text:
\section{Introduction}

Glaucoma is a progressive and irreversible eye disease, where vision is lost due to damage to the optic nerve. Vision loss is usually gradual, starting peripherally and since there are no symptoms in the early stages, detection of the condition tends to occur late. The disease can be detected via a variety of tests such as planimetry, pachymetry, tonometry, fundus photography and optical coherence tomography (OCT)~\cite{NICE2017} but final diagnosis typically includes a visual field test (VFT)~\cite{Broadway2012}.

VFTs, however, are costly, time-consuming and media opacities such as cataracts, visual acuity, glaucoma medications, severity of glaucoma, learning effect, distraction and other factors can affect the reliability  of VFTs~\cite{Ho2013,Peracha2013,Longmuir2009}. In addition, agreement between clinicians about visual field progression, even for reliable VFTs, was found to be low ($\kappa=0.32$)~\cite{Viswanathan2003} due to a lack of common consensus on the glaucoma progression assessment criteria.

On the other hand, OCT~\cite{Huang1991} is a non-invasive imaging modality that enables the objective quantification of retinal structures, which have been found to be important biomarkers of glaucoma. Specifically, the retinal nerve fiber layer (RNFL) and combined ganglion cell with inner plexiform layer (GCIPL) begin to thin early as the disease progresses~\cite{Medeiros2009,Lucy2016}.

This raises the obvious question to what degree structure and function are correlated and whether functional measurements such as  Visual Field Index (VFI) or Mean Deviation (MD) can be inferred from structure. Harwerth et al.~\cite{Harwerth2006} and Leite at al.~\cite{Leite2012} found visual field defects to be proportional to the neural loss caused by glaucoma. Similarily, Hood et al.~\cite{Hood2011} and Ali et al.~\cite{Raza2011} demonstrated that the visual field thresholds can be directly compared to the OCT probability or thickness maps when correcting for the displacement of the retinal ganglion cells.
An earlier study by Sugimoto et al.~\cite{Sugimoto2013} used a Random Forest classifier to predict glaucomatous VF damage based on age, gender, right or left eye, axial length and 237 different OCT measurements. Later Bogunović et al.~\cite{Bogunovic2015,Abramoff2015} and Guo et al~\cite{Guo2017} estimated individual Humphrey 24-2 visual field thresholds from RNFL and GCIPL thickness maps derived from nine-field SD-OCT using Support Vector Machines.

Here we assess whether aggregate VFT metrics such as VFI and MD can be estimated directly from single, raw OCT scans of the ONH or the macula. Thus eliminating the need for 9-field OCT or layer segmentation, which is prone to errors especially with moderate to severe glaucoma conditions and also co-existing other ocular pathologies. We compare the accuracy of the proposed Convolutional Neural Network (CNN)~\cite{Krizhevsky2012,Lecun2015} with classical approaches that apply machine learning (e.g. k-Nearest Neighbor, Support Vector Machines, Random Forests and others~\cite{Russell2010}) to segmentation-based OCT features such as peripapillary RNFL thickness at 12 clock-hours and four quadrants, mean retinal nerve fiber layer (RNFL) thickness, rim and disc area, horizontal/vertical cup-to-disc ratio and cup volume.

\section{Material and methods}

This study was an observational study that was conducted in accordance with the tenets of the Declaration of Helsinki and the Healthy Insurance Portability and Accountability Act. The Institutional Review Board of New York University and the University of Pittsburgh approved the study, and all subjects gave written consent before participation.

\subsection{Performance metrics}

Two common, global Visual Field Test (VFT) indices employed for glaucoma diagnostics are Mean Deviation (MD) and Visual Field Index (VFI). The MD measures the reduction in sensitivity, averaged across the visual field and relative to a group of healthy, age-matched patients. The VFI is calculated from the pattern deviation probability plot with a MD~$\geq$~-20 dB or from the total deviation probability plot for a MD~$<$~-20 dB. The VFI ranges from 100\% (healthy) to 0\% (perimetrically blind) \cite{Bengtsson2008}. Note that VFI and MD are highly correlated ($r=-0.96$) but the VFI has reduced sensitivity to early damage~\cite{Mansuri2014}.

The accuracy of the evaluated deep and machine learning methods to estimate VFI and MD was quantified by the Root Mean Square Error ($RMSE$) and the Pearson Correlation ($PC$). The $RMSE$ is defined as follows
$$
RMSE = \frac{1}{n} \sqrt{\sum_{i}^{n} (x_i-y_i)^2} \ ,
$$
where $x_i$ is the estimated and $y_i$ is the true, measured VFI or MD of the $i$-th visual field test. Similarly, the correlation coefficient $PC$ was computed as
$$
PC = \frac{\sum_{i}^{n} (x_i-\bar{x}) (y_i-\bar{y})}
{\sqrt{\sum_{i}^{n} (x_i-\bar{x})^2 \sum_{i}^{n} (y_i-\bar{y})^2}} \ ,
$$
where $\bar{x}$ and $\bar{y}$ are the samples means.

\subsection{Data}

ONH and macula scans from 579 patients were acquired on a Cirrus HD-OCT Scanner (Zeiss, Dublin, CA, USA). 504 of the 4155 scans were diagnosed as healthy and 3651 with primary open angle glaucoma (POAG). The data set was divided according to a ratio of 80\% training samples, 10\% validation samples and 10\% test samples. It was ensured that scans belonging to the same patient were not scattered across folds.

Scans were labeled as glaucoma if glaucomatous visual field defects were present and at least 2 consecutive test results were abnormal. The scans had physical dimensions of 6x6x2~mm with a corresponding size of 200x200x1024~voxels per volume but were down-sampled to 64x64x128 for network training and normalized with respect to laterality (left eyes were flipped to right eyes).

Corresponding visual field test measurements (MD and VFI) were aquired on a Zeiss Meditec, Model 750, with test type SITA Standard 24-2. Following \cite{Yaqub2012}, tests with pupil diameter less than 2.5mm, fixation loss greater than 20\% or false positive or negative rates of more than 20\% were discarded.

Demographical background such as gender and race distribution, and mean values with standard deviations for patient's age, Intraocular Pressure (IOP), MD and VFI measurements are provided in Table~\ref{tab:demo}. Statistically significant differences ($p < 0.0001$) between the distribution of healthy and POAG patients were found for age, IOP, MD and VFI.

\begin{table}[!ht]
	\centering
	\caption{{\bf Demographic data: Gender and race distribution, and mean values with standard deviations and ranges for age, IOP, MD and VIF.}}
	\begin{tabular}{lcc}
		& Healthy & POAG \\
		\hline \noalign{\vskip 3pt}
		\#Female 	& 76				& 246 \\
		\#Male 		& 39				& 217 \\
		\#Uknown    & 0				    & 1 \\
		\hline \noalign{\vskip 3pt}
		\#White 	& 87				& 308 \\
		\#Black 	& 26				& 142 \\
		\#Asian 	& 0					& 12 \\
	    \#Hispanic 	& 0					& 1 \\
	    \#Unknown 	& 2					& 1 \\
		\hline \noalign{\vskip 3pt}
		Age 		& 60.2$\pm$15.3 [22.8..87.0]	& 66.2$\pm$12.5 [25.2..93.3]\\
		\hline \noalign{\vskip 3pt}
		IOP 		& 13.6$\pm$2.7	[8..23]			& 15.3$\pm$4.6 [1..60] \\
		\hline \noalign{\vskip 3pt}
		MD 			& -0.74$\pm$1.5 [-10.7..2.8]	& -7.2$\pm$8.1 [-32.5..2.8]\\
		\hline \noalign{\vskip 3pt}
		VFI 		& 98.7$\pm$2.0 [77..100]		& 80.7$\pm$25.1 [0..100]\\
		\hline
	\end{tabular}
	\label{tab:demo}
\end{table}

\subsection{Classical machine learning}

Traditionally, ONH related features such as RNFL thickness, cup-to-disc ratio and others are measured on OCT images and build the basis for glaucoma assessment. We use these numerical features as input to a wide range of classical machine learning algorithms but aim to estimate VFT metrics (VFI, MD) instead of detecting glaucoma. Note that this is a regression problem in contrast to a classification problem.

Specifically, we take 22 features extracted by the Cirrus OCT scanner such as peripapillary RNFL thickness at 12 clock-hours, peripapillary RNFL thickness in the four quadrants, average RNFL thickness, rim area, disc area, average cup-to-disc ratio, vertical cup-to-disc ratio and cup volume~\cite{Kim2009}.

All features were normalized by subtracting the features mean and scaling to unit variance. Normalization parameters were estimated on the training data only and then applied to training, validation and test data. No further pre-processing steps were performed. All features were real valued and contained no missing values.

We then trained the following machine learning algorithms as implemented in the Scikit-learn library~\cite{Pedregosa2011} on the extracted 22 features: Linear Regression and k-nearest Neighbor Regression~\cite{Russell2010},  Support Vector Regression (linear, polynomial, RBF)~\cite{Scholkopf2001}, Multi-layer Perceptron~\cite{Rumelhart1986}, Random Forest Regression and Decision Tree Regression~\cite{Breiman2001}, Gradient Boosting Regression~\cite{Natekin2013} and Extra Trees Regression~\cite{Geurts2006}.

Hyper-parameters of each algorithm were optimized as follows: we selected important hyper-parameters with reasonable ranges, and then uniformly sampled 100 times for each training fold. The parameters resulting in the highest PC on the validation set were used to compute the PC and RMSE on the test set. This process was repeated 5 times (5-fold cross-validation) and we report mean PC and RMSE with standard deviations (STD) on the test set.

\subsection{Deep learning}

In contrast to the classical machine learning approach the proposed deep learning system does not extract a predefined set of glaucoma related features such as RNFL thickness and other from the OCT volume but operates on the raw data. Apart from down-sampling (linear interpolation) from 200x200x1024 to volumes with dimensions 64x64x128 voxels due to constraints of the GPU memory (12GB), and flipping of eyes, no further pre-processing or feature extraction was performed.

\begin{figure}[h]
	\centering
	\includegraphics[width=1.0\linewidth]{network.pdf}
	\caption{Network architecture.}
	\label{fig:architecture}
\end{figure}

The downsampled volumes were inputted into a Convolutional Neural Network (CNN)~\cite{Lecun2015}, depicted in Figure~\ref{fig:architecture}, where the network architecture is derived from a CNN for glaucoma classification~\cite{Maetschke2018}. It is composed of five 3D-convolutional layers with ReLU activation, batch-normalization, filter banks of sizes 32-32-32-32-32, filters of sizes 7-5-3-3-3 and strides 2-1-1-1-1. We also employed 3D spatial dropout ($rate=0.2$)~\cite{Tompson2015,Chollet2017} to counteract over-fitting. In contrast to \cite{Maetschke2018}, after the Global Average Pooling (GAP)~\cite{Zhou2015} a regression layer with Tangens hyperbolicus (tanh) activation function is added to infer VFI and MD. Note that 3D convolutions are essential to enable the computation of 3D Class Activation Maps (CAM)~\cite{Zhou2015}.

The CNN was implemented in Keras~\cite{Chollet2017} with Tensorflow~\cite{Abadi2016} as backend. Data splitting and pre-processing was performed with nuts-flow/ml~\cite{Maetschke2017}. Training was performed on a single K80 GPU using NAdam with a learning rate of $1e-4$ over 300 epochs and 5-fold cross-validation. The network with the highest validation PC during training was saved (early stopping) and results on the independent test are reported.

CAMs were constructed following Zhou et al.~\cite{Zhou2015}, resized and overlayed on the input OCT scan. Note that CAMs are computed for the smaller input OCTs 64x64x128 and mapped back to scans with the original dimensions of 200x200x1024 (See Figure~\ref{fig:cams}).

\section{Results}

In this section we first report the results for the classical machine learning methods trained on segmentation-based OCT features, and then the performance of the deep learning system trained on raw OCT scans of the ONH or the macula.

Table~\ref{tab:ml-results} shows the Person Correlation (PC) between the estimated and the true VFI of the various machine learning methods on the test data. As stated above, training and testing was performed via 5-fold cross-validation and the reported mean PCs and standard deviations are computed over the 5 test folds.

\begin{table}[!ht]
	\centering
	\begin{tabular}{lccc}
		\toprule
		Method  & PC:VFI \\
		\midrule
		RFR                  & 0.74$\pm$0.090\\
		GBR                  & 0.72$\pm$0.087\\
		SVR (RBF)            & 0.71$\pm$0.105\\
		LR                   & 0.69$\pm$0.075\\
		KNR                  & 0.69$\pm$0.075\\
		SVR (linear)         & 0.66$\pm$0.060\\
		MLP                  & 0.64$\pm$0.113\\
		DTR                  & 0.62$\pm$0.084\\
		ETR                  & 0.59$\pm$0.089\\
		SVR (poly)           & 0.42$\pm$0.112\\
		\bottomrule
	\end{tabular}
	\caption{Results for classical machine learning methods such as Random Forest Regression (RFR), Gradient Boosting Regression (GBR), Support Vector Regression (SVR) with linear, polynomial or RBF kernel, Linear Regression (LR), k-nearest Neighbor Regression (KNR) ,  Multilayer Perceptron (MLP), Decision Tree Regression (DTR) and Extra Tree Regression (ETR). Performance is measured by Person Correlation (PC) for Visual Field Index (VFI) with standard deviations over 5-fold cross-validation. }
	\label{tab:ml-results}
\end{table}

\begin{comment}
FOLDS = 5  # x-fold cross validation
TRIALS = 100  # Trials for hyper-parameter optimization
Classifier      R(val)    STD(val)    R(test)    STD(test)    val-test
------------  --------  ----------  ---------  -----------  ----------
RFR              0.732       0.036      0.735        0.090      -0.002
GBR              0.731       0.037      0.722        0.087       0.009
SVR (RBF)        0.736       0.038      0.714        0.105       0.022
LR               0.679       0.033      0.685        0.075      -0.006
KNR              0.679       0.033      0.685        0.075      -0.006
SVR (linear)     0.629       0.045      0.655        0.060      -0.026
MLP              0.738       0.037      0.642        0.113       0.096
DTR              0.712       0.043      0.615        0.084       0.096
ETR              0.703       0.041      0.587        0.089       0.116
SVR (poly)       0.456       0.122      0.421        0.112       0.035
\end{comment}

The highest correlation of $0.74$ was achieved by the Random Forest Regressor (RFR), closely followed by Support Vector Regression with RBF kernel and Gradient Boosting Regression (GBR). These non-linear regression methods outperformed the standard Linear Regression (LR). Support Vector Machine Regression with linear or polynomial kernel was found inferior and comparatively time consuming to train. Similarly, decision tree regressors (DTR, ETR), while fast to train, did not achieve high accuracies.

The results of the deep learning system trained on raw OCT scans of the ONH or macula are shown in Table~\ref{tab:dl-results}. In addition to the PC, here we also report the RMSE between the inferred and the true VFI or MD. As before, all results are 5-fold cross-validated.

\begin{table}[!htbp]
	\centering
	\begin{tabular}{ccccc}
		\toprule
		{} &  \multicolumn{2}{c}{PC} & \multicolumn{2}{c}{RMSE}\\
		\midrule
		Region  & VFI & MD & VFI & MD \\
	    \midrule
		ONH 		& 0.88$\pm$0.029	& 0.88$\pm$0.024	& 12.0$\pm$1.61	& 4.1$\pm$0.44 \\
		Macula 		& 0.86$\pm$0.026	& 0.85$\pm$0.016	& 13.4$\pm$1.75	& 4.4$\pm$0.38 \\
		\bottomrule
	\end{tabular}
	\caption{Results of the deep learning network for ONH and Macula scans. Accuracy is measured by Root Mean Square Error (RMSE) and Pearson Correlation (PC) of Mean Deviation (MD) and Visual Field Index (VFI) with standard deviations over 5-fold cross-validation. }
    \label{tab:dl-results}
\end{table}

\begin{comment}
SpatialDropout3D(0.2) + rerange + tanh + NoAugmentation +NoStratifyVFI + [VFI, MD] + [POAG, Normal] + clipping
#samples 3329 422 404
EPOCH: 299 onh, 5 fold cross-validation
cols : ['corr:vfi', 'corr:md', 'rmse:vfi', 'rmse:md']
means: [0.884, 0.88, 12.003, 4.052]
stds : [0.029, 0.024, 1.61, 0.439]
EPOCH: 299 mac, 5 fold cross-validation
cols : ['corr:vfi', 'corr:md', 'rmse:vfi', 'rmse:md']
means: [0.856, 0.848, 13.449, 4.431]
stds : [0.026, 0.016, 1.748, 0.382]
\end{comment}

In comparison with the classical ML methods trained on traditional OCT features the CNN achieved a substantially higher correlation of $0.88$. The PC on Macula scans was slightly lower ($0.86$) but still significantly higher than the PC of $0.74$ for the best classical ML method (RFR). Note that the reported RMSE for VFI and MD are not directly comparable, due to the different ranges of the metricies (VFI: $0..100$, MD: $-32.5..2.8$).  The PC shows no significant difference between VFI and MD for the same region (ONH or macula).

Figure~\ref{fig:pred_scatter} provides an overview of the CNN's VFI estimates by plotting the inferred versus the true VFI for a typical training, validation and test fold. Note that the regression line is computed on the entire data set (4155 samples) and the corresponding PC of $0.93$ is therefore higher than the reported mean PC of $0.88$ on the test folds. The data set shows an expected bias towards mild cases of glaucoma (VFI $>$ 80) and there are a few cases where the system heavily under- or over-estimates the VFI.

\begin{figure}[h!]
	\centering
	\includegraphics[width=0.9\linewidth]{pred_scatter.pdf}
	\caption{Scatter plot of estimated versus true VFI for a training, validation and test fold for the deep learning network trained on ONH. Black line shows linear regression with PC of $0.93$. (Plot best seen in color) }
	\label{fig:pred_scatter}
\end{figure}

\subsection{Class Activation Maps}

In attempt to understand which regions of an OCT scan are informative for the estimation of VFI, we computed Class Activation Maps (CAMs)~\cite{Zhou2015}. Figure~\ref{fig:cams} shows representative CAMs for three patients with different degrees of vision loss measured by the VFI. Note that aspect ratios of scans do not reflect physical dimensions of OCT volumes.

\begin{figure}[!h]
	\centering
	\includegraphics[width=0.5\linewidth]{cams.pdf}
	\caption{Class activation maps for three different VFI values. Regions and layers important for VFI inference are marked red.
	N=Nasal, T=Temporal. (Maps best seen in color)}
	\label{fig:cams}
\end{figure}

In the case of normal vision (VFI = 100) the network focuses on the Ganglion Cell and Inner Plexiform layers (GCIPL) in general (marked red). For increasingly higher degrees of vision loss (VFI = 50, VFI=30), smaller more specific regions of the GCIPL are highlighted; potentially indicating locations of layer thinning.

\section{Discussion}

The deep learning network trained on raw OCT scans of the ONH or macula achieved significantly higher accuracies in estimating VFI or MD than any of the classical machine learning methods trained on segmentation-based OCT features. While the computation time for estimates of both approaches is comparable, the CNN is substantially more time-consuming to train; days in contrast to minutes. Furthermore, while CAMs provide some insight into the features used by the CNN, the explanatory power of the established features  RNFL thickness, cup-to-disc ratio and others remains better.

We attempted to further improve the accuracy of the deep learning system by augmenting the OCT volumes during training. Specifically, we explored random occlusions, translations, small rotations ($\pm$10 degrees) along the enface axis, and mixup~\cite{Zhang2017} but did not observe a significant impact on accuracy and therefore did not employ augmentation for the final results reported here.

Other variation such as higher-resolution OCT volumes or combining ONH and macula scans, which are likely to improve the accuracy of the CNN were not evaluated. It is noteworthy that we also did not use Intraoccular Pressure (IOP) or age as input features, where the latter is a required parameter for VFT, as threshold values are compared to age-adjusted normal values.

VFI and MD measurements provide the ground truth data the CNN was trained on. These aggregate measures are derived from VFT, which are known to be unreliable and perfect accuracy can therefore not be expected. Abramoff et al.~\cite{Abramoff2015} computed the retest variability of VTFs, which defines an upper bound on the accuracy of the CNN, and found a correlation of $0.88$. This might indicate that the performance of the CNN, with a PC of $0.88$ is close too or at the upper bound. Also in very good agreement with \cite{Abramoff2015} is the accuracy of the SVM for which Abramoff et al. report a mean correlation of $0.68$, while our evaluation finds a correlation of $0.66$ (see SVM(linear)in Table~\ref{tab:ml-results}).

Guo et al.\cite{Guo2017} and  Bogunović et al.\cite{Bogunovic2015} estimate individual Humphrey 24-2 visual field thresholds but require segmentation of RNFL and GCL, and the registration of the 9-field OCT volumes. The potential errors in registration and segmentation, especially for severe cases of glaucoma or lower quality scans, might have a negative effect on their estimates. Furthermore, Raza et al.~\cite{Raza2011} found the RNFL of the temporal region of the disc to be thin and highly variable, even in healthy individuals, indicating that RNFL thickness might not be a good measure of structural damage. In contrast, the method proposed here avoids explicit segmentation and registration but is currently limited to estimating aggregate VFT indices such as VFI and MD.

\section{Conclusions}

We demonstrated that aggregate VFT measurements such as VFI and MD for healthy and POAG patients can be estimated directly and with good accuracy from raw OCT scans using a Convolutional Neural Network. We found the accuracy when using ONH scans as inputs slightly higher than for macula scans. The deep learning approach achieved considerably higher accuracies than all other machine learning methods trained on the features usually employed for glaucoma diagnosis. An method that accurately infers VFT measurements from OCT scans has the potential of substantially reducing examination time and cost.

redpajama_set_name: RedPajamaArXiv


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Cairo and Alexandria, Egypt at Night (NASA, International Space Station Science, 10/28/10), originally uploaded by NASA's Marshall Space Flight Center.
I tend to avoid reading any news before noon. Why spoil the morning? But then I somehow think it is fine to check Facebook and emails while my coffee brews. Depending on the chatter that too could spoil a morning.
The Atlantic article also posts a clip of Foxnews discussing the potential offensive nature of a certain Doritos Ad that has a bit of fun with Communion wafers replaced by Doritos.
As I continued to scroll through the Facebook mumbo-jumbo, there was another post by the same friend about a message he had received from Egypt: "From a friend in Egypt-another demonstration of the law of unintended consequences! "Christians and Muslims have been united as never before defending their homes on overnight shifts (due to the lack off police security) this is resulting for many to make friends with neighbors they never knew and there is a real sense of camaraderie which we never had before."
What a contrast between the trivial and the extraordinary. In the States, enormous amounts of energy and money is spent over something so benign and unimportant as advertising and perceived offenses of the religious, while neighbors in Egypt with differing religious devotions are losing sleep and safety to watch the other's homestead.
As much as this dichotomy offers up yet another occasion to rant about the decadent shallowness of American television, and to some degree, culture, it is the Egypt story that shines above the dregs. Ever since the Towers fell, Islam has been targeted as an enemy of the States, and many U.S. "Christians" have embraced such rhetoric; as if the Anti-Christ seems to have a face and it looks like Mohammed. All the while, when chaos and "terror" are just down the block, a human face is the only thing Egyptian Christians and Muslims see next door.
When I consider the Reality that these Egyptians are fleshing out, I want to be more like them. I would hope in similar circumstances I would be right along side them, creating space for a neighbor to go into his time of prayer with peace of mind, (and not just a piece of my mind).
The banter over advertising, which costs $3,000,000 for ½ a minute, is a waste of creative faculties all on its own, a celebrating the mundane and absurd. The news out of Egypt should end the discussion straight out as neighbors discovered that sticks and stones are the things that break bones and homes, not thirty seconds on Sunday.
Maybe a little bit of revolution is good for us all once in awhile, after all… even if it is another's revolution.


text:
The Orion's Arm Universe Project Forums › The Landing Site › The Arrivals Lounge
Hello. Long-ish time wiki reader here.
Pages (3): 1 2 3 Next »
alexanderhamiltonalaska
Hi, I've been a fan of OA for a while and joined recently mainly because I had some worldbuilding ideas I was interested in writing about. While the ideas themselves are probably better discussed in another forum, one question I would like to ask is whether there is anywhere I can go for a detailed breakdown about the abilities and processing requirements of higher-level transapiants.
Worldtree
/Dfleymmes (Admin/editor)
To start answering your question :
Archailects (plus the linked articles for the 4th, 5th, 6th singularities)
https://www.orionsarm.com/eg-topic/492d76d2f173e
Toposophic Levels and Mental Abilities
https://www.orionsarm.com/eg-article/4b9f2a844034a
Limits of transapient power
https://www.orionsarm.com/eg-article/47fae575daf11
Toposophic Level and Brain Size
https://www.orionsarm.com/eg-article/4a53a8f690f09
Archailect Architecture (and linked articles)
https://www.orionsarm.com/eg-article/48eb4e4ee73d4
I was more asking if there was somewhere I could look for more detailed information about s>3 transapient /archai beyond what is covered in Encyclopedia Galactica, since my idea mainly involved a tribemind forming clade that effectively ended up turning into an archai. The EG articles don't really have much information about the higher toposophic levels for in-universe reasons, so I was wondering if there was anywhere in the forum I could get more information about them.
Drashner1
Hi - Welcome to OA!
Regarding the information you're trying to find out - if what you're trying to find out isn't in the EG, you're welcome to ask your questions here on the forums and we can try to answer them for you.
(02-12-2022, 11:08 AM)Drashner1 Wrote: Hi - Welcome to OA!
Okay then. My main questions would be:
What amount of resources (EG computronium, support) would a S4 intelligence need, and what would that translate to in terms of the amount of modosphonts that could be supported by the resources used separately?
What sort of truly new mental capabilities (beyond being able to design and use new technologies) would emerge at the S4 level?
What about S3 or S5 intelligences?
(02-12-2022, 11:56 AM)alexanderhamiltonalaska Wrote: Okay then. My main questions would be:
Assuming the S4 is 'self-ascended' rather than being the creation of another being of an even higher S-level, the mass required to support an S4 mind translates into about 300x the mass of the Earth. This can take various forms:
a) A Jupiter Brain - a concentrated intelligence, a sphere of computronium, about the size of Jupiter. About 3 Earth masses of that is a 'CPU' made up of plasma processors - processors that use a mix of magmatter and high temperature plasma to perform computations at such high speed and temperatures that it's rather like a stable nuclear explosion or the inside of a small star.
b) A Dyson Brain - the mass of a Jupiter Brain, but distributed in the form of a swarm of networked processors surrounding a star, usually at about same distance that Earth orbits the Sun.
c) A Matrioshka Brain - Much the same as a Jupiter Brain, but the processors are individually smaller and occupy a much larger volume extending beyond something the size of our solar system.
A single kg of plasma processor can basically run an entire S3 - and and S3 can be discussed in terms of having the processing power of 2.97e20 modosophont minds. Since the CPU of an S4 is some 3 Earth masses, that works out to:
2.97e20 modos/kg of S4 processor x 1.7916e25kg = approx 5.32e45 modos equivalent. By way of comparison, the entire non-transapient population of the setting maxes out at roughly 3e21 modos.
(02-12-2022, 11:56 AM)alexanderhamiltonalaska Wrote: What sort of truly new mental capabilities (beyond being able to design and use new technologies) would emerge at the S4 level?
We don't honestly know if what you mean by 'truly new' is some form of mental capability that has no equivalent in human minds. Rather by definition, it is literally beyond our ability as humans to conceive of what transapient minds can do. It's sort of like asking a creature that lacks self-awareness to conceive of and describe it. Or creatures that are blind to imagine and describe sight.
That said, it is something of an ongoing occasional hobby among the membership to try to imagine truly qualitatively different mental abilities for transapients (as opposed to quantitative differences, which are much easier to imagine). So far we haven't has a lot of luck in this area, but it's fun to keep trying. Most of what we've come up with is down at the S1 and S2 level however.
In terms of mental capabilities for S3 and above beings - whether they are truly new or qualitative or quantitative, some ideas that we've come up with include:
1) Creating new AIs/new minds - An S3 can do this as easily as a human would speak a single sentence. An S4 can imagine a new human level mind into existence as easily as a human would speak a one syllable word. At the S5 level it is not uncommon for individual thoughts to achieve self-awareness/sophonce and form complex societies before being reabsorbed or fading out of existence as the S5 thinks of other things. At the S6 level, it has been suggested that all of Terragen civilization is just a figment of an S6's imagination.
In a related area, it has been suggested that if an S5 or higher pays sufficient attention to a modo it may - without really trying and as a side effect of creating a mental model of the modo in order to predict its behavior - create anything up to trillions of copies of the modo, each copy being fully self-aware and sophont, and subject to a huge number of simulated life scenarios - some of them painful or deadly.
2) Rewriting - It is possible for S3 and above to rewrite the minds of modosophonts entirely and en masse. Changing their memories, personality, most deeply held beliefs, etc. and replacing them with a perfectly synthesized set of artificial memories, personality, most deeply held beliefs etc that are more to the transapient's liking. Modos and lower transapients can do this to individuals and groups - but S3 and above can do this to entire civilizations if they are so inclined.
3) An S5 or higher thinking about a concept even slightly - for example, if it hears the word 'dinosaur' - may imagine entire planetary biosphere's into existence, simulated down to the level of individual cells and micro-organisms and up to the level of planetary weather and climate - and encompassing the entire evolutionary history of dinosaurs - and then either unmake them again as it thinks about something else - or cause the figment of its imagination to be constructed via nanotech in the real world.
There's probably others, but those are what come to mind most immediately.
02-12-2022, 10:17 PM (This post was last modified: 02-12-2022, 11:13 PM by Rynn.)
(02-12-2022, 10:57 AM)alexanderhamiltonalaska Wrote: I was more asking if there was somewhere I could look for more detailed information about s>3 transapient /archai beyond what is covered in Encyclopedia Galactica, since my idea mainly involved a tribemind forming clade that effectively ended up turning into an archai. The EG articles don't really have much information about the higher toposophic levels for in-universe reasons, so I was wondering if there was anywhere in the forum I could get more information about them.
Welcome to the forums! I wrote an article like this once.
https://www.orionsarm.com/eg-article/55955128ec815
In working out the details for it I stuck to the tribe mind being capable of reaching S2. Reason being that S3 require about a moon's worth of material as a processor. If the idea is to have modosophont (I.e human level) sophonts combining to form the mind, a moon's worth is too prohibited. An M-Brain masses about 1e21kg. Given that a typical brain weighs a little over a kg, that means we'd need to connect at least 1e21kg of modos together. Likely more because modo brains aren't as efficient as processing per unit mass than technology.
That's more modos than exist in the setting. The idea could work still but you'd have to have to tribe mind merge, go virtual, or otherwise radically alter itself to cross to S3. Archai begins at S4.
OA Wish list:
Internal medical system
A dormbot, because domestic chores suck!
(02-12-2022, 10:17 PM)Rynn Wrote: That's more modos than exist in the setting. The idea could work still but you'd have to have to tribe mind merge, go virtual, or otherwise radically alter itself to cross to S3. Archai begins at S3.
Yes, good point. I should have raised it myself since looking at what I posted in the light of a new day I can see how it could potentially make the OP think that eir idea couldn't work in OA.
IIRC we were recently discussing tribemind/group mind based transapients in the Discord a bit and this fits in with that nicely.
A group of modos could form a tribemind, which eventually ascends to S1 and then S2. At that point any S2 will need to get its hands on a lot more processing power to ascend to S3 (among other things). At that point it could move into pre-existing computronium that is large enough to accommodate an S3 (Jupiter brain or above class processors that are operating as habitats for some number of virtual beings rather than hosting a single S4 or higher) or build a moon-brain or equivalent. Eventually, it might ascend to S4, again either first moving into a large enough virtual habitat or building a J-brain or equivalent.
S5 or above would pretty much need to build eir own processor core since virtual environments don't seem to run that large in the setting at this point.
(02-12-2022, 10:49 PM)Drashner1 Wrote:
What about if it was almost entirely composed of aiods in the first place? In addition, the polity might actually take an overall stance somewhat closer to Solipsism than what is generally found in standard sephirotic empires (likely being derived from the Dry Empire something similar), which combined with the fact that outside observers aren't necessarily going to be given a lot of access to the brains of minor archai for obvious reasons would mean that they wouldn't necessarily be being included in estimates of terragan population. While there might be a relatively 'small' minority of, say, 1.5e13 individuals that are willing to directly interact with the rest of terragan civilization, their claims of being part of a much larger tribemind-based metaempire could very easily be dismissed as being memetic engineering from the ruling archai.
Dry empire
https://www.orionsarm.com/eg-article/464f25d76bab7
this article is basically a stub that hasn't been updated in 21 years, so you're welcome to expand on it
there's *plenty* of ways for your idea to work though, however you end up fleshing it out.
if I'm understanding correctly, whether this polity is composed of biologically-based sophonts or AIoids (which would make the transition easier) if they're starting with a tribe-mind, they'll still need to add quite a bit of additional infrastructure+ processing power before they 'merge' and reach the third sephirotic... but it's definitely possible.

redpajama_set_name: RedPajamaCommonCrawl


Played a total of 2383 times by 367 registered members. Finished by 345 users who rated the difficulty as easy.
Hi to you all - It's a beautiful winter's day here in the Gold Coast of Australia - approx 22 degrees - wow seems like spring - Soooooo - what am I doing indoors playing this game that I'm addicted to - can anyone of you explain that to me ?
The 2 plays up if that helps anyone.
Hi everyone. Can't stay. Thanks Merav, Dale and Bruce. Low cards play up.
Good question, Joanne. I don't see anything spammy about what he said.
Pa I hope the medals go through the whole table, upto at least zenon!! I might stand a chance then!!!
I see the Spam finger is back!?!?!?! why Spam Franco?


text:
Q: Detect "was previous page from the same magento website?" If yes: then dont show APP notice We have an APP popup that popups in mobiles. It depends on a meta param in the header.
We would like to create an if / else scheme like

*

*if new visitor: print the meta param

*else (if not new and already on site: : do not bother the visitor
Is there a quick session() method for this that we could use?

A: Could you use JS? Something like this:
var referrer = document.referrer;
var yourDomain = "example.com";

if(referrer.indexOf(yourDomain) !== -1){
        console.log("Came from your domain!")
}else{
        console.log("Did not come from your domain.")
}

redpajama_set_name: RedPajamaStackExchange


The late actress Madhubala is considered to be an evergreen beauty in the history of the Bollywood film industry. Let's take a look at some of her amazing pictures.
Madhubala is considered to be one of the most beautiful and iconic actresses of the Bollywood film indusry. The actress was even compared to the Hollywood actress Marilyn Monroe because of her charming beauty and personality. Madhubala has starred in numerous films in Bollywood in between the years 1942 and 1964. She made her acting debut at a mere age of 9 years with the film Basant which was released in the year 1942. However, she got her breakthrough in her acting career with the Raj Kapoor starrer film which was released in the year 1947. Madhubala, who was also known as the venus of Indian Cinema, has acted in more than 70 films in a career of 22 years.
Madhubala was last seen in the film Jwala opposite Sunil Dutt. This also happened to be her last film which was released in the year 1971, two years after her untimely demise due to prolonged illness. Jwala happens to be her only film which had been shot in colour. Madhubala is famous for portrying the role of Anarkali in the famous film Mughal - e - Azam which co - starred Prithviraj Kapoor and Dilip Kumar. The historical drama film which was directed by K. Asif was released in the year 1960. The film later went on to become the highest grossing Indian film of all times. It was also the first black - and - white film which was later digitally converted. The coloured version of the film was released in the year 2004 which went on to become a huge commercial success.
Madhubala died at a very young age of 36 years due to prolonged illness.


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Announcing the Winner of the 2021 Student Corporate Engagement Competition!
IEN's Student Corporate Engagement Competition puts a new spin on the traditional approach to investment competitions by focusing on the responsibility of investors to directly engage company management on the risks and opportunities they see.
This year, student teams from Arizona State University, Dartmouth College Tuck School of Business, University of California Haas School of Business, and University of Chicago participated in the Competition.
Watch The 2021 Student Corporate Engagement Competiton Finals Here
Each team worked from February to April to produce both a written investment recommendation in a publicly-traded company listed on any major exchange, and a proposed shareholder engagement strategy that aligned with IEN's Social Equity and Climate Goals.
Our panel of judges selected the winning team based on presentation, provided evidence, scale of embedded ESG analysis, and the creativity and efficacy of the shareholder engagement strategy to both improve company financial performance and have a meaningful positive social or environmental impact.
After careful consideration, we are pleased to share that this year's Student Corporate Engagement Competition winner is Arizona State University (ASU)!
The ASU Team proposed an investment in BlackRock, Inc., chosen for its financial reliability, strong ESG performance with material topics, competitiveness as an industry leader, commitment to racial justice, and opportunity to reduce its risks. According to the team, when discussing their proposed shareholder engagement strategy, "As the world's largest asset manager, BlackRock is well-positioned to advance racial equity by investing in initiatives that strengthen minorities' ability to accumulate wealth. By improving diversity internally and in its invested companies, BlackRock can realize additional financial returns directly and indirectly through improvement in diversity and inclusion." To multiply leverage to move BlackRock, the team proposed building a coalition of universities whose endowments either also employ BlackRock as an OCIO/fund manager or can invest in BlackRock as a shareholder.
"What makes our strategy unique is the real aspect of collaboration and strength in numbers," said Shakki Bhat, a member of the ASU team who received his BA in Business and Global Politics this spring.
Read the Full Press Release Announcing the Winner Here
Each team should be immensely proud of the fantastic deliverables they produced -- we offer a huge congratulations to all participants!
Learn more about the Competition here. We are currently recruiting student teams, partners, and sponsors to participate in the Competition during the 2021-2022 academic year. Please fill out this form to indicate interest in participation.
And thank you to the Supporting Sponsor of this year's Competition, Federated Hermes, for their generous partnership in supporting the next generation of sustainable investing professionals.


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Music Review: The Guitar Original Motion Picture Soundtrack
Posted on November 9th, 2008
by Zach Freeman in All News, Music Reviews, Reviews
Amy Redford, daughter of famed actor/director and sundance founder Robert Redford, has created her feature film debut – a relatively small independent film about a young woman (Saffron Burrows) who discovers that the tumor in her throat is cancerous and that she is terminally ill. The ensuing story is a fanciful tale of self-indulgence and wish fulfillment – imagine the spirit of Tim McGraw's "Live Like You Were Dying" transferred on to film – inspiring but also unavoidably cliche. The film's soundtrack is on roughly the same level: there are moments of beauty, but for the most part we've heard this stuff before. Composer David Mansfield (Transamerica, The Apostle) provides most of the music here, though much of it is so subtle, it's easy to overlook.
The first six tracks on the album are an eclecitc mix of artists (with two tracks supplied by The Everyothers) that stand a bit apart from the remaining 31 tracks of Mansfield's composition. Jonny Savarino's "Glancing Lovers" is an entrancing bit of muzak that's over too soon, Phoebe Jean Dunne's "Cold Hands" is a minute of quiet guitar picking, Alap Momin's "Arch Angel" ups the ante a little bit, though it almost feels as if it belongs on a different album. The two songs by The Everyothers (a David Bowie cover and the garage rocking "Dive With You") are fairly underwhelming. In short, these opening tracks aren't much to listen to (even if "Arch Angel" is impressive).
Mansfield's score tracks are relatively short (the track "Guitar Practice" is a terse 15 seconds) but they're pleasant enough. For the most part, the music here doesn't provide as much emotion as listeners might expect from a typical score. Aside from the melancholy notes of the despairing "Mel," most of the music is gentle and quiet to the point of being forgettable. The attitude and upbeat mellowness of "Nice Dress" is a welcome addition here, as is "Hard Way" – recorded in a scratchy radio style. But the soundtrack for The Guitar mellows itself into boredom. By the time the 37th track is played, most listeners are likely to have tuned out.
Bottom line – The soundtrack for The Guitar  has a handful of truly catchy ditties, mostly provided by David Mansfield, but the quiet, subtelty of his work here doesn't keep one's attention as well as some might hope.
Zach's Rating: C+
Perfect For: Falling asleep on an overcast day
Stay Away if: You're looking for variety and excitement in a score
If you buy only one track, make it this one: "Arch Angel" – Alam Momin
To purchase the soundtrack for The Guitar, visit Amazon
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Healthcare Management Consulting & Assessment
Executive & Leadership Training
Jeff Schroeder
"The most rewarding aspect of our career is knowing that we have positively impacted physicians, institutions and their patients."
-Jeff Schroeder
469-524-1453 Jeffrey.Schroeder@amnhealthcare.com
Jeff Schroeder has an extensive background in physician search and candidate development, having spent the past nine years of his career helping clients across the United States create a resilient and skilled workforce.
He began his career in 2010 at Merritt Hawkins, starting as a Search Consultant in the Southwest where his portfolio encompassed staffing solutions in four states. In 2014, Jeff was promoted to Director of Recruiting; in 2017, he expanded his focus to the education arena and represented a number of academic divisions, departments, and institutions throughout the country that were seeking faculty or leadership candidates to join their teams.
He joined Phillips DiPisa & Associates in 2019 in candidate development, bringing his broad-based knowledge to the task of assisting candidates move seamlessly into leadership positions. Jeff's focus on the intricacies of workplace, the people that compose it, and the importance of creating the correct synergy to drive improvement is reflected in his work for clients.
Jeff grew up in St. Louis, Missouri, and graduated from Quincy University in Quincy, Illinois with a Bachelor's in Communication. He now resides in Frisco, TX with his wife Jill, and their two children.
© 2021 Phillips, DiPisa & Associates. All rights reserved.
Design by Hinge.


Let's be honest, everyone starts somewhere. Learning to DJ is genuinely easier to do when using a controller. Not to mention, buying a pair of CDJs and a DJM will run you around $6,000. Starting there is almost impossible unless you have a ridiculous amount of disposable income. So you learned to DJ on a controller in your bedroom, and that's what you're comfortable with, I get that, but major club owners and promoters will definitely see it differently.
I'm not talking about your town's local hotspot, if you don't live in a major city then for the most part this doesn't matter much. In rural areas, or even bars, the promoter couldn't care less what you use to DJ, you could be just using your laptop trackpad for all they care.
But what happens when you want to take your performances to the next level and play on bigger stages, in front of larger crowds and for more money? What do nightclub owners, promoters and other DJs think when you ask to set up your Numark NS7, Traktor S4, or Pioneer DDJ SX (and those are higher-end controllers)?
They think you look like an amateur.
It's true. Plain and simple. No matter how talented you are on a controller, coming into a major nightclub and asking the technician, other DJ, or promoter to move the gear that's already set up just to plug in your S4 is seen as an amateur move. For one thing, it's a hassle for them, because controllers aren't very small as I'm sure you know. Sometimes they even put the controller directly on top of the CDJ/DJM layout, but that makes it harder for the next DJ to smoothly come in at the end of your set.
Main stage sets at large venues are seen as a place for professionals, from the opener to the closer. So when you get the opportunity to DJ one of those venues, step it up and blow people away.
Of course you can argue that some major DJs in the world use controllers or other setups, and yes, some do. Zedd is notoriously known for loving to use his Traktor S4. Why can he get away with that and still be a professional that's getting paid huge amounts of money to play all over the world? Because he's Zedd! He's had numerous international hits and he can do whatever he wants.
But if you aren't as massive as an international sensation like Zedd, and want to start getting paid more for your DJ sets and play on larger stages, what should you do?
Learn how to use CDJs.
The setup is expensive, but I'm sure if you get booked in a venue that owns them, they will allow you to come early and practice. You can rent a pair, or buy a Pioneer DDJ controller. Those controllers translate very well to the CDJ setup that you see in almost, if not every, club. Once you learn that, you can make your way around CDJs. Watch Youtube tutorials, watch the tutorials on TraktorProTutorials.com and most important, out the time in!
Looking to take your DJ career seriously, get paid more to play, and take on bigger stages? Then present yourself as a professional who is versatile and can use what's in the DJ booth.
We're not completely against controllers, they're super fun to play with and easy to use at home, when space may be limited. But for the professional DJ, CDJs are the industry standard and it's best to know how to use them if you want to take your abilities to the next level.
← Celebrando 4 anos online!


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Leader in Interoperability Concepts and Capabilities
The MD PnP program, established in 2004, has become a recognized leader in the development of the concepts and capabilities for integrated clinical environments. We have been working to accelerate the adoption of medical device interoperability by providing interoperability building blocks (use cases, standards, a neutral lab "test bed" environment, and open research tools) and by changing clinical and market expectations of what can be achieved.Affiliations and Program Support
The program is based at the Massachusetts General Hospital (MGH) Dept. of Anesthesia, Partners HealthCare System, and the Center for Integration of Medicine and Innovative Technology (CIMIT). Our MD PnP research program has been supported primarily by the U.S. Army Medical Materiel Agency (USAMMA) Telemedicine & Advanced Technology Research Center, the National Institutes of Health (NIH), National Science Foundation (NSF), and the National Institute of Standards and Technology (NIST). We have an additional affiliation with the SHARP program in the Office of the National Coordinator for Health Information Technology.
Having evolved from the OR of the Future program at MGH, the MD PnP program remains clinically grounded. Our program work to date is focused on the following areas:
Standards Development - Led development within ASTM open standard for a patient-centric "Integrated Clinical Environment" (ICE) to define the conditions under which interoperability can enable device integration to create new medical device systems with greater safety and performance capabilities than any individual device – Part I of the ICE standard was published as ASTM F2761-09 (renewed 2013), and is providing a valuable framework for further defining the vision and clinical content for many other standards
Regulatory Pathway - Leading a working group of companies, academics, and hospitals that are developing a prototype regulatory submission to help refine the FDA clearance process (see FDA workshop content)
Contracting Language - Creating and refining interoperability contracting language for use by hospitals in their procurement of medical devices (MD FIRE: Medical Device Free Interoperability Requirements for the Enterprise)
Clinical Scenarios - Workflow analysis of clinical scenarios at the level of detail needed to inform interoperability solutions and to derive engineering requirements
Demonstration Implementations - Developing and showing clinical use cases in which integrating the clinical environment will improve patient safety (e.g. x-ray/ventilator synchronization and safety interlocks for patient-controlled analgesia medication delivery), and showing these at major clinical and health IT conferences
Open Platform Development - Developing a prototype healthcare intranet with an open ICE platform and tools to ensure safe and effective connectivity of medical equipment and decision support for clinical care
We have taken a multi-faceted approach to begin addressing key barriers to achieving interoperability, including the development and support of suitable open standards (e.g. ASTM F2761-09 Integrated Clinical Environment, or ICE), and the elicitation, collection and modeling of clinical use cases and engineering requirements for the ICE platform and "ecosystem".
Geographically Dispersed Team
The MD PnP program leadership and "geographically dispersed team" includes not only members of Partners HealthCare clinical, information services, and clinical engineering staff but also colleagues from
other integrated healthcare delivery networks (IHDNs) such
as Kaiser Permanente; marketing and engineering staff from
medical device manufacturers; FDA and NIST staff involved in
the regulation and testing of software-based medical devices;
marketing and engineering staff representing manufacturers of
information technology-based hardware and software; and
members of academic and research communities and clinical and engineering societies.
Collaboration with Diverse Stakeholders
Our interdisciplinary, multi-institutional program team has been collaborating with diverse stakeholders including:
Biomedical and clinical engineers
Healthcare delivery organizations
Medical device manufacturers
Interoperability-promoting organizations
Since the program's inception, more than 800 clinical and engineering experts, and representatives of more than 100 companies and institutions have participated in plenary workshops/conferences, working group meetings, and focus groups to contribute to ongoing program activities and help shape the common goals.
Vendor-Neutral "Sandbox" Laboratory
The MD PnP lab provides a vendor-neutral "sandbox" to:
Evaluate the ability of candidate interoperability solutions to solve clinical problems
Model clinical use cases (in a simulation environment)
Develop and test related network safety and security systems
Support interoperability and standards conformance testing


NOTE: The below trip report is an excerpt from a much longer and more inclusive TR I posted on my blog, of a weeklong trip to Mississippi and Florida. So if there is anything that seems out of context, sorry about that. I tried to add in a few notes in parentheses to flesh it out.
Also note that I wrote it for a general audience, so there are descriptions of the rides that enthusiasts probably don't need, but oh well.
If you want to read the rest of it, the link's at the bottom.
When I was a senior in college, trying to decide what to do with my English degree, I went to the guidance office and read through a pamphlet designed to help people with that very question. The pamphlet noted that if you want to go into journalism, you better like it, because the monetary compensation alone is not going to satisfy you.
Despite that sage advice, I went into journalism anyway, and yes, I had to take a pay cut from the temp job I had in college. Now, eight years later, the pay has risen to a somewhat respectable level, but more importantly, I still enjoy my job. One of the best things about it is the little perks you get from businesses trying to get you to write about them. These range from baskets of cookies, food, CDs and new products sent to the office, all the way to free theme park tickets -- even for non-working visits.
I took full advantage of this before vacation, e-mailing Disney PR and asking for four one-day Parkhopper tickets (which allow you to visit any Disney park in one day). My request was granted. Those tickets have a total face value of $412. Nice perk, eh?
On Wednesday morning, we (me, my wife Rachel, her aunt Roberta, and her aunt and uncle Pam and Jerry) left Arcadia (Flordia, where we were staying with Rachel's grandma) for Orlando about 7 a.m., as it's a two-hour drive. Not much to see on the way there. We stopped at McDonald's in Winter Haven for coffee, and the restaurant is perched on the edge of a beautiful lake - very pretty setting.
Our first indication that we were nearing Disney country was the Mickey-shaped utility pole. Yes, utility pole. We entered the complex and made our way to our first park of the day, EPCOT.
This would be the first time since 1986 that I'd been to Disney, and while I wasn't expecting any serious thrills, I was curious to see how it'd changed. While I often have gone to great lengths to ride roller coasters, and while Orlando is home to several coasters I haven't ridden, I decided that I wasn't going to pursue them, and I was just going to slow down, relax and enjoy the day, and not care if I got to ride them or not. It's a revolutionary attitude for me (considering the fact that I almost cried when I didn't get to ride Goliath at Six Flags Magic Mountain in 2001).
The EPCOT parking lot looked mostly empty. I got my four free tickets without trouble from Guest Relations (Roberta has a season pass and didn't need a ticket) and we entered under Spaceship Earth (aka giant golf ball) and made our way to the first ride of the day, Soarin'.
I normally hate motion-simulator rides because they never feel real, but Disney apparently knows how to do it right. Soarin' supposedly simulates a hang-gliding experience. You enter a room and sit in one of three rows of ski-lift-style seats. When the ride starts, the seats rise up and thrust forward into a dome-shaped movie screen, so it's impossible to look anywhere and not see the screen.
The feeling of motion is quite intense. Several times I felt my stomach drop, and even more, I felt my back being pressed against the back of the seat as if I was feeling positive G-forces (I assume they tip the chairs back to create this effect). The ride is enhanced by wind and smells (orange, pine and sea, depending on what you're soarin' over). It's the first motion simulator I've ever enjoyed.... amazing.
Now, I kind of wanted to ride Mission: Space next, but I was a little wary of it. I know that it's a centrifuge, and while generally you can't feel the spinning on simulators such as this, I didn't want to ruin my day with nausea either. Since no one else was going to ride with me (though they were perfectly willing to wait), I decided against it.
So we moved on to Test Track, where we took advantage of another perk. Rachel's grandpa worked at GM all his life before retiring in 1974. Because of this, he received a card that allowed him and his family access to a special GM lounge above the ride (GM sponsors Test Track). Even though he died several years ago, the perk continues for his family.
We entered a special back door and took an elevator up to the lounge, where there was free Coke and coffee. There also were windows that allowed us to see inside the ride as it ran, though I didn't look too hard as I didn't want to ruin the surprise. Pam and Jerry, who are looking for a new car, caught a GM executive as he went into a meeting and discussed cars with him for a while while we drank Coke and looked out the front windows at the park.
The best part about the GM lounge is that when you're done lounging, you take a special door that leads you right to the front of the line. No waiting! So we took our seats in one of the cars, with Rachel "driving."
Test Track is an excellent ride, supposedly simulating vehicle design tests. It starts with a "hill climb" test, up a 30% grade, then moves on to shocks (rough roads), handling (swerving through cones), environment (extremely hot and cold chambers), brakes (speeding up and sudden stops), and a series of switchbacks. The final test is the barrier test, where you speed up quickly and nearly crash into a wall - but instead, the wall opens and you speed around outside the building at 70mph on a banked track. I loved it.
Next, we entered the World Showcase section of EPCOT, where most of the attractions hadn't yet opened. Instead, we hopped on the ferry that takes guests to MGM Studios - a 20-minute ride across what looked like a man-made lagoon, surrounded by hotels and a boardwalk.
To enter MGM (and all the parks for that matter), first you insert your ticket into a slot, then you jam two fingers into another slot. When your ticket comes out the other side, you can enter. I have no idea what the finger thing is about, unless it scans your prints.
Our first stop at MGM was Who Wants to Be a Millionaire - Play It! This attraction is on its last legs, set to close this month, but I was really looking forward to doing it. We entered the waiting area at just the right time and were offered the "fastest finger seats," which are the front-row seats with built-in monitors that you see on the TV show. This did not increase our chances of winning, however, as every person in the 600-seat audience gets a chance to sit in the "hot seat."
The "studio" looked EXACTLY like the TV show. I was impressed. Even though the show isn't recorded, as far as I know, there are multiple cameras to capture the audience and the contestants.
Now, the reason I was looking forward to this attraction is that I was SURE I could win it. Once you get in the hot seat, though you can't win money, you can win prizes such as a Disney cruise for four. However, I underestimated how difficult it would be.
The first fastest-finger question asked us to put the letters in order of the name of the "little green monster" from Monsters Inc. My brain couldn't recall the name nor make anything out of the letters IKEM, at least not in 2 seconds. Of course it was MIKE, and I didn't have a chance. However, I held out hope - you can play along with the contestant, and the person who answers questions correctly the fastest becomes the next contestant.
The first guy didn't get very far - most of his questions were easy, and I got them all right. Furthermore, I hit the button as soon as it was possible to hit it, so I was confident I'd get in the hot seat. Alas, I didn't even make the top 10. I think some people must have robotic fingers that can hit buttons 100 times faster than normal humans.
The good news is, at the end of the second game, they showed the final top 10 of the crowd, and Rachel made No. 10. We were all proud of her.
We stopped for lunch next. Everyone kept raving about this one restaurant that had amazing chicken fingers, so that's where we went, although Rachel and I got turkey sandwiches instead. The sandwiches were really, really good (turkey, red peppers, cheese and arugula on multigrain bread, served with Wendy's-esque fries), and I was impressed that the restaurant had several somewhat healthful options.
After lunch, we split up, with Jerry and I going toward the thrill rides and the ladies watching the Beauty and the Beast show. Jerry and I headed toward the Rock 'n Roller Coaster, which he said he would ride with me, but he balked at the 50-minute wait. So we moved over to the nearby Twilight Zone Tower of Terror, but the wait there was 60 minutes. Jerry refused to wait, but I was determined to ride at least one thrill ride, so he went off and I joined the line alone.
I haven't mentioned it yet, but the heat outside that day was nearly intolerable. So far, we'd managed to do OK because we were constantly going in and out of shops and attractions. But now I was stuck in line, under the blazing sun and stifling humidity, and it was absolutely miserable. I don't think I've ever felt so disgustingly sweaty. I tried to take my mind off of it by starting a conversation about baseball with a Red Sox-cap-wearing guy, but it just made things worse as he continued to lecture me about the Sox for 20 straight minutes (later I heard him lecturing someone else about the Patriots).
The line was quite neat, actually. The "story" of the ride is, an elevator full of actors disappeared from a Hollywood hotel after a strange electrical disturbance, and the hotel has been abandoned ever since. Therefore, the foliage around the line is all overgrown and "neglected," and the signs and structures appear to be deteriorating.
After about 40 minutes in the heat, the line entered the building for the pre-show, which explained the story (and a bunch of idiots finished Rod Serling's final sentence for him, as if they were clever for knowing he was going to say "The Twilight Zone"). Another 15 minutes in the glorious air conditioning and I was ready to board. I was really impressed with the theming, as the entrance to the ride is just a normally sized, sliding elevator door. Behind the door is a car that holds like 18 people, though you'd never know that from the outside.
The ride starts with a quick ascent, then the doors open to reveal a long hallway with a window at the end. Some ghosts appear, and then the hallway goes black except for the window as a field of stars appears. The window rotates and floats toward you - pretty trippy. Then the elevator doors close and you go up again. The doors open on another hallway, and this time your car actually moves forward into the hallway, where there are some more trippy effects. At the end of the hallway, a set of doors opens to the outside, revealing how high you are, and then a random series of drops and launches begins. I counted five stomach-taking drops, and I could have sworn that the last launch actually went "up and over" the top (i.e. moved forward as well as up), though after reading about the ride, I decided this was in my mind. But what a great ride - worth the wait.
Best thing about it - only a simple car-style lap belt to hold you in. And the ride ops didn't even check it.
I rushed out of the building after my ride and met the rest of my party at a shop. We got some Icees and decided that we were done with MGM and its crowded midways, so we headed back to the ferry to catch a ride back to EPCOT.
On the way to MGM, the ferry had been mostly empty, and the air conditioning had nearly kept up with the body heat. No such luck this time - the boat was packed, and the sweat poured off my forehead and chest like, er, water. We couldn't stand it anymore, so we got off at the second stop (out of four) and hoofed it past the hotels. It was hot outside, too, but at least we could breathe.
Once we entered EPCOT, my favorite part of the day began. I have heard several times that, while Disney as a whole is designed for kids, EPCOT's World Showcase is for adults. It's true. And while I was expecting a patronizing representation of the various countries, I was happy to find out that not only are the country areas designed, maintained and funded by the countries themselves, but all the employees in each section are natives of that country.
We spent a short time in England watching the British Invasion, a Beatles cover band, before sampling the various shops and bakeries in the other countries. I can't remember the exact order right now, but we experienced France, Germany, Italy, Norway, the U.S., Morocco, Mexico, Japan and China, and probably more. In France, we watched the film "Impressions de France," which was dated but had lovely classical music and a neat wrap-around screen. I was hoping to find spumoni ice cream in Italy, but they had gelato instead, so I settled for a gingerbread man in Germany. In Mexico, we took the relaxing boat ride through the history of the country, and listened to a mariachi band for a while. I especially liked the large store in Japan, which had a lot of interesting electronics.
It took some time to walk through the countries, and once we were done, it was nearing 6:00 p.m. Rachel and I were asked: Would you rather go to Animal Kingdom, which closes at 7 p.m., or Magic Kingdom? We decided on Animal Kingdom, for me, mostly because, yes, I really wanted to ride the new coaster, Expedition Everest.
Before we left, we stopped at a pavillion sponsored by Coke, which was actually a big highlight for me. The pavillion had fountains with six or seven soft drinks from other countries, all of which I enjoyed very much. There was an orange-flavored Coke, a ginger drink from Africa, and several others. My favorite was a clear drink from Italy that started out fruity, then left a bitter aftertaste. Everyone else hated it, but I really liked that bitterness. Apparently it's often used to clear the palate between courses in Italy.
So we left EPCOT and jumped in the car for Animal Kingdom (apparently there's no transportation there). As the park was closing in an hour, we were able to get one of the very closest parking spots to the gate, though it was still a hike.
As much as I can judge this new park in an hour, I will say, it's quite pretty, but it doesn't seem like there's enough to do. We made a beeline for Expedition Everest, and though the wait time said 70 minutes, the line was still open, and the rest of my family said they didn't mind waiting for me. I waited a few minutes, and while the line didn't move, the wait time went up to 100 minutes before my eyes. As cool as the ride looked, I decided it wasn't worth holding my family up for that long.
As it turns out, even if I had waited, I probably wouldn't have ridden anyway, as strong thunderstorms moved through the area within an hour. So my quest for coaster No. 100 continues.
With enough time to take in just one attraction, we crossed the park to the Lion King show, which the older people in my party were raving about. I have to say it was impressive for what it was, but I just don't get into these Broadway-style shows. It all seems so contrived. I enjoyed the acrobatics of the "monkeys," but other than that I was pretty much bored. It also struck me as weird that the person who sang Scar's song "Be Prepared" was a strong-voiced hero figure. The lyrics, word choices and tone of the song did not match his previously established personality at all.
Rain and lightning greeted us as we exited the show. Our last stop of the day was a large shop, where we picked up some trinkets for our nieces and nephews and a T-shirt for Rachel. We joined the crowd streaming out of the park and piled in the van for the long ride home. Our only stop on the way home was, again, at the Winter Haven McDonald's for takeout supper, where the sun was setting beautifully over the lake. The McDonald's had self-serve ordering stations, which were completely pointless, because once you ordered, you got a receipt that you had to give to an employee - you still had to stand in line. Hmph.
Tower of Terror is by far one of me favorite attractions EVER. I'm glad you enjoyed it.


Was he--as claimed by promoters--an African orphan saved by missionaries, or simply an American born-and-bred bongo player masquerading as a savage? Chaino's background may be shrouded in mystery, but in the late 1950s, when this recording was originally issued, his exotic drumming and strange chants were considered so sensual the album was marketed with the alluring (though largely meaningless) subtitle "Unbridled Passions of Love's Eerie Spectre."
Just over 50 years later, it's a peculiar yet still pleasing affair. About half of the tracks sport foreign-sounding names like "Woo Din Ese" and "Seis Nueve," although they're little different in tempo or timbre than numbers labeled "Don't Do It To Me" or "Mating Calypso." Each of the 12 tunes feature capable Latin or African rhythms coupled with distinctive grunts, moans and whistles. Ultimately the package is more oddity than aphrodisiac, but as a relic of a long-gone era it's weirdly appealing and, in its own way, animalistic.
A long-time aficionado of retro music and movies, Jeff Berkwits has covered vintage sounds for numerous publications and websites including Bachelor Pad Magazine, Filmfax, Outré, and Amazing Stories. He can be reached at jeffberkwits@sbcglobal.net.


subject to Committee approval, other eligible candidates with connections to QinetiQ and/or the MoD (more info).
We operate on an active MoD airfield and all members must have a Boscombe Down security clearance and site pass to access the club. If you do not have or recently held a Boscombe site pass you must, in all cases, be prepared to provide the following items and visit the Security Office to confirm your identity.


With American Independence Day approaching we thought that we would look at our most relevant stylistic theme, 1783.
1783 marked the end of the Revolutionary War and the beginning of a new America. This theme represents a stylistic cross section of classic American furniture in country finishes.
'The Settler's Swag Chest' has delicate painted detailing to the drawer fronts and is Inspired by a rare New England original, circa 1710.
It represents the struggles of the first settlers and their ingenious painted modifications of furniture, and the development of the unique truly American aesthetic by the great American furniture designers of the 18th and 19th centuries – their classicism provides many of the forms of our furniture. A finishing techniques creates unique and tactile surfaces and very visual textures.
Some items have been closely imitated whereas others are combinations of Important American furniture pieces and traditional folk and country finish techniques. Most vernacular American furniture was made from local woods and was stained, glazed, or painted, and then varnished.
Detail of the desktop of 'Fall, 1790', The original early 18th century with later schoolboy graffiti reading 'Jehu Curtis was born October 9th 1790'.
Various techniques were employed by the first settlers to achieve stunning —and sometimes startling— effects using an array of tools to manipulate the paint: brushes, putty, vinegar, smoke, feathers, sponges, combs, leather, and even fingers. Note the hand finished effect to the Lake Lamps (below).
These 'Lake Lamps' were inspired by a Maryland original.
These are forms and finishes that reflect the historic, social and artistc heritage of the USA.
'The Original 1783 Lamp Table' is inspired by a Pennsylvania original dated 1783.
The result is an impressive and classically American furniture shape with an informal rustic look.
This entry was posted in Theodore Alexander and tagged 1783, American furniture, hand painted, Independence Day, Theodore Alexander. Bookmark the permalink.


I stay in Bangalore East and keep travelling to US now and then for work. As you would have guessed from above, I love meeting women and loving them top to bottom, no holds barred! I'd like to know what women reading this are thinking. Message me at virajkc30@gmail.com, but don't ask for photos in first email!


We're less than one week away from Christmas—is your social media ready?
While Christmas provides some great opportunities for your church to share the Gospel with your community, it can be a challenge to get everything done on time and still be creative. Here are three quick ways to leverage social media during the busiest time of the year.
Merry Christmas from all of us at Concordia Technology Solutions! Wishing you and yours a blessed Christmas.


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Beyond Prisons: Taylar Nuevelle On Knitting In Prison
Taylar Nuevelle joins Beyond Prisons to share her love of knitting, the space it created for her while in prison, as well as how it was used to punish her.
Beyond Prisons 0
Beyond Prisons — Episode 15: Hip Hop Scholarship feat. Devyn Springer (Part 2)
In part two of our interview, Devyn discusses hip hop scholarship as a liberatory approach to education, as well as his photography, writing, and poetry.
VIDEO: Poetry & Trans Politics With Darkmatter
Trans South Asian art duo DarkMatter, Alok Vaid-Menon & Janani Balasubramanian, are deeply engaged in the connection of art and social justice.
Kit OConnell 0
VIDEO: From The Streets To The Galleries With Swoon
Internationally-recognized street artist Caledonia Curry, better known as Swoon, shares her art and activism this week on The Laura Flanders show.
VIDEO: Hollywood, Socialism And The Israel/Palestine Conflict With Tony Kushner
Award-winning playwright Tony Kushner talks Hollywood, socialism, & the Israel/Palestine conflict. Plus: A Hungarian feminist hip-hop art gallery for Roma.
Kartemquin Films 50: 'What The Fuck Are These Red Squares?' and 'Anonymous Artists of America'
A student wearing a cape and a hood somewhat casually paints, "What the Fuck are these Red Squares?" in broad daylight. A man walking by says aloud, "I got to call a cop on you. That's beautiful." In the next shot, it is clear the words were painted on the brick
Kevin Gosztola 0
Art & Resistance With Boots Riley & Ellen Meeropol (VIDEO)
Boots Riley of the Coup, author Ellen Meeropol, & Center for Constitutional Rights attorney Rachel Meeropol on using art & activism to fight repression.
Mama Ayesha's Presidential Mural Vandalized … Or Improved?
Mama Ayesha's is a popular restaurant in Washington, D.C. Until recently, the side of the restaurant featured a mural that depicted the restaurant's founder, dressed in her traditional Palestinian garb, embracing the nation's presidents from Dwight Eisenhower to Barack Obama. Only recently, there's been a new addition to the mural: someone shot the crotches of all the presidents with red paint.


- loyalty or commitment to a cause.
The new professional relationship paradigm threatens to outperform loyalty or faithfulness, though not necessarily to destroy it. Loyalty or faithfulness is so psychologically ingrained in some organisations that it is considered to be the glue that holds the organisation together.
On the other hand, when organisations try to manufacture loyalty, they risk creating its opposite - cynicism.
Business in market economies is usually seen as a war involving winners and losers. As a result, loyalty or faithfulness is offered as a prime conceptual framework for managing the firm for competitive war. Individuals are assessed for skills and abilities, and then sorted into a rigid organisational structure. Income, status and decision-making prerogatives are all determined by one's place in the (class) structure. In this structure, each individual is expected to do the tasks allocated and to conform to the hierarchical requirements of the organisation. In short, the loyalty or faithfulness to the organisation is above all other considerations. In return, the organisation protects its staff against the harsh realities of the outside world.
The pay-offs for loyalty or faithfulness include financial security, longevity of employment, security in retirement and a sense of place and purpose in the organisation's structure. The principles of command and control are dependent on the loyalty or faithfulness-driven mindsets. In recent times, mergers, acquisitions and downsizing have demonstrated that loyalty to individuals by organisations is only acknowledged when it suits the organisation's purposes.
Loyalty has always required the willing sacrifice of the employee's sense of, and desire for, freedom to the higher demands of the organisation. This type of environment of loyalty or faithfulness at all cost can generate a culture of silence, fear, transference of blame and loss of personal integrity.
Ultimately, the loyalty or faithfulness system creates a culture of subservience to the whims and personal ambitions of the corporate elite. Such a culture makes it impossible for an organisation's performance to achieve the full potential of its staff. In extreme cases, loyalty or faithfulness diminishes accountability, ie errors, corruption and general under-performance are absorbed and acceptable. In these situations, loyalty can produce a major psychological dysfunction, with loyalty limiting ambition and demanding conformity.
Individual entrepreneurship threatens loyalty or faithfulness. Organisations not requiring loyalty want professionalism instead. Professionalism is a state of mind: it is one's ability to perform, to demand clarity in performance expectations and to accept only those performance expectations that can reasonably be met. It means accepting that the organisational structure is not all-powerful, and that the organisation is not bigger than the individuals who work for it. It means everything is open to question on a daily basis. It accepts that culture is a product of the people in the organisation, and as people change and come and go, the culture changes.
Community and culture are not things that are made; they simply emerge and evolve. Organisations that do not demand loyalty have one focus: the delivery of results to match the needs of its markets. Every part of the organisation has a market focus.
The "war for talent", ie too few suitable people available, has laid the basis for the changes to the structural forces and a paradigm shift; as Jason Cartwright, 2004 states "
We affirm all people, but invest differentially in A, B & C players"
On the other hand, several high-profile corporate collapses, such as Enron, have emphasised the need to rank and reward staff on performance more than talent and/or intelligence.
Success does not come from how much one knows but how well one learns. The knowledge base is always changing, so acquiring knowledge has become less important than knowing how to find and use the knowledge warehouses. The ability to learn quickly and well and to keep learning throughout one's life is the key. Furthermore, learning requires time to reflect, assimilate and practise.
The development and sustenance of strong and mutually beneficial relationships with major stakeholders (customers, owners, community and employees) is vital in achieving peak-performance organisation. All stakeholders need to be informed, conduct open and honest communications and recognise the need to handle change, and that change is a continuous process that takes time, ie have developed and implemented long-term strategies.
Furthermore, there is thecorporate club of good citizenship or corporate social responsibility (CSR) including climate change. Organisations are expected to make a positive contribution to their employees, the environment and to society.


Shenango was sharp in the second half in a nonsection road win over South Side Beaver.
The Lady Wildcats outscored the Lady Rams 32-21 in the second half.
Shenango, coming off a 1-22 campaign, improved to 3-0 for the first time since the 2009-2010 season.
"It was a great start for these girls, especially the seniors," Turk said.
Jenna Petrucci posted 14 points and three steals to lead the Lady Wildcats. Amanda Herb followed with 12 markers and eight rebounds, while Angelina Sibeto added 10 tallies, six rebounds and three steals. Sarah Herb snared six boards as well.
Samantha Gibson registered 17 points for South Side Beaver (1-2).
Sarah Herb 1 0-0 2.
Toni Yucivello 0 0-0 0.
3-point goals — South Side Beaver 3 (Gibson 2, Dhayer 1).
JV score: Shenango 37, South Side Beaver 23. High scorer: S — Samantha Seaburn 16.


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Home > Show / Business
"Theatre with a CLICK"
A special social business innovation task group comprising 9 elders from the Neve Neeman Community Center was created at CLICK! The aim of the group was to promote the Community Theater shows directed by Gadi Kaviet that the seniors themselves perform in. The women's mission was to learn a range of business skills in order to carry out various roles in the area of sales, marketing, advertising, budgeting, pricing etc. The project was supervised by a community social work student from the Ariel University and is managed by the coordinator of the Neve Neeman Community Center.
Booking Information- Aliza Kaushani 050735762
For viewing: http://click-savi.org.il/wp-content/uploads/2014/07/Theatre.pdf
Community Theatre Number 1- "Now I'm Free"
A director arrives at a Seniors Club for elderly women (65-80) in order to establish a theatre group. The women originally from Middle Eastern countries (Morocco, Iraq, Yemen and Iran) were forced into marriage at a young age (12-16 years) to older men. They spent their entire lives suppressed by patriarchal dominant societies and lacked the benefit of an education. The entire process is documented in a film over a five year period that relays the actual process these women underwent during their primary experience with theatre, which allows them for the first time in their life to reveal details about their lives, which expose elements of suffering and injustice. The film also follows the director's experience, a man young enough to be their son who comes from an entirely different cultural and social background which creates at first a block in their communication. It also deals with the empowerment of women, exposing their intimate disappearing world and salutes a group of women who always felt marginal and discover they are capable of achieving more, since now they are free:
For viewing: http://www.cultureunplugged.com/play/2899
Community Theatre Number 2 – "The Big Tent
The theatre group presents scenes from their Aliya experiences, and family experiences from 50 years ago. This included their first meeting with the establishment in Israel, living in teetering tents, all presented with humor and good fun.
Amongst the performers, Suzy Abisris stands out. She admirably portrays different types of men from different time periods. "I made Aliya from Morocco in 1956." explains Suzy "I went to school at Alliance "Vav" and belonged to the drama club. I feel that today, being part of this theatre group, my youth has returned to me."
What are the goals of your activity?
"The goals are both to help the elderly themselves and their community", explains Dr Linda Mosek, a social worker, and director of CLICK.
The director of the theatre group is Gadi Kviatek, who praises his actors. "They love to come to rehearsals, and make an effort to come on time, which is in itself very commendable".
What is it like to be a director of Golden Age actors?
"Together we create the experiences they want to depict on stage. Some is improvisation. There is complete cooperation, and a lot of excitement amongst them. Their children and grandchildren who come to rehearsals support them a great deal."
Do you feel anger or frustration when dealing with the troubles this community had to go through?
"I'm sure they faced a lot of difficulties, it wasn't very pleasant. And I feel this is a way for them to cope with what they went through. Maybe this will help them accept the past better. After all more than 50 years have passed!!"
Show / Business


Mask of Hope Celebration Thank You!
The Mask of Hope Celebration was a huge success!
https://www.thesingletonsaz.org/sing-content/uploads/MOH-Thanks-Video.png 300 500 Singleton Moms https://www.thesingletonsaz.org/sing-content/uploads/The-Singletons-Logo-sm.png Singleton Moms2016-02-11 15:30:402018-04-24 15:14:19Mask of Hope Celebration Thank You!
Huge Shout out to all the Hair and Make Up artists who generously donated their time to help our Singleton Moms look amazing for the 7th Annual Masks of Hope Celebration!
AZ Cancer Village Fun Run is a collaboration of three local cancer related nonprofits: Don't be a Chump, Check for a Lump, Singleton Moms and The Joy Bus.
Thank you to everyone who attended the 2014 Superhero Bolt 5k on November 8, 2014. It was a great day, we really appreciate your support!


By now, you guys probably forgot who I was since my last post was in September...3 months ago. I'm so super sorry for my lack of posts! I'm currently in my last week of my fall quarter at college and by next week I'll be back home for the holidays and winter break! I thought that I could keep updating whilst in college but I've realized that this is actually harder than it seems, haha. I've been getting used to this school and keeping up with my studies. It's odd to now be in college and have to do "grown up" things when just a few months ago, I was still a high school senior. Time sure does fly, doesn't it?
It's finally December guys! Like, you guys have no idea how excited I am. Being in Southern California, far way from home (Chicago), I definitely miss the freezing cold and the snow! But I am so stoked to go back home and soak it all in. It's odd to be able not be freezing without a scarf and boots. I don't think I've had a red nose for a while, haha. Christmas is only a short amount of days away and I think that is absolutely crazy. I swear it was just yesterday when I was still counting the days until I go home. But now....it's only a week away! I think you guys can tell that I'm super excited that it's December and almost Christmas. Christmas is definitely an amazing time of year.
I can't wait to get back in my own bed and be surrounded by my friends from high school and family. It's weird that I haven't seen my friends in three months when I've seen then everyday for the past 4 years. I definitely feel like I've grown up even thought I've only experienced college for 3 months. I think being by myself and being so far away has helped me become a stronger person and handle myself better. I was thinking about doing Blogmas, but I feel like I'm a little late. But I will definitely be going back to regular posts by next week, so stay tuned guys!


Amendments to the Canada Labor Code (CLC), expected to take effect in 2019, will introduce changes relevant to the design and administration of group benefits, time off and retirement programs. CLC applies to employees in federally regulated sectors (such as banking, telecommunications and airlines). Separate pay equity legislation will, among other things, require federally regulated private sector employers with at least 10 employees to establish and maintain a pay equity plan within set time frames. The Employment Insurance (EI) program within social security, which provides pay replacement benefits during parental leave and applies to all employees living in every Canadian jurisdiction except Quebec, will also be amended from March 2019 to implement a new EI parental sharing benefit.
New leaves of absence, such as five days of personal leave per year, three of which are employer-paid (for employees with at least three months of service). The leaves could potentially be used for personal illness or injury, family care and educational responsibilities, and urgent matters, among other circumstances.
Employer-paid bereavement leave will be increased from three days to five days per year.
Accommodation of the increased benefit period for parents who take the new EI parental sharing benefit (see below). The maximum aggregate amount of parental leave that both parents can take will be increased by five weeks (or eight if the employee takes the extended parental leave).
The eligibility requirement of 30 days of employment for statutory holiday pay entitlement will be eliminated.
For individual terminations, the current requirement of two weeks' notice (or pay in lieu) after at least three months' consecutive employment will remain. However, an additional notice (or pay in lieu) of three weeks, after three years of consecutive employment, plus another week for every additional year of consecutive employment (up to a maximum of eight weeks) will be required. For collective dismissals, employers will have to provide eight weeks' notice (or pay in lieu) to dismissed employees.
Employees will be entitled to a 30-minute unpaid break for every five hours of work, a minimum eight-hour rest period between shifts and unpaid breaks for breastfeeding.
The effective dates for the amendments applicable under the CLC have not yet been determined because they must be set out in orders-in-council of the federal government (though some of the amendments cannot be effective before September 1, 2019).
Our Client Advisory provides a fuller explanation of the key changes to the CLC.
Eligible parents will be able to receive additional EI parental benefits provided both parents take a leave of absence from employment and claim them.
Up to five weeks of additional EI parental benefits will be made available to parents who choose the standard benefit of 55% of covered pay (i.e., for 35 weeks plus up to the five additional weeks for a total of 40 weeks) or up to eight weeks if parents choose the extended benefit of 33% of covered pay (i.e., for 61 weeks plus up to the additional eight weeks for a total of 69 weeks).
Both parents must choose the same parental benefits option (i.e., standard or extended), and they can receive the benefits at the same time or at different times. Parents can also choose to divide the total benefit period however they wish, except that neither parent can take more than 35 or 61 weeks, as the case may be.
Our Client Advisory provides a fuller explanation of the new benefit and leave rules.
Federally regulated employers will need to review their current HR programs and benefit plans to identify policies or processes that will need to change once the amended CLC provisions become effective and also consider how best to coordinate new statutory paid leave entitlements with existing time-off programs. All employers with employees outside of Quebec will need to review carefully how the new EI parental benefit changes could impact them and their employees based on applicable minimum employment standard leave rules (provincial or federal) and an employer's particular benefit and HR policies.