In some ways, the Democrats for Life convention was similar to any other anti-abortion gathering: There were candles to honor aborted children; panelists generally (but not universally) knocked Planned Parenthood and physician-assisted suicide; and the whole conference had Christian, particularly Catholic, undertones. The main difference: Any mention of Donald Trump got, at minimum, an eye roll. Along with other non-Republican anti-abortion movements—such as Secular Pro-Life and Pro-Life Humanists—Democrats for Life likes to use the term “whole life” to describe their cause, a label that encompasses support for life from conception to natural death and everything in between, including child care, parental leave, health care and education. They argue that unlike Republican anti-abortion groups, they want to support children and their mothers once babies are outside the womb, too—even if that means they lead a lonely political existence.
Some of the names on the list were no surprise, as some priests had faced public criminal proceedings and were removed from ministry. Other priests had been the subject of rumors. But many, like Father Crowley, had died before their actions were publicly revealed. As national anger has boiled over, and as the Vatican insisted to victims that Pope Francis was on their side and dioceses rolled out crisis communications playbooks, the families of Holy Angels have grappled with what to do.
“You could read horrible things about Hillary Clinton and wonderful things about Donald Trump, and people were exposed to this at many supermarkets,” said Kathleen Hall Jamieson, director of the Annenberg Public Policy Center and professor of communication at the Annenberg School for Communication. “You might say nobody reads the tabloids, but actually most of us do — through inadvertent exposure.”
Women who have children young tend to live in areas that view family ties as paramount. Parents might be physically healthier because of their youth, and the children’s grandparents are younger and often live nearby. But parents are less likely to have significant savings or a college degree and career. Their pregnancies are more likely to be unintended, and three-quarters of first-time mothers under 25 are unmarried.
It’s a truth Trump knows well based on the life he’s lived. He was reared by a father who made millions of dollars by doing business with the Brooklyn Democratic machine. Practitioners of this cynical, self-serving strain of politics “knew how to buy and sell loyalty, a valued skill in the culture of the clubhouse that required a sense of timing. One had to know how to inspire loyalty in others, and how to give it to the bosses who could nurture your career. But a player in this game also had to know when to jump ship, abandoning career-long friendships suddenly, without emotion, and with a ready and usually petty alibi,” New York investigative reporters Jack Newfield and Wayne Barrett wrote in their 1988 book, City for Sale.
When asked whether she would consider having a second child, Li Keli, an accountant at an electronics maker in the southern city of Huizhou, said, “Absolutely not.” Her factory laid off two-thirds of its workers in June when the United States-China trade war escalated. Her monthly pay of $500 was cut by 10 percent. She used to take her son, 7, to visit nearby cities on weekends. Now she takes him to the playgrounds of big residential complexes because they’re free.
“To put it bluntly, the birth of a baby is not only a matter of the family itself, but also a state affair,” the official newspaper People’s Daily said in an editorial this week, prompting widespread criticism and debate online.
Security isn’t just about who has more Cray supercomputers and cryptography experts but about understanding how attention, information overload, and social bonding work in the digital era. This potent combination explains why, since the Arab Spring, authoritarianism and misinformation have thrived, and a free-flowing contest of ideas has not. Perhaps the simplest statement of the problem, though, is encapsulated in Facebook’s original mission statement (which the social network changed in 2017, after a backlash against its role in spreading misinformation). It was to make the world “more open and connected.” It turns out that this isn’t necessarily an unalloyed good. Open to what, and connected how? The need to ask those questions is perhaps the biggest lesson of all.
Be reasonable about your expenses, but not chintzy. This is not human travel, it is business travel. The value of business travel is that you arrive in a place capable of interacting with humans. ... There are a lot of other tips I have, but those seem like the most salient. Just keep in mind that you are worth shipping across the country carefully because you are a precious and hard-to-replace part of the company, and they want you to arrive undamaged, functional, and able to do good work.
Alphabet Inc.’s Google and Mastercard Inc. brokered a business partnership during about four years of negotiations, according to four people with knowledge of the deal, three of whom worked on it directly. The alliance gave Google an unprecedented asset for measuring retail spending, part of the search giant’s strategy to fortify its primary business against onslaughts from Amazon.com Inc. and others.
This is particularly important if times are good. There’s an old adage that there are stumps and garbage at the bottom of a pond, but no one sees them when the water is rising. When the water—or the cash—starts to dry up, it makes it far more obvious where the problems are. Take time regularly, especially in good times, to look for areas to save and improve efficiencies.
The Castle doctrine has been around a long time. Cicero (106–43 BCE) wrote, “What more sacred, what more strongly guarded by every holy feeling, than a man’s own home?” In Book 4, Chapter 16 of his Commentaries on the Laws of England, William Blackstone (1723–1780 CE) added, “And the law of England has so particular and tender a regard to the immunity of a man’s house, that it stiles it his castle, and will never suffer it to be violated with impunity: agreeing herein with the sentiments of ancient Rome…”
Another false adtech assumption is that “big data” can “know us better than we know ourselves.” This is worse than wrong: it is delusional, and an insult to our sovereign humanity. All of us are not only different from each other, but from how we were ten minutes ago. To be fully human is to learn and change constantly. “I know this orbit of mine cannot be swept by a carpenter’s compass,” Whitman writes. “I do not trouble my spirit to vindicate itself or be understood… I was never measured, and never will be measured… The spotted hawk swoops by and accuses me. He complains of my gab and my loitering. I too am not a bit tamed. I too am untranslatable. I sound my barbaric yawp over the roofs of the world.”
Again, while search ads are called ads, they’re really direct marketing. They are data-driven, want to get personal, and are looking for a direct response. Brand advertising is also data-driven, but the data is always in aggregate form, because the targets are populations, not individuals. Brand advertising doesn’t want to get personal. That would be too expensive, might creep people out, and isn’t the idea anyway, because brand advertising isn’t looking for a direct response. All it wants is to make an impression. Not a sale.
To recap: The trouble began when early in the second set, Ms. Williams was given a warning for coaching. This one is on her coach: Patrick Mouratoglou was using both hands to motion to Ms. Williams to move forward and got called on it. While it is true that illegal coaching is quite common and that most coaches do it, it’s also true that despite what many commentators have said following Saturday’s events, they are called on it quite frequently and that most of the time, players just shrug it off and know that going forward, they and their coaches now need to behave, because the next infraction will cost them a point. The player is responsible for his or her coach’s conduct. And it is actually irrelevant whether the player saw or heard whatever instructions were given; either way, it is still an infraction.
The landfill “island,” a 350-hectare feat of engineering reclaimed from the sea, opened the day after the last of five mainland landfills closed in 1999. Every day it takes shipments of over 2,000 tonnes of ash — the charred remnants of 93 percent of Singapore’s rubbish, burnt at its four incinerators. The National Environment Agency (NEA) predicts a new multimillion dollar incinerator will be needed every five to seven years, and a new landfill like Pulau Semakau every 25 to 30 years. With nowhere to site another landfill, recycling, though not yet rolled out to the masses in condominiums or state Housing Development Board (HDB) skyscrapers, is no longer just nice to have, but a necessity, said Ong.
The whole key to such encoding problems is to understand that there are in principle two distinct concepts of "string": (1) string of characters, and (2) string/array of bytes. This distinction has been mostly ignored for a long time because of the historic ubiquity of encodings with no more than 256 characters (ASCII, Latin-1, Windows-1252, Mac OS Roman,…): these encodings map a set of common characters to numbers between 0 and 255 (i.e. bytes); the relatively limited exchange of files before the advent of the web made this situation of incompatible encodings tolerable, as most programs could ignore the fact that there were multiple encodings as long as they produced text that remained on the same operating system: such programs would simply treat text as bytes (through the encoding used by the operating system). The correct, modern view properly separates these two string concepts, based on the following two points: Characters are mostly unrelated to computers: one can draw them on a chalk board, etc., like for instance بايثون, 中蟒 and 🐍. "Characters" for machines also include "drawing instructions" like for example spaces, carriage return, instructions to set the writing direction (for Arabic, etc.), accents, etc. A very large character list is included in the Unicode standard; it covers most of the known characters. On the other hand, computers do need to represent abstract characters in some way: for this, they use arrays of bytes (numbers between 0 and 255 included), because their memory comes in byte chunks. The necessary process that converts characters to bytes is called encoding. Thus, a computer requires an encoding in order to represent characters. Any text present on your computer is encoded (until it is displayed), whether it be sent to a terminal (which expects characters encoded in a specific way), or saved in a file. In order to be displayed or properly "understood" (by, say, the Python interpreter), streams of bytes are decoded into characters. A few encodings (UTF-8, UTF-16,…) are defined by Unicode for its list of characters (Unicode thus defines both a list of characters and encodings for these characters—there are still places where one sees the expression "Unicode encoding" as a way to refer to the ubiquitous UTF-8, but this is incorrect terminology, as Unicode provides multiple encodings). In summary, computers need to internally represent characters with bytes, and they do so through two operations: Encoding: characters → bytes Decoding: bytes → characters Some encodings cannot encode all characters (e.g., ASCII), while (some) Unicode encodings allow you to encode all Unicode characters. The encoding is also not necessarily unique, because some characters can be represented either directly or as a combination (e.g. of a base character and of accents). Note that the concept of newline adds a layer of complication, since it can be represented by different (control) characters that depend on the operating system (this is the reason for Python's universal newline file reading mode). Now, what I have called "character" above is what Unicode calls a "user-perceived character". A single user-perceived character can sometimes be represented in Unicode by combining character parts (base character, accents,…) found at different indexes in the Unicode list, which are called "code points"—these codes points can be combined together to form a "grapheme cluster". Unicode thus leads to a third concept of string, made of a sequence of Unicode code points, that sits between byte and character strings, and which is closer to the latter. I will call them "Unicode strings" (like in Python 2). While Python can print strings of (user-perceived) characters, Python non-byte strings are essentially sequences of Unicode code points, not of user-perceived characters. The code point values are the ones used in Python's \u and \U Unicode string syntax. They should not be confused with the encoding of a character (and do not have to bear any relationship with it: Unicode code points can be encoded in various ways). This has an important consequence: the length of a Python (Unicode) string is its number of code points, which is not always its number of user-perceived characters: thus s = "\u1100\u1161\u11a8"; print(s, "len", len(s)) (Python 3) gives 각 len 3 despite s having a single user-perceived (Korean) character (because it is represented with 3 code points—even if it does not have to, as print("\uac01") shows). However, in many practical circumstances, the length of a string is its number of user-perceived characters, because many characters are typically stored by Python as a single Unicode code point. In Python 2, Unicode strings are called… "Unicode strings" (unicode type, literal form u"…"), while byte arrays are "strings" (str type, where the array of bytes can for instance be constructed with string literals "…"). In Python 3, Unicode strings are simply called "strings" (str type, literal form "…"), while byte arrays are "bytes" (bytes type, literal form b"…"). With these few key points, you should be able to understand most encoding related questions! Normally, when you print u"…" to a terminal, you should not get garbage: Python knows the encoding of your terminal. In fact, you can check what encoding the terminal expects: % python Python 2.7.6 (default, Nov 15 2013, 15:20:37) [GCC 4.2.1 Compatible Apple LLVM 5.0 (clang-500.2.79)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> import sys >>> print sys.stdout.encoding UTF-8 If your input characters can be encoded with the terminal's encoding, Python will do so and will send the corresponding bytes to your terminal without complaining. The terminal will then do its best to display the characters after decoding the input bytes (at worst the terminal font does not have some of the characters and will print some kind of blank instead). If your input characters cannot be encoded with the terminal's encoding, then it means that the terminal is not configured for displaying these characters. Python will complain (in Python with a UnicodeEncodeError since the character string cannot be encoded in a way that suits your terminal). The only possible solution is to use a terminal that can display the characters (either by configuring the terminal so that it accepts an encoding that can represent your characters, or by using a different terminal program). This is important when you distribute programs that can be used in different environments: messages that you print should be representable in the user's terminal. Sometimes it is thus best to stick to strings that only contain ASCII characters. However, when you redirect or pipe the output of your program, then it is generally not possible to know what the input encoding of the receiving program is, and the above code returns some default encoding: None (Python 2.7) or UTF-8 (Python 3): % python2.7 -c "import sys; print sys.stdout.encoding" | cat None % python3.4 -c "import sys; print(sys.stdout.encoding)" | cat UTF-8 The encoding of stdin, stdout and stderr can however be set through the PYTHONIOENCODING environment variable, if needed: % PYTHONIOENCODING=UTF-8 python2.7 -c "import sys; print sys.stdout.encoding" | cat UTF-8 If the printing to a terminal does not produce what you expect, you can check the UTF-8 encoding that you put manually in is correct; for instance, your first character (\u001A) is not printable, if I'm not mistaken. At http://wiki.python.org/moin/PrintFails, you can find a solution like the following, for Python 2.x: import codecs import locale import sys # Wrap sys.stdout into a StreamWriter to allow writing unicode. sys.stdout = codecs.getwriter(locale.getpreferredencoding())(sys.stdout) uni = u"\u001A\u0BC3\u1451\U0001D10C" print uni For Python 3, you can check one of the questions asked previously on StackOverflow.
In September 2017, a screenshot of a simple conversation went viral on the Russian-speaking segment of the internet. It showed the same phrase addressed to two conversational agents: the English-speaking Google Assistant, and the Russian-speaking Alisa, developed by the popular Russian search engine Yandex. The phrase was straightforward: ‘I feel sad.’ The responses to it, however, couldn’t be more different. ‘I wish I had arms so I could give you a hug,’ said Google. ‘No one said life was about having fun,’ replied Alisa.
Soon enough, we might not even need to confide our secrets to our phones. Several universities and companies are exploring how mental illness and mood swings could be diagnosed just by analysing the tone or speed of your voice. Sonde Health, a company launched in 2016 in Boston, uses vocal tests to monitor new mothers for postnatal depression, and older people for dementia, Parkinson’s and other age-related diseases. The company is working with hospitals and insurance companies to set up pilot studies of its AI platform, which detects acoustic changes in the voice to screen for mental-health conditions. By 2022, it’s possible that ‘your personal device will know more about your emotional state than your own family,’ said Annette Zimmermann, research vice-president at the consulting company Gartner, in a company blog post.
I wish I could say the same for the rest of the concerto. Habits are hard to break, and Mr. Lang’s crept into the performance as the piece progressed. The second movement opens with a naïvely pure theme ripe for interpretation; instead, Mr. Lang infused it with drama, sinking heavily into the keys while playing a melody with the simplicity of “Twinkle Twinkle Little Star.”
Cutouts is an open source application. Code licensed under the MIT license. Copyright 2018 Siddharth Kannan