text:
Q: Flyweight design pattern in java, what is the purpose? I have the following code:
public class Sentence {

    private String [] words;
    private Map<Integer, WordToken> tokens = new HashMap<>();

    public Sentence(String plainText) {
        words = plainText.split(" ");
    }

    public WordToken getWord(int index) {
        WordToken wt = new WordToken();
        tokens.put(index, wt);
        return tokens.get(index);
    }

    @Override
    public String toString() {
        List<String> ws = new ArrayList<>();
        for (int i = 0; i < words.length; ++i) {
            String w = words[i];
            if (tokens.containsKey(i) && tokens.get(i).capitalize) {
                w = w.toUpperCase();
            }
            ws.add(w);
        }
        return String.join(" ", ws);
    }
}

and test:
@Test
public void test() {
    Sentence s = new Sentence("alpha beta gamma");
    s.getWord(1).capitalize = true;
    assertEquals("alpha BETA gamma", s.toString());
}

My question is: what is the purpose of use flyweight pattern in that way?

A: The Flyweight Pattern is a re-use pattern that reduces the memory footprint of a program by re-using identical objects. This is common with value objects, which represent simple values, such as words, since words with the same characters are identical. For example, suppose we have the following sentence (ignore capitalization for now):
the doorman held the door for the guest

This sentence has 39 characters, which means that if we created a String from this sentence, we would need to store 39 characters (ignore the length field used by the Java String implementation for now). If we look at the sentence, there are 3 instances of the, which are identical to one another. There are also 7 spaces, which are identical to one another. If we tokenized the string, we would obtain the following words:
["the", "doorman", "held", "the", "door", "for", "the", "guest"]

If we take only the unique values in this list, we obtain:
["the", "doorman", "held", "door", "for", "guest"]

Using these unique words, we could create the sentence by mapping the indexes of the word in the sentence to the unique words:
[0, 1, 2, 0, 3, 4, 0, 5]

To reconstruct the sentence, we would simple map the indices above to the list of unique words, adding a space between each of the words.
In the case of the example you provided, it appears that the algorithm is incorrect (it does not save any space, since it stores both the words and the tokens). A more correct solution (one of many) would resemble):
public class Sentence {

    private final List<Integer> wordMap = new ArrayList<>();
    private final List<String> words = new ArrayList<>();

    public Sentence(String sentence) {
        for (String word: sentence.split(" ")) {
            addIfNotExists(word);
            wordMap.add(words.indexOf(word));
        }
    }

    private void addIfNotExists(String word) {

        if (!words.contains(word)) {
            words.add(word);
        }
    }

    public List<Integer> getWordMap() {
        return wordMap;
    }

    public List<String> getWords() {
        return words;
    }

    public static void main(String[] args) {
        Sentence s = new Sentence("the doorman held the door for the guest");
        System.out.println(s.getWordMap());
        System.out.println(s.getWords());
    }
}

Running this results in the following output:
[0, 1, 2, 0, 3, 4, 0, 5]
[the, doorman, held, door, for, guest]

I left it to you to implement the toString method.


text:
\section{Introduction}

Nowadays most video games are played online and every action by every player is recorded. This generates extremely rich datasets that---with the aid of machine learning techniques---can provide deep insights on user behavior, including accurate predictions of the future actions of each player. Increasingly diverse demographics are now playing games in a highly competitive market. Furthermore, we are clearly in the middle of a paradigm shift, as studios rely more and more in in-app purchases for income. For all these reasons, developing an in-depth knowledge of its players and their motivations is key to the success of any title. In particular, appropriately profiling players in order to meaningfully target them and cater to their needs can prove to be a game changer.

Here we propose to use lifetime, in-game progression (in terms of game level reached), playtime and purchase predictions for individual players---understood as a proxy for their expected engagement---to define meaningful segmentations (groupings of the players).

\begin{figure*}[ht!]
  \centering
  \includegraphics[width=0.33\textwidth]{scs_days.png}\hfill
  \includegraphics[width=0.33\textwidth]{scs_level.png}\hfill
  \includegraphics[width=0.33\textwidth]{scs_playtime.png}
\caption{
Survival curves for all considered players in terms of lifetime (days since first login; left), in-game progression (game level reached; middle) and accumulated playtime (hours played; right). Colors distinguish the various lifespan groups (\emph{short, medium, long} and \emph{loyal}) for the corresponding variable.}
\label{fig:scs}
\end{figure*}

\begin{figure*}[hb!]
  \centering
  \includegraphics[width=0.25\textwidth]{dist_days.png
  \includegraphics[width=0.25\textwidth]{dist_level.png
  \includegraphics[width=0.25\textwidth]{dist_playtime.png
  \includegraphics[width=0.25\textwidth]{dist_ltv.png}
\caption{
Histograms of the predicted (from left to right) lifetime, in-game progression, playtime and LTV. Players are classified as described in the text, with groups shown in different colors. All players except those labeled as \emph{loyal} (for whom the median value of the survival curve does not exist) are shown.}
\label{fig:hist}
\end{figure*}

Player engagement is a complex abstract concept and a formal quantitative definition remains elusive. For the sake of segmentation, where the main goal is typically to pinpoint high-value users, outlay has been traditionally considered as the main variable---in particular in free-to-play games, where in-game purchases often constitute the main source of revenue. Player expenditure is definitely the best way to measure purchase engagement, which is of utmost importance but only tells part of story. Considering additional behavioral information on players can greatly enrich the picture and help attain a classification reflecting not only their economic value, but also markedly different playstyles, skills and interests.

To describe expected engagement we will consider the predicted values of four different variables, namely lifetime (in terms of days after first login), playtime (in hours), in-game progression (in terms of game level attained) and total expenditure or \emph{lifetime value} (LTV, in real or in-game currency). Note that all these variables are general enough to be present in virtually all titles, which makes the method proposed in this work easily generalizable to games of any kind.\looseness=-1

And not only are these variables interesting for classification purposes in themselves, but their combination also provides a deeper understanding of the different types of players in a game. For instance, players with a very rapid in-game progression (who reach a high level after a relatively short playtime, regardless of their lifetime) and low spend might be overlooked by traditional segmentation methods due to their lack of direct economic value; however, these are the most skillful players, and a careful study of their traits and behavior---allowed by our approach---could provide developers with a lot of useful insights.

The use of predictions allow us to appropriately profile players from their very first steps in the game and to consider all available information, including that of players who are no longer in the game---but who can nonetheless help to better understand
the active players and what can be expected of them.\looseness=-1

Our method characterizes each player by means of a collection of survival curves that present the (past and future) probability of remaining in the game after a certain lifetime, playtime or number of levels. These three variables---which we take as indicators of player engagement---are modeled using survival ensembles, as thoroughly described in \cite{perianez2016churn,GameBigData}. Moreover, we also include lifetime value (LTV, the total spend of a player throughout their lifetime in the game) predictions, generated through a deep learning method based on \emph{long short-term memory} (LSTM).
To the best of our knowledge, this is the first work that proposes performing player segmentation using not only historic data, but also predictions of future behavior.

\section{Models used}
\label{sec:models}

\subsection{Conditional inference survival ensembles}
Conditional inference survival ensembles \cite{hothorn2006unbiased} are ensemble learning models with survival \cite{clark} trees as the underlying algorithm. A detailed explanation of this technique, exact settings and performance can be found in \cite{perianez2016churn, GameBigData}.\looseness=-1

\subsection{Long short-term memory models}
Long short-term memory \cite{hochreiter1997long} is a recurrent neural network architecture designed to model temporal sequences and their long-range dependencies. The specific implementation used here consists of two time series---player actions and purchase logs---that are separately introduced in the model using two LSTM layers, whose outputs are concatenated and inputted to a fully connected layer followed by other three fully connected layers. The output of the last layer represents the desired LTV.

\section{Methodology}
\label{sec:method}

Therefore, after running the models, we have each player characterized by three survival curves (days after first login, game level and playtime) and a single value (LTV prediction).

For the three variables modeled through survival ensembles, we profile users by assigning them to one of four groups based on the quartile values of their survival curves and on the relation of these to the average values for the population studied. These groups correspond to \emph{short}, \emph{medium} and \emph{long} lifespans (in any of the variables) and to \emph{loyal} players, namely users who are not in risk of engagement loss according to the model and the available data. Meanwhile, LTV predictions are used to classify players into \emph{high}, \emph{normal} and \emph{low} spending groups. This grouping can be performed in many different ways, which are more or less useful depending on the particular game and the aim of the profiling. Below we describe a simple approach that provides reasonable results (see Section~\ref{sec:results}) and is general enough to be applied to a broad range of games.

For lifetime, playtime and in-game progression, players whose survival probability always remains above 50\% (i.e., for whom the median value of the survival curve does not exist) are labeled as \emph{loyal}. Players are considered to have \emph{long} lifespans if their ``final probability'' is greater than or equal to 25\% and smaller than 50\% (by this we mean that the survival probability eventually falls below 50\% but never drops below 25\%) and their median value is greater than or equal to the population's average. The \emph{medium} lifespan group is comprised by players (i) with final probability between 25\% and 50\% but median value smaller than the population's average; (ii) with final probability below 25\% (but not zero), provided that the value at which the 25\% survival probability is reached is greater than or equal to the population's average; and (iii) with vanishing final probability, provided that their median value is greater than or equal to the average (computed considering just players whose survival probability never reaches zero). The rest are \emph{short}-lived players.

In regard to LTV, all players are considered \emph{medium} spenders except those with expected outlay less than half of the average expected outlay, who are classified as \emph{low} spenders, and those with at least twice the expected average, who are deemed \emph{high} spenders.

\section{Results}
\label{sec:results}

The dataset used in the present work comes from the role-playing, freemium, social game \emph{Age of Ishtaria}, developed by Silicon Studio. Only top spenders (players with accumulated outlay above a certain threshold, computed from the first two months of data
so that around 50\% of all purchases come from players above it) are considered. The data used to train the models covers October 2014 through April 2017 and contains 3265 users. Predictions are then run for the 1771 players who had not churned yet as of May 1, 2017 (by definition, those who had connected at least once in the previous 9 days).

Figure~\ref{fig:scs} displays output survival curves for all players in terms of lifetime, in-game progression and playtime---with colors distinguishing the various groups discussed above---while Figure~\ref{fig:hist} shows histograms for the corresponding median values (when these exist, i.e., for \emph{non-loyal} players) and also for the expected LTV. We can see that the predicted values are distributed differently for each variable: the distribution is more uniform for lifetime, skewed to larger and smaller values for level and playtime, respectively, and almost monotonously decreasing for LTV.

Exploring the relations among the different predicted variables can provide insights into the dynamics of the game. For instance, Figure~\ref{fig:days-playtime-ltv-levelg} compares predicted playtime (in hours) and lifetime (in days) for all players for whom median values exist, i.e., \emph{non-loyal} in both variables. As expected, the spread in playtime increases with lifetime, since periods of inactivity and differences in session lengths among players gain importance as time passes.
The area of each circle is proportional to the predicted LTV and colors represent lifespan groups in terms of game level. Although large LTVs tend to be associated to players with longer lifetimes, there are also some users with low playtime and/or lifetime and relatively large LTV, and players with small predicted outlay can be found across all scales. In regard to the expected in-game progression, there is an obvious correlation with playtime, but with variations reflecting different player skills, as shown e.g.\ by the occurrence of short level lifespans for very large playtime values (corresponding to not so skillful players). Note this kind of analysis can also point very clearly to players with extreme behaviors. For example, in Figure~\ref{fig:days-playtime-ltv-levelg} there is a player with very high expected playtime as compared to their predicted lifetime (nearly 5000 hours of playtime in less than 600 days).

Figure~\ref{fig:playtime-level-days-ltv-groups} further explores the playtime--level relation. Here the area of the circles is again proportional to the predicted LTV and colors represent groups in terms of expected lifetime. Progression through the first levels is clearly quick and easy (as reflected by the steep slope and relatively small spread), while for higher levels the relation between both predictions flattens and the spread becomes larger. This shows it takes longer to go through those levels and highlights the significant impact of player skills on the expected in-game progression.\looseness=-1

\begin{figure}
  \centering

   \includegraphics[width= 0.45\textwidth]{days_playtime_ltv_grouplevel.png}
\caption
Playtime versus lifetime predictions (median survival values) for all players \emph{non-loyal} in both variables. Color represents grouping in terms of predicted game level. The area of the circles is proportional to the expected LTV.\looseness=-1}
\label{fig:days-playtime-ltv-levelg}
\end{figure}

\begin{figure}
\centering%
\includegraphics[width= 0.45\textwidth]{playtimex_levely_ltva_groupdaysc.png}%

\caption{
Game level versus playtime predictions (median survival values) for all players non \emph{loyal} in both variables. Color represents grouping in terms of predicted lifetime. The area of the circles is proportional to the expected LTV.}
\label{fig:playtime-level-days-ltv-groups}
\end{figure}

\begin{figure}
  \centering
  \includegraphics[width= 0.45\textwidth]{ltvx_levely_daysa_groupplaytimec.png}
\caption{
Game level versus LTV predictions for all players \emph{non-loyal} in level. Color represents grouping in terms of predicted playtime. The area of the circles is proportional to the expected lifetime.}
\label{fig:ltv-level-days-playtime-group}
\end{figure}

\begin{figure*}[t!]
  \centering
  \includegraphics[width=0.33\textwidth]{dist_days_skilled.png}\hfill
   \includegraphics[width=0.33\textwidth]{dist_playtime_skilled.png}\hfill
  \includegraphics[width=0.33\textwidth]{dist_ltv_skilled.png}
\caption
Histograms of predicted lifetime (left), playtime (middle) and LTV (right) for players \emph{loyal} with respect to level and \emph{non-loyal} in terms of playtime. Colors represent different groups for the corresponding variable.}
\label{fig:dist_skilled}
\end{figure*}

\begin{figure}
  \centering
  \includegraphics[width= 0.45\textwidth]{skilled_days_playtime_ltv_groupltv.png}
\caption{
Playtime versus lifetime (in days) predicted values for all players \emph{non-loyal} in both variables and \emph{loyal} in terms of level. Color represents grouping in terms of expected LTV and the area of the circles is also proportional to LTV.\looseness=-1}
\label{fig:days-playtime-ltv-ltvg-skilled}
\end{figure}

The relation between the highest level to be reached and the amount of money to be spent is studied in more detail in Figure~\ref{fig:ltv-level-days-playtime-group}, which shows that, while all players with high expected LTV will make significant in-game progression, players with small predicted outlays can do just as good. As we have seen, the correlation with playtime is not perfect either. This could point to the relative fairness of the game: while spending money \emph{might} help with in-game progression (note that the correlation could simply be showing that players who advance further in the game are likely to spend more), the latter has much more to do with the combination of skill and time spent playing.

Profiling users in terms of these variables also allow us to focus on interesting groups of players. For example, players predicted to be \emph{loyal} in terms of in-game progression (whose survival probability remains over 50\% even at high levels) and \emph{non-loyal} in playtime are conceivably the most skillful ones. The histograms of the expected lifetime, playtime and LTV for the 385 players fulfilling these conditions are displayed in Figure~\ref{fig:dist_skilled}. These variables (except for the LTV) show noticeably different patterns for this subset of skillful players as compared to the total population (cf.\ Figure~\ref{fig:hist}): now playtime is more evenly distributed and lifetime skewed to larger values. While it is normal to expect these players to have long lifetimes, interestingly, playtime predictions suggest a number of them will play frequently but for a short time or with many inactive days between sessions. Figure~\ref{fig:days-playtime-ltv-ltvg-skilled} explores the predicted lifetime vs.\ playtime relation for this group of skillful players, with the area and color of the circles related to the expected LTV. It confirms not only the pattern just described, but also the previous discussion about the relative fairness of the game: the distribution of predicted outlays does not vary significantly with respect to the global population and there are many low spending players, spread across all lifetime and playtime values.\looseness=-1

\section{Summary and Conclusion}
\label{sec:conc}

We used individual player predictions of lifetime, game level and playtime (obtained through a conditional inference survival ensembles model) and also LTV (through a LSTM-based deep learning method) to explore a simple user profiling approach, classifying players into broad categories for each of these variables. Moreover, exploring the relations between them has allowed us to analyze behavioral patterns, pinpoint outlier behaviors, draw qualitative conclusions about the game dynamics (e.g.\ about its \emph{fairness}) or focus on certain groups of players of particular interest. This suggests the proposed method constitutes a promising approach to a richer profiling landscape. Future work includes exploring different segmentation strategies, such us focusing only in detecting outliers in any/all of the variables considered, or using unsupervised time series clustering to group survival curves.
\section*{Acknowledgements}

We thank Javier Grande for his careful review of the paper.\looseness=-1

\bibliographystyle{abbrv}

redpajama_set_name: RedPajamaArXiv


text:
Q: i.vi writing null data to output raster on first attempt I have the following lines of code in a bash script I wrote using osgeo's GRASS command line tools:
i.vi viname=ndvi output=$ndvi_fn nir=$nir_fn red=$red_fn --overwrite
while r.info $ndvi_fn -r | grep NULL;do
  echo "Failed to write NDVI file, trying again"
  sleep 2
  i.vi viname=ndvi output=$ndvi_fn nir=$nir_fn red=$red_fn --overwrite
done

This will loop indefinitely. If I stop my script, and rerun it, usually the NDVI band is actually written to the file. Sometimes the third try or more (not always on the second attempt). I can not understand for the life of me why restarting the script makes a difference from sleeping and running it again.
The script will only work if I comment out the while loop, and I rerun the script. I have also tried using g.remove type=raster name=$ndvi_fn -f in the while loop to remove and recreate the file every iteration. no luck.
Has anyone else seen erratic behavior with i.vi? I checked the docs.. but it seems like I'm using it correctly.

A: Please be sure if the computational region been set to the input map(s) prior to the i.vi command.
In your case, just use the variable to pass on the raster map name:
g.region raster=$nir_fn [-p]

redpajama_set_name: RedPajamaStackExchange


text: Q: JS convert date string in ISO 8601 UTC to Date object I have to parse a date string that looks like 20191128T000658Z into a JavaScript Date Object. How can I do this without having to parse the string myself?


Harry Potter And The Cursed Child arrives on the London stage in a spellbinding two-part epic.
Wands at the ready! Harry Potter is back. Premiering at the Palace Theatre in May 2016, Harry Potter And The Cursed Child has dazzled London's theatre world.
Based on a new story by JK Rowling, this magical play by Jack Thorne has something tastier than Bertie Bott's Every Flavour Beans to offer audiences young and old.
In Harry Potter And The Cursed Child, our wizard heroes Harry, Hermione and Ron are now all grown up and faced with a problem more scary than Voldemort: raising children. Set a world away from the dark and creaky corridors of Hogwarts, the boy wizard is now a dad of three and knuckling down to work at the Ministry of Magic.
But will Harry be able to find the right spell to make everything OK with his son Albus?
Jamie Ballard leads the cast as Harry. Susie Trayling and Joe Idris-Roberts complete the Potter family as Ginny and Albus. Thomas Aldridge plays Ron with Rakie Ayola as Hermione and Helen Aluko as their daughter Rose. James Howard takes the role of Draco Malfoy with Jonathan Case as his son Scorpius.
John Tiffany directs this enchanting first outing on stage for JK Rowling's Harry Potter. The eighth story of the epic tale, Harry Potter and the Cursed Child is split into two parts, designed to be seen on the same day (matinee and evening) or on two consecutive evenings.
Book your tickets early, as this production is set to send queues all the way back to platform 9 3/4 and beyond.
Winner of 9 awards at the 2017 Olivier Awards with MasterCard.


text:
Q: Magento 2.4 Error flushing Varnish server. Host: "127.0.0.1". PURGE response code: 405 message: Not Allowed after running upgrade command I enabled varnish cache from admin(magento 2.4), then I ran this command
bin/magento setup:config:set --http-cache-hosts=127.0.0.1

Now I can't run the upgrade script. I'm getting this error:
Error flushing Varnish server. Host: "127.0.0.1". PURGE response code: 405 message: Not Allowed
Server: nginx/1.18.0 (Ubuntu)

I have not changed anything in /etc/varnish/default.vcl and in /etc/default/varnish
Any kind of help would be appreciated

A: The problem is related to the purging ACL in your VCL file. Apparently the client IP doesn't match any IP address in the ACL.
This somewhat makes sense, because Varnish doesn't receive the actual client IP address, because Nginx is jammed in between as a TLS proxy.
Please share your full VCL file, including the purging ACL.
Potential solutions

*

*Modify the VCL to use the value of the X-Forwarded-For header instead of client.ip

*Add the port of Varnish server to the IP address of your --http-cache-hosts parameter.

The 2nd solution is probably the easiest one because it doesn't require a lot of effort. If Varnish runs on port 6081 for example, your config command could look like this:
bin/magento setup:config:set --http-cache-hosts=127.0.0.1:6081

This will ensure that Varnish receives the purges directly, rather than through ports 80 or 8080 that are configured by Nginx.
See https://devdocs.magento.com/guides/v2.4/config-guide/varnish/use-varnish-cache.html for more information.


text:
HomeHealth & Medicine
Shoreline Recovery Center Looking to Serve the Community
Shoreline Recovery Center and sister center Park Mental Health collect donations for food drive partnership with San Diego Food Bank
SAN DIEGO - November 16, 2022 - (Newswire.com)
Shoreline Recovery Center and its sister site Park Mental Health are more than facilities that only offer addiction recovery services. They are devoted to the development of purpose. That's why as part of its mission to give back to the community it serves, Shoreline Recovery Center is partnering with the San Diego Food Bank by having a holiday food drive this season.
"Part of any good recovery program are their acts of service and being of service," said Shoreline's Executive Director Kate Judd. "This is one way to encourage our clients to give back during the holidays while creating important connections within the community."
The food drive for the San Diego Food Bank begins on Nov. 22 and runs through Dec. 17. While it's closed to the public in order to protect client confidentiality, nonperishable donations are being accepted internally from family, friends and staff members.
The core values of Shoreline are embedded in its curriculum and include the development of purpose, self-compassion, responsibility, resilience and community. These values are instilled in clients throughout a minimum six-month plan that begins with an intentional connection with experts and moves through a strategic plan to implement and then transition out of the facility with goals to achieve sober, independent living.
A safe haven for individuals in crisis, Shoreline Recovery Center lays the foundation for hope and resilience through programs that give them the foundational tools they need in order to become better fathers, partners and functioning, contributing citizens. Upon graduation, these self-actualized men learn how to reacclimate into their communities, and in some cases, go into business for themselves and many of them end up working in the recovery industry.
Reaching sobriety after struggling with addiction or substance use disorder is a significant accomplishment and getting patients actively involved in things bigger than themselves is a critical part of their overall recovery. Shoreline Recovery Center's aftercare programs are designed to help the patients maximize everything that was learned to maintain the newer healthy and sober lifestyle.
"The clients we work with come to us as individuals who would otherwise create less than favorable outcomes for themselves and their community," said Executive Director Kate Judd. "In the last five years, there's definitely been a ripple effect with the majority of guys that have advanced through our program."
Craig Burson, Kate Judd and Robert Wilson founded the company five years ago to create treatment programs that blend evidence-based therapies, clinical best practices as well as expand job skills and training.
"Each of us are in recovery and began working in the addiction and recovery field because we wanted to contribute to others facing similar struggles," Judd said. "We teach people how to take care of themselves so they can ultimately help others."
For more information, visit: www.shorelinerecoverycenter.com and www.mentalhealthtreatmentsandiego.com
Steven Esparza
Craig Burson
Original Source: Shoreline Recovery Center Looking to Serve the Community
University of Virginia- Darden School of Business, Boston University, University of Regina Release Research: News From Artificial Intelligence is Believed Less
Deepika Padukone's 82°E Introduces Moisturiser and Sunscreen as the Launch Products
ZetrOZ Systems to Showcase New Soft Tissue Healing Innovations sam®x1 and sam®2.0 Technologies at Regenerative and Musculoskeletal Ultrasound Course
Criterium, Inc. Announces Formation of New Oncology Research Consortium for Genito-Urinary Indications

redpajama_set_name: RedPajamaCommonCrawl


Designed and crafted in Athens, Greece by notable Greek designer THIROS, the Cappuccino Clutch is fashioned from soft, genuine Greek leather in rich coffee tones. Simple yet sophisticated, it's pairs perfectly with denim skinnies and those sandals you'll be styling all summer long. And did we mention it can accommodate all the essentials? Smartphone, coin purse, lipstick... you're covered!


text:
Q: Error in cookie law info plugin for Wordpress I've got a problem with one of my plugins.
The log files said:

PHP Warning: stripslashes() expects parameter 1 to be string, array given in /mnt/web008/c1/24/57250724/htdocs/WordPress_01/wp-content/plugins/cookie-law-info/php/shortcodes.php on line 125

It looks like that there is an aray given but a string expected? I dont know how i can fix this.
/** Returns HTML for a standard (green, medium sized) 'Accept' button */
function cookielawinfo_shortcode_accept_button( $atts ) {
    extract( shortcode_atts( array(
        'colour' => 'green'
    ), $atts ) );

    // Fixing button translate text bug
    // 18/05/2015 by RA
    $defaults = array(
        'button_1_text' => ''
    );
    $settings = wp_parse_args( cookielawinfo_get_admin_settings(), $defaults );

    /*This is line 125:*/ return '' . stripslashes( $settings ) . '';
}

A: Well, the error itself is pretty self explanatory.
The function stripslashes expects its parameter to be a string. A quick look at the Wordpress documentation suggests that the return value of wp_parse_args is an array, meaning the $settings variable is an array not a string and therefore passing it as an argument in stripslashes causes your error.
You can use stripslashes on an array, however, it requires a little bit more work. Here's the example given in the PHP documentation.
<?php
function stripslashes_deep($value) {
    $value = is_array($value) ?
               array_map('stripslashes_deep', $value) :
               stripslashes($value);

    return $value;
}

// Example
$array = array("f\\'oo", "b\\'ar", array("fo\\'o", "b\\'ar"));
$array = stripslashes_deep($array);

// Output
print_r($array);
?>

https://developer.wordpress.org/reference/functions/wp_parse_args/
http://php.net/manual/en/function.stripslashes.php
EDIT: It's probably worth noting that stripslashes_deep will return an array. If this is not the desired output then wrap the call the stripslashes_deep function via the implode function to convert it to a string.
implode(stripslashes_deep($settings))


Executive, author, speaker, and creator of of the RapidStartPMO approach.
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Our corporate website that contains information about the company services in consulting and training as well as whitepapers on a range of topics.
A range of easy to use templates that are designed to enable project management practitioners to quickly get started in planning and managing their projects.
If you have any questions or would like to learn more about our services please be sure to reach out to us.


text:
Côte d'Ivoire National Team and Professional Football Player
Abdel-Kader Keïta
Date of Birth: Aug/6/1981
Place of Origin: Cote d'Ivoire
Abdel-Kader Keïta is an Ivorian professional football player. Keïta plays as a winger for Professional Football Player in the Turkish Super League and the Cote d'Ivoire national football team.
He is a versatile player who can also play on the right and left wings in, which is where he was positioned while playing for Lille before signing for Lyon.
Like the Touré brothers, the Kalou brothers, and the Koné brothers, Keita is also part of a footballing family. He has an older brother called Fadel Keïta, who is a former Côte d'Ivoire international.
Keïta, also known as 'Popito', began his career at homeland club Africa Sports, before moving on to Tunisian Club Etoile du Sahel. Following spells in United Arab Emirates with Al Ain and Qatar with Al Sadd, he moved to France with Ligue 1 club OSC Lille in 2005.
On May 31, 2007, Lyon chairman Jean-Michel Aulas revealed that the club had made bids for both Keïta and his fellow club-mate Mathieu Bodmer.
On June 14, 2007, Lyon officially announced that they would be unveiling Keïta and Bodmer to the media, the pair having already passed their medicals at the Stade Gerland. On June 16, 2007, Lyon confirmed the signing of Keïta from Lille for 18.5 million euro. Keïta was given the number 9 shirt.But due to the jersey change of Brazilian striker, Fred, from 11 to 9, Abdul has changed to number 32. But again he changed to number 23 after the departure of Jérémy Berthod.
On 2 July 2009, Galatasaray officially announced that Keïta joined the Turkish club and signed a three year contract. He scored his first goal for Galatasaray in a qualification match for UEFA Europa cup against Macabbi Netenya in the 5th minute. On December 12, Keïta scored for Galatasaray in a 3-2 victory over Antalyaspor.
On 18 February 2010 Keita scored a late equalizer to secure a 1-1 away draw for Galatasaray against Atletico Madrid in the Europa Cup. Later, in the second leg he equalized again to make it 1-1, but Galatasaray failed to qualify. On February 28 Keita scored the second and fourth goals in a 4-1 victory over Kasimpasa. His first goal was a magnificent volley from just inside the penalty area.
In Galatasaray's 3-0 victory over Ankaragucu in March, Keita scored the second goal as well as assisting the final goal. On 11 April 2010 Keita assisted two of Milan Baros' goals in a 4-1 victory over Diyarbakirspor. A week later Keita scored the first goal in a 1-2 victory over
Mohamed Lamine Zemmamouche
Algeria, Soccer
Anthony Annan
Ghana, Soccer
Adlène Guedioura
Aaron Mokoena
Soccer, South Africa
Rowen Fernandez


text:
Dean of Students Home
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Free Speech At Boise State
Complainant Information
Any member of the University community may file charges against any student for an alleged violation of the Student Code of Conduct. If you are reporting a student for an alleged violation, you may be asked to act as the complainant for the incident. Submit a potential Student Code of Conduct violation.
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Respondent Information
Parent and Family Conduct Information
University Conduct Body
Jump To Section Conduct Report Form Conference/Hearing Process, Rights & Responsibilities Support Resources
Conduct Report Form
Conference/Hearing Process, Rights & Responsibilities
Please fill out the form below and provide a description of the incident in question which you feel may be a violation of the Student Code of Conduct. Include all relevant information such as names, dates, time, places, evidence, etc. Be as thorough as possible. Please refer to Section 6: Non-Academic Misconduct Complaints and Procedures in the Student Code of Conduct for a full description of your rights and responsibilities in the conduct process or visit with the Associate Dean of Students if you have any questions.
Important Note: Upon review of the Complainant(s) statement, the University reserves the right to identify the sections of the Student Code of Conduct (and/or any University policy) that may have been violated based solely off of the written report. Please keep in mind that a completed Conduct Report Form, in and of itself, does not necessarily infer that a violation has occurred.
Go to Conduct Report Form
What happens after I submit the allegation(s)?
The assigned hearing officer will determine whether or not the allegations constitute a potential violation of the Student Code of Conduct. If it is determined that a violation of the Student Code of Conduct has occurred, the assigned hearing officer will meet with the respondent to discuss the allegations. If the incident is being handled administratively, an outcome will be sent via email within 10 business days of the Administrative Conference with the respondent. As the complainant in the situation, you will also receive notification of the outcome.
An administrative hearing decision may be appealed but another hearing will not be conducted unless the Appeal Board provides direction to do so. If you would like to appeal the decision, appeals must be submitted within ten (10) University business days of the date printed on the decision notification.
Learn more about how to file an Appeal
Please note that Boise State strictly prohibits retaliation against any individual for their participation in the Student Conduct Process as a complainant, respondent or witness. If you feel you are experiencing retaliation, report it to your Hearing Officer or Student Conduct Administrator immediately. If you are in immediate physical danger, please call 9-1-1.
We encourage you to reach out to support resources as needed. Here is a great list of campus resources that are able to assist with emotional and mental health, academic guidance, and general support.
The Office of Institutional Compliance & Ethics oversees allegations involving discrimination on the basis of sex. If you are/have been subject to sexual harassment and/or sexual assault such as: dating violence, domestic violence, and "bullying" on the basis of sex, gender, or gender stereotypes, please reach out to the Office of Institutional Compliance & Ethics at (208) 426-1258 to file a report.
The Gender Equity Center offers support for people of all gender identities and can assist complainants in need of resources beyond those offered by the Conduct Process. If you are in need of support and would like to meet with a staff member from The Gender Equity Center, please call (208) 426-4259 or email genderequity@boisestate.edu
deanofstudents@boisestate.edu
Campus School, Ste. 120


Are you property renter? Would you like to have an electronic payment system to collect your rent bill payments online? If that is so, Rentpayment.com will be a useful website for you to visit. Rent Payment is company offering tons of electronic payment solutions you can use to collect rent bill payments online.
On this site, people who rent can pay their rent bills online using the site's electronic payment systems. Besides, on Rentpayment.com you will find a catalog of online payment solutions for renters including online credit card payment systems, systems to pay rent bills with e-checks and property management softwares among other.
Would you like to pay your rent bills with e-checks and credit cards? Are you looking for online payment solutions to make online credit card payments of your rent from home? If that is your case, Rentpayment.com might be the solution you have been looking for.


American author John Green (John Michael Green), is not only a novelist but a vlogger in YouTube, creates online educational videos and a historian as well. This novelist whose birthplace is in Indianapolis wanted to be an Episcopalian minister. But fate had him in a different direction. Green graduated at the Kenyon College, with a degree of "double major in English and Religious studies". Later on, he was inspired by his experience as he worked with in a children hospital being a chaplain, hence, the birth of his novels.
Below, we have gathered some of his creations for you book lovers out there.
1. An Abundance of Catherines: Tells about the story of Colin Singleton, a high school graduate, who seems to be of ill-fate being dumped by numerous Katherines. The male protagonist then quests to prove his Theorem of Underlying Katherine Predictability with his friend Judge Judy.
2.Looking for Alaska. This fiction novel has been awarded several times such as Winner of the Michael L. Printz Award and a finalist of Los Angeles Times Book Prize. Published in 2005, this work became a New York Times bestseller.
3. Paper Towns. Now, soon to be on the big screen this summer 2015, starring model-actress-singer Cara Delevingne and Nat Wolff, this book takes you to the heights of teen years, quenching curiosity and understanding love.
4. Let It Snow: Three Holiday Romances. John Green along with two other equally distinct authors, Lauren Myracle and Maureen Johnson present you with this wonderful creation for the winter season.
5. The Fault in Our Stars. Having been adapted into cinemas last 2014 starred by Shailene Woodley and Ansel Elgort, this book hadn't lost its shine.
Want more of John Green's creation? Here is a Box Set especially for you!
Next article Gotta Love Anne Curtis!


The Syrian Army said on Sunday it had repulsed a major offensive by IS militants in the northeastern city of Hasaka and drove out gunmen who had taken over key installations on the southern edge of the city.
The northeastern corner of Syria is strategically important because it links areas controlled by the extremist group, World Bulletin reported.
The group, approaching from their stronghold the city of Shadadi, further south of Hasaka, made lighting advances this week after conducting around a dozen suicide attacks using explosives-laden trucks on army checkpoints in the city.
But Syrian state television, quoting an army source, said in a newsflash they had taken back an electricity station, a juvenile prison and two villages almost 2 km south of the city that had been occupied by gunmen.
The Kurds, whose militia YPG receives air support from a US-led alliance bombing IS, had been helping government forces to repel last week's attack, according to the Syrian Observatory for Human Rights.
The observatory, which tracks violence across the country, said at least 71 army and loyalist militias were killed in the weeklong battles with IS.


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Beard, Winkel Experience the Dedication of the HR Recruiting Team
The Department of Human Services (DHS) strives to improve the lives of Arkansans by offering a variety of programs.
Ryan Winkel and Cecile Beard are both part of the DHS mission. Winkel is a human resources recruiter. Beard is a Division of Child Care and Early Childhood Education program eligibility specialist.
Something else Winkel and Beard have in common is they found their jobs due mostly from getting DHS information at an employment fair.
Winkel, a graduate of the University of Central Arkansas (UCA), approached DHS staff while attending a fair at the school. Beard, a Navy veteran and a UCA alum, learned about DHS employment opportunities through social media and a community job fair.
"After my time in the military, I wanted a government job because of the benefits and the opportunity to continue serving people," Beard said. "Before meeting staff at the fair, I found several openings on the DHS jobs site that caught my attention. But speaking to DHS recruiters at the fair was absolutely worth my time."
They kept talking to Beard, well after the fair.
"I constantly received advice from the DHS HR staff," she said. "It helped having a reliable recruiter encourage me to stay on the lookout for DHS openings."
Winkel also sought a state job.
"I wanted to work for the government, specifically in recruiting, as I enjoy making a positive impact in people's lives," he said. "That's why I got DHS jobs information. I'm glad they were at the UCA recruitment fair."
Winkel didn't expect what happened after his visit to the DHS recruiting booth.
"I was surprised at how quick the recruiters called me," he said. "While at the fair, I spoke a lot to the former head of HR recruiting. Four days later, I got an e-mail asking me to give him a call."
HR recruiters attend job fairs with the goal of finding qualified people to fill DHS job openings. Of course, that task hits close to home for Winkel.
"I always put myself in the job candidate's shoes, remembering when I was in their exact situation," he said.


text:
Q: How to combine a GPS and SMS app? I am attempting to create an app that acts passivly in the background. What I want it to do is keep track of the speed (interchangeable between MPH and KmPH based on the user's wishes) passively. When a text message comes to the device, I want it to check the speed and if it's below the user defined threshhold, I want it to send the SMS to the default app. If over the threshhold, I want it to send an automatic message back to the sender.
Currently I have 2 activites because I cannot extend both Activity and BroadcastReceiver.
My first question is.. how to I keep track of the speed passively...
My second question is.. how do I pass the speed to the SMS activity when a SMS is received?
Here is my GPSActivity
package biz.midl.drivereply;

import android.app.Activity;
import android.content.Context;
import android.content.Intent;
import android.location.Location;
import android.location.LocationListener;
import android.location.LocationManager;
import android.os.Bundle;
import android.view.Menu;
import android.widget.TextView;

public class MainActivity extends Activity implements LocationListener {
    String lsms;
    String prefName = "chaosgpsreply";

    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.main);
        LocationManager lm = (LocationManager) this.getSystemService(Context.LOCATION_SERVICE);
        lm.requestLocationUpdates(LocationManager.GPS_PROVIDER, 0, 0, this);

        this.onLocationChanged(null);

    }

    @Override
    public boolean onCreateOptionsMenu(Menu menu) {
        // Inflate the menu; this adds items to the action bar if it is present.
        getMenuInflater().inflate(R.menu.main, menu);
        return true;
    }

    @Override
    public void onLocationChanged(Location location) {
        TextView tv = (TextView) findViewById(R.id.textView1);

        if (location==null)
        {
            tv.setText("-.- m/s");
        }
        else
        {
            float nCurrentSpeed = location.getSpeed();
            tv.setText("" + nCurrentSpeed + " m/s");
        }
    }

    @Override
    public void onProviderDisabled(String provider) {
        // TODO Auto-generated method stub

    }

    @Override
    public void onProviderEnabled(String provider) {
        // TODO Auto-generated method stub

    }

    @Override
    public void onStatusChanged(String provider, int status, Bundle extras) {
        // TODO Auto-generated method stub

    }

}

Here is my SMSActivity
package biz.midl.drivereply;

import java.util.Timer;
import java.util.TimerTask;

import android.content.BroadcastReceiver;
import android.content.Context;
import android.content.Intent;
import android.telephony.SmsManager;

public class SMSportion extends BroadcastReceiver {
    String lsms;
    String prefName = "chaosgpsreply";
    static Timer timer1 = new Timer();
    static long delay = 30000;
    static TimerTask tt1;

        @Override
        public void onReceive(Context context, Intent intent) {
            String phoneNumber=null, messageText=null;
            String textMessage = "I can't come to the phone right now, be back soon";
            //---gather up all the necessary user input---
            SmsManager sms = SmsManager.getDefault();
            try
            {
                sms.sendTextMessage(phoneNumber, null, messageText, null, null);
            }
            catch(IllegalArgumentException e)
            {

            }

            //timer();   //this will be integrated in later - ignore this
            sendSMS(phoneNumber, textMessage);

        }

        public void sendSMS(String phoneNumber, String message)
        {
            SmsManager sms = SmsManager.getDefault();
            sms.sendTextMessage(phoneNumber, null, message, null, null);
        }
}


text:
Běla kan syfta på följande platser:

Bulgarien

 Bjala (ort), Varna, Obsjtina Bjala,

Tjeckien

 Rohovládova Bělá, ort, Pardubice,

Robotskapade Bulgarienförgreningar
Robotskapade Tjeckienförgreningar

redpajama_set_name: RedPajamaWikipedia


Your kids love magic? Here's the perfect chance to catch a great show and benefit a good cause at the same time.
On Saturday November 24, Webster Parks and Recreation will host a magic show with Rich the Magic Man to benefit Rochester Challenger Miracle Field.
The show will begin at 1 p.m., but come early for balloon animals and temporary tattoos. Other highlights of the afternoon include raffles, an auction, and a special appearance from Santa. Pizza and soda will be available for purchase.
Tickets are $10 for adults and $5 for children. For more information and to register, click here.
One more fun thing I want to add today: this photo from yesterday's Barry Bowl, an annual touch football game hosted by Danny and Jessica Barry, owners of Barry's Irish Pub in the the village.
I think this is the third year the Barrys have organized the game, but the first time it was held at their farmhouse out in Hilton. As you can see, about a dozen pub staff members, family members and friends joined the snowy, cold fun. Jess made chili, there was a bonfire and lots of trash talk. And despite the slippery conditions, I'm pleased to report there were not serious injuries.
But I am reallllllly sore today.


text:
Q: CSS Basic Layout - 3 divs + 1 div inside another, centered I got a problem that i just can't get my head around.
I want three different divs, filling the whole page (no scrollbars) and the middle div with another div centered horizontally and vertically inside of it.
I tried so much, but something is always destroying the layout.
So far, this is my code:
html, body {
background-image: url(images/bg_tile.gif);
background-repeat: repeat;
margin: 0;
padding: 0;
resize:none;
width: 100%;
height: 100%;
}

#header {
width: 100%;
height: 14%;
background-color: #09F;
top: 0px;
}

#body_con {
width: 100%;
height: 80%;
background-color: #0CF;
}

#footer {
width: 100%;
height: 6%;
background-color: #09F;
bottom: 0px;
}

#body_image {
width: 90%;
height: 90%;
margin:0px auto;
background-color: white;
}

I know, somehow it's possible but i just can't get it to work.
Any ideas ?
EDIT: http://jsfiddle.net/w774g/
Thank you,
Leo

A: You can set the positions of the edges of an absolutely positioned div, like this:
http://jsfiddle.net/w774g/1/
#header {
    position: absolute;
    width: 100%;
    top: 0;
    bottom: 86%;
    background-color: #09F;
}

#body_con {
    position: absolute;
    width: 100%;
    top: 14%;
    bottom: 6%;
    background-color: #0CF;
}

#footer {
    position: absolute;
    width: 100%;
    top: 94%;
    bottom: 0;
    background-color: #09F;
}

#body_image {
    position: absolute;
    top: 5%;
    bottom: 5%;
    left: 5%;
    right: 5%;
    background: black;
}

A: Try this:
#body_con {
    width: 100%;
    height: 80%;
    background-color: #0CF;
    /* added */
    position: relative;
}
#body_image {
    width: 90%;
    height: 90%;
    margin:0px auto;
    background-color: white;
    /* added */
    position: absolute;
    transform: translate(-50%, -50%);
    -webkit-transform: translate(-50%, -50%);
    -moz-transform: translate(-50%, -50%);
    -o-transform: translate(-50%, -50%);
    top: 50%;
    left: 50%;
}

Working Fiddle


In order to make compliance with the new TRID requirements regarding agent license numbers on the new financial disclosure forms easier, the Commission is now including license numbers on the information provided on our website for individual licensee searches. Click on the "Licensee & Applicant Information Search" on the left side of the Commission homepage to access the licensee search function. The license numbers are displayed on the lower right of on the individual licensee information pages.
The TRID requirements from the Consumer Finance Protection Bureau regarding the paperwork required for closing most consumer credit transactions secured by real property, such as a traditional residential mortgage require real estate licensees acting as agents in the transaction to provide their individual salesperson's or broker's license number. In the past we have generally advised licensees to keep their license numbers private, however, they will need to provide them to the lending institutions under the new law. The forms also ask for a "State License ID". This has been interpreted or referred to shorthand as a company ID or broker ID or license number. The Commission does not issue a "State License ID" to brokerage companies, and some lenders do not ask for it on the form. However some lenders do request a company or broker ID, in those instances the designated broker's individual license number should be provided. The designated broker's license number is also available on our website through the individual licensee search function.


text:
Q: Does a webpage load images slower if there are multiple sources? Scenario 1: I post pictures on my Facebook profile and create a webpage that has image SRCs linking to the Facebook profile
Scenario 2: I link my SRCs to images from Google searches. This means multiple sources for my images.
Is scenario 1 faster than scenario 2 since it's pulling from one page, or are they the same because each image SRC is a request that takes time to process depending on the source?


text:
Sotheby's 'Banksy-ed' as painting 'self-destructs' live at auction
Girl with a Balloon (2006) had just hammered at £860,000
Anny Shaw
Banksy's Girl With Balloon (2006) mysteriously self-destructed at the end of a Sotheby's auction Casterline Goodman Gallery / Instagram
Was Banksy at the evening sale at Sotheby's on Friday night? That was the question on everyone's lips when one of the Bristolian street artist's paintings mysteriously self-destructed as the contemporary auction drew to a close.
Girl with a Balloon (2006) was the final lot of the night, and just as the canvas hammered at £860,000, or £1.04m with fees—just above his auction record in pounds achieved in 2008—an alarm was triggered inside the work of art. Onlookers turned just in time to see the canvas slip through its faux-gilt frame and be shredded into pieces.
"It appears we just got Banksy-ed," said Alex Branczik, the auction house's head of contemporary art, Europe, immediately after the sale. "He is arguably the greatest British street artist, and tonight we saw a little piece of Banksy genius," he said, adding that he was "not in on the ruse", although it is not clear whether other members of staff were. Some commented on the unusually thick frame, which could have easily concealed a shredding mechanism.
After a man dressed in black sporting sunglasses and a hat was seen scuffling with security guards near the entrance to Sotheby's shortly after the incident, speculation mounted that the elusive artist had himself pressed the button that destroyed the work. According to the provenance, Girl with a Balloon was acquired directly from the artist in 2006.
"We are busy figuring out what this means in an auction context," Branczik said. "The shredding is now part of the integral art work. We have not experienced a situation where a painting has spontaneously shredded, upon achieving a record for the artist."
One potential outcome, according to a spokeswoman, is that the destroyed painting could be preserved as a document of the guerrilla tactic. "You could argue that the work is now more valuable," Branczik said. "It's certainly the first piece to be spontaneously shredded as an auction ends."
More NewsTopicsAuctionsSotheby'sBanksyFrieze London 2018
Flipping the Bacon: Sotheby's £69m post-war and contemporary sale lacks fizz
Female painters steal the limelight at Phillips contemporary evening sale in London
Sofa King's collection plumps up Sotheby's Old Master sale—helped by a suite of guarantees
Fresh talent breathes life into slim £45m postwar and contemporary evening sale at Christie's London
Mini Impressionist and Modern sale at Sotheby's makes £99m thanks to auction debutantes


text:
Curious Properties
Monday, September 11, 2017, By News Staff
College of Arts and SciencesfacultyresearchSTEM
Editor's Note: The following piece was prepared for the Kavli Institute for Theoretical Physics (KITP) at the University of California, Santa Barbara. The article highlights three members of Syracuse's Department of Physics: Mark Bowick, the Joel Dorman Steele Professor of Physics, as well as a visiting scientist and deputy director at KITP; Cristina Marchetti, the William R. Kenan Distinguished Professor of Physics and a KITP general member; and Suraj Shankar, a Ph.D. student and KITP Graduate Fellow.
A murmuration of starlings. The phrase reads like something from literature or the title of an arthouse film. In fact, it is meant to describe the phenomenon that results when hundreds, sometimes thousands, of these birds fly in swooping, intricately coordinated patterns through the sky.
Or in more technical terms, flocking.
Mark Bowick (Photo by Sonia Fernandez)
But birds are not the only creatures that flock. Such behavior also takes place on a microscopic scale, such as when bacteria roam the folds of the gut. Yet bird or bacteria, all flocking has one prerequisite: The form of the entity must be elongated with a "head" and "tail" to align and move with neighbors in an ordered state.
Physicists study flocking to better understand dynamic organization at various scales, often as a way to expand their knowledge of the rapidly developing field of active matter. Case in point is a new analysis by a group of theoretical physicists, including Mark Bowick, deputy director of UC Santa Barbara's Kavli Institute for Theoretical Physics (KITP).
Generalizing the standard model of flocking motion to the curved surface of a sphere rather than the usual linear plane or flat three-dimensional space, Bowick's team found that instead of spreading out uniformly over the whole sphere, arrowlike agents spontaneously order into circular bands centered on the equator. The team's findings appear in the journal Physical Review X.
"Whether it's bacteria swarming, cells roaming or energy-consuming 'arrows' flying, these systems share universal characteristics independent of the precise size and structure of the agents as well as their detailed interactions," said corresponding author Bowick, who is on leave from Syracuse University while in his role at KITP. "The ordered states of these systems are never perfectly uniform, so fluctuations in density generate sound, much in the same way that wind instruments create music."
On curved surfaces, the team, which includes KITP general member [and Syracuse's Kenan Distinguished Professor of Physics] Cristina Marchetti and KITP graduate fellow Suraj Shankar, found "special" sound modes that don't dissipate and flow around obstacles. According to Bowick, these special modes correspond to special harmonics or tones that don't mix with all the other harmonics.
He also noted that these modes are special precisely because the band geometry of the equator is very different from the planar geometry of a flat surface. For example, a particle moving on a ring comes back to its starting point even though it moves along a "straight" path. This doesn't happen on a plane, where entities continue forever in a straight line, never to return, unless they encounter an edge. This feature is a direct consequence of the very different topology of the sphere and the plane.
Steady flocks on a sphere and a catenoid. (Courtesy of Suraj Shankar)
"Even though a sphere itself has no edge, the swarming patterns have an edge—the edge of the band," Bowick said. "So simply by locally consuming energy, active agents on the sphere spontaneously swarm and create an edge."
The authors also analyzed another curved shape, an hourglass-shaped figure called a catenoid. Unlike a sphere on which parallel lines converge, the catenoid's concave curvature causes parallels to diverge. This opposite curvature pushes the flocking entities and associated sound waves to the top and bottom edges of the hourglass, leaving the middle bare—the opposite of what happens on a sphere.
"Just the fact that these systems flock is pretty remarkable because they dynamically generate motion," said Shankar, a doctoral student in the soft matter program in Syracuse University's physics department. "But they are far richer systems than we expected because they also generate these 'topologically protected' sound modes."
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A key process during the development of an embryo is tissue morphogenesis, where the number of cells in an organism increase through cell division and tissues begins to take shape. Heidi Hehnly, assistant professor of biology, has been awarded a…
The Role of Digital Forensics and Tracking Down US Capitol Riot Criminals
With just under a week left before President-elect Joe Biden's inauguration ceremony, investigators and law enforcement agencies across the country are working speedily to identify as many of the Jan. 6 U.S. Capitol riot offenders as they can. Knowing exactly…
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Professor Shikha Nangia Selected as Associate Editor for ACS Applied Bio Materials Journal
Biomedical and chemical engineering Professor Shikha Nangia was selected as the associate editor for the ACS Applied Bio Materials journal. ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond…


A definite improvement on the results in my last post, I'm sure you'll agree.
that said, even though progress is being made, my recently-amended, search engine-friendly twitter profile still hasn't been updated on google and my blog is nowhere to be seen!
I think a little more time is in order before I get me one of those global domains and start looking to generate more links in.


text:
Jussie Smollett reveals how he made his Langston Hughes role in Marshall a full biopic
October 13th, 2017 by KRNB
John Shearer/Getty Images via ABC
Jussie Smollett stars as the prolific poet and activist Langston Hughes in the Thurgood Marshall biopic, Marshall. While the Empire star says he only has a "small cameo," in the film, Smollett says the opportunity to portray Hughes was welcomed — but definitely unexpected.
"I was doing the Image Awards and I was singing a tribute to John Legend and Reggie [Hudlin] came up to me and said, 'Listen.. we're doing the Thurgood Marshall with Chadwick Boseman and Josh Gad and Sterling Brown and all of these amazing… Kate Hudson.. amazing actors,'" Smollett tells ABC Radio. "And he said, 'I'd love it if you'd come play Langston Hughes.'"
After he got over the initial shock of the film's director asking him to play one of his icons, the actor says he quickly realized the bigger opportunity in taking the smaller part.
"I told him I would do it on one condition," Smollett explains. "He said, 'What?' I said, 'Within three to four years we're doing the full Langston Hughes story. And he said, 'Done.' So I went on and did it and had an amazing time."
Smollett continues: "And the night before I went up to Buffalo to film it, I went and sat in front of Hughes house in Harlem and I've been able to go in now and visit and walk around and feel it and it's just incredible. I LOVE Langston Hughes."
Marshall hits theaters today.
Copyright © 2017, ABC Radio. All rights reserved.
Biopic Hughes jussie Langston Marshall reveals Smollett
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Fifth Avenue New York, home to one of the worlds most famous 'big brand' jewellers. Our take on the Tiffany inspired classic six claw coronet setting has a more rounded ( and we believe a more comfortable) shank. Available in platinum and 18ct gold.


A look at some of the best images from Spain's 2-2 draw against Morocco in World Cup 2018.
Spain will face hosts Russia in the last 16 of the World Cup after finishing top of Group B following a dramatic 2-2 draw with already-eliminated Morocco in Kaliningrad.
Spain, 2-1 down thanks to Morocco substitute Youssef En-Nesyri's 81st minute header, were set to finish second and therefore take on Uruguay in the next round.
Their substitute Iago Aspas then flicked the ball into the net in the dying seconds and saw that the flag was up for offside – but the goal was subsequently given following a VAR review.
Spain had gone 1-0 down in the 14th minute when Khalid Boutaib punished a mix-up between Andres Iniesta and Sergio Ramos, before drawing level five minutes later through Isco's strike.
While Fernando Hierro's side – who survived a scare 10 minutes after the break as Nordin Amrabat's strike hit the woodwork – snatched a point, Portugal were held to a 1-1 draw by Iran thanks to a late goal by their opponents.
It leaves Spain and Portugal level on five points each in first and second place, with goals scored putting the former ahead, and the latter set to face Group A winners Uruguay in the next round.
Here, we take a look at some of the best images from the game!


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The Wishy-Washy, Squishy-Squashy Pseudoscience of Electability
By Jason Zengerle
Once upon a time, about, oh, ten months ago, the political class was dead certain of two things: Hillary Clinton and Rudy Giuliani were pretty close to unelectable. Hillary's case was the more obvious of the two. Although she was clearly the Democratic front-runner, political pros doubted whether such a polarizing politician, one who was viewed unfavorably by nearly half of all Americans surveyed, could convince Democratic primary voters that she gave their party the best shot to win back the White House. As the Washington Post editorialized on the occasion of her formal entry into the race, "The question about Hillary Clinton may be not so much whether a woman can win the presidency but whether this woman can."
Rudy faced similar questions. It was widely assumed that his moderate views on abortion and guns would help him in a general election. But students of political history—and New York political history in particular—were dubious about how his act would play in Poughkeepsie, much less Peoria. After all, it's an iron rule of politics that the New York City's mayor's office is a "tomb for the politically ambitious," which is why even popular mayors (La Guardia) and presidential-looking mayors (Lindsay) never managed to ascend to higher office. And while many Americans may consider Giuliani "America's Mayor" because of his 9/11 performance, New Yorkers had lived under the real, pre-9/11 Rudy—and had no doubt that over the course of a long campaign, the rest of America would come to know that Rudy, too. As an article in National Review Online put it, Giuliani "will probably suffer in a general election campaign from the fact that there is so much evidence in the public record that he is a total jerk."
So it must have come as something of a shock to the political professionals to pick up the New York Times in mid-November and find a front-page story about a couple of polls of Iowa and New Hampshire voters. Headlined "Polls Find Voters Weighing Issues vs. Electability," the article reaffirmed the conventional wisdom that electability will heavily influence primary and caucus voters. But the shock came when these voters considered who is the most electable: 47 percent of Iowa Democrats and 68 percent of New Hampshire Democrats named Clinton, and a plurality of Republicans in both states gave the nod to Giuliani. In less than a year, the two candidates had managed to turn what was thought to be their Achilles' heel into one of their greatest strengths.
Which just goes to show how squishy and even bankrupt "electability" is as a political concept. Unlike political judgments that are based on concrete assessments of, say, a candidate's record or even something as grubby as his fund-raising prowess, those that are based on a candidate's supposed electability can change on a moment's notice. And then change again. Electability is completely ephemeral. Even those hoary and maddeningly indefinable political qualities like "character" and "authenticity" have more meat on their bones.
And that's probably why those candidates who resort to playing the electability card are, more often than not, losers. According to Merriam-Webster's, the term electable has been with us since 1879, but it really wasn't until late last century that candidates started adding electability arguments to their political arsenals. They usually haven't worked. Adlai Stevenson and his allies, including Eleanor Roosevelt, tried to no avail to use electability against John Kennedy in 1960, claiming that his Catholicism would keep him from winning the general election. In 1984, Gary Hart based much of his unsuccessful campaign for the Democratic nomination on the contention that Walter Mondale, the eventual Democratic nominee, couldn't beat Ronald Reagan in November. (That Hart turned out to be right was cold comfort for him.) Four years later, Bob Dole argued that George Bush wasn't electable, and four years after that, Bob Kerrey said the same about Bill Clinton. (Kerrey was much more colorful than Dole, predicting that Clinton was "going to be opened up like a soft peanut" by Bush.)
The reductio ad absurdum of electability arguments may have come last month, when John McCain's campaign sent out an e-mail blast titled "Good Polling News" hyping a national poll by Fox News that, in the McCain campaign's estimation, showed that "John McCain is the Republican candidate best positioned to beat Hillary Clinton"—because in hypothetical head-to-head matchups with Clinton, McCain outperformed Giuliani by one percentage point. Alas, there was an inconvenient truth about the poll: It showed McCain and Rudy both losing to Clinton, by three and four points, respectively. In other words, the McCain team's electability argument boiled down to this lame claim: Our guy will lose by less!
Photo: Frank Micelotta/Getty Images
It's enough to give electability a bad name among some political pros. "When someone walks into the room and says we're twenty points behind but we're the most electable, you know they don't have much to rest their argument on," says the Democratic pollster Mark Mellman. "It's the last resort of people who think they have no chance."
And yet, despite such a sorry track record, the electability argument had a shining moment of sorts in the 2004 presidential race, when John Kerry rode it to the Democratic nomination. Granted, Kerry never made the electability argument in explicit terms. But in the weeks and months leading up to the Iowa caucuses, the Kerry campaign worked to plant seeds of doubt in Democrats' minds as to whether the then front-runner, Howard Dean, had what it took to beat President Bush. At the same time, Kerry talked up his foreign-policy credentials and his Vietnam service in the hope of convincing Democrats that he could, as his campaign manager Bob Shrum recounts in his memoir No Excuses, "go toe-to-toe with Bush" on what were seen as Bush's strengths. The strategy worked as Kerry scored an upset victory over Dean in Iowa. "There were a lot of people out there who really liked Governor Dean's message of standing up to the Republicans and President Bush and his strong antiwar stance," recalls Gordon Fischer, who was the Iowa Democratic Party chairman in 2004, "but they ultimately felt that Senator Kerry was close enough to those principles and was more electable in 2004. They chose their head over their heart."
That pattern continued in the nomination contests that followed. Where just 7 percent of New Hampshire Democratic-primary voters in a 2000 exit poll chose "best chance to win in November" as the most important reason for their vote, 20 percent of New Hampshire Democrats said "can beat George W. Bush" was the reason for their vote in 2004—which helped put Kerry over the top there. In fact, according to the National Election Pool exit poll, nearly four in ten Democratic-primary voters in 2004 said that having a nominee who could beat Bush was more important than having a nominee with whom they agreed on the issues. While Dean may have been many Democrats' personal choice, Kerry was their strategic one.
Memories of the "Dated Dean, Married Kerry" phenomenon are probably one reason the '08 presidential primaries have become an electability bonanza. On the Democratic side, John Edwards and Barack Obama have repeatedly held themselves out as the most electable Democrat; second-tier candidates like Joe Biden and Chris Dodd have made the far-fetched argument that even though they are mired in single digits in the polls, they'd outperform Hillary, Edwards, or Obama in November. And these arguments could turn out to be effective. According to an aide on one Democratic campaign, their internal polling shows that electability has surpassed Iraq as the issue most important to Iowans. Meanwhile, in GOP-land, Rudy Giuliani somewhat improbably sits atop the national polls thanks to a plurality of Republicans who are apparently willing to tolerate his liberal social views and messy personal life because they believe him when he claims that only he can stop Hillary from storming the White House. Indeed, even more than a MySpace page and a health-care plan, the ultimate must-have for '08 presidential candidates is a memo from their pollster spelling out—in words, numbers, and sometimes color-coded maps—exactly why their guy (or gal) is the best bet to win in November.
But there's likely more going on than just fond memories of '04. The current electability fixation probably has as much if not more to do with the politician still leading the '08 field: Clinton. Despite polls like the Times one from earlier this month, the doubts about Hillary's electability—at least those harbored by the political class—stubbornly refuse to die. As one Democratic strategist who typically pooh-poohs electability arguments says, "I think this year is different. Something's going on. I really think electability is more important this cycle than ever before, at least among hyperinformed voters like you have in Iowa or New Hampshire. And that's because it's been forced on them. It's been the story line about Hillary for so much of the race, and voters have framed the race the way it's been given to them by the press. So much of the question has been, 'Can she win a general election?' How could any voter have escaped that that's a serious question about her? And how could that not affect their own criteria for voting?"
Photo: Charles Ommanney/Getty Images
Political scientists, for their part, have taken a stab at gauging electability. At conferences and in journal articles, these academics have tried to suss out just what makes a candidate electable—or, at the very least, what makes voters perceive a candidate as electable. Physically attractive male candidates, one group of political scientists concluded, enjoy an electability advantage, but the same group could find no straightforward link between attractiveness and electability for female candidates. Similarly, some political scientists found that male politicians with hair tend to get elected more than balding ones. (There doesn't appear to be any research on the electability of balding female candidates.) And in 1994, two professors from William & Mary and the University of Colorado went so far as to come up with an actual electability formula, which looks like this:
Candidate electability = a + b1 (party) + b2 (evaluation of C) + b3 (C's proximity to R) + b4 (C's proximity to the average voter) + b5 (C's proximity to party) + b6 (C's nomination chances) + b7 (C's TV performance) + e
Political professionals, however, take a more straightforward approach: They gauge electability by looking at public-opinion polls. Of course, polls can be twisted in certain ways—and no one's done more twisting to his advantage than Giuliani.
On one level, the argument for Giuliani's electability is simple logic. The political environment right now couldn't be worse for Republicans: A recent NBC/Wall Street Journal poll found that a generic Democratic presidential candidate trounces a generic Republican presidential candidate 50 to 35 percent. So it stands to reason that an unconventional Republican like Giuliani—with his liberal-to-moderate views on social issues and his New York City address—is more electable than a conventional one like Mitt Romney, Fred Thompson, or McCain circa 2008. (McCain circa 2000 would have been a different story.) What's more, Giuliani's less-appealing, unconventional features—namely his messy personal life—probably wouldn't prove too great a liability in a general election. While an October New York Times/CBS News poll found that two thirds of Republicans believe that presidential candidates should be judged on both their political records and their personal lives, those same Republicans would have presumably made their peace with Giuliani if they'd chosen him as their party's nominee. Meanwhile, the same poll found that only half of Democrats and independents—the very voters Giuliani would be making a play for in November—think that a presidential candidate's personal life matters. Rudy's religion wouldn't hurt him, either: Numerous public-opinion surveys show that more than 90 percent of Americans would have no trouble voting for a Catholic. (Mitt Romney's religion, however, may be another story: A recent Newsweek poll found that 28 percent of Americans wouldn't vote for a Mormon presidential candidate.)
The former GOP pollster Frank Luntz, who has been conducting postdebate focus groups for Fox News, describes Giuliani's electability as a simple matter of personality: "Rudy exudes electability," he says. "He exudes confidence to a Republican Party scared to death of losing to Hillary Clinton."
The Giuliani campaign, for its part, has seized on electability and attempted to run with it well past the point of reason. In October, Giuliani's "strategy director," Brent Seaborn, produced one of those ever-popular "electability" memos, which came out at the same time a map was leaked from the campaign showing that in a general-election matchup with Clinton, Rudy would win, or strongly contend in, a whopping 48 states—with the only states "safe" for Clinton being the pinko playgrounds of Massachusetts and Vermont. Even if Rudy doesn't come close to pulling a Nixon and winning in 49 states, Seaborn argued, merely being competitive in them would prove beneficial: "Hillary Clinton will be forced to advertise in New York City, Los Angeles, and Chicago—the three most expensive media markets in the country, something Democrats haven't had to do in twenty years. This will effectively take Florida off of the Democrats' target map—making it a safe Republican state in 2008 if Mayor Giuliani is the nominee. If another Republican is the nominee, traditional blue states will be safe, meaning the Democrats can plow all their resources into Ohio and Florida."
Unfortunately for Giuliani, Seaborn's electoral map is so optimistic it's delusional. Outside Rudyworld, it's hard to find anyone who believes that states like California, Washington, and Maryland—all deemed toss-ups by Seaborn in a Giuliani-versus-Clinton matchup—won't go to the Democratic candidate by wide margins in 2008. Indeed, even some inhabitants of Rudyworld implicitly acknowledge as much: Would so many Giuliani supporters be backing a California ballot initiative that seeks to apportion the state's electoral votes by congressional district instead of by the usual winner-take-all method if they thought their guy actually had a shot at winning there? In fact, in a SurveyUSA poll from October, Hillary's thumping Rudy in California 55 to 39. L.A. TV stations better not count on Hillary's advertising to fill their coffers come next fall. The same goes for TV stations on Rudy's—and Hillary's—home turf. Although Seaborn says New York would be in play in a Rudy-versus-Hillary contest, the polls disagree: According to an October poll from Quinnipiac University, Hillary beats Rudy 52 to 41 in their home state. Indeed, the greatest chink in Rudy's electability armor is another October poll, this one by ABC News and the Washington Post, which showed Hillary leading Rudy 51 to 43 in a nationwide contest. Even worse for Rudy's electability prospects, the same poll found that while 41 percent of Americans would never vote for Hillary, 44 percent would decline to vote for Giuliani. Although a November NBC/Wall Street Journal poll showed Giuliani pulling to within one point against Clinton—losing 45 to 46—that hardly makes him a slam dunk.
There's also the potential complication of a pro-life candidate, or a certain billionaire from New York, running on a third-party ticket should Giuliani get the Republican nomination. With a pro-life candidate in the race, according to an October Rasmussen poll, Rudy would get only 30 percent of the vote, with 14 percent going to the third-party conservative and 46 percent going to Hillary.
Then again, regardless of any third-party candidate, 54 percent of people surveyed in the recent ABC News/Washington Post poll said they'd never vote for Fred Thompson, and 57 percent put the kibosh on ever voting for Romney. So, relatively speaking, maybe there is something to Giuliani's electability argument.
Photo: Stephanie Kuykendal/Getty Images
But electability could turn out to be irrelevant on the GOP side. Having had the White House for the last eight years, Republicans may not be so fixated on winning in November that they're willing to compromise their principles in the primaries. The same, of course, can't be said of Democrats. If nearly 40 percent of Democrats chose their nominee on electability grounds in 2004, after only four years of Bush in the White House, imagine how they'll be feeling after eight. "We've been on the outs for so long and have been nominating losers," says a Democratic consultant. "Democrats feel like we really need to win this thing this time around." Which is why so many Democratic candidates are making the electability argument so explicitly in the current campaign.
The most novel electability claim undoubtedly comes from the Biden and Dodd camps. Call it the blandness argument. Pointing to the polling that shows a generic Democrat beating a generic Republican, Biden and Dodd supporters argue that their guys—both white, sixtysomething men who have been marinating on Capitol Hill for the past few decades—are in fact that generic Democrat. "There's a terrific wind at the backs of Democrats," says one Democratic consultant, "but we may be rushing toward nominating the one person, Hillary Clinton, who could turn a political tsunami into a nail-biter … With these kind of tailwinds, we'd almost be sure to win if we nominated a hyperconventional candidate, so you can make a strong electability case for Biden or Dodd." Alas, Biden and Dodd's electability argument is ultimately undermined by their present circumstances. Mired in single-digit-land at this fairly late date, these candidates have virtually no shot of ending up in the general election anyway.
Pollster Frank Luntz describes Giuliani's electability as a simple matter of personality. "Rudy exudes electability. He exudes confidence to a Republican Party scared to death of losing to Hillary Clinton."
Barack Obama's electability argument is seemingly stronger. He has good favorability/unfavorability numbers, with a recent NBC/Wall Street Journal poll finding a 43/24 split (in striking contrast to Hillary, whose favorable/unfavorable numbers were 43/44). What's more, Republicans and independents—especially those with advanced degrees—have a generally favorable opinion of him, according to an August analysis by Gallup. Nor does Obama's race appear to be a disadvantage in electability terms—and, according to Obama, it is actually a plus. Most public-opinion polls find that more than 90 percent of Americans say they would cast a presidential vote for a well-qualified candidate who happened to be African-American. And in August, Obama boasted (in New Hampshire, of all places) about how his support among African-Americans would "redraw the political map," saying that if the turnout of African-Americans relative to whites matched their percentage of the population in Mississippi and Georgia, those would become Democratic states, and that if African-Americans did the same in South Carolina, it would suddenly be in play.
But there are some definite chinks in Obama's electability armor. For one thing, his favorability ratings don't necessarily translate into votes. As GQ reported this summer, Obama's own pollsters have discovered that less than half of those who say they like the candidate actually say they'd vote for him; by contrast, about two thirds of those who say they like Hillary say they'd vote for her.
The fact that more than 90 percent of Americans say they'd vote for a black presidential candidate isn't insignificant—especially when you consider that in 1963, only 48 percent of Americans said they would do so. But some pollsters think these sorts of generic questions about race—and gender, for that matter—are unreliable. A strategist affiliated with one Democratic campaign says that in focus groups, Obama's race does sometimes have a negative impact on assessments of the candidate. "People say, 'I'd have no problem voting for him, but I worry about whether my neighbor will,' " says the strategist. And when public-opinion polls ask voters not whether they'd vote for a qualified African-American presidential candidate but whether they think "voters of this country are ready" to elect a black president, as a recent NBC/Wall Street Journal poll put it, the numbers go down—to 63 percent, in that example.
Photo: Justin Sullivan/Getty Images
Similarly, some polls find that people come up with other reasons for why they or their friends won't vote for Obama—reasons that could be proxies for race. For instance, a CBS News poll in August found that 38 percent of voters believe Obama's name (and its unfortunate resonance with the world's most famous terrorist) could prevent people from voting for him. And Obama's claim that his race will actually benefit him in the South is far-fetched—in 2004, for instance, African-Americans made up 34 percent of the voters in Mississippi—just a smidgen under their 37 percent share of the state's population—and Kerry still lost there by twenty points.
While Obama says being black will help him in the South, John Edwards argues that being southern will help him everywhere. As he mused in an interview with Time this summer, "It's simple geography. Ask Middle Americans: You've got three Democratic candidates. One's from New York, one's from Chicago, and one's from rural North Carolina. Who do you think is most like you?" Which, Edwards claims, gives him a certain amount of ideological wiggle room, as he explained in the same interview: "I think most journalists would agree that I'm the most progressive, Senator Obama next, and Senator Clinton closest to the center. But I'd be willing to bet that if you ask most Americans the same question, they'd reverse it."
And there is some polling data to back up Edwards's claim. A November survey by Rasmussen Reports found that while 51 percent of voters perceive Clinton as liberal and 44 percent view Obama this way, only 38 percent attach the L-word to Edwards. What's more, 13 percent actually view Edwards as conservative, with only 9 percent using that term to describe Clinton and 6 for Obama. These perceptions, the Edwards campaign argues, make him a more formidable candidate than Clinton or Obama in swing states and among downscale voters—and thus make him more electable. "If you look at the people who used to vote Democrat but no longer vote Democrat, John Edwards does particularly well," says Edwards's pollster, Harrison Hickman. "He does well with working-class people, and that gives him an advantage in states with large numbers of what used to be called Reagan Democrats—states like Ohio."
But Edwards's advantage in, say, Ohio isn't that clear-cut— at least not where it matters most. While SurveyUSA in September found him winning the state by twenty points in a hypothetical head-to-head matchup with Romney, he lost in a head-to-head matchup with Giuliani by one point. Which, the same poll found, is the same lead Rudy enjoys over Hillary in the state. In other words, when it comes to taking on the Republican front-runner in a key battleground state, Edwards does no better than the candidate Edwards hopes to bring down with his electability argument.
And then there is Hillary. As the front-runner, she's less inclined than her competitors to make many explicit claims about electability. Just a couple of months ago, her husband dismissed "this electability thing" as a "canard [that] doesn't amount to a hill of beans." But since her electability has become the fundamental question of the 2008 race, it has to be examined. And, surprisingly, the case for Hillary's electability turns out to be pretty strong.
First, her gender doesn't seem to be much of an impediment—and may even be an advantage. Although the number of Americans who said they had no reservations about voting for a female presidential candidate dipped in the year after the 9/11 attacks—from about 95 percent to 65 percent—it has returned to close to its previous level, with a February USA Today/Gallup poll finding 88 percent of Americans willing to put a woman in the White House. And support for Hillary among women is quite strong. While a Gallup analysis of polling data between 2005 and 2007 found that men were almost evenly divided in their opinion of Hillary—with 49 percent rating her unfavorably and 47 percent rating her favorably—women were far more positive about her: 59 percent rated Hillary favorably and only 36 percent unfavorably. That gender gap could prove decisive for Clinton. As Mark Penn, Clinton's chief strategist, notes, "Women were 54 percent of voters in the last election. It wouldn't be the question of electing a minority but a majority."
Second, even Hillary's high unfavorability numbers may not serve as that much of an impediment in a general election. For one thing, in today's polarized political environment, high unfavorables are the likely fate for either party's nominee: Hillary, by dint of the fact that she's been in the national spotlight for fifteen years and has been subjected to political attacks for just as long, merely has a head start on the other Democratic candidates in terms of amassing those unfavorables. "She starts out where any other nominee is going to get," says a Democratic pollster. "Anyone who gets the nomination is going to be the same kind of lightning rod."
What's more, high unfavorable ratings in January aren't necessarily the kiss of death in November. According to a recent analysis from Gallup, Bill Clinton and George W. Bush started out their presidential campaigns with high unfavorable ratings: Clinton had a 49 percent unfavorable rating at the outset of 1992, and Bush was at 47 percent unfavorable at the start of the '04 campaign. Approval ratings tend to change over the course of a campaign, and Hillary's probably will, too. Although it's conventional wisdom that everyone has already made up their minds about the junior senator from New York, her favorable/unfavorable ratings over the past fifteen years have fluctuated. And while it's true that a candidate's negatives tend to go up over the course of a presidential campaign, Gallup argues that might not apply to Hillary, since she's already so well known. "Typically, a winning presidential candidate's favorable rating is only slightly more positive than negative on the eve of the election," Gallup concludes. "Clinton would only need to boost her positives a few points to achieve that position."
How Gallup and Penn—and Edwards and Obama, for that matter—assess Clinton's electability is ultimately irrelevant. What matters is how Democratic caucusgoers and primary voters view it, since a good number of them will likely take that view into account when deciding which candidate to support. And on this metric, Hillary is in very good shape. We already know about Democrats in Iowa and New Hampshire, but they're not the only ones who are deeming Hillary electable. While an April NBC/Wall Street Journal poll found 39 percent of Democrats saying Hillary was the most electable candidate (compared with 32 percent who picked Obama and 22 percent who picked Edwards), another NBC/Wall Street Journal poll in September found that the percentage of Democrats who viewed Hillary as the Democrats' best bet in November had jumped to 54 percent (with Obama dropping to 18 percent and Edwards to 15 percent). Over the course of those same five months, Hillary nearly doubled her lead over Edwards and quadrupled her lead over Obama.
So how did Hillary do it? How, in less than a year, did she go from unelectable albatross—in the eyes of Democratic voters, at least—to their party's best bet to take back the White House? Part of the answer has to do with the difference between the idea and the reality of Hillary. In the abstract, or in the cross-tabs of a polling report, she can appear to be the cold, calculating, evasive, polarizing figure her critics have long painted her to be. But in the flesh, on the stump in Iowa and New Hampshire and onstage at the debates with her vast herd of rivals, she has shown herself to be a commanding and formidable politician. More than that, she's been ahead the whole time, and that, by itself, has boosted the perception of her electability. There's a snowballing effect, or what an economist might call a "cumulative advantage," which simply means the bigger you are, the bigger you get, like a Hollywood blockbuster or a chain of office-supply stores. Hillary's the dominant Democratic Party brand at the moment. But it's far from an invincible position. If her electability advantage is little more than a reflection of her place in the polls, then it could disappear as quickly as her leads over Obama and Edwards in Iowa and New Hampshire have been shrinking. A single upset, and Hillary's electability problem comes roaring right back.
The Wishy-Washy, Squishy-Squashy Pseudoscience of […]


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