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domain: medical


Human behaviour needs radical change to protect our individual and collective well-being. To achieve this, we need to develop more effective behaviour change interventions, tailored to the behaviour, population and setting. The Human Behaviour-Change Project will build an Artificial Intelligence system to continually scan the world literature on behaviour change, extract key information, and use this to build and update a model of human behaviour to answer the big question:
‘What behaviour change interventions work, how well, for whom, in what setting, for what behaviours and why?’
Many of the global threats we face, for example, to health and environmental sustainability, can only be solved by people, organisations and governments changing their behaviour. To achieve this we need to rapidly improve our understanding of behaviour and how to change it.
The scientific literature on behaviour change is vast and accumulating at an accelerating rate. However, this literature is fragmented, and is inconsistently and incompletely reported. The result is that most of it is wasted. Current attempts to synthesise this evidence can take years, miss much that is relevant and fail to detect patterns which can generate knowledge allowing generalisation beyond the contexts within which the evidence was generated.
Advances in computing such as the IBM Watson platform demonstrate how it is possible to apply Natural Language Processing and Machine Learning technologies to reveal insights from large volumes of unstructured text. For example, Watson for Oncology recommends interventions for individual cancer patients based on clinical evidence extracted and organised from research publications, medical reports and clinical trials.
It is now possible to create Artificial Intelligence systems to identify relevant information in the world literature, extract it into an organised knowledge base (‘ontology’) created by behavioural scientists, and generate new insights about behaviour change.
This knowledge base can then be interrogated on demand to answer questions about behaviour change, big and small. It will provide answers drawing on knowledge integrated from a broader literature than humans can review, and will also be able to point to relevant references as well as estimate the confidence with which statements can be made.
The Human Behaviour-Change Project,
funded by the Wellcome Trust and led by Professor Susan Michie, is a
collaboration between behavioural scientists (Michie, Johnston, Kelly, West),
computer scientists (Shawe-Taylor and Mac Aonghusa) and system architects (Thomas) based at University College London and Universities of Cambridge and
Aberdeen, UK, and the IBM Research Laboratory in Ireland. A multi-disciplinary
team of 12 will work over four years to revolutionise current practices of
evidence synthesis and our ability to generate new knowledge. The work will
depend on a close interplay between the scientific disciplines involved.
The behavioural scientists will develop an “ontology” of behaviour
change interventions that will organise the fragmented knowledge in the
scientific literature into a form that enables the efficient accumulation of
knowledge, as shown below:
- Top level of the Behaviour Change Intervention Ontology
The computer scientists will build an Artificial Intelligence system, trained by behavioural scientists, to apply Natural Language Processing to extract relevant information from scientific reports and to organise that information into the Ontology using reasoning and machine learning. The Artificial Intelligence system will furthermore infer new knowledge while continually learning from new information fed into it.
The system architects will build and evaluate a sophisticated online user interface to interact with the Artificial Intelligence system to enable users to readily access the breadth and depth of up-to-date evidence, and get answers to their questions, with explanations of these answers that people can understand and trust.


Nobel Peace Laureate Liu Xiaobo’s Final Wish: 'Free My Wife'
I first visited Liu Xiaobo’s home in West Beijing in May 2008. Under the dim lights in his small living room, he answered my question about why he did not go abroad.
“The children were killed, but the bearded man lived on. It defies imagination.”
At first, I could not understand what he meant.
Mr. Liu, who was born and raised in Jilin Province, spoke with a northeasterner’s accent and used many unique expressions in our conversation. For example, the phrase “bearded man” refers to an adult male. Only 33 years old at the time of the 1989 Tiananmen Square Incident, Liu was referring to himself when he used this phrase.
Until just before the Tiananmen Square incident, Liu had been a popular professor at Beijing Normal University. In his lectures, he passionately proclaimed, “China must be democratized.” Even large lecture halls were always filled to capacity, with students coming even from other universities to listen to the professor whom they had heard their friends talk about. Due to Liu’s influence, many of his students participated in the democratization movement, and many became victims of oppression.
The deep regret etched on Liu’s heart after the Tiananmen incident became the impetus for him to stay in China for his whole life and fight against the system of one-party dictatorship. When he was released from prison after several years, Liu visited mothers who lost their children in the Tiananmen incident and apologized to them, one by one.
Liu has said, “I misjudged the situation when I believed that our movement might be able to bring about democratization. I was intoxicated with the attention I was receiving.”
At the time of the Tiananmen Square Incident, there were many university students and prominent experts who were being called “democratization leaders.” However, there was no one, like Liu, constantly in a state of deep reflection and speaking of the responsibility that he himself bears.
Liu energetically continued his writing work in Beijing following his third release from prison in 1999 until his fourth detention at the end of 2008, even contributing to the Sankei Shimbun. That was during the administration of President Hu Jintao, who eased, relatively, the restrictions on the democratization movement. Even so, a police box was installed in front of Liu’s home. Liu was under strict supervision—when he went anywhere, he had no choice but to come and go in a police vehicle.
Whenever anyone visited Liu’s house, Liu Xia, his wife, would always bring tea, but she almost never joined in conversations. She would often sit down next to her husband and quietly listen to his stories. Mrs. Liu is a poet and photographer. Her father was a university president and a cadre in the Communist Party, and Liu Xia grew up in a wealthy household. She met and fell in love with Liu Xiaobo during the Tiananmen Square incident.
Liu Xia is a strong woman. She decided to marry Liu Xiaobo while he was imprisoned, because the prison did not allow prisoners to have visits from their girlfriends. During his life, Liu Xiaobo once said, “I am ready to die anytime. My only regret would be not being able to see my wife again.”
Liu Xiaobo did not leave China no matter how much the authorities tried to oppress him. Just before he died, he strongly hoped to receive treatment overseas, such as in the United States or Germany. Supporters said that Liu Xiaobo believed that if he went overseas with his wife for treatment, then his wife would be able to remain abroad even if he were to die while outside of China.
However, Liu’s final wish that his wife be set free was rejected by the Chinese authorities. She is still under house arrest. Demonstrations demanding her immediate release were held in Hong Kong and New York, while statements from Europe, the US, and other countries were announced, all asking that Liu Xia be set free. The Communist Chinese authorities do not seem inclined to listen to these voices from the international community.
One week before he died after suffering from terminal cancer, Liu Xiaobo used the last of his strength to write a more-than-500-word foreword for his wife’s photograph collection. The collection will be published in the United States and other countries in the near future. These sentiments contain Liu Xiaobo’s final message to the world. Will the world be listening?
Akio Yaita is a senior staff writer of the Sankei Shimbun International News Department. He is a former correspondent of the Sankei Shimbun Beijing Bureau.
(Click here for the original article in Japanese.)
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text:
Residents of Mbieri road area in Owerri, Imo state capital, are currently in trouble as the major road leading into their vicinity from works layout is about to be cut off by erosion.
This is coming one week after people living at Trinity Street, Akwakuma in Owerri raised alarm over government’s lack of interest in tackling the gully erosion menace already destroying houses in the area.
The Mbieri road erosion crisis began two years ago after former governor Rochas Okorocha’s contractors did a shoddy job that destroyed the drainage on the road without proper replacement. This led to devastation of the road by heavy flooding that ravages the area during rainy season.
The situation has been like that since Okorocha’s government left office even after government officials visited the area during Emeka Ihedioha’s short stay in office.
Governor Hope Uzodinma has yet to make any move to save the situation as heavy flooding continues to gradually erode the road.
Residents of both areas, Mbieri Road by Works Lay out, and Trinity Street, Akwakuma are calling for governor Uzodinma’s assistance in addressing the situation before it gets worse.

domain: geography


text:
This week, I embarked on a most exciting adventure with Jameson, introducing me to both Dublin and Ireland for the first time as well as a fascinating discovery of whiskey that took us all over (and under) the city.
Although their main distillery is near Cork, it’s obvious that Dublin is the spiritual home of Jameson (pardon the pun) and always has been since it was founded in 1780. Whiskey is to Ireland what wine is to France, so what better way to become acquainted with a city, than with a brand who’s connection to its streets and people is not only engrained in its heritage, but its inspiration for the future.
This is the Jameson guide to Dublin; exploring the past, present and future of the city’s culture, history and culinary talent.
Under The Streets Of Dublin
We started our journey under the streets of Dublin and taken to the Fitzwilliam Lane cellars. Here, we met Ger Buckley the master cooper of Jameson, who’s family have looked after the cooperage, (maintaining the whiskey barrels) for five generations. The cooper broad axe and hammer Ger uses to maintain the barrels for Jameson have been passed down from his father and his father before him and are ancient tools that date back 9000 years. For such a global company, I find this really rather romantic and a testament to Jameson’s artisanal values.
The Culture Of Dublin – Past, Present and Future
Next stop was the Dublin Writer’s Musuem on the north side of Parnell Square, which showcases the original work of some of Ireland’s biggest literary talents. Here you’ll find the collections of Oscar Wilde, Samuel Beckett, James Joyce, Bram Stoker and Jonathan Swift.
This beautiful Georgian building is the former home of George Jameson, who commissioned the intricate stained glass windows that bear his monogram and coat of arms.
We then went on a walking tour of Temple Bar with street and graffiti artist, James Earley who has designed this year’s limited edition Jameson bottle. Temple Bar, is actually an area and not just a pub as I thought the name suggested!
At night, it is alive with revellers that slosh their way from pub to pub, but during the day it is a cobbled, cultural gem punctuated with rickety Irish pubs and incredible graffiti street art. James Earley is the man behind many of the outstanding and colourful pieces that adorn the walls of Temple Bar’s buildings and he was the most fascinating tour guide, telling us each painting’s deeper meaning, all of which are poignantly inspired by the people of Ireland. This particular piece of a cow trampling a cowboy, represents the uprising of people against the ‘cowboy’ bankers during the global recession.
One of his most impressive pieces is the mural on the walls of the Bloom Hotel. Earley’s inspiration for this, is the book Ulysses by James Joyce and was painted entirely by free hand. You must go and see it for yourself.
This is the limited edition bottle by James Earley and includes these Dublin landmarks in his design:
Walking through Dublin also opened my eyes and ears to the thriving live music scene here. There’s something very sexy about the Irish voice; it’s gravelly, raw and bursting with passion. It’s also bursting out of almost every pub in Temple bar and many of the other establishments we encountered on our exploration of the city. Suitably therefore, we were taken to a secret gig at the Jameson Bow Street Sessions, where Dublin-native band Kodaline played a headline set.
The next day marked one of the biggest in the Irish calendar; St Patrick’s Day and what better time to visit Dublin than on this national holiday, where the patriotism of the Irish is stronger than ever and everyone dresses in green. Sadly, I didn’t see any leprechauns, but some of the costumes from onlookers of the St Patrick’s Day parade were ‘grand to be sure’!
We spent our St Patrick’s Day at the Old Jameson Distillery, which hosted a huge party with live bands, Irish craft stalls and the opportunity to tour the distillery itself. Did you know that the word “uisce” is Gaelic for water, which is the root for the English word “whiskey”? If ever there was proof of how important whiskey is to the Irish, then I think this is it!
Where To Eat In Dublin
If you’re looking for creative and delicious food, then Dublin offers some of the very best.
Our first dinner was at The Fumbally, where hotly-tipped Katie Sanderson created the most incredible 7 course tasting menu for us to enjoy. This is a chef who creates her own salt, so as you can imagine her intricate style yields some very exciting culinary experimentation. Proudly using only local produce, the menu was inspired by Irish food from past to present.
We also ate lunch at The Drury Buildings on Drury Lane (no muffin man in sight unfortunately). This is in the hipster area of town near Temple Bar and the food did not disappoint. I opted for the stone bass with potato gratin as a main, which was delicately cooked and divine to taste.
Not to be missed is dinner at L Mulligans Grocer, a traditional pub and grocer that has now become one of the best gastro-pubs in Dublin. Here we paired Irish cheese and Jameson whiskey, a most delectable combination before tucking into our hearty meals. Although traditional, the dishes here are lifted with hints of unexpected flavour, such as the ginger and lime butter that accompanied my smoked salmon starter. Of course, Irish produce is the name of the game here and the whiskey, beer and food menu change with the seasons.
The Burgers we had for lunch at Jo Burger, on site at the Old Jameson Distillery are out of this world. Literally, they are about the size of a planet and absolutely delicious. Make sure you order fries and choose three of the five types of Mayo they offer; we had curry mayo, pesto mayo and garlic mayo -INSANE!
Our final meal was at Angler’s Rest, a seafood restaurant that has been entertaining Dubliners since 1865 with fine food and great live music. I was still so full from my burger that I could only manage some of my soup and wild mushroom tart, but the food and ambience here is really quite magical. Its rustic oak and stone decor is the perfect setting for traditional Irish music played by the open hearth and as we watched the band and sipped the golden swirls of our Jameson whiskey aperitif, I couldn’t have felt more content.
Thank you Jameson for an absolutely fantastic week!
Are you heading to Dublin? If you have any comments or questions, please leave them below!

domain: artistic


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The UK’s cabin baggage ban on laptops and tablets must be implemented by Saturday, the Department for Transport said.
The move was ordered by Prime Minister Theresa May on Tuesday in the latest of a series of meetings on aviation security, although it was not immediately clear whether it was in response to a general terror threat or a specific attack from the likes of Islamic State or al Qaida.
Which countries are affected?
The restriction prohibits airline passengers from carrying laptops in cabin luggage on inbound direct flights from Turkey, Lebanon, Jordan, Egypt, Tunisia and Saudi Arabia.
Passengers travelling on these flights are advised to check online with their carrier if they require further information.
Which devices will be affected?
Large phones, all laptops and all tablets and e-readers will be affected under the ban.
Devices including Kindles and other e-readers will be banned from the cabin, along with hybrid devices such as the Microsoft Surface and iPad Pro, as well as the new Nintendo Switch gaming system, the Press Association reports.
What are the dimensions allowed?
The move, which mirrors rules implemented in the US on Tuesday, will see devices that are larger than a typical smartphone measuring 16cm by 9.3cm by 1.5cm banned from carry-on luggage and will have to be placed in the plane’s hold.Any phones, laptops or tablets larger than the above dimensions will not be allowed in the cabin, regardless of whether they were purchased in duty free.
Which mobile phones will be allowed on the cabin?
The Department for Transport said most smart phones will be allowed in the cabin, except those with dimensions exceeding the allowance.Some of common handsets allowed in the cabin include:
iPhone 7 Plus
Samsung Galaxy 7 Edge
Samsung Galaxy Note 3
Sony Xperia Z2
Which airlines will be affected?
UK airlines operating direct flights which will be hit by the new measures are British Airways, easyJet, Jet2.com, Monarch, Thomas Cook and Thomson, while overseas airlines affected are Turkish Airlines, Pegasus Airways, Atlas-Global Airlines, Middle East Airlines, EgyptAir, Royal Jordanian, Tunis Air and Saudia.Affected airlines were informed immediately, but may take a few days to implement the new security measure, said Number 10.
It follows a similar measure announced on Tuesday by the US authorities affecting flights originating in a longer list of eight mainly Muslim countries.

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text:
In the third week of pregnancy, Morula turns into a blastocyst - an cavity is formed inside the cell ball in which the embryo develops. At the third week of pregnancy, the attachment of blastocysts towards the wall of the uterus occurs. If before that, the egg cell, which connected with the spermatozoa, was fluent in phallopy tubes, now she fell into the uterus, and she needs to be gaining. Sometimes the embryo can swim in the uterus a few more days.
At 3 week of pregnancy, the fruit has not yet been formed, but only an embryo, which is not at all like a person at all. It is a ball of about 250 cells with a diameter of about 0.2 mm. The embryo is in the yolk bag. Before attaching to the end of the uterus, the embryo is powered by the so-called yellow, or luteane body - the temporal endocrine gland, which is formed every time ovulation occurs.
Yellow body exists up to 12-16 weeks of pregnancy. It produces a hormone progesterone, overwhelming menstruation. The yellow body supports the life of the embryo while it is still "in free swimming". After attachment, it will fully depend on the mother's body.
While the embryo was not implanted, he still autonomy from the body of the mother. Therefore, what is happening in the body of the woman does not have so much effect on the embryo. It's time to adjust your food and get rid of bad habits if they are.
A part of the embryo cells, the one that was obtained from the father, alien to the mother's body, so the embryo produces a protein, overwhelming immunity. It is necessary that the uterus does not reflect it. As a consequence, 3 weeks of pregnancy is characterized by a decrease in immunity, so there is a state similar to a cold: a runny nose, sore throat, sneezing, nasal congestion. These symptoms of changes in health in the third week are considered one of the likely signs of pregnancy.
In the beginning of 3 weeks of pregnancy, the blisterocyst grows with a villus, which she is attached to the uterine shell. After rustling in the endometrium, the villi is in contact with the blood of the mother, through them the power is carried out. Vorki will develop throughout the 3 week. After fixing the embryo, another most important process begins for which the yellow body is also answered - the formation of the placenta. At this time, half a child is already laid at the cellular level, although it does not appear externally.
3 week of pregnancy can give itself felt as a change in the well-being in a woman. This in most cases is happening before the menstruation delay. Some women say that they already feel that pregnant, although there are no objective signs yet.
The home test for pregnancy can already show two stripes at this time. The test determines the presence and level of hormone hgch - human chorionic gonadotropin. This hormone is produced by an external leaflet of the embryo. Its level in the urine at 3 week is still small, but the sensitivity of pharmacy tests may be enough to determine the occurrence of pregnancy. At the 4th week of pregnancy, the level of this hCG in the blood is much higher, so blood test on hCG will confirm the fact of pregnancy more accurately. 3 week of pregnancy can have the first signs of pregnancy, which can not be called accurate:
All this suggests that a serious restructuring began in the body of a woman, during which he is prepared for having a child. However, such symptoms in a woman can be a sign of approaching menstruation, and self-sustaining, if she really wants or on the contrary, it is afraid to get pregnant.
One of the most important periods after conception is the third obstetric week of pregnancy. It is at this time that the fully matched egg is found in a masterpiece with one of the millions of spermatozoa, further fertilization and promotion of the zygota in the uterus. On the third week it becomes clear whether the fertilized egg was entrenched in the body of the uterus or the body gave failure. After fixing in the body, a woman begins to produce a certain hormone called HCG, under the influence of this hormone becomes a positive pregnancy test. That is, by the end of the third week of pregnancy or at the beginning of the fourth, you can already see the test of the test to see two cherished stripes. This is where the time comes to question: but we hope that pregnancy is welcome and you know what to do next.
Sperm, moving towards the royaltic pipes, meets in its path a lot of obstacles and therefore the ultimate goal is suitable for the strongest and hardy. One of them is embedded under the shell of the waiting for its egg cell and comes in fertilization, as a result of which the future child receives 23 chromosomes from each of their parents. What is developing at the 3rd week of pregnancy? It is at this moment that the floor of your baby is determined, the color of the iris and hair and hair color, genetic features are transmitted. By the way, you can try to pre-determine.
After entering the uterus, the most important process of the implantation of the zygota to the walls of the body begins, if everything goes successfully, we can say that the pregnancy has successfully come. Its preservation in the future will largely depend on the work of the body of a woman.
After implantation, the zygota uterine gets another name - blastocyst. This blastocyst is in continuous development. In the third week, the cavity is formed inside it, in which the embryonic disk is laid, at one end of its end, the head of the embryo will be formed, and on another tail.
Cells blastocysts are continuously divided and form blood vessels inside the walls of the uterus, of which the placenta will be formed in the future. Throughout the period of pregnancy, the development of the baby will depend on the placenta. Through the placenta to it will flow nutrient components and oxygen, slags will be displayed through it. The final formation of the placenta occurs approximately to.
Before implantation of the zygotes in the body of the uterus for its food and life, the yellow body of the ovary is responsible and therefore the harmful substances incoming, in the form of alcohol, harmful elements of tobacco and other adverse components do not have a negative influence on the germ, but as soon as The zygote will consolidate, the body of the woman begins to be responsible for it. That is, the future child gets useful and harmful substances falling from the outside or formed inside the body of the mother.
By the end of the third week of pregnancy, the mother begins to receive signals that there is another life in it. And it causes a lot of responses, some of which ensures the safety of the child, and the other part of the opposite perceives it as an alien organism. It is with this confusion that the sensations arise from a woman by the end of the third week of pregnancy are connected and later.
The zigode is then cleaved by 100 cells. This process lasts a couple of days after conception. Some cells in the future forming the embryo, other placenta, but for now it is only cells that make up one fifth of the size of the future fetus.
If you are pregnant at 3 week, you are 1 month pregnancy. It remains only 8 months! Have questions? Here are some more information about how weeks, months and trimesters are disintegrated during pregnancy.
Throughout the pregnancy, the woman should eat right. How to make a diet so that pregnancy and childbirth have passed without complications?
At 38, the fruit weighs about 3 kg, and the growth reached 50 cm. The fruit can already be tightly grabged with his hands, in which you can soon make sure, holding it for the handle for the first time. To the thirty-eighth week of pregnancy, organs and systems are ready to live outside. To the outcome of the Z8 week of jumps in development no longer be noted, the improvement of all functions occurs smoothly and continues, and after the advent of the baby.
Our clinic employs highly qualified gynecologists, which will help in the shortest possible time to diagnose a frasonal pregnancy. Experts will help to conduct high-quality cleaning with the minimum risk of developing complications.
From January 1, 2021, the amount of benefits on children and maternal payments depending on the minimum wage was changed. From February 1, 2021 children's payments set in fixed amounts are indexed. What state support can parents and those who are preparing to become? Consider all payments and benefits for children in 2021 in order, including new and changes.
When and why the insomnia arises, how to overcome insomnia and how to sleep, to get enough sleep, tell me in this article.
You can learn about the reasons for the appearance of insomnia during pregnancy on the website of the international hemostasis clinic. Most often, this phenomenon occurs in late terms.
Can pregnancy be protected without symptoms, how to regard delay without other signs of conception. What is the cause of an unexpected position. As women explain the implicit signs of asymptomatic pregnancy.
Mioma uterus: treatment without surgery with drugs when transactions can not be avoided which drugs need to take in the uterus.
There are many folk methods, how to determine pregnancy before delay without dough at home. For thousands of years, people came up with many ways, but only some of them received scientific confirmation and are reliable. But even their use is less efficient than going to the gynecologist. Therefore, at the first suspicions about the beginning of pregnancy, it is best to visit the doctor, and not to look for
September 14, 2020 Group of Companies Mother and Child replied: The main sign of the occurrence of pregnancy is the latency of menstruation. However, it may also be a consequence of a hormonal violation. Therefore, in the case of a long delay, we recommend contacting the doctor a gynecologist-endocrinologist.
Early toxicosis is usually observed in the first trimester. The prevalence of early toxicosis is so large that it is very often its symptoms consider classical signs of pregnancy.
All causes of back pain in the loan area can be divided into 2 groups: diseases of the spine and the pathology of the internal organs, in particular this ...
Are there any pain in the chest during pregnancy. Ways to relieve and relieve pain. Factors that may be caused by the appearance of pain in lactic glands
True legs during pregnancy at night: natural causes, pathological conditions. Restless leg syndrome: what it is, than dangerous for pregnant women.
The tertomat of the ovary is one of the types of germinogenic tumors, which has synonyms of embryo, a triederma, parasitic fruit, complex cell tumor, mixed teratogenic formation, monodermomom.
Pains in the vagina during pregnancy - the symptoms of human diseases on the EUROLAB portal - pain and characteristic external signs of diseases, determining the cause of pain and illness, first aid, diagnosis of illness and treatment. All about health and medicinal products.
Pain in the right side during pregnancy - the symptoms of human diseases on the portal EUROLAB - pain and characteristic external signs of diseases, determining the cause of pain and illness, first aid, diagnosis of disease and treatment. All about health and medicinal products.


Formerly Engineer-in-Chief, United States Coast Guard, Washington, D.C.
Admiral Johnson was born in Wheatley, Ark., on August 27, 1882. He was graduated from Cornell University with the degree of Mechanical Engineer in 1906, and a year later was appointed an engineering cadet in the U.S. Coast Guard, receiving a commission as ensign in February 1908.
During World War I Admiral Johnson was on duty in European waters, serving as engineer officer of the Aphrodite. In 1919 he was assigned to Coast Guard Headquarters in the office of the Engineer-in-Chief for three years, and then was ordered to the cutter Pequot as engineer officer. In 1924 he was at the Philadelphia Navy Yard in connection with the reconditioning of the destroyer Jouett and served as engineer officer of the Jouett until 1926. He was again assigned to the Philadelphia Navy Yard for duty in connection with the reconditioning of destroyers for transfer to the Coast Guard and subsequently was assigned to the destroyer Tucker as engineer officer.
From 1928 to 1931 Admiral Johnson served a tour of duty at Coast Guard Headquarters. In January 1932, he became Inspector of Machinery at Trenton, N.J., following which he was assigned as Chief Inspector at the Defoe Shipbuilding Company, Bay City, Mich., in connection with the construction of the cutter Escanaba.
Admiral Johnson was appointed Engineer-in-chief of the Coast Guard in December 1935 and served continuously in this capacity until his retirement on August 1, 1946.
Click here to see the original biographical sketch.


text:
I worked on this game from the very beginning, through all of its twists, turns, and re-boots. I learned a lot on the project. It forced a lot of painful, but positive growth at the studio, as this was by far the largest project the studio had ever taken on. Early on we had aggressive goals for number of characters on screen and the size and detail of the world. This forced us to consider new ways of working.
I did a lot of R&D on this project in several areas, from level creation to look dev and heavy NPR rendering techniques.
This project drove me to explore and begin to learn Houdini, and really think about what future game productions could look like. It changed my path, and I am very thankful for that.

domain: design


- Financial Fraud Detection Using Machine Learning vs. Traditional Rule-Based Systems
- Use Cases of Fraud Detection Using Machine Learning
- Email Phishing
- Credit Card Fraud
- Mobile Wallet Fraud
- Identity Theft
- Fraud Insurance Claims
- ATM Skimming
- Benefits of Financial Fraud Detection Using Machine Learning
- Faster Data Collection
- Effortless Scaling
- Increased Efficiency
- Reduced Security Breach
- Machine Learning Models for Fraud Detection
- Supervised Learning
- Unsupervised Learning
- Semi-Supervised Learning
- Reinforcement Learning
- How Does an ML System Work for Fraud Detection?
- Input Data
- Extract Features
- Train Algorithm
- Create a Model
- Real-World Examples of Fraud Detection Using Machine Learning
- Detect Fraud in FinTech with Appinventiv
With the ever-increasing growth of digital banking and online transactions, financial fraud detection has become an indispensable aspect of the BFSI market. Cybercrime activities like account takeover (ATO), credit card scams, and identity fraud can result in significant financial losses, legal implications, and reputational damage to financial firms.
According to Statista, the global eCommerce losses to online payment fraud reached $41 billion in 2022 and are estimated to cross $48 billion by the end of 2023. Therefore, detecting incidents of payment fraud and preventing associated losses has become a prime concern for businesses.
However, traditional fraud detection approach count on rule-based systems and have some limitations that can’t efficiently identify sophisticated fraud threats. This is where financial fraud detection using machine learning comes into play.
ML-based financial fraud detection offers more advanced techniques to analyze vast amounts of data and detect patterns to help identify susceptible behavior and prevent fraud related to money laundering, insurance claims, electronic payments, bank transactions, etc. Machine learning algorithms allow systems to automatically learn and improve from experience without being explicitly programmed.
Financial Fraud Detection Using Machine Learning vs. Traditional Rule-Based Systems
Financial fraud detection using machine learning has gained immense traction in recent years and shifted the industry from traditional rule-based systems to ML-based solutions.
Conventional methods of detecting fraudulent activities using rule-based systems have become obsolete in today’s tech-driven age. Since these systems work on predefined rules, they can effectively see known transaction patterns, but their capabilities are limited when it comes to identifying new and evolving ones. Also, they often generate false positives, flagging legitimate transactions as fraudulent activities.
One of the key benefits of using machine learning for fraud detection is its ability to adapt to new fraud patterns and reduce false positives. ML algorithms can learn from past fraud cases and adapt to new patterns, making them more efficient in identifying and preventing scams.
Also, machine learning models can analyze vast amounts of data and detect even the slightest change in customer behavior and transaction patterns that may not be apparent using traditional systems.
By using ML and AI for fraud detection in banking, companies can now leverage more advanced techniques for identifying unauthorized and suspicious activity, thus minimizing potentially fraudulent activities in real-time.
While traditional fraud detection methods have been effective for years, it has been seamlessly replaced by advanced ML algorithms, emerging as a more effective tool to reduce false positives and fraud cases.
Use Cases of Fraud Detection Using Machine Learning
In the corporate world, financial fraud can take place in many forms, such as identity theft, unauthorized access, money laundering, etc. Considering the wide scenarios of fraudulent activities, let’s discover some of the most common areas where financial fraud detection using machine learning can assist enterprises.
This is a type of cybercrime wherein attackers send fake messages and website links to users via email. These emails are seemingly legit and authentic; even users with good technical skills can misjudge them and enter vulnerable data, which puts them at risk.
Credit Card Fraud
In today’s ever-evolving digital landscape, credit card fraud has become a common activity of cybercriminals. This type of financial fraud involves stealing the details of debit cards or credit cards through unsecured internet connections.
Credit card fraud detection using artificial intelligence and machine learning helps differentiate between authentic and illegal actions. Consequently, if hackers try to cheat the system, an ML model alerts the internal cybersecurity teams and takes proactive measures to prevent attackers from executing their malicious plans.
Mobile Wallet Fraud
Machine learning integration is a highly valuable anti-fraud system in today’s digital age, where payment methods extend beyond physical cards and enter the realm of mobile wallets.
Smartphones now feature NFC chips, enabling users to pay for products with just a few taps of their phones, posing a higher risk of hacks and cyber threats. Machine learning for fraud detection efficiently detects abnormal activities for each user, thus minimizing digital wallet fraud risks.
Cybercriminals always look for vulnerabilities to steal financial information, such as customers’ names, bank details, passwords, login credentials, and other sensitive data, keeping both customers and companies at risk.
Financial fraud detection using AI and ML helps examine and check identity documents such as passports, driving licenses, PAN cards, etc, against secure databases to detect fraudulent activities. Besides, ML models also help fight fake IDs by enabling biometric scanning and face recognition features in fintech solutions.
Fraud Insurance Claims
Insurance fraud typically includes fake claims of car damage, property, and even unemployment. Insurance companies spend a lot of time, money, and resources to prevent such cases and validate each claim.
Insurance fraud detection using machine learning is a superior option. With its amazing pattern recognition capabilities, ML helps resolve insurance claims with utmost accuracy and identify fake claims.
Another common use case of fraud detection using machine learning is ATM skimming. It happens when a fraudster places a skimming device on an ATM, which steals the user’s card information when they swipe their cards at the machine.
Machine learning can detect such kinds of fraud by analyzing transactional data, identifying patterns, and detecting unusual activity, such as a sudden increase in ATM withdrawals.
Benefits of Financial Fraud Detection Using Machine Learning
Transaction fraud detection using machine learning and artificial intelligence has taken the prime spot in the finance sector. The BFSI market has to deal with a high volume of transactional data on a daily basis, and AI/ML algorithms can process a large dataset more easily and efficiently than humans, making it an ideal choice for fraud detection in real time. Let’s discover the multifarious benefits of fraud detection in banking using machine learning.
Faster Data Collection
With the ever-evolving trend of eCommerce, it has been vital for businesses to have quicker solutions like machine learning to detect fraud. Machine learning algorithms can evaluate enormous amounts of data in a short amount of time. They can continuously collect and analyze data and detect frauds in real time.
As data sets continue to expand across industries, the prowess of machine learning algorithms amplifies. With an influx of data, machine learning models enhance their learning capabilities, thus, identifying patterns, similarities, and anomalies between multiple behaviors. Once genuine and fraudulent transactions are found, the system instantly processes them, discerning the nuances that characterize each category.
Unlike humans, machines can automate repetitive tasks, instantly detect changes across large volumes of data and identify fraud. Machine learning algorithms can accurately analyze thousands of payments per second. It reduces the time, cost, and resources required to analyze transactions, making the process more accurate and efficient.
Reduced Security Breach
With the implementation of payment fraud detection using machine learning, companies can efficiently straighten their cybersecurity practices, prevent data breaches and provide the highest level of security to their customers. It works by comparing every new transaction with the previous (personal information, data, IP address, location, etc.) one and detecting suspicious cases. As a result, financial units can prevent fraud related to online payments or credit cards.
Machine Learning Models for Fraud Detection
Financial fraud detection with machine learning leverages several machine learning models. These models are typically a kind of program that is trained to detect patterns within the new dataset and make predictions about whether a given transaction is legitimate. Some of these models are more suitable and efficient in detecting fraud than others.
Here are the four most remarkable machine learning models/algorithms businesses can apply to detect fraud. Let’s describe each of them in detail:
Supervised learning is the most common type of ML model that works for cases like financial fraud detection in deep learning environments. In this model, all information is labeled as good or bad, meaning all data sets are already tagged with the correct answers. This fraud detection ML algorithm is based on predictive data analysis, and its accuracy depends on the training data. The only drawback of using a supervised model is that it will not be able to detect fraud if a similar fraud case is not included in the historical data used for its training.
Businesses can consider using unsupervised learning models, among others, to improve financial fraud detection using machine learning. An unsupervised learning model detects anomalous behavior in cases where there is no relevant data or little transaction data available. It continuously analyzes and processes new data and updates its models based on the findings to differentiate between legitimate and fraudulent operations.
Semi-supervised learning is something between supervised and unsupervised models. In this model, the machine learning algorithm processes a small volume of labeled information with a large amount of unlabeled data. This approach works for cases where labeling information is either impossible or too expensive and requires human intervention.
In the reinforcement learning approach, the machine detects ideal behavior automatically within a specified context. It helps machines to learn from the environment and find actions that minimize risks.
You may like reading: Estimating the Time, Cost, and Deliverables of an ML App Project
How Does an ML System Work for Fraud Detection?
Financial fraud detection using machine learning starts with gathering and segmenting the data. Then this data is fed to the machine learning model to predict the probability of fraud. Below are the steps that show how an ML system works for fraud detection:
Machine learning for fraud detection first needs to collect data. The more data an ML model gets, the better it can learn and polish its fraud detection skills. So, you first need to input enough data into the models.
The next step is feature extraction. At this stage, features describing both good customer behaviors and fraudulent customer behaviors are added. These features usually include customers’:
- Identity: It comprises the fraud rate of customers’ IP addresses, the age of their account, the number of devices they were seen on, etc.
- Order: This feature shows the number of orders customers made, average order value, number of failed transactions, and more.
- Location: This feature checks customers’ locations and the fraud rates at the customer’s IP address and shipping address.
- Payment Methods: It helps identify the fraud rates in credit/debit card issuing banks, the similarity between customers’ names and billing names, etc.
- Network: It includes the number of emails, phone numbers, or payment methods shared within a network.
An algorithm is a set of rules that needs to be followed by an ML model to decide whether an operation is fraudulent or legitimate. The more data your business can provide for a training set, the better the ML model will perform to distinguish between ‘genuine’ and ‘fraud’ transactions.
Create a Model
Once you have trained the machine learning algorithm using a specific dataset, you are ready with a model that can detect fraud in no time with high accuracy. However, to be effective in fraud detection, a machine learning model needs to be constantly improved and updated.
Real-World Examples of Fraud Detection Using Machine Learning
Businesses across industries, like eCommerce, banking, online gaming, and healthcare are using artificial intelligence and machine learning for financial fraud detection. No matter your industry, you can always enjoy the power of AI and ML to process huge amounts of data and draw patterns to protect it from fraud. For instance, ML and AI in finance detect account takeovers, unauthorized access, and other scams by tracing patterns in customers’ behavior. Here are some real-world examples of companies that are already leveraging the power of financial fraud detection with machine learning
Compliance.ai software for compliance management use adaptive machine learning models in fintech to automate research and track financial regulatory updates in a single platform.
PayPal, a leading fintech company worldwide also uses machine learning to enhance its fraud detection and risk management capabilities. Through a combination of linear, neural networks, and deep learning techniques, PayPal’s risk management engines can determine the risk levels associated with a customer within milliseconds.
MasterCard, the second-largest payment-processing corporation worldwide, integrates AI and ML to track and process variables such as transaction time, size, location, device, and purchase data. MasterCard’s ML-based financial fraud detection assesses customers’ account behavior in each operation and provides real-time insight into whether a transaction is genuine or fraudulent.
Feedzai, a fintech company, develops real-time machine learning solutions to detect fraudulent payment transactions in finance, retail, eCommerce, and other industries. The company believes that a fine-tuned machine learning tool can see up to 95% of all fraud while reducing the amount of human labor required during the investigation stage, which accounts for 25% of fraud expenditures.
These leading examples of companies using machine learning for fraud detection testifies to how ML models take care of all the complex work of data analysis and allow companies to grow safe from fraud.
Detect Fraud in FinTech with Appinventiv
Enterprises all over the world have started using machine learning to prevent financial fraud. It is the most innovative tool that enables organizations to create more complex algorithms for analyzing various transactions and suspicious economic behavior, thus minimizing the risks of financial losses.
Accordingly, hiring machine learning development services from a trusted AI Development Company like Appinventiv has become the topmost priority for businesses across industries to secure their payment systems.
As a leading AI development company, we leverage artificial intelligence, machine learning, and other emerging technologies to detect and prevent financial fraud and protect brand reputation.
We use a combination of machine learning models and AI trends to build cutting-edge solutions that analyze large amounts of data, identify patterns and detect anomalies that are indicative of fraudulent activities.
For instance, we helped Bajaj Finserv, a leading FinTech enterprise, build a secure digital platform to increase merchant onboarding and transactions. As we worked with a pioneer fintech application, implementing advanced security methods to predict and prevent financial fraud was our top priority. Our skilled engineers developed effective solutions and created an efficient online platform for merchants. It led the company to gain 300+ merchants and three lacs daily transactions.
Being a professional Fintech Software Development Company, we empower global organizations with various innovative solutions and approaches to improve their productivity and reduce financial risk.
Contact us now and see how we can help protect your business!
Q. What is ML-based financial fraud detection?
A. Machine learning for financial fraud detection deploys various ML models and algorithms to analyze vast amounts of data and detect patterns. These models are trained using an extensive data set. They are self-learning and adaptive to new, unknown, and innovative fraud patterns.
Q. What are common ML techniques used in fraud detection?
A. Logistic regression, random forests, decision trees, and neural networks are some of the most remarkable ML techniques used in financial fraud detection.
Q. What types of financial frauds can ML detect?
A. Fraud detection in banking using machine learning can detect almost all types of financial fraud, such as suspicious logins, email phishing, insurance claims, identity theft, fraudulent transactions, etc.


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The Seventh Day Sabbath
The seventh day sabbath is the seventh day after working 6 days.
Genesis 2:1 Thus the heavens and the earth were finished, and all the host of them. And on the seventh day God ended his work which he had made; and he rested on the seventh day from all his work which he had made. And God blessed the seventh day, and sanctified it: because that in it he had rested from all his work which God created and made.
No, I am not of the 7th day adventist religion. Those people worship on Saturday, not on the 7th day. They worship on the 7th day of the Gregorian calendar week, Saturday. This is not the 7th day sabbath written about in the Bible.
Some people call the 7th day sabbath a lunar sabbath to distinguish it as the sabbaths calculated by the new moon. When the sabbath was given by God in Genesis 2:3, there was no Babylonian calendar, no Greek calendar, No Julian calendar, no Gregorian calendar. It was very simple. After six days of work you rested on the seventh day.
With God's month beginning with the new moon, this was a day of worship and rest. So on the first day of the month, we rest. On the next six days we work, as God worked six days.
Sabbath Described in Genesis
Exodus 16:1 And they took their journey from Elim, and all the congregation of the children of Israel came unto the wilderness of Sin, which is between Elim and Sinai, on the fifteenth day of the second month after their departing out of the land of Egypt....And it shall come to pass, that on the sixth day they shall prepare that which they bring in; and it shall be twice as much as they gather daily...And Moses and Aaron said unto all the children of Israel, At even, then ye shall know that the LORD hath brought you out from the land of Egypt: And in the morning, then ye shall see the glory of the LORD; for that he heareth your murmurings against the LORD: and what are we, that ye murmur against us?... And it came to pass, that on the sixth day they gathered twice as much bread, two omers for one man: and all the rulers of the congregation came and told Moses. And he said unto them, This is that which the LORD hath said, To morrow is the rest of the holy sabbath unto the LORD: bake that which ye will bake to day, and seethe that ye will seethe; and that which remaineth over lay up for you to be kept until the morning....
I've omitted verses for your convenience. I encourage you to read this chapter and the whole Bible for that matter.
In Exodus, on the 15th day of the month, God gave commandment that they were to gather the manna for six days and rest on the 7th day. They would find out in the evening (the beginning of a day). So if you work six days (days 16 through 21), then the next sabbath would be on the 22th. The scriptures are for our learning. There is a reason why the Bible records on which day of the month they were told things and which day were sabbaths. God is not the author of confusion.
Exodus 20:9 Six days shalt thou labour, and do all thy work:
Exodus 20:11 For in six days the LORD made heaven and earth, the sea, and all that in them is, and rested the seventh day: wherefore the LORD blessed the sabbath day, and hallowed it.
Exodus23:12 Six days thou shalt do thy work, and on the seventh day thou shalt rest: that thine ox and thine ass may rest, and the son of thy handmaid, and the stranger, may be refreshed.
Exodus 31:15 Six days may work be done; but in the seventh is the sabbath of rest, holy to the LORD: whosoever doeth any work in the sabbath day, he shall surely be put to death.
Exodus 31:17 It is a sign between me and the children of Israel for ever: for in six days the LORD made heaven and earth, and on the seventh day he rested, and was refreshed.
It's interesting how some people want to be a child of Abraham but not a child of Israel. Weren't Abraham and Israel both children of God?
Exodus 34:21 Six days thou shalt work, but on the seventh day thou shalt rest: in earing time and in harvest thou shalt rest.
Exodus 35:2 Six days shall work be done, but on the seventh day there shall be to you an holy day, a sabbath of rest to the LORD: whosoever doeth work therein shall be put to death.
Lev_23:3 Six days shall work be done: but the seventh day is the sabbath of rest, an holy convocation; ye shall do no work therein: it is the sabbath of the LORD in all your dwellings.
Ezekiel 46:1 Thus saith the Lord GOD; The gate of the inner court that looketh toward the east shall be shut the six working days; but on the sabbath it shall be opened, and in the day of the new moon it shall be opened.
Disciples of Jesus Christ Observed 7th Day Sabbath
Mark 16:1 And when the sabbath was past, Mary Magdalene, and Mary the mother of James, and Salome, had bought sweet spices, that they might come and anoint him.
Luke 23:56 And they returned, and prepared spices and ointments; and rested the sabbath day according to the commandment.
Matthew 24:20 But pray ye that your flight be not in the winter, neither on the sabbath day:
There are tons of verses which refer to the 7th day sabbath and I have not listed them all.
I have come to love the seventh day sabbath. It is a day of rest. After working 6 days at my job I can sit down to the scriptures and read and learn more about God. This is a blessing and gift of God, to work 6 days and have the 7th day to rest. Thanks God :)
New Moon Day
7th day Sabbath
How To -Time Keeping
Feast of Tabernacles
Days of Week
|To open their eyes, and to turn them from darkness to light, and from the power of Satan unto God, that they may receive forgiveness of sins, and inheritance among them which are sanctified by faith that is in me. - Jesus Christ speaking to Saul, see Act 26:18, see Salvation through Jesus Christ.|

domain: literature


PETA Kills 97% of Dogs & Cats Brought in 2009 for a total of 2,301 — Adopts Out Only 8!
July 8, 2010
It’s no secret that I’m no fan of PETA and believe their operation borders on being a cult. They are quite clear in their core message, no animal should be used by any human for any purpose; not for medical research, not for food and not as pets.
But many people think of them as the ‘good guys’ fighting for animal rights and support them without really understanding where their money is going. Would you send them $25 if you knew that they kill almost every dog and cat that is surrendered to them?
“It’s whoring itself out for media coverage,” David Martosko, director of research at the Center for Consumer Freedom, said of PETA. “They’ll do the ridiculous stuff, but they won’t put an ad in the Norfolk press saying, ‘We have puppies and kittens, come adopt one.'”
For the complete article go to the Care 2 website here.


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Caldicot Castle Country Park, Caldicot CastleChurch Road, Caldicot, Monmouthshire, NP26 4PJ
This event is FREE
FREE entry and some exceptional exhibits with a castle packed full of World War Two era machines and beyond, equipment and re-enactors. With larger and heavier vehicles sprawling out in to the grounds around. British, American and German World War Two military exhibits will include motorcycles, jeeps, trucks and tracked armoured vehicles. With vintage military vehicles and displays stretching from Vietnam to the 1980’s.
FREE entry make it a fantastic, affordable this Bank Holiday weekend.
Cafeteria and food stands will be open throughout the event.
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words of readers not our view. check before travelling.
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domain: hobby


2002 Volume 2002 Issue 4 Pages 11-32
Species composition of soft corals from the Yaeyama and Miyako island groups, of Sakishima Is., located at the southern part of the Ryukyu Archipelago were studied during 1992 and 1993. SCUBA collections were carried out at 18 sites around the islands down to 30m. The collection, comprising approximately 200 specimens, yielded 45 species. The survey established two new species: Sinularia higai and S. tanakai, and in addition revealed 14 new zoogeographical records. Among the latter are Protodendron and Rhytisma species, which are the first records of these genera in the Ryukyu Archipelago. The obtained results along with a previous survey on Sesoko Is. show the genus Sinularia have the highest species diversity on the reefs, comprising 33-45% of total species number. Synthesizing the existing data for the south Ryukyu Archipelago yielded a total of 56 soft coral species (11 genera) of the families Clavulariidae, Tubiporidae, Alcyoniidae and Briareidae.
Since the survey was conducted prior to the recent mass coral bleaching event (1998) in the region, it is of prime importance to monitor changes in soft coral species diversity and abundance there. Such data will indicate possible shifts in benthic community structure on the reefs and the rate of recovery.


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Caramel Decoration Tips & Tricks. Desserts recepie. So Yummy easy recepie Luxury decorations
Find supreme deals for your room to match style and budget ⋆ Enjoy Free Shipping ⋆ Shop Today's Deals @ Rosseta Home™ Your Online home decor store.
DIY Newborn photo photography props Crowns trim fabric from www.hamptonphotographyny.com
Here is another simple DIY photography prop from Hampton Photography. SIMPLE! All you need is a roll of trim fabric. I bought mine from Wal-mart BUT you can buy this in any fabric store. Make sure it's flat on one side and sort of has a crown shape to it. For newborn photos I cut a 10.5 inch length, then spray it with either GOLD or SILVER spray paint (you can buy this at any hardware store)let it dry, then spray with FABRIC STIFFENER (also from Wal-mart) The brand I used was Aleene's…
How to Make Newborn Wraps | DIY Newborn Photography Prop | San Diego Newborn Photographer
I finally found a use for kool-aid and it isn't for a drink. I am super excited to do more newborn photography sessions this year and wanted to make beautiful newborn wraps to add a pop of color to the photographs as well as keep the newborn comfortable during the session.
Fabric Flower Baby Headbands - Create and Babble
Ever since I heard the words: “it’s a girl” I’ve been oohing and aahing over all the cute baby girl stuff that I want to make. First up are these fabric flower baby headbands. These were so super simple to make. If the thought of operating a sewing machine makes you a little woozy, you’ll […]
Sadie Bear Crochet Pattern
Original Design By: Maggie Weldon Skill Level: Easy Size: About 15" high (11" when sitting) Materials: Teddy Bear - Worsted Weight Yarn : Sea Green – 18oz, 870yds (510g, 798m) (Vanna’s Choice - Seaspray Mist - used in model) Sweater - Sport Weight Yarn : White - 1.75 oz, 136 yds (50 g, 125 m) (Patons Grace - Snow - used in model.) Additional Materials: Yarn Needle. 12mm Black Plastic Safety Eyes - 2 15mm by 12mm Oval Black Safety Nose - 1 Black Embroidery Thread & Needle. Fiberfill 1¾”…
i might have made this look more complicated than necessary, because i'm the kind of person who likes every little thing spelled out. only four of these steps (6, 8, 12, 13) actually involve sewing. yellow is right side of shirt, turquoise is wrong side. let me know if you have questions or i wrote…
Where to Buy Quality Fabric Online, The Ultimate Guide! - It's Just Sewing
Finally, A Comprehensive list of Quality Online Fabric Shops just for you! Quality comes in so many forms. The type of fabric we buy and who we buy it from can make a huge difference to the outcome of our projects AND how we feel about those projects. Q


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Samsung might do away with the flat-screen Galaxy S
Samsung’s curved “edge” display has certainly given a new lease of life to the company’s Galaxy S series of flagships. Not only does it produce a unique and sleek looking design, but Samsung has also managed to create a selection of useful software features that make the most of the hardware. Now the company is hinting that it may ditch the regular flat-screen option for its flagship smartphones in the future, in order to focus on its edge technology.
Demand for the Galaxy S6 Edge initially caught Samsung a little by surprise a couple of years ago, leaving the company scrambling to produce enough units and resulting in unsold stock of the regular flat-screen Galaxy S6. This time around, Samsung has been able to ramp up production of its dual-edge curved display for the Galaxy S7 Edge, and the Note 7 now comes exclusively with the curved display and has even dropped the edge moniker.
A similar situation could be heading to the company’s main Galaxy S range in the next year or so. Samsung has indicated that it will put more focus on curved Galaxy S models in the future and that it may eventually eliminate flat-screen Galaxy S handsets further down the line. Production yields for Samsung’s edge display are now high enough to keep up with demand, enough so that the company has been selling excess panels to rival smartphone manufacturers.
“Samsung has considered that it would make the edge display as the identity of the Galaxy S smartphone lineup if the company can provide consumers differentiated user experience through software and user-friendly functions” – Koh Dong-jin, head of Samsung’s mobile business
Although this might not happen in time for the Galaxy S8 next year, the current theory is that the Galaxy Note 7 is acting a gauge to see how well consumers react to only having the single display option to pick from. This may then influence the company’s decision to issue a single curved S flagship, although Koh’s comment is far from confirmation that the flat-screen display model will be eliminated any time soon.
[related_videos align=”center” type=”custom” videos=”706763,690098,680806″]
Where do you stand on the topic? Is Samsung’s curved display technology the future of the Galaxy flagship line, or does a regular flat-screen variant still appeal to you?


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A weekly report on the politics, economics and science of climate action
By Jenny Goldie, CCL member from the electorate of Eden Monaro, NSW.
PM on the defensive at the G7
The G7 nations are meeting in Cornwall this weekend and our Prime Minister has gone off to join them, though we are not a G7 member. Mr Morrison will likely protest the imminent imposition of carbon border tariffs against nations like Australia, which do not promise strong climate action. It is estimated that in Australia 43 export industries are expected to be affected by these new tariffs. Let’s see how that goes.
Also on the international front, a critical joint report by the top organisations on climate (IPCC) and biodiversity (IPBES) concluded that both crises must be solved together, or not at all. The full report – with a harrowing picture of a starving polar bear – can be found here.
The highest CO2 level ever recorded
We had hoped that Covid might have had reduced overall levels of carbon dioxide in the air. However, that’s not the case. All that happened was that annual emissions fell, but net emissions did not go negative. The Mauna Loa station in Hawaii, well away from all pollution in the mid-Pacific, recorded 419ppm CO2 levels in May, the highest level in 63 years of operation.
It was freezing cold – snow even fell – earlier this week. This prompted the pro-coal and gas former Resources Minister Matt Canavan to sneer at the idea of global warming. “Why is fire climate change but snow not climate change?” he asked on Twitter. Good question, I guess, given snow is rare in Queensland. Nevertheless, it is a common phenomenon on the Central and Northern Tablelands of NSW so, no Mr Canavan, the world is not on a cooling trend.
There were a couple of victories through the week. A court sided with Greenpeace after AGL had taken them to court alleging breach of copyright. Greenpeace had parodied AGL’s logo. The other victory was the NSW Planning Department strongly recommending against Hume Coal’s proposed mine at Sutton Forest, since it would not be compatible with rural land use in the area.
In the absence of effective climate action at federal level, the states are doing the work for them. The Queensland government announced a $1.86 billion jobs fund, a feasibility study for 1GW of pumped hydro, and a $2 billion investment for renewable energy and hydrogen.
In NSW Transport Minister Andrew Constance promised to electrify the entire NSW railway fleet by 2025 and eventually all vehicles, though more for air quality and health reasons than climate. NSW’s Treasury also predicts coal will be dead in 20 years.
Petitions to sign
- Call on the NSW Government to sign the Fossil Fuels Non-Proliferation Treatyhere.
- Call on all governments to commit to climate and environmental literacy at the COP26 meeting in Glasgow in Novemberhere.
Manufacturing for a zero-emissions economy. Tuesday June 15 1 to 2pm. Register here.
- Fears Antarctic glacier could melt faster as it speeds up and ice shelf ‘rips apart’. Antarctica’s Pine Island Glacier is speeding up again as its ice shelf is breaking up, and scientists say they’ve underestimated how quickly it may disappear.
- Bright side: what Australia’s rooftop solar can teach us about electric cars. Our solar rollout has been world-leading and can point the way to get us moving on EVs.
- We don’t need supersonic travel—in the “new normal,” we should slow down. If we’re going to take climate change seriously, it also needs to come with a new aesthetic.
- Morrison government’s $600m gas power plant at Kurri Kurri not needed and won’t cover costs, analysts say. Little demand is likely for the ‘peaking’ plant before 2030, calling into question the Coalition’s claim it will reduce electricity prices.
- Electric vehicle taxes not needed to offset falling fuel excise revenue: report. The report argues the federal government should instead upgrade the nation’s energy grid and push the mining sector to convert from diesel to electric-powered off-road vehicles.
- Climate change a security threat: report. A new report by former defence and security leaders suggests climate change presents a clear and present danger to the world’s collective security.
- Climate crisis to shrink G7 economies twice as much as Covid-19, says research. G7 countries will lose $5tn a year by 2050 if temperatures rise by 2.6C
- An enormous missing contribution to global warming may have been right under our feet. Long before the era of fossil fuels, humans may have triggered a massive but mysterious “carbon bomb” lurking beneath the Earth’s surface, a new scientific study suggests.
- Warm clouds are cooling Earth, confounding climate models. While the amount of carbon dioxide emissions steadily increases in the atmosphere, the formation of warmer clouds appears to have a cooling effect that has been underestimated by widely used climate models.
- My new hero, Mathias Cormann, now valiant for truth and on the winning side. Now he is head of the OECD, new insight has come to Cormann in a blinding flash: market principles work to cut carbon.
The views and wishes expressed in this blog post are those of the author, and not necessarily of CCL Australia.


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This map was created by a user. Learn how to create your own.
Jul 01, 2019 · Call of Duty: Black Ops 4 has finally released their brand new Blackout map, which sees a newly redesigned version of the iconic Alcatraz Island. Unlike the original Blackout map though, Alcatraz ...
In 1976, Alcatraz Island became part of the National Register of Historic Places, and in 1986 it became a National Historic Landmark. Atlas Obscura Trips Escape: Art of Joshua Tree and the Mojave
Alcatraz (Google Maps). Explore Alcatraz in San Francisco, CA as it appears on Google Maps as well as pictures, stories and other notable nearby locations on VirtualGlobetrotting.com.
Originally built as request for an Australian server, the 1960 edition of our Alcatraz Island reproduction is now available for everybody! We are conscious of the popularity of our map for prison servers and want to share with you this alternative version of the island, specially built for an use on servers, including (almost) all buildings present on the map in the 1960 years (the last year ...
Alcatraz Map. Consult an Alcatraz map, and you will notice that the Main Cellhouse lies in the island's center. This cellhouse was where the prisoners were held and is a major Alcatraz feature. Visitors can also stroll through the old prison Recreation Yard, which is found just off the Main Cellhouse. This enclosed yard was used by prisoners ...
Alcatraz was featured in the video game Call of Duty: Black Ops II in a downloadable zombie survival map called "Mob of the Dead" in which players could explore the Main Cellhouse, the Boat Dock, and a fictional area called the Catacombs which runs through the island.
T4M Link - This map does require T4M. Created by: Whippytrout Story: March 21, 1963 The year Alcatraz Federal Penitentiary closed. President John F. Kennedy had scheduled a political trip to Dallas, Texas in order to smooth over frictions in the [/img]Democratic Party.
Alcatraz Island, also known as ‘The Rock,’ a rocky island in San Francisco Bay, off the coast of California, in the United States. From 1934 to 1963, a facility on the island served as a federal prison for some of the most dangerous civilian prisoners. Learn more about the history of Alcatraz Island here.
Feb 15, 2019 · The small island of Alcatraz in the middle of San Francisco Bay was first a lighthouse, then a military fortification, then a military prison and finally a federal prison until 1963. Covering 22.86 acres, the island was discovered by Spaniard Juan Manuel de Ayala in 1775. He named it "La Isla de los Alcatraces" (The Island of the Pelicans).

domain: history