Since Gehenna annihilated all traditions and authorities anyway, the powerful, organized Clans of yore are a thing of the past. What is left is only a bunch of survivors, passing on their weaknesses and their special powers from Sire to Childer, not because it matters, but because it's in the blood. All vampiric families are now known as bloodlines: groups with no real allegiance, but who share ancestry and common traits. Some still remember the history of their origin, although almost nobody cares.
As for who's left: a few major Clans were destroyed to their last members, but on the other hand some minor lineages resurged after Gehenna, finding a more propitious habitat in the unmasqued world.
What follows is a comprehensive list of all existing bloodlines, with all you need to know about their background and their current situation.
N.B.: whenever typical attitudes are mentioned, keep in mind they are never absolute. For instance, Ventrue had a tradition of Embracing the ambitious and authoritative, but atypical members might have been chosen for whatever reason. After Gehenna, such traditions are getting more and more diluted, new Embraces depending more on a personal penchant than on fitting a lineage's stereotype.
Brujah history is a long and tormented one: once a proud Clan of warriors and scholars, equally admired for their wisdom and their strength, in recent centuries they had lost most of their past glory, Embracing rabble-rousers, rebels with or without a cause, and being used as foot soldiers by both major Sects.
As for today, they're still fuelled by their old passion, and they are the most vehement in protesting against their societal status. Due to their short temper, however, they're often regarded with some discomfort not only by mortals, but by others vampires as well, since many fear their lack of control could reflect poorly on all vampirekind.
Weakness: Brujah have a harder time resisting frenzy.
Caitiff aren't technically a bloodline. Instead, they are what happens when a vampire does not inherit the typical traits of their Sire. Once looked down as they belonged nowhere, they are now both more common and not especially despised.
Disciplines: Caitiff can choose any three of these Disciplines: Animalism, Auspex, Celerity, Dominate, Fortitude, Obfuscate, Potence, Presence, however, since they aren't especially skilled in any, they cannot start with more than two powers.
Weakness: Not being properly a bloodline, they don't suffer from any inherited weakness; before Gehenna, their lowly status was their real curse.
A small, elusive group of vampires who devote their existence to music.
Traditionally known for Embracing only women, selected for nothing else than their beautiful voices, nowadays they are more likely to make exceptions. Some argue their member should at least identify as not entirely masculine, some others would take issue at that.
Weakness: The Daughters od Cacophony are perpetually distracted by an inner music they hear constantly.
A lineage of survivors par excellance, a fair number of them saw Gehenna and got through to tell the story.
Due to their wild inclinations and disregard for material comfort, they're often intolerant to the compromises that coexistence requires, and are likely to live in the wilderness or to the fringes of society.
Exceptions exist, however, and are quite sick of being stereotyped as aggressive vagrants.
Weakness: Whenever they frenzy, the Gangrel get an animal feature, such as tufted ears, a patch of fur or feathers, a tail, etc.
The Gargoyle can be immediately recognized for their inhuman, stone-like appearance, that closely reminds the statues after which they are named.
Originally created by Clan Tremere to serve them as slaves, they had later gained some amount of freedom, although they were still despised for their lowly origin, and regarded as a threat to the Masquerade due to their obviously inhuman appearance.
Nowadays, since Clan Tremere's been wiped out by Gehenna, and the Masquerade is no concern anymore, the Gargoyle may enjoy more freedom, however, due to their grotesque appearance, they are all too often regarded as freaks and ultimately as unpeople (although most won't openly admit that).
Disciplines: Flight, Fortitude, Potence, Visceratika.
Weakness: Due to their origin, Gargoyle are more susceptible to mind control, especially by Dominate users. Additionally, they are inhuman-looking and, unlike the Nosferatu, don't have any inherent power to disguise themselves.
N.B.: unlike in V:tM canon, Embraced Gargoyles are not amnesiac.
A once obscure bloodline of scholarly tradition, whose alien appearance all but forced its members to reclusive unlives, after the Masquerade fell apart they had at least more chances to get out of their door.
Since either them or their Sires had typically hoarded vast amounts of knowledge, they are the last keepers of what little is left of vampiric history.
Weakness: Besides their freakish appearance (that's not inherently repulsive, but very obviously non-human), they are vulnerable to cold iron, which simple touch can wound them as fire would.
The most obviously cursed vampire family, the Nosferatu had become adept at hiding themselves, and anyway disguising their repulsive appearance. Before Gehenna, most of them dwelled in the sewers, working as spies and information brokers for other vampires, but being otherwise unwelcome. Even though now the Masquerade is not a concern, and other inhuman-looking vampires may show themselves around, their utter hideousness is still a cause of stigma, and most would still adopt a more acceptable appearance through their usual supernatural means. Some other, however, would make a point to display their horrid faces to the world, either to challenge prejudices or just out of spite.
Weakness: Their appearance isn't only inhuman, but horrifically deformed and repulsive.
A lineage of travellers and illusionists with their distant roots in India, the Ravnos suffered a twofold blow: first of all, their Antediluvian was the first to rise, and quite rabid against his progeny; then the few survivors were often hunted and executed by mortal authorities when their compulsions led them to illegal actions - as they quite often did. A few are still around, however; either those with more acceptable vices, or those more skilled at hiding them.
Weakness: Every Ravnos has a penchant for a specific vice - such as lying, cruelty, theft, or indulging in a severe addiction.
The Salubri's fortunes have been as uneven as you can get: an admired lineage of healers and mystics in the Dark Ages, they were later slandered by the Tremere and hunted down almost to extinction. After Gehenna, they seemed to resurge from oblivion, their feeding requirements being now a non-issue and their skills being admittedly useful.
Weakness: The Salubri cannot feed from an unwilling vessel.
Artists, hedonists and charmers, the Toreador have always been the beautiful élite of the night. Traditionally the most adept supporters of the Masquerade, the surviving Toreador however rarely miss their past existence. Their social graces, in fact, make them more accepted than most by polite society (the 'vampire friend' all hip people seem to have is more often than not a Toreador), and not having to hide means no restraint in flaunting their beautiful art - or their beautiful personas. Together with the Brujah, they're the most passionate advocates of vampire rights, and while their spirit is sometimes less idealistic, their means often prove more effective.
Weakness: When a Toreador sees something remarkably beautiful, they may fall into a state of helpless stupor until something or someone comes to distract them.
Traditionally a Clan of leaders, often uptight and business-like, the Venture who survived Gehenna are approaching their new world with their typical pragmatism, taking the chance to openly rule their businesses if nothing else. Not all of them have adapted as easily, however; the deciding factor being how easily and legitimately they could get their preferred blood.
Weakness: Every Ventrue can only feed from a very specific type of blood (such as the blood of young redheads, unrepented criminals, tennis players, aristocrats... anything as long as it's sufficiently specific). They can't get any sustenance from animal blood.


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Home » Banking & Finance » Cashkumar receives NBFC-P2P license from RBI
Cashkumar receives NBFC-P2P license from RBI
Focused exclusively on short-term loans for salaried individuals, Cashkumar to expand operations
Cashkumar, among the only P2P lending platforms focused exclusively on short term loans for salaried individuals, today announced that it has received the NBFC-P2P license from RBI (Reserve Bank of India). The license marks Cashkumar's entry to a set of four to five other leading fintech firms that have received the accreditation, ever since the national regulatory body announced guidelines for the fast growing Peer-to-Peer (P2P) lending space in October 2017.
In the Indian P2P lending ecosystem, Cashkumar has carved a unique niche for itself, by focusing only on providing loans between Rs. 20,000 to 1 lakh with tenures of 3 to 12 months and catering only to salaried individuals. In a short span since inception of P2P lending, Cashkumar has emerged as a leader within this niche, with 2 lakh+ applicants and more than 1300 loan disbursals worth over Rs.6 crores. With the RBI license in place, Cashkumar will now further expand its operations to grow to 10000+ lenders and target loan disbursals worth Rs. 45 Crores by end of FY 2018-19.
Dhiren Makhija, Co-founder of Cashkumar says, "Despite being a more recent entrant in this space, the fact that we are among the first few firms to have received the license (CoR) from RBI is an acknowledgement of our strong business model, systems, processes and regulations that we have put in place. Our recent seed round of Rs. 5 Crores, has helped us scale operations and now with the licence (CoR) from RBI, we will focus on further strengthening of our credit underwriting and technology. The licence will also help in instilling confidence amongst lenders which in turn will help scale our lender base. Our customer centric approach will continue to emphasise on introducing technology-led innovations and making financial borrowing for salaried individuals an easy and fast task".
P2P lending is still at a nascent stage in India and has disrupted the way people avail credit. With the RBI guidelines for the sector, the industry has formal recognition and no longer needs to operate in a regulatory grey area. This is expected to further accelerate growth within the space and the Indian P2P lending industry is estimated to grow to 4-5 billion USD by 2021 according to a recent Morgan Stanley report.
About Cashkumar
Conceptualised in 2016 by Dhiren Makhija, Kannan Kandappan and Yogesh Joshi, Cashkumar is one of India's leading P2P lending companies offering short term loan to borrowers. With online P2P lending becoming a valid investment route, short-term loans help people secure finances for their immediate needs and Cashkumar is at the forefront of creating an alternate channel of credit and investment.
Cashkumar
Dhiren Makhija
Kannan Kandappan
loan for salaried individuals
Yogesh Joshi

redpajama_set_name: RedPajamaCommonCrawl


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Home » News » Money Invested In Renewable Energy Is Not Enough: IRENA
Money Invested In Renewable Energy Is Not Enough: IRENA
By Saur News Bureau/ Updated On Mon, Jan 16th, 2017
Investment in renewable energy has increased dramatically in the last decade, but the rate of growth is not sufficient yet to meet the climate goals
Abu Dhabi-based green energy organization, IRENA on Sunday said money invested in renewable energy is not enough to reach a climate goal of limiting global warming to 2.0 degrees Celsius.
Investment in renewables has increased dramatically in the last decade, but "the rate of growth is not sufficient yet to meet the climate goals", Adnan Amin, the head of renewable energy agency IRENA said.
His comments come less than a week before the inauguration of US President-elect Donald Trump, a climate sceptic who has promised to "cancel" a 196-nation deal to curb global warming.
The landmark climate pact signed in December 2015 sets the goal of limiting average global warming to 2.0 degrees Celsius (3.6 degrees Fahrenheit) over pre-Industrial Revolution levels, by cutting greenhouse gases from burning fossil fuels.
Countries, including the United States, have pledged to curb emissions under the deal by shifting to renewable energy sources.
But a recent IRENA report said the current share of renewable energies in the global energy mix of 18 percent should double by 2030 to keep global warming under 2.0 degrees.
To achieve this, "investments must be scaled up from some $305 billion in 2015, to an average of $900 billion per year between 2016 and 2030," Amin said at the agency's annual conference.
Renewable energies have become drastically cheaper thanks to recent developments in technology, he said, allowing them to become a "preferred solution", even despite a decline in fossil fuel prices.
The IRENA report said solar panels "costs — now half of what they were in 2010 — could fall by another 60 percent over the next decade".
"Off-grid renewables provide electricity to an estimated 90 million people worldwide," it added.
Tags: International, IRENA, Renewable Energy, renewable energy market, Solar Cells, Solar Energy, solar inverter, Solar Market, Solar News, Solar Panels, Solar Power, Solar PV


This sure is no Disney movie.
The realities of what nature is would never make it to the big screen as a kid movie from Hollywood.
A starving polar bear vs. a walrus go head-to-head.
Both animals heavily portrayed as victims by PETA.


Our Toronto wedding videographer and cinematographer team create beautiful, visually stunning stories that truly capture your special day. From engagement, pre-wedding, love stories, to the big wedding day, our videographers are ready to capture all of the details. If you are looking for a modern look, black and white, blush or romantic, we've done it all. Have a look at our videography gallery and you will see how we used different editing styles to work best with each location. With one team and one dream in mind, we promise to capture the laughter and love of your special day for you to enjoy for years. Embark upon your once in a lifetime experience, and know that AgI will be right behind to capture every memorable second.
They say you never forget your wedding day, and with a beautifully shot wedding video that will certainly be true. Every moment of your wedding day is precious and our wedding videographers will be there to capture it all. From the intimate moments leading up to the ceremony to the joyous celebration after, wedding videography is about capturing the moment you cemented your love for you to rewatch and enjoy for years to come.
Not everyone wants to wait to see their wedding video. Same day edit videography means you can re-experience your special day before its even over! With same day edit, our wedding videographer will edit a highlight video that will allow you to play it later at your reception. Guests will be stunned to experience all of the intimate moments leading up to the event they missed out on. These short clips are a great way to wow guests and share your love story with them.
Our love story videos are customized videos that show off a couple's individual love story. Our cinematographer will take the time to learn about you, being sure to capture your personality and story. It can include anything you want, from how you met, fell in love, got engaged, and even advice from loved ones. Whether you show it at the reception or privately share it later, a personalized love story video is a great way to capture your own epic tale.
Destination weddings are always ones to remember. Destination wedding videos capture the local style and allow you to share the special day for those who couldn't make the trip, making them feel like they were right there with you. Whether it's a romantic castle in France or a tropical beach in The Bahamas, our wedding videographer will capture the beauty of the couple, the ceremony, and the location.
What is included in a normal video package?
The normal video package includes a short video and a long story. The short film is tailored to the the requirements of the guests by our professional editors. Depending on the content, the length of each film varies between 3-6 minutes. The long story is the content recorded in one day, edited chronologically, and edited into a video about an hour long or so with music for the family and guests who are not present to see the whole process of the wedding. The video will be a record of the big day for the newly-weds.
How long does it take to edit the wedding video?
It usually takes about eight weeks to edit and compile the wedding video. Once it is finished it will be delivered on a custom USB.
What do we need to do to prepare for the video shooting?
Two weeks before the wedding, we will have a final meeting with the newly-weds to go through the final process of the wedding. At that time we will make suggestions for some areas that can be improved, and this is also a good time for everyone to get to know and get familiar with each other. Once the contract is signed, you will receive a questionnaire to fill out. This questionnaire will provide you with more information and give your wedding videographer the chance to learn more about you.
Can we suggest any ideas we would like included in the video?
Of course, we are always happy to hear our clients ideas. We will try our best to achieve everything you can think of. If you feel that your idea needs some early preparation or implementation, it is better that you mention to us during the earlier meetings or when we sign the contract. You can also reference some of the pre-marriage shooting services we offer. Often times, these small details and additional shots will make your wedding more distinctive and tailored to your individual needs.
Can we include our own video clips into the wedding videos in addition to the content the videographer shoots?
Yes, of course. We will be happy to integrate video material that our clients have provide. We will carefully select the best moments and include them into the videos. These materials that have been taken in the past do not have to be high quality or taken by professional equipment. We want to see everything you can provide even if it is a dated video that is very low resolution. The bits and pieces of your life record the most important moments of the past can definitely complete the circle of your and enrich your love story videos.
What exactly is add-on shooting? Why do you recommend this add-on service?
Add on video is to get some shots before the real wedding to better show a full picture of your life and your relationship story. The add -on video will not be played on the wedding day, but will be edited with other highlight. If you are interested in playing these shots on the wedding day, then you can choose our same day edit service, where we will integrate the shots during the daytime of your wedding day and you can play it during the dinner party and show what happened during your big day to your clients. If you choose to go with the Same Day Edit combo, we will still do a highlight video.
What is a save the date package?
A save the date video is like a trailer to a movie. Instead of sending out invitations, we inform your guests by means of a video. A save the date video is usually around a minute and half. We will have a meeting with our clients to decide on a creative idea of the video and try to make it as interesting as possible. The purpose of a save the date video is to inform your guests of your wedding date.
What is a love story shooting?
A love story is different from add on shooting and save the date videos. It is an independent short film about 3 – 5 minutes long and tells the story of how the newly-weds fell in love and their life experiences. This is a record of the bride's and the groom's life before the wedding and will be edited before the big day. Shots from this package can be used in the highlight edit to add more layers to the video. The difference between love story and add-on shooting is that clients do not get an independent edited video from add-on shooting and a love story shooting usually takes longer than an add-on shooting.
Is the highlight video entirely based on the editor's own opinion? Can we come up with specific requirements?
No, the highlight video is not based solely on the editor's opinion. Usually, we will definitely confirm with the guests during the meeting if they have any specific requirements about video editing. It should be noted that the the final editing decisions would not entirely same with the clients ideas. We hope our clients can trust us with the final decisions in editing and that we will fully respect and reference the creative inputs of our clients.
Can I request a modification after receiving the film? Is there a limit on the number of modifications?
After receiving the final edit, you can require a modification up to three times. For the process to be most efficient, we kindly ask our clients to mark the timeline with the revised comments, and put all requests into one document and send to us. If you require any modifications, the more specific your description is, the better. For the long videos, the changes are more discretionary, so unless there are technical problems, we usually do not provide modification services for long videos.
I saw a video that I like on your website. Can I hire the same videographer to shoot at my wedding?
Yes, of course. If you have a preference of videographers, it works better if you inform us early so that we can help schedule that videogapher for you as soon as possible.


The polemical, theological spirit of early fundamentalism is all but dead. Modern evangelicals are too willing to downplay doctrine. Unlike our fundamentalist forebears, many today are perfectly agreeable to the suggestion that true Christianity ought to be broad enough to accommodate widely differing—even contradictory—belief systems. Many evangelicals are seeking to forge spiritual alliances with Catholicism, Eastern Orthodoxy, charismatic extremists, and even rank liberals—without regard to the fundamental doctrinal differences.
Historically, evangelicals and fundamentalists almost universally have rejected the ecumenical movement. The primary force in ecumenism has been the World Council of Churches, an organization that never really cared for biblical Christianity, preferring to recruit its membership primarily from among ultra-liberal denominations. Consequently, ecumenism has had little or no influence among evangelicals.
Even during the ecumenical movement's most prosperous era, the 1960s, evangelical churches experienced dramatic growth while ecumenical churches quickly waned. A decade ago the World Council of Churches appeared to be a monument to a lost cause.
But now the picture is changing. Incredibly, today's most powerful ecumenical forces are all under the banner of a foundering evangelicalism: the charismatic movement, Catholic-evangelical accords, cooperative mass evangelism, and a host of voices in the Christian media.
An aggressive effort is being made to divest "the fundamentals" of key evangelical distinctives. Influential voices within evangelicalism are urging us to pare back the essentials to the barest possible statement of faith, and these voices can be heard across the spectrum of evangelicalism. Appeals for broader tolerance and more inclusivism have come from charismatics, dispensationalists, Calvinists and Arminians, Reformed and Lutheran leaders—so-called evangelicals of almost every stripe.
Crouch, as one voice in an ever-growing chorus, argued that the Apostles' Creed should be the dividing line between who is in "the faith" and who is not. But does that creed offer us a definitive set of non-negotiable fundamentals for the Christian faith? And how can we be confidant in it as authoritative on these matters? We'll examine that next time.


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\section{Introduction}

Modern deep neural network (DNN) models have been used in various molecular applications, such as high-throughput screening for drug discovery \cite{gomes2017atomic, jimenez2018k, mayr2016deeptox, ozturk2018deepdta}, \textit{de novo} molecular design \cite{de2018molgan, gomez2018automatic, guimaraes2017objective, jin2018junction, kusner2017grammar, li2018learning, segler2017generating, you2018graph} and planning chemical reaction \cite{segler2018planning, wei2016neural, zhou2017optimizing}.
DNNs show comparable or sometimes better performance than traditional approaches grounded on quantum chemical theories in predicting some molecular properties \cite{faber2017prediction, gilmer2017neural, schutt2017schnet, schutt2017quantum, smith2017ani}, if a vast amount of well-qualified data is secured.
Despite the remarkable potential of DNN models, the direct use of their outputs is sometimes limited because most data in practical applications is likely to involve undesirable problems caused by the lack of both data quality and quantity.

Such data discourages a reliable statistical analysis based on DNN models, since their accuracy critically depends on training data.
For example, \citeauthor{feinberg2018spatial} mentioned that more qualified data should be provided to improve the prediction accuracy on drug-target interactions, which is a key step for drug discovery \cite{feinberg2018spatial}.
The number of ligand-protein complex samples in the PDB-bind database \cite{liu2017forging} is only about 15,000, limiting the development of reliable DNN models.
In order to prepare more qualified data, expensive and time-consuming experiments are inevitable.
Synthetic data from computations can be used as an alternative, like the Harvard Clean Energy Project set \cite{hachmann2011harvard}, but it often suffers from unintentional errors caused by approximation methods employed.
In addition, data-inherent bias and noise hurt the quality of data.
Tox21 \cite{mayr2016deeptox} and DUD-E dataset \cite{mysinger2012directory} are such examples.
The number of data in the Tox21 dataset is less than 10,000.
There are far more negative samples than positive samples.
Of various toxic types, the lowest percentage of positive samples is 2.9\% and the highest is 15.5\%.
For the DUD-E dataset, it is highly imbalanced that the number of decoy samples are almost 50 times larger than that of active samples.
All of those situations would interrupt developing reliable models.

It has been stressed in deep learning researches that uncertainty analysis is necessary to address namely the AI-safety problems. \cite{gal2016uncertainty, begoli2019need, mcallister2017concrete}
That is because even though DNNs push the bounds of data-driven approaches, they often make catastrophic decisions.
The uncertainty analysis has been performed to analyze the processes of decision making with deep neural networks.
\citeauthor{kendall2017uncertainties} studied quantitative uncertainty analysis on computer vision problems by using Bayesian neural networks (BNNs).\cite{kendall2017uncertainties}
They separated model- and data-driven uncertainties, which helps to identify the sources of prediction errors.
It is possible because Bayesian inference allows uncertainty assessments, giving probabilistic interpretations of model outputs.

In this paper, we propose to exploit BNNs to quantify uncertainties implied in molecular property predictions.
Previous studies on uncertainty quantification have regarded a predictive variance as a predictive uncertainty \cite{kendall2017uncertainties, kwon2018uncertainty}.
The predictive uncertainty can be decomposed into (i) an aleatoric uncertainty arisen from data noise and (ii) an epistemic uncertainty arisen from the incompleteness of model \cite{der2009aleatory}.
We adopt the same method in this study.
As a DNN model for molecular applications, we use augmented graph convolutional networks (GCNs) \cite{duvenaud2015convolutional, kipf2016semi, ryu2018deeply}.
In what follows, we briefly introduce BNNs, the uncertainty quantification methods based on Bayesian inference, and the augmented-GCN used in this work.
Then, we show the results of uncertainty analysis on three experimental studies.
The main results are summarized as follows.
\begin{itemize}
    \item We first applied the Bayesian GCN to a simple example, the logP prediction of molecules in the ZINC set\cite{irwin2005zinc}, in order to demonstrate the uncertainty quantification in molecular applications.
    As expected, the aleatoric uncertainty increases as the data noise increases, while the epistemic uncertainty slightly depends on the quality of data.
    \item Second, we evaluate the quality of synthetic data and find erroneous samples fabricated by poor approximations.
    The Harvard Clean Energy Project (CEP) set \cite{hachmann2011harvard} contains synthetic power conversion efficiency (PCE) values of molecules.
    We noted that molecules with exactly zero values have a conspicuously large aleatoric uncertainty, which have been verified as incorrect annotations.
    \item In the last example, for the binary classification of bio-activity and toxicity, we studied the relationship between predicted probability and uncertainties.
    Our analysis shows that prediction with a lower uncertainty turned out to be more accurate, indicating that the uncertainty can be regarded as the confidence of prediction.
\end{itemize}

\section{Theoretical backgrounds}
\subsection{Bayesian neural network}

For a given training set $\{ \textbf{X}, \textbf{Y} \}$, let  $p(\textbf{Y}|\textbf{X},\textbf{w})$ and $ p(\textbf{w})$ be a model likelihood and a prior distribution for a parameter $\textbf{w} \in \Omega$, respectively.
Under the Bayesian framework, the model parameter and output are considered as random variables.
The posterior distribution is given by
\begin{equation} \label{eq:1}
p(\textbf{w}|\textbf{X},\textbf{Y}) = \frac{p(\textbf{Y}|\textbf{X},\textbf{w})p(\textbf{w})}{p(\textbf{Y}|\textbf{X})}
\end{equation}
and the predictive distribution is defined as
\begin{equation} \label{eq:2}
p(\textbf{y}^*|\textbf{x}^*,\textbf{X},\textbf{Y}) = \int _\Omega p(\textbf{y}^*|\textbf{x}^*,\textbf{w}) p(\textbf{w}|\textbf{X},\textbf{Y}) d\textbf{w}
\end{equation}
for a new input $\textbf{x}^*$ and an output $\textbf{y}^*$.
These simple formulations make the two following tasks possible: (i) assessing uncertainty of the random variables in a conditional manner and (ii) predicting a distribution of the new output $\textbf{y}^*$ given both the new input $\textbf{x}^*$ and the training set $\{ \textbf{X}, \textbf{Y} \}$.

However, direct computation of eq. \eqref{eq:2} is often infeasible when deep neural network models are exploited because the integration over the whole parameter space $\Omega$ entails heavy computational costs.
Many practical approximation methods have been proposed to handle this computation cost.
A variational inference, one of the most popular approximation methods, approximates the posterior distribution with a tractable distribution $q_{\theta}(\textbf{w})$ parametrized by a variational parameter $\theta$ \cite{blundell2015weight, graves2011practical}.
Minimizing the Kullback-Leibler divergence,
\begin{equation} \label{eq:3}
\textrm{KL}(q_{\theta}(\textbf{w}) \Vert p(\textbf{w}|\textbf{X},\textbf{Y})) = \int _\Omega q_{\theta}(\textbf{w}) \log \frac{q_{\theta}(\textbf{w})}{p(\textbf{w}|\textbf{X},\textbf{Y})} d\textbf{w},
\end{equation}
makes the two distributions similar to one another in principle.
We can replace the intractable posterior distribution in \eqref{eq:3} with $p(\textbf{Y}|\textbf{X},\textbf{w})p(\textbf{w})$ due to the Bayes' theorem \eqref{eq:1}.
Then, our minimization objective, called the negative evidence lower-bound, is
\begin{equation} \label{eq:4}
\mathcal{L}_{\textrm{VI}}(\theta) = -\int _\Omega q_{\theta}(\textbf{w})\log{p(\textbf{Y}|\textbf{X},\textbf{w})}d\textbf{w}+\textrm{KL}(q_{\theta}(\textbf{w}) \Vert p(\textbf{w})).
\end{equation}

In order to implement Bayesian models, we need to be cautious in choosing a variational distribution $q_{\theta}(\textbf{w})$.
\citeauthor{blundell2015weight} proposed to use a product of Gaussian distributions for the variational distribution $q_{\theta}(\textbf{w})$.
In addition, a multiplicative normalizing flow \cite{louizos2017multiplicative} can be applied to increase the expressive power of variational distribution.
However, the two approaches often require a large number of weight parameters.
The Monte-Carlo dropout (MC-dropout) using a dropout\cite{srivastava2014dropout} variational distribution approximates the posterior distribution by a product of Bernoulli distribution \cite{gal2016dropout}.
The MC-dropout is practical in that it does not need extra learnable parameters to model the variational posterior distribution and the integration over the whole parameter space can be easily approximated with the summation of models sampled by a Monte-Carlo estimator \cite{gal2016uncertainty, gal2016dropout}.
Thus, we adopted the MC-dropout in this work.

\subsection{Uncertainty quantification with Bayesian neural network}
A variational inference approximating a posterior with a variational distribution $q_{\theta}(\textbf{w})$ provides a variational predictive distribution of a new output $\textbf{y}^*$ given a new input $\textbf{x}^*$ as
\begin{equation} \label{eq:5}
q_{\theta}^*(\textbf{y}^*|\textbf{x}^*) = \int _\Omega q_{\theta}(\textbf{w}) p(\textbf{y}^*|f^{\textbf{w}}(\textbf{x}^*)) d\textbf{w},
\end{equation}
where $f^{\textbf{w}}(\textbf{x}^*)$ is a model output with a given $\textbf{w}$.
For regression tasks, a predictive mean of this distribution with $T$ times of MC sampling is estimated by
\begin{equation} \label{eq:6}
    \hat{E} [\textbf{y}^*|\textbf{x}^*] = \frac{1}{T}\sum_{t=1}^{T} f^{\hat{\textbf{w}}_t}(\textbf{x}^*),
\end{equation}
and a predictive variance is estimated by
\begin{equation} \label{eq:7}
    \widehat{Var} [\textbf{y}^*|\textbf{x}^*] = \sigma^2I + \frac{1}{T} \sum_{t=1}^{T} f^{\hat{\textbf{w}}_t}(\textbf{x}^*)^T f^{\hat{\textbf{w}}_t}(\textbf{x}^*) - \hat{E} [\textbf{y}^* | \textbf{x}^*]^T  \hat{E} [\textbf{y}^* | \textbf{x}^*],
\end{equation}
with $\hat{\textbf{w}}_t$ drawn from $q_{\theta}(\textbf{w})$ at the sampling step $t$ and an assumption $p(\textbf{y}^*|f^{\textbf{w}}(\textbf{x}^*)) = N(\textbf{y}^*;f^{\textbf{w}}(\textbf{x}^*), \sigma^2I)$. Here, the model assumes a homoscedasticity with a known quantity, meaning that every data point gives a distribution with a same variance $\sigma^2$.
Further to this, obtaining the distributions with different variances allows deducing a heteroscedastic uncertainty.
Assuming the heteroscedasticity, the output given the $t$-th sample $\hat{\textbf{w}}_t$ is
\begin{equation} \label{eq:8}
    [\hat{\textbf{y}}_{t}^*, \hat{\sigma}_{t}] = f^{\hat{\textbf{w}}_t}(\textbf{x}^*).
\end{equation}
The heteroscedastic predictive uncertainty given by \eqref{eq:9} can be partitioned into two different uncertainties: aleatoric and epistemic uncertainties.
\begin{equation} \label{eq:9}
    \widehat{Var} [\textbf{y}^*|\textbf{x}^*] = \underbrace{\frac{1}{T} \sum_{t=1}^{T} (\hat{\textbf{y}}_{t}^{*})^2 - (\frac{1}{T} \sum_{t=1}^{T} \hat{\textbf{y}}_{t}^*)^2}_\textrm{epistemic} + \underbrace{\frac{1}{T} \sum_{t=1}^{T} \hat{\sigma}_{t}^2}_\textrm{aleatoric}.
\end{equation}
The aleatoric uncertainty arises from data inherent noise, while the epistemic uncertainty is related to the model incompleteness.
Note that the latter can be reduced by increasing the amount of training data, because it comes from insufficient amount of data as well as the use of inappropriate model \cite{der2009aleatory}.

In classification problems, \citeauthor{kwon2018uncertainty} proposed a natural way to quantify aleatoric and epistemic uncertainties as follows.
\begin{equation} \label{eq:10}
\widehat{Var} [\textbf{y}^* | \textbf{x}^*] = \underbrace{\frac{1}{T} \sum_{t=1}^{T}(\hat{\textbf{y}}_t^* - \bar{\textbf{y}})(\hat{\textbf{y}}_t^* - \bar{\textbf{y}})^T}_\textrm{epistemic} + \underbrace{\frac{1}{T} \sum_{t=1}^{T} (\textrm{diag}(\hat{\textbf{y}}_t^*) - (\hat{\textbf{y}}_t^*)(\hat{\textbf{y}}_t^*)^T)}_\textrm{aleatoric},
\end{equation}
where $\bar{\textbf{y}} = \sum_{t=1}^{T} \hat{\textbf{y}}_t^*/T$ and $\hat{\textbf{y}}_t^* = \textrm{softmax}(\textbf{f}^{\hat{\textbf{w}}_t}(\textbf{x}^*))$.
While \citeauthor{kendall2017uncertainties}'s method requires extra parameters $\hat{{\sigma}}_t$ at the last hidden layer and often causes unstable parameter updates in a training phase,\cite{kendall2017uncertainties} the method in \citeauthor{kwon2018uncertainty} has advantages in that models do not need the extra parameters.\cite{kwon2018uncertainty}
The equation \eqref{eq:10} also utilizes a functional relationship between mean and variance of multinomial random variables.
We refer to \citeauthor{kwon2018uncertainty} for more details.

\subsection{Graph convolutional network for molecular property predictions}

Molecules, social graphs, images and language sentences can be represented as graph structures \cite{battaglia2018relational}.
GCN is one of the most popular graph neural networks and is widely adopted to process molcular graphs.
Inputs to the GCN is $\textbf{G}=(\textbf{A},\textbf{X})$,
where $\textbf{A} \in \mathds{R}^{N \times N}$ is an adjacency matrix with the number of nodes $N$ and $\textbf{X} = \textbf{H}^{(0)}\in \mathds{R}^{N \times F_{inp}}$ is a set of initial node features whose dimensionality is $F_{inp}$.
The GCN gives new node features as follows.
\begin{equation} \label{eq:11}
\textbf{H}^{(l+1)} = \textrm{ReLU}(\textbf{A}\textbf{H}^{(l)}\textbf{W}^{(l)}),
\end{equation}
where $\textbf{H}^{(l)} \in \mathds{R}^{N \times F}$ and $\textbf{W}^{(l)} \in \mathds{R}^{F \times F}$ are node features and weight parameters for the $l$-th graph convolution layer for $l \in \{ 0, \dots, L-1\}$, respectively.
The GCN updates node features $\textbf{H}^{(l+1)}$ with information of only adjacent nodes.

Applying a self-attention\cite{vaswani2017attention} enables the GCN to learn relations between node pairs by reflecting the importance of adjacent nodes.\cite{velickovic2017graph}
Updating node features with the $K$-head self-attention is given by
\begin{equation} \label{eqn:eq12}
\tilde{\textbf{H}}_i^{(l+1)} =  [\text{ReLU}(\sum_{j \in \mathcal{N}_i} \alpha_{ij,1}^{(l)} \textbf{H}_{j}^{(l)} \textbf{W}_{1}^{(l)}), ..., \text{ReLU}(\sum_{j \in \mathcal{N}_i} \alpha_{ij,K}^{(l)} \textbf{H}_{j}^{(l)} \textbf{W}_{K}^{(l)})] \textbf{W}_{O}^{(l)},
\end{equation}
where $\mathcal{N}_i$ denotes the adjacent nodes of the $i$-th node,
$H_j^{(l)} \in \mathds{R}^{1 \times F}$ is the $j$-th node feature updated at $l$-th graph convolution,
$W_k^{(l)} \in \mathds{R}^{F \times F}$ is a weight parameter for the $k$-th attention head,
$\textbf{W}_O^{(l)} \in \mathds{R}^{K F \times F}$ is a weight parameter to combine the node features from $K$-different attention heads,
and the attention coefficient $\alpha_{ij,k}^{(l)}$ is given by
\begin{equation}
\alpha_{ij,k}^{(l)} = \text{tanh}((\textbf{H}_i^{(l)} \textbf{W}_k^{(l)}) \textbf{C}_k^{(l)} (\textbf{H}_j^{(l)} \textbf{W}_k^{(l)})^T),
\end{equation}
where $\textbf{C}_k^{(l)} \in \mathds{R}^{F \times F}$ is a weight parameter.

In addition, the GCN has room for improvement because its accuracy is gradually lowered as the number of graph convolution layers increases. \cite{kipf2016semi, ryu2018deeply}
We used a gated-skip connection to prevent this problem as follows.
\begin{equation} \label{eq:13}
\textbf{H}^{(l+1)} = \textbf{r} \odot \tilde{\textbf{H}}^{(l+1)} + (\textbf{1}-\textbf{r}) \odot \textbf{H}^{(l)}, \quad \textbf{r} = \textrm{sigmoid}(\textbf{U}_{r,1} \textbf{H}^{(l)} + \textbf{U}_{r,2} \tilde{\textbf{H}}^{(l+1)} + \textbf{b}_r),
\end{equation}
where $\textbf{U}_{r,1}$ and $\textbf{U}_{r,2}$ are trainable parameters and $\odot$ denotes Hadamard product.

After computing the node features $L$-times by following eq. \eqref{eq:13}, a graph feature $\textbf{z}_{\textrm{G}} \in \mathds{R}^{d_G}$ is aggregated as the summation of all node features in a set of nodes $\mathcal{V}$,
\begin{equation} \label{eq:14}
\textbf{z}_{\textrm{G}} = \sum_{v \in \mathcal{V}} \textrm{MLP}_1(\textbf{H}_v^{(L)}),
\end{equation}
where $\textrm{MLP}$ denotes a multi-layer perceptron. The graph feature is invariant to permutations of the node states. A molecular property, which is the final output from the model, is a function of the graph feature.
\begin{equation} \label{eq:15}
y_{pred} = \textrm{MLP}_2(\textbf{z}_{\textrm{G}}).
\end{equation}

\section{Implementation details}
\subsection{Model architecture}
\begin{figure}
    \centering
    \includegraphics[width=0.5\textwidth]{model_architecture.jpg}
    \caption{The architecture of Bayesian GCN used in this work. (a) The entire model is composed of three augemented graph convolutional layers, readout layers and three linear layers with non-linear activation. (b) Detailed description of the graph convolution layer augmented with attention and gate mechanisms. We added dropout layers in order for the model parameters to have stochasticity.}
    \label{fig:model_architecture}
\end{figure}

As illustrated in Figure \ref{fig:model_architecture}, our graph convolutional MC-dropout network used in this work consists of the following three parts:
\begin{itemize}
    \item Three augmented graph convolution layers update node features according to \eqref{eq:13}. The number of self-attention head is four. The dimension of output from each layer is ($N \times F$) = ($75\times32$).
    \item A readout function produces a graph feature whose dimension $d_G$ is 256 by following \eqref{eq:14}.
    \item A feed-forward MLP, which is composed of two fully-connected layers, turns out a molecular property. The hidden dimension of each fully-connected layer is 256.
\end{itemize}
In order for the model parameters to have stochasticity, we applied dropouts at every hidden layer.
Note that we did not use the standard dropout with a pre-defined dropout rate, but used Concrete dropout\cite{gal2017concrete} to develop as an accurate Bayesian model as possible.
By using the Concrete dropout, we can obtain an optimal dropout rate for individual hidden layer by a stochastic optimization.
We used Gaussian priors $\mathcal{N}(0, l^2)$ with length scale $l=10^{-4}$ for all model parameters.
In the training phase, we used the Adam optimizer\cite{kingma2014adam} with an initial learning rate $10^{-3}$, and the learning rate is decayed by half at every 10 epoch.
The number of total training epoches is $100$ and the batch size is $100$.
We randomly split datasets in the ratio of $(0.72:0.08:0.2)$ for training, validation and test.
The code used for the experiments is available at \url{https://github.com/seongokryu/uq-molecule}.

\section{Experiments}

\subsection{Implication of data quality on aleatoric and epistemic uncertainties}
\begin{figure}
    \centering
    \includegraphics[width=1.0\textwidth]{Bayesian_logP.jpg}
    \caption{Histograms of (a) aleatoric , (b) epistemic and (c) total uncertanties as the amount of additive noise $\sigma^2$ increases.}
    \label{fig:Bayesian_logP}
\end{figure}

In this experiment, we applied the uncertainty quantification method to a simple example, logP prediction.
We chose this example because we can obtain the logP value of molecules from the analytic expression of logP as implemented in the RDKit \cite{landrum2006rdkit} without data inherent noise.
To examine the effect of data quality on uncertainties, we adjust the extent of noise in logP by adding a random Gaussian noise $\epsilon \sim \mathcal{N}(0,\sigma^2)$.
We trained the model with 97,287 samples and analyzed uncertainties of each predicted logP for 27,023 samples. The samples were chosen randomly from the ZINC dataset.

Figure \ref{fig:Bayesian_logP} shows the distribution of the three uncertainties as a function of the amount of additive noise $\sigma^2$.
As the noise level increases, the aleatoric and total uncertainties increase, but the epistemic uncertainty is slightly changed.
This result verifies that the aleatoric uncertainty arises from data inherent noises, while the epistemic uncertainty does not depend on data quality.
Theoretically, the epistemic uncertainty should not increase by the changes in the amount of data noise.
We guess that the slight change of the epistemic uncertainty arises from the stochastic numerical optimization of model parameters.

\subsection{Evaluating quality of synthetic data based on uncertainty analysis}

\begin{figure}
    \centering
    \includegraphics[width=0.5\textwidth]{Bayesian_CEP.jpg}
    \caption{(a) Aleatoric, (b) epistemic, (c) total uncertainties and (d) predicted PCE against the PCE value in the dataset. The samples colored in red show the total uncertainty greater than two.}
    \label{fig:Bayesian_CEP}
\end{figure}

Based on the analysis of the previous experiment, we attempted to evaluate the quality of synthetic data.
Synthetic PCE values in the CEP dataset \cite{hachmann2011harvard} was obtained from the Scharber model with statistical approximations \cite{scharber2006design}.
In this procedure, unintentional errors can be involved in the resulting synthetic data.
Since the aleatoric uncertainty arises due to data quality, we evaluated quality of the synthetic data by analyzing the uncertainties of predicted PCE values.
We used the same dataset in \citeauthor{duvenaud2015convolutional} \footnote{\url{https://github.com/HIPS/neural-fingerprint}} for training and test.

Figure \ref{fig:Bayesian_CEP} shows the scatter plot of three uncertainties in the CEP predictions for 5,995 molecules in the test set.
Samples with the total uncertainty greater than two are highlighted with red color.
Some samples with large PCE values above eight had relatively large total uncertainties.
Their PCE values deviated considerably from the black line in Figure \ref{fig:Bayesian_CEP}-(d).
More interestingly, we found that most molecules with the zero PCE value had large total uncertainties as well.
Those large uncertainties came from the aleatoric uncertainty as depicted in Figure \ref{fig:Bayesian_CEP}-(a), indicating that the data quality of those particular samples is relatively poor.
Hence, we speculated that data inherent noises might cause large prediction errors.

To elaborate the origin of such errors, we investigated the procedure of obtaining the PCE values. The Havard Organic Photovolatic Dataset \cite{lopez2016harvard} contains both experimental and synthetic PCE values of 350 organic photovoltaic materials.
The synthetic PCE values were computed according to \eqref{eq:16}, which is the result of the Scharber model \cite{scharber2006design}.
\begin{equation}\label{eq:16}
\textrm{PCE} \propto V_{OC} \times FF \times J_{SC},
\end{equation}
where $V_{OC}$ is an open circuit potential, $FF$ is a fill factor, and $J_{SC}$ is a short circuit current density.
$FF$ was set to 65\%. $V_{OC}$ and $J_{SC}$ were obtained from electronic structure calculations of molecules.\cite{hachmann2011harvard}
We found that $J_{SC}$ of some molecules were zero or nearly zero, resulting in zero or almost zero synthetic PCE values, in contrast to their non-zero experimental PCE values.
Especially, $J_{SC}$ and PCE values computed using the M06-2X functional \cite{zhao2008m06} were almost zero consistently.
We suspect that those approximated values caused a significant drop of data quality, resulting in large aleatoric uncertainties as highlighted in Figure \ref{fig:Bayesian_CEP}.
Consequently, the data noise due to poorly fabricated data was identified as the large aleatoric uncertainties.

\subsection{Uncertainty as confidence indicator: bio-activity and toxicity classification}

\begin{figure}
    \centering
    \includegraphics[width=1.0\textwidth]{Bayesian_EGFR_unc.jpg}
    \caption{(a) Aleatoric, (b) epistemic and (c) total uncertainty of predicted probabilities in the classification of bio-activity against the EGFR target.}
    \label{fig:6}
\end{figure}

In this experiment, we demonstrate that the uncertainty analysis can lead reliable classification.
In classification problems, it tends to interpret the final outputs from a sigmoid or softmax activation as their confidence, which means that the higher the output probability, the higher the prediction accuracy.
However, as \citeauthor{gal2016dropout} pointed out, such interpretation is erroneous. \cite{gal2016dropout}
Thus, we applied the uncertainty quantification on the bio-activity and toxicity classification problems and show that the predictive uncertainty can be used as the confidence of outcomes.

\begin{figure}
    \centering
    \includegraphics[width=1.0\textwidth]{Bayesian_group_accuracy.jpg}
    \caption{Test accuracy for the classifications of (a) bio-activities against the five target proteins in the DUD-E set and (b) the five toxic effects in the Tox21 set.}
    \label{fig:Bayesian_group_accuracy}
\end{figure}

We trained the Bayesian GCN using 25,627 molecules with the labels for EGFR-activity in the DUD-E dataset.
Figure \ref{fig:6} shows the results for 7,118 molecules in the test set.
In order for the predictive uncertainty to be interpreted as a confidence, its value should be minimum on the output probability of zero or one and should be maximum on that of 0.5.
Indeed, the total uncertainty predicted from our model shows such behaviour.
In other words, more uncertain outcomes have lower predictive probability values.
We also noted that the aleatoric uncertainty affected the total uncertainty more significantly than the epistemic uncertainty did.

To further investigate a relationship between accuracy and uncertainty, we trained the Bayesian GCN for various bio-activity labels in the DUD-E dataset and toxicity labels in the Tox21 dataset.
Then, we sorted the molecules in the order of increasing uncertainty and then divided them into five groups as follows:
molecules in the $i$-th group have total uncertainties in the range of $((i-1)\times0.1, i\times0.1)$.
Figure \ref{fig:Bayesian_group_accuracy} shows the classification accuracy of each group; (a) and (b) denote the classification results of bio-acitvities against the five different targets and the five different toxicities of Tox21 set molecules, respectively.
This result is an evidence that the uncertainty can be used as a confidence indicator in binary classification problems.

\section{Conclusion}
Deep neural network models show promising performances in the prediction of molecular properties.
In practical applications, however, a lack of data quality and quantity discourages developing accurate models.
To make reliable decisions in such a case, we have proposed to analyze uncertainties in the prediction results by using the Bayesian GCN.

Our first experiment on the logP prediction showed that data inherent noise can be identified by the aleatoric uncertainty.
The aleatoric uncertainty in the predicted logP values increases as the amount of noise increases.
In contrast, the epistemic uncertainty slightly depends on the data noise as expected.
In the second experiment, we applied the uncertainty analysis to the Harvard Clean Energy Project dataset.
It was able to identify erroneous data by noting the abnormally increased aleatoric uncertainty in the poorly approximated synthetic data, which is helpful to find the source of the errors.
In the third experiment of bio-activity and toxicity predictions, we showed that the uncertainty is closely related to the confidence of prediction for binary classification problems.
As grouping the molecules in the increasing order of uncertainty, the groups with lower uncertainty show higher accuracy than those with higher uncertainty.

We have demonstrated how useful the uncertainty quantification is in molecular applications.
By using the Bayesian GCN, we can analyze the quality of data that is often noisy because of the stochastic nature of experimental results.
From the relationship between output probability and confidence of prediction, it is able to extract more reliable results selectively from entire predictions,
which is critical to making a desirable decision.
Such analysis can be used to screen bio-active and toxic molecules, where reliable prediction is vital.
We believe that our study on the uncertainty quantification of molecular properties offers insights to tackle AI-safety problems in molecular applications.

redpajama_set_name: RedPajamaArXiv


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The University of Manchester has a strong reputation of delivering industry focused on professional development courses, consultancy and applied research in plant maintenance and reliability over the past 20 years. The current effort is aimed at providing a common platform by which professionals, engineers, practitioners and researchers working in the field of plant maintenance and reliability can share their experience by presenting plant maintenance related studies and research at this IncoME - III 2018 Conference.
The Centre for Mechanical Engineering Materials and Processes (Research Unit nº 285 of the Portuguese Foundation for Science and Technology) aims to develop interdisciplinary research in the areas of Mechanical and Materials Engineering and other related areas. Its main objectives are to promote innovation, facilitating the dissemination of scientific and technological knowledge in close collaboration with the business and social network and supporting the creation of start-ups.
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The Director, José Maura, participated in the International Shipping Summit in Istanbul, Turkey on 17 March 2018. The event, which was opened by Prime Minister of Turkey, Binali Yıldırım, was hosted by the Ministry of Transport, Maritime Affairs and Communications in honour of the 70th anniversary of the International Maritime Organization. Transport Minister, Ahmet Arslan, also spoke at the opening ceremony.
The event was attended by prominent maritime industry representatives and senior members of maritime administrations from various States. A number of panel discussions took place during the event, with a keynote speech from the Secretary-General of IMO on the Organization's achievements. The Director delivered a presentation on the international liability and compensation regime during one of the panel sessions.


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text:
The politics of Malta takes place within a framework of a parliamentary representative democratic republic, whereby the President of Malta is the constitutional head of state. Executive Authority is vested in the President of Malta with the general direction and control of the Government of Malta remaining with the Prime Minister of Malta who is the head of government and the cabinet. Legislative power is vested in the Parliament of Malta which consists of the President of Malta and the unicameral House of Representatives of Malta with the Speaker presiding officer of the legislative body. Judicial power remains with the Chief Justice and the Judiciary of Malta. Since Independence, the party electoral system has been dominated by the Christian democratic Nationalist Party (Partit Nazzjonalista) and the social democratic Labour Party (Partit Laburista).

Political developments since Independence

Since independence, two parties have dominated Malta's polarized and evenly divided politics during this period: the centre-right Nationalist Party and the centre-left Labour Party.
From the pre-independence 1962 general election until 2017 third parties failed to score any electoral success. In the 2013 election, the Democratic Alternative (a green party established in 1989), had managed to secure only 1.8% of the first preference votes nationwide.

The 1996 elections resulted in the election of the Labour Party, by 8,000 votes, to replace the Nationalists who had won in 1987 and 1992. Voter turnout was characteristically high at 96%, with the Labour Party receiving 50.72%, the Nationalist Party 47.8%, the Democratic Alternative 1.46%, and independent candidates 0.02%.

In 1998, the Labour Party's loss in a parliamentary vote led the Prime Minister to call an early election. The Nationalist Party was returned to office in September 1998 by a majority of 13,000 votes, holding a five-seat majority in Parliament. Voter turnout was 95%, with the Nationalist Party receiving 51.81%, the Labour Party 46.97%, the Democratic Alternative 1.21%, and independent candidates 0.01%.

By the end of 2002 the Nationalist government wrapped up negotiations for European Union membership. A referendum on the issue was called in March 2003 for which the Nationalists and the Democratic Alternative campaigned for a "yes" vote while Labour campaigned heavily for "no" vote, invalidate their vote or abstain. Turnout was 91%, with more than 53% voting "yes".

The Labour Party argued that the "yes" votes amounted to less than 50% of the overall votes, hence, and citing the 1956 Maltese United Kingdom integration referendum as an example, they claimed that the "yes" had not in fact won the referendum. The then MLP Leader Alfred Sant said that the General Election which was to be held within a month would settle the affair. In the General Elections the Nationalists were returned to office with 51.79% of the vote to Labour's 47.51%. The Democratic Alternative polled 0.68%. The Nationalists were thus able to form a government and sign and ratify the EU Accession Treaty on 16 April 2003.

On 1 May 2004 Malta joined the EU and on 1 January 2008, the Eurozone with the euro as the national currency. The first elections after membership were held in March 2008 resulting in a narrow victory for the Nationalist Party with 49.34% of first preference votes. In May 2011, a nationwide referendum was held on the introduction of divorce. This was the first time in the history of parliament that Parliament approved a motion originating outside from the Cabinet.

In March 2013, the Labour Party returned to Government after fifteen years in Opposition with a record-breaking lead of 36,000 votes leading to the resignation of the Nationalist leader Lawrence Gonzi, and Joseph Muscat became Prime Minister.  In June 2017, the Labour Party called in a snap election on its May Day celebrations and increased its vote disparity to around 40,000 votes. The then leader of the opposition Simon Busuttil announced his resignation shortly thereafter. This election saw the first third party elected to Malta's Parliament since its Independence, with the election of Marlene Farrugia in the 10th District representing the Democratic Party. Joseph Muscat continued to be Prime Minister In January 2020, he stepped down after the 2019 Malta political crisis surrounding the carbombing of investigative journalist Daphne Caruana Galizia. Robert Abela - the son of Malta's former President George Abela - elected a new leader of Labour Party and new prime minister of Malta in January 2020.

Democratic Alternative and the Democratic Party merged into a new party, AD+PD, on 17 October 2020.

In March 2022, the ruling Labour party, led by Prime Minister Robert Abela, won its third successive election. It gained even bigger victory than in 2013 and in 2017.

Executive branch
Under its 1964 constitution, Malta became a parliamentary democracy within the Commonwealth. Queen Elizabeth II of the United Kingdom was sovereign of Malta, and a Governor-General exercised executive authority on her behalf, while the actual direction and control of the government and the nation's affairs were in the hands of the cabinet under the leadership of a Maltese prime minister.

On December 13, 1974, the constitution was revised, and Malta became a republic within the Commonwealth, with executive authority vested in the President of Malta which can be exercised directly or through officers subordinate to him. The president is elected by the House of Representatives for a five-year term. They appoint as Prime Minister the leader of the party with a majority of seats in the unicameral House of Representatives, known in Maltese as Kamra tar-Rappreżentanti.

The President also nominally appoints, upon recommendation of the Prime Minister, the individual ministers. Ministers are selected from among the members of the House of Representatives, which usually consists of 65 members unless bonus seats are given to a party which gains an absolute majority of votes but not a Parliamentary majority. Elections must be held at least every 5 years and the electoral system used is single transferable vote.

Administrative divisions
Malta is divided into 68 elected local councils, with each council responsible for the administration of cities or regions of varying sizes. Administrative responsibility is distributed between the local councils and the central government in Valletta.
The Local Councils Act, 1993 (Act XV of 1993) was published on June 30, 1993, subdividing Malta into 54 local councils in Malta and 14 in Gozo. The inhabitants who are registered elect the Council every three years, as voters in the Local Councils' Electoral Register. Elections are held by means of the system of proportional representation using the single transferable vote. The mayor is the head of the Local Council and the representative of the Council for all effects under the Act. The Executive Secretary, who is appointed by the Council, is the executive, administrative, and financial head of the Council. All decisions are taken collectively with the other members of the Council. Local councils are responsible for the general upkeep and embellishment of the locality, local wardens, and refuse collection, and carry out general administrative duties for the central government such as collection of government rents and funds, and answering government-related public inquiries.

There are also Administrative Committees elected with responsibility for smaller regions.

Legislative branch

Elections to the House of Representatives (Kamra tad-Deputati) are based on the single transferable vote system, a variant of the proportional representation electoral system. First, vacancies are filled through casual election and subsequent vacancies through co-option, meaning that no by-elections are held between one general election and the other. The Parliamentary term cannot exceed five years.

Ordinarily, 65 members are elected to the House from 13 multi-seat constituencies each returning 5 MPs. Additional MPs are elected in two circumstances:

 When a party achieves 50%+1 of first-preference valid votes in the election but does not secure a Parliamentary majority it is awarded enough seats (filled by the best runner-up candidates) to make a Parliamentary majority
 When in an election contested by more than two parties only two parties are elected to Parliament and the relative Parliamentary strength is not proportionate to the first preference votes obtained, additional seats are allocated to establish proportionality

A third electoral amendment has been enacted which guarantees strict-proportionality with respect to votes and seats to parliamentary political groups.

Political party standings as of the most recent election

Judicial branch

The Judicial system in Malta comprises Inferior Courts, Civil and Criminal Courts of
Appeal, and a Constitutional Court.  Inferior courts are presided over by Magistrates which have original jurisdiction in criminal and civil actions. In the Criminal Courts, the presiding judge sits with a jury of nine.  The Court of Appeal and the Court of Criminal Appeal hear appeals from decisions of the civil and criminal actions respectively.

The highest court, the Constitutional Court, has both original and appellate jurisdiction. In its appellate jurisdiction it adjudicates cases involving violations of human rights and interpretation of the Constitution. It can also perform judicial review. In its original jurisdiction it has jurisdiction over disputed parliamentary elections and electoral corrupt practices.

There is a legal aid scheme offered to citizens lacking the means to afford legal defence.

According to the Constitution, the President appoints the Chief Justice of Malta acting in accordance with a resolution of the House supported by the votes of not less than two-thirds of all the members of the House of Representatives. The Judges of the Superior Court and the Magistrates of the Inferior Courts are appointed through the Judicial Appointments Committee of Malta.

Guarantees for the independence of the judiciary include the security of tenure for judges until their retiring age set at 65 (with a choice to extend retirement till 68), or until impeachment. The impeachment procedure for judges foresees a removal decision of the President upon request by the Commission for the Administration for Justice.

The independence of the judiciary is also guaranteed by the constitutional requirement that the judges' salaries are paid from the Consolidated Fund and thus the government may not diminish or amend them to their prejudice.

The Maltese system is considered in line with the principles of separation of powers and of independence of the judiciary. However, in its pre-accession evaluation reports, the European Commission has suggested in 2003 the need to reform the procedure for appointment of the members of the judiciary, currently "controlled by political bodies" (i.e. the Parliament and parties therein), in order to improve its objectivity. The Commission has also pointed to the need to check the compliance of the procedure for challenging judges and magistrates provided for by Article 738 of the Code of Organisation and Civil Procedure with the principle of an impartial tribunal enshrined in the European Convention on Human Rights.

International organization participation
Malta is a member of the Commonwealth of Nations, CE, EBRD, ECE, EU (member from 1 May 2004), FAO, IAEA, IBRD, ICAO, ICCt, ICFTU, ICRM, IFAD, IFRCS, ILO, IMF, IMO, Inmarsat, Intelsat, Interpol, IOC, IOM, ISO, ITU, OPCW, OSCE, PCA, UN, UNCTAD, UNESCO, UNIDO, UPU, WCL, WCO, WHO, WIPO, WMO, WToO, WTrO

Malta was a long-time member of the Non-Aligned Movement. It ceased to be part of the movement when it joined the European Union.

See also

People's Party
Volt Malta
Mass meeting

Notes

References

External links
Central Government of Malta
House of Representatives
Laws of Malta
Local Councils of Malta
Constitution of Malta (pdf file)
Labour Party
Nationalist Party

Politics of Europe

redpajama_set_name: RedPajamaWikipedia


text:
Q: how to execute method c() if method b() has not been called for more than N seconds? method a() sends data to method b(), how to execute method c() if method b() has not been called for more than N seconds and repeat this cycle if method b() receives data again?
public void methodB(byte[] audioData) throws IOException {
            byte[] transcodedVoice = transcodeVoice(audioData);
            recognizer.acceptWaveForm(transcodedVoice, transcodedVoice.length);
    }

public void methodC() {
            //do Something
            System.out.println("Method B stops getting data")
    }

A: Debouncer class
public class Debouncer {
private final ScheduledExecutorService scheduler = Executors.newSingleThreadScheduledExecutor();
private final ConcurrentHashMap<Object, Future<?>> delayedMap = new ConcurrentHashMap<>();

/**
 * Debounces {@code callable} by {@code delay}, i.e., schedules it to be executed after {@code delay},
 * or cancels its execution if the method is called with the same key within the {@code delay} again.
 */
public void debounce(final Object key, final Runnable runnable, long delay, TimeUnit unit) {
    final Future<?> prev = delayedMap.put(key, scheduler.schedule(new Runnable() {
        @Override
        public void run() {
            try {
                runnable.run();
            } finally {
                delayedMap.remove(key);
            }
        }
    }, delay, unit));
    if (prev != null) {
        prev.cancel(true);
    }
}

public void shutdown() {
    scheduler.shutdownNow();
}
}

My class with method b()
final Debouncer debouncer = new Debouncer();
public void methodB(byte[] audioData) throws IOException {
        byte[] transcodedVoice = transcodeVoice(audioData);
        recognizer.acceptWaveForm(transcodedVoice, transcodedVoice.length);

        debouncer.debounce(Void.class, new Runnable() {
                @Override public void run() {
                    System.out.println("Method B stops getting data");
                }
            }, 300, TimeUnit.MILLISECONDS);
}

redpajama_set_name: RedPajamaStackExchange


Asana's 'hack' feature that enabled you to add up numbers contained in square brackets was recently removed by Asana to encourage use of Custom Fields, which is a premium feature. This doesn't suit freelancers like me because Asana premium is for 5 members or more with a price tag to match, so I created my own hack that does the same thing. It's a little more effort (copy and paste) but allows me to continue using Asana and not change my workflow. Feel free to use and share.


I spent the week-end of March 11 & 12 at the Tucson Festival of Books, the third largest such event in the country. My goal was to learn from the best and the brightest, knowing from past experience that a number of hot, new writers come to Tucson to introduce their works to the world.
I was not disappointed and am happy to share with my LateLastNightBook followers the names of some authors you might want to give a try.
The one who stood out the most out of the authors I heard over the two days was Emily Fridlund, author of History of Wolves, a novel set in northern Minnesota which turns on its head the usual exploitation relationship of teacher and student. Given the praise for her novel, although I haven't read it yet, I recommend it highly.
The Holocaust continues to haunt writers and readers, as well it should. Affinity Konar takes on the "Angel of Death's" experiments on twins in Mischling, a book that has garnered recognition from the New York Times and others.
Another bright young author worth paying attention to is Tara Ison, whose most recent product is Ball, a book of short stories. She admits she writes about things she fears and then pushes them as far as she can. Her novels, Rockaway and A Child Out of Alcatraz, have also gotten excellent attention.
If you love the Mexican-American culture, you need to pick up The Water Museum stories by Luis Urrea. His novel, The Hummingbird's Daughter, is described as an epic mystical drama of a young woman's sudden sainthood in 19th century Mexico.
If you are into young adult fantasy fiction, Aprilynne Pike, Maggie Stiefvater, and Shannon Messenger are three bright young authors to watch out for. Pike's most recent novel, Glitter, is a stand-alone, but she's best known for the Wing series of five novels. Stiefvator is the author of The Raven Cycle series, and Messenger is the author of four Keeper novels.
I hope you give one or more of the above a try, but don't complain to me if you're disappointed. If so, you'll just have to make the trip out to Tucson in 2018 and select your own up and coming authors.


text:
Q: constexpr Offsetof with pointer to member data Just before this question is being dismissed for being a duplicate, most (if not all) questions have accepted-answers with outdated / undefined behavior solutions.
The question:
Is there a way to get at, compile-time, the offset of a pointer to member data that:

*

*does not rely on undefined behavior (nullptr things)

*Works on the latest gcc version (the gcc trunk in compiler explorer)

*works the same way as offsetof (or similarly, like the proposed code do).

I do not care about:

*

*non standard-layout types

*msvc compatibility. (it could be nice, but optional)

*having a special case for a specific compiler

The issue:
With the trunk version of GCC, the following trick (hack) does not work:
#include <cstdint>
#include <cstddef>

namespace detail
{
    // The union stuff is for CLang to avoid creating warnings
    template<typename T, auto MPtr>
    struct offsetof_ptr_helper
    {
        union helper_t { int i = 0;  T value; };
        static constexpr helper_t v = {};
        static constexpr size_t sz = sizeof
        (uint8_t[
            (uint8_t *)&(v.value.*MPtr) -
            (uint8_t *)&v.value
        ]);
    };
}

template<typename T, auto MPtr>
static constexpr size_t offsetof_ptr()
{
    return detail::offsetofptr_helper<T, MPtr>::sz;
}

size_t f()
{
    struct X { char c[10]; int a; };
    return offsetof_ptr<X, &X::a>();
}

To be clear, this is a hack using C++98 features and this is not a real surprise that its support is being removed by latest compilers. It works on clang (using the -std=gnu++17 flag) and gcc (including/up-to g++ 7.3 using the flag -std=c++17).

A: If you jump to the definition of offsetof in VS, it gives you this:
#define offsetof(s,m) ((::size_t)&reinterpret_cast<char const volatile&>((((s*)0)->m)))

Modified a bit to match your problem:
template<typename T, auto MPtr>
static constexpr size_t offsetof_ptr()
{
    return ((::size_t) & reinterpret_cast<char const volatile&>((((T*)0)->*MPtr)));
}

size_t f()
{
    struct X { char c[10]; int a; };
    return offsetof_ptr<X, &X::a>();
}

This compiles on GCC and MSVC. (It requires C++17 because of the template auto parameter.)

A: For GCC compiler it's relatively easy to support constexpr compile-time calculation of field offset via member pointer. Solution below works without nullptrs, unions and compile-time struct instantiation and uses c++17. Also there are no requirements like construct-ability, small size or being constexpr-compatible class/struct
#include <type_traits>
#include <functional>
#include <cstdint>

template<typename> struct struct_member_types;
template<typename T, typename F> struct struct_member_types<F T::*> {
  using struct_type = T;
  using member_type = F;
};
template<typename T> using struct_type_t = typename struct_member_types<T>::struct_type;
template<typename T> using member_type_t = typename struct_member_types<T>::member_type;

template<auto field> struct constexpr_field_offset {
  using T = struct_type_t<decltype(field)>;
  using F = member_type_t<decltype(field)>;
  static constexpr const char const_holder = 0;
  static constexpr const T& const_value = reinterpret_cast<const T&>(const_holder);
  static constexpr const F T::* const_field = field;
  static constexpr const char* base_addr = &reinterpret_cast<char const&>(const_value);
  static constexpr const char* field_addr = &reinterpret_cast<char const&>(const_value.*const_field);
  static constexpr const size_t offset = field_addr - base_addr;
};

template<auto field> inline constexpr std::size_t constexpr_field_offset_v = constexpr_field_offset<field>::offset;

struct pod_t {
  uint32_t a;
  uint16_t b;
  uint8_t c;
};

struct __attribute__((__packed__)) tricky_t {
private:
  tricky_t() = delete;
  tricky_t(const tricky_t&) = delete;
  tricky_t(tricky_t&&) = delete;
  ~tricky_t() = delete;
public:
  uint8_t a;
  uint32_t b;
};

int main() {
  static_assert(
    constexpr_field_offset_v<&pod_t::a> == 0,
    "Fail"
  );
  static_assert(
    constexpr_field_offset_v<&pod_t::b> == 4,
    "Fail"
  );
  static_assert(
    constexpr_field_offset_v<&pod_t::c> == 6,
    "Fail"
  );

  static_assert(
    constexpr_field_offset_v<&tricky_t::a> == 0,
    "Fail"
  );
  static_assert(
    constexpr_field_offset_v<&tricky_t::b> == 1,
    "Fail"
  );

  return 0;
}

Live demo: https://godbolt.org/z/r163c1KMP


text:
Best books about fiction and mystery that are the best sellers of all time
In 2012, the epidemic of zombies broke out, pushing humans to the brink of destruction. But luckily escape the chase of the bloodthirsty zombies but the female student was tricked into being a prey for a beast and its genome was invaded into the body. After a hundred-year-long sleep, she regained consciousness in a beastly form with an extraordinary power.
Through the fierce battles with humans, zombies and robots, her resilience, integrity but equally good and honest has made the leaders of these armies to be amazed and free from bottomless vibrations.
If you are a fan of mysterious and fantasy literature, the God of War is a work that you should not ignore at all
Death comes as the end- Agatha Christie
In Egypt in 2000 BC, death is considered to bring meaning to life. At the foot of a cliff is Nofret's crumbling body. Young, beautiful and cruel, most people agree that it is destiny – she deserves to die like a snake!
However, at her father's house on the banks of the Nile, the daughter of the missionary Renisenb thought that the woman's death was suspicious. More and more she believes the germ of evil flourishes in her home – and helplessly witnesses the family's infatuation in death.
Alchemist – the secret of immortal Nicholas Flamel – Michael Scott
From the disappearance of an old book … The modern world can be torn and broken. The person who holds the secret can kill the world. And when no one is against them, Dee and those like him will release the dark Elders into the human world again. Everything will be very chaotic, civilization will collapse. Where's Nicholas?
Nicholas Flamel was an alchemist, born in 1330. The battle between Immortal Flamel and Dark Dee took place between the era of wifi, ipod, internet, laptop and mobile phones that unintentionally attracted participation of twins Josh and Sophie Newman.
The appearance of the sisters is quite similar to the prediction in Codex that existed thousands of years ago by Abraham. In the battle between Flamel Immortal and Dark Dee, the two sisters, in front of which Sophie was awakened to her potential powers.
This is one of the very good and worth reading books about the mystical and fictional topic.


2170 Blakers Boulevard, Bluffton, SC, 29909 - Photos, Videos & More!
Located in a desirable community of Mill Creek at Cypress Ridge, close to schools, shopping, & dining in Bluffton. Short drive to Savannah. Property is light & bright with cathedral ceilings, lots of closets, oversized 2 car garage, stainless steel appliances, spacious corner lot by a walking trail around a lagoon with a dock & resort-style amenities: 3 story fitness complex including a studio, cardio & weight rooms, tennis & basketball courts, playground, clubhouse, dog park, & community pool with lazy river, all included in a low association fee. 3-zone HVAC system was replaced in 2018 with a 5-year warranty. Zoned for the May River HS.


Celebrate restitution of your Constitutional right!
WHICH ACCURATELY DESCRIBES THE WORK YOU DO!
The amended law will restrict only the title "registered interior designer" to those who qualify under the previously established guidelines.
This bill to amend the "pure" title law was filed in order to avoid defending against the lawsuit filed by the Institute for Justice challenging violation of Oklahoma citizens' First Amendment rights, which inevitably would have been lost by Oklahoma.
So go ahead, Oklahoma designers — celebrate the freedom you deserve!
Oklahoma's violation of interior designers' free speech rights is OVER!
SPIN, DENIAL, OR PLAIN STUPIDITY?
How utterly absurd to think that any intellegent, informed person would actually believe that.
Hello IIDA! Perhaps you haven't heard…. IDPC will expose ALL such blatantly untrue and/or misleading statements and provide the design community with the TRUTH!
Of the five states that enacted "pure" title acts, i.e. they restricted the use of the terms "interior designer" and "interior design," New Mexico, Illinois, Texas and Oklahoma have been turned back, allowing designers' First Amendment rights to be restored.
Only Connecticut's pure title law remains — but a lawsuit challenging their law was filed by the Institute for Justice in September, 2008, and CT will almost most likely come to realize their indefensible position and join their predecessors in waving the white flag. And we will be only too happy to report that good news when it happens.
Even ASID has their white flag billowing in the breeze — their "new" legislation policy admits the title "interior designer" cannot be restricted and in defeat, have retreated from their goal of securing that title for a very tiny minority of elitist insiders.
Soon, perhaps even by the end of 2009, the United States of America will no longer be a nation that violates ANY interior designers' rights to accurately describe the services they provide or to use the title which portrays their professional occupation.
This has been an exciting month for our Freedom Movement, but. . .
Thank you IJ, for restoring the rights of Oklahoma designers!
But the fight is not over. . .
If you have any questions, please feel free to contact us at info@IDPCinfo.org.
IDPC is the only national organization solely dedicated to protecting the rights and livelihoods of ALL designers in our country.
Click here to become a member of IDPC.
View full formatted email with all links here.


text:
#pragma once

#include "stdafx.h"

#define CMD_MAX_LEN 8192

enum cmd_err {
	CMD_ERR_SUCCESS, /* no error */
	CMD_ERR_TOO_LONG, /* exceeded maximum command length (CMD_MAX_LEN) */
	CMD_ERR_POPEN_FAILED /* _tpopen() was unsuccessful */
};

enum cmd_err run(int*, LPCTSTR, ...);
enum cmd_err runw(FILE**, LPCTSTR, ...);

redpajama_set_name: RedPajamaGithub


Smokey Diamond learned today that the ancestry group–findyourroots.com, has put up a kickstarter page to raise money to provide free DNA Tests for racists. The tests which will determine percentage country or region of origin cost about $100. People who take the test are invariably surprised by how diverse their backgrounds are.
This entry was posted in gang gang dance, Humor, parody and tagged ancestry, DNA test, racism, racists, smokey diamond. Bookmark the permalink.
Thanks! I enjoyed this article very much. I used to live in California, where my husband and I enjoyed Rocky Jr free-range chickens. (I think they really are. . . ). Now we live in France where we are almost invariably diostpainped with the chicken — even when you pay a very high price for it. Just can't figure that out. The French are so good about supporting small business. I guess more research would be a good thing.


text:
Q: Getting an empty array when trying to filter out a single object based on it's Id from react-redux store My filter function is currently returning an empty array. Instead of an array containing the matched object based on the Id.
console:
operators (51) [{…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}]0: created_at: "2022-06-02T07:21:08.492Z"id: 3name: "operator1"phone: 1478subdomain: "test101"updated_at: "2022-06-02T07:21:08.492Z"user_id: 1[[Prototype]]: Object1: {id: 4, name: 'operator4', phone: 14785, subdomain: 'test104', created_at: '2022-06-02T13:13:42.898Z', …}2: {id: 5, name: 'operator12', phone: 14782, subdomain: 'test20', created_at: '2022-06-03T06:51:12.950Z', …}3: {id: 2, name: 'test1r', phone: 1234451699, subdomain: 'sub10', created_at: '2022-06-01T15:51:29.098Z', …}4: {id: 6, name: 'operator16', phone: 147823, subdomain: 'test21', created_at: '2022-06-06T14:17:25.576Z', …}5: {id: 7, name: 'operator22', phone: 1478237, subdomain: 'test213', created_at: '2022-06-06T14:59:30.342Z', …}6: {id: 8, name: 'operator23', phone: 14782376, subdomain: 'test2153', created_at: '2022-06-06T17:07:34.840Z', …}7: {id: 9, name: 'crystal parking', phone: 81059218, subdomain: 'sub27', created_at: '2022-06-07T17:56:09.142Z', …}8: {id: 10, name: 'lay park', phone: 70255956, subdomain: 'sub11', created_at: '2022-06-07T22:32:54.829Z', …}9: {id: 11, name: 'monk parking', phone: 82059218, subdomain: 'sub07', created_at: '2022-06-07T22:35:24.980Z', …}10: {id: 12, name: 'mabilla park', phone: 71255956, subdomain: 'sub04', created_at: '2022-06-07T22:38:09.079Z', …}11: {id: 13, name: 'java parking', phone: 81055418, subdomain: 'sub19', created_at: '2022-06-07T23:07:42.734Z', …}12: {id: 14, name: 'loading park', phone: 81159215, subdomain: 'sub24', created_at: '2022-06-07T23:11:51.894Z', …}13: {id: 15, name: 'laya park', phone: 70255752, subdomain: 'test2167', created_at: '2022-06-07T23:25:47.786Z', …}14: {id: 16, name: 'cornerStone park', phone: 70980956, subdomain: 'sub21', created_at: '2022-06-09T08:23:47.909Z', …}15: {id: 17, name: 'IPC Staging', phone: null, subdomain: 'ipc-staging', created_at: '2022-06-09T19:31:21.886Z', …}16: {id: 18, name: 'operator121331', phone: 1245787989, subdomain: 'test46', created_at: '2022-06-16T11:43:54.280Z', …}17: {id: 19, name: 'operator81', phone: 124548, subdomain: 'dsrt7', created_at: '2022-06-16T12:36:08.918Z', …}18: {id: 20, name: 'operator87', phone: 124542, subdomain: 'dsrt5', created_at: '2022-06-16T13:40:33.744Z', …}19: {id: 21, name: 'operator88', phone: 124541, subdomain: 'dsrt9', created_at: '2022-06-17T21:25:24.321Z', …}20: {id: 23, name: 'operator89', phone: 124544, subdomain: 'dsrt11', created_at: '2022-06-17T21:29:02.275Z', …}21: {id: 24, name: 'PLECCO Technologies, Inc.', phone: 184334589, subdomain: 'titos1', created_at: '2022-06-18T05:46:53.596Z', …}22: {id: 25, name: 'sat park', phone: 1923671, subdomain: 'sub13', created_at: '2022-06-18T11:49:40.806Z', …}23: {id: 26, name: 'me park', phone: 1923679, subdomain: 'sub14', created_at: '2022-06-18T13:25:14.101Z', …}24: {id: 27, name: 'lushu park', phone: 1923673, subdomain: 'sub06', created_at: '2022-06-20T07:21:06.236Z', …}25: {id: 28, name: 'lome park', phone: 1923672, subdomain: 'sub09', created_at: '2022-06-20T08:37:14.750Z', …}26: {id: 29, name: 'operator85', phone: 124546, subdomain: 'dsrt13', created_at: '2022-06-21T15:08:52.690Z', …}27: {id: 30, name: 'ladaf park', phone: 1923677, subdomain: 'sub18', created_at: '2022-06-21T15:13:51.959Z', …}28: {id: 31, name: 'operator123', phone: 147821, subdomain: 'test120', created_at: '2022-06-23T00:35:39.639Z', …}29: {id: 32, name: 'operator121339', phone: 1245787982, subdomain: 'test09', created_at: '2022-06-24T13:05:35.451Z', …}30: {id: 33, name: 'operator121332', phone: 1245787981, subdomain: 'test01', created_at: '2022-06-24T23:30:48.697Z', …}31: {id: 34, name: 'authen parking', phone: 19236731, subdomain: 'sub16', created_at: '2022-06-26T14:53:01.328Z', …}32: {id: 35, name: 'larky', phone: 1923675, subdomain: 'sub023', created_at: '2022-06-26T17:21:51.401Z', …}33: {id: 36, name: 'operator131332', phone: 1245747981, subdomain: 'test03', created_at: '2022-06-26T22:18:44.953Z', …}34: {id: 37, name: 'warm park', phone: 1225747981, subdomain: 'test04', created_at: '2022-06-26T22:21:44.050Z', …}35: {id: 38, name: 'wood park', phone: 1623673, subdomain: 'sub018', created_at: '2022-06-26T22:58:01.366Z', …}36: {id: 39, name: 'look park', phone: 1523672, subdomain: 'sub33', created_at: '2022-06-26T23:06:42.957Z', …}37: {id: 40, name: 'vodo park', phone: 1123676, subdomain: 'sub221', created_at: '2022-06-26T23:37:22.580Z', …}38: {id: 41, name: 'demo park', phone: 1923372, subdomain: 'sub031', created_at: '2022-06-27T13:21:47.356Z', …}39: {id: 42, name: 'hilltop parking', phone: 1923674, subdomain: 'sub034', created_at: '2022-06-27T14:11:32.882Z', …}40: {id: 43, name: 'lagos park', phone: 1923572, subdomain: 'sub035', created_at: '2022-06-28T14:21:40.734Z', …}41: {id: 44, name: 'ooiuwdddt', phone: 787494, subdomain: 'subd', created_at: '2022-07-06T16:07:18.592Z', …}42: {id: 45, name: 'latam park', phone: 1922671, subdomain: 'sub091', created_at: '2022-07-06T16:29:14.202Z', …}43: {id: 46, name: 'find parking', phone: 1920674, subdomain: 'sub049', created_at: '2022-07-06T21:06:55.743Z', …}44: {id: 47, name: 'lotus', phone: 787491, subdomain: 'sub016', created_at: '2022-07-07T08:25:42.692Z', …}45: {id: 48, name: 'manti park', phone: 1913676, subdomain: 'sub019', created_at: '2022-07-07T12:34:14.164Z', …}46: {id: 49, name: 'lumbak parking', phone: 1913671, subdomain: 'sub087', created_at: '2022-07-07T17:29:36.156Z', …}47: {id: 50, name: 'agbor park', phone: 1923670, subdomain: 'sub071', created_at: '2022-07-07T17:52:41.114Z', …}48: {id: 51, name: 'lotus1', phone: 787496, subdomain: 'sub634', created_at: '2022-07-07T19:14:03.874Z', …}49: {id: 52, name: 'peak park', phone: 1923676, subdomain: 'sub041', created_at: '2022-07-07T19:39:53.717Z', …}50: {id: 53, name: 'fungy park', phone: 1923571, subdomain: 'sub032', created_at: '2022-07-07T19:53:41.606Z', …}length: 51[[Prototype]]: Array(0)
NewLocation.js:41

operator []

length: 0[[Prototype]]: Array(0)

My code:
const NewLocations = () => {
  const { operatorId } = useParams();
  console.log('id', operatorId);
  const [successful, setSuccessful] = useState(false);
  const operators = useSelector((state) => state.operators.data)
  console.log('operators', operators);
  const operator = operators.filter((operator) => operator.id === operatorId)
  console.log('operator', operator);

  remaining codes...

I really don't know what I'm missing...
I have check similar questions/solutions, but none solve my issue.

A: Might be the id that you are extracting is not there in the operators array, that's why you are getting an empty array
you can run this line of code whether the id is there or not
  const operator = operators.filter((operator) => operator.id !== operatorId)

A: The useParams hook will return any values as strings. In your case, you need the operatorId to be a number. You can use parseInt to make the comparison work:
const operator = operators.filter((operator) => operator.id === parseInt(operatorId));


text:
UPDATED 1/17/23 – Fire Chief Job Opening
The Town of Blandford is seeking candidates to fill a part-time Fire Chief position responsible for overseeing the operation of the all-volunteer department, pursuant to Massachusetts General Laws, Chapter 48, Section 42. Candidates must have three to five years' experience, with minimum of two years in supervisory position, in fire/EMS service. The compensation for this 19.5-hour-a-week position is $23.00-25.00 an hour. The Town of Blandford is an Equal Employment Opportunity/Affirmative Action Employer.
Read the full description and find instructions on how to apply.
January 17, 2023 in Fire Department, Job Listings
POSTPONED – Planning Board Meeting for 2/1/23
The Planning Board meeting scheduled for Wednesday, February 1 has been postponed to February 8.
January 17, 2023 in Meetings, Planning Board
Public Hearing – February 8, 2023 – Planning Board
Pursuant to MGL, CH40A Sec. 9, the Planning Board will hold a Public Hearing at the Blandford Town Hall, 1 Russell Stage Road, Blandford, MA 01008 at 6:00pm on February 8, 2023. This hearing is scheduled under the following Zoning By-Laws of the Town of Blandford: Section IX – Site Plan Review and Special Permits and XV – Adult Use Marijuana Establishments. of the Zoning By-Laws of the Town of Blandford to consider the application for a Site Plan Review and Special Permit for PUDDING HILL FARM, LLC, Marijuana Cultivation Project, located at 1 Julius Hall Road, Blandford, MA 01008. This application is for a Tier 1 Cannabis Cultivation Facility.
The applicants, Thomas W. Fielding and Michael Scott O'Connor propose to start a small indoor heritage marijuana cultivation facility in an existing, renovated barn, located on 1 Julius Hall Road, Lot No. 414-0-17 which consists of 3.6 acres, that is currently zoned as Agricultural and Undeveloped.
The completed application and plans are available for public inspection here.
Or make an appointment to view a hard copy of these forms at the Town Hall by e-mailing the Planning Board Chair at [email protected].
If unable to attend please submit comments to [email protected] or by writing, to the Blandford Planning Board at 1 Russell Stage Road, Blandford, MA 01008.
Paul Martin, Chairman
Blandford Planning Board
January 13, 2023 in Planning Board, Public Hearings
Town Offices Closed for Martin Luther King Jr. Day – 1/16/23
The Town Offices will be closed on Monday, January 16, 2023 in observance of Martin Luther King Jr. Day.
January 10, 2023 in Community, Meetings, Office Hours
ASSISTANT TREASURER-COLLECTOR/TREASURER-COLLECTOR
The Town of Blandford is seeking candidates to fill an Assistant Treasurer-Collector position responsible for administrative and supervisory work involving the receipt and the collection of all money due to the Town. Candidates must have a minimum of one to three years' experience in municipal finance. Bachelor's degree in finance or accounting, or more than three years' experience in municipal finance preferred. The compensation range for this 28-hour-a-week benefitted position is $23.00 to $24.00 an hour. The right candidate will have the opportunity for promotion to the position of Treasurer-Collector within one year with a 30-to-40-hour-a-week schedule compensated inside the range of $26.00 to $35.00 an hour. Closing date for all applications is Tuesday, January 24, 2023, by 12:00 noon. The Town of Blandford is an Equal Employment Opportunity/Affirmative Action Employer
January 10, 2023 in Job Listings, Tax Collector