Samuel Davies was a powerful preacher and notable Southern presbyterian. He was the fourth president of Princeton (following Jonathan Edwards), was involved in the Great Awakening, and was instrumental in converting and ministering to many hundreds of black slaves.
Sermons of Samuel Davies, vol. 1, "Christ Precious to All True Believers," in , Vol. 1 (1993 SDG ed.), p. 384.
As a prophet, how sweet are His instructions to a bewildered soul! How precious the words of His lips, which are the words of eternal life! How delightful to sit and hear Him teach the way of duty and happiness, revealing the Father, and the wonders of the invisible state! How transporting to hear Him declare upon what terms an offended God may be reconciled! A discovery beyond the searches of all the sages and philosophers of the heathen world. How reviving is it to listen to His gracious promises and invitations; promises and invitations to the poor, the weary, and the heavy laden, the broken-hearted, and even to the chief of sinners!


Take to the water with Egg Splash, an underwater egg hunt!
This event takes place at Homestead Aquatic Center, 300 Aquatic Drive, Chapel Hill, on Sunday, April 14th, 2019, starting at 9:30 a.m.
Plastic eggs are filled to float and sink in the pool. Kids collect the eggs and turn them in for prizes.
It's for kids age 1-16, and you need to sign them up for their time slot, based on their age.
At the time of this post, most 15-minute time slots still have availability…but not the one for age 4-6, although you can get on a wait list.
The cost is $5 for Chapel Hill residents, and $7 for non-residents.


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Place des Moines 55300 Saint Mihiel03 29 89 15 11
Ville de Saint Mihiel
Comptes-rendus et bulletins municipaux
Arrêtés municipaux, rapports
Vidéos et presse
Démarches et services communaux
État civil/élections/cimetières
Bibliothèque de prêt
Musée d'Art Sacré
Urbanisme et Établissements Recevant du Public (ERP)
Permis de construire, déclaration préalable de travaux
Aides à la rénovation de façade
Établissements Recevant du Public (E.R.P.)
Transports / véhicules électriques
Borne de recharge pour véhicule électrique
Résidence Les Tilleuls
Affouages
Petite Cité de Caractère
Office de Tourisme Coeur de Lorraine
Ligier Richier
Saillant de Saint-Mihiel
Exposition "Le Saillant de Saint-Mihiel 1914-1918, de l'occupation à la libération"
Bibliothèque bénédictine
Abbatiale Saint Michel
Collégiale Saint Étienne
L'abbaye bénédictine
Histoire de Saint Mihiel
Hébergement/Restauration
Gîtes/Chambres d'hôtes
Hôtel/Restaurants
Concours maisons fleuries et jardins ouvriers
Concours "Maisons illuminées"
Festival Baroque
Pershing & Patton Memory Days
Associations patriotiques
Benedictine library
St. Michael's Abbey in Saint-Mihiel was founded in the Carolingian era. The first books (manuscripts) were stored in the church outbuildings at that time. Over the centuries, their number grew, especially after the invention of the printing press in the 15th century. The collection was moved several times but was eventually given a magnificent new home circa 1775, in purpose-built rooms.
Today, the town of Saint-Mihiel is unusually fortunate to have retained much of the collection built up by the Benedictines and to be able to display it in the rooms and on the shelves that it has occupied for most of that time despite the losses resulting from the abandonment of the library between 1791, when it was confiscated as national property, and 1848 when it was entrusted to Saint-Mihiel town council. It also suffered during the destruction that marked the 1914-1918 war.
For the past two centuries, then, the library has been laid out in two rooms with a floor-to-ceiling height of 5 metres. The first of the rooms is square and it is particularly remarkable for two features – its richly decorated moulded plaster ceiling representing the four seasons, the four elements and four of the five continents, and its carved oak panelling dating from the 18th century. The second room is 50 metres long. It is more austere but has 17 windows. Its ceiling and panelling were painstakingly restored after being badly damaged during the First World War.
At present, the so-called "Benedictine" collection consists of almost 9,000 books, most of them from the actual abbey. However, this is not the entire collection. Some of the books were sold, exchanged and, unfortunately, stolen after the French Revolution. On the other hand, the collection has been extended to include books from other sources in the town.
Of the 8,780 "books", 74 are manuscripts dating from the 9th to the 16th centuries. The actual books include 86 incunables (books printed in the 15th century) and 1,150 books from the 16th century. Some 6,000 works contain the handwritten ex-libris of Saint-Mihiel's Benedictine abbey.
The books are not limited to religious subjects. Almost one-half of them consist of history, literature, law, the sciences, travel etc.
Over the summer season, thematic exhibitions turn the spotlight on some of the remarkable works from the first room in the library. Screens set up in the great chamber show the most beautiful pages of manuscripts from the Benedictine collection.
Digitised works can be consulted online during visits to the Benedictine library. A manuscript by Dom Loupvent, a monk at St. Michael's Abbey, describes his journey to the Holy Land in the 16th century. A film about this monk by a researcher can be seen here: http://domloupvent.univ-lorraine.fr/#/la-carte
Other manuscripts, including the famous Gradual (choir book) can be seen here: http://archives.meuse.fr/resource/a011418741123RPcAW4
For information, contact the Coeur de Lorraine tourist office.
Accès rapides:
News immo
Mairie de Saint-Mihiel
Place des Moines
55300 Saint-Mihiel
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© 2020 Ville de Saint Mihiel | Tous droits réservés | Mentions légales | Création et conception Articom

redpajama_set_name: RedPajamaCommonCrawl


text:
from sqlalchemy import event, Column, String, Integer, ForeignKey, BigInteger, UniqueConstraint, Index
from sqlalchemy.dialects.mysql import JSON

from rdr_service.model.base import Base, model_insert_listener, model_update_listener
from rdr_service.model.utils import UTCDateTime6

class ResourceData(Base):
    """
    Resource Data Model
    """
    __tablename__ = "resource_data"

    # Primary Key
    id = Column("id", BigInteger, primary_key=True, autoincrement=True, nullable=False)
    # have mysql set the creation data for each new order
    created = Column("created", UTCDateTime6, nullable=True)
    # have mysql always update the modified data when the record is changed
    modified = Column("modified", UTCDateTime6, nullable=True)
    resourceTypeID = Column("resource_type_id", ForeignKey("resource_type.id"), nullable=False)
    resourceSchemaID = Column("resource_schema_id", ForeignKey("resource_schema.id"), nullable=False)
    uri = Column("uri", String(1024), nullable=True)
    hpoId = Column("hpo_id", Integer, nullable=True)
    resourcePKID = Column("resource_pk_id", Integer, nullable=True)
    # Alternate Primary Key when the primary key is a string instead of an Integer.
    resourcePKAltID = Column("resource_pk_alt_id", String(80), nullable=True)
    # Points to parent record in ResourceData. To keep the number of indexes down, these are not setup as ForeignKeys.
    parentID = Column("parent_id", BigInteger, nullable=True)
    parentTypeID = Column("parent_type_id", BigInteger, nullable=True)
    resource = Column("resource", JSON, nullable=False)

    __table_args__ = (
        UniqueConstraint("uri"),
    )

Index("ix_res_data_type_modified_hpo_id", ResourceData.resourceTypeID, ResourceData.modified, ResourceData.hpoId)
Index('ix_res_data_type_pk_id', ResourceData.resourceTypeID, ResourceData.resourcePKID)
Index('ix_res_data_type_pkalt_id', ResourceData.resourceTypeID, ResourceData.resourcePKAltID)

event.listen(ResourceData, "before_insert", model_insert_listener)
event.listen(ResourceData, "before_update", model_update_listener)

redpajama_set_name: RedPajamaGithub


Step into the 2012 Chevrolet Corvette!
Quite possibly the perfect car for you! This 2 door, 2 passenger coupe just recently passed the 60,000 mile mark! Chevrolet prioritized practicality, efficiency, and style by including: leather upholstery, high intensity discharge headlights, and cruise control. Chevrolet made sure to keep road-handling and sportiness at the top of it's priority list. Smooth gearshifts are achieved thanks to the powerful 8 cylinder engine, and for added security, dynamic Stability Control supplements the drivetrain.


First convocation of any university is a major milestone in its academic journey. We at K.R. Mangalam University organized our first convocation on 21 February, 2018. The grand event was organized in the lush green campus of University, in the lap of Aravali Hills.
Prof. Kaptan Singh Solanki, Honorable Governor of Haryana presided over the ceremony as the chief guest. Many eminent personalities from different walks of life, besides prominent men from academia were in attendance on the day of convocation. 395 students from the disciplines of Pharmacy, Management, Engineering, Basic and Applied Sciences received their degrees from the hands of Honorable Governor. Taking the cognizance of academic excellence of our toppers and further motivating them to excel in their chosen fields, thirteen gold medals were conferred upon the following meritorious students.
Best all- rounder awards 2017 were given to two outstanding students for their excellent overall performance during their academic tenure at the university, falling under the category of male to Mr. Niladri Bhattacharya B.Tech. (ECE) and Ms. Nikita Khatana B.Com. (Honours) under the category of female.
Chief Guest of the ceremony Prof. Kaptan Singh Solanki while delivering his Convocation Address congratulated the graduands on their brilliant performance and urged the students in making a fine balance between the core values of our culture and education. He inspired the students on becoming active contributors to the nation. Honourable Governor also congratulated the parents and mentors as the day signified culmination of years of their hard work and dedication.
The Chancellor of the University Prof. K.K Agrawal welcomed the Chief Guest of the ceremony. While addressing the graduands the Chancellor of the University mentioned that Graduation doesn't mean bidding 'good bye' to the University. He recognised contributions of the students in making the University as an excellent educational destination and expected the graduands to be in touch with the university. Prof. Aggarwal mentioned that the university was working in consonance with the "Skill India" programme initiated by the central Government and was working in the direction of providing quality Education to equip the students with adequate and appropriate knowledge and technical skills, thus making a small contribution to Nation Building.
Prof. R. K Mittal, Vice Chancellor, K.R. Mangalam University presented the annual report highlighting the achievements of the university with regard to its expansion in terms of addition of new courses, diversifying into different disciplines, creating state of the art infrastructure facilities, providing quality education, and providing excellent ambience for research and innovation. He acknowledged the contribution of the management, faculty, students and parents for making the university an excellent academic destination in NCR. Prof. Mittal also brought to the forefront various initiatives undertaken by the University with regard to female education and female empowerment, which is the need of the hour.
Some of the graduands who are working abroad couldn't attend the convocation ceremony in person. However, their parents had come to receive the degree on their behalf; they lauded the contribution of the University in shaping their wards' academic and professional career.
The convocation ended on a jubilant note and all the graduates marched for their destined success with flying colors.


This stem, from the Menlo Park Farmers Market, managed to spring into full seasonal glory just in time for Thanksgiving.
Image was captured by InMenlo contributor Scott Loftesness using a (new!) Canon S90 in close-up mode.


Like many in the aircraft sales business Steve Varsano is a pilot by inclination. He has eschewed flying for a living in favour of making bigger bucks buying and selling bizjets. However, his love of technology and all things aeronautical permeates his new showroom in Grosvenor Place London. Doorhandles are designed to look like engine cowls, branding is based on isogonal lines on aviation charts and his business address includes the shop's latitude and longitude coordinates.
He prefers today to sit in the back, as he says, "sipping wine and enjoying the journey." (Just as well he's not in the cockpit then). What he's offering clients is a supercharged broker experience and "raising the game" for aircraft sales and acquisition. 20% of his business is from new customers, so he is working with bizjet manufacturers.
People new to jet ownership, or even old hands, can source an aircraft that meets their needs in minutes, rather than months, courtesy of an app he's designed that offers graphical comparisons projected onto a huge screen the size of a Gulfstream G550 cabin. The design is simple and takes the viewer easily through a series of questions, such as 'how far do I want to go?", " How much should I spend?", and "how many people will I have on board?' .
Aircraft floors and cabins are overlaid on top of each other and the viewer can stand in front of the screen to get a true idea of cabin height and width. Once the field is narrowed down, Varsano pulls up a list of available aircraft on his books, for which he has lots of photographs and specs.
Like any brokerage, there is a full time team of analysts sourcing aircraft. Varsano is also offering his showroom to manufacturers should they wish to take their clients there to take a detailed look at their product range.
The back of the shop contains a full-size mockup of an Airbus ACJ, outfitted by Design Q (they of the camper jet fame), which is stunning. Varsano took me through the differences in dB levels on board, with an app that does just that. Each 5 dB really does make a huge difference. I mean I knew that – but I never really knew how much difference each increment makes. 10 minutes of playing – er testing – was a revelation.
More wizadry and fun comes with a special secret entrance behind the shop for clients who really don't wish to be seen, and a dimmable window that clouds the front window, hiding what's going on inside from prying eyes. Expect startled drivers for the next wee while as the hologram beaming out from the reception window engages people driving past. With offerings from each of the major bizjet manufacturers, the planes seem to fly out to the road. In the five days the room has been open Varsano has pulled in two prospects on spec -a Canadian and a someone from the Middle East.
The Jet Business is aimed at upping the customer experience. If clients are unable to meet at the shop, the team will travel to any destination in the world and bring a mobile version on a specially customised IPad. Next stop is China. Varsano is also keen to develop the app further, moving into interiors, with what he calls the "Star Trek" version.
Will it work? Having invested what he says is 'the price of a small jet' into the concept, Varsano believes so. If it does, it will change the face of used aircraft sales forever. Well worth a look.


Having been diagnosed with heart failure, one of the most important relationships you can have is the one with your doctor and care team. Heart failure is a long-term condition so this relationship is important to help you manage the condition and help keep symptoms at bay1.
Your doctor is there to support you; however, it has to be up to you to take control of your health. Only you are the true expert on how you are feeling, the impact that symptoms have on your life and if they are changing in any way. The doctor needs your help in order to help you!
We understand that talking to a doctor, sharing symptoms and concerns, can be in itself incredibly challenging. But this two-way communication is vital in achieving the best levels of management possible. We've put together a 'Talking to your doctor guide' that we hope will help you have these conversations. The guide will help you recognise symptoms and any changes in them, suggest a number of questions that you may wish to ask as well as providing general advice for before, during and after appointments and a glossary of heart failure terms you may come across.
Download the Keep It Pumping Talking to Your Doctors Guide and take back control of your heath.
She couldn't believe her heart, her "best part," had failed her.
Whether you are a patient, a carer, or a supporter, Keep It Pumping has resources for you.
Join Keep It Pumping™ to stay informed about heart failure. We will let you know when we make updates to our site. You can learn more about heart failure, read articles about current events, and watch videos of people telling their stories.
You're in the forefront of the global movement to raise heart failure awareness. We will keep you posted on updates, news, and important events.
To get you started, download our patient education brochure.
©2016 Keep it Pumping, All Rights Reserved.


text:
About Mr Oak
Mr Oak is a consultant obstetrician and gynaecologist providing care for private patients at The London Independent Hospital. He is fully registered with the General Medical Council (UK) and keeps up to date with continuous professional development and annual appraisal requirements.
His special interests are gynaecological endocrinology, pelvic pain, endometriosis, infertility, benign gynaecological surgery, minimal access surgery, vaginal surgery and reversal of sterilisation.
He has undertaken numerous research and audit projects and has published and presented in national and international journals. He reviews scientific papers for British Journal of Obstetrics and Gynaecology, Journal of Obstetrics and Gynaecology and British Medical Journal.
He believes in decision making with patients and as such informed consent is of great interest to him. He has developed information consent papers for frequently performed gynaecological procedures.
He has a busy NHS practice in NHS Lanarkshire based at Wishaw General Hospital.
To contact Mr M Oak please call 02077802400; email jas.bhambra@hotmail.com; mkoak@btinternet.com.
2019 - Oak Clinic © | Website designed & built by Quinn Wilson Associates


Canadian Rockies Public Schools welcomes both the opportunities and the challenges that emerging educational technology brings as we prepare our children to thrive in the exponentially changing 21st Century. CCHS, BCHS and LGMS have 1:1 partnerships with parents, while all our schools provide a variety of means to access rich online resources, as well as tools for creativity, communication and collaboration. This partnership reflects the continuing work of Inspiring Hearts and Minds in engaging today's learners and providing opportunities to learn using 21st Century skills to acquire knowledge for a changing world inside and out of school.
We also continue to invest in student learning by ensuring a robust infrastructive via a Shared Services Partnership with Wild Rose Public Schools and a growing collaboration between several school divisions.
Canadian Rockies Public Schools supports the Learning and Technology Policy Framework: Today's generation has seen the rise of knowledge as a key resource of the world's economy. In the future, Alberta's economy will be even more knowledge-based, diverse and grounded in value-added industries. If we are to shape the future of education and not have it shaped for us, we must become more purposeful in our approach to technology. We need to understand what may be emerging, its implications, and how it can be used for education. Ultimately, the power of technology should be harnessed to support innovation and discovery, not simply to aid teaching. We need to engage learners to use these new technologies as designers and creators of knowledge.


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It All Adds Up With Kumon
To own a franchise that has a good name, you have to have a sizable lump sum to invest, right? Wrong actually, since the arrival of Kumon. This highly effective tutoring method, born in Japan half a century ago, now helps around 45,000 students in the UK improve their maths and English results. Around three and a half million students worldwide follow the Kumon method.
This is a franchise opportunity ideally suited to educational professionals and others who want a more flexible lifestyle but cannot afford high start-up costs. There are 550 franchises in the UK already and the company has capacity for over 400 more.
Instructor Ella Ritchie opened her study centre in Linlithgow in January 2003. "I have a degree in maths and English and I also worked as an accountant for many years," says Ritchie. "I have young children so I wanted to do something that was flexible. I was also keen to have my own business. Kumon combines a lot of attractive things for me."
Ritchie runs her classes in her local borough hall, which she hires by the hour. "I recruit my own staff and organise all my own classes. You have a fair bit of latitude to do things in your own way. Because I work from home I can do a lot of my work while my children are at school."
The hours Kumon instructors work depend on the number of students they have, says Ritchie. " I started with six students which took up a few hours a week. Now I have 85 students and I probably work 20 to 25 hours a week." Likewise, potential earnings depend on how much the individual wants to put into the business. "Some people want to keep costs to a minimum but I like to use incentives like giving medals and prizes to students. I also employ several people as classroom assistants, so my costs are probably higher than other instructors. It's very individual." <
Ritchie believes that location is an important factor in the success of her business. "I am very fortunate in that I live in a town where parents are willing to pay for after-school activities for their children and they take education very seriously. Now that parents have seen the results we achieve, most of my enquiries come through word of mouth."
Her aim is to have 100 students by the end of this year. "When I started out I didn't think I'd cope with 30 students, but once I had 30 I thought it was fine. You add staff accordingly and find different ways to do things."
Kumon offers very good business growth opportunities for the right applicants, says Terry Kelly, Kumon Educational's business development advisor. All applicants need to have good secondary school level maths and English, but Kelly points out that it's not only about results on paper. He says, "In addition to aptitudes for the subjects, the focus is on strong communication skills. What we're looking for is someone who can communicate on all levels."
New instructors build on their initial training every three months for the first year, focusing on the syllabus and classroom management as well as issues such as identifying potential markets for Kumon teaching. Instructors continue to attend local and regional meetings and workshops each year to keep their skills current. In addition, each instructor is allocated a Kumon centre development advisor who monitors the classroom work and business-related activities.
The cost for the franchise licence is £400 and instructors pay royalties of 40% on student fees (this amount is 45% in the first year). Students pay £41 per month per subject. Kumon also offers subsidies on rent for teaching premises in the first year. The company is currently particularly keen to attract franchisees to 35 locations in Scotland.
*Article taken from Business Franchise Magazine June 2004


Positive returns on analytics investment require management action. But many managers are reluctant to take action based on analytics, especially when the numbers don't seem to match with their own gut understanding. They don't know much about analytics and don't really trust the process.
1. Business objectives are the origin of every data mining solution: If you don't know what problem you're trying to solve, you probably won't solve it.
2. Business knowledge is central to every step of the data mining process: If you don't have someone who knows the business on the team, you won't get good results.
3. Data preparation is more than half of every data mining process: Analytics isn't always pretty. Most of the time and effort goes into the dirty work of cleaning data and getting it in shape for analysis.
4. The right model for a given application can only be discovered by experiment: In business applications, it takes a lot of trial and error to find predictive methods that work for you. This is different from classic scientific research processes.
5. There are always patterns: In practice, your data always holds useful information to support decision-making and action.
6. Data mining amplifies perception in the business domain: Do the analysis and you'll know and understand more than you did before.
7. Prediction increases information locally by generalization: Good analytics processes provide useful predictions and a better understanding of what's likely to happen in specific business situations.
8. The value of data mining results is not determined by the accuracy or stability of predictive models: Judge results by the value they yield for the business, not by the mathematical details.
9. All patterns are subject to change: What works today may not work tomorrow. You've got to keep investigating.
Positive returns on analytics investment are a realistic expectation when you begin with the right plan. You've got to understand the process, and that includes the understanding that analytics is a down-to-earth, nitty-gritty process that only produces results when you use the results to drive action.


Here are some of the restaurants you have seen featured in movies.
Le Grand Vefour: An old standard in Paris, it is outside this restaurant where Cary Grant shoots it out with Walter Matthau in "Charade". See the website here: http://www.grand-vefour.com/. Parts of "Midnight in Paris" were also filmed here. Sorry, no clip for this one!


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#cybersecurity | hacker | Ringing in a new National Privacy Law?
Privacy advocates have long called for a federal privacy law and it's coming…in the mean time, experts say complying with the CCPA will lay the groundwork for future compliance with a federal law.
Like revelers packing Times Square on New Year's Eve waiting for the ball to drop, a close teeming crowd of organizations spent the waning moments of 2019 – with both trepidation and excitement – ringing in the California Consumer Privacy Act (CCPA), one of the strongest state laws safeguarding privacy and whose underlying tenets might eventually serve as the basis of federal privacy legislation.
Although technically the CCPA went into effect New Year's Day, in reality regulators won't begin enforcing the law for another six months, which means for many enterprises struggling to comply, July will be a very hot month indeed.
"CCPA will impact any business above a certain size that handles personal data relating to a citizen of the state of California irrespective of where that enterprise may be located," says Steve Durbin, managing director of the Information Security Forum (ISF).
Facing the prospect that the CCPA will likely embolden other states to codify privacy protections as well. "We'll have to wait and see but in much the same way that GDPR has far reaching effects outside the EU," he says. "I would expect many other states to take action after a period of wait and see to determine the impact of CCPA." A handful, including New York and Massachusetts already have crafted their takes.
States weigh in on security
With the focus trained on national legislation to safeguard data and privacy, legislative activity at the state level often gets overlooked, though it has flourished in recent years. Many states either passed, rejected or have pending bills primarily focused on compelling businesses to inform customers about how their data is used. Here is a quick rundown of the major wins and losses from across the United States – at the very least these bills give organizations a peek at what's on lawmakers' minds. Let's take a look….
"We are still nowhere near a consistent approach to privacy and personal information usage in the United States and I do not anticipate this changing with a federal regulation any time soon," says Durbin, though a proliferation of state laws will likely nudge Congress toward acting on the national level.
He points to "a very real need for a federal law to avoid states introducing their own variations and interpretations on privacy which adds a further compliance burden to already overstretched businesses looking to understand and comply with their obligations across the various regions in which they are transacting business."
Indeed, the notion of a national law has gotten a boost from tech giants like Apple, Google and Facebook. "Tech CEOs have been very vocal in their support," says Baffle cofounder and CEO Ameesh Divatia.
Apple CEO Tim Cook, for example, has given a federal privacy law a full-throated endorsement, telling attendees at the 2018 International Conference of Data Protection and Privacy Commissioners, that his company is "in full support of a comprehensive federal privacy law in the United States."
Lawmakers, too, have started to push in earnest for a national law. "Over the last year, I have unveiled a range of bipartisan bills to put consumers back in control, in the hope that these proposals would be incorporated into comprehensive privacy legislation my colleagues have been working on," Sen. Mark Warner, D-Va., noted in a statement after the CCPA took effect January 1. "These bipartisan bills range from legislation that would prohibit manipulative and deceptive design practices often used to trick consumers into unfair and invasive terms of service; legislation that would provide consumers full transparency on the types of data being collected, its uses, and the value of that data to service-providers; and legislation that, building on CCPA and GDPR, would make user data portable to competing providers – while also making dominant providers support interoperability and consumer use of third-party 'privacy managers.'"
Contending the enactment of the comprehensive California law casts a harsh spotlight on the "failure of the federal government to lead on privacy," Warner said, "Congress can no longer sit idly by in this data privacy debate."
Sen. Ron Wyden, D-Ore., a privacy advocate, has no intention of remaing idle as concerns over and the call for privacy legislation mount. Aiming to protect data and punish corporate executives who abuse it, Wyden last fall introduced The Mind Your Own Business Act.
Billed by the senator as going further than the GDPR, the bill would let consumers control how their data is used – in a single click – and puts the authority for enforcing the legislation on the shoulders of the Federal Trade Commission (FTC).
The contents of the proposed legislation reflects feedback from that year of listening, strengthening "Do Not Track," extending lifeline protections for services aimed at low-income users, giving state attorneys general the authority to enforce the bill's regulations, creating right of action protections for advocacy and protection groups, and levying tax penalties on organizations when their CEOs lie about privacy safeguards.
Under the terms of the legislation, the FTC would have the authority to create minimum privacy and cybersecurity standards, impose steep fines – as much as four percent of annual revenue – on companies for a first offense as well as 10-20-year criminal sentences on executives who deliberately lie to the commission and create the Do Not Track system that consumers can use to stop organizations from tracking them, selling or sharing their information or using it to target ads. The agency also would be able to review the personal information companies have used and how it has been shared.
While Wyden says the Mind Your Own Business Act is not meant to supersede the CCPA and other state laws, any federal legislation will likely do just that. "Is there a chance of the CCPA being overwritten by a federal law? Unfortunately, yes," says Robert Cruz, senior director of information governance at Smarsh, explaining that the patchwork of state laws, "each with unique provisions around rights of minors, opt out requirements, biometric data, social media, etc." could "create a very complex quilt of regulations that firms with clients in multiple states would have to comply with, which is why many organizations such as Facebook and Google are advocating for a consistent set of federal rules."
Cruz believes the resulting legislation would be "based upon a set of common denominators across states" that he fears "would very likely be weaker than CCPA."
As Durbin contends, the CCPA is not at stringent as GDPR, but it does include "a few provisions where it has been further developed, such as in the areas of cybersecurity and protection of information from minors," says Cruz. "CCPA is also attempting to define personal information broadly, including making devices associated with specific individuals subject to" its provisions and offers an apparently unique 12-month reach back provision "where firms' obligations in response to requests will reach back up to a period of 12 months," making them "potentially responsible for information they may be using inappropriately at this very minute."
Comply now with the future
in mind
The shortcomings and vagaries of the California law – such as the failure to define "reasonable" privacy protection measures that companies must implement – as well as the absence of a regulatory framework for enforcement in the U.S. similar to the one found in the EU have complicated the compliance picture. Smart organizations, though, are tackling those issues and using CCPA the pre-game for compliance with a federal law.
Legislators crafted the California law around a set of four rights – the right to notice; right to know; the right to opt out; and the right to delete – that organizations can use as guideposts for compliance beyond the state act itself.
Take a data centric approach.
"Am I protecting a server or data on a server," says Myke Lyons, CISO at Collibri. "If server goes boom it might cause a little heartache," but losing or compromising data could be disastrous.
• Categorize it. "You have to figure out if it structured or unstructured data and begin to bag it," says Divatia.
• Set guidelines for data use. "Businesses will also need an effective communication strategy to outline when customer information may be sold or disclosed for business-related purposes," says Heather Paunet, vice president of product management at Untangle. "Transparency in data collection will be a foundational pillar for businesses looking to maintain a trusting relationship with their customers."
Focus on privacy policy, not compliance.
"When we did GDPR we didn't treat it like a project, treated it as our privacy policy – a platform across initiatives," says Lyons, who explains the company turned planks like the right to be forgotten into general procedures.
Expand protections to all customers and partners, not just those in California.
"In terms of accepting the CCPA across the U.S., we believe it is a great move from the industry to take a rigorous standard and apply it uniformly, in contrast to taking a lower standard and then attempt to 'super charge' it for more rigorous jurisdictions," Cruz says. "We have heard some firms subject to GDPR take a similar approach: build practices, policies, and technologies around the more rigorous standard and relax in specific scenarios if and when necessary."
Insist third parties adhere to a predetermined privacy policy.
"Vendor management is often the weakest leak in the chain," says Carlo Di Florio, clobal chief services officer, ACA Compliance Group. "Only work with vendor that complies with your" policies, he says.
Raise user awareness.
"Educating employees about CCPA compliance will be key for businesses during this next phase of data privacy regulations. As the handling of customer data becomes more regulated, businesses will need to learn about and put in place, provisions to adhere to these regulations," says Paunet.
Regulated firms "will have a head start in meeting requirements, in that they are already accustomed to actively managing the retention of data, and thus will start with a better understanding of where personal data lives in their organizations and have had the opportunity to implement governance policies to ensure that sensitive data can be brought under control," says Cruz. Their "biggest change will likely be to create additional pressure to finally delete data that is redundant or outdated and that has outlived its business purpose. That has been a challenge for almost all organizations."
Di Florio explains that financial firms under the guidance of the SEC already have stringent requirements around governance, audits, data loss prevention and the like to follow. "Privacy and information security have become key priorities for SEC in last few years" in an attempt to help companies protect investments and developing operating resilience," he says.
Those not already under strict regulations might have a tougher road. "For non-regulated firms that have not been focused on proactive information governance controls, a larger amount of work lies ahead," Cruz explains.
Federal law: not if, when
Federal law could debut by the end of the year, spurred by on by an election year, says Divatia, explaining that privacy has bipartisan support. "With the election coming up, [privacy could] become a campaign promise."
But the election could have the opposite effect as well. "In a highly partisan legislature and an election year, don't expect to see national-level data privacy legislation passed in the United States," Rick Holland, CISO, vice president of strategy at Digital Shadows. "More state-level privacy legislation, like the CCPA, is the most likely scenario."
And who's in the White House makes a difference, too. "The likelihood of such federal rules under the current administration is low," Cruz says.
From the February 2020 Issue of SC Media


Using a standard air conditioning system isn't the only way to provide comfort for your house during hot weather. If you are interested in finding an alternative residential cooling system for that will help you rely far less on the AC, then you should consider putting in a whole house fan. What these installations do is draw warm air up through your house, which then pulls in cooler air from the outside so you receive natural cross breezes through open windows. Right now, we are offering a spring special: 10% off the installation of a new whole-house fan. We recommend and install the QuietCool model.


text:
"""TensorFlow composable models used as building blocks for estimators."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import math
import re

import six

from tensorflow.contrib import layers
from tensorflow.contrib.layers.python.layers import feature_column_ops
from tensorflow.contrib.learn.python.learn.utils import checkpoints
from tensorflow.python.framework import ops
from tensorflow.python.ops import clip_ops
from tensorflow.python.ops import gradients
from tensorflow.python.ops import logging_ops
from tensorflow.python.ops import nn
from tensorflow.python.ops import partitioned_variables
from tensorflow.python.ops import variable_scope

class _ComposableModel(object):
  """ABC for building blocks that can be used to create estimators.

  Subclasses need to implement the following methods:
    - build_model
    - _get_optimizer
  See below for the required signatures.
  _ComposableModel and its subclasses are not part of the public tf.learn API.
  """

  def __init__(self,
               num_label_columns,
               optimizer,
               gradient_clip_norm,
               num_ps_replicas,
               scope):
    """Common initialization for all _ComposableModel objects.

    Args:
      num_label_columns: The number of label/target columns.
      optimizer: An instance of `tf.Optimizer` used to apply gradients to
        the model. If `None`, will use a FTRL optimizer.
      gradient_clip_norm: A float > 0. If provided, gradients are clipped
        to their global norm with this clipping ratio. See
        tf.clip_by_global_norm for more details.
      num_ps_replicas: The number of parameter server replicas.
      scope: Scope for variables created in this model.
    """
    self._num_label_columns = num_label_columns
    self._optimizer = optimizer
    self._gradient_clip_norm = gradient_clip_norm
    self._num_ps_replicas = num_ps_replicas
    self._scope = scope
    self._feature_columns = None

  def get_scope_name(self):
    """Returns the scope name used by this model for variables."""
    return self._scope

  def build_model(self, features, feature_columns, is_training):
    """Builds the model that can calculate the logits.

    Args:
      features: A mapping from feature columns to tensors.
      feature_columns: An iterable containing all the feature columns used
        by the model. All items in the set should be instances of
        classes derived from `FeatureColumn`.
      is_training: Set to True when training, False otherwise.

    Returns:
      The logits for this model.
    """
    raise NotImplementedError

  def get_train_step(self, loss):
    """Returns the ops to run to perform a training step on this estimator.

    Args:
      loss: The loss to use when calculating gradients.

    Returns:
      The ops to run to perform a training step.
    """
    my_vars = self._get_vars()
    if not (self._get_feature_columns() or my_vars):
      return []

    grads = gradients.gradients(loss, my_vars)
    if self._gradient_clip_norm:
      grads, _ = clip_ops.clip_by_global_norm(grads, self._gradient_clip_norm)
    return [self._get_optimizer().apply_gradients(zip(grads, my_vars))]

  def _get_feature_columns(self):
    if not self._feature_columns:
      return None
    feature_column_ops.check_feature_columns(self._feature_columns)
    return sorted(set(self._feature_columns), key=lambda x: x.key)

  def _get_vars(self):
    if self._get_feature_columns():
      return ops.get_collection(self._scope)
    return []

  def _get_optimizer(self):
    if (self._optimizer is None or isinstance(self._optimizer,
                                              six.string_types)):
      optimizer = self._get_default_optimizer(self._optimizer)
    elif callable(self._optimizer):
      optimizer = self._optimizer()
    else:
      optimizer = self._optimizer
    return optimizer

  def _get_default_optimizer(self, optimizer_name=None):
    raise NotImplementedError

class LinearComposableModel(_ComposableModel):
  """A _ComposableModel that implements linear regression.

  Instances of this class can be used to build estimators through the use
  of composition.
  """

  def __init__(self,
               num_label_columns,
               optimizer=None,
               gradient_clip_norm=None,
               num_ps_replicas=0,
               scope=None):
    """Initializes LinearComposableModel objects.

    Args:
      num_label_columns: The number of label/target columns.
      optimizer: An instance of `tf.Optimizer` used to apply gradients to
        the model. If `None`, will use a FTRL optimizer.
      gradient_clip_norm: A float > 0. If provided, gradients are clipped
        to their global norm with this clipping ratio. See
        tf.clip_by_global_norm for more details.
      num_ps_replicas: The number of parameter server replicas.
      scope: Optional scope for variables created in this model. If scope
        is not supplied, it will default to 'linear'.
    """
    scope = "linear" if not scope else scope
    super(LinearComposableModel, self).__init__(
        num_label_columns=num_label_columns,
        optimizer=optimizer,
        gradient_clip_norm=gradient_clip_norm,
        num_ps_replicas=num_ps_replicas,
        scope=scope)

  def get_weights(self, model_dir):
    """Returns weights per feature of the linear part.

    Args:
      model_dir: Directory where model parameters, graph and etc. are saved.

    Returns:
      The weights created by this model (without the optimizer weights).
    """
    all_variables = [name for name, _ in checkpoints.list_variables(model_dir)]
    values = {}
    optimizer_regex = r".*/" + self._get_optimizer().get_name() + r"(_\d)?$"
    for name in all_variables:
      if (name.startswith(self._scope + "/") and
          name != self._scope + "/bias_weight" and
          not re.match(optimizer_regex, name)):
        values[name] = checkpoints.load_variable(model_dir, name)
    if len(values) == 1:
      return values[list(values.keys())[0]]
    return values

  def get_bias(self, model_dir):
    """Returns bias of the model.

    Args:
      model_dir: Directory where model parameters, graph and etc. are saved.

    Returns:
      The bias weights created by this model.
    """
    return checkpoints.load_variable(model_dir,
                                     name=(self._scope+"/bias_weight"))

  def build_model(self, features, feature_columns, is_training):
    """See base class."""
    self._feature_columns = feature_columns
    partitioner = partitioned_variables.min_max_variable_partitioner(
        max_partitions=self._num_ps_replicas,
        min_slice_size=64 << 20)
    with variable_scope.variable_op_scope(
        features.values(), self._scope, partitioner=partitioner) as scope:
      logits, _, _ = layers.weighted_sum_from_feature_columns(
          columns_to_tensors=features,
          feature_columns=self._get_feature_columns(),
          num_outputs=self._num_label_columns,
          weight_collections=[self._scope],
          scope=scope)
    return logits

  def _get_default_optimizer(self, optimizer_name=None):
    if optimizer_name is None:
      optimizer_name = "Ftrl"
    default_learning_rate = 1. / math.sqrt(len(self._get_feature_columns()))
    default_learning_rate = min(0.2, default_learning_rate)
    return layers.OPTIMIZER_CLS_NAMES[optimizer_name](
        learning_rate=default_learning_rate)

class DNNComposableModel(_ComposableModel):
  """A _ComposableModel that implements a DNN.

  Instances of this class can be used to build estimators through the use
  of composition.
  """

  def __init__(self,
               num_label_columns,
               hidden_units,
               optimizer=None,
               activation_fn=nn.relu,
               dropout=None,
               gradient_clip_norm=None,
               num_ps_replicas=0,
               scope=None):
    """Initializes DNNComposableModel objects.

    Args:
      num_label_columns: The number of label/target columns.
      hidden_units: List of hidden units per layer. All layers are fully
        connected.
      optimizer: An instance of `tf.Optimizer` used to apply gradients to
        the model. If `None`, will use a FTRL optimizer.
      activation_fn: Activation function applied to each layer. If `None`,
        will use `tf.nn.relu`.
      dropout: When not None, the probability we will drop out
        a given coordinate.
      gradient_clip_norm: A float > 0. If provided, gradients are clipped
        to their global norm with this clipping ratio. See
        tf.clip_by_global_norm for more details.
      num_ps_replicas: The number of parameter server replicas.
      scope: Optional scope for variables created in this model. If not scope
        is supplied, one is generated.
    """
    scope = "dnn" if not scope else scope
    super(DNNComposableModel, self).__init__(
        num_label_columns=num_label_columns,
        optimizer=optimizer,
        gradient_clip_norm=gradient_clip_norm,
        num_ps_replicas=num_ps_replicas,
        scope=scope)
    self._hidden_units = hidden_units
    self._activation_fn = activation_fn
    self._dropout = dropout

  def get_weights(self, model_dir):
    """Returns the weights of the model.

    Args:
      model_dir: Directory where model parameters, graph and etc. are saved.

    Returns:
      The weights created by this model.
    """
    return [checkpoints.load_variable(
        model_dir, name=(self._scope+"/hiddenlayer_%d/weights" % i))
            for i, _ in enumerate(self._hidden_units)] + [
                checkpoints.load_variable(
                    model_dir, name=(self._scope+"/logits/weights"))]

  def get_bias(self, model_dir):
    """Returns the bias of the model.

    Args:
      model_dir: Directory where model parameters, graph and etc. are saved.

    Returns:
      The bias weights created by this model.
    """
    return [checkpoints.load_variable(
        model_dir, name=(self._scope+"/hiddenlayer_%d/biases" % i))
            for i, _ in enumerate(self._hidden_units)] + [
                checkpoints.load_variable(
                    model_dir, name=(self._scope+"/logits/biases"))]

  def _add_hidden_layer_summary(self, value, tag):
    # TODO(zakaria): Move this code to tf.learn and add test.
    logging_ops.scalar_summary("%s:fraction_of_zero_values" % tag,
                               nn.zero_fraction(value))
    logging_ops.histogram_summary("%s:activation" % tag, value)

  def build_model(self, features, feature_columns, is_training):
    """See base class."""
    self._feature_columns = feature_columns

    input_layer_partitioner = (
        partitioned_variables.min_max_variable_partitioner(
            max_partitions=self._num_ps_replicas,
            min_slice_size=64 << 20))
    with variable_scope.variable_op_scope(
        features.values(),
        self._scope + "/input_from_feature_columns",
        partitioner=input_layer_partitioner) as scope:
      net = layers.input_from_feature_columns(
          features,
          self._get_feature_columns(),
          weight_collections=[self._scope],
          scope=scope)

    hidden_layer_partitioner = (
        partitioned_variables.min_max_variable_partitioner(
            max_partitions=self._num_ps_replicas))
    for layer_id, num_hidden_units in enumerate(self._hidden_units):
      with variable_scope.variable_op_scope(
          [net], self._scope + "/hiddenlayer_%d" % layer_id,
          partitioner=hidden_layer_partitioner) as scope:
        net = layers.fully_connected(
            net,
            num_hidden_units,
            activation_fn=self._activation_fn,
            variables_collections=[self._scope],
            scope=scope)
        if self._dropout is not None and is_training:
          net = layers.dropout(
              net,
              keep_prob=(1.0 - self._dropout))
      self._add_hidden_layer_summary(net, scope.name)

    with variable_scope.variable_op_scope(
        [net], self._scope + "/logits",
        partitioner=hidden_layer_partitioner) as scope:
      logits = layers.fully_connected(
          net,
          self._num_label_columns,
          activation_fn=None,
          variables_collections=[self._scope],
          scope=scope)
    self._add_hidden_layer_summary(logits, "logits")
    return logits

  def _get_default_optimizer(self, optimizer_name=None):
    if optimizer_name is None:
      optimizer_name = "Adagrad"
    return layers.OPTIMIZER_CLS_NAMES[optimizer_name](learning_rate=0.05)


I love this post I love that you went there! It's high time someone call him on the bs! You and the kids deserve way better than what you have been given. 6 years of not being supported but lied to about so many things is garbage! I won't add all my feelings so that your blog can remain pg haha!


In this paper everyday reasoning is examined fromm the standpoint of natural logic. In natural logic there is the supposition of the concept of schematisation, i.e. the discursive representation of a situation that a speaker A constructs for a listener B and that B must reconstruct for himself. Under these circumstances, in order to prove that a statement s is true A must present it in such a way that B does not call it into question, that he considers it a fact. For this it is necessary to have proofs. Moreover, a fact is never isolated and it may therefore appear inconsistent with other facts. A is thus led to provide reasons in order to substantiate his statements. Some mechanisms of proofs and of reasons are investigated.


As summer is drawing towards its close, you may be thinking about the fun in the sand you and your family have experienced using your Evanston Beach Tokens. These tokens began to be used in 1931,only on some of the beaches. There were free beaches at Calvary, Lincoln and Lake St. Beaches and token beaches at Main St. and South Blvd. By 1939, there were 9 beaches open. Some were still free and some token beaches. There was also a 2 tiered system for the pay beaches. Some required $3.00 tokens and some $2.00 tokens. The number of amenities provided at the various beaches was used to justify the difference in token costs. It should be noted that the $3.00 token allowed a family to swim at any Evanston beach for the entire summer. The $2.00 token provided access to the $2.00 beaches only.
In 1939 and 1968, the city was sued by parties seeking to abolish the beach token charges. The city successfully defended itself in both instances and the beach tokens remained.
Over the years, beach tokens have been made of various materials. They were metal in the 1930's, became plastic during the years of WWII, returned to metal in 1946 and remained so until 1979 when they became a cloth patch for one year only. From the 1980's through the present they have been plastic with pin backs.
The Evanston History Center has a large collection of beach tokens from 1931 through the present, but,there are gaps. We are seeking to fill these in and are asking the public to consider donating missing years. These are: 1932-1934, 1941, 1947-1949, 1950-1957, 1960-1961, 1968, 1981-85, 1989, 1990-1996, 2004-2005, 2007, 2013.
Northwestern University also has had beach tokens. We only have tokens from 1935 and 1960. So, we are also interested in building a complete collection of these.


LOS ANGELES (Reuters) - The bullet that struck and killed a woman at a Trader Joe's grocery store in Los Angeles in the chaotic early moments of a weekend hostage siege was fired by police during a gunfight with the armed suspect, authorities revealed on Tuesday.
But Los Angeles Police Chief Michel Moore commended his officers' conduct in what he described as a "devastating ordeal," while the man they arrested was charged with murder for the death of the woman caught in their crossfire.
The victim, Melyda Corado, 27, identified by relatives as a manager at the store, was one of several people who fled the market after the gunman crashed his car just outside while being chased by police on Saturday, Moore told reporters.
The suspect, identified as Gene Atkins, 28, exchanged fire with officers pursuing him into the crowded store in the city's Silver Lake district, then took more than a dozen people hostage as he barricaded himself inside, police said. He finally surrendered following a three-hour standoff.
Suspected of having already shot and wounded his grandmother and a teenage girl elsewhere in the city, Atkins was himself shot in the arm during the gun battle outside Trader Joe's, police said.
Corado, pronounced dead at the scene, was initially said by police to have been killed by gunshots from Atkins. An investigation later proved otherwise.
"I'm sorry to report that we've now determined through our forensic investigation that one of the officers' rounds struck Ms. Corado as she was exiting the market and was in close proximity to Atkins," Moore said. She ran back inside and collapsed behind the manager's desk.
A judge on Tuesday set bail for Atkins at $18.7 million and scheduled his arraignment for Aug. 14, said Shiara Davila-Morales, a spokeswoman for the Los Angeles County district attorney. Atkins was charged with 31 felony counts, including a murder charge stemming from Corado's death.
According to police, the chain of events began at the home of Atkins' grandmother in South Los Angeles, where he is accused of shooting both the 76-year-old woman and a 17-year-old girl.
Police said Atkins then kidnapped the wounded teenager, identified in media accounts as his girlfriend, as he fled the initial crime scene by car. Police spotted him a short time later in Hollywood, sparking a chase that ended at the Trader Joe's.
Atkins' grandmother and the girl remained in critical condition two days later, Moore said.
Moore said the scenario confronting the two officers who exchanged gunfire with Atkins was "every officer's worst nightmare." But the chief said both officers did "what they needed to do" to defend the public and themselves.


text:
Q: Only show 3 or more Races - a grouping issue with DAX Setting up the problem:
Here is my data:
Primary Key Car Type     Race Day           Gas Type        Track or City Course    Place
  1            Audi      1/1/2017           unleaded        track                   1
  2            Ford      1/1/2017           unleaded        track                   2
  3            BMW       1/1/2017           unleaded        track                   3
  4            Audi      1/2/2017           unleaded        track                   3
  5            Ford      1/2/2017           unleaded        track                   2
  6            BMW       1/2/2017           unleaded        track                   1
  7            Audi      1/3/2017           unleaded        track                   2
  8            Ford      1/3/2017           unleaded        city                    3
  9            BMW       1/3/2017           unleaded        city                    1
  10           Audi      1/4/2017           unleaded        city                    1
  11           Ford      1/4/2017           unleaded        city                    3
  12           BMW       1/4/2017           unleaded        city                    2
  13           Audi      1/5/2017           unleaded        city                    1
  14           Ford      1/5/2017           unleaded        city                    3
  15           BMW       1/5/2017           unleaded        city                    2
  16           Audi      1/6/2017           unleaded        city                    2
  17           Ford      1/6/2017           unleaded        city                    3
  18           BMW       1/6/2017           leaded          city                    1
  19           Audi      1/7/2017           leaded          city                    3
  20           Ford      1/7/2017           leaded          city                    1
  21           BMW       1/7/2017           leaded          city                    2
  22           Audi      1/8/2017           leaded          city                    3
  23           Ford      1/8/2017           leaded          city                    1
  24           BMW       1/8/2017           leaded          city                    2
  25           Audi      1/9/2017           leaded          city                    2
  26           Ford      1/9/2017           leaded          city                    1
  27            BMW      1/9/2017           leaded          city                    3
  28           Audi      1/10/2017          leaded          track                   3
  29           Ford      1/10/2017          leaded          track                   2
  30           BMW       1/10/2017          leaded          track                   1
  31           Audi      1/11/2017          leaded          track                   2
  32           Ford      1/11/2017          leaded          track                   1
  33           BMW       1/11/2017          leaded          track                   3
  34           Audi      1/12/2017          leaded          track                   1
  35           Ford      1/12/2017          leaded          track                   3
  36           BMW       1/12/2017          leaded          track                 2

I'm running into a grouping problem with a DAX formula. I will walk through the dashboard and then state the problem.
The dashboard is a collection of races by three different cars, Ford, Audi, and BMW.
The cars have had 12 races on two types of courses (City or Track) and the cars had two gas options (leaded or unleaded).
This is what the dashboard looks like with no slicers selected:

On the right hand side we see the count of races by car type, the Box and Whisker in the middle is showing race outcome.

So for example, when I selected 'unleaded' for gas we see Ford does not have any 1st place finishes with unleaded gas and normally finishes 3rd when it does have unleaded gas.

And we also see on the right hand side, Audi and Ford have performed in six races with unleaded gas, and BMW five races.

Starting to get into the problem:
I only want a car type to show in the Box and Whisker when that car type has had at least three races.
Here is an example:

In this example, the Box and Whisker graph is working exactly as I expect because BMW has less than three races and they do not show up on the Box and Whisker plot.
The Box and Whisker is running off the following formula:
Show when 3 total races = if(CALCULATE(DISTINCTCOUNT(cars[Races]), ALLEXCEPT(cars, cars[Car Type], cars[Gas Type], cars[Race Day], cars[Track or City Course])) > 2.5, sum(cars[Place]), blank())

HERE IS AN EXAMPLE OF THE ISSUE
Consider the following, there are four races for each car type:

Yet when I select 'Ford' in the slicer, I get the following

Even though there are four races by Ford, the Box and Whisker does not show. I expect it to show, because I know Ford has been in four races, even the table on the right has four listed. The only thing that has changed between the last two pictures is I have Ford selected as a slicer.
I want to show any combination of the four slicers to show in the Box and Whisker plot if the count of races is 3 or above.
Does anyone have any insight on this issue?

A: It is because the BoxWhiskerChart has a different evaluation context than the count of races table that you have set up.
In order to filter which car type to display in the chart, you can set up a measure to count the number of selected races:
Number of Races = CALCULATE(COUNT(Cars[Races]), ALLSELECTED(Cars[Races]))

And add it to the visual level filter:

The results should be as expected:

redpajama_set_name: RedPajamaStackExchange


text:
	#define TRIM_COMMAND_H

//Standard Libraries
#include <iostream>
#include <time.h>

//Third Parties Libraries

//Local Includes
#include "command.h"
#include "macro.h"

//MACRO

class Trim_Command: public Command 	{
	private:
	protected:
	public:
		Trim_Command(double issueTime, long startingBlock, long nextNBlock);
		~Trim_Command();
};

#endif


text:
Marijuana, abortion, greyhounds: The local issues on U.S. midterm ballots
Nov 8, 2018 9:38 AM PHT
From legalizing recreational marijuana to banning greyhound racing, here are local initiatives that Americans voted on during the midterm elections
WASHINGTON DC, USA – In addition to choosing members of Congress and state governors, Americans also cast ballots on a slew of local initiatives in the midterm elections, including the legalization of recreational marijuana, limits on abortions and banning greyhound racing.
Michigan became the 10th state to legalize recreational marijuana, and in the future residents will be able to grow up to 12 plants for their own personal use. A 10% tax was imposed on marijuana sales, with the revenue to be used to fund local councils, education and transport.
Missouri and Utah each legalized medical marijuana, which will carry a tax of 4%, with the funds earmarked to support health care for veterans.
Voters in Alabama and West Virginia approved amendments aimed at limiting future access to abortion.
The Alabama amendment aimed to "support the sanctity of unborn life and the rights of unborn children, most importantly the right to life in all manners."
The text of the proposal stated that "this state does not protect the right to abortion or require the funding of abortion." The state makes no exception for abortions in cases where the pregnancy results from incest, rape or where the mother's life is in danger.
Women's rights advocates fear the measures could lead to a challenge to the landmark Roe vs Wade Supreme Court ruling of 1973, especially at a time when appointments by President Donald Trump have swung the court far to the right.
Louisiana scrapped a law dating back to its segregated past that allowed non-unanimous decisions in juries deliberating in felony trials.
The law, from 1898, allowed a jury to convict a person of felony by only 10 out of 12 jury votes, a move designed to negate the influence of black jury members who were allowed by the 14th Amendment after the Civil War to serve on juries. Its stated aim was to "perpetuate the supremacy of the Anglo-Saxon race in Louisiana."
Oregon is the only other state that does not require a unanimous jury decision in felony cases, except for murder.
Florida pass an initiative to restore voting rights to convicted felons who have served their sentence, except for those convicted of sex crimes or murder.
That will give an estimated 1.5 million people the right to cast ballots in a key swing state in presidential elections.
Colorado also voted to remove the word "slavery" from its statute books as a punishment for crime. The western state's constitution had until the vote on Tuesday, November 6, stated that "there shall never be in this state either slavery or involuntary servitude, except as a punishment for crime."
Missouri approved raising the minimum wage from $7.83 dollars an hour to $12 dollars by 2023. In Arkansas, it will go up from $8.50 to $11 an hour by 2021.
The Ten Commandments –
Alabama voted to allow the display of the biblical Ten Commandments in public buildings and schools.
Nevada backed a measure calling for public electricity providers to increase the amount of power generated from renewable sources from 20% to 50% by 2030.
Under the western state's regulations, however, the proposal has to be approved again in a second election, in 2020, to become law.
Florida banned offshore drilling in waters belonging to the state and also forbade vaping in the workplace.
In Florida, 69% of voters supported a ban on greyhound racing to come into effect by 2020, backing animal rights activists who denounce the sport as cruel.
Florida has 12 of the United States' 18 dog tracks, while 40 US states ban betting on greyhound races.
California passed an initiative requiring all eggs in the state to come from cage-free hens by 2022, while setting minimum cage size requirements for pigs and calves raised for veal.
Alaskans however rejected a ballot measure increasing protections for wild salmon and their habitat, that would have tightened the permitting process for oil developments, mines and dams.
Tech tax for homeless
San Francisco voters backed a tax on the city's wealthiest companies to tackle homelessness, passing a measure that divided the tech community.
A tally posted Wednesday, November 7, showed that 60% of voters in the city that is home to Airbnb, Uber, Salesforce, and Twitter cast ballots in favor of "Proposition C," a local ballot measure brought about by a 28,000 signature petition this summer.
Designed to rake in $250 to $300 million in taxes per year, the Robin Hood-esque measure is intended to fund housing for 5,000 people and finance mental health and housing aid services, according to its backers.
Generally, San Francisco's tech bosses – including Twitter chief Jack Dorsey and Patrick Collison of payment start-up Stripe – resisted the proposal.
But billionaire Marc Benioff, head of cloud computing firm Salesforce, pumped millions of dollars into the "Yes On C" campaign. – Rappler.com


We brewed Loopulus, in collaboration with our friends Creature Comforts, for our 20th anniversary last year. They loved it so much, they wanted to can it and re-release it. If you can't make the Loopulus launch in Athens this day, we have it pouring on tap here! Loopulus is named after our loop system we use to serve our tables and play on words for the scientific name for hops - Humulus lupulus. This 8% Double IPA is made with Citra and Nelson hops and double-dry hopped.


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text:
Q: How to add values from different dataframes together? I didn't think it would be this complicated, but I want to do basic math from a value from a cell in one dataframe with another value from a cell in another dataframe.
These are the dataframes I am using
url = 'https://www.basketball-reference.com/leagues/NBA_2021.html'
page = requests.get(url)
soup = BeautifulSoup(page.content, 'html.parser')
table = soup.find('table', id='per_game-team')
teamdf = pd.read_html(str(table))[0]
teamdf

and
url = 'https://www.basketball-reference.com/leagues/NBA_2021.html'
page = requests.get(url)
soup = BeautifulSoup(page.content, 'html.parser')
table = soup.find('table', id='advanced-team')
advdf = pd.read_html(str(table))[0]
advdf.columns = advdf.columns.map('_'.join)
advdf.rename_axis('Rk').reset_index()
advdf.drop(columns=['Unnamed: 17_level_0_Unnamed: 17_level_1', 'Unnamed: 22_level_0_Unnamed: 22_level_1', 'Unnamed: 27_level_0_Unnamed: 27_level_1', 'Unnamed: 28_level_0_Arena', 'Unnamed: 29_level_0_Attend.', 'Unnamed: 30_level_0_Attend./G'], inplace=True)
advdf.rename(
    columns={
        'Unnamed: 0_level_0_Rk': 'Rk',
        'Unnamed: 1_level_0_Team': 'Team',
        'Unnamed: 2_level_0_Age': 'Age',
        'Unnamed: 3_level_0_W': 'W',
        'Unnamed: 4_level_0_L': 'L',
        'Unnamed: 5_level_0_PW': 'PW',
        'Unnamed: 6_level_0_PL': 'PL',
        'Unnamed: 7_level_0_MOV': 'MOV',
        'Unnamed: 8_level_0_SOS': 'SOS',
        'Unnamed: 9_level_0_SRS': 'SRS',
        'Unnamed: 10_level_0_ORtg': 'ORtg',
        'Unnamed: 11_level_0_DRtg': 'DRtg',
        'Unnamed: 12_level_0_NRtg': 'NRtg',
        'Unnamed: 13_level_0_Pace': 'Pace',
        'Unnamed: 14_level_0_FTr': 'FTr',
        'Unnamed: 15_level_0_3PAr': '3PAr',
        'Unnamed: 16_level_0_TS%': 'TS%',
        'Offense Four Factors_eFG%': 'O_eFG%',
        'Offense Four Factors_TOV%': 'O_TOV%',
        'Offense Four Factors_ORB%': 'O_ORB%',
        'Offense Four Factors_FT/FGA': 'O_FT/FGA',
        'Defense Four Factors_eFG%': 'D_eFG%',
        'Defense Four Factors_TOV%': 'D_TOV%',
        'Defense Four Factors_DRB%': 'D_DRB%',
        'Defense Four Factors_FT/FGA': 'D_FT/FGA'
    }, inplace=True)
advdf

So I filter by team, and select the values from there
team1df = teamdf[teamdf.Team == 'Philadelphia 76ers*']
team1adf = advdf[advdf.Team == 'Philadelphia 76ers*']

If I wanted to multiply any values, for this example the their field goal percentage and offensive rating, I would do
t1_fgp = team1df['FG%']
t1a_ortg = team1adf['ORtg']

t1_fgp*t1a_ortg

But instead of giving me the value I want, output looks like
Output:
4    NaN
13   NaN
dtype: float64

Please help this is frustrating.

A: The problem is that the 4 and 13 are the indices of 76ers in the corresponding tables. When you try to multiply series, pandas tries to match the values by the given index.
Instead of multiplying the series directly you could try:
t1_fgp = team1df['FG%']
t1a_ortg = team1adf['ORtg']

t1a_ortg.iloc[0]*t1_fgp.iloc[0]

Output:
53.8832

Edit:
Or a better way might be merging the dataframes:
# Teamdf: Rename the rk column to teamdfrk
teamdf.rename(columns={'Rk': 'teamdfrk'}, inplace=True)

# Advdf: Rename the rk column to advrk
advdf.rename(columns={'Rk': 'advrk'}, inplace=True)

# Merge the two dataframes based on the Team column
mergeddf = pd.merge(teamdf, advdf, on='Team')

Then use it accordingly:
phil = mergeddf[mergeddf.Team == 'Philadelphia 76ers*']
phil['FG%'] * phil['ORtg']

Output:
13    53.8832
dtype: float64

A: As stated, the index doesn't match. Another option is to reset the index first:
team1df = teamdf[teamdf.Team == 'Philadelphia 76ers*'].reset_index(drop=True)
team1adf = advdf[advdf.Team == 'Philadelphia 76ers*'].reset_index(drop=True)

Personally, I'd merge the two dataframes, then can just apply that calulation on the entire columns.
Also, I cleaned up your code a bit. It's over kill here to use requests and beautifulsoup, as pandas uses those both in the .read_html()
Code:
import pandas as pd

url = 'https://www.basketball-reference.com/leagues/NBA_2021.html'
teamdf = pd.read_html(url, attrs={'id':'per_game-team'})[0]

url = 'https://www.basketball-reference.com/leagues/NBA_2021.html'
advdf = pd.read_html(url, attrs={'id':'advanced-team'}, header=1)[0]

full_df = pd.merge(teamdf, advdf.drop('Rk', axis=1), on=['Team'])
full_df['calculated_column'] = full_df['FG%'] * full_df['ORtg']

Output:
print(full_df)
      Rk                     Team   G  ...   Attend.  Attend./G  calculated_column
0    1.0         Milwaukee Bucks*  72  ...   64780.0     1799.0            57.0764
1    2.0           Brooklyn Nets*  72  ...   30491.0      847.0            58.4402
2    3.0      Washington Wizards*  72  ...   19198.0      533.0            52.8200
3    4.0               Utah Jazz*  72  ...  151300.0     4203.0            55.0368
4    5.0  Portland Trail Blazers*  72  ...    5817.0      162.0            53.3634
5    6.0            Phoenix Suns*  72  ...  104027.0     2890.0            57.4280
6    7.0           Indiana Pacers  72  ...       NaN        NaN            53.2776
7    8.0          Denver Nuggets*  72  ...   54563.0     1516.0            56.7935
8    9.0     New Orleans Pelicans  72  ...   93120.0     2587.0            54.1395
9   10.0    Los Angeles Clippers*  72  ...   13901.0      386.0            56.6832
10  11.0           Atlanta Hawks*  72  ...   59288.0     1647.0            54.1476
11  12.0         Sacramento Kings  72  ...       NaN        NaN            54.6416
12  13.0    Golden State Warriors  72  ...   33457.0      929.0            51.9948
13  14.0      Philadelphia 76ers*  72  ...   68583.0     1905.0            53.8832
14  15.0       Memphis Grizzlies*  72  ...   61449.0     1707.0            52.3040
15  16.0          Boston Celtics*  72  ...   30067.0      835.0            53.1240
16  17.0        Dallas Mavericks*  72  ...   94849.0     2635.0            54.2380
17  18.0   Minnesota Timberwolves  72  ...   15774.0      438.0            49.0560
18  19.0          Toronto Raptors  72  ...   26024.0      723.0            50.1760
19  20.0        San Antonio Spurs  72  ...   61053.0     1696.0            51.2820
20  21.0            Chicago Bulls  72  ...   13655.0      379.0            52.8836
21  22.0      Los Angeles Lakers*  72  ...   23313.0      648.0            51.8728
22  23.0        Charlotte Hornets  72  ...   68255.0     1896.0            50.4595
23  24.0          Houston Rockets  72  ...  117009.0     3250.0            47.5524
24  25.0              Miami Heat*  72  ...       NaN        NaN            52.0416
25  26.0         New York Knicks*  72  ...   42131.0     1170.0            50.4336
26  27.0          Detroit Pistons  72  ...   14250.0      396.0            48.8160
27  28.0    Oklahoma City Thunder  72  ...       NaN        NaN            45.6435
28  29.0            Orlando Magic  72  ...  126463.0     3513.0            45.0879
29  30.0      Cleveland Cavaliers  72  ...   91476.0     2541.0            47.6100
30   NaN           League Average  72  ...   49476.0     1374.0            52.3318


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It's worth noting that the roster will be slightly different in the game's Xbox 360 version, which is being developed by fellow British studio Sumo Digital.
The Xbox 360 version will also offer more than 200 motors, however. To what extent the line-ups will differ isn't currently known.
Can you run forza horizon 2? Want to know forza horizon 2 system requirements?
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text:
VOTE NOW: The Naples Daily News Athlete of the Week sponsored by Babcock Ranch, Feb. 11-16
It's time to vote for the Naples Daily News high school athlete of the week sponsored by Babcock Ranch. Voting will close at 10 a.m. Thursday.
VOTE NOW: The Naples Daily News Athlete of the Week sponsored by Babcock Ranch, Feb. 11-16 It's time to vote for the Naples Daily News high school athlete of the week sponsored by Babcock Ranch. Voting will close at 10 a.m. Thursday. Check out this story on naplesnews.com: https://www.naplesnews.com/story/sports/high-school/2019/02/18/vote-naples-daily-news-athlete-week-sponsored-babcock-ranch/2899859002/
Adam Fisher, Naples Daily News Published 10:00 a.m. ET Feb. 18, 2019 | Updated 12:10 p.m. ET Feb. 18, 2019
The Naples Daily News Athlete of the Week sponsored by Babcock Ranch (Photo: Naples Daily News)
Nominees are derived from scores and stats emailed in by Collier County's coaches during the week. Voting begins each Monday at 10 a.m.
The Naples Daily News Athlete of the Week sponsored by Babcock Ranch for Feb. 11-16
To vote in this week's poll, CLICK HERE!
Voting is restricted to once per device an hour.
SUPPORT SWFL JOURNALISM: Find special offers here
Coaches can email scores to sports@naplesnews.com. The deadline for each night's results is 10:30 p.m.
Each winner will be presented with an Athlete of the Week T-shirt provided by BSN SPORTS as well as a Naples Daily News gift bag. A video featuring the winner will be posted Thursday on naplesnews.com.
Alvarado wins the award for Feb. 4-9 after scoring the winning goal in FBA's first regional victory Adam Fisher, adam.fisher@naplesnews.com; 239-403-6135
Congratulations to First Baptist soccer player Lorena Alvarado, who won the previous poll.
The nominees for Feb. 11-16 are:
Preston Urbancic, First Baptist Academy – Scored 28 points to lead the Lions to a 64-41 win over Canterbury in the Class 3A-District 6 championship game
Halie Egan, Barron Collier – Had 15 points and 9 rebounds, including four key free throws in the fourth quarter, as the Cougars beat Lehigh 55-51 in the Class 7A regional quarterfinals
Adam Feins, Seacrest – Won a singles and a doubles match in each of the Stingrays' wins over Naples and St. John Neumann
Bella Heaslip, First Baptist Academy – Won at No. 2 singles and No. 1 doubles to help the Lions beat Naples
Loren Brown, Community School – Set a personal best while winning the 400-meter hurdles in 1:08.54 at the Ida Baker Indoor/Outdoor Meet
Celebration of Life for Colby Singletary set for Saturday
The Big 15: Naples LB Ar'Quel Smith more physical than ever


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Iron Speed has released Iron Speed Designer Version 7.1, the newest version of its Web 2.0 application development tool. Iron Speed Designer generates database applications for the .NET, cloud, and Microsoft SharePoint environments.
"There is one very critical aspect about the tool that sets it apart from others, Iron Speed Designer delivers "database-driven" SharePoint apps. That's not something you can do with other SharePoint facilities," said Alan Fisher, Iron Speed cofounder.
In Iron Speed Designer V7.1, users can generate Microsoft SharePoint 2010 applications straight from an existing database. Generated applications run inside and are fully integrated with SharePoint. No knowledge of ASPX, .NET, or SharePoint APIs is required.
V7.1 also provides support for Microsoft Visual Studio 2010. Application code generated by Iron Speed Designer is designed to work directly with Microsoft Visual Studio .NET.


text:
Верхнетроицкое (пер. с татар.) — деревня в Бакалинском районе Республики Башкортостан Российской Федерации. Входит в состав Старошарашлинского сельсовета.

География

Географическое положение
Расстояние до:
 районного центра (Бакалы): 10 км,
 центра сельсовета (Старые Шарашли): 2 км,
 ближайшей ж/д. станции (Туймазы): 85 км.

Население

Согласно переписи 2002 года, преобладающие национальности — русские (42 %), кряшены (37 %).

Примечания

Ссылки
 Совет муниципальных образований Республики Башкортостан.

Населённые пункты Бакалинского района

redpajama_set_name: RedPajamaWikipedia


text:
Casper City Council Wants Rocky Mountain Power 7% Franchise Fee to Remain
Tom Morton
Tom Morton Published: September 8, 2020
Courtesy Rocky Mountain Power
The Casper City Council on Tuesday tentatively agreed to ask Rocky Mountain Power to retain a franchise fee that generates significant revenues for the city.
In 2017, the council signed a 20-year utility easement agreement with the Oregon-based PacifiCorp, which does business in Wyoming as Rocky Mountain Power, and in return the city would receive a 7% franchise fee from the company, according to the agenda for the Tuesday work session.
The agreement had a sunset provision that required the city to renew the 7% fee by 2021. Otherwise, the rate drops to 5%, and the city would lose $760,000 a year, which would be "impractical and unworkable from a budgetary perspective," according to a memo in the agenda from the city attorneys to City Manager Carter Napier.
To keep the current rate, the city needs to give Rocky Mountain Power a 60-day notice.
Mayor Steve Freel asked City Attorney John Henley if the rate could be increased to 8%.
Henley responded that such a request would be frowned upon by the company, and that 7% is about as much as could be reasonably expected.
Of that 7%, 1% is allocated to the economic development group Advance Casper, formerly known as the Casper Area Economic Development Alliance, which is jointly funded by the city and Natrona County.
Council member Mike Huber said he would like to have a work session discussion later about what Advance Casper does with its money.
Council member Shawn Johnson wanted the franchise fee to revert to 5%, but didn't explain why.
Most council members voted to keep the rate at 7%.
To be official, it will require an ordinance and passage after three readings including public hearings.
15 Things Every Casper 90s Kid Totally Remembers Doing
15 Things Every 90s Kid in Casper Totally Remembers Doing
Filed Under: casper, City Council, franchise fee, Rocky Mountain Power


Many people didn't like the G.W. Bush administration, and many don't like the Obama administration. That does not mean these people don't like Americans or America as a whole. Waters, not to mention many Jews across the world, don't like the policies of the sitting Israeli government. That doesn't mean these people are anti Semitic or anti Israel.
Ms. Pump's death is tragic. By all accounts the driver was sober, not speeding, the cross walk sign was missing, and the cross walk is poorly lit.
"Waters says he wants it known that his barbs are aimed solely at the current Israeli government. "It's not the Israeli people, not Jews and not Judaism," he says. "I would never dream of attacking them. In fact, a lot of the Israelis are the people who are putting the most into fighting the hardest because they believe it is the most effective tool for changing policies of their own government."
What do you have to say about Mr. Lee??? I'll bet he's not the subject of any of your racist comments.
Waters has called out plenty of countries for human rights violations, he doesn't single out Jews. The sitting Israeli government is not a jew and it's policies do not reflect the views of all jews, and perhaps only those of a minority. His words explaining his position on Israel have been posted here on this forum repeatedly but you choose to ignore his clarifications regarding his position. It is you sir who are single minded and clearly very biased towards anything that questions Israel's actions or motives. No one (and no country) is beyond reproach.
You miss my point. Many of the statements you make and represent as facts are actually your opinions.
The Muslim Brotherhood is a radical group and their agenda represented in 1991's "An Explanatory Memorandum on the General Strategic goal for the group in North America", is certainly not one anyone outside of the brotherhood would endorse.
The Muslim Brotherhood does not represent the average Palestinian any more than Rabbi Dov Lior represents the average Israeli. He makes lovely statements like "All of those who believe in the Torah know that this land (Israel) was promised solely to these people. (by whom, an imaginary being in the sky?) There is no room for another national entity in this place. There has never been a state belonging to another people here. It belongs exclusively to the Jewish people."
Are his statements fact or opinion? Do I agree with him? No. Do you?
There are two sides to every story. Neither side is wholly correct. That was what I meant in my previous post about no gray area. If there is no gray, there is no solution, and the Palestinians and Israelis can just keep spilling blood until there is no one left to fight.
Biba, I do understand. As far as you are concerned there is no gray, no discussion, only your view is valid. There is no possibility for discourse since you believe you are right and all other's opinions are invalid.
I have no beef with your post, but I will take this opportunity to point out something that is a personal pet peeve.
It is the Democratic Party not the Democrat Party. The latter name was bestowed by the RNC several years ago as a petty insult. I recall reading that all Republican members of Congress were encouraged to use the new name as often as possible.
Anyone who posts here and has the temerity to dismiss Mr. Quinn's eloquently stated opinion on the danger of having untrained "good guys with guns" in a mass shooting should just stop talking now. Here is a man with 25 years in the military who has the training and experience to be one of those good guys and he explains very clearly what a difficult chaotic experience a gunfight is even for those with experience and training.