投稿時間:2023-05-28 04:31:21 RSSフィード2023-05-28 04:00 分まとめ(33件)

カテゴリー等	サイト名等	記事タイトル・トレンドワード等	リンクURL	頻出ワード・要約等/検索ボリューム	登録日
IT	InfoQ	AI, ML & Data News Roundup: Generative Fill, Copilot, Aria, and Brain Chips	https://www.infoq.com/news/2023/05/ai-ml-data-news-may22-2023/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global	AI ML amp Data News Roundup Generative Fill Copilot Aria and Brain ChipsThe most recent update covering the week starting May nd encompasses the latest progress and declarations in the fields of data science machine learning and artificial intelligence This week the focus is on prominent figures such Adobe Microsoft Opera and the University of Lausanne By Daniel Dominguez	2023-05-27 18:08:00
技術ブログ	Developers.IO	[アップデート] Amazon Rekognition で顔写真の視線の方向（Eye Direction）を検出できるようになりました	https://dev.classmethod.jp/articles/amazon-rekognition-eyes-gaze-direction-detection-in-face-apis/	amazonrekognition	2023-05-27 18:10:14
海外TECH	MakeUseOf	What Is GNU/Linux and Why Does Hardly Anyone Call It That?	https://www.makeuseof.com/tag/hardly-anyone-calls-linux-gnulinux/	others	2023-05-27 18:30:18
海外TECH	MakeUseOf	How to Share Your Nintendo Switch Gameplay Online	https://www.makeuseof.com/tag/share-nintendo-switch-gameplay-online/	online	2023-05-27 18:15:18
海外TECH	DEV Community	Deep Neural Network from Scratch in Rust 🦀- Part 5- Training and Inference	https://dev.to/akshayballal/deep-neural-network-from-scratch-in-rust-part-5-training-and-inference-20k7	Deep Neural Network from Scratch in Rust Part Training and InferenceGreat You have made it to the final part of the series In this part we will train our model and test it by building a prediction function Luckily there is no math involved in this part So let s get coding TrainingFirst we are going to build our training loop which takes in the training data x train data training labels y train data the parameters dictionary parameters the number of training loop iterations iterations and the learning rate The function will return the new parameters after a training iteration In impl DeepNeuralNetwork add the following function pub fn train model amp self x train data amp Array lt f gt y train data amp Array lt f gt mut parameters HashMap lt String Array lt f gt gt iterations usize learning rate f gt HashMap lt String Array lt f gt gt let mut costs Vec lt f gt vec for i in iterations let al caches self forward amp x train data amp parameters let cost self cost amp al amp y train data let grads self backward amp al amp y train data caches parameters self update parameters amp parameters grads clone learning rate if i costs append amp mut vec cost println Epoch Cost i iterations cost parameters This function performs the following steps It initializes an empty vector called costs to store the cost values for each iteration It iterates over the specified number of iterations In each iteration It performs forward propagation using the forward method to obtain the final activation al and the caches It calculates the cost using the cost method It performs backward propagation using the backward method to compute the gradients It updates the parameters using the update parameters method with the computed gradients and the learning rate If the current iteration is a multiple of it appends the cost value to the costs vector and prints the current epoch number and cost value After the loop it returns the updated parameters PredictAfter the training loop is done we can make a predict function that takes in the test data x test data and the optimized parameters parameters pub fn predict amp self x test data amp Array lt f gt parameters HashMap lt String Array lt f gt gt gt Array lt f gt let al self forward amp x test data amp parameters let y hat al map x x gt amp as i as f y hat pub fn score amp self y hat amp Array lt f gt y test data amp Array lt f gt gt f let error y hat y test data map x x abs sum y test data shape as f error The predict function performs the following steps It calls the forward method with the test data and the optimized parameters to obtain the final activation al It applies a threshold of to the elements of al using the map method converting values greater than to and values less than or equal to to It returns the predicted labels as y hat The score function calculates the accuracy score of the predicted labels compared to the actual test labels It performs the following steps It calculates the element wise absolute difference between the predicted labels y hat and the actual test labels y test data It sums the absolute differences using the sum method It divides the sum by the number of examples y test data shape and multiplies by to get the error percentage It subtracts the error percentage from to get the accuracy score and returns it Some Helper functions Write Parameters to a JSON fileWe can define a helper function to write the trained model s parameters to a JSON file This allows us to save the parameters for later use without requiring retraining First in Cargo toml add this lineserde json Then in lib rs import OpenOptions and create the function lib rsuse std fs OpenOptions pub fn write parameters to json file parameters amp HashMap lt String Array lt f gt gt file path PathBuf let file OpenOptions new create true write true truncate true open file path unwrap serde json to writer file parameters This function takes in the parameters and a file path where the JSON file will be created It opens the file in write mode truncating any existing content Then it uses the serde json crate to serialize the parameters and write them to the file Application ExampleTo demonstrate the usage of the library we can create an application that loads the data trains the model and tests it We can create a file named rust dnn rs inside the src bin folder Here s an example implementation use dnn rust blog use std env fn main env set var RUST BACKTRACE let neural network layers Vec lt usize gt vec let learning rate let iterations let training data training labels dataframe from csv datasets training set csv into unwrap let test data test labels dataframe from csv datasets test set csv into unwrap let training data array array from dataframe amp training data let training labels array array from dataframe amp training labels let test data array array from dataframe amp test data let test labels array array from dataframe amp test labels let model DeepNeuralNetwork layers neural network layers learning rate let parameters model initialize parameters let parameters model train model amp training data array amp training labels array parameters iterations model learning rate write parameters to json file amp parameters model json into let training predictions model predict amp training data array amp parameters println Training Set Accuracy model score amp training predictions amp training labels array let test predictions model predict amp test data array amp parameters println Test Set Accuracy model score amp test predictions amp test labels array We set the neural network layers learning rate and number of iterations We load the training and test data from CSV files using the dataframe from csv function We convert the dataframes to arrays and normalize the pixel values to the range We create an instance of the DeepNeuralNetwork struct with the specified layers and learning rate We initialize the parameters using the initialize parameters method We train the model using the train model method passing in the training data training labels initial parameters iterations and learning rate We write the trained parameters to a JSON file using the write parameters to json file function We predict the labels for the training and test data using the predict method We calculate and print the accuracy scores for the training and test predictions using the score method Now in the terminal run the following command to install the binary and to run itcargo install path amp amp rust dnnThis will install the dependencies and start the training Wrap upAlthough the dataset used in our example was small and the network architecture was not complex the purpose of this series was to provide a general workflow and introduce the inner workings of a neural network With this foundation you can now expand and enhance the library to handle larger datasets more complex network architectures and additional features By building this neural network library in Rust we benefited from the language s safety performance and concurrency features Rust s strong type system and memory safety guarantees help prevent common bugs and ensure code correctness Additionally Rust s focus on efficiency and parallelism allows us to leverage multi threading and take advantage of modern hardware capabilities With this library you now have a powerful tool for developing neural network models in Rust You can further explore and experiment with different network architectures activation functions optimization techniques and regularization methods to improve the performance of your models As you continue your journey in machine learning and deep learning remember to stay curious keep exploring new concepts and techniques and leverage the rich Rust ecosystem to further enhance your neural network library GitHub Repository My Website Twitter‍LinkedIn	2023-05-27 18:42:42
海外TECH	DEV Community	RAID Explained	https://dev.to/pheianox/raid-explained-178f	RAID ExplainedRAID is an important concept in data storage and management It is a system that combines multiple hard drives into one logical unit resulting in better performance data redundancy and increased dependability  This blog post will break down RAID explain its various forms and assist you in making an informed decision when selecting the best RAID configuration for your individual needs What is RAID RAID stands for Redundant Array of Independent Disks It is a method of organizing multiple physical hard drives into a single logical unit to improve data storage performance reliability and availability By distributing or replicating data across multiple drives RAID offers improved read and write speeds as well as fault tolerance in the event of drive failures RAID technology finds applications in various sectors including enterprise IT environments server systems data centers and even personal computers It is particularly valuable in scenarios where high speed data access data protection and uninterrupted availability are crucial such as database servers file servers and video editing workstations There are several different RAID levels each offering specific features and benefits Let s dive into the most commonly used ones which are RAID RAID RAID RAID and RAID RAID RAID also known as striping distributes data across multiple drives allowing for enhanced performance It does not provide redundancy or fault tolerance as there is no data redundancy or mirroring RAID can be beneficial for applications that prioritize speed such as video editing or gaming However it carries a higher risk of data loss in the event of a drive failure ProsImproved performance due to data striping across multiple drives Ideal for applications that require high speed data access Cost effective as it utilizes the full capacity of all drives ConsNo data redundancy making it vulnerable to data loss If one drive fails the entire array is at risk Not recommended for critical data storage RAID RAID also known as mirroring involves creating an exact replica of data on two or more drives This provides data redundancy and high availability Every write operation is simultaneously performed on both drives ensuring that if one fails the other can take over seamlessly RAID is commonly used for storing important data such as operating system files and critical documents ProsData redundancy ensures high data availability and protection Quick recovery from drive failures Good read performance as data can be read from any of the mirrored drives ConsCostlier than RAID as it requires double the amount of storage Write performance is slower due to the need to duplicate data Inefficient use of drive capacity since half the total capacity is used for mirroring RAID RAID combines striping and parity to provide performance and redundancy Data is striped across multiple drives and parity information is distributed across the drives as well The parity information allows the system to reconstruct data in the event of a drive failure RAID requires a minimum of three drives to implement ProsOffers a good balance of performance and data redundancy Efficient use of storage capacity as parity is distributed across drives Can withstand the failure of a single drive without data loss ConsWrite performance can be impacted due to the need to calculate parity Rebuilding an array after a drive failure can be time consuming and resource intensive If multiple drives fail or develop bad sectors during the rebuild process data loss may occur RAID RAID is similar to RAID but it uses dual parity instead of single parity This means it can withstand the failure of two drives simultaneously without data loss RAID requires a minimum of four drives ProsProvides enhanced data protection compared to RAID by tolerating the failure of two drives Good balance of performance capacity and redundancy Reduces the risk of data loss during array rebuilds ConsWrite performance can be slower due to the additional parity calculations Requires more drives than RAID resulting in higher costs Rebuilding a failed array can take longer due to the dual parity calculations RAID RAID also known as RAID combines the features of RAID mirroring and RAID striping It provides both data redundancy and improved performance Data is mirrored across multiple pairs of drives and these pairs are then striped together RAID requires a minimum of four drives ProsExcellent performance due to data striping High data availability and quick recovery from drive failures Efficient use of storage capacity as only half the total capacity is used for mirroring ConsRequires a larger number of drives resulting in higher costs Less storage capacity available compared to RAID or RAID Rebuilding the array after a drive failure can be time consuming In certain situations even with the robustness of RAID unforeseen events can lead to data loss or RAID failures If you find yourself facing such a situation and in need of professional assistance to recover your valuable data there are specialized RAID recovery services available to help Remember it s always recommended to consult with professionals when dealing with data loss or RAID failures as they have the knowledge and tools required to handle complex recovery scenarios Which One To Choose Selecting the appropriate RAID configuration depends on your specific requirements and considerations When deciding on the RAID level it is crucial to take into account factors such as the importance of data redundancy performance needs available budget and capacity utilization By carefully evaluating these factors you can make an informed decision that aligns with your specific needs For non critical applications that prioritize speed and do not require data redundancy RAID can be a suitable choice RAID offers improved performance through data striping across multiple drives It is commonly utilized in scenarios such as video editing workstations or gaming setups where fast data access is essential However it s important to note that RAID does not provide data redundancy meaning that if one drive fails the entire array is at risk of data loss On the other hand if data redundancy and high availability are paramount RAID or RAID configurations should be considered RAID also known as mirroring creates an exact replica of data on two or more drives This redundancy ensures data availability even if one drive fails RAID is particularly suitable for storing critical data such as operating system files and essential documents However keep in mind that RAID utilizes half of the total capacity for mirroring resulting in a lower effective storage capacity and increased cost compared to RAID RAID combines the benefits of RAID and RAID It creates multiple mirrored sets of drives and then stripes data across them This configuration offers both data redundancy and improved performance RAID provides excellent read and write speeds and is well suited for applications that require high performance and data protection simultaneously While RAID requires a larger number of drives compared to RAID or RAID it ensures efficient utilization of storage capacity and provides quick recovery from drive failures For a balance between performance and redundancy RAID or RAID configurations are worth considering RAID utilizes data striping across multiple drives along with parity information distributed across the drives This allows the system to reconstruct data in case of a single drive failure RAID requires a minimum of three drives and provides a good balance between performance and data redundancy However it s important to note that the rebuild process after a drive failure can be resource intensive and time consuming RAID similar to RAID incorporates dual parity to provide an additional layer of fault tolerance This configuration can withstand the failure of two drives simultaneously without data loss RAID requires a minimum of four drives and offers enhanced data protection compared to RAID However similar to RAID the rebuild process can be time consuming due to the dual parity calculations Ultimately the choice of RAID configuration depends on your specific needs and priorities Assessing factors such as the level of data redundancy required performance expectations available budget and storage capacity utilization will guide you toward selecting the most suitable RAID level for your particular scenario ConclusionRAID technology is a powerful tool for enhancing data storage performance reliability and availability By understanding the different RAID levels and their advantages and disadvantages you can make an informed decision when choosing the appropriate RAID configuration for your specific needs Remember to consider factors such as performance requirements data redundancy cost and capacity utilization Whether you re setting up a personal computer or managing an enterprise level storage solution RAID can play a crucial role in ensuring the integrity and accessibility of your data	2023-05-27 18:24:49
海外TECH	DEV Community	Install tool easy by Toolbox	https://dev.to/milkcoke/install-tool-easy-by-toolbox-13o1	Install tool easy by ToolboxI developed desktop app for developersThis app will save your time from annoying downloading visiting web sites one by one You can get it free Toolbox for developers Preview Contact meFeel free to give us your opinion about the app	2023-05-27 18:03:34
海外TECH	Engadget	Twitter pulls out of EU’s voluntary Code of Practice against disinformation	https://www.engadget.com/twitter-pulls-out-of-eus-voluntary-code-of-practice-against-disinformation-183726045.html?src=rss	Twitter pulls out of EU s voluntary Code of Practice against disinformationTwitter has withdrawn from a voluntary European Union agreement to combat online disinformation In a tweet spotted by TechCrunch Thierry Breton the bloc s internal market commissioner said Twitter had pulled out of the EU s “Code of Practice against disinformation “You can run but you can t hide Our teams are ready for enforcement Breton said referring to the EU s Digital Services Act As of August th the DSA will require “very large online platforms like Twitter to be more proactive with content moderation Twitter leaves EU voluntary Code of Practice against disinformation But obligations remain You can run but you can t hide Beyond voluntary commitments fighting disinformation will be legal obligation under DSA as of August Our teams will be ready for enforcement ーThierry Breton ThierryBreton May Twitter does not operate a communications department Engadget could contact for comment Before Elon Musk s takeover last October Twitter signed onto the EU s Code of Practice against disinformation in alongside companies like Facebook parent Meta Google and TikTok While the Code is voluntary the EU announced in June that sticking to the agreement would count towards DSA compliance As TechCrunch notes Twitter s decision to withdraw from the deal just three months before the EU starts enforcing the DSA would appear to suggest the company plans to skirt the bloc s rules on content moderation However ignoring the DSA could turn into an expensive fight for Twitter and Elon Musk The legislation allows EU officials to hand out penalties of up to percent of global annual turnover for infractions with the potential for fines of up to percent of worldwide turnover for repeat instances of non compliance The European Commission has also said that repeat non compliance could lead to the EU blocking access to offending services This article originally appeared on Engadget at	2023-05-27 18:37:26
ニュース	BBC News - Home	Phillip Schofield: Holly Willoughby says she is hurt over affair lies	https://www.bbc.co.uk/news/entertainment-arts-65735702?at_medium=RSS&at_campaign=KARANGA	affair	2023-05-27 18:26:44
ニュース	BBC News - Home	Oxford split over Kathleen Stock's invite to Union debate	https://www.bbc.co.uk/news/education-65722845?at_medium=RSS&at_campaign=KARANGA	disagree	2023-05-27 18:47:03
ニュース	BBC News - Home	Coventry City 1-1 Luton Town (5-6 pens): Hatters win shootout to reach Premier League	https://www.bbc.co.uk/sport/football/65654937?at_medium=RSS&at_campaign=KARANGA	league	2023-05-27 18:57:04
ビジネス	ダイヤモンド・オンライン - 新着記事	「緊張して話せない」とき「コミュ力が高い人」が行う「自然と話しやすくなる動作」とは？ - 超完璧な伝え方	https://diamond.jp/articles/-/323571	「緊張して話せない」とき「コミュ力が高い人」が行う「自然と話しやすくなる動作」とは超完璧な伝え方「自分の考えていることが、うまく人に伝えられない」「他人とのコミュニケーションに苦手意識がある」と悩む方は多くいます。	2023-05-28 03:50:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【投資のプロが教える】ミドル以降の資産活用層が、お金を増やすために今すぐやったほうがいい2つのこと - インフレ・円安からお金を守る最強の投資	https://diamond.jp/articles/-/323574	【投資のプロが教える】ミドル以降の資産活用層が、お金を増やすために今すぐやったほうがいいつのことインフレ・円安からお金を守る最強の投資インフレ・円安の時代に入った今、資産を預金だけで持つことはリスクがあり、おすすめできない。	2023-05-28 03:48:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【マンガ】『世界一受けたい授業』で話題！ 体が硬い人は絶対やってみて！ ストレッチ効果を劇的に高める超シンプルなコツ - いつでも､どこでも､1回20秒で硬い体が超ラクになる!　スキマ★ストレッチ	https://diamond.jp/articles/-/321713	そこで参考にしたいのが、『世界一受けたい授業』日本テレビ系、『金スマ』TBS系、『体が硬い人のための柔軟講座』NHKなどで話題のフィジカルトレーナー・中野ジェームズ修一氏の著書『いつでも、どこでも、回秒で硬い体が超ラクになるスキマストレッチ』ダイヤモンド社だ。	2023-05-28 03:46:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【91歳の医師が明かす】 卵のコレステロールについて 100年前に医師が人体実験してみた結果 - 91歳の現役医師がやっている 一生ボケない習慣	https://diamond.jp/articles/-/321836	【歳の医師が明かす】卵のコレステロールについて年前に医師が人体実験してみた結果歳の現役医師がやっている一生ボケない習慣映画『ダイ・ハード』シリーズなどのヒット作で知られる米俳優ブルース・ウィリスさん歳が認知症前頭側頭型認知症と診断されたことを家族が公表し、世界的に大きなニュースとなった。	2023-05-28 03:44:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【元国税専門官が明かす】 安定した国家公務員の年収を捨て フリーランスに転身した決定的理由 - だから、この本。	https://diamond.jp/articles/-/322128	本書は、東京国税局の元国税専門官・小林義崇氏が、相続税調査を通じて得た「“トップの富裕層が密かにやっていること」を体系化したもの。	2023-05-28 03:42:00
ビジネス	ダイヤモンド・オンライン - 新着記事	MARCHに続く人気大学！ 専修大学のキャンパス環境はどんな雰囲気？【各キャンパス紹介付き】 - 大学図鑑！2024 有名大学82校のすべてがわかる！	https://diamond.jp/articles/-/323535		2023-05-28 03:40:00
ビジネス	ダイヤモンド・オンライン - 新着記事	職場で信頼される人が「悩みを相談されたとき」に絶対にやらないたった1つのこと - 1秒で答えをつくる力 お笑い芸人が学ぶ「切り返し」のプロになる48の技術	https://diamond.jp/articles/-/323533		2023-05-28 03:38:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【お金を増やす】 儲かる投資先を見つける2つのポイント - 個人投資家もマネできる 世界の富裕層がお金を増やしている方法	https://diamond.jp/articles/-/322552	米国の富裕層の間では、米国以外の海外資産を組み入れるグローバル投資の動きが、以前にも増して加速しているという。	2023-05-28 03:36:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【一度使ったらやめられない】ショートカットキー「お薦めランキング」ベスト5 - 良書発見	https://diamond.jp/articles/-/321482	【一度使ったらやめられない】ショートカットキー「お薦めランキング」ベスト良書発見ほとんどの人がパソコン仕事で使っている「マウス」。	2023-05-28 03:34:00
ビジネス	ダイヤモンド・オンライン - 新着記事	凡人が「逆T字型人間」と「逆π字型人間」に変わる方法 - １位思考	https://diamond.jp/articles/-/322650	凡人が「逆T字型人間」と「逆π字型人間」に変わる方法位思考話題沸騰刷【日経新聞掲載有力紙書評続々】注目著者、初の著書創業年目で売上億円にしたアンカー・ジャパンCEOの猿渡歩が初めて語る“大逆転の新手法。	2023-05-28 03:32:00
ビジネス	ダイヤモンド・オンライン - 新着記事	元お笑い芸人の僕が「人が辞めない派遣会社」をつくれたワケ - 時間最短化、成果最大化の法則	https://diamond.jp/articles/-/323019	元お笑い芸人の僕が「人が辞めない派遣会社」をつくれたワケ時間最短化、成果最大化の法則シリーズ万部突破【がっちりマンデー】で「ニトリ」似鳥会長「食べチョク」秋元代表が「年に読んだオススメ本選」に選抜【日経新聞掲載】有隣堂横浜駅西口店「週間総合」ベスト入り。	2023-05-28 03:30:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【日本人最大の弱点！ 出口学長・哲学と宗教特別講義】 キルケゴールがヘーゲルと真逆の主張をした理由 - 哲学と宗教全史	https://diamond.jp/articles/-/321609		2023-05-28 03:28:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【スタンフォード発】社員でありながら楽しく起業して人生を謳歌する方法とは？ - スタンフォード式生き抜く力	https://diamond.jp/articles/-/322674	【スタンフォード発】社員でありながら楽しく起業して人生を謳歌する方法とはスタンフォード式生き抜く力万部突破スタンフォード大学・オンラインハイスクールはオンラインにもかかわらず、全米トップの常連で、年は全米の大学進学校位となった。	2023-05-28 03:26:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【9割の人が知らない！ 第一人者のコピーライティング技術100】 お客の抱える「痛み」を 「不安や怒り」として シンプルに表現する方法 - コピーライティング技術大全	https://diamond.jp/articles/-/322809	【割の人が知らない第一人者のコピーライティング技術】お客の抱える「痛み」を「不安や怒り」としてシンプルに表現する方法コピーライティング技術大全「この本は万円以上の価値がある」東証プライム上場社長で現役マーケッターである「北の達人コーポレーション」木下勝寿社長が絶賛。	2023-05-28 03:22:00
ビジネス	ダイヤモンド・オンライン - 新着記事	「ちょっとした言い方」だけで、損する人と得する人の差とは？ - だから、この本。	https://diamond.jp/articles/-/322056	「ちょっとした言い方」だけで、損する人と得する人の差とはだから、この本。	2023-05-28 03:20:00
ビジネス	ダイヤモンド・オンライン - 新着記事	「ダメな管理職かどうか」を試す、たった1つの質問 - とにかく仕組み化	https://diamond.jp/articles/-/323235	「ダメな管理職かどうか」を試す、たったつの質問とにかく仕組み化人の上に立つと、やるべき仕事や責任が格段に増える。	2023-05-28 03:18:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【精神科医が教える】 他人に頼る人ほど最後に失敗するワケ - 精神科医Tomyが教える 40代を後悔せず生きる言葉	https://diamond.jp/articles/-/322269	そんなときの助けになるのが、『精神科医Tomyが教える代を後悔せず生きる言葉』ダイヤモンド社だ。	2023-05-28 03:16:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【英語でどう言う？】心配です、懸念してます【5分で英会話力アップ】 - 5分間英単語	https://diamond.jp/articles/-/322915	【英語でどう言う】心配です、懸念してます【分で英会話力アップ】分間英単語「たくさん勉強したのに英語を話せない……」。	2023-05-28 03:14:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【売上が伸びる】“ごく一部の企業”だけが知っている「新時代の営業メソッド」 - 良書発見	https://diamond.jp/articles/-/322578		2023-05-28 03:12:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【医師が教える】 実は「果物」が“体の害悪”になる決定的理由 - 内臓脂肪がストンと落ちる食事術	https://diamond.jp/articles/-/323278	身長は年をとっても縮んでいない歯は全部残っていて虫歯も歯周病もない視力もよく『広辞苑』の小さな文字も裸眼で読める聴力の低下もない毎日時間睡眠で夜中に尿意で目覚めることはない定期的に飲んでいる薬もなければサプリメントとも無縁コレステロール値も中性脂肪値も基準値内いまも朝勃ち夜間陰茎勃起現象する「朝勃ち」なんていうと下品に思われるかもしれないが、バカにしてはいけない。	2023-05-28 03:10:00
ビジネス	ダイヤモンド・オンライン - 新着記事	「しんどい時も、この本は大丈夫やって言うてくれる気がする」 - あの日、選ばれなかった君へ	https://diamond.jp/articles/-/323318	「しんどい時も、この本は大丈夫やって言うてくれる気がする」あの日、選ばれなかった君へゴールデンウィークも終わり、「月病」に悩まされる人もちらほらいるのではないだろうか。	2023-05-28 03:08:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【名医が教える】ケトン体誘導の大きなカギとなる、身体の中のバランスとは？ - 糖質制限はやらなくていい	https://diamond.jp/articles/-/318932	【名医が教える】ケトン体誘導の大きなカギとなる、身体の中のバランスとは糖質制限はやらなくていい「日食では、どうしても糖質オーバーになる」「やせるためには糖質制限が必要」…。	2023-05-28 03:06:00