly, this method labels each cell (or cluster) in users’ datasets basing on similarity to a reference datasets. SingleR has recommended some datasets, so we enable quick loading of these references. Please see Cell Type Labeling Documentation for detail.
Choosing a reference from the recommended builtin references would also require some prior knowledge of user data. Users should choose a reference that covers the cell types possibly existing in the user dataset. SingleR works by scoring the similarity to each cell type and assigning a cell type by the highest score, regardless of how low the score is. A beta cell from pancreas data could even be wrongly labeled as a platelet if using a blood cell reference.
Users can visualize the labeling via a UMAP, by going back to the clustering tab.
first.labels
, labels
or pruned.labels
.The recommended reference can be chosen by specifying the abbreviation name of them in argument useBltinRef
. Please click on the function name for usage detail.
sce <- runSingleR(sce, useAssay = "logcounts", level = "fine")
The result of labeling will again be saved to colData
slot of the SCE object. There will be multiple types of information being stored, including a scoring matrix named by "SingleR_{ref}_{level}_scores"
, where {ref}
refers to the reference selected, {level}
refers to the level
argument being passed to the function. And three "SingleR_{ref}_{level}_{typeOfLabels}"
columns, where {typeOfLabels}
includes first.labels
, labels
, pruned.labels
. For the difference, please refer to ?SingleR::classifySingleR
.
We can also plot the labeling on to the UMAP we got previously.
plotSCEDimReduceColData(sce, colorBy = "SingleR_hpca_fine_pruned.labels",
reducedDimName = "UMAP")
The goal of the differential abundance analysis is to determine if categorical variables such as phenotype or sample (e.g. treatment or control) are enriched in different cell clusters using the Fisher’s exact test (FET). Any categorical variables in colData(sce)
can be used by passing the variable name to argument cluster
or variable
. Categories in the phenotype variable (used for variable
) can be passed to case
or control
. For this example, we try to examine whether there are any cell clusters enriched in an annotated cell type using SingleR.
# Returns a vector where TRUE for a type of NK cell
isNKCell <- startsWith(colData(sce)$SingleR_hpca_fine_pruned.labels, "NK_cell")
# Returns a vector where TRUE for a type of T cell
isTCell <- startsWith(colData(sce)$SingleR_hpca_fine_pruned.labels, "T_cell")
# Make up a variable with only categories of "NK_cell", "T_cell" and "Other".
colData(sce)$cell_type <- ifelse(isNKCell, "NK_cell", "Other")
colData(sce)$cell_type[isTCell] <- "T_cell"
colData(sce)$cell_type[is.na(colData(sce)$cell_type)] <- "Other"
# Run differential abundance test
sce <- diffAbundanceFET(sce, cluster = "cluster",
variable = "cell_type",
case = "NK_cell", control = "T_cell",
analysisName = "NK_VS_T")
Users can get the table of result with the method below, using the analysisName
specified when running the analysis.
getDiffAbundanceResults(sce, analysisName = "NK_VS_T")
| Cluster | Number of cells in cluster and in T_cell | Number of cells NOT in cluster and in T_cell | Number of cells in cluster and in NK_cell | Number of cells NOT in cluster and in NK_cell | Fraction of cells in cluster and in T_cell | Fraction of cells NOT in cluster and in T_cell | Fraction of cells in cluster and in NK_cell | Fraction of cells NOT in cluster and in NK_cell | Odds_Ratio | Pvalue | FDR |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 555 | 881 | 0 | 151 | 0.386490 | 0.614 | 0.00000 | 1.000 | Inf | 1.32e-30 | 5.95e-30 |
| 2 | 529 | 907 | 1 | 150 | 0.368384 | 0.632 | 0.00662 | 0.993 | 87.39191 | 7.76e-27 | 2.33e-26 |
| 3 | 1 | 1435 | 0 | 151 | 0.000696 | 0.999 | 0.00000 | 1.000 | Inf | 1.00e+00 | 1.00e+00 |
| 4 | 4 | 1432 | 0 | 151 | 0.002786 | 0.997 | 0.00000 | 1.000 | Inf | 1.00e+00 | 1.00e+00 |
| 5 | 324 | 1112 | 19 | 132 | 0.225627 | 0.774 | 0.12583 | 0.874 | 2.02348 | 3.55e-03 | 7.99e-03 |
| 6 | 0 | 1436 | 0 | 151 | 0.000000 | 1.000 | 0.00000 | 1.000 | 0.00000 | 1.00e+00 | 1.00e+00 |
| 7 | 23 | 1413 | 131 | 20 | 0.016017 | 0.984 | 0.86755 | 0.132 | 0.00254 | 4.81e-144 | 4.33e-143 |
| 8 | 0 | 1436 | 0 | 151 | 0.000000 | 1.000 | 0.00000 | 1.000 | 0.00000 | 1.00e+00 | 1.00e+00 |
| 9 | 0 | 1436 | 0 | 151 | 0.000000 | 1.000 | 0.00000 | 1.000 | 0.00000 | 1.00e+00 | 1.00e+00 |
Alternatively, users can choose to directly make a plot using the two variables and the function plotClusterAbundance()
will automatically calculate the statistic and visualize the result. The proportion or count of each category in each cluster will be displayed in stacked bar plots:
plotClusterAbundance(sce, cluster = "cluster", variable = "cell_type")
For the purpose of gene set enrichment (GSE) analysis, SCTK imports VAM and GSVA as options. Both of them work by loading some user-defined gene sets (more about loading gene sets), and calculating the enrichment score of each gene set in each cell. Here we will go through calling VAM to inspect the enrichment of the hallmark gene sets available in MSigDB database. Please refer to the document for the detail of running pathway analysis with VAM or GSVA.
SCTK also supports GSEA method from EnrichR, which queries a given gene list and finds the significant overlap against the curated gene sets from multiple gene set libraries. For detail, please refer to EnrichR Documentation.
After finished, a violin plot will be shown in the right main panel. By default, SCTK shows scores in all cells for the first gene set in the selected collection, in a single violin plot. With options in the dropdown menu, users can choose to shown the scores of a different gene set at seletion “Select Geneset”, or group the scores by the cluster labels by choosing the cluster variable at the selection “Select condition of interest to group data”. After tweaking the options, click on button “Update Plot” to apply the changes.
sce <- importGeneSetsFromMSigDB(sce, categoryIDs = "H", species = "Homo sapiens")
sce <- runVAM(sce, geneSetCollectionName = "H", useAssay = "logcounts")
To visualize the result, we simply adopt a violin plot to show the distribution of the CDF scores of the cells, which can be, optionally, grouped by the cluster labels.
hallmark <- "HALLMARK_INFLAMMATORY_RESPONSE"
plotPathway(sce, resultName = "VAM_H_CDF", geneset = hallmark, groupBy = "cluster")
Note that available options for argument resultName
and geneset
can be printed with getter functions below.
getPathwayResultNames(sce)
getGenesetNamesFromCollection(sce, geneSetCollectionName = "H")
Note: In the current version of SCTK, the returned score matrices from either VAM or GSVA are stored in the
reducedDims
slot, since the feature dimensions are for the gene sets instead of the genes or subsets of genes. In the future, SCTK will adopt other types of data container for simpler operation on different types of feature sets.
SCTK allows users to select the score matrix from pathway analysis to perform differential expression analysis. In this process, each geneset will be treated as the feature, and comparison groups can still be set in the same way as introduced in DE analysis section.
Please refer to the DE analysis section for how to reach the tab for performing DE analysis.
The same result presentation methods will be shown at the bottom of this tab. Users might need to check the console log message at this point if the heatmap is not shown. The default log2 fold-change cutoff works for the log-normalized gene expression value, and is usually too high for the pathway analysis score to keep any gene sets. Therefore, we recommend users to open the dropdown menu and set the log2 fold-change cutoff to a value around 0.03
to update the heatmap.
To run DE analysis with matrix in the reducedDims
slot, users only need to simply specify the matrix name to argument useReducedDim
(useAssay
will be ignored in this case).
sce <- runDEAnalysis(inSCE = sce, method = "wilcox", useReducedDim = "VAM_H_CDF",
class = "cluster", classGroup1 = c(1, 2, 5), classGroup2 = c(3, 6),
groupName1 = "T_cells", groupName2 = "monocytes",
analysisName = "T_cells_VS_monocytes_VAM_H_CDF", overwrite=T)
As the nature of the pathway analysis score is different from a log-normalized gene expression value, the default cutoff for log2 fold-change is likely to rule out all gene sets in this case. Therefore, we need to manually set a rather small value for this cutoff.
plotDEGHeatmap(sce, useResult = "T_cells_VS_monocytes_VAM_H_CDF", rowTitle = "Geneset", log2fcThreshold = 0.05)


ABOUT
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It is a website created for a private Island Resort that includes ;
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Level 100 character build that utilizes thrown ranged attacks. Race: Dryad Levels: * Combat: 0 * Melee: 0 * Nature: 0 * Ranged: 100 * 20 Critical Shot * 20 Quick Draw * 20 Bleed * 1 Penetrate * 19 Cunning Renewal * 20 Ricochet


While the consequences of overturning Roe remains uncertain, what is not uncertain are people’s beliefs about abortion. A person typically identifies as "pro-choice" or "pro-life". In the following sections, we explore the logic of three topics at the center of people’s beliefs. These topics are bodily autonomy, inequity in abortion access, and when "life" starts.
in-context


SVG Graphic Fundamentals
Visualization tools like D3.js or C3.js use the SVG (Scalable Vector Graphics) format by default, so it's important to understand how that format uses XML style commands to generate graphics. Let's dive straight into some code.
SVG is pretty easy to read and if you know HTML it should be even easier. An SVG graphic begins and ends with the <svg></svg>
tags like many other HTML elements and you can add different attributes like the width and height of the graphic. As a matter of fact, the very first thing you do with SVG is specify the canvas that the rest of the graphics will be using.
Just like with any other HTML tag we can add a style attribute and pass it common CSS commands, here we've set the color of the background to a bluish medium gray.
Inside the SVG tag, you can create additional elements that generate graphics. Here's a comprehensive reference to all of the SVG elements that you can create. Common elements (with examples) include:
|<path d="M 100 100 L 300 100 L 200 300 z" fill="orange" stroke="black" stroke-width="3" />
| Paths |
If you come from an HTML background, there are some important things to note about this code. First, you'll notice that the tags use a self closing style when they are single tags. So instead of writing something like <rect></rect>
you can write something like <rect> />
. SGV looks like HTML, but it isn't exactly HTML, so an XHTML style is used for the tags. Although most browsers will be forgiving on some traditional XML rules like capitalization, punctuation and quotes around attributes, the format itself is more strict.
For example, technically, the <svg>
tag should include an SVG namespace declaration specifying the version and format of the library you're using.
<svg xmlns="http://www.w3.org/2000/svg" …>
<rect …/>
</svg>
Here's where you can learn more about the SVG specification and format.
You might also notice that like with HTML we can use the style attribute and use CSS.


Sync Google Calendar With Org Agenda
Category: sysadmin
Category: emacs
I use org-mode an awful lot - it helps me manage my tasks and code all in one place. However, the organisation that I work for have just migrated over to Google Suite and manage meetings extensively using Google Calendar. I really wanted my Google Calendar to sync with my org-agenda. Org-agenda is a tool that pulls in any scheduled activities from all your files in to one dynamic view. It’s pretty much what drives my working day. Having meetings arranged with colleagues in my org-agenda will help me schedule my day.
The package org-gcal provides two way syncing with Google Calendar (and has other documentation).
This is how I did it.
Install org-cal
Using elpa, I installed the package:
M-x package-list
Highlight the org-gcal
package and install.
Create Api Credentials
Then, go to google and get credentials to access your calendar. You will need to go to the google developers portal where you may need to enable the developers’ api. You will need to find Api & Services and then click on credentials. You will create some OAuth 2.0 client IDs credentials - one being the API key and the other being a secret. Make a note of these, or download the JSON file that Google provides.
Enable these credentials for Google Calendar.
Identify Calendar
Then, the README for org-cal tells you to find the link for your calendar. This didn’t work for me. Instead, I found the link in the url in the address bar of my browser (click on the image to see more detail):
Create settings
(require ‘org-gcal) (setq org-gcal-client-id “your-id-foo.apps.googleusercontent.com” org-gcal-client-secret “your-secret” org-gcal-file-alist<EMAIL_ADDRESS>. “~/schedule.org”<EMAIL_ADDRESS>. “~/task.org”)))
Copy that string in to your ~.emacs
file, substituting the proper parts (your org-gcal-client-id and secret and the files that you wish to create when you sync).
Save the file and then execute M-x load-file <RET>.emacs
to reload this file.
Sync and org-agenda-file-to-front
Now you need to sync your calendar, which will create a new org file (as you specified in the settings.
M-x org-gcal-sync
Once that file is created open it C-x C-f
</path/to/file>
You can also create a hook to run org-gcal-sync
when you open your agenda by placing this snippet in your .emacs
file:
(add-hook 'org-agenda-mode-hook (lambda () (org-gcal-sync) ))


[gecode-users] Error message with fzn-gecode
Jean-Noël Monette
jean-noel.monette at it.uu.se
Wed Mar 25 15:25:43 CET 2015
Hi,
The following small FlatZinc model:
var bool: x;
array[1..1] of var int: y = [x];
solve satisfy;
produces:
Error: undefined identifier x in line no. 2
with fzn-gecode of Gecode 4.3.3. However, "x" is defined, but not of the
right type (bool vs int). Really not so important, but I though you
would like to know, in case you want to correct the error message in
that case.
(By the way, I just discovered that Gecode 4.4.0 had been released a few
days ago. Did I miss the announcement?)
Best,
Jean-Noël
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Kassandra:
That's all I can see. Ask Uncle Ogmar, he used to travel a lot, maybe he would know where it is. Please help the princess!


Product Recommendations at Gilt
Product recommendations at Gilt work a little differently than they do at other companies. For example, at Amazon they enjoy the benefit of having a relatively static and large inventory so they can do things like collaborative filter – where you can recommend a product based on what other people have bought or looked at. Gilt is unique because our inventory is in constant flux. The products we have one week are gone the next and there is a chance we won’t have them again.
At Gilt, we’ve employed a technique called contextual retrieval. Contextual retrieval is a search method where we take elements from the user context to help them conduct a search. When someone sees a product that is sold out and they decide to waitlist it, we can infer a lot of things about the user. One is that they really want that product. Another is that we know everything about the product they are interested in. In fact, we use that product as a search query to find related ones that we have in our inventory whether they are currently on sale or not.
So the steps involved in setting up a contextual retrieval based recommendation service are as follows:
· First, you are going to have to create a search index of your products.
Apache Lucene is a great piece of open source technology for doing just that. You are going to want to create an index that contains all the fields that you have describing your products. Those fields are basically the metadata that you need to find similar ones.
· The second step is search query manufacturing.
This is where the recommendation magic really happens. When you construct your search from a product, not all fields are going to be equally important. In fact, it is very likely that different genres of products will have different fields that are going to be more valuable than others. To that end, you need to devise a weighting scheme where you boost the value of some fields over others.
· The third step is caching those recommendations.
You can quite easily get away with caching all your recommendations because unlike a search engine, you already know all the search queries that you are going to encounter – they are the products you have for sale. At Gilt, since we have new products every day, we generate and cache our recommendations once a day.
· The fourth (and most rewarding) step is using those recommendations in ways to help your users.
One of our customer pain points is that the product at Gilt sells out quickly. When a user has decided that they want an item so much that they are willing to sign up for it on a waitlist, we want to do everything in our power to try to find them another product that they will be happy with.
That’s pretty much what we aim to achieve at Gilt – Simple, Fast and Fun!


Blueberry & Basil Muffins
metadata
Created on 2018-11-26
Inspired by Blueberry Basil Muffins by Liz @ OhMyVeggies.com (2018-12-18)
Recipe should yield this much: 12 muffins.
Estimated time needed: At least 64 minutes. At most 73 minutes.
Ingredients
| 350 | g | blueberries | ||
| 230 | g | flour | ||
| 150 | g | sugar | ||
| 115 | g | milk | ||
| 112 | g | butter | ||
| 2 | tsp | baking powder | ||
| 2 | eggs | |||
| 1 | tsp | salt | ||
| 1 | tbsp | lemon zest | ||
| 1 | plant | basil |
Scaling
Timeline
Directions
⌛ Active time 10 minutes
- 112 g butter
Melt butter
⌛ Active time 1 minutes | Passive time 5 minutes
- 115 g milk
Add milk to to the butter and let cool
⌛ Active time 3 minutes
- 1 plant basil
- 350 g blueberries
Wash basil and berries
⌛ Active time 1 minutes
Pour mixture over into kitchen machine bowl
⌛ Active time 1 minutes
- 2 eggs
Add egg:
Make sure you've let the butter and milk cool down a bit so that you don't end up with chunks of boiled eggs in the dough.
⌛ Active time 4 minutes
- 1 tbsp lemon zest
Add basil, berries, and lemon zest
⌛ Active time 5 minutes
- 230 g flour
- 150 g sugar
- 2 tsp baking powder
- 1 tsp salt
In a separate bow, mix the dry ingredients
⌛ Active time 1 minutes
Pre-heat oven:
175 ℃, convection.
⌛ Active time 5 minutes
Add dry to wet in kitchen machin while it's working:
You want to run the kitchen machine on low, and add the dry stuff gradually (don't just dump it all in there at once).
⌛ Active time 10 minutes
Pour into forms:
With the amounts specified here you should get a decent size on the muffins if you divide the dough on approximately 12 muffin forms.
⌛ Active time 2 minutes | Passive time 25 minutes
Bake for 25 minutes:
Put the muffins into the oven that you have pre-heated to 175 ℃ and set to convection. They should be done after about 25 minutes.


This plugin let you use Velocity.js to make Ractive.js transitions, with full support for all of Velocity.js' properties and options (except complete, which is used by the plugin itself)
And if you add the Velocity.js UI Pack aling with Velocity.js (optional, but recommended), all the packaged effects will be readily available as transitions too.


AMAZING PEOPLE ARE MAKING DESIGNS IN A FUN ENVIRONMENT
Our approach unifies design, development and product management to create exceptional products.
We start each project by understanding your business goals, the users needs and the product requirements
Then we help trnaslate them into effective and elegant solutions.The more we engage you our client the more you gain.


{% extends "pretixcontrol/event/base.html" %} {% load i18n %} {% load bootstrap3 %} {% block content %}
{% trans "Your shop is currently live. If you take it down, it will only be visible to you and your team." %}
{% else %} {% if issues|length > 0 %}{% trans "Your ticket shop is currently not live. It is thus only visible to you and your team, not to any visitors." %}
{% trans "To publish your ticket shop, you first need to resolve the following issues:" %}
{% trans "Your ticket shop is currently not live. It is thus only visible to you and your team, not to any visitors."  %}
{% endif %} {% endif %}{% trans "Your shop is currently in production mode." %}
{% trans "If you want to do some test orders, you can enable test mode for your shop. As long as the shop is in test mode, all orders that are created are marked as test orders and can be deleted again." %} {% trans "Please note that test orders still count into your quotas, actually use vouchers and might perform actual payments. The only difference is that you can delete test orders. Use at your own risk!" %}
{% trans "Also, test mode only covers the main web shop. Orders created through other sales channels such as the box office or resellers module are still created as production orders." %}
{% if actual_orders %}


| Package | Description |
|---|---|
| org.apache.taverna.reference.impl |
Implementation of the reference manager APIs backed by Hibernate.
|
| Class and Description |
|---|
| AbstractEntityImpl
Abstract superclass of ReferenceSetImpl, IdentifiedArrayList and
ErrorDocumentImpl, manages the T2Reference field for these types and their
hibernate backing.
|
| AbstractErrorDocumentServiceImpl
Abstract implementation of ErrorDocumentService, inject with an appropriate
ErrorDocumentDao and T2ReferenceGenerator to enable.
|
| AbstractListServiceImpl
Abstract implementation of ListService, inject with an appropriate ListDao
and T2ReferenceGenerator to enable.
|
| AbstractReferenceServiceImpl
Implementation of ReferenceService, inject with ReferenceSetService,
ErrorDocumentService and ListService to enable.
|
| AbstractReferenceSetServiceImpl
Abstract implementation of ReferenceSetService, inject with an appropriate
ReferenceSetDao to enable.
|
| AbstractServiceImpl
Abstract superclass for all service implementation objects, will be used to
allow injection of thread pooling logic as and when we implement it.
|
| AbstractT2ReferenceGenerator
An abstract class for implementing simple
T2ReferenceGenerator s. |
| IdentifiedArrayList
Implementation of IdentifiedList which delegates to an ArrayList for its
storage functionality.
|
| T2ReferenceImpl
An implementation of T2Reference specific to the ReferenceSetImpl.
|
| TranslationPath
A path from one external reference to another along with a total estimated
path cost through one or more reference translators.
|
Copyright © 2015–2016 The Apache Software Foundation. All rights reserved.


"Education is a human right with immense power to transform. On its foundation rest the cornerstones of freedom, democracy and sustainable human development."
- Vietlabo Company -
Our clients
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique.


National Park Trivia
Start
All done, here's how you did!
Correct Answers:
Incorrect Answers:
Unanswered:


Funeral prayer for MP Moinuddin Khan Badal held at parliament building
by bdnews24.comA funeral prayer for Moinuddin Khan Badal, a member of parliament and leftist leader from Chattogram, has been held at the South Plaza of the parliament building.
The freedom fighter was accorded the state honour after the funeral on Saturday morning.
Prime Minister Sheikh Hasina and other leaders of the Awami League paid tribute to Badal by placing wreaths on his coffin.
President Abdul Hamid’s Military Secretary SM Shamim Uz Zaman paid homage on behalf of the head of state.
Badal died during treatment in a hospital in India on Nov 7 at age of 67.
He was suffering from ill health after a stroke last year and was last admitted to Narayana Institute of Cardiac Sciences in India’s Bengaluru.
A three-time MP from the Chattogram-8 (Chandgaon-Boalkhali) seat, Badal was a member of the standing committee on liberation war affairs in the 11 national parliament.
His body will be taken to Chattogram after the funeral prayers, said JSD Presidium Member Mushtaq Hossain. A namaz-e-janaza will held in Chattogram’s Darul Falah Jame Mosque after the Asr prayers following which he will be laid to rest beside his parents’ graves in Boalkhali.


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Thank you so much for agreeing to be awesome today! Now get out there and do awesome things awesomely to make the world more awesome!


GO (M). (Columbia Tristar) Director: Doug Liman Stars: Sarah Polley, Katie Holmes, Timothy Olyphant, Desmond Askew, Taye Diggs, Breckin Meyer, James Duval, Scott Wolf, Jay Mohr, William Fichtner, J E Freeman, Nathan Bexton, Jay Paulson, Jimmy Shubert, Jane Krakowski Running time: 102 minutes.
Doug Liman's follow up to Swingers is a much more entertaining and accomplished film, and one of the cinematic surprises of this year so far. The film also features a hot and hip ensemble young cast, drawn primarily from the world of television soaps (Katie Holmes from Dawson's Creek and Scott Wolf from Party Of Five), and a number of rising actors on the cusp of stardom.
Go deals with a drug bust gone wrong, and the narrative thread follows the various characters through an incredibly hectic 24 hour period.
Ronna (Sarah Polley, from The Sweet Hereafter, etc), a check out clerkk in a Los Angeles supermarket, is about to be evicted from her apartment because she is behind in her rent. She agrees to take a double shift, thus allowing her colleague Simon (beautifully played by British actor Desmond Askew) to go to Vegas with three friends. Ronna is approached by Adam (Scott Wolf) and Zack (Jay Mohr, from Jerry Maguire, etc), the stars of a popular tv soap opera, who are looking for some drugs to liven up a party later that evening. Ronna reluctantly agrees, hoping to score some extra money on the side.
She buys the drugs from Simon's contact Todd (Timothy Olyphant, from Scream 2, etc), "the nice drug dealer". But when she approaches the two actors, she finds out the whole thing is a set-up.
Go explores the aftermath of this drug deal. The film then switches to follows Simon's misadventures in Vegas. While two of his friends come down with food poisoning, Simon and Marcus (Taye Diggs, from How Stella Got Her Groove Back) visit a strip joint and run afoul of the management. They are pursued back to LA by the club's owner (J E Freeman), with murder on his mind.
Meanwhile, we learn more about the relationship between Zack and Adam, and how they came to be blackmailed into co-operating with a sleazy cop (William Fichtner, from Armageddon, etc) for the drug operation.
First time writer John August has obviously been inspired by Tarantino and, in particular, Pulp Fiction, and Go wears its influences openly and proudly. In his sophomore film Liman handles the various narrative strands with assurance, and brings the whole thing full circle to a satisfying finish.
Liman directs the complex structure with energy and style, and shows that he is quite adept at staging some inventive action sequences. The use of hand held cameras, especially during the exciting car chase through the streets of Las Vegas, adds to the movie's breakneck pace. The film is also suffused with generous dollops of wry black humour, and a marvellous soundtrack that seems to propel the action along.
Go is an exhilarating, entertaining and stylish film! Don't miss it!
**** greg king http://www.netau.com.au/gregking
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


If you need support, experience any trouble with Recent Menu or would like to see additional features implemented, please consult the Support Page on the Recent Menu website. You may also drop a line to the developer at support@timschroeder.net.


---
layout: archive
title: Lean Prover Zulip Chat Archive
permalink: 116395maths/14012modulogroupaction.html
---
The archive URL format has changed. Please find this page at:
https://leanprover-community.github.io/archive/stream/116395-maths/topic/modulo.20group.20action.html


So who are the brilliant people behind Una?
Soedarsono
The Platform Ninja
A curious geek, Soedar loves experimenting (and be frustrated) with new technologies, and absolutely adores beautful and elegant code. He has spent a year in San Francisco building engaging math games on the iOS platform. When not tinkering, you can see him obsessing over Hayley Williams and her bright orange hair.
Le Viet Tien
The Hacker Ninja
A fun loving geek, Viet Tien is passionate about making applications and Software Engineering in general. He has some hands-on experience developing on the iOS platform and web, mostly worked as a ninja monkey coder.  He really hates slow walking. Oh, his Dota skills are not bad either.
Tay Yang Shun
The UI/UX Ninja
A driven and creative person, Yang Shun's two main passions lie in coding and designing. He has developed a few apps for the iOS platform and has extensive experience in graphic designing having performed freelance design tasks and winning design competitions. He spent a year in Silicon Valley as a Software Engineering intern at a bay area startup, exploring front-end web development technologies and is currently building beautiful kickass sites, such as this site.


'Messi & Ronaldo Are Monsters'
by Kurt BuckerfieldLiverpool superstar Sadio Mane is among the best players in the world at the moment, but has played down talk of being on the same level as "monsters" Lionel Messi and Cristiano Ronaldo, whom he is up against for the 2019 Ballon d'Or.
9 Players Who Left Barca Because Of Messi
The Senegalese winger was sublime for the Reds last season, but has seemingly taken his game to new heights in the 2019/20 campaign so far.
Mane's brilliance over the past year as earned him a place among the nominees for the Ballon d'Or, which he will challenge teammates Mohamed Salah and Virgil van Dijk for, as well as the two five-time winners.
Asked if he sees himself on a similar level to the FC Barcelona and Juventus forwards, the Senegal superstar insisted he is still working hard to match up to them.
"These players are monsters," he said, according to the Daily Star.
"I think that I am still far away from them.
"As I have said, I am going to do everything I can to come a little closer to them."
Earn Airtime & Data With Soccer Laduma's Social Media App - Download Now
Mane also admitted that winning the prestigious individual prize is something he has always dreamed of.
"Honestly, as I've said, it has always been a childhood dream of mine," he added.
"The fact that I am listed as one of the nominees is due to the fruits of the work that I've been putting in for a long time.
"This is more of a dream than an obsession, I am at the service of the collective first and foremost.
"And if I am able to distinguish myself amongst this collective then, of course, the Ballon d'Or has always been my dream. And when a dream comes true, it is always exceptional.
"All of the Senegalese people, my friends, my family, would be so happy, I would be so happy."
Cristiano Jr. Following In CR7's Footsteps
Mane has played 15 matches for Liverpool so far this season, scoring 10 goals and assisting a further five strikes.


My SPARQL endpoint is: {{mysparqlendpoint}}
{{result}}
Query Results: {{resultQ2}}
Query Results: {{resultQ1}}


is/2
[ISO]-Term is
+Expression
Evaluates Expression as an arithmetic expression, and unifies the resulting number with Term.
An expression made up of:
Evaluation errors.
| ?- X is 2 * 3 + 4. X = 10 | ?- Y = 32.1, X is Y * Y. X = 1030.41 Y = 32.1 | ?- Arity is 3 * 8, X is 4 + Arity + (3 * Arity * Arity). Arity = 24 X = 1756
| ?- X is 6/0. ! Domain error in argument 2 of is/2 ! expected an integer not equal to 0, but found 0 ! goal: _98 is 6/0
| ?- X is "a". X = 97 | ?- X is 4 * 5, Y is X * 4. X = 20, Y = 80
If a variable in an arithmetic expression is
bound to another arithmetic expression (as opposed to a number) at
runtime then the cost of evaluating that expression is much greater.
It is approximately equal to the cost of call/1
of an arithmetic
goal.


| Name | Captains | Destinations | Stops | Last Shipped | Last Salvaged | Total Shipments | Total Salvage Runs |
|---|---|---|---|---|---|---|---|
| {{#if can_ply}} {{/if}} {{name}} | {{total_captains}} | {{destinations.length}} | {{total_stops}} | {{last_shipped}} | {{last_salvage_run}} | {{total_shipments}} | {{salvage_plans}} |


T
2
WS Debug Server
File Access
Show
Download
Tcl Console
Enter above your Tcl code, validate with 'enter'"


|
sfImagePoolPlugin
|
Static Public Member Functions | |
| static | deleteImageFile ($filename) |
| static | addImageChooser ($form, $useSsl=false) |
| static | addImagePoolMooEditable ($form, $fieldName, $tag= '') |
| static | addImageField ($form, $field_name= 'image') |
| static | getValidatorOptions () |
| static | getValidatorMessages () |
| static | processImageField ($form, $field_name= 'image') |
| static | createImageFromUpload ($upload, $tags=null) |
| static | getUploadErrors ($uploaded_file) |
| static addImageChooser | ( | $ | form, |
| $ | useSsl = false |
||
| ) | [static] |
Add an image pool chooser widget to the form
Requires MooTools.More: * More/Fx.Reveal
| $form | Form object which to add widget to |
| $useSsl | backend app uses SSL so return the MooTools JS with ssl |
| static addImageField | ( | $ | form, |
| $ | field_name = 'image' |
||
| ) | [static] |
Add a validated image upload field to a form.
| sfForm | $form | Form to modify |
| string | $field_name | Name of the image upload field, default 'image' |
| static addImagePoolMooEditable | ( | $ | form, |
| $ | fieldName, | ||
| $ | tag = '' |
||
| ) | [static] |
Add a MooEditable textarea widget with images from Image Pool as the selection
e.g: sfImagePoolUtil::addImagePoolMooEditable($this, 'summary', 'editorial');
Requires Javascripts and Stylesheets to be included in form
public function getJavaScripts() { $js = parent::getJavascripts();
return array_merge($js, array('/sfImagePoolPlugin/js/MooEditable.ImagePool.js')); }
public function getStylesheets() { $css = parent::getStylesheets();
return array_merge($css, array('/sfImagePoolPlugin/css/MooEditable.ImagePool.css'=>'all')); }
Use this as a basis for any textarea which requires MooEditable + ImagePool as config options are REQUIRED
sfMooToolsFormExtraPlugin (REQUIRED)
| sfForm | $form | Form object which to add widget to |
| string | $fieldName | the field to set the textarea to |
| string | $tag | (optional) tag to restrict images for insertion - comma separated |
| static createImageFromUpload | ( | $ | upload, |
| $ | tags = null |
||
| ) | [static] |
Take array of data for a single upload and create an image, assigning content of $tags as tag (CSV string or single tag or array).
This common logic is abstracted out so it can easily be used by other plugins that require image upload but need to handle the actual upload logic themselves.
| array | $upload | |
| mixed | $tags |
| static deleteImageFile | ( | $ | filename | ) | [static] |
Deletes an image, and all cached crops and scales.
| static getUploadErrors | ( | $ | uploaded_file | ) | [static] |
Helper method for checking for upload errors when doing a basic non-Symfony Forms upload which can sometimes be needed by other plugins (Symfony and/or Javascript).
| array | $uploaded_file |
| static getValidatorMessages | ( | ) | [static] |
| static getValidatorOptions | ( | ) | [static] |
| static processImageField | ( | $ | form, |
| $ | field_name = 'image' |
||
| ) | [static] |
Perform the creation of an sfImagePool image and associate it with the object being created by the given form.
This method should be called after the call to isValid() returns true.


The West Wing
The series is set primarily in the West Wing of the White House, where the Oval Office and offices of presidential senior staff are located, during the fictitious Democratic administration of Josiah Bartlet.


A Cockapoo can be the result of mating either the American Cocker Spaniel or English Cocker Spaniel with a Poodle. They have been known in the United States since the 1950s.
The cockapoo gets its cockamamy name from its history of being crossbred from cocker spaniels and poodles. For more detailed information about the breed itself, history and health expectations, head over to this article all about the cockapoo breed.
Generally, Cockapoos are highly affectionate, outgoing, and become playful at the drop of a hat. But they have one trait that stands out above the rest. In June, we conducted a poll of our members, asking them to choose one word that best describes their Cockapoo’s personality.


Oops...
We failed to connect to the mothership. Trying to reconnect in 10...
try harder
Oops...
We got disconnected from the server. Trying to reconnect in 10...
reconnect now
Waiting for content
We're connected to the mothership, now waiting for
content. Good time to get yourself a
.
Connecting...
Please wait while I reconnect you to the mothership...


AlienCollective
Eventos
(current)
Produções
(current)
Contato
(current)
Djs
(current)
CarnacVandom
Cyberskull
Andrew Cardoso
Liv


Super_Search:Forget_Last_Search template tag
By default, the Super_Search:Form tag remembers the last search a user conducted so that when they return to a search form on the site, the search variables they submitted can be recalled and the search form repopulated. If you wish to provide an option for the user to clear the history of their last search, you can provide a link that points to a template with the Super_Search:Forget_Last_Search function in it. This will cause the search form on the site to be cleared or reset.
{exp:super_search:forget_last_search} content {/exp:super_search:forget_last_search}
Variables
The following variable is available for use:
message
{message}
This variable returns a message indicating the success or failure of the action.
Conditionals
The following conditionals are available for use:
if failure
{if failure}{/if}
This conditional will show its contents if the action fails for any reason.
if success
{if success}{/if}
This conditional will show its contents if the action succeeds.
Examples
The following code should be a complete example for using this function:
{exp:super_search:forget_last_search} {if success}
Successful!
 {/if} {if failure}
Error!
 {/if}
{message}
 {/exp:super_search:forget_last_search}
Setup
To implement this feature from your search form, your code would look something like this:
{exp:super_search:form return="supersearch/results" }
Search for Products:

  Forget Last Search?

 Keywords: <input type="text" name="keywords" id="keywords" value="{super_search_keywords}" />

 Price from: <input type="text" name="price-from" id="price-from" value="{super_search_price-from}" /> to: <input type="text" name="price-to" id="price-to" value="{super_search_price-to}" />

 <input type="submit" name="submit" value="Search!" />
 {/exp:super_search:form}


Free
Pictures to Selected Gravesites
Looking for an ancestor s
grave? This might help. Dave Distler has been doing historical and
genealogical research on his family lines in Monroe County, Ohio. He recently announced his project to make
photos of gravesites available to other researchers. These data are available free as described by Dave below. Dave also has a pay-for-service website at: http://orvf.com.
Dave
Distler writes:
I
have been photographing hundreds of headstones and updating my orvf.com
database with selected interments in Summit Township cemeteries over the past
couple of years.
My
main listing webpage is on a free server called findagrave.com and can be found
here:
http://www.findagrave.com/cgi-bin/fg.cgi?page=mr&MRid=46528272
Surnames
can be searched from the above link.
Of
specific interest to those researching Monroe County would be:
Middle
(St John's) Church Cemetery in Summit Township:
http://www.findagrave.com/cgi-bin/fg.cgi?page=gsr&GScid=43122
Evangelical
Reformed Church Cemetery in Lewisville:
http://www.findagrave.com/cgi-bin/fg.cgi?page=gsr&GScid=1182423
Friendship
Cemetery in Lewisville:
http://www.findagrave.com/cgi-bin/fg.cgi?page=gsr&GScid=40970
Miltonsburg
(St Peters) Church Cemetery in Malaga Township:
http://www.findagrave.com/cgi-bin/fg.cgi?page=gsr&GScid=42160
Buchanan
Presbyterian Church Cemetery in Summit Township:
http://www.findagrave.com/cgi-bin/fg.cgi?page=gsr&GScid=1183424
Bracken
Ridge Church Cemetery in Summit Township:
http://www.findagrave.com/cgi-bin/fg.cgi?page=gsr&GScid=1160518
Oaklawn
Cemetery in Woodsfield:
http://www.findagrave.com/cgi-bin/fg.cgi?page=gsr&GScid=42492
Pioneer
Cemetery in Woodsfield, Ohio:
http://www.findagrave.com/cgi-bin/fg.cgi?page=cr&GRid=12656226&CRid=42686
Feel
free to link to it from your web pages. You may use this text to create a
new html page if you wish.
Visitors
to individuals in findagrave can add additional photos of the headstone or the
individual or simply leave digital flowers as a reminder of their visit.
There
may also be individuals in these cemeteries that I have not listed. The
only ones I have listed are those already in my database. New listings
can be added by anyone registering at findagrave for free and adding their
listings. Be sure the individual is not already shown.
I
hope sharing this information will be of help to you and others. My
main database contains only allied families and lineage-linked
individuals, either of myself or my wife.
My
direct Monroe County lines include the surnames: DISTLER, MORRIS, JUNG (YOUNG),
LEISURE, VAN FOSSEN and SWAIN.
While
not 100% documented, my direct line is to William MORRIS b. 1782 Greene Co., PA
d. 1843 in Monroe Co., OH.
Dave
Distler
Ohio
River Valley Families
Provided by Dave Distler


Graph Surgeon API
UFF API
Workflows
Package Reference
Index
The UFF package contains a set of utilites to convert trained models from various frameworks to a common format.
UFF
uff.
from_tensorflow
Helper function for calling the conversion from TensorFlow
from_tensorflow_frozen_model


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A Search Engine is a program that searches documents for specified keywords and returns a list of the documents where the keywords are found.
Although search engine is really a general class of programs, the term is often used to specifically describe systems like Google,Alta Vista and Excite that enable users to search for documents on the World Wide Web and USENET newsgroups.
Techniques for using a Search Engine
The best way to learn how to use a search engine is to read the help information and practise. If you want to search for words that must be together you can put them within quotation marks. Thus if your first search doesn't find what you want, it is a good idea to try different combinations.
There are two easy ways to narrow the search.
a. Use a plus (+) sign to indicate you want only Web pages that contain a specific word.
b. Use a minus (-) sign to indicate you want only Web pages that do not contain a specific word.


Mars is the fourth planet from the Sun and the second-smallest planet in the Solar System after Mercury.
In English, Mars carries a name of the Roman god of war, and is often referred to as the Red Planet because the iron oxide prevalent on its surface gives it a reddish appearance that is distinctive among the astronomical bodies visible to the naked eye.
Mars's average distance from the Sun is roughly 230 million km (143 million mi), and its orbital period is 687 (Earth) days. The solar day (or sol) on Mars is only slightly longer than an Earth day: 24 hours, 39 minutes, and 35.244 seconds. A Martian year is equal to 1.8809 Earth years, or 1 year, 320 days, and 18.2 hours.
The axial tilt of Mars is 25.19 degrees relative to its orbital plane, which is similar to the axial tilt of Earth. As a result, Mars has seasons like Earth, though on Mars they are nearly twice as long because its orbital period is that much longer. In the present day epoch, the orientation of the north pole of Mars is close to the star Deneb.
Mars has a relatively pronounced orbital eccentricity of about 0.09; of the seven other planets in the Solar System, only Mercury has a larger orbital eccentricity. It is known that in the past, Mars has had a much more circular orbit. At one point, 1.35 million Earth years ago, Mars had an eccentricity of roughly 0.002, much less than that of Earth today. Mars's cycle of eccentricity is 96,000 Earth years compared to Earth's cycle of 100,000 years. Mars has a much longer cycle of eccentricity, with a period of 2.2 million Earth years, and this overshadows the 96,000-year cycle in the eccentricity graphs. For the last 35,000 years, the orbit of Mars has been getting slightly more eccentric because of the gravitational effects of the other planets. The closest distance between Earth and Mars will continue to mildly decrease for the next 25,000 years.


 #Apollo11 @NASA https://t.co/6Nb2cQVU32
— Buzz Aldrin (@TheRealBuzz) July 21, 2018
I love overhearing dog owners talking to their dogs
— Julia Galef (@juliagalef) July 17, 2018
eg, I was petting this dog who seemed happy but then suddenly growled at me, so I left
As I turned the corner I could hear his owner saying to him reproachfully, "You always do this, Oscar, you drive away all your friends"
There’s 7 million people in this world and you think I’m gonna let one customer with a bad attitude to ruin my day??? damn right I am I’ll probably even go cry in the freezer too
— Jenna Cherry (@jennacherry_10) July 14, 2018
【盗撮注意】公衆トイレや試着室に、フック型隠しカメラが設置されていることがあるそう。一見、隠しカメラとは思えないものなので、フックがあれば全体を布か何かでフック全体を覆うようにした方が良いかも。これは是非とも皆に知って欲しい。 pic.twitter.com/jdL20x1Mhh
— she (@oshoyu_egg) July 24, 2018
Just needs a little help pic.twitter.com/mydc3vybZM
— Nature is Amazing 🌴 (@AMAZlNGNATURE) July 26, 2018
me opening the same app i just closed https://t.co/ttFbf1Qb5p
— josh (@yunginstitution) July 25, 2018
How to NOT kill yourself pt 1
— KANYE WEST (@kanyewest) July 27, 2018
Avoid being around people who make you want to kill yourself
eclipse #RM pic.twitter.com/uFDjljdxOM
— 방탄소년단 (@BTS_twt) July 27, 2018
Direct deposit ? I know https://t.co/CshhfX0rvI
— D (@yeeerderrick) July 26, 2018
eclipse #RM pic.twitter.com/uFDjljdxOM
— 방탄소년단 (@BTS_twt) July 27, 2018
SABON日本上陸10周年を記念してTwitter限定キャンペーンがスタート。
— 【公式】SABON(サボン) (@SABON_Japan) July 13, 2018
つるんとなめらか肌へと導く「フェイスポリッシャー」を抽選で20名様にプレゼントします。
 LMAO funny how that works out https://t.co/lEjfv4K4hv
— 𝘽🧡 (@_bbrirose) July 27, 2018
90+ Grades
— JhonAlbertJuario (@Jalbert444) July 21, 2018
90+ Grades
90+ Grades
90+ Grades
90+ Grades
90+ Grades
90+ Grades
90+ Grades
90+ Grades
90+ Grades
90+ Grades
90+ Grades
90+ Grades
For this SY 2018-2019
Rt now✨
#BTS #방탄소년단 #VLIVE channel hit 10 million followers! 천만 구독자 달성 기념 축하 메시지가 네이버 그린팩토리 외벽에 게시되었습니다! V❤BTS 천만! #BTS_VLIVE_10million pic.twitter.com/WECPlX58EC
— V LIVE (@Vliveofficial) July 27, 2018
do coke and pepsi taste the same??????
— shenk (@taylorshenk) July 22, 2018
rt for no
like for yes
it’s time to finally settle this
Sooo today my 6 year old cousin tried to kill me ...Follow thread to see the rest ..I promise ITS WORTH ALL YOUR TIME . pic.twitter.com/wNgoRmsoLl
— cass🦄 (@darealcass_) July 30, 2017
I don’t know how I thought jeans were being made, but this wasn’t it. https://t.co/IKKBdfCOFe
— Zoi🤸🏾♀ (@zoisthoughts) July 26, 2018
*logs into gmail on different device*
— pull the receipts type beat (@Groovy1u) July 26, 2018
Google 2 seconds later: https://t.co/RjANdDfNGW
eclipse #RM pic.twitter.com/uFDjljdxOM
— 방탄소년단 (@BTS_twt) July 27, 2018
No I’m just gay https://t.co/qoSPo3w0aS
— Kait (@kaitlinmaarie) July 25, 2018
猛暑の影響で救急出動が急増し、通常より救急隊を増やして対応していますが、1日の出動が22件となった隊もあります。
— 名古屋市消防局【公式】 (@NagoyaShobo) July 26, 2018
そのため出動が連続し消防署に戻れない時は、救急車でコンビニ等に立ち寄り飲料水等を購入する場合があります。
その際も、出動態勢は維持していますので、ご理解をお願いします。
It all makes sense now.  Lock him up https://t.co/x5O1CTxhme
— Jonte’ (@BOO_Dank) July 25, 2018
do coke and pepsi taste the same??????
— shenk (@taylorshenk) July 22, 2018
rt for no
like for yes
it’s time to finally settle this


|
Fling Engine
0.00.1
Fling Engine is a game engine written in Vulkan
|
Functions | |
| UINT32 | FindMemoryType (VkPhysicalDevice t_PhysicalDevice, UINT32 t_Filter, VkMemoryPropertyFlags t_Props) |
| Find a suitable memory type for use on the current device. More... | |
| void | CreateBuffer (VkDevice t_Device, VkPhysicalDevice t_PhysicalDevice, VkDeviceSize t_Size, VkBufferUsageFlags t_Usage, VkMemoryPropertyFlags t_Properties, VkBuffer &t_Buffer, VkDeviceMemory &t_BuffMemory) |
| VkCommandBuffer | BeginSingleTimeCommands () |
| void | EndSingleTimeCommands (VkCommandBuffer t_CommandBuffer) |
| void | CreateVkImage (UINT32 t_Width, UINT32 t_Height, VkFormat t_Format, VkImageTiling t_Tiling, VkImageUsageFlags t_Useage, VkMemoryPropertyFlags t_Props, VkImage &t_Image, VkDeviceMemory &t_Memory) |
| VkImageView | CreateVkImageView (VkImage t_Image, VkFormat t_Format, VkImageAspectFlags t_AspectFalgs) |
| Create a an image view for vulkan with the given format. More... | |
| VkFormat | FindSupportedFormat (const std::vector< VkFormat > &t_Candidates, VkImageTiling t_Tiling, VkFormatFeatureFlags t_Features) |
| void | TransitionImageLayout (VkImage t_Image, VkFormat t_Format, VkImageLayout t_oldLayout, VkImageLayout t_NewLayout) |
| bool | HasStencilComponent (VkFormat t_format) |
| Returns true if the given format has a stencil component. More... | |
| VkCommandBuffer Fling::GraphicsHelpers::BeginSingleTimeCommands | ( | ) |
| void Fling::GraphicsHelpers::CreateBuffer | ( | VkDevice | t_Device, |
| VkPhysicalDevice | t_PhysicalDevice, | ||
| VkDeviceSize | t_Size, | ||
| VkBufferUsageFlags | t_Usage, | ||
| VkMemoryPropertyFlags | t_Properties, | ||
| VkBuffer & | t_Buffer, | ||
| VkDeviceMemory & | t_BuffMemory | ||
| ) |
| void Fling::GraphicsHelpers::CreateVkImage | ( | UINT32 | t_Width, |
| UINT32 | t_Height, | ||
| VkFormat | t_Format, | ||
| VkImageTiling | t_Tiling, | ||
| VkImageUsageFlags | t_Useage, | ||
| VkMemoryPropertyFlags | t_Props, | ||
| VkImage & | t_Image, | ||
| VkDeviceMemory & | t_Memory | ||
| ) |
| VkImageView Fling::GraphicsHelpers::CreateVkImageView | ( | VkImage | t_Image, |
| VkFormat | t_Format, | ||
| VkImageAspectFlags | t_AspectFalgs | ||
| ) |
Create a an image view for vulkan with the given format.
| void Fling::GraphicsHelpers::EndSingleTimeCommands | ( | VkCommandBuffer | t_CommandBuffer | ) |
| UINT32 Fling::GraphicsHelpers::FindMemoryType | ( | VkPhysicalDevice | t_PhysicalDevice, |
| UINT32 | t_Filter, | ||
| VkMemoryPropertyFlags | t_Props | ||
| ) |
Find a suitable memory type for use on the current device.
| t_Filter | Type of memory types that are suitable for this application |
| t_Props | Memory properties |
| VkFormat Fling::GraphicsHelpers::FindSupportedFormat | ( | const std::vector< VkFormat > & | t_Candidates, |
| VkImageTiling | t_Tiling, | ||
| VkFormatFeatureFlags | t_Features | ||
| ) |
| bool Fling::GraphicsHelpers::HasStencilComponent | ( | VkFormat | t_format | ) |
Returns true if the given format has a stencil component.
| void Fling::GraphicsHelpers::TransitionImageLayout | ( | VkImage | t_Image, |
| VkFormat | t_Format, | ||
| VkImageLayout | t_oldLayout, | ||
| VkImageLayout | t_NewLayout | ||
| ) |


Data Analysis and Machine Learning: Logistic Regression
Contents
Plans for week 38
Thursday September 23
Ridge and LASSO Regression, reminder
Various steps in cross-validation
How to set up the cross-validation for Ridge and/or Lasso
Cross-validation in brief
Code Example for Cross-validation and \( k \)-fold Cross-validation
To think about, first part
More thinking
Still thinking
What does centering (subtracting the mean values) mean mathematically?
Further Manipulations
Wrapping it up
Linear Regression code, Intercept handling first
Code Examples
Taking out the mean
More complicated Example: The Ising model
Reformulating the problem to suit regression
Linear regression
Singular Value decomposition
The one-dimensional Ising model
Ridge regression
LASSO regression
Performance as function of the regularization parameter
Finding the optimal value of \( \lambda \)
Logistic Regression
Classification problems
Optimization and Deep learning
Basics
Linear classifier
Some selected properties
Simple example
Plotting the mean value for each group
The logistic function
Examples of likelihood functions used in logistic regression and nueral networks
Two parameters
Maximum likelihood
The cost function rewritten
Minimizing the cross entropy
A more compact expression
Extending to more predictors
Including more classes
More classes
Friday September 24
Wisconsin Cancer Data
Using the correlation matrix
Discussing the correlation data
Other measures in classification studies: Cancer Data again
Friday September 25
Optimization, the central part of any Machine Learning algortithm
Revisiting our Logistic Regression case
The equations to solve
Solving using Newton-Raphson's method
Brief reminder on Newton-Raphson's method
The equations
Simple geometric interpretation
Extending to more than one variable
Steepest descent
More on Steepest descent
The ideal
The sensitiveness of the gradient descent
Plans for week 38
Thursday: Summary of regression methods and discussion of project 1. Start Logistic Regression
Video of Lecture September 23
Friday: Logistic Regression and Optimization methods
Video of Lecture September 24
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Flag¶
-
class
chainer.
Flag
[source]¶ Ternary flag object for variables.
It takes three values: ON, OFF, and AUTO.
ON and OFF flag can be evaluated as a boolean value. These are converted to True and False, respectively. AUTO flag cannot be converted to boolean. In this case, ValueError is raised.
Parameters: name (str, bool, or None) – Name of the flag. Following values are allowed:
'on'
,'ON'
, orTrue
for ON value'off'
,'OFF'
, orFalse
for OFF value'auto'
,'AUTO'
, orNone
for AUTO value
-
chainer.
ON
= ON¶ Equivalent to Flag(‘on’).
-
chainer.
OFF
= OFF¶ Equivalent to Flag(‘off’).
-
chainer.
AUTO
= AUTO¶ Equivalent to Flag(‘auto’).
-
chainer.flag.
aggregate_flags
(flags)[source]¶ Returns an aggregated flag given a sequence of flags.
If both ON and OFF are found, this function raises an error. Otherwise, either of ON and OFF that appeared is returned. If all flags are AUTO, then it returns AUTO.
Parameters: flags (sequence of Flag) – Input flags. Returns: The result of aggregation. Return type: Flag


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Enter your Username and Password.


That being said, most entrepreneurs struggle at making a startup pitch that gets attention and interest from them. Without a clear idea, no venture capitalists would invest and no customers will consume. Creating a startup pitch isn’t really that hard; all it takes is some practice and passion.
Here are few of the most important things when creating you idea startup pitch.
An adult’s attention span last no more than 8 seconds so you have to make sure you’re clear from the beginning. JUST REMEMBER, CLARITY TRUMPS PERSUASION!
Keep it simple as if you were telling this to a 5 year old kid. Filter out the clutter, big words, and get right to the points using simple, everyday language. YOU HAVE TO FOCUS ON BEING UNDERSTOOD.
Passion makes your pitch much more memorable, different, unique, personal, and engaging. Be enthusiastic about it. PERHAPS, IT MAY OPEN DOORS TO FUTURE OPPORTUNITIES.
 You want to get as much feedback as possible to refine and strengthen the pitch of your delivery.
Angel Investors and Venture Capitalists are being pitched to everyday by hundreds and hundreds of people every day. You want to stand out and grab their attention. You want to start out with something catchy, compelling, and interesting.
You have to make the audience and VC realize that the problem actually exists and how it impacts our everyday life. You have to make them feel “some pain” so they seek for some remedy, aka your solution to the problem.
Discuss about how you solve the problem but you got to be creative on this one. You have to capture the desires and need of the VC and Angel Investors with something new and creative that catches their minds and eyes. You have to differentiate yourself. What can you offer that no one else can?
Venture Capitalists invest, not only on your startup, but the people that are involved in it. You and your team members could be really essential to deal breakers. As much as it matters about the idea, what matters more is being able to execute them; being able to turn those “ideas” into reality. VC look whether you have the capability to execute or not. Show positive examples, dedication, and determination to get your work done.
How engaging is your product within the market? If you can build enough traction from consumers, the VC will jump in to invest what your startup has to offer. For example, Groupon achieved multi-million dollar investment from investors despite the hundreds of copycat companies that were in the market simply through traction and follow base.
This is your chance to ask for business cards, give out business cards, or even ask an Investor to personally meet up with him/her. Take advantage of this opportunity. It’s not how you start, but it’s how you end. End strong.
These are few of the things that will help you with your startup pitch. But what are some top rookie mistakes Entrepreneurs make when pitching to VC? Stay tuned.


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The personal website and portfolio of Alex Ruble (that's me!). Mobile-first and -friendly, and a continual work-in-progress.


 My Chemical Romance is going to reunite
Cape Town - Get ready emo kids! Your favourite band is getting back together!
After years and years of speculation, it has been confirmed My Chemical Romance will reunite for one show, at least, at the Shrine Expo Hall in Los Angeles. Speculation was at its highest earlier this year when Joe Jonas claimed My Chemical Romance had been rehearsing in the studio next door to the Jonas Brothers, which guitarist Frank Iero later denied.
The show - taking place on 20 December - will be the band's first since 2012.
My Chemical Romance released their last album, Danger Days: The True Lives of the Fabulous Killjoys in 2010.
Tickets for the reunion gig go on sale Friday via AXS.
Compiled by Alex Isaacs. (Sources: Rolling Stone Magazine , Bang Showbiz)
(Photo: Getty Images)


Image match game
About
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{% include header.html %}
{% include about.html %}
{% include professors.html %}
{% include members.html %}
{% include publications.html %}
{% include projects.html %}
{% include activities.html %}
{% include support.html %}
{% include footer.html %}


Dr Emmanuel
Here's the timeline of Dr Emmanuel's life:
- 1914 - Born in Cresco, Iowa
- 1933-Leaves his family's farm to attend the University of Minnesota, thanks to a Depression era program known as the "National Youth Administration"
- 1935-Has to stop school and save up more money. Works in the Civilian Conservation Corps, helping starving Americans. "I saw how food changed them", he said. "All of this left scars on me."
- 1937-Finishes university and takes a job in the US Forestry Service
- 1938- Marries wife of 69 years Margret Gibson. Gets laid off due to budget cuts. Inspired by Elvin Charles Stakman, he returns to school study under Stakman, who teaches him about breeding pest-resistent plants. Tries to enroll in the military after the Pearl Harbor attack, but is rejected. Instead, the military asked his lab to work on waterproof glue, DDT to control malaria, disinfectants, and other applied science.
- 1941- Receives a Ph.D. in Genetics and Plant Pathology
- 1942 - Rejects a 100% salary increase from Dupont, leaves behind his pregnant wife, and flies to Mexico to head a new plant pathology program. Over the next 16 years, his team breeds 6,000 different strains of disease resistent wheat - including different varieties for each major climate on Earth.
- 1945-Discovers a way to grown wheat twice each season, doubling wheat yields
- 1953- crosses a short, sturdy dwarf breed of wheat with a high-yeidling American breed, creating a strain that responds well to fertilizer. It goes on to provide 95% of Mexico's wheat.
- 1962- Visits Delhi and brings his high-yielding strains of wheat to the Indian subcontinent in time to help mitigate mass starvation due to a rapidly expanding population
- 1970- receives the Nobel Peace Prize
- 1983- helps seven African countries dramatically increase their maize and sorghum yields
- 1984 - becomes a distinguished professor at Texas A&M University
- 2005 - states "we will have to double the world food supply by 2050." Argues that genetically modified crops are the only way we can meet the demand, as we run out of arable land. Says that GM crops are not inherently dangerous because "we've been genetically modifying plants and animals for a long time. Long before we called it science, people were selecting the best breeds."
- 2009- dies at the age of 95.
"He was a very great man."


flexponsive is a consulting company using big data and live user experiments to improve campaign performance and understand user behavior.
On this site, we plan to host open source contributions. Please check again soon


@* * Copyright 2023 HM Revenue & Customs * * 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 forms.AwrsFormFields @import services.DataCacheKeys._ @import views.html.view_application.helpers._ @import views.view_application.ViewApplicationHelper._ @import views.view_application.helpers.ViewApplicationType @import views.view_application.subviews.SubviewIds @(headingKey: String, someModel: Option[models.Products], showTableHeader: Boolean = true )(implicit viewApplicationType: ViewApplicationType, request:Request[AnyContent], messages : Messages) @heading = @{messages(headingKey)} @wrapperId = @{SubviewIds.productsId} @href = @{controllers.routes.ProductsController.showProducts(false).url} @content(model: models.Products) = { @if(showTableHeader) {
@Html(edit_link_s(href, s"$heading"))
}


Save Electricity, Save the Earth
Tips to Use All Year Long
- Keep your refrigerator and freezer full. That way they don’t warm up as fast when you open the door and they have to work less. Just don’t keep the door open too long when deciding what of all that food you want to eat.
- Plant trees in the yard. They shade in the summer and break cold winds in the winter.
- Clean the lint filter of your dryer after every load.
- Close doors and heating/cooling vents in rooms that you aren’t using.
- Unless a recipe tells you otherwise, before putting hot food in the refrigerator, cool it to room temperature.
- Defrost manual-defrost refrigerators and freezers when the frost is 1/4" thick.
- Dry multiple loads of laundry immediately after one another. You’ll use less energy because the dryer is already heated.
- Dishwashers use less water than hand washing dishes. Let the dishes air dry to save even more.
- If you’re away from home for more than a few days, turn down the water heater.
Tips for Summer
- Line dry clothes instead of using the drying machine.
- To naturally cool the house, keep blinds, drapes or shades closed during the day.
- Install a whole-house fan (in the attic). It draws cool air into the home through the windows while forcing hot air out through attic vents. Use it after sundown when the outside temperature is cooler, and in the early morning. This helps to affordably cool the house, by reducing air conditioning use.
Tips for Winter
- Let natural sunlight warm up the house by opening curtains, blinds, etc.
- Caulking the inside of window frames and doors for better insulation.
- Move furniture around so you sit near interior walls. Since exterior walls and older windows are likely to be drafty, by not sitting near the draft you’ll feel less need to set the thermostat higher.
We hope you have liked these tips. Want to provide us with some more energy saving tips of your own? Please send us an email at<EMAIL_ADDRESS>We’d love to hear from you. If you give us a new tip that we don’t already have on this page we’ll give you a discount on future work or products we offer.
We wish you all the best in your energy saving efforts. Remember that no matter how much energy you save, you still have to use some electricity. What better way to generate it than the environmentally clean and safe solar energy? Our experts can answer any questions you have, give price quotes and much more. Just give us a call at<PHONE_NUMBER>.
Solar Fact of the Day
Even small solar electric systems have significant environmental impacts. The 2.5kW solar system reduces CO2 emissions in equal measure to planting one acre of trees. This offsets a value equivalent to the CO2 emitted by a passenger car driving 7,800 miles.
Copyright © NY Solar


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|
image = file handle for previously loaded image
width# = new width in pixels height# = new height in pixels |
|
Similar to ScaleImage, but uses pixel values instead of percentages. Use this command to resize an image previously loaded with LoadImage or LoadAnimImage.
This is NOT intended for REAL TIME scaling of images! Precalculate your images before running your program, or you will likely see massively slow renderings of graphics. |
|
; ResizeImage example
; Set Graphics Mode Graphics 800,600,16 ; Randomize the random seed SeedRnd MilliSecs() ; Load an image to tile (your location might vary) gfxBall=LoadImage("C:Program FilesBlitz Basicsamplesall.bmp") ; Size it randomly from 300 to -300 both x and y ResizeImage gfxBall,Rnd(-300,300),Rnd(-300,300) ; Wait for ESC to hit While Not KeyHit(1) DrawImage gfxball,Rnd(800),Rnd(600) VWait Wend |


APS Framework tester
This app will attempt to fully test the framework from the dev files at
../../js/src/


Paper to CAD; Construction documents for analysis, planning & execution; Interior design solution with 2D & 3D; Building Elevation Design; Retail space planning; Land development design and Sketch up modeling.
HVAC System Design; Plumbing System Design; Electrical System Design & Fire Fighting System Design.
Furniture, Fixtures & Equipment(FF&E); Transport & Traffic Engineering Consultant and Green Building.
We kick-started operations on August, 2014 with the goal of providing superior solutions and great support, all at a minimal costs.
Determined to widen our scope of services, we expanded our operations to interior design solutions, retail space planning, and FF&E
With expected turnover and good support that we received from our clients, we further expanded our scope to consulting and engineering services.
Lead Designer
Lead Marketer
Lead Developer
<EMAIL_ADDRESS>+91<PHONE_NUMBER>


Reasonable and affordable solution for hosting and data storage, customize marketing strategy for small, medium and others.
Forcus on web and mobile design, provide best approach when the budgets are varying even it's insufficient.
Provide secure web services, enables clients to control access, protects users from threats, and secures their sensitive data.