Pringle says metering will increase rather than solve water problems

first_img WhatsApp Twitter Twitter Google+ Pinterest 365 additional cases of Covid-19 in Republic Facebook Man arrested on suspicion of drugs and criminal property offences in Derry A Donegal Councillor is accusing the government of cynically presenting water metering as a solution to the supply problems that have hit the country since Christmas.Cllr Thomas Pringle says the problems experienced after the severe weather will not be helped by the introduction of meters. He says the real problem is that ater services will continue to be starved of investment and the replacement of problem mains will continue at a snails pace.Cllr Pringle says Donegal County Council had to borrow over €9.5million to install meters for just over 10,000 customers.With more than three times as many residential customers to be metered, he fears a huge debt will be incurred this year, with higher charges the end result………..[podcast]http://www.highlandradio.com/wp-content/uploads/2011/01/pring1pm.mp3[/podcast] WhatsApp By News Highland – January 5, 2011 Main Evening News, Sport and Obituaries Tuesday May 25th center_img Pinterest Facebook Previous articleApproval for Macosquin dump angers local residentsNext articleBureaucracy blamed for stopping schools opening News Highland RELATED ARTICLESMORE FROM AUTHOR Pringle says metering will increase rather than solve water problems 75 positive cases of Covid confirmed in North Newsx Adverts Gardai continue to investigate Kilmacrennan fire Further drop in people receiving PUP in Donegal Google+last_img read more

Pregnant women with COVID-19 may not pass virus to newborn, study suggests

first_img Related Pregnant women may be especially vulnerable to developing more severe cases of COVID-19 following SARS-CoV-2 infection, but little is known about their anti-SARS-CoV-2 immune response or how it may affect their offspring.In a study published in JAMA Network Open, a group led by investigators at Harvard-affiliated Massachusetts General Hospital (MGH) provides new insights that could help improve care for these women and their newborns and emphasizes the need for pregnant women to be considered in vaccine rollout plans.The study included 127 pregnant women in their third trimester who received care at three Boston hospitals between April 2 and June 13, 2020. Among the 64 women who tested positive for SARS-CoV-2, investigators detected no virus in maternal or cord blood (despite detection in the women’s respiratory system), no signs of the virus in placentas and no evidence of viral transmission to newborns. The researchers suspect that transmission to the fetus may be blocked not only due to the lack of virus in the mothers’ blood, but also because the major molecules used by SARS-CoV-2 to enter cells (ACE2 receptor and TMPRSS2 enzyme) are often not physically located together in the placenta.Most of the women who tested positive developed antibody responses against SARS-CoV-2 proteins, but mother-to-newborn transfer of anti-SARS-CoV-2 antibodies through the placenta was significantly lower than transfer of anti-influenza antibodies. Experts detail vaccine unknowns, need to continue masking, distancing Mass. General study shows the benefits of inhaled nitric oxide therapy for pregnant patients with severe and critical COVID-19 Fauci says herd immunity possible by fall, ‘normality’ by end of 2021 Breathing freely “Our finding of compromised mother-to-baby transfer of SARS-CoV-2–specific antibodies in third trimester infections has implications for maternal vaccine administration. Specifically, it highlights that pregnant women are a key population to consider in vaccine rollouts. It also raises questions regarding the optimal timing of vaccine administration to best support maternal and newborn immunity,” says lead author Andrea Edlow, a maternal-fetal medicine specialist at MGH and an assistant professor of obstetrics, gynecology and reproductive biology at Harvard Medical School.Edlow notes that transplacental transfer of antibodies to the fetus is typically highest in the third trimester, so it was unexpected to see significantly reduced transfer of SARS-CoV-2 antibodies relative to those against influenza. “Understanding the mechanisms underlying this inefficient transfer of SARS-CoV-2–specific antibodies after third trimester infection, as well as understanding whether vaccine-generated antibodies have the same or different properties than those from actual infection with the virus, will be critical directions for future research,” she says.last_img read more

Are members upside-down on auto loans?

first_img 6SHARESShareShareSharePrintMailGooglePinterestDiggRedditStumbleuponDeliciousBufferTumblr Higher loan amounts bring greater risk for members and your CU.Increasing numbers of Americans appear at risk of going upside-down on their auto loans, meaning they’d owe more than the car is worth. And many of these Americans might be your members.The market forces that put people into this predicament also make it less likely consumers can repay the loans if they totaled their vehicles in an accident.If your credit union’s auto loan portfolio mirrors the national trends toward larger loans and longer terms, many of your members will be at risk.Front-line employees are well-positioned to explain to members how they can put themselves on better footing.Financial safety nets shrinkFor the most part, Americans have kept current on their auto loan payments. But a growing percentage appears to have little or no financial safety net. continue reading »last_img read more

Palisadoes Shoreline Project Completed Within Budget

first_imgWork on the Palisadoes Shoreline Protection Project in Kingston has been completed within budget, Transport, Works and Housing Minister, Dr. the Hon. Omar Davies, has announced.He made the disclosure during Friday’s, February 15, media briefing at the Transport, Works and Housing Ministry’s offices in Kingston, where he updated journalists on a range of projects and developments, being spearheaded by the Ministry. The Palisadoes Shoreline Protection Project, which commenced in September 2010, was completed by contractors, China Harbour Engineering Company (CHEC), within a 15-month period. The development entailed significant upgrading works along the corridor preceding the roadway leading to the Norman Manley International Airport.“I believe we all have seen it and realize it is an excellent job; and it was completed in December of last year (2012) at the initial contracted price of US$65.4 million,” Dr. Davies said.The Minister also indicated that additional work may need to be effected on an area beyond the airport’s round-a-bout, along the corridor leading to Port Royal. This undertaking, he pointed out, was not in the original scope of the project, but is the focus of concern due to erosion.Meanwhile, Dr. Davies advised that the deadline for the completion of the Jamaica Development Infrastructure Programme (JDIP) has been extended to June 2013 to facilitate the conclusion of several projects.He informed that JDIP was originally scheduled for completion at the end of the 2012/13 fiscal year in March, but has been pushed back due to delays in the completion of work on some of the programme’s original projects.These include: the Cassia Park and Queensborough bridges in the Corporate Area, where work is 88 per cent and 95 per cent complete respectively; and the Westmoreland Bridge in St. Mary, where 83 per cent of the work is done. Dr. Davies disclosed that approximately US$50 million remains to be spent under the project.He pointed out that the Government’s 15 per cent input, totalling some $800 million, which is reflected in the Supplementary Estimates of Expenditure as savings in the Budget, will be carried forward to the 2013/14 financial year to complement the equivalent of 85 per cent of the financing being provided by the China EXIM Bank.The JDIP, which is being carried out by contractors, China Harbour Engineering Company (CHEC), is a major Government of Jamaica undertaking, which began in 2010 to significantly improve the island’s road network.last_img read more

Patty Smyth Returns With Christmas Album

first_imgAfter helping define the 1980s new wave aesthetic with her band Scandal, singer-songwriter and performer, Patty Smyth, continued her triumphant run throughout the 1990s, writing and performing chart-topping and award-winning singles. But since 1999’s greatest hits package, Patty hasn’t issued any albums. Now, just in time for the holiday season, Patty is gifting her fans with her first release in 16 years with the Christmas album, Come On December.Patty Smyth – Come On DecemberThe eight-track album puts Patty’s signature pristine and emotive vocals front and center within this cozy, elegant, acoustic pop-rock collection of cherished standards and spirited originals. Patty’s eloquent, signature sense of phrasing and melody make this album both a holiday classic and unmistakably a Patty Smyth record.On Come On December, she sings defining modern versions of “Have Yourself A Merry Little Christmas,” “The Christmas Song,” “Do You Hear What I Hear,” and “Auld Lang Syne.” Her newly minted originals, “Come On December,” “Walk With Me” and “Broken” exquisitely conjure up feelings of instant nostalgia and heartwarming emotionality brought on by the cherished canon of holiday music.In conjunction with the album, Patty has launched a PledgeMusic campaign that runs from Friday, Oct. 23rd thru Thursday, November 19th. One hundred percent of the money from the campaign will benefit Headstrong, a non-profit organization whose mission is to provide cost-free, stigma-free, and bureaucracy-free mental healthcare to post-911, and Iraq and Afghanistan combat veterans.Come On December will be available on Patty’s online store and digital stores (via Tunecore) Friday, November 20th. In December, Patty and band will be performing in both New York and Los Angeles. Currently, Patty is in the studio working on her 2016 release.last_img read more

NEW YEAR NEW DRAMA GLOBAL GEARS UP FOR THE SEASON 7 PREMIERE

first_imgAdvertisement Twitter Click here for the latest promoTORONTO – Big Brother Canada is back! Global announced today the seventh season of its monster hit reality series Big Brother Canada premieres Wednesday, March 6 at 7 p.m. ET/PT. The reality juggernaut returns to Global’s schedule three nights a week on Wednesdays at 7 p.m. ET/PT, Thursdays at 8 p.m. ET/PT, and Sundays at 8 p.m. ET/PT. Hosted by Arisa Cox, the award-winning series takes viewers on a wild ride filled with socially savvy, and not so savvy, houseguests, unpredictable twists, unforgettable challenges, and jaw-dropping drama.“We are so proud to be ushering in an all-new season of Big Brother Canada on Global,” said Maria Hale, Senior Vice President, Global Entertainment & Content Acquisition, Corus Entertainment. “With a new house and a whole new crop of houseguests, we can’t wait to bring viewers another hit season of the show they can’t get enough of. Growing its audience year over year, we take great pride in creating an unforgettable season filled with epic TV moments and even more snackable digital content for our hungry viewers.” Following a coast-to-coast casting call, Big Brother Canada plucks a group of hand-picked strangers from their homes, sequesters them from the outside world, and places them inside a house outfitted wall-to-wall with cameras and microphones that capture their every move. Competing for a grand cash prize, each week the houseguests battle in a series of challenges that give them power or punishment, voting each other out until the fate of the final two is decided by a jury of fellow houseguests.“We have planned the most epic and exciting season of Big Brother Canada and cannot wait to share it with our amazing fans,” said Executive Producer & SVP Erin Brock. “What we have in store for our batch of houseguests in Season 7 will be a wildly exciting ride that viewers will be talking about all season long!”Additional details about Season 7 of Big Brother Canada, including this season’s theme, houseguests, and the grand prize details, will be announced in the coming weeks.In anticipation of the premiere, fans can stream their favourite moments from Season 6 on GlobalTV.com, Global GO (now available on Apple TV, Google Chromecast, and Amazon Fire TV) and stay updated on all things #BBCAN7 on BigBrotherCanada.ca. For Season 7, viewers can stream Big Brother Canada live on GlobalTV.com and Global GO by signing in with their TV service provider credentials or catch up the next day on GlobalTV.com, Global GO, and BigBrotherCanada.ca.While viewers anxiously await the electrifying new #BBCAN7 season, fans can watch the season two premiere of Big Brother: Celebrity tonight at 8 p.m. ET/PT on Global. The star-studded series airs multiple nights over the course of three weeks, before a winner is crowned on Wednesday, February 13. For more information, including full schedule details, visit GlobalTV.com.Commissioned by Corus Entertainment, Season 7 of Big Brother Canada is produced by Insight Productions Ltd. in association with Corus Entertainment and Endemol Shine. Executive Producers are John Brunton and Erin Brock.SOCIAL MEDIA LINKS:#BBCAN7Twitter: @[email protected]  @GlobalTV_PR @CorusPRFacebook: http://www.facebok.com/BigBrotherCAhttps://www.facebook.com/GlobalTVInstagram: @[email protected] Television is a Corus Entertainment Network.Corus EntertainmentCorus Entertainment Inc. (TSX: CJR.B) is a leading media and content company that creates and delivers high quality brands and content across platforms for audiences around the world. The company’s portfolio of multimedia offerings encompasses 44 specialty television services, 39 radio stations, 15 conventional television stations, a global content business, digital assets, live events, children’s book publishing, animation software, technology and media services. Corus’ roster of premium brands includes Global Television, W Network, OWN: Oprah Winfrey Network Canada, HGTV Canada, Food Network Canada, HISTORY®, Showcase, National Geographic Channel, Q107, CKNW, Fresh Radio, Disney Channel Canada, YTV and Nickelodeon Canada. Visit Corus at www.corusent.com.About Insight Productions Ltd.Insight Productions, known for its award-winning ratings juggernauts, is Canada’s most established content producer and an industry leader in the development, financing, and production of hit programming, both scripted and unscripted, as well as digital content.  With thousands of hours of programming under its belt, the company has created some of the most dynamic and top-rated programs in the world including Big Brother Canada (for which Erin Brockserves as EP and Showrunner alongside EP John Brunton); The Amazing Race Canada; The JUNO Awards; Top Chef Canada; Intervention; and original formats including The Launch and Battle of the Blades. Insight’s scripted programming includes award-winning Ready Or Not; Falcon Beach; Hatching, Matching & Dispatching A Fury Christmas; But I’m Chris Jericho!; and The Jon Dore Television Show. In 2017, Insight produced The Tragically Hip: A National Celebration, a live concert special watched by one in three Canadians. Insight Productions was founded in 1979 and has since created thousands of hours of groundbreaking content.  For more information on Insight Productions, please visit www.insighttv.com or on Twitter – @insightprod. Or Facebook www.facebook.com/InsightProductions. Facebook Advertisement Login/Register With: Advertisement LEAVE A REPLY Cancel replyLog in to leave a comment last_img read more

Sherin Thomas explains how to build a pipeline in PyTorch for deep

first_imgA typical deep learning workflow starts with ideation and research around a problem statement, where the architectural design and model decisions come into play. Following this, the theoretical model is experimented using prototypes. This includes trying out different models or techniques, such as skip connection, or making decisions on what not to try out. PyTorch was started as a research framework by a Facebook intern, and now it has grown to be used as a research or prototype framework and to write an efficient model with serving modules. The PyTorch deep learning workflow is fairly equivalent to the workflow implemented by almost everyone in the industry, even for highly sophisticated implementations, with slight variations. In this article, we explain the core of ideation and planning, design and experimentation of the PyTorch deep learning workflow. This article is an excerpt from the book PyTorch Deep Learning Hands-On by Sherin Thomas and Sudhanshi Passi. This book attempts to provide an entirely practical introduction to PyTorch. This PyTorch publication has numerous examples and dynamic AI applications and demonstrates the simplicity and efficiency of the PyTorch approach to machine intelligence and deep learning. Ideation and planning Usually, in an organization, the product team comes up with a problem statement for the engineering team, to know whether they can solve it or not. This is the start of the ideation phase. However, in academia, this could be the decision phase where candidates have to find a problem for their thesis. In the ideation phase, engineers brainstorm and find the theoretical implementations that could potentially solve the problem. In addition to converting the problem statement to a theoretical solution, the ideation phase is where we decide what the data types are and what dataset we should use to build the proof of concept (POC) of the minimum viable product (MVP). Also, this is the stage where the team decides which framework to go with by analyzing the behavior of the problem statement, available implementations, available pretrained models, and so on. This stage is very common in the industry, and I have come across numerous examples where a well-planned ideation phase helped the team to roll out a reliable product on time, while a non-planned ideation phase destroyed the whole product creation. Design and experimentation The crucial part of design and experimentation lies in the dataset and the preprocessing of the dataset. For any data science project, the major timeshare is spent on data cleaning and preprocessing. Deep learning is no exception from this. Data preprocessing is one of the vital parts of building a deep learning pipeline. Usually, for a neural network to process, real-world datasets are not cleaned or formatted. Conversion to floats or integers, normalization and so on, is required before further processing. Building a data processing pipeline is also a non-trivial task, which consists of writing a lot of boilerplate code. For making it much easier, dataset builders and DataLoader pipeline packages are built into the core of PyTorch. The dataset and DataLoader classes Different types of deep learning problems require different types of datasets, and each of them might require different types of preprocessing depending on the neural network architecture we use. This is one of the core problems in deep learning pipeline building. Although the community has made the datasets for different tasks available for free, writing a preprocessing script is almost always painful. PyTorch solves this problem by giving abstract classes to write custom datasets and data loaders. The example given here is a simple dataset class to load the fizzbuzz dataset, but extending this to handle any type of dataset is fairly straightforward. PyTorch’s official documentation uses a similar approach to preprocess an image dataset before passing that to a complex convolutional neural network (CNN) architecture. A dataset class in PyTorch is a high-level abstraction that handles almost everything required by the data loaders. The custom dataset class defined by the user needs to override the __len__ and __getitem__ functions of the parent class, where __len__ is being used by the data loaders to determine the length of the dataset and __getitem__ is being used by the data loaders to get the item. The __getitem__ function expects the user to pass the index as an argument and get the item that resides on that index: from dataclasses import dataclassfrom torch.utils.data import Dataset, [email protected](eq=False)class FizBuzDataset(Dataset):    input_size: int    start: int = 0    end: int = 1000    def encoder(self,num):        ret = [int(i) for i in ‘{0:b}’.format(num)]        return[0] * (self.input_size – len(ret)) + ret    def __getitem__(self, idx):        x = self.encoder(idx)        if idx % 15 == 0:            y = [1,0,0,0]        elif idx % 5 ==0:            y = [0,1,0,0]        elif idx % 3 == 0:            y = [0,0,1,0]        else:            y = [0,0,0,1]        return x,y           def __len__(self):        return self.end – self.start The implementation of a custom dataset uses brand new dataclasses from Python 3.7. dataclasses help to eliminate boilerplate code for Python magic functions, such as __init__, using dynamic code generation. This needs the code to be type-hinted and that’s what the first three lines inside the class are for. You can read more about dataclasses in the official documentation of Python (https://docs.python.org/3/library/dataclasses.html). The __len__ function returns the difference between the end and start values passed to the class. In the fizzbuzz dataset, the data is generated by the program. The implementation of data generation is inside the __getitem__ function, where the class instance generates the data based on the index passed by DataLoader. PyTorch made the class abstraction as generic as possible such that the user can define what the data loader should return for each id. In this particular case, the class instance returns input and output for each index, where, input, x is the binary-encoder version of the index itself and output is the one-hot encoded output with four states. The four states represent whether the next number is a multiple of three (fizz), or a multiple of five (buzz), or a multiple of both three and five (fizzbuzz), or not a multiple of either three or five. Note: For Python newbies, the way the dataset works can be understood by looking first for the loop that loops over the integers, starting from zero to the length of the dataset (the length is returned by the __len__ function when len(object) is called). The following snippet shows the simple loop: dataset = FizBuzDataset()for i in range(len(dataset)):    x, y = dataset[i]dataloader = DataLoader(dataset, batch_size=10, shuffle=True,                     num_workers=4)for batch in dataloader:    print(batch) The DataLoader class accepts a dataset class that is inherited from torch.utils.data.Dataset. DataLoader accepts dataset and does non-trivial operations such as mini-batching, multithreading, shuffling, and so on, to fetch the data from the dataset. It accepts a dataset instance from the user and uses the sampler strategy to sample data as mini-batches. The num_worker argument decides how many parallel threads should be operating to fetch the data. This helps to avoid a CPU bottleneck so that the CPU can catch up with the GPU’s parallel operations. Data loaders allow users to specify whether to use pinned CUDA memory or not, which copies the data tensors to CUDA’s pinned memory before returning it to the user. Using pinned memory is the key to fast data transfers between devices, since the data is loaded into the pinned memory by the data loader itself, which is done by multiple cores of the CPU anyway. Most often, especially while prototyping, custom datasets might not be available for developers and in such cases, they have to rely on existing open datasets. The good thing about working on open datasets is that most of them are free from licensing burdens, and thousands of people have already tried preprocessing them, so the community will help out. PyTorch came up with utility packages for all three types of datasets with pretrained models, preprocessed datasets, and utility functions to work with these datasets. This article is about how to build a basic pipeline for deep learning development. The system we defined here is a very common/general approach that is followed by different sorts of companies, with slight changes. The benefit of starting with a generic workflow like this is that you can build a really complex workflow as your team/project grows on top of it. Build deep learning workflows and take deep learning models from prototyping to production with PyTorch Deep Learning Hands-On written by Sherin Thomas and Sudhanshu Passi. Read Next F8 PyTorch announcements: PyTorch 1.1 releases with new AI tools, open sourcing BoTorch and Ax, and more Facebook AI open-sources PyTorch-BigGraph for faster embeddings in large graphs Top 10 deep learning frameworkslast_img read more

Pearlman joins Travel Leaders Network as Sr VP International Leisure

first_img<< Previous PostNext Post >> Pearlman joins Travel Leaders Network as Sr. VP, International Leisure Tags: Travel Leaders Network Share Travelweek Group center_img Posted by Wednesday, July 10, 2019 TORONTO — Travel Leaders Network has appointed Lindsay Pearlman to the newly-created position of Senior Vice President, International Leisure.Pearlman reports to Travel Leaders Network President Roger E. Block, CTC.“Lindsay will work with our International Partners to expand Travel Leaders Network leisure programs throughout Latin America, Europe, the Middle East, Africa and Asia Pacific,” said Block. “Many of our international partner agencies have a very large leisure operation in addition to their corporate division and we are pleased that Lindsay will bring his years of industry experience to help us grow our leisure division with partners across many countries.”Pearlman most recently served as Co-President of Ensemble, where he worked for 12 years, including as executive vice president and general manager of the retail travel group. Prior to Ensemble, Pearlman was with American Express Global Travel Services for 11 years in a variety of roles. Based in Toronto, Pearlman will work closely with Angeles Yugdar, Senior Vice President of International Markets for Travel Leaders Group.More news:  Sunwing offers ultimate package deal ahead of YXU flights to SNU, PUJTravel Leaders Network now counts travel agency members in more than 60 countries worldwide as it continues its international expansion.last_img read more