投稿時間:2022-12-15 06:24:25 RSSフィード2022-12-15 06:00 分まとめ(30件)

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IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] LINEで業務連絡、私用PCで仕事──悪気ない「シャドーIT」をどう防ぐか？	https://www.itmedia.co.jp/business/articles/2212/09/news153.html	itmedia	2022-12-15 05:30:00
AWS	AWS Partner Network (APN) Blog	Create Dynamic Serverless Applications with Neo4j Graph Database and AWS Lambda	https://aws.amazon.com/blogs/apn/create-dynamic-serverless-applications-with-neo4j-graph-database-and-aws-lambda/	Create Dynamic Serverless Applications with Neoj Graph Database and AWS LambdaThe AWS Cloud Development Kit AWS CDK is a framework that provides an automated and repeatable way of handling cloud infrastructure Learn how to use the AWS CDK to build an AWS Lambda function in Java that connects to Neoj The framework described here can be used to build dynamic serverless applications where the frontend scales based on system demand This makes it possible to easily get value from your connected graph data in front end applications	2022-12-14 20:36:53
AWS	AWS Big Data Blog	Migrate Google BigQuery to Amazon Redshift using AWS Schema Conversion tool (SCT)	https://aws.amazon.com/blogs/big-data/migrate-google-bigquery-to-amazon-redshift-using-aws-schema-conversion-tool-sct/	Migrate Google BigQuery to Amazon Redshift using AWS Schema Conversion tool SCT Amazon Redshift is a fast fully managed petabyte scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads Using Amazon Redshift Serverless and Query Editor v you can load and query large datasets in just a few clicks and pay only for what you use The decoupled compute and …	2022-12-14 20:15:18
AWS	AWS Big Data Blog	Create, Train and Deploy Multi Layer Perceptron (MLP) models using Amazon Redshift ML	https://aws.amazon.com/blogs/big-data/create-train-and-deploy-multi-layer-perceptron-mlp-models-using-amazon-redshift-ml/	Create Train and Deploy Multi Layer Perceptron MLP models using Amazon Redshift MLAmazon Redshift is a fully managed and petabyte scale cloud data warehouse which is being used by tens of thousands of customers to process exabytes of data every day to power their analytics workloads Amazon Redshift comes with a feature called Amazon Redshift ML which puts the power of machine learning in the hands of every …	2022-12-14 20:03:56
AWS	AWS Database Blog	How Amazon Finance Technologies simplified global payments by creating a payments repository using Amazon DocumentDB	https://aws.amazon.com/blogs/database/how-amazon-finance-technologies-simplified-global-payments-by-creating-a-payments-repository-using-amazon-documentdb/	How Amazon Finance Technologies simplified global payments by creating a payments repository using Amazon DocumentDBAmazon Finance Technologies FinTech Payments systems disburse Accounts Payable AP payments to Amazon s suppliers and service providers In FinTech AP systems disbursed millions of payments in over countries and in more than currencies through various payment options In this post we show you how we built an extensible payments metadata repository solution …	2022-12-14 20:15:51
AWS	AWS Database Blog	Partition existing tables using native commands in Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL	https://aws.amazon.com/blogs/database/partition-existing-tables-using-native-commands-in-amazon-rds-for-postgresql-and-amazon-aurora-postgresql/	Partition existing tables using native commands in Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQLCustomers use Amazon Relational Database Service Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL Compatible Edition for hosting their Online Transaction Processing OLTP database workloads Considering the scale at which today s applications operate databases can grow to hundreds of terabytes in a very short span of time Databases grow in size because the majority share of …	2022-12-14 20:03:29
AWS	AWS Government, Education, and Nonprofits Blog	How US federal agencies can apply TIC 3.0 to AWS workloads	https://aws.amazon.com/blogs/publicsector/how-us-federal-agencies-can-apply-tic-3-0-to-aws-workloads/	How US federal agencies can apply TIC to AWS workloadsThis blog post introduces Amazon Web Services AWS Trusted Internet Connections TIC overlay artifacts TIC is a federal cybersecurity initiative intended to enhance network and data security across the Federal Government	2022-12-14 20:43:57
AWS	AWS	Join Data from CDC and Streaming Sources to Enhance Analytics | Amazon Web Services	https://www.youtube.com/watch?v=zX-OQrWxHfQ	Join Data from CDC and Streaming Sources to Enhance Analytics Amazon Web ServicesIn this video you ll see how to join data from Change Data Capture CDC and streaming sources to enhance analytics Using Amazon Kinesis Data Analytics for Apache Flink you can create a Studio notebook for interactive data analytics query CDC data from a relational database and use JOIN queries to enrich CDC data with streaming data For more information on this topic please visit the resource s below Subscribe More AWS videos More AWS events videos 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 cdc streaming analytics join kinesis flink AWS AmazonWebServices CloudComputing	2022-12-14 20:41:26
js	JavaScriptタグが付けられた新着投稿 - Qiita	【個人開発】絵本を検索して図書館で「貸出可能」か確認できるサービスを作ってみた	https://qiita.com/zakirun/items/2cf035a74db6646928d6	rubyonrails	2022-12-15 05:06:43
Ruby	Rubyタグが付けられた新着投稿 - Qiita	【個人開発】絵本を検索して図書館で「貸出可能」か確認できるサービスを作ってみた	https://qiita.com/zakirun/items/2cf035a74db6646928d6	rubyonrails	2022-12-15 05:06:43
Ruby	Railsタグが付けられた新着投稿 - Qiita	【個人開発】絵本を検索して図書館で「貸出可能」か確認できるサービスを作ってみた	https://qiita.com/zakirun/items/2cf035a74db6646928d6	rubyonrails	2022-12-15 05:06:43
海外TECH	Ars Technica	Scientists discover a new supergroup of rare single-celled predators	https://arstechnica.com/?p=1904474	microbes	2022-12-14 20:09:35
海外TECH	DEV Community	Intrinsic motivation models	https://dev.to/aismagulov/intrinsic-motivation-1ja8	Intrinsic motivation modelsLet s look at modern motivation theories particularly intrinsic motivation Extrinsic motivation reward and punishmentMotivation systems distinguish extrinsic and intrinsic motivating factors At the workplace the most common extrinsic motivators are reward and punishment carrots and sticks Until recently they were the default approach to people management As Peter from Office Space brilliantly describes it Now if I work my ass off and Initech ships a few extra units I don t see another dime So where s the motivation …And here s another thing when I make a mistake I have eight different people coming by to tell me about it That s my real motivation is not to be hassled That and the fear of losing my job but y know Bob it will only make someone work hard enough not to get fired Notice how Peter is depicted as motivated only by money or being hassled fired Intrinsic motivation RAMP modelBut researchers also noticed that people voluntarily partake in activities that don t provide any reward playing games solving puzzles tackling challenges Something inside us makes us do that these are the intrinsic motivation factors Two models are mentioned the most frequently in my social network bubble The first one is the Theory of Self Determination SDT by Deci and Ryan It lists three core motivators Autonomy the feeling of having choice and control over your actions and decisions Relatedness the need to feel connected to others to belong to a group Competence being an expert being effective at what you do Another popular theory is the Drive model by Daniel Pink Its core components are Autonomy same as in SDT Mastery corresponds to Competence in SDT and Purpose knowing why you do what you do Since there is a noticeable overlap there is a third model created from the previous two called RAMP an abbreviation for Relationships Autonomy Mastery and Purpose If I understand correctly the model was created by A Human Workplace For example mission command approach contains all four RAMP components Extrinsic motivators suppress the intrinsic onesIn the book Drive Daniel Pink describes an experiment where one group of children were promised a reward for drawing pictures and others just drew because they enjoyed it After the experiment the children in the first group showed less interest in drawing later It turns out an extrinsic motivator can deplete the intrinsic ones In life once you attempt to motivate with a reward or a threat there is a spike of motivation that rapidly depletes To maintain it you must provide bigger rewards or increasingly scarier threats Otherwise you end up with highly demotivated people Here is a talk by Andrzej Marczewski from the Gamification Europe conference the second case he describes is how an extrinsic reward ruined a system with built in intrinsic motivation A notable quote What you must not do and you really must not do is to offer a reward Using motivation modelsOne way to apply a motivation model is to define the driving motivating factor for every team member It sounds a bit troublesome so I use it as a checklist for detecting gaps Do people feel like a team that moves towards a common goal Is the objective clear enough Does everyone have a chance to express their opinion Can people decide how to do their work Can they choose how to contribute And to summarize with another popular saying that I like You don t need to motivate people ーinstead remove what demotivates them Cover photo by Todd Diemer on Unsplash	2022-12-14 20:20:41
海外TECH	DEV Community	Why we ditched GraphQL for tRPC	https://dev.to/alexanderson1993/why-we-ditched-graphql-for-trpc-8c4	Why we ditched GraphQL for tRPCAt Echobind we re committed to building the best software we can for our clients As we choose our technology stack we have to balance a number of tradeoffs including stability flexibility scalability and the speed of development We wrap our favorite tools in a starter repository we call Bison We adopted GraphQL in Bison to give our apps end to end type checking with type safety from the database all the way to the UI It s served us well and has been the API layer for dozens of apps developed by Echobind We re always looking for ways to improve our processes so when we noticed tRPC starting to become popular we decided we would take a look What we saw impressed us so we ve decided to adopt tRPC as the official API layer for Bison We ve made the change to tRPC in the canary branch which means it isn t fully released yet If you want to see what it took to make this migration in Bison take a look at this commit What is tRPC tRPC and GraphQL serve the same purpose Getting data from the server to the client GraphQL is a specification which allows the client to request specific data which the server resolves into a response with just the fields that were requested tRPC on the other hand lets the client call server defined procedures passing along any relevant inputs and getting back a response Inputs are type checked at runtime using validator libraries like Zod and the types of the procedures are inferred from the server to the client While you can make direct fetch calls to tRPC s API it includes a wrapper around React Query a caching layer that provides an excellent user and developer experience Both GraphQL and tRPC are perfectly compatible with React and React Native and have first party client side library support Both support end to end type checking with GraphQL requiring a codegen step And both are fast enough for our purposes Here s what that looks like in practice with mostly equivalent examples for both GraphQL and tRPC First let s look at GraphQL both defining the resolver and fetching on the client excluding any generated code On the serverexport const User objectType name User description A User definition t t nonNull id id t nonNull date createdAt t nonNull date updatedAt t nonNull list nonNull field roles type Role Show email as null for unauthorized users t string email resolve profile args ctx gt canAccess profile ctx profile email null export const UserRole enumType name Role members Object values Role export const UserWhereUniqueInput inputObjectType name UserWhereUniqueInput description Input to find users based on unique fields definition t t id id t string email export const findUniqueUserQuery queryField user type User args where nonNull arg type UserWhereUniqueInput resolve async root args ctx gt return await ctx db user findUnique where prismaArgObject args where On the clientexport const QUERY gql query User id ID user id id name export const UserCell userId userId string gt const data loading error useUserQuery variables where id userId And then the same but using tRPC instead On the serverexport const defaultUserSelect Prisma validator lt Prisma UserSelect gt id true email true createdAt true updatedAt true roles true profile select firstName true lastName true export const userRouter t router find t procedure input z object id z string optional email z string optional query async ctx input gt const user await ctx db user findUniqueOrThrow where input select defaultUserSelect if isAdmin ctx user amp amp user id ctx user id return user email null return user On the clientexport const UserCell userId userId string gt const data loading error trpc user find useQuery id userId The difference between these two examples highlights the initial reason we switched from GraphQL to tRPC Less BoilerplateYou ll notice in the code samples above tRPC is able to do the same work with much fewer lines of code In fact when we migrated Bison to tRPC we added lines of code while removing  a net change of lines of code This is partially because GraphQL famously has the “Double declaration problem there s a lot of repeating yourself especially if you re using TypeScript Tools like GraphQL codegen help with this but it s still a lot Define the database schema Prisma Define the API schema Nexus Write a GraphQL Operation gql Define the response type definition GraphQL codegen Define the query Apollo Client tRPC trims this down significantly Define the database schema Prisma Define the procedure tRPC router Define the query tRPC client React Query The simplicity speaks for itself Avoiding Code GenerationIn both cases we can achieve end to end type safety which is table stakes for our apps but the method of achieving this type safety is much more complicated with GraphQL requiring three layers of code generation Prisma generates types from our database schema Nexus generates types from our database schema GraphQL Codegen generates frontend types and React hooks from our GraphQL request definitions This code generation doesn t come without its consequences For one app we built at Echobind Nexus generates a line type file while GraphQL codegen generates an dense type file All of that takes a long time for the type checker to parse and check both when running tsc and in VSCode We often need to restart our VSCode language server because it gets bogged down with all of the type checking it has to do tRPC instead relies on one very large assumption Your server is written in TypeScript and is colocated with the client code tRPC has you define a server side router for your procedures then export the type of that which Typescript automatically infers and then import that type to be used on the client side Since types are automatically removed when Typescript code is compiled there is no extra code added to the client bundle and no extra types to slow down the type checker Just type safety Client Bundle SizeIt s no secret the less JavaScript you ship to your users the better their experience will be To build great software you need some JavaScript but if an alternative comes along that uses less JavaScript it s worth a second look Let s compare the client side dependencies needed for both approaches These numbers were calculated by putting the packages through bundlephobia com and tracking the “minified gzip sizes GraphQLtRPC apollo client kb trpc client kbapollo upload client kb trpc react query kbgraphql kb tanstack react query kb trpc next kbTOTAL kbTOTAL kbThe GraphQL bundle is almost times the size of tRPC which means that much more loading time for sites that use it As an aside we could still get the bundle size savings while using GraphQL by combining React Query with a GraphQL request library like the conveniently named graphql request kb React Query amp Cache ManagementA frequent bug we ve run into building with Apollo Client has to do with updating the cache after a mutation If you create your queries right and if your mutations return the correct data mutations are supposed to automatically update its fancy normalized cache But that s rarely how it works out in practice This could be a classic case of “you re holding it wrong except it s not clear what the correct solution is Do we need to use refetchQueries That gets kind of messy depending on which variables are being used for the query Maybe we should use writeQuery or writeFragment That has the same pitfalls plus we have to write a bunch of extra code to surgically alter the cache It shouldn t be this hard to keep the cache up to date after a request It s impossible to overstate how many nice things React Query provides out of the box Compared to Apollo Client s incredibly complicated normalized cache React Query is a walk in the park tRPC simplifies it further by keying the cache entries to each procedure Triggering a refetch is as easy as running utils user find invalidate id user id Along with it comes easy mutation handling simple patterns for optimistic updates along with rollbacks in case there are errors and heuristics for automatically refetching data so it stays fresh Combined with tRPC s type safety React Query is the most delightful way to fetch data on the client IDE ImprovementsThe methods tRPC uses for type checking have some surprising and convenient side effects Since the frontend queries are type checked based on the backend procedures VS Code s “Go To Definition feature works across the network boundary I can click on a procedure definition in a client side file and it will take me right to where that procedure is defined on the server side It gets better Not only can we jump to the file if we use VS Codes “Rename All Instances on an input or procedure name those changes also propagate between the server and client Even with the fancy GraphQL codegen this just isn t possible with the way GraphQL works Having these tools right in the IDE is a huge win for convenience and productivity What did we lose Very rarely does a major change like this not have downsides and leaving GraphQL is no exception As we ve made the jump there are a handful of things GraphQL provided for free that require a bit more effort using tRPC Field RequestsThe most obvious is that the client doesn t get to pick which fields it fetches whereas GraphQL allows the client to define exactly the fields it wants for any request There are two workarounds First a tRPC procedure could be defined with an input where the client can request certain fields This might take a bit of finagling to get the input and output types to line up but would provide a similar experience to GraphQL However I think a better option is to embrace the simplicity of having the client accept whatever the server returns In my experience over fetching is not as big of a problem as many people make it out to be If there is a particular procedure that returns far too much or not enough data there s nothing wrong with creating a second procedure that returns data more closely scoped to what the client needs Field ResolversAnother huge benefit of GraphQL is the ability to create custom resolvers on a field by field basis The default is to just pass through whatever value the parent resolver provided for that field but GraphQL makes it really easy to combine and transform fields even using arguments from the request as part of the transformation Common examples include a virtual fullName field which combines the firstName and lastName fields or a date field which lets the user choose what format they want for the date This is another case where tRPC can get around the limitation either by using an input or creating a new procedure to provide the transformed data Probably my biggest lesson in using tRPC Creating a new procedure is cheap So long as they are named well having many procedures is not a bad thing Introspection and DocumentationGraphQL is famous for its self documenting API As part of the spec GraphQL servers can publish an introspection query which lets anyone see what objects queries and mutations the server supports It s great for visibility and learning what the API supports tRPC has no such introspection query In fact it isn t great for creating a public facing API The types themselves work great for building first party apps but if you want to open your API up to third parties you ll have to create your own documentation There is an OpenAPI Extension for tRPC that can be used to create a more REST like API from your procedures and that in turn can be used for auto generating documentation But if my app needed to offer third party API access I would likely reach for GraphQL again Colocated TypeScript OnlyOne of the best things about GraphQL is that it isn t actually a technology it s just a specification That means anyone can create a GraphQL server or in any language So long as it matches the spec it will work across whatever platform it s used on whether it be Ruby JavaScript Elixir or Python That s part of the reason GraphQL codegen is so valuable It allows schema definitions and types to be generated regardless of the backend that hosts the GraphQL server The same can t be said for tRPC Its type checking only works if the server is written in TypeScript since the client needs those TypeScript types to enjoy its type safety It s possible in the future that servers that implement the tRPC HTTP spec could be written in other languages but they would require a codegen process to make the proper types available to the client And if your tRPC server is located in a different repository you ll have to figure out a way to get the generated types into your client app to enjoy the type safety tRPC works best when the client and server are either part of the same app like with Next js or part of a monorepo ConclusiontRPC has proven to be exactly the tool that Echobind needs for building our client s apps GraphQL may be powerful and capable but the boilerplate and complexity it requires often slows us down and makes it difficult to build robust responsive sites With tRPC we hope to double down on our commitment to building the best possible software we can for ourselves and our clients	2022-12-14 20:07:00
Apple	AppleInsider - Frontpage News	Some Apple HomeKit setups are breaking after iOS 16.2 update	https://appleinsider.com/articles/22/12/14/some-apple-homekit-setups-are-breaking-after-ios-162-update?utm_medium=rss	Some Apple HomeKit setups are breaking after iOS updateApple HomeKit users can upgrade the underlying architecture of their Apple Home in iOS but it hasn t been a smooth transition for some Apple HomeKit has an architecture upgrade availableApple says that it has rebuilt the underlying architecture of HomeKit in iOS which translates to improved performance It is significant enough a change that users must jump through a few hoops to initiate the process Read more	2022-12-14 20:16:05
海外TECH	Engadget	Here's everything Sam Bankman-Fried is accused of by the US government	https://www.engadget.com/ftx-sam-bankman-fried-criminal-and-civil-charges-200410951.html?src=rss	Here x s everything Sam Bankman Fried is accused of by the US governmentOn Monday evening Bahamian authorities arrested FTX founder and former CEO Sam Bankman Fried at the request of the US government The following morning the Securities and Exchange Commission SEC Department of Justice DOJ and Commodity Futures Trading Commission CFTC filed formal civil and criminal charges against Bankman Fried in quot parallel actions quot It was a lot to take in all at once so below Engadget has broken up current charges against SBF by agency with some additional context provided Those indictments likely represent only the start of Bankman Fried s troubles In addition to the charges it announced on Tuesday the SEC said it was investigating Bankman Fried for other securities violations The agency also announced that it s actively examining the actions of other FTX executives and employees As more charges are unsealed Engadget will continue to update this article Securities and Exchange CommissionThe Securities and Exchange Commission accused SBF of defrauding FTX investors and customers of more than billion Starting as early as May until as recently as this past November quot Bankman Fried was orchestrating a massive years long fraud diverting billions of dollars of the trading platform s customers funds for his own personal benefit and to help grow his crypto empire quot the SEC said All the while Bankman Fried portrayed himself as a responsible business leader building a safe trading platform with quot sophisticated automated measures to protect customer assets quot In reality the SEC says quot Bankman Fried orchestrated a fraud to conceal the diversion of customer funds to his privately held crypto hedge fund Alameda Research quot Today we charged FTX Trading Ltd CEO and co founder Samuel Bankman Fried with orchestrating a scheme to defraud equity investors Investigations as to other securities law violations and into other entities and persons relating to the alleged misconduct are ongoing ーU S Securities and Exchange Commission SECGov December Bankman Fried told investors and customers FTX s sister company was just another platform on the exchange with no special privileges to speak of quot These statements were false and misleading quot according to the SEC Alameda had access to a quot virtually unlimited line of credit quot unknowingly funded by FTX customers In May when Alameda s lenders demanded the firm repay loans worth billions of dollars Bankman Fried allegedly directed FTX to divert even more money to the hedge fund The SEC seeks to bar Bankman Friend from trading securities in the future The agency also wants to seize his ill gotten gains and bar him from acting as an officer or director at another company Current FTX CEO John Ray III testified before the House Financial Services Committee on Tuesday ー SBF had said he would attend the hearing before his arrest Ray spoke to some of the allegations detailed by the SEC quot This is really old fashioned embezzlement quot he told the panel quot We ve lost billion I don t trust a single piece of paper in this organization quot Department of JusticeIn addition to civil charges Bankman Fried faces a criminal indictment from the Justice Department On Tuesday prosecutors from the Southern District of New York filed eight charges against the former executive including multiple counts of wire fraud The Justice Department alleges SBF conspired with other individuals to defraud investors by sharing misleading information about FTX and Alameda s financial condition Prosecutors further accused him of attempting to commit commodities and securities fraud On top of that Bankman Fried allegedly broke federal election laws by donating more than is legally allowed and in the names of other people Watch today s complete FTX hearing with CEO John Ray re airing at pm ET on C SPAN or anytime online here pic twitter com qmLfRVWiNーCSPAN cspan December SBF spoke about his political donations in a recent interview with journalist Tiffany Fong quot I donated to both parties I donated about the same amount to both parties quot he said quot All my Republican donations were dark The reason was not for regulatory reasons it s because reporters freak the fuck out if you donate to Republicans quot It s worth emphasizing how serious the criminal charges against Bankman Fried are For context a federal judge recently sentenced Theranos founder and former CEO Elizabeth Holmes to years in prison for defrauding the company s investors and patients Meanwhile Ramesh quot Sunny quot Balwani the startup s former chief operating officer was sentenced to nearly years in prison for his role in the scheme Sam Bankman Fried stands accused of defrauding investors of almost billion or about twice what investors lost to Theranos Commodity Futures Trading CommissionRounding out the current charges against Bankman Fried the Commodity Futures Trading Commission accused the former executive of using Alameda Research to quot surreptitiously quot siphon customer funds quot At Bankman Fried s direction FTX executives created features in the underlying code for FTX that allowed Alameda to maintain an essentially unlimited line of credit on FTX quot the regulator alleges It adds that Alameda had other quot unfair quot advantages including an exemption from the platform s auto liquidation risk management process AOC D NY questions new FTX CEO John Ray on timing of Sam Bankman Fried s arrest by the Bahamian government pic twitter com foxUpsitRーCSPAN cspan December As early as May SBF and quot at least one quot other Alameda executive directed the firm to use FTX customer funds to trade on competing platforms and buy quot high risk quot digital assets Additionally the CFTC alleges that Bankman Fried and his cohorts quot took hundreds of millions of dollars in poorly documented loans from Alameda quot which they then used to purchase real estate and make political donations For his actions the CFTC is seeking to ban Bankman Fried from trading derivatives and impose civil penalties against him It also wants to bar him from acting as a director or officer in the future	2022-12-14 20:04:10
海外科学	NYT > Science	Who Are the ‘Never-Coviders’?	https://www.nytimes.com/2022/12/14/briefing/never-covid.html	covid	2022-12-14 20:09:53
ビジネス	ダイヤモンド・オンライン - 新着記事	軽自動車も大学進学も今や「高級品」！データで見る日本社会と、停滞の“突破口” - 総予測2023	https://diamond.jp/articles/-/314492	大学進学	2022-12-15 05:25:00
ビジネス	ダイヤモンド・オンライン - 新着記事	紙・パルプ業界の苦境鮮明！25社の倒産危険度が5軸チャートで一目瞭然！金利上昇、インフレに弱いのは？ - 倒産危険度ランキング×インフレ・過剰債務で危ない725社	https://diamond.jp/articles/-/314188	紙・パルプ業界の苦境鮮明社の倒産危険度が軸チャートで一目瞭然金利上昇、インフレに弱いのは倒産危険度ランキング×インフレ・過剰債務で危ない社昨年から複数回にわたり値上げを試みている紙・パルプ業界。	2022-12-15 05:20:00
ビジネス	ダイヤモンド・オンライン - 新着記事	八方ふさがり日本経済の「特効薬」とは？気鋭の女性エコノミスト3人が激論！ - 総予測2023	https://diamond.jp/articles/-/314491	八方ふさがり	2022-12-15 05:15:00
ビジネス	ダイヤモンド・オンライン - 新着記事	日経平均3万6000円説も！2023年の株価をプロ9人が予測、投資戦略・注目テーマは？ - 総予測2023	https://diamond.jp/articles/-/314490	投資戦略	2022-12-15 05:10:00
ビジネス	ダイヤモンド・オンライン - 新着記事	暴君・JR東海と重工3社の愛憎劇…日立は蜜月、三菱重工は面従腹背、川崎重工は出禁 - 迷走 皇帝なきJR東海	https://diamond.jp/articles/-/314198	三菱重工	2022-12-15 05:05:00
ビジネス	電通報 | 広告業界動向とマーケティングのコラム・ニュース	商いとビジネスの、ほどよい関係	https://dentsu-ho.com/articles/8388	電通	2022-12-15 06:00:00
北海道	北海道新聞	米、０・５％利上げ決定　景気配慮で上げ幅縮小	https://www.hokkaido-np.co.jp/article/775186/	中央銀行	2022-12-15 05:52:41
北海道	北海道新聞	中国、医薬品入手困難に　コロナ流行、価格つり上げ	https://www.hokkaido-np.co.jp/article/775185/	新型コロナウイルス	2022-12-15 05:12:00
北海道	北海道新聞	＜社説＞防衛費の財源　増税も国債も理がない	https://www.hokkaido-np.co.jp/article/775152/	岸田文雄	2022-12-15 05:01:00
ビジネス	東洋経済オンライン	飲酒運転の被害者遺族｢人型パネル｣に救われた訳 母娘の軌跡から家族とグリーフケアを考える | 災害･事件･裁判 | 東洋経済オンライン	https://toyokeizai.net/articles/-/639428?utm_source=rss&utm_medium=http&utm_campaign=link_back	交通事故	2022-12-15 05:31:00
ビジネス	東洋経済オンライン	命奪われた被害者遺族が作る｢人型パネル｣の意味 年内閉館｢いのちのミュージアム｣が果たした役割 | 災害･事件･裁判 | 東洋経済オンライン	https://toyokeizai.net/articles/-/639422?utm_source=rss&utm_medium=http&utm_campaign=link_back	交通事故	2022-12-15 05:30:00
ビジネス	東洋経済オンライン	｢デジタルストーカー｣されてる人の衝撃の実態 離婚した元妻が位置情報をチェックしていた | スマホ・ガジェット | 東洋経済オンライン	https://toyokeizai.net/articles/-/638198?utm_source=rss&utm_medium=http&utm_campaign=link_back	位置情報	2022-12-15 05:25:00
Azure	Azure の更新情報	General availability: Yocto recipes for IoT Edge 1.4 LTS	https://azure.microsoft.com/ja-jp/updates/general-availability-yocto-recipes-for-iot-edge-14-lts/	availability	2022-12-14 20:04:33