Tag: 上海后花园夜生活

Usain Bolts funniest moments

first_imgIBTimes VideoRelated VideosMore videos Play VideoPauseMute0:01/1:21Loaded: 0%0:01Progress: 0%Stream TypeLIVE-1:20?Playback Rate1xChaptersChaptersDescriptionsdescriptions off, selectedSubtitlessubtitles settings, opens subtitles settings dialogsubtitles off, selectedAudio Trackdefault, selectedFullscreenThis is a modal window.Beginning of dialog window. Escape will cancel and close the window.TextColorWhiteBlackRedGreenBlueYellowMagentaCyanTransparencyOpaqueSemi-TransparentBackgroundColorBlackWhiteRedGreenBlueYellowMagentaCyanTransparencyOpaqueSemi-TransparentTransparentWindowColorBlackWhiteRedGreenBlueYellowMagentaCyanTransparencyTransparentSemi-TransparentOpaqueFont Size50%75%100%125%150%175%200%300%400%Text Edge StyleNoneRaisedDepressedUniformDropshadowFont FamilyProportional Sans-SerifMonospace Sans-SerifProportional SerifMonospace SerifCasualScriptSmall CapsReset restore all settings to the default valuesDoneClose Modal DialogEnd of dialog window. COPY LINKAD Loading … Usain Bolts funniest moments Usain Bolt has cemented himself as a sprinting legend, smashing world records and becoming the first person in history to win the 100m and 200m at three consecutive Olympic Games. But the fastest man alive is also known for his fun personality, as he regularly jokes with the press and messes around with fans.center_img Closelast_img read more

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Lunar rock samples reveal variations in water concentrations

first_img Citation: Lunar rock samples reveal variations in water concentrations (2014, May 26) retrieved 18 August 2019 from https://phys.org/news/2014-05-lunar-samples-reveal-variations.html (Phys.org) —A team of researchers studying rocks returned from the moon by Apollo 17 astronauts has found that rocks found in different locations have different amounts of water in them. In their paper published in the journal Nature Geoscience, the team describes their findings and offer possible explanations for the concentration differences. Secondary electron image of pits left by ion microprobe analyses of a heterogeneous apatite grain in Apollo sample 14321, 1047. Water has now been detected in apatite in many different lunar rock types. Credit: K.L. Robinson, HIGP. Optical micrograph of pyroclastic glass beads in Apollo sample 74220, 383, the famous “orange soil”. Water was first detected by Saal et al., 2008 in glass beads similar to these. Credit: G.J. Taylor, HIGP More information: Heterogeneous distribution of water in the Moon, Nature Geoscience (2014) DOI: 10.1038/ngeo2173AbstractInitial analyses of lunar samples returned by the Apollo missions indicated that the Moon was essentially devoid of water. However, improved analytical techniques have revealed that pyroclastic glass beads in Apollo samples contain measurable amounts of water. Taking into account volatile loss during eruption of the glass beads onto the surface, the pre-eruption magma could have contained water on the order of 100 ppm by weight, concentrations that are similar to the mantle sources of mid-ocean ridge basalts on Earth. Lava flows from vast basaltic plains—the lunar maria—also contain appreciable amounts of water, as shown by analyses of apatite in mare basalt samples. In contrast, apatite in most non-mare rocks contains much less water than the mare basalts and glass beads. The hydrogen isotopic composition of lunar samples is relatively similar to that of the Earth’s interior, but the deuterium to hydrogen ratios obtained from lunar samples seem to have a larger range than found in Earth’s mantle. Thus, measurements of water concentration and hydrogen isotopic composition suggest that water is heterogeneously distributed in the Moon and varies in isotopic composition. The variability in the Moon’s water may reflect heterogeneity in accretion processes, redistribution during differentiation or later additions by volatile-rich impactors. Explore further © 2014 Phys.org Digging deep in search of water on the moon Journal information: Nature Geoscience It was just six years ago that scientists learned that there was water on the moon, prior to that, conventional wisdom suggested the moon was not only barren, but completely dry. That discovery led to more research which revealed that not only is there water on the moon, but it’s actually widespread—sealed inside of rocks, but present nonetheless. In this new effort, the research team reports that in studying the findings of several other teams analyzing the rocks since water was first found in them, they’ve discovered that some of the rocks have more water sealed inside of them than others—the difference appears to be related to where on the moon the rocks were found. This suggests, the team reports, that some parts of the moon are wetter than others. The new research team also found that the chemical composition of the water was different depending on the rock source as well.The findings have led the researchers to consider how differing water concentrations relate to theories regarding the origin of the moon. Most scientists believe the moon came to exist approximately four and half billion years ago when a collision occurred between Earth and another planet. The general consensus is that some of the moon came from Earth, some from the other planet and the rest from other bodies such as comets and asteroids that subsequently struck the moon. Water on the moon could therefore have come from the Earth, the other planet or comets. Intriguingly, the researchers have found that the chemical makeup of water samples in some of the rocks (volcanic glass) is similar to magma samples that once resided in Earth’s mantle. Others, on the other hand, were found to be much drier. The researchers conclude that the formation of the moon appears to have been a far more complex series of events than theories have suggested. This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.last_img read more

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A serverless online store on AWS could save you money Build one

first_imgIn this article you will learn to build an entire serverless project of an AWS online store, beginning with a React SPA frontend hosted on AWS followed by a serverless backend with API Gateway and Lambda functions. This article is an excerpt taken from the book, ‘Building Serverless Web Applications‘ written by Diego Zanon. In this book, you will be introduced to the AWS services, and you’ll learn how to estimate costs, and how to set up and use the Serverless Framework. The serverless architecture of AWS’ online store We will build a real-world use case of a serverless solution. This sample application is an online store with the following requirements: List of available products Product details with user rating Add products to a shopping cart Create account and login pages For a better understanding of the architecture, take a look at the following diagram which gives a general view of how different services are organized and how they interact: Estimating costs In this section, we will estimate the costs of our sample application demo based on some usage assumptions and Amazon’s pricing model. All pricing values used here are from mid 2017 and considers the cheapest region, US East (Northern Virginia). This section covers an example to illustrate how costs are calculated. Since the billing model and prices can change over time, always refer to the official sources to get updated prices before making your own estimations. You can use Amazon’s calculator, which is accessible at this link: http://calculator.s3.amazonaws.com/index.html. If you still have any doubts after reading the instructions, you can always contact Amazon’s support for free to get commercial guidance. Assumptions For our pricing example, we can assume that our online store will receive the following traffic per month: 100,000 page views 1,000 registered user accounts 200 GB of data transferred considering an average page size of 2 MB 5,000,000 code executions (Lambda functions) with an average of 200 milliseconds per request Route 53 pricing We need a hosted zone for our domain name and it costs US$ 0.50 per month. Also, we need to pay US$ 0.40 per million DNS queries to our domain. As this is a prorated cost, 100,000 page views will cost only US$ 0.04. Total: US$ 0.54 S3 pricing Amazon S3 charges you US$ 0.023 per GB/month stored, US$ 0.004 per 10,000 requests to your files, and US$ 0.09 per GB transferred. However, as we are considering the CloudFront usage, transfer costs will be charged by CloudFront prices and will not be considered in S3 billing. If our website occupies less than 1 GB of static files and has an average per page of 2 MB and 20 files, we can serve 100,000 page views for less than US$ 20. Considering CloudFront, S3 costs will go down to US$ 0.82 while you need to pay for CloudFront usage in another section. Real costs would be even lower because CloudFront caches files and it would not need to make 2,000,000 file requests to S3, but let’s skip this detail to reduce the complexity of this estimation. On a side note, the cost would be much higher if you had to provision machines to handle this number of page views to a static website with the same availability and scalability. Total: US$ 0.82 CloudFront pricing CloudFront is slightly more complicated to price since you need to guess how much traffic comes from each region, as they are priced differently. The following table shows an example of estimation: RegionEstimated trafficCost per GB transferredCost per 10,000 HTTPS requestsNorth America70%US$ 0.085US$ 0.010Europe15%US$ 0.085US$ 0.012Asia10%US$ 0.140US$ 0.012South America5%US$ 0.250US$ 0.022 As we have estimated 200 GB of files transferred with 2,000,000 requests, the total will be US$ 21.97. Total: US$ 21.97 Certificate Manager pricing Certificate Manager provides SSL/TLS certificates for free. You only need to pay for the AWS resources you create to run your application. IAM pricing There is no charge specifically for IAM usage. You will be charged only by what AWS resources your users are consuming. Cognito pricing Each user has an associated profile that costs US$ 0.0055 per month. However, there is a permanent free tier that allows 50,000 monthly active users without charges, which is more than enough for our use case. Besides that, we are charged for Cognito Syncs of our user profiles. It costs US$ 0.15 for each 10,000 sync operations and US$ 0.15 per GB/month stored. If we estimate 1,000 active and registered users with less than 1 MB per profile, with less than 10 visits per month in average, we can estimate a charge of US$ 0.30. Total: US$ 0.30 IoT pricing IoT charges starts at US$ 5 per million messages exchanged. As each page view will make at least 2 requests, one to connect and another to subscribe to a topic, we can estimate a minimum of 200,000 messages per month. We need to add 1,000 messages if we suppose that 1% of the users will rate the products and we can ignore other requests like disconnect and unsubscribed because they are excluded from billing. In this setting, the total cost would be of US$ 1.01. Total: US$ 1.01 SNS pricing We will use SNS only for internal notifications, when CloudWatch triggers a warning about issues in our infrastructure. SNS charges US$ 2.00 per 100,000 e-mail messages, but it offers a permanent free tier of 1,000 e-mails. So, it will be free for us. CloudWatch pricing CloudWatch charges US$ 0.30 per metric/month and US$ 0.10 per alarm and offers a permanent free tier of 50 metrics and 10 alarms per month. If we create 20 metrics and expect 20 alarms in a month, we can estimate a cost of US$ 1.00. Total: US$ 1.00 API Gateway pricing API Gateway starts charging US$ 3.50 per million of API calls received and US$ 0.09 per GB transferred out to the Internet. If we assume 5 million requests per month with each response with an average of 1 KB, the total cost of this service will be US$ 17.93. Total: US$ 17.93 Lambda pricing When you create a Lambda function, you need to configure the amount of RAM memory that will be available for use. It ranges from 128 MB to 1.5 GB. Allocating more memory means additional costs. It breaks the philosophy of avoiding provision, but at least it’s the only thing you need to worry about. The good practice here is to estimate how much memory each function needs and make some tests before deploying to production. A bad provision may result in errors or higher costs. Lambda has the following billing model: US$ 0.20 per 1 million requests US$ 0.00001667 GB-second Running time is counted in fractions of seconds, rounding up to the nearest multiple of 100 milliseconds. Furthermore, there is a permanent free tier that gives you 1 million requests and 400,000 GB-seconds per month without charges. In our use case scenario, we have assumed 5 million requests per month with an average of 200 milliseconds per execution. We can also assume that the allocated RAM memory is 512 MB per function: Request charges: Since 1 million requests are free, you pay for 4 million that will cost US$ 0.80. Compute charges: Here, 5 million executions of 200 milliseconds each gives us 1 million seconds. As we are running with a 512 MB capacity, it results in 500,000 GB-seconds, where 400,000 GB-seconds of these are free, resulting in a charge of 100,000 GB-seconds that costs US$ 1.67. Total: US$ 2.47 SimpleDB pricing Take a look at the following SimpleDB billing where the free tier is valid for new and existing users: US$ 0.14 per machine-hour (25 hours free) US$ 0.09 per GB transferred out to the internet (1 GB is free) US$ 0.25 per GB stored (1 GB is free) Take a look at the following charges: Compute charges: Considering 5 million requests with an average of 200 milliseconds of execution time, where 50% of this time is waiting for the database engine to execute, we estimate 139 machine hours per month. Discounting 25 free hours, we have an execution cost of US$ 15.96. Transfer costs: Since we’ll transfer data between SimpleDB and AWS Lambda, there is no transfer cost. Storage charges: If we assume a 5 GB database, it results in US$ 1.00, since 1 GB is free. Total: US$ 16.96, but this will not be added in the final estimation since we will run our application using DynamoDB. DynamoDB DynamoDB requires you to provision the throughput capacity that you expect your tables to offer. Instead of provisioning hardware, memory, CPU, and other factors, you need to say how many read and write operations you expect and AWS will handle the necessary machine resources to meet your throughput needs with consistent and low-latency performance. One read capacity unit represents one strongly consistent read per second or two eventually consistent reads per second, where objects have a size up to 4 KB. Regarding the writing capacity, one unit means that you can write one object of size 1 KB per second. Considering these definitions, AWS offers in the permanent free tier 25 read units and 25 write units of throughput capacity, in addition to 25 GB of free storage. It charges as follows: US$ 0.47 per month for every Write Capacity Unit (WCU) US$ 0.09 per month for every Read Capacity Unit (RCU) US$ 0.25 per GB/month stored US$ 0.09 GB per GB transferred out to the Internet Since our estimated database will have only 5 GB, we are on the free tier and we will not pay for transferred data because there is no transfer cost to AWS Lambda. Regarding read/write capacities, we have estimated 5 million requests per month. If we evenly distribute them, we will get two requests per second. In this case, we will consider that it’s one read and one write operation per second. We need to estimate now how many objects are affected by a read and a write operation. For a write operation, we can estimate that we will manipulate 10 items on average and a read operation will scan 100 objects. In this scenario, we would need to reserve 10 WCU and 100 RCU. As we have 25 WCU and 25 RCU for free, we only need to pay for 75 RCU per month, which costs US$ 6.75. Total: US$ 6.75 Total pricing Let’s summarize the cost of each service in the following table: ServiceMonthly CostsRoute 53US$ 0.54S3US$ 0.82CloudFrontUS$ 21.97CognitoUS$ 0.30IoTUS$ 1.01CloudWatchUS$ 1.00API GatewayUS$ 17.93LambdaUS$ 2.47DynamoDBUS$ 6.75TotalUS$ 52.79 It results in a total cost of ~ US$ 50 per month in infrastructure to serve 100,000 page views. If you have a conversion rate of 1%, you can get 1,000 sales per month, which means that you pay US$ 0.05 in infrastructure for each product that you sell. Thus, in this article you learned the serverless architecture of AWS online store also learned how to estimate its costs. If you’ve enjoyed reading the excerpt, do check out, Building Serverless Web Applications to monitor the performance, efficiency and errors of your apps and also learn how to test and deploy your applications. Read Next: Google Compute Engine Plugin makes it easy to use Jenkins on Google Cloud Platform Serverless computing wars: AWS Lambdas vs Azure Functions Using Amazon Simple Notification Service (SNS) to create an SNS topiclast_img read more

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Competition Bureau takes action to strengthen competition in travel industry

first_imgCompetition Bureau takes action to strengthen competition in travel industry Share Travelweek Group OTTAWA — After an investigation, Canada’s Competition Bureau has issued a press release advising that it has taken action to strengthen competition and innovation in Canada’s travel industry.As per the release, Softvoyage will not enforce several types of exclusionary and restrictive contract terms in its contracts.John Pecman, Commissioner of Competition, stated: “We commend Softvoyage for its collaboration in resolving our concerns. We believe that today’s agreement will promote greater competition and innovation in the travel industry, resulting in better choices for Canadian travellers.”To read the full press release go to canada.ca/en/competition-bureau/news/2018/01/competition_bureautakesactiontostrengthencompetitionandinnovatio.html. Thursday, January 18, 2018 center_img Posted by Tags: Softvoyage << Previous PostNext Post >>last_img read more

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