I am experienced in using animal models and clinical studies to gain biological insights into mental illness. Integrative approaches and collaborative thinking foster discoveries that will transform medicine and improve people's lives.
Studied a family of monozygotic twins with childhood-onset schizophrenia sharing 15q11.2 microdeletion. Analyzed neuropsychological tests, event-related potential, diffusion spectrum magnetic resonance imaging, and iPS cell characterization. Reviewed and discussed literature on the copy number variation in schizophrenia and other neurodevelopmental disorders.
Spontaneous bursts of action potentials spread across the developing neural tissue and drive circuit refinement. To investigate if patterned spontaneous activity could be substrate of neurodevelopmental disease, I studied a neural transmission machinery protein “dysbindin”, also known as a schizophrenia-susceptibility protein. I applied a transient expression system in organotypic culture of postnatal rat retina to manipulate expression level of dysbindin. Using calcium imaging and whole-cell patch-clamp recording, I showed that dysbindin regulates spatiotemporal pattern of retinal waves and pairwise correlations in neighboring neurons.
Anxious-prone people are predisposed to social submissiveness under stress. To model trait anxiety, I tested outbred rats and classified them with behavioral experiments. Given that stress and social hierarchy strongly modulate neural activity in the ventral striatum, I examined if extracellular dopamine level at the nucleus accumbens (NAc) alters as a function of trait anxiety and stress. I demonstrated that dopamine level increases upon stress, as modeled with infusing corticosterone into NAc, compared with baseline. However, anxious-prone rats do not differ from normal rats in terms of dopamine level at baseline or upon stress. Further study in the lab revealed decreased dopamine receptors at the NAc in anxious-prone rats.
Drosophila genetic toolbox enables precise control of gene expression in single neuron. Rab27 is a neuron-specific small GTPase and Rab27-knockout flies showed deficits in memory function. I applied the GAL4/UAS system and olfactory aversive conditioning to dissect the the role of Rab27 in different brain regions and stages of memory. I also helped the lab generate CRISPR/Cas9 flies.
Medical License, Taiwan R.O.C.
(10 out of >1,200 for outstanding achievements in extracurricular activity)
Apart from being in labs and hospitals, I enjoy my time being outdoors. I have travelled to the mountains of Tibet and rainforests of Borneo. Watching wild animals in their natural habitat being themselves is one of the most invigorating experiences.
I am a PokemonGo trainer of Team Instinct at top level. I enjoy the encounter with lovely beasts while exploring the city. I am also a fan of Japanese culture, fictions, movies, and games. I have done a clinical internship at Kyoto University Hospital and had the luck to enjoy the city thoroughly.


Many thanks to the folks who helped: Darren Westlund and Dee Dee Leichtfuss, for help with the manuscript; the people at the Harmony Pasta Factory and the Pine Tree Inn, for their tolerance and support; Pam Jacobson and Kathe Frahm, for their faith; Mike Molnar, for keeping the machine running; Nick Ellison and Paul Haas, for running the gauntlet for me; and Faye Moore, for mom stuff.


No one (including parents) is permitted to smoke inside the premises or in the outside areas such as the garden and front garden, which surround the premises.
A no smoking policy will be promoted and children will be educated that it is unhealthy.


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extremely low
very low
low
undetermined
medium
high
very high


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Hi, I am Alice. This is my personal webpage. Please vote on Free TON blockchain for the next article theme.


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They realized something was wrong when I turned 14 and suddenly became depressed. Like, 14, BAM. It's like someone turned on a switch for depression and I transformed into a completely different person. I wasn't a happy child anymore. It freaked me out and the worst part was that there was no reason for my constant sadness and suicidal dreams. Depression supposedly is genetic and since everyone in my family has it, I should not have been surprised. Supposedly your body chemistry changes every 7 years, too...7+7=14....I don't know the reason. I really wish I did. Because 5 years later it's still here.
I started seeing a psychiatrist who I really didn't like and he put me on Prozac. Well, that did nothing but give me convulsions, literally make me jump out of my skin, and it just increased my desire for death. So they tried Paxil instead. I started on 10 mg, and it seemed okay, but not enough. It didn't have any real side effect besides making me really tired, so I took it at night instead. They upped it to 20mg and I stayed on that dose for a while. It worked, I guess.    I ended up at 40mg when I was around 17 I think.....and it seemed okay. Every time that they upped it 10mgs, it seemed to do the trick. But now I'm wondering if it was the right drug.
Now I'm 19 and I've been on Paxil for 5 years. Lately, life just has not been doing it for me. I live alone at my college and try to force myself to function but its been harder and harder lateley. Over Holiday break my psych upped and changed my dose to Paxil Continued Release instead of the regular wham-bam-thank-you-maam stuff. And now it's at 37.5mgs, which is equivilent to 60mgs of regular Paxil. The bottom line is I still feel like killing myself and I think my body has built up a tolerance to the Paxil that has made it ineffective. My psych also put me on Topamax to 'stabilize my moods', which is crap because Topamax is an epilepsy medication and I don't have seizures, man, period.  But I can't get off the Paxil.
I can't not take it because if I don't, I'll shake constantly, I'll get wicked dizzy and lightheaded to the point of falling over, and it will just manifest into a panic attack. The only time I ever have a panic attack is if I have not taken the Paxil for a few days (anywhere between 2-6 days of missed doses). This happens more often than one might think, as I am more likely to forget to take my meds if I forgot to take them the day before that, and the day before that, and so on. So if I forget for a week, I am royally screwed. I forget to take them a lot. I forget things. I'm a forgetful person.  I had never had a panic attack before I took Paxil.
I can't not take this medication. Yet, it costs me money, and it doesn't fix my seratonin like it's supposed to. I'm not happy, am I? No. So it doesn't work, at least not anymore. I have been on Paxil for 5 years.  I've been trying to research online about SSRIs and other types of antidepressents just try and figure out what the hell is going on. The only thing that makes me feel better is weed. And weed's still illegal, and hella expensive, and it still makes me lethargic. No matter how much I love marijuana, I hate that I'm addicted to it, because it only makes me more depressed in the end, because nothing can mask unhappiness.
This experience is recorded not to prove anything but maybe to add some insight. Maybe I'm not the only one.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


|
NOTES
1 Not present when DataSourceReportChar=False and ServiceCodePage=Database
2 Only present when ServiceCodePage=Database
3 Only present when DataSourceFetchTimestampAsString=False
4 Only present when DataSourceFetchTimestampAsString=True
5 Not present when ServiceCodePage=Database
6 Only present when ServiceCodePage=Database and database character set is UTF-8
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How DBSCAN works and why should we use it?
Density-based spatial clustering of applications with noise (DBSCAN) is a well-known data clustering algorithm that is commonly used in data mining and machine learning.
Based on a set of points (let’s think in a bidimensional space as exemplified in the figure), DBSCAN groups together points that are close to each other based on a distance measurement (usually Euclidean distance) and a minimum number of points. It also marks as outliers the points that are in low-density regions.
Parameters:
The DBSCAN algorithm basically requires 2 parameters:
eps: specifies how close points should be to each other to be considered a part of a cluster. It means that if the distance between two points is lower or equal to this value (eps), these points are considered neighbors.
minPoints: the minimum number of points to form a dense region. For example, if we set the minPoints parameter as 5, then we need at least 5 points to form a dense region.
Parameter estimation:
The parameter estimation is a problem for every data mining task. To choose good parameters we need to understand how they are used and have at least a basic previous knowledge about the data set that will be used.
eps: if the eps value chosen is too small, a large part of the data will not be clustered. It will be considered outliers because don’t satisfy the number of points to create a dense region. On the other hand, if the value that was chosen is too high, clusters will merge and the majority of objects will be in the same cluster. The eps should be chosen based on the distance of the dataset (we can use a k-distance graph to find it), but in general small eps values are preferable.
minPoints: As a general rule, a minimum minPoints can be derived from a number of dimensions (D) in the data set, as minPoints ≥ D + 1. Larger values are usually better for data sets with noise and will form more significant clusters. The minimum value for the minPoints must be 3, but the larger the data set, the larger the minPoints value that should be chosen.
You can find more about parameter estimation here.
Why should we use DBSCAN?
The DBSCAN algorithm should be used to find associations and structures in data that are hard to find manually but that can be relevant and useful to find patterns and predict trends.
Clustering methods are usually used in biology, medicine, social sciences, archaeology, marketing, characters recognition, management systems and so on.
Let’s think in a practical use of DBSCAN. Suppose we have an e-commerce and we want to improve our sales by recommending relevant products to our customers. We don’t know exactly what our customers are looking for but based on a data set we can predict and recommend a relevant product to a specific customer. We can apply the DBSCAN to our data set (based on the e-commerce database) and find clusters based on the products that the users have bought. Using this clusters we can find similarities between customers, for example, the customer A have bought 1 pen, 1 book and 1 scissors and the customer B have bought 1 book and 1 scissors, then we can recommend 1 pen to the customer B. This is just a little example of use of DBSCAN, but it can be used in a lot of applications in several areas.
How can we easily implement it?
As I already wrote (tip: don’t believe in everything I write) the DBSCAN is a well-known algorithm, therefore, you don’t need to worry about implement it yourself. You can use one of the libraries/packages that can be found on the internet. Here is a list of links that you can find the DBSCAN implementation: Matlab, R, R, Python, Python.
I also have developed an application (in Portuguese) to explain how DBSCAN works in a didactically way. The application was written in C++ and you can find it on Github.
References:
- Ester, M., Kriegel, H. P., Sander, J., & Xu, X. (1996, August). A density-based algorithm for discovering clusters in large spatial databases with noise. In Kdd (Vol. 96, №34, pp. 226–231).
- DBSCAN: https://en.wikipedia.org/wiki/DBSCAN


Preparation time
less than 30 mins
Cooking time
30 mins to 1 hour
Serves
Serves 40
This recipe feeds a lot of people so you will need large frying pans and ovenproof dishes. It may be easier to cook it in batches.
Preheat the oven to 180C/350F/Gas 4.
Place the flour into a bowl and season with salt and freshly ground pepper. Dredge the chicken in the flour, shaking off any excess.
Heat a large, deep frying pan and add the oil. Fry the chicken pieces skin-side down for 1-2 minutes until golden-brown, turn over and brown on the other side. Remove the chicken from the pans and set aside.
Add a little more oil if the pans are dry then add the mushrooms and fry for 2-3 minutes. Add the onion and cook for a further five minutes.
Place the chicken back in the pans and add the stock, tomato purée, whole tarragon sprigs and tomatoes. Bring to the boil and transfer the chicken to ovenproof dishes. Cover with aluminium foil and place in the oven for 45 minutes, or until the chicken is cooked through.
Adjust the seasoning if necessary then add the parsley and the chopped tarragon.


Water worries: Toxic chemicals are being dumped in the Merrimack River
by Wale Aliyu , Manoella MacedoLOWELL, Mass. - It provides the drinking water for over half a million people, but some say toxic chemicals are now being dumped into the Merrimack River.
The Merrimack River Watershed Council says it mostly stems from the Turnkey Landfill in Rochester, New Hampshire after the federal government loosened regulations on Obama-era landmark water protections.
According to the council, the highly toxic chemicals are being dumped into the river from the landfill.
In September, the Trump administration repealed the Clean Water Act, a set of protections that limited the amount of pollution and chemicals in streams, rivers, lakes and wetlands across the country. The new rule also limits the number of waterways nationwide the government can protect from pollution.
However, many residents who drink the water from the Merrimack say they have no idea what is in the water.
"I've been drinking Merrimack River water all my life," said Bob Minasian, of Lawrence. "I'm 80 years old and nothing's happened to me, my teeth have not fallen out."
Others are wary of what this could mean for the future.
"There's not a lot of accountability [or] caring about people except for the profits," said Joanna Woolworth, of North Andover.
The council says they have asked the Environmental Protection Agency to require the Lowell Regional Wastewater Facility to screen for PFAS, or per- and polyfluoroalkyl substances in the river, but were declined.
"They are not required by law and they should do it whether or not they are required by law," said Christina Eckert, the Co-Executive Director for the Merrimack River Watershed Council. "Anyway, if not, we better pass a law quick. There are multiple manufacturers. We know the PFAS are there, the question is how do we get rid of it and that's a problem because it does not break down naturally. And what I've been told is it requires being heated to extreme temperatures, up to 1000 degrees, to break it down and if you do it wrong it just makes the chemical more dangerous."
The chemicals have been linked to kidney cancer, low infant birth weights and other diseases.
"I can't worry about the type of water I drink so in a way I trust people to do the right thing and protect people," said Woolworth.
Experts say the PFAS chemical does not easily break down in the body and it could be in the water of 600,000 people.


import com.sleepycat.db.*;public DbLock() throws DbException;
public DbLock(DbLock that) throws DbException;
public DbLock(int lockid); throws DbException;
The DbLock class is used in conjunction with the DbLockTab class to provide general-purpose locking. While designed to work with the other Db classes, these classes are also useful for more general locking purposes. Locks can be shared between processes. In most cases, when multiple threads or processes are using locking, the deadlock detector, db_deadlock should be run.


{% extends 'vehicle/mechanicbase.html' %} {% load static %} {% block content %}
New Work Assigned
Work In Progress
Work Completed
Salary


[1]
Android Market, Full Qwerty Keypad, Touch Screen, Applications, Facebook, Myspace, Twitter, YouTube; It's all great!
[2]
all the google functions, good apps; no skype!!!


Hello there! I'm Luca.
I'm a Student from Germany and i'm programming as a Hobby.
HTML5
CSS
JavaScript
Email
Discord


Uncertainty in the parameters of linear regression
I recently found out that linear regression assumed that the output variable comes from normal distribution, which consequently turns the coefficient to have probabilistic interpretation. I was confused at first because I was taught linear regression from a machine learning model perspective: input some features and linear regression will fit a line that minimizes a certain cost function such as root mean squared error (RMSE) and then we use that for prediction. I went blank when I realized that there are probabilistic metrics associated with each coefficient. For example, if we use python libraries such as statmodels, it is going to show these probabilistic metrics.
Where does the confidence interval parameter come from? What about the std error, t statistics, and the p-value that is associated with each coefficient? Where do they come from? In this post we are going to take a look on how does this probability metrics came about.
Random variables in linear model
Probabilistic metrics exist with the notion of random variables. In linear regression, the variable of interest \(y\) that we want to predict is assumed to be generated from a normal distribution. In mathematical form, it looks like this:
\[\mu = X w_{true}\] \[y \sim \mathcal{N}(\mu, \epsilon)\]This form can be rewritten as:
\[y = X w_{true} + \epsilon\] \[\epsilon \sim \mathcal{N}(0, \mathbb{I})\]where \(X\) is our observed dataset, \(w_{true}\) is the true parameter that we cannot observe, and \(\epsilon\) is an independent noise.
Why does it looks like this? Why does we have to assume that \(y\) sampled from a normal distribution? The short answer is because we assume linear regression to have this property. In reality, we will never know the value of \(w_{true}\), hence we want to approximate \(w_{true}\) by looking at the observed data \(X\). To do that, we introduce a new variable called \(w_{opt}\), the parameter that we can calculate from observed data. I would assume the reader is familiar with the closed form solution to find the optimal \(w_{opt}\) that approximates \(w_{true}\). The equation is given as:
\[w_{opt} = (X^T X)^{-1} X^T Y\]where the \(Y\) is the label observations in the data. Notice the difference here: \(y\) is a random variable sampled from a normal distribution, whereas \(Y\) is the label observations in the data. We assume that the observed \(Y\) does not equal to \(X w_{true}\), but rather to \(X w_{true}\) plus some corrupted gaussian noise \(\epsilon\). Hence, we further assume that \(Y\) is the observations that we get from sampling the random variable of interest \(y\).
If we look closer to the equation above, we will notice another thing: \(w_{opt}\) is calculated by linearly transforming two components: \(X\) and \(Y\). Since we model \(Y\) as a sample from the random variable \(y\), we can introduce another random variable \(\hat{w}\) that is calculated as:
\[\hat{w} = (X^T X)^{-1} X^T y\]\(\hat{w}\) represents a distribution of learnt parameter values. \(w_{opt}\), the variable that we use to approximate \(w_{true}\), can be seen as a sample from the distribution of learn parameter values \(\hat{w}\). This is because \(\hat{w}\) is defined as a linear transformation from the random variable \(y\), with \((X^T X)^{-1} X^T\) being the transformer matrix. And since \(Y\) is a sample from \(y\), \(w_{opt}\) is defined by applying the same transformation to the sample \(Y\).
Probability density function for \(\hat{w}\)
Now we want turn \(\hat{w}\) into a probability density function. To get that, we can apply multivariate gaussian linear transformation rule to \(y \sim \mathcal{N}(\mu, \epsilon)\). I will not go into the details of the derivation in this post. For those interested, please see here. Applying the transformation rule yields:
\[\hat{w} \sim N(w_{true}, (X^T X)^{-1} \eta^2)\]where \(\eta^2\) is the variance of each single random variable \(\epsilon\). It is defined by
\[\epsilon \sim \mathcal{N}(0, \mathbb{I} \eta^2)\]where \(\mathbb{I}\) is the identity matrix. In this case, \(\epsilon\) that we introduce in \(y \sim \mathcal{N}(\mu, \epsilon)\) is a multivariate Gaussian noise where it represents noise that is independent at each data point. Hence, the dimension of \(\eta^2\) is \(n\), where \(n\) is the number of data points.
This leaves us with two unknown parameters that we need to define, namely \(w_{true}\) and \(\eta^2\), before we can get the probabilistic metrics out of \(\hat{w}\).
For \(w_{true}\), we use \(w_{opt}\) as it is only sample that we observed in the training data. For \(\eta^2\), we need an observable value for the calculation. Since we already know that \(\hat{w}\) is transformed by the random variable \(y\), we use the variance of \(y\) to represent the noise part for unknown parameters \(\eta^2\). By definition, the variance of \(y\) is the same as the variance of \(\epsilon\) which is the same as the variance of \(\eta^2\). The variance of \(y\) can be calculated by taking the predicted value \(\hat{Y} = X w_{opt}\) versus the observed value \(Y\). Plugging this into a standard deviation formula, we get:
\[\eta^2 = \frac{1}{n-1} (\hat{Y} - Y)^T (\hat{Y} - Y)\]Note that \(\eta^2\) becomes a scalar now. That’s it! We can now proceed to look at each of the probabilistic metrics
Standard deviation
We have defined this above. The standard deviation of our weight distribution is given by \((X^T X)^{-1} \eta^2\). The \((X^T X)^{-1}\) matrix is of p x p dimension and \(\eta^2\) is a scalar, yielding a p x p matrix, where \(p\) is the number of features that we have. The variance of each feature is at the main diagonal of this matrix.
Confidence interval
Since \(\hat{w}\) is a multivariate Gaussian random variable, the confidence interval for each univariate random variable in \(\hat{w}\) is just some standard deviation away from its mean. We use the standard deviation parameter that we have computed above to calculate the confidence interval. For the mean, we use each elements in the \(w_{opt}\) vector.
T-statistic and \(P > t\)
These two metrics measure how likely the mean of the parameter is \(0\). Having a \(0\) mean indicates that the feature does not contribute to predicting the target variable \(Y\). The \(P > t\) is the p-value telling us how far is our mean parameter from \(0\), represented by t-statistics. High p-value tells us that the parameter is unlikely to be meaningful for the prediction, whereas low p-value tells us that the parameter is likely to have high contribution to the prediction.
We calculate the t-statistics of the feature by:
\[t_j = \frac{\mu_j - 0}{\eta_j}\]where \(\mu_j\) is the j-th feature mean and \(\eta_j\) is the j-th standard deviation of the j-th feature. To get the p-value of the j-th feature we evaluate the t-statistics under \(\mathcal{N}(0,1)\)
Closing
There were more stuff going on under linear regression that I hadn’t realized before. I hope this post can help you in understanding where does the probabilistic metrics came from.


Why Boris Johnson must publish Russia report
by LettersA Tory PM is suppressing evidence by the intelligence agencies about the activities of hostile forces, says Richard Norton-Taylor, and Adrian Cosker says there will be a permanent question mark over the validity of recent elections
Chris Bryant rightly reminds us of Russian cyber-attacks on targets here and how Conservative governments have allowed Russian “dirty money” to enter the country as he called on Boris Johnson to come clean and publish the cross-party intelligence and security committee’s report on Kremlin meddling in Britain (Tories ‘have deliberate amnesia’ over Russia’s UK meddling, 14 November).
If Jeremy Corbyn had blocked a parliamentary report on attempts by Putin’s Russia to interfere in British politics, we could be sure that opposition MPs, egged on by large sections of the media, would seize on it as evidence that we cannot trust the Labour leader to protect Britain’s national security. A Conservative prime minister is now suppressing evidence given to the committee by the intelligence agencies about the activities of hostile forces. Perhaps we should ask whether a Johnson government can be trusted with protecting our security.
Richard Norton-Taylor
London
• Can I urge the Guardian to support Marina Litvinenko’s legal action for the urgent and full publication of the report on Russian interference in our elections (Litvinenko’s widow to sue over release of Russia report, 16 November)? We also need to know now if there are any lawful means by which Mr Johnson could possibly suppress publication of the report if he gains a majority in parliament. If so, it is all the more vital that the report is released before the election, otherwise there will be a permanent question mark over the validity not only of 2016 and 2107 votes, but also over this election. And the nation will become perhaps even more bitterly divided than at present, with the legitimacy of the referendum – and of any mandate Mr Johnson might get – put in doubt.
Adrian Cosker
Hitchin, Hertfordshire
• Join the debate – email<EMAIL_ADDRESS>• Read more Guardian letters – click here to visit gu.com/letters
• Do you have a photo you’d like to share with Guardian readers? Click here to upload it and we’ll publish the best submissions in the letters spread of our print edition


BOX OF MOONLIGHT
A Film Review by James Berardinelli
RATING (0 TO 10): 6.5 Alternative Scale: **1/2 out of ****
United States, 1997 U.S. Release Date: 8/8/97 (limited) Running Length: 1:50 MPAA Classification: R (Nudity, profanity, violence) Theatrical Aspect Ratio: 1.85:1
Cast: John Turturro, Sam Rockwell, Catherine Keener, Lisa Blount, Annie Corley Director: Tom DiCillo Producers: Thomas A. Bliss, Marcus Viscidi Screenplay: Tom DiCillo Cinematography: Paul Ryan Music: Jim Farmer U.S. Distributor: Trimark Pictures
Tom DiCillo's offbeat BOX OF MOONLIGHT is a film that I wanted to like a great deal more than I actually did. DiCillo is one of those few quirky directors who loves to play with both his audience and his subject matter. Unfortunately, all the little twists, turns, and tweaks in BOX OF MOONLIGHT can't eclipse the fact that it's basically nothing more than a combination mid-life crisis/buddy movie. There are number of enchanting scenes, but, in concert, they somehow fail to gel into a magical whole.
The central problem with BOX OF MOONLIGHT may be that it loses its direction. This is a malady that neither of DiCillo's previous movies suffered. The film maker's first effort, JOHNNY SUEDE (starring a then- unknown Brad Pitt) possessed the same dreamlike quality evident here, but it knew exactly where it was going. LIVING IN OBLIVION, a brilliant satire of independent film making, was tightly written from beginning to end. BOX OF MOONLIGHT, on the other hand, starts out strong, then starts to wander during the second half. Rather than building to a satisfying conclusion, the movie sort of fizzles out, leaving behind the impression that, even though it was a long 110 minutes, something was missing.
BOX OF MOONLIGHT opens with John Turturro playing Al Fountain, the kind of uptight boss whom everyone equally despises and pities. Al, an electrical engineer "specializing in the field distribution of Zeus turbine engines," is in charge of a crew of hard-working men involved in the construction of a windshield wiper plant in Drip Rock, Tennessee.  The group's foreman, Soapy (Ray Aranha), feels sorry for Al and invites him to a poker game, but, when the boss shows up ready to hobnob with the men, he overhears a barrage of disparaging comments that sends him scurrying back to his hotel room.
The job in Drip Rock ends abruptly, and Al finds himself alone in the middle of nowhere with nothing to do. Instead of returning home to his wife and son, he decides to take a journey to Lake Splatchee, an idyllic park where he spent a wonderful summer as a child. Al's intention is to re-discover himself, but Lake Splatchee has turned into a chemical waste dump, and that further disheartens him. Then he runs into the Kid (Sam Rockwell). A freespirit with a Davy Crockett outfit (complete with coonskin cap) and a busted distributor under his hood, the Kid prevails on Al for a little automobile assistance. What starts out as a chance encounter turns into a several day odyssey that includes skinnydipping, a tomato fight, a bar brawl, and a flirtatious picnic with a phonesex girl (Catherine Keener) and her sister (Lisa Blount).
There are moments when BOX OF MOONLIGHT is a joy to sit through, but the disjointed film never generates any momentum. It has its share of strange characters and odd moments, such as when Al sees things moving backwards in time (for example, water being sucked out of a glass back into the pitcher), but they don't amount to much. The movie is assembled like a series of episodes, and that's is part of the problem. DiCillo seems to be constantly changing his mind about what he wants to accomplish.
The primary goal of BOX OF MOONLIGHT is to show Al's redemption through his relationship with the Kid. One is constricted by convention; the other has no respect for rules. Obviously, each has something to teach the other. It's an old plot, but DiCillo keeps it interesting. In the final third, however, two female characters are introduced, and, while they add a little spice to the proceedings, they ultimately dilute the focus. Suddenly, it's not just one damaged human being we're dealing with, but several, and DiCillo doesn't have the time to develop the potentially interesting sisters into more than half- characters.
John Turturro, who has played his share of unusual roles in unconventional films (take BARTON FINK, for example), is superb. The temptation in a part like this is to go a little over-the-top and add some caricature to Al's personae. Turturro avoids the trap, remaining true to his screen identity. As a result, it requires little effort to sympathize with him. Sam Rockwell, although solid in his portrayal of the Kid, lacks his co-star's mastery. While Rockwell displays boundless energy and enthusiasm, his reading of the character isn't as deep as Turturro's. Lisa Blount and DiCillo regular Catherine Keener (WALKING AND TALKING) are on hand in supporting roles, and Dermot Mulroney (the title character in MY BEST FRIEND'S WEDDING) has a two-scene cameo.
It would be hard to classify BOX OF MOONLIGHT as unsuccessful, since it represents a pleasantly diverting two hours. On the other hand, given DiCillo's impressive (albeit short) track-record, I was a little disappointed by what's on-screen. In the final analysis, BOX OF MOONLIGHT is a relatively standard, unambitious story with a few neat quirks, but it isn't nearly as delightful as the title indicates.
Copyright 1997 James Berardinelli
- James Berardinelli e-mail<EMAIL_ADDRESS>ReelViews web site: http://www.cybernex.net/~berardin
"A film is a petrified fountain of thought." - Jean Cocteau
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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{% extends 'epi/exposure_detail.html' %} {% block content %} {{ block.super }} {% include "hawc/_delete_block.html" with name="exposure" notes="" %} {% endblock content %}


Welcome!
Choose the function you would like to use:
Select Column and
Save Column Data
Select an Input and
Enter Saved Data
Use Scan Function
for Saved Data


{% comment %}
# Copyright 2010 by Google Inc
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
{% endcomment %}
{% extends "map.html" %}
{% load i18n %}
{% block home-link %}
{% include "home_link.html" %}
{% endblock home-link %}
{% comment %}
# Remove print link
{% endcomment %}
{% block print-link %}
{% endblock print-link %}
{% block stylesheets %}
{{block.super}}
{% endblock stylesheets %}
{% comment %}
# Remove language selector
{% endcomment %}
{% block language-select %}
{% endblock language-select %}
{% block title %}
{% comment %}
#i18n: Name of the application.
{% endcomment %}
{% trans "Resource Finder" %}
{% endblock title %}
{% block print-summary %}
{% comment %}
#i18n: Total number of facilities shown on the map.
{% endcomment %}
{% trans "Total facilities" %}
{% comment %}
#i18n: Header for the number of facilities less than 10 miles from
#i18n: a location.
{% endcomment %}
{% trans "no more than 10 miles away" %}
{% comment %}
#i18n: Header for the number of facilities with available beds.
#i18n: OK to translate without the 'and' if it makes more sense
{% endcomment %}
{% trans "and with availability." %}
{% endblock print-summary %}
{% block data %}
{% comment %}
# Use nested tables here so that we can have two different thead sections
# that show up on every new page when printed (on modern browsers)
{% endcomment %}
{% comment %}
#i18n: Name of the application.
{% endcomment %}
{% trans "Resource Finder" %}
{% comment %}
#i18n: Heading for number of available beds and number
#i18n: of total beds in a hospital.
{% endcomment %}
{% trans "Beds open / total" %}
{% comment %}
#i18n: Header for a place that provides a particular service
{% endcomment %}
{% trans "Facility" %}
{% comment %}
#i18n: Header for a distance from the current subject to
#i18n: another location
{% endcomment %}
{% trans "Distance" %}
{% comment %}
#i18n: Header for a street address
{% endcomment %}
{% trans "Address" %}
{% comment %}
#i18n: Header for general information about a subject
{% endcomment %}
{% comment %}
#i18n: Explains how to correct incorrect information that has been printed.
{% endcomment %}
{% trans "If any information is wrong or missing, please correct it on the web site:" %}


Sub-Org name is required.
Enter a valid email address.
{$ error_message $}
Note 1: Sub-organizations can not be deleted.
Note 2: Parent organization members are not automatically made members of sub-organizations.


Hi! Please just call me Ken. I am currently working on my bachelor's degree at Bellevue College. I code in C#, JavaScript, and T-SQL.


Where I am right now...
Currently at iO Academy in beautiful Bath studying the Full-Stack track path.
A bit about me...
I have an exciting new direcetion in my life, currently I am studying to become a Full-Stack web developer at iO Academy in Bath where I will learn about front-end and back-end development. I have a passion for learning new skills, and wish to develop these every day.
I love designing and making things.
My story starts just over a year ago, I wanted to learn, more, something new and I discovered a passion for coding, I investigated with a little self-education at home before signing up to Bath college where I took evening classes in HTML and CSS. In addition to growing my web development skills, I previously had experience of working in a small group where I enjoyed sharing ideas, knowledge and feedback with others. I hope this, along with my determination and passion for creativity will help drive me forward in my new career as a Full-Stack web developer.
In my spare time I enjoy baking, hiking outside, gaming and exercise (yep!)


Simple Cookie Consent
This page is an example of a simple Cookie Consent Management pop-up built using JavaScript to work in alongside Google Tag Manager (GTM).
Don't see the pop-up? You may have already accepted/declined it. Use the button below to trigger it again.
Test This Page
This page is firing three Custom HTML tags via GTM, which log a message in the developer console.
- One tag fires on all page views.
- One tag fires only on page views with cookies allowed. (This tag also fires when fresh consent is given)
How it works
This consent pop-up uses JavaScript alongside GTM. It allows setting up GTM tags to only fire if consent is true. A full tutorial and walk-through of this is available on my blog. Check the console log to see which tags fired.
Source Code
This cookie consent pop-up mechanism is fairly simple and easy to use and understand. Find the full source code on GitHub.


Q: Snapshots seem to be working. Why am I getting SnapshotMissingException
messages?edit
A: A load balancer, or other network fixture could be timing out your connection.edit
A gateway, proxy, or load balancer timeout will usually result in 504 HTTP responses:
- 504 Gateway Timeout
- The server, while acting as a gateway or proxy, did not receive a timely response from the upstream server specified by the URI (e.g. HTTP, FTP, LDAP) or some other auxiliary server (e.g. DNS) it needed to access in attempting to complete the request.
An easy way to check is to change the loglevel to DEBUG and look for 504 errors and long requests, like these:
2015-04-02 13:18:37,702 DEBUG urllib3.connectionpool _make_request:368 "PUT /_snapshot/my_backup_s3_repository/curator-20150402121735?wait_for_completion=true HTTP/1.1" 504 0 2015-04-02 13:18:37,703 WARNING elasticsearch log_request_fail:81 PUT /_snapshot/my_backup_s3_repository/curator-20150402121735?wait_for_completion=true [status:504 request:59.777s]
Note the status:504
and the request:59.777s
at the right end of the line.
In the case of these error messages, it turned out to be an AWS load balancer that had a 60 second timeout for connections. The fix was to increase the timeout. Another potential resolution would be to have Curator connect to a client directly, rather than through a load balancer or proxy.
You will need to set blacklist: []
in your
configuration file to catch these 504 errors, as they are
filtered by default.


Which Christmas Movie Shall I Watch? Why choose a Christmas movie yourself? Let me do it for you. Commence Christmas


{% extends "public/templates/public_template.html" %} {% block title %} SNP TOOL - Ayuda {% endblock %} {% block main %}
| * | Término | Descripción | SO accession | Display term | IMPACTO |
|---|---|---|---|---|---|
| transcript_ablation | Una ablación de características mediante la cual la región eliminada incluye una característica de transcripción. | SO:0001893 | Transcript ablation | ||
| stop_gained | A sequence variant whereby at least one base of a codon is changed, resulting in a premature stop codon, leading to a shortened transcript | SO:0001587 | Stop gained | ||
| frameshift_variant | A sequence variant which causes a disruption of the translational reading frame, because the number of nucleotides inserted or deleted is not a multiple of three | SO:0001589 | Frameshift variant | ||
| stop_lost | A sequence variant where at least one base of the terminator codon (stop) is changed, resulting in an elongated transcript | SO:0001578 | Stop lost | ||
| start_lost | A codon variant that changes at least one base of the canonical start codon | SO:0002012 | Start lost | ||
| transcript_amplification | A feature amplification of a region containing a transcript | SO:0001889 | Transcript amplification | ||
| inframe_insertion | An inframe non synonymous variant that inserts bases into in the coding sequence | SO:0001821 | Inframe insertion | ||
| inframe_deletion | An inframe non synonymous variant that deletes bases from the coding sequence | SO:0001822 | Inframe deletion | ||
| missense_variant | A sequence variant, that changes one or more bases, resulting in a different amino acid sequence but where the length is preserved | SO:0001583 | Missense variant | ||
| protein_altering_variant | A sequence_variant which is predicted to change the protein encoded in the coding sequence | SO:0001818 | Protein altering variant | ||
| splice_region_variant | A sequence variant in which a change has occurred within the region of the splice site, either within 1-3 bases of the exon or 3-8 bases of the intron | SO:0001630 | Splice region variant | ||
| incomplete_terminal_codon_variant | A sequence variant where at least one base of the final codon of an incompletely annotated transcript is changed | SO:0001626 | Incomplete terminal codon variant | ||
| start_retained_variant | A sequence variant where at least one base in the start codon is changed, but the start remains | SO:0002019 | Start retained variant | ||
| stop_retained_variant | A sequence variant where at least one base in the terminator codon is changed, but the terminator remains | SO:0001567 | Stop retained variant | ||
| synonymous_variant | A sequence variant where there is no resulting change to the encoded amino acid | SO:0001819 | Synonymous variant | ||
| coding_sequence_variant | A sequence variant that changes the coding sequence | SO:0001580 | Coding sequence variant | ||
| mature_miRNA_variant | A transcript variant located with the sequence of the mature miRNA | SO:0001620 | Mature miRNA variant | ||
| 5_prime_UTR_variant | A UTR variant of the 5' UTR | SO:0001623 | 5 prime UTR variant | ||
| 3_prime_UTR_variant | A UTR variant of the 3' UTR | SO:0001624 | 3 prime UTR variant | ||
| non_coding_transcript_exon_variant | A sequence variant that changes non-coding exon sequence in a non-coding transcript | SO:0001792 | Non coding transcript exon variant | ||
| intron_variant | A transcript variant occurring within an intron | SO:0001627 | Intron variant | ||
| NMD_transcript_variant | A variant in a transcript that is the target of NMD | SO:0001621 | NMD transcript variant | ||
| non_coding_transcript_variant | A transcript variant of a non coding RNA gene | SO:0001619 | Non coding transcript variant | ||
| upstream_gene_variant | A sequence variant located 5' of a gene | SO:0001631 | Upstream gene variant | ||
| downstream_gene_variant | A sequence variant located 3' of a gene | SO:0001632 | Downstream gene variant | ||
| TFBS_ablation | A feature ablation whereby the deleted region includes a transcription factor binding site | SO:0001895 | TFBS ablation | ||
| TFBS_amplification | A feature amplification of a region containing a transcription factor binding site | SO:0001892 | TFBS amplification | ||
| TF_binding_site_variant | A sequence variant located within a transcription factor binding site | SO:0001782 | TF binding site variant | ||
| regulatory_region_ablation | A feature ablation whereby the deleted region includes a regulatory region | SO:0001894 | Regulatory region ablation | ||
| regulatory_region_amplification | A feature amplification of a region containing a regulatory region | SO:0001891 | Regulatory region amplification | ||
| feature_elongation | A sequence variant that causes the extension of a genomic feature, with regard to the reference sequence | SO:0001907 | Feature elongation | ||
| regulatory_region_variant | A sequence variant located within a regulatory region | SO:0001566 | Regulatory region variant | ||
| feature_truncation | A sequence variant that causes the reduction of a genomic feature, with regard to the reference sequence | SO:0001906 | Feature truncation | ||
| intergenic_variant | A sequence variant located in the intergenic region, between genes | SO:0001628 | Intergenic variant |


2.7. StringsStrings in Python are identified as a contiguous set of characters in between quotation marks. Python allows for either pairs of single or double quotes. Triple quotes (three consecutive single or double quotes) can be used to escape special characters. Subsets of strings can be taken using the index ( [ ] ) and slice ( [ : ] ) operators, which work with indexes starting at 0 in the beginning of the string and working their way from -1 at the end. The plus ( + ) sign is the string concatenation operator, and the asterisk ( * ) is the repetition operator. Here are some examples of strings and string usage: >>> pystr = 'Python'
>>> iscool = 'is cool!'
>>> pystr[0]
'P'
>>> pystr[2:5]
'tho'
>>> iscool[:2]
'is'
>>> iscool[3:]
'cool!'
>>> iscool[-1]
'!'
>>> pystr + iscool
'Pythonis cool!'
>>> pystr + ' ' + iscool
'Python is cool!'
>>> pystr * 2
'PythonPython'
>>> '-' * 20
'--------------------'
>>> pystr = '''python
... is cool'''
>>> pystr
'python\nis cool'
>>> print pystr
python
is cool
>>> You can learn more about strings in Chapter 6. |


Back
Accept and return to overview I want to update the details
{% endblock %}
Payment
Payment by direct debit on the day after the completion of the repairs.
Claimant should make sure the defendant knows their bank details...?
Accept and return to overview I want to update the details


First doc patch in on Ruby trunk. Wahoo! Thanks to @avdi for his excellent screencast showing how straightforward the process was!
1/21/2014, 8:49:01 AM
Favs: 4
Retweets: 1
link--- layout: tweet ---
First doc patch in on Ruby trunk. Wahoo! Thanks to @avdi for his excellent screencast showing how straightforward the process was!
1/21/2014, 8:49:01 AM
Favs: 4
Retweets: 1
link


Jason R Hicks
|
Web Developer
Software Developer
Music Lover
All Around Geek
Dad
skills to pay the bills
Home
My Work
Projects
About
Contact


|
Simulino 2000
1.0
2D physics engine with CUDA integration
|
#include <CEntity.h>
Public Member Functions | |
| CEntity (unsigned int id_, std::unique_ptr< IMoveable > moveable_, std::unique_ptr< IDrawable > drawable_) | |
| CEntity (const CEntity &other_) | |
| CEntity & | operator= (const CEntity &rhs) |
| virtual | ~CEntity () |
| void | SetId (unsigned int id_) |
| unsigned int | GetId () const |
| virtual bool | IsHit (const C2DVector &coords_) const |
| virtual void | HandleMouseButtonDown (std::shared_ptr< C2DVector > cursor_position_) |
| virtual void | HandleMouseButtonUp (std::shared_ptr< C2DVector > cursor_position_) |
| virtual void | Update (const C2DVector &external_force_, float dt) |
| virtual void | Draw () const |
Protected Attributes | |
| unsigned int | m_id |
| std::unique_ptr< IMoveable > | mp_moveable |
| std::unique_ptr< IDrawable > | mp_drawable |
CEntity defines the interface of the entities populating the game/simulation.
| CEntity::CEntity | ( | const CEntity & | other_) |
|
virtual |
|
virtual |
Draw renders the Entity if an IDrawable is available
Reimplemented in CEntityGalaxy, CEntityCloth, and CEntityParticle.
|
inline |
|
inlinevirtual |
Reimplemented in CEntityGalaxy, CEntityParticle, CEntityCloth, and CEntityButton.
|
inlinevirtual |
Reimplemented in CEntityGalaxy, CEntityParticle, CEntityCloth, and CEntityButton.
|
virtual |
Reimplemented in CEntityButton.
|
inline |
|
inlinevirtual |
Update should be overridden and called if the Entity is subject to external forces and has an IMoveable
Reimplemented in CEntityGalaxy, CEntityCloth, and CEntityParticle.
|
protected |
|
protected |
|
protected |


|
libARSAL
1.0
|
| ARSAL.h | Library global header for libARSAL |
| ARSAL_BLEManager.h | Private headers of BLE manager allow to use Bluetooth low energy api's |
| ARSAL_CentralManager.h | |
| ARSAL_Endianness.h | This file contains headers about endianness abstraction layer |
| ARSAL_Error.h | |
| ARSAL_Ftw.h | LibARSAL Ftw header file |
| ARSAL_MD5_Manager.h | |
| ARSAL_Mutex.h | This file contains headers about mutex abstraction layer |
| ARSAL_Print.h | This file contains headers about debug print abstraction layer |
| ARSAL_Sem.h | This file contains headers about semaphore abstraction layer |
| ARSAL_Singleton.h | Headers to define singletons |
| ARSAL_Socket.h | This file contains headers about socket abstraction layer |
| ARSAL_Thread.h | This file contains headers about thread abstraction layer |
| ARSAL_Time.h | This file contains headers about time abstraction layer |


public class ArrayOperator
extends java.lang.Object
ArrayOperation
includes frequently used operation
functions on double
arrays. The argument vector is
required to have been allocated memory before being used in
the array operations.| Constructor and Description |
|---|
ArrayOperator() |
| Modifier and Type | Method and Description |
|---|---|
static double[] |
allocate1DArray(int n)
Allocate continuous memory block for a 1D
double
array. |
static double[] |
allocate1DArray(int n,
double v)
Allocate continuous memory block for a 1D
double
array and assign all elements with a given value. |
static double[][] |
allocate2DArray(int m,
int n)
Allocate a 2D
double array and assign all
elements with zero by default. |
static double[][] |
allocate2DArray(int m,
int n,
double v)
Allocate a 2D
double array and assign all
elements with a given value. |
static int[] |
allocateIntegerVector(int n)
Allocate continuous memory block for a 1D
int
array. |
static int[] |
allocateIntegerVector(int n,
int v)
Allocate continuous memory block for a 1D
int
array. |
static double[][] |
allocateMatrix(int nRows,
int nCols)
Allocate memory for a 2D
double array. |
static double[] |
allocateVector(int n)
Allocate continuous memory block for a 1D
double
array. |
static double[] |
allocateVector(int n,
double v)
Allocate continuous memory block for a 1D
double
array and assign all elements with a given value. |
static int |
argmax(double[] V)
Compute the maximum argument.
|
static void |
assignIntegerVector(int[] V,
int v)
Assign a 1D
int array by a real scalar. |
static void |
assignVector(double[] V,
double v)
Assign a 1D
double array by a real scalar. |
static void |
assignVector(double[] V1,
double[] V2)
Element-wise assignment operation.
|
static void |
clearMatrix(double[][] M)
Clear all elements of a 2D
double array to zero. |
static void |
clearVector(double[] V)
Clear all elements of a 1D
double array to zero. |
static void |
divideAssign(double[] V,
double v)
Element-wise division and assignment operation.
|
static void |
divideAssign(double[] V1,
double[] V2)
Element-wise division and assignment operation.
|
static double |
innerProduct(double[] V1,
double[] V2)
Inner product of two vectors, i.e.,
|
static double[] |
minus(double[] V1,
double[] V2)
Element-wise subtraction.
|
static void |
minusAssign(double[] V,
double v)
Element-wise subtraction and assignment operation.
|
static void |
minusAssign(double[] V1,
double[] V2)
Element-wise subtraction and assignment operation.
|
static void |
minusAssign(int[] V,
int v)
Element-wise subtraction and assignment operation.
|
static double[] |
operate(double[][] A,
double[] V)
res = A * V;
|
static double[] |
operate(double[] V,
double[][] A)
res' = V' * A
|
static void |
operate(double[] V1,
double[][] A,
double[] V2)
V1 = A * V2.
|
static void |
operate(double[] V1,
double[] V2,
double[][] A)
V1' = V2' * A.
|
static double[] |
plus(double[] V1,
double[] V2)
Element-wise addition.
|
static void |
plusAssign(double[] V,
double v)
Element-wise addition and assignment operation.
|
static void |
plusAssign(double[] V1,
double[] V2)
Element-wise addition and assignment operation.
|
static double |
sum(double[] V)
Compute the sum of a 1D
double array. |
static void |
sum2one(double[] V)
Sum a 1D
double array to one, i.e., V[i] = V[i] / sum(V). |
static double[] |
times(double[] V1,
double[] V2)
Element-wise multiplication.
|
static void |
timesAssign(double[] V,
double v)
Element-wise multiplication and assignment operation.
|
static void |
timesAssign(double[] V1,
double[] V2)
Element-wise multiplication and assignment operation.
|
public static int argmax(double[] V)
V
- a double
arraypublic static void assignVector(double[] V, double v)
double
array by a real scalar.V
- a 1D double
arrayv
- a real scalarpublic static void assignIntegerVector(int[] V, int v)
int
array by a real scalar.V
- a 1D int
arrayv
- a real scalarpublic static void clearVector(double[] V)
double
array to zero.V
- a double
arraypublic static void clearMatrix(double[][] M)
double
array to zero.M
- a 2D double
arraypublic static double[] allocate1DArray(int n)
double
array.n
- number of elements to be allocateddouble
array of length npublic static double[] allocate1DArray(int n, double v)
double
array and assign all elements with a given value.n
- number of elements to be allocatedv
- a real scalar to assign the 1D double
arraydouble
array of length npublic static double[] allocateVector(int n)
double
array.n
- number of elements to be allocateddouble
array of length npublic static double[] allocateVector(int n, double v)
double
array and assign all elements with a given value.n
- number of elements to be allocatedv
- a real scalar to assign the 1D double
arraydouble
array of length npublic static double[][] allocate2DArray(int m, int n, double v)
double
array and assign all
elements with a given value.m
- number of rowsn
- number of columnsv
- a real scalardouble
arraypublic static double[][] allocate2DArray(int m, int n)
double
array and assign all
elements with zero by default.m
- number of rowsn
- number of columnsdouble
arraypublic static int[] allocateIntegerVector(int n)
int
array.n
- number of elements to be allocatedint
array of length npublic static int[] allocateIntegerVector(int n, int v)
int
array.n
- number of elements to be allocatedv
- an integer to initialize the vectorint
array of length npublic static double[][] allocateMatrix(int nRows, int nCols)
double
array.nRows
- number of rowsnCols
- number of columnsdouble
arraypublic static void divideAssign(double[] V, double v)
V
- a 1D double
arrayv
- a real scalarpublic static void divideAssign(double[] V1, double[] V2)
V1
- a 1D double
arrayV2
- a 1D double
arraypublic static void timesAssign(double[] V, double v)
V
- a 1D double
arrayv
- a real scalarpublic static void timesAssign(double[] V1, double[] V2)
V1
- a 1D double
arrayV2
- a 1D double
arraypublic static double sum(double[] V)
double
array.V
- a 1D double
arraypublic static void sum2one(double[] V)
double
array to one, i.e., V[i] = V[i] / sum(V).V
- a 1D double
arraypublic static void plusAssign(double[] V, double v)
V
- a 1D double
arrayv
- a real scalarpublic static void plusAssign(double[] V1, double[] V2)
V1
- a 1D double
arrayV2
- a 1D double
arraypublic static void minusAssign(int[] V, int v)
V
- a 1D int
arrayv
- an integerpublic static void minusAssign(double[] V, double v)
V
- a 1D double
arrayv
- a real scalarpublic static void minusAssign(double[] V1, double[] V2)
V1
- a 1D double
arrayV2
- a 1D double
arraypublic static void assignVector(double[] V1, double[] V2)
V1
- a 1D double
arrayV2
- a 1D double
arraypublic static double[] operate(double[][] A, double[] V)
A
- a 2D double
arrayV
- a 1D double
arraypublic static void operate(double[] V1, double[][] A, double[] V2)
V1
- a 1D double
arrayA
- a 2D double
arrayV2
- a 1D double
arraypublic static double[] operate(double[] V, double[][] A)
V
- a 1D double
arrayA
- a 2D double
arraypublic static void operate(double[] V1, double[] V2, double[][] A)
V1
- a 1D double
arrayV2
- a 1D double
arrayA
- a 2D double
arraypublic static double innerProduct(double[] V1, double[] V2)
V1
- a 1D double
arrayV2
- a 1D double
arraypublic static double[] times(double[] V1, double[] V2)
V1
- a 1D double
arrayV2
- a 1D double
arraypublic static double[] plus(double[] V1, double[] V2)
V1
- a 1D double
arrayV2
- a 1D double
arraypublic static double[] minus(double[] V1, double[] V2)
V1
- a 1D double
arrayV2
- a 1D double
array


Calcium Citrate (E333,CAS no.5785-44-4 HS code291815) is the calcium salt of citric acid, available as Fine white powder.
Calcium Citrate (E333,CAS no.5785-44-4 HS code291815) is the calcium salt of citric acid, available as Fine white powder. Calcium Citrate along with citric acid, Sodium Citrate, Magnesium Citrate, Potassium Citrate is widely used as food acidity regulator. Calcium Citrate is also used as preservative in food.
Calcium citrate is also found in some dietary calcium supplements (e.g. Citracal). Calcium makes up 24.1% of calcium citrate (anhydrous) and 21.1% of calcium citrate (tetrahydrate) by mass. The tetrahydrate occurs in nature as the mineral Earlandite.
| ITEM | STANDARD |
| Appearance | Colorless or white crystal |
| Content,% | 97.5-100.5 |
| Arsenic ≤% | 0.0003 |
| Fluorine ≤% | 0.003 |
| Heavy metals(As Pb) ≤% | 0.002 |
| Lead ≤% | 0.001 |
| Loss on drying,% | 10.0-13.3 |
| Acid-insoluble substance≤% | 0.2 |
| Alkalinity | According with the test |
| Easy carbony substance | According with the test |
| Identification A | Meet the erquirement |
| Identification B | Meet the erquirement |
| Mercury ≤ PPM | 1 |
| Yeast ≤ | 10/g |
| Mold ≤ | 10/g |
| E.Coli | Absendt in 30g |
| Salmonella | Absendt in 25g |
Calcium Citrate is a Calcium salt widely used as acidity regulator and preservative in food and beverage. As a acidity regulator and preservative, Calcium Citrate can be used in a wide variety of industries including: food production, beverage, pharmaceutical, and various other industries.
Shipping items: Shipping items will be delivered by international express like EMS, TNT, UPS, FedEx or DHL after receiving received. Every item will be shipped out in 1-2working days after the payment is done. The product usually arrives in 1-4 days based on the different destination, and online track is provided. Please kindly supply the shipping address, contact and tel number for successful shipment.
Calcium Citrate is widely used as acidulants in food and beverage industries. food grade Calcium Citrate is available as fine powder(more than 97.5% purity)
Calcium Citrate gluten freeYes. Calcium Citrate is gluten free and widely used in gluten free food to provide fresh acidic taste to soft drinks.
Halal Certified Calcium CitrateCalcium Citrate is the calcium salt of citric acid, available as Fine white powder. As a synthesized chemical, Calcium Citrate is general recognized as halal. We will still audit another 2 key points to make sure that our Calcium Citrate is 100% halal: Are there any pig products used in manufacturing process of this ingredient? Does the ingredient contain Alcohol (impure) or other haraam ingredients?
Price: Please let us know the quantity you required, because for small order and bulk purchase, the price will be difference.
Payment: Western Union, MoneyGram We will supply the receivers information or the bank account information for payment use.


Hey you! My is Diogenes I'm 28 years old computer scientist with more than 5 years of work experience in crafting innovative and sustainable products that really love 4 things in the world: learn about products and frameworks, enjoy a beach on sunset, play tennis (not a Alcaraz, buut we try!) and last but not least, coding, be games or alternative projects.
As a new job growing fast in every tech companies, the product operations brazil community represents an effort to bring discussions and evolve this area in in our realities. Some of my responsibilities are:
Previously knew as Hotel Urbano, is one of the biggest OTAs(Online Travel Agency) in LATam that offers a wide range of travel services. As Product Operations, my challenge is support the evolutio of Product Team and Product mindset in the company. Some of my responsibilities are:
As Product Operations, a crucial part of our role in onboarding product teams and day-to-day work is training, maintenance, and evolution of the technologies that the team uses, as well as establishing best practices of governance that involve them.
DetailsI've been lucky enough to have my work featured on courses, events, mentorships and papers sharing my love for teach and learn about products, people and processes.
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Be through offering my it we strained in lose she in decided sufficient usual. It blind of tuned it from the actual leather the the a any that's got happiness live after greatest.
Be through offering my it we strained in lose she in decided sufficient usual. It blind of tuned it from the actual leather the the a any that's got happiness live after greatest.
Be through offering my it we strained in lose she in decided sufficient usual. It blind of tuned it from the actual leather the the a any that's got happiness live after greatest.
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module SycLink::Infrastructure
Helper methods to setup the infrastructure for syclink
Helper methods to setup the infrastructure for syclink
Public Instance Methods
copy_file_if_missing(file, to_directory)
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Copies a file to a target directory
# File lib/syclink/infrastructure.rb, line 15 def copy_file_if_missing(file, to_directory) unless File.exists? File.join(to_directory, File.basename(file)) FileUtils.cp(file, to_directory) end end
create_directory_if_missing(directory)
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Creates a directory if it does not exist
# File lib/syclink/infrastructure.rb, line 8 def create_directory_if_missing(directory) unless File.exists? directory Dir.mkdir directory end end
html_file(directory = '.', website)
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Creates an html filename to save the html representation of the website to
# File lib/syclink/infrastructure.rb, line 38 def html_file(directory = '.', website) File.join(directory, "#{website.downcase.gsub(/\s/, '-')}.html") end
load_config(file)
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Loads the configuration from a file
# File lib/syclink/infrastructure.rb, line 22 def load_config(file) unless File.exists? file File.open(file, 'w') do |f| YAML.dump({ default_website: 'default' }, f) end end YAML.load_file(file) end
yaml_file(directory = '.', website)
click to toggle source
Creates the filename of the website for saving, loading and deleting
# File lib/syclink/infrastructure.rb, line 32 def yaml_file(directory = '.', website) File.join(directory, "#{website.downcase.gsub(/\s/, '-')}.website") end


| Matrix |
Base Matrix class.
| Note: | Indexes in all matrix operation start with 1 (as you expect in mathematics) not with 0 (as you expect in C programming). So first element of a matrix is accessed as (1,1). |
As the package defines some operators for Matrix classes you can carry out complex matrix operation in the simple case as showed on follow example. Matrix<float> a(3,3),b(3,3),c(3,3); c(3,3)=a+b; c+=(b//a); cout << c.Transpose();
All operation with matrixes can be divided into some groups:
| o | construction. Allows to create a matrix from another. Matrix<float> a(2,3); Matrix<float> b(a); |
| o | size operation. Allows to retrieve and change matrix dimensions. Matrix<float> a(2,3); int columns=a.GetColumns(); a.SetDimensions(5,4); |
| o | access operation. Allows to get and set matrix elements. for(int row=1;row<=a.GetRows();row++) for(int column=1;column<=a.GetColumns();column++) a(row,column)=1; b(1,1)=a(1,2); |
| o | mathematical operation. Allows to sum, substruct, multiply two matrixes and sum a matrix with scalal. Addition matrix operations (transposition) is also provided. Matrix<float> c(2,3); c=a+b; Matrix<float> d(c*a.Transpose()); cout << d; |
Subclasses
GrowMatrix, RedundandEquationSystem, SquareMatrix, and Vector
Groups
See Also


Below are listed all available API routes together with detailed explanations of their purpose, parameters, response types and statuses, as well as potential errors.
Authenticates user by his email/password combination and returns a JWT API access token (long-term, lasting 30 days), which should be sent in the Authorization HTTP header with each subsequent request.
Parameters
User's email address, used for password recovery, important communications and sending notifications about interesting updates.
Must be unique.
User's password, used together with username for API access authentication.
Minimum length: 6 characters.
Response
JSON response containing API access_token
and
user_id
{
"data": {
"access_token": string,
"user_id": integer
}
}
Errors
Creates a new user with given account data. When using the API in the future, the user should be authenticated with the API by his username/password combination.
Parameters
User's full name, first and last names combined.
User's email address, used for password recovery, important communications and sending notifications about interesting updates.
Must be unique.
User's password, used together with username for API access authentication.
Minimum length: 6 characters.
Response
Success response
{
"success": string
}
Errors
Returns active user's profile informations, some of which are considered private (eg. email) and should not be shared other users.
Parameters
Response
User profile data
{
"data": {
"email": string,
"fullname": string,
"id": integer
}
}
Errors
Modifies user's account data and returns the modified profile informations.
If any of the user's account properties is unchanged, it can be left out from the request.
Parameters
User's full name, first and last names combined.
User's email address, used for password recovery, important communications and sending notifications about interesting updates.
Must be unique.
User's password, used together with username for API access authentication.
Minimum length: 6 characters.
Response
User profile data (after modifications).
{
"data": {
"email": string,
"fullname": string,
"id": integer
}
}
Errors
Permanently deletes user's profile, together with all of his notes and categories.
Parameters
Response
Empty response
Errors
Returns a paginated list of user's own notes.
Parameters
Index of the first requested item.
Amount of requested items to be returned in the response.
Response
User's notes
{
"data": {
"notes": [
{
"category": {
"id": integer,
"name": string
},
"date_modified": Datetime,
"id": integer,
"title": string
}
]
}
}
Errors
Returns a list of all user's categories.
Parameters
Response
User's categories
{
"data": {
"categories": [
{
"id": integer,
"name": string,
"parent": {
"id": integer,
"name": string
}
}
]
}
}
Errors
Creates a new category for the user, can be either top-level or nested. Has to have a unique name.
Parameters
Category name, visible to the user. Maximum length: 64 characters.
Parent category's name, can be left empty if the category has no parent.
Response
Success response
{
"success": string
}
Errors
Returns basic category info together with the number of notes present in the category.
Parameters
Unique category name
Response
Category info
{
"data": {
"id": integer,
"name": string,
"notes_count": integer,
"parent": {
"id": integer,
"name": string
}
}
}
Errors
Modifies category info and returns the updated representation.
Parameters
Unique category name
Category name, visible to the user. Maximum length: 64 characters.
Parent category's name, can be left empty if the category has no parent.
Response
Updated category info
{
"data": {
"id": integer,
"name": string,
"notes_count": integer,
"parent": {
"id": integer,
"name": string
}
}
}
Errors
Deletes existing category and returns an empty response.
Parameters
Unique category name
Response
Empty response
Errors
Returns a paginated list of notes belonging to the category.
Parameters
Unique category name
Index of the first requested item.
Amount of requested items to be returned in the response.
Response
Notes belonging to the category
{
"data": {
"notes": [
{
"category": {
"id": integer,
"name": string
},
"date_modified": Datetime,
"id": integer,
"title": string
}
]
}
}
Errors
Adds a new note to the user's board. Note's content
can be Markdown-formatted.
Parameters
Category name, visible to the user. Maximum length: 64 characters.
=======Unique category name
>>>>>>> Tests written, API redesigned, docs regenerated, lab doneNote's title, limited to 255 characters
Note's content, either plain text or Markdown-formatted. Unlimited length.
Response
Success response
{
"success": string
}
Errors
Returns note contents and metadata. Contents, if in Markdown format, are returned raw, so that the client can parse them at will.
Parameters
Unique category name
Unique note ID, used to identify it among all the others.
Response
Note content and info
{
"data": {
"category": {
"id": integer,
"name": string
},
"content": string,
"date_created": Datetime,
"date_modified": Datetime,
"id": integer,
"title": string
}
}
Errors
Edits note content, title or category, and returns the updated representation.
Parameters
Unique category name
Unique note ID, used to identify it among all the others.
Category name, visible to the user. Maximum length: 64 characters.
=======Note's title, limited to 255 characters
>>>>>>> Tests written, API redesigned, docs regenerated, lab doneNote's content, either plain text or Markdown-formatted. Unlimited length.
Name of note's category
Response
Updated note content
{
"data": {
"category": {
"id": integer,
"name": string
},
"content": string,
"date_created": Datetime,
"date_modified": Datetime,
"id": integer,
"title": string
}
}
Errors
Deletes an existing note and returns an empty response.
Parameters
Unique category name
Unique note ID, used to identify it among all the others.
Response
Empty response


O.T. Genasis Proves His NEVER KNEW Anthem Is Blowing Up: “I Wish I Was At This House Party”
by Biz JonesWest Coast rapper O.T. Genasis is here for the people. The hip-hop entertainer has shared new footage of people turning up to his new “Never Knew” song.
Last night, O.T. went to Instagram to share a clip of an epic house party.
I wish I was at this house party ♿
On Sunday, New York rapper 50 Cent shared his support for O.T.’s hilarious banger.
This past weekend, singer Keyshia Cole reacted to Genasis wanting a duet with her for Christmas following the song’s release.
All I want for Christmas is my duet ♿ @keyshiacole
It didn’t take long before Cole weighed-in on O.T.’s savage revamped “Love” video.


@(hosts: uk.bl.monitrix.model.KnownHostList, cappedHosts: List[String]) @import tags.{ navbar, embedParam } @main("Monitrix - Hosts") { @navbar("/hosts") } {
| Hosts by Top-Level Domain | |
| Capped Hosts (@cappedHosts.size) |
@for(host <- cappedHosts) {
@host } |
| Average Retries |
|
| Average Delay |
|
| % of Robots.txt Blocks |
|
| % of Redirects |
|


--- layout: post title: SelectMany, Sorting and Grouping Objects date: 2010-07-02 17:14:30.000000000 +02:00 categories: [] tags: - C# - LINQ status: publish type: post published: true meta: {} author: login: admin email<EMAIL_ADDRESS>display_name: Philippe first_name: Philippe last_name: Vlérick excerpt: !ruby/object:Hpricot::Doc options: {} ---
So here is the problem: I have a list of items that
var collection = new[] { new { Title = "One", References = "1;3" }, new { Title = "Two", References = "2;3" }, new { Title = "Three", References = "1;4" }, new { Title = "Four", References = "4"} };
The References fields of these object is some kind of category. What I want to do here is to have a list for each different reference (in this example: 1, 2, 3 and 4) containing all the items that are in the reference. Items will be duplicated if they are in more than one category.
To sum it up, the expected output would be: One, Three, Two, One, Two, Three, Four
After fooling around a bit, here is the query I came out with:
var query = from c in collection from d in c.References.Split(';') orderby d group c by d into groups select groups;
This does exactly what I want and produces the output I expected from the input data.
However, when I use Linq, I generally use extensions methods directly and not the pretty query syntax. This is mostly because I want to understand what happens behind the scene, and I have to admit that this query was quite a beast.
First, as there are two from clauses, there is a SelectMany somewhere. You probably know that SelectMany is a kind of the beast and that understanding it fully is quite a challenge compared to the other operators/extensions methods. Also, I thought that the GroupBy clause was going to be tough, as we groups c items by d which is in the other collection.
I couldn’t figure out by myself how to write that query using extension methods, so I fell back on the good old Reflector that gave me a straight answer:
var query = collection.SelectMany(delegate (<>f__AnonymousType0c) { return c.Values.Split(new char[] { ';' }); }, delegate (<>f__AnonymousType0 c, string d) { return new { c = c, d = d }; }).OrderBy(delegate (<>f__AnonymousType1<<>f__AnonymousType0 , string> <>h__TransparentIdentifier0) { return <>h__TransparentIdentifier0.d; }).GroupBy(delegate (<>f__AnonymousType1<<>f__AnonymousType0 , string> <>h__TransparentIdentifier0) { return <>h__TransparentIdentifier0.d; }, delegate (<>f__AnonymousType1<<>f__AnonymousType0 , string> <>h__TransparentIdentifier0) { return <>h__TransparentIdentifier0.c; }).Select(delegate (IGrouping <>f__AnonymousType0 > groups) { return groups; });
After reading that, it made much more sense. Here is what I came up with when writing it on my own:
var p = collection .SelectMany(c => c.References.Split(';'), (c, d) => new { c, d }) .OrderBy(t => t.d) .GroupBy(t => t.d, c => c.c);
Much more readable. The idea here is that the SelectMany clause outputs a sequence of anonymous types that contains the two kind of elements. This sequence is then sorted with the OrderBy, and finally fed trough a GroupBy that uses the d property as the grouping key and the c property as the project in the resulting collections. Not that difficult after all…
Here is another version that is probably a bit more clear:
var q = collection .SelectMany(c => c.References.Split(';'), (c, d) => new { Title = c.Title, Reference = d }) .GroupBy(c => c.Reference, c => c.Title) .OrderBy(g => g.Key);
Note that this is a simplified version of the original issue. The issue itself was to do this with some ListItems retrieved from SharePoint. Objects were a bit more complicated, but logic is the same.


{% extends 'base.html' %} {% block content %}
Category: {{pitch.category}}
Posted by: {{pitch.user.username}}
{{pitch.posted}}
Upvote: {{pitch.upvotes.count()}}
Downvote: {{pitch.downvotes.count()}}


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DocNote creates a paragraph with the class attribute set to "note", that starts with an info icon.
DocHint does the same as docNote, except that the class is "hint", and the icon is a lightbulb.
You can style the note or hint with this file: /css/o2mlDocStyle.css
This is a note.
or
This is a hint.