投稿時間:2023-07-01 03:25:07 RSSフィード2023-07-01 03:00 分まとめ(25件)

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AWS	AWS Partner Network (APN) Blog	Live Troubleshooting of Amazon EKS Applications with Dynamic Instrumentation and Lightrun	https://aws.amazon.com/blogs/apn/live-troubleshooting-of-amazon-eks-applications-with-dynamic-instrumentation-and-lightrun/	Live Troubleshooting of Amazon EKS Applications with Dynamic Instrumentation and LightrunAmazon EKS provides a managed scaled control plane which eliminates the undifferentiated heavy lifting for the enterprise platform team Learn how using the Lightrun developer observability platform and Amazon EKS together organizations can maximize their mean time to resolution of defects enhance developer productivity and reduce overall logging costs Lightrun and Amazon EKS enable full cycle developer observability	2023-06-30 17:29:05
AWS	AWS Messaging and Targeting Blog	How To Build an Email Service on SES	https://aws.amazon.com/blogs/messaging-and-targeting/how-to-build-an-email-service-on-ses/	How To Build an Email Service on SESFoundations Amazon Simple Email Service SES handles hundreds of billions of email messages every month While many are outbound one of the fastest growing parts of the business is for inbound traffic Customers send and receive email via SES using a combination of public SMTP interfaces and the SES SDK Traditionally most customers used SES alongside …	2023-06-30 17:30:42
AWS	AWS Networking and Content Delivery	Using load balancer target group health thresholds to improve availability	https://aws.amazon.com/blogs/networking-and-content-delivery/using-load-balancer-target-group-health-thresholds-to-improve-availability/	Using load balancer target group health thresholds to improve availabilityIntroduction AWS recently added features to our Elastic Load Balancers ELB that give you control over when they take measures to shift traffic between targets In this blog we will explore these new capabilities and review how you can use them to improve the availability and resiliency of your applications Two types of Elastic Load …	2023-06-30 17:02:13
AWS	AWS	Inventing the Future of Transportation: How Iveco is Driving Transformation | Amazon Web Services	https://www.youtube.com/watch?v=qqEP_GFahac	Inventing the Future of Transportation How Iveco is Driving Transformation Amazon Web ServicesA conversation with Fabrizio Conicella Global Head of Digital and Advanced Technology for Iveco Group Giulia Rossi EMEA Digital Innovation Programs Lead AWS and Paolo Cimadoro Enterprise Account Manager AWS Learn more at Subscribe More AWS videos More AWS events videos Do you have technical AWS questions Ask the community of experts on AWS re Post ABOUT AWSAmazon Web Services AWS is the world s most comprehensive and broadly adopted cloud platform offering over fully featured services from data centers globally Millions of customers ーincluding the fastest growing startups largest enterprises and leading government agencies ーare using AWS to lower costs become more agile and innovate faster AWS AmazonWebServices CloudComputing	2023-06-30 17:08:59
AWS	AWS - Webinar Channel	Deploying machine learning models for inference- AWS Virtual Workshop	https://www.youtube.com/watch?v=ZzWs8RsACug	Deploying machine learning models for inference AWS Virtual WorkshopMaximizing inference performance while reducing cost is critical to delivering great customer experiences through ML Amazon SageMaker provides a breadth and depth of fully managed deployment features to achieve optimal inference performance and cost at scale without the operational burden In this episode learn how to use SageMaker inference capabilities to quickly deploy ML models in production for any use case including hyper personalization Generative AI and Large Language Models LLMs Learning Objectives Objective Learn about how to deploy ML models on Amazon SageMaker for inference Objective Discover the SageMaker inference endpoint options that fit your use case Objective Learn how to deploy Large Language Models LLMs for inference To learn more about the services featured in this talk please visit To download a copy of the slide deck from this webinar visit	2023-06-30 17:00:17
js	JavaScriptタグが付けられた新着投稿 - Qiita	【Blazor】JavascriptからC#(.Net)のstaticもしくはインスタンスメソッドを呼び出す。	https://qiita.com/kbrucke08/items/6d81e1cf2df9067123cf	blazor	2023-07-01 02:49:34
海外TECH	MakeUseOf	7 Free Travel Planning AI and ChatGPT Apps to Get an Instant Itinerary	https://www.makeuseof.com/free-travel-planning-ai-chatgpt-apps/	chatgpt	2023-06-30 17:15:18
海外TECH	DEV Community	AI-MediSphere™ - The Cardiovascular Prognosticator	https://dev.to/aws-builders/ai-medisphere-the-cardiovascular-prognosticator-4118	AI MediSphere The Cardiovascular Prognosticator OverviewHeart diseases are the cause of death every year Why It s usually already too late when people realise something is wrong and contact a medic How can we help people realise sooner and simultaneously how can we help medics save lives Our app powered by a chatbot AI collects minimal but crucial user data related to cardiovascular health including age weight gender lifestyle factors blood pressure cholesterol and glucose levels With this information the chatbot provides personalized explanations and recommendations guiding users to consult a medical professional if necessary By offering tailored insights our app aims to empower individuals to take proactive steps towards their cardiovascular well being potentially saving lives through early detection and intervention Problem statementThe aim of this project is to detect the presence or absence of cardiovascular disease in a person based on a set of given features The features available for analysis include the parameters like Age Height Weight Gender Physical Activity Level Drinking habits Various Blood Pressure parameters Cholesterol level Glucose level et cetera Proposed Solution and ApproachWe want to save the lives of many The best way to approach people and drive use is with a non invasive user friendly solution We preferred a simple and achievable goal to a technically complex solution that didn t add value So we decided to build an app with chatbot AI to collect just the minimum set of data the most important features and make a personalized explanation and recommendation based on the User s knowledge and data available to consult a medic eventually We use known and proven components only in a different way There are two parts to this project One we trained an ML model to predict cardiovascular diseases from decisive inputs Two the frontend chatbot application With today s countless alternatives we preferred to focus on the back end on milestone Today it s not about the code effective communication is the most important part of the stack The most important step is getting users to use the app understand it and act Step by Step Solution Details Classification The Cardio Vascular Prediction solution utilizes the powerful and widely acclaimed XGBoost algorithm for accurate predictions XGBoost also known as Extreme Gradient Boosting is a supervised learning algorithm that excels in both regression and classification tasks Its success lies in its ability to combine predictions from multiple weak models forming a robust ensemble XGBoost s strength stems from its adaptability to various data types and complex distributions This makes it a suitable choice for cardiovascular prediction where the dataset is often diverse and intricate Additionally XGBoost offers a multitude of hyperparameters that can be tuned to enhance the model s performance and fit With XGBoost the Cardio Vascular Prediction solution can effectively identify fraudulent transactions by calculating the probability of fraud based on transaction features By leveraging ensemble techniques like bagging and boosting XGBoost combines a group of relatively average models to create a potent algorithm This approach is analogous to a powerful random forest algorithm where multiple decision trees collaborate to achieve superior results Ensemble techniques such as bagging and boosting enable the solution to reduce variance mitigate overfitting and enhance the model s robustness Similar to a group of blind men describing an elephant each contributing their unique perspective the collaboration of models in the ensemble brings diverse experiences and backgrounds to solve the prediction problem resulting in more accurate and reliable outcomes By leveraging the immense capabilities of XGBoost the Cardio Vascular Prediction solution on AWS ensures high quality predictions while considering the complexity and diversity of cardiovascular data Model Performance Assessment Confusion Matrix A confusion matrix is a valuable tool for evaluating the performance of a classification model It provides a comprehensive view of how well the model predicts the classes of the data The matrix consists of four elements True positives TP These are the cases in which the classifier correctly predicted the positive class e g a patient having a disease and the actual class was indeed positive True negatives TN These are the cases in which the classifier accurately predicted the negative class e g a patient without a disease and the actual class was indeed negative False positives FP Type I error These occur when the classifier incorrectly predicted the positive class indicating that a patient has the disease but the actual class was negative e g a false alarm or a patient wrongly identified as having the disease False negatives FN Type II error These occur when the classifier incorrectly predicted the negative class suggesting that a patient does not have the disease while the actual class was positive e g a failure to identify a patient who actually has the disease By analyzing the values in the confusion matrix we can assess the model s performance identify areas where it excels and pinpoint potential weaknesses This information enables us to fine tune the model optimize its accuracy and ensure reliable predictions in real world scenarios Architecture ExplanationThe proposed solution is an intelligent health monitoring system that utilizes various AWS services and the OpenAI platform to analyze input data and provide valuable insights to end users The system incorporates data from multiple sources including objective and subjective features to predict the presence or absence of cardiovascular disease The system follows a series of stages involving API Gateway AWS Lambda AWS Sagemaker and OpenAI endpoints to process and deliver the final response to the end user Stage Input ProcessingThe system begins by receiving input data through the API Gateway The input data consists of various features related to an individual s health such as age height weight gender blood pressure cholesterol level glucose level smoking habits alcohol intake physical activity and the presence or absence of cardiovascular disease This data is passed to the AWS Lambda function for further processing Stage AWS Lambda FunctionIn this stage the AWS Lambda function receives the input data from the API Gateway The Lambda function acts as the central processing unit extracting the relevant information from the input and performing any necessary data transformations or validations The extracted data is prepared for further analysis and passed on to the next stage Stage AWS Sagemaker EndpointAfter preprocessing the data the Lambda function invokes the AWS Sagemaker endpoint Sagemaker is a fully managed machine learning service provided by AWS The endpoint is responsible for deploying and running the machine learning model that predicts the presence or absence of cardiovascular disease The processed data is sent to the Sagemaker endpoint for inference Stage Sagemaker Endpoint ResponseThe Sagemaker endpoint performs inference using the deployed machine learning model and returns the prediction results back to the Lambda function The results include a raw output that indicates the likelihood of the presence or absence of cardiovascular disease based on the input data The Lambda function receives this output for further processing Stage OpenAI EndpointIn this stage the Lambda function utilizes the OpenAI platform to enhance the raw output received from the Sagemaker endpoint OpenAI is an AI powered platform capable of generating human like text The Lambda function sends the raw output to the OpenAI endpoint for further analysis and processing Stage OpenAI Response and API GatewayThe OpenAI endpoint processes the raw output and generates a processed and curated response This response contains valuable insights and explanations regarding the prediction of cardiovascular disease The Lambda function receives the processed output from OpenAI and prepares it to be served back to the end user Finally the processed output is returned via the API Gateway as a response to the end user providing them with valuable health related information based on the input data Outcomes Learnings and Best Practices Learned in the ProcessToday AI is no longer solely about writing elite code With the availability of large pre trained models and numerous developed technologies AI has become a journey towards solving meaningful challenges and building something together In this pursuit we as technical builders at heart are passionate about problem solving and are driven by the desire to make a real difference During our exploration we came across a startling fact every year more people lose their lives to heart diseases than even to cancer and epidemics combined What makes this even more tragic is that most of these deaths are preventable This realization presented us with an opportunity to have a tangible impact on the lives of countless individuals Throughout our journey we ve come to understand a crucial lesson there is an abundance of architectures and solutions available today It s incredibly easy to get side tracked and lose sight of what truly matters Therefore we made a conscious decision to stay laser focused on what will ultimately help us achieve our goal of saving lives We carefully considered various options and weighed their significance By narrowing down our focus we ensured that our efforts are directed towards solutions that directly address the problem at hand Our commitment to making a difference serves as our guiding principle guiding us towards the most effective paths In our quest to combat heart diseases and save lives we are determined to leverage the advancements in AI and technology By doing so we believe we can bring about substantial improvements in detection prevention and treatment Through collaboration innovation and unwavering dedication we are optimistic that we can make a significant impact and help save lives affected by heart diseases Examples of prompts and chatbot responsesNo riskHello Mary Sue Based on the information you provided I m glad to inform you that you are currently at a lower risk of heart disease Let s explore each factor that contributes to your positive health profile Age At years old you are at an age where heart diseases are less common However it s still important to maintain a healthy lifestyle to prevent future risks Gender Being female typically provides certain cardiovascular advantages resulting in a lower risk of heart disease compared to males Body Measurements Your height of m and weight of kg indicate a healthy body mass index BMI which suggests that you are within a desirable weight range Blood Pressure Your blood pressure readings of mmHg high low fall within the normal range indicating a healthy blood pressure level Cholesterol Levels Having low cholesterol levels implies that you have a decreased risk of plaque buildup in your arteries reducing the likelihood of heart disease Blood Glucose Level A normal blood glucose level indicates that you have a well regulated metabolism which contributes to a lower risk of heart disease Smoking Not smoking is a significant advantage since smoking is a major risk factor for heart disease Your decision to abstain from smoking protects your heart health Alcohol Consumption Avoiding alcohol consumption is beneficial as excessive alcohol intake can elevate blood pressure and increase the risk of heart disease Physical Activity Engaging in regular physical activity is excellent for heart health Your commitment to regular exercise strengthens the heart improves blood flow and lowers the risk of heart disease Given your positive health profile you are not currently at high risk for heart disease However it s still essential to maintain a healthy lifestyle including regular exercise a balanced diet and routine health check ups By prioritizing these aspects you can continue to safeguard your heart health and overall well being If you have any concerns or experience changes in your health it s always wise to consult a doctor for personalized guidance Keep up the good work in taking care of yourself Risk uneducated young userHello John Doe I m here to discuss an important matter related to your health Based on the information you provided there are several factors that indicate you may be at a high risk of heart disease Let s take a closer look at each risk factor Age Being years old doesn t guarantee protection against heart diseases While it s less common at a young age certain risk factors can still contribute to heart problems Gender Men like you have a higher risk of heart disease due to biological and lifestyle factors Body Measurements Your height of m and weight of kg indicate that your body mass index BMI is higher than the recommended range This suggests that you might be carrying excess weight which can strain your heart and increase the risk of heart disease Blood Pressure Your high blood pressure reading of and low blood pressure reading of are both concerning Consistently elevated or fluctuating blood pressure levels can damage your blood vessels putting you at a higher risk of heart disease Cholesterol Levels High cholesterol levels can lead to the buildup of plaque in your arteries restricting blood flow and increasing the risk of heart disease Blood Glucose Level High blood glucose levels suggest that you may have elevated blood sugar This can contribute to the development of diabetes which in turn increases the risk of heart disease Smoking Smoking is extremely harmful to your heart and blood vessels The chemicals in cigarettes damage the arteries increase blood pressure and elevate the risk of heart disease Alcohol Consumption Excessive alcohol consumption such as drinking several glasses per day can lead to high blood pressure irregular heart rhythms and other heart related problems Physical Inactivity Not engaging in regular physical activity puts you at a higher risk of heart disease Exercise helps maintain a healthy weight lower blood pressure and improve overall cardiovascular health Considering all these risk factors it is crucial for you to consult a doctor as soon as possible They can evaluate your health comprehensively conduct necessary tests and provide personalized guidance to manage and mitigate these risks effectively Taking proactive steps and seeking medical advice will greatly improve your chances of preventing heart disease Your health is important so please prioritize it by consulting a doctor promptly Risk experienced and adult userDear Mr John Doe based on the provided information I must emphasize that your current health profile places you at a significantly high risk of heart disease Allow me to elaborate on each risk factor and its potential detrimental effects Age At years old the risk of developing heart disease tends to increase due to the natural aging process and cumulative exposure to various risk factors over time Gender Being male you are more predisposed to heart diseases compared to females as hormonal and genetic factors contribute to a higher prevalence Body Measurements With a height of m and a weight of kg your body mass index BMI indicates that you are overweight Excessive weight puts strain on your heart and elevates the risk of cardiovascular complications Blood Pressure Your blood pressure readings of mmHg high low demonstrate hypertension a condition that burdens the heart and blood vessels potentially leading to heart disease stroke and organ damage Cholesterol Levels Elevated cholesterol levels especially if your low density lipoprotein LDL cholesterol is high promote the deposition of fatty plaques in arterial walls obstructing blood flow and heightening the likelihood of heart diseases Blood Glucose Level High blood glucose levels suggest impaired glucose regulation potentially indicating diabetes or prediabetes Elevated blood sugar levels contribute to the development of atherosclerosis increasing the risk of heart disease Smoking Smoking is a significant risk factor that damages the inner lining of blood vessels accelerates the formation of arterial plaques and raises blood pressure significantly increasing the likelihood of heart disease Alcohol Consumption Consuming several glasses of alcohol per day contributes to high blood pressure irregular heart rhythms and weakening of heart muscles augmenting the risk of heart diseases Physical Inactivity The absence of regular physical activity reduces cardiovascular fitness weakens the heart muscle and impairs overall heart health increasing the susceptibility to heart diseases Considering these multiple risk factors I strongly urge you to promptly consult a doctor Medical professionals can assess your specific circumstances conduct comprehensive evaluations and develop a personalized plan to manage and mitigate these risks By taking proactive measures and seeking professional guidance you can significantly improve your cardiovascular health and reduce the chances of heart disease Your well being is paramount so please prioritize your health and seek medical attention without delay ConclusionThe intelligent health monitoring system described above utilizes AWS services such as API Gateway Lambda and Sagemaker along with the OpenAI platform to process input data and deliver valuable insights to end users By leveraging machine learning and natural language processing capabilities the system can predict the presence or absence of cardiovascular disease and provide detailed explanations for the prediction This solution enables users to monitor their health more effectively and make informed decisions regarding their well being Next StepsWe ll build the front end to consume the model support all major platforms and sources of input like Apple Health and other integrations to make this completely automatic with less need for the user to answer the chatbot manually The less work from the user the higher the adoption rate We want to save lives so it s critical we make it easy Later on we may create APIs for medics and labs to read and write provided regulatory compliance We ll also train the model to add fine grained information on different heart diseases This Blog post was Co Authored byErmanno AttardoWebsite www ermannoattardo comGovind KumarWebsite www elngovind comGithub Link	2023-06-30 17:32:41
海外TECH	DEV Community	Bank Account Summary II | LeetCode | MSSQL	https://dev.to/ranggakd/bank-account-summary-ii-leetcode-mssql-1ema	Bank Account Summary II LeetCode MSSQL The ProblemTable UsersColumn NameTypeaccountintnamevarcharaccount is the primary key for this table Each row of this table contains the account number of each user in the bank There will be no two users having the same name in the table Table TransactionsColumn NameTypetrans idintaccountintamountinttransacted ondatetrans id is the primary key for this table Each row of this table contains all changes made to all accounts amount is positive if the user received money and negative if they transferred money All accounts start with a balance of Problem Write an SQL query to report the name and balance of users with a balance higher than The balance of an account is equal to the sum of the amounts of all transactions involving that account Sample Input and OutputUsers table accountnameAliceBobCharlieTransactions table trans idaccountamounttransacted on Output namebalanceAliceExplanation Alice s balance is Bob s balance is Charlie s balance is The SolutionWe present three different SQL queries to solve the problem Each of them uses different SQL concepts like aggregate functions subqueries and Common Table Expressions CTE Source Code This code is the simplest It joins Users with Transactions on account groups by name and sums the amount for each group The HAVING clause filters out the groups with a balance not greater than SELECT u name SUM t amount balance FROM Users u JOIN Transactions t ON u account t accountGROUP BY u nameHAVING SUM t amount gt The runtime of this code is ms beating of submissions Source Code This code uses window function SUM OVER PARTITION BY u name to calculate the balance for each user Then it filters the users with balance greater than SELECT name balanceFROM SELECT DISTINCT u name SUM t amount OVER PARTITION BY u name balance FROM Users u JOIN Transactions t ON u account t account aWHERE balance gt This code runs in ms beating of submissions Source Code This code does the same as Source Code but with a CTE to improve readability WITH result AS SELECT DISTINCT u name SUM t amount OVER PARTITION BY u name balance FROM Users u JOIN Transactions t ON u account t account SELECT name balanceFROM resultWHERE balance gt The runtime of this code is ms beating of submissions ConclusionThese solutions illustrate different approaches to the problem However based on the LeetCode metrics the first solution seems to be the most efficient likely because it doesn t rely on window functions which could add overhead in certain SQL engines From best to worst in terms of LeetCode performance we rank the solutions as follows Source Code Source Code Source Code Please note the performance on LeetCode might not always translate directly to performance in a real world RDBMS Factors such as database engine optimizations hardware and the distribution of data can affect performance in ways that may not be reflected in these rankings You can find the original problem at LeetCode For more insightful solutions and tech related content feel free to connect with me on my Beacons page ranggakd Link in Bio amp Creator Tools Beacons ranggakd center details summary summary Oh hello there I m a an Programmer AI Tech Writer Data Practitioner Statistics Math Addict Open Source Contributor Quantum Computing Enthusiast details center beacons ai	2023-06-30 17:01:00
Apple	AppleInsider - Frontpage News	How to automatically delete two-factor authentication codes in iOS 17	https://appleinsider.com/inside/ios-17/tips/how-to-automatically-delete-two-factor-authentication-codes-in-ios-17?utm_medium=rss	How to automatically delete two factor authentication codes in iOS The Messages and Mail apps on iOS can quickly become cluttered with SMS codes for two factor authentication but iOS can automatically delete them Here s where to find it SMS codes in Messages and MailSMS two factor authentication SMS FA is a security mechanism that provides protection to online accounts and services It involves using a user s mobile phone number to verify their identity during the login process Read more	2023-06-30 17:24:03
海外TECH	Engadget	Sega's COO says the company is not for sale	https://www.engadget.com/segas-coo-says-the-company-is-not-for-sale-174334550.html?src=rss	Sega x s COO says the company is not for saleSega is not for sale according to company COO Shuji Utsumi The executive told Bloomberg News that the company isn t open to acquisition talks at the moment despite rampant speculation that Microsoft was about to swoop in and force a shotgun wedding between Sonic and Master Chief Some of these rumors popped up due to a general consolidation trend in the gaming industry with big fish gobbling up everything in sight Microsoft s one of the biggest fish of all and it s been many years since Sega sat on top of the gaming throne despite remaining a solid developer and publisher Also a potential merger between Microsoft and Activision Blizzard led to the FTC filing an antitrust lawsuit which is ongoing During the associated trial it was revealed that Microsoft had many companies on its wishlist including Sega So the rumor mill continued unabated Utsumi declined to comment as to whether or not Microsoft approached Sega with an acquisition offer but touted the “great relationship between the two companies This relationship has been on full display in recent years with former Playstation exclusives from the Yakuza series to the Persona series showing up on Xbox consoles A next gen refresh of Yakuza Like a Dragon was even an Xbox Series X S exclusive for a few months before going multi platform The budding corporate friendship aww is extremely important to Microsoft as Sega titles are popular in Japan and well Xbox consoles aren t This is another reason the acquisition rumors spread so readily However Sega will remain as Sega Sammy Holdings for the time being even if documents indicate that Microsoft was at one point ready to fork over serious cash to buy the house that Sonic built Speaking of there s a new sidescrolling Sonic title launching later this year along with a new sidescrolling Mario What is this This article originally appeared on Engadget at	2023-06-30 17:43:34
海外TECH	CodeProject Latest Articles	Git – 4 ways to ignore files	https://www.codeproject.com/Articles/5363864/Git-4-ways-to-ignore-files	solution	2023-06-30 17:53:00
海外科学	NYT > Science	Climate Change Is Common Thread for Heat and Smoke Crises	https://www.nytimes.com/2023/06/28/climate/heat-smoke-climate-change.html	catastrophic	2023-06-30 17:56:39
金融	金融庁ホームページ	「サステナブルファイナンス有識者会議第三次報告書」を公表しました。	https://www.fsa.go.jp/news/r4/singi/20230630.html	有識者会議	2023-06-30 18:00:00
金融	金融庁ホームページ	「インパクト投資等に関する検討会報告書」について公表しました。	https://www.fsa.go.jp/news/r4/singi/20230630_2.html	検討会	2023-06-30 18:00:00
金融	金融庁ホームページ	「インパクト投資に関する基本的指針（案）」への意見募集について公表しました。	https://www.fsa.go.jp/news/r4/singi/20230630_3.html	意見募集	2023-06-30 18:00:00
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ニュース	BBC News - Home	Austrian Grand Prix 2023: Max Verstappen on pole ahead of Charles Leclerc	https://www.bbc.co.uk/sport/formula1/66067724?at_medium=RSS&at_campaign=KARANGA	Austrian Grand Prix Max Verstappen on pole ahead of Charles LeclercMax Verstappen takes a comfortable pole position from Ferrari s Charles Leclerc at his Red Bull team s home race the Austrian Grand Prix	2023-06-30 17:01:56
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ニュース	BBC News - Home	France shooting: Who was Nahel M, shot by French police in Nanterre?	https://www.bbc.co.uk/news/world-europe-66052104?at_medium=RSS&at_campaign=KARANGA	paris	2023-06-30 17:44:46
ビジネス	ダイヤモンド・オンライン - 新着記事	同性婚巡る業務拒否、米最高裁が認める判決 - WSJ発	https://diamond.jp/articles/-/325493	業務	2023-07-01 02:22:00