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Newton’s Laws in Society: How Social Forces Move Physical Bodies

সমাজে নিউটনের আইন: সামাজিক শক্তিগুলি কীভাবে শারীরিক দেহগুলিকে স্থানান্তরিত করে

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Las leyes de Newton en la sociedad: cómo las fuerzas sociales mueven los cuerpos físicos

Les lois de Newton dans la société : comment les forces sociales déplacent les corps physiques

समाज में न्यूटन के नियम: सामाजिक शक्तियां भौतिक निकायों को कैसे स्थानांतरित करती हैं

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Định luật Newton trong xã hội: Các lực lượng xã hội di chuyển cơ thể vật chất như thế nào

社会中的牛顿定律：社会力量如何移动身体

The New York Times Company v. OpenAI Update Court Filing, retrieved on February 26, 2024 is part of . You can jump to any part in this filing . This part is 13 of 15. HackerNoon’s Legal PDF Series here C. The DMCA Claim Fails for Multiple Independent Reasons Count V is a claim for violation of Section 1202(b) of the Copyright Act, which prohibits the “[r]emoval or [a]lteration” of copyright management information or “CMI.” 17 U.S.C. § 1202(b). Congress passed that provision in the early days of the internet in recognition of the ease with which unauthorized copies of images and other works might proliferate in cyberspace. The provision encourages rightsholders to affix CMI to their works (and prohibits its removal) so that, if their works do proliferate on the internet, the public will be able to trace those works back to their owner. S. Rep. No. 105-190, at 16–17 (1998) (CMI intended to “track[] and monitor[]”). But Congress limited the statute with a “double-scienter requirement” that prevents its application when the CMI removal occurs as an unintended result of an “automatic [] process.” Zuma Press, Inc. v. Getty Images (US), Inc., 845 F. App’x 54, 57–58 (2d Cir. 2021). A typical CMI case might involve the surreptitious removal of a photograph’s “gutter credit” to conceal a failure to seek a license from the rightsholder. Mango v. BuzzFeed, Inc., 970 F.3d 167, 169–70, 173 (2d Cir. 2020). 1. The Times Did Not Specify the CMI at Issue Count V should be dismissed at the outset for failure to specify the CMI at issue. The Complaint’s relevant paragraph fails to state what CMI is included in what work, and simply repeats the statutory text. Compl. ¶ 182 (alleging “one or more forms of [CMI]” and parroting language of Section 1202(c)).[36] The only firm allegation states that the Times placed “copyright notices” and “terms of service” links on “every page of its websites.” Compl. ¶ 125. But, at least for some articles, it did not.[37] And when it did, the information was not “conveyed in connection with” the works, 17 U.S.C. § 1202(c) (defining CMI), but hidden in small text at the bottom of the page.[38] Judge Orrick of the Northern District of California rejected similar allegations as deficient in another recent AI case. Andersen v. Stability AI Ltd., No. 23-cv-00201, 2023 WL 7132064, at *11 (N.D. Cal. Oct. 30, 2023) (must plead “exact type of CMI included in [each] work”).[39] 2. The Training-Based Section 1202 Claim Fails The first Section 1202 violation alleged in the Complaint asserts that OpenAI “removed” CMI “in building the training datasets” in violation of Section 1202(b)(1) of the DMCA. Compl. ¶ 184. As a preliminary matter, to the extent this claim is based on the “building [of] training datasets” that occurred more than three years ago, it is time-barred. 17 U.S.C. § 507(b). The Complaint also fails to plausibly allege that any CMI was removed. The Times advances three theories of removal: (1) removal of CMI when OpenAI allegedly “scraped” articles from the Times’s website; (2) removal of CMI “from third-party datasets,” i.e., Common Crawl; and (3) removal of CMI during “the training process,” which the Times alleges “does not preserve any [CMI]” “by design.” Compl. ¶¶ 184, 187. As a preliminary matter, each theory fails for failure to allege what CMI was removed or “not preserve[d],” which is particularly damning as the Times concedes that some CMI was preserved.[40] Judge Martínez-Olguín of the Northern District of California recently held an identical set of allegations to be insufficient. See Tremblay v. OpenAI, Inc., No. 3:23-cv-03416, 2024 WL 557720, at *4 (N.D. Cal. Feb. 12, 2024) (allegation that “training process does not preserve any CMI” “by design” was “conclusory”). Each theory fails separately as well. The first theory fails because, while the Times states that OpenAI “scraped” its articles “directly from [its] websites,” none of the specific allegations actually suggest OpenAI designed its alleged “scrap[ing]” process to omit CMI. Compl. ¶ 184.[41] And the only allegations about OpenAI “scraping” articles from Times websites relate to the creation of WebText, which occurred over three years before this lawsuit. Supra Section IV.A.[42] The second theory fails because the Complaint lacks allegations about the inclusion (or exclusion) of the Times’s CMI in any “third-party datasets” like Common Crawl,[43] much less about OpenAI scrubbing any CMI from those datasets. First Nationwide Bank v. Gelt Funding Corp., 27 F.3d 763, 771 (2d Cir. 1994) (courts ignore “unwarranted deductions of fact”). And the third theory fails because there is no allegation in the Complaint supporting the conclusion that the “training process” excludes CMI “[b]y design.” Compl. ¶ 187; see also Tremblay, 2024 WL 557720, at *4. Moreover, the Times fails to allege facts that could show how the alleged CMI removal could “induce, enable, facilitate, or conceal an infringement” of copyright—much less how OpenAI could have “reasonable grounds to know” it would. 17 U.S.C. § 1202(b). The “point of CMI” is to provide information to “the public,” not to govern purely internal databases. Roberts v. BroadwayHD LLC, 518 F. Supp. 3d 719, 737 (S.D.N.Y. 2021); Compl. ¶ 59. As Judge Martínez-Olguín explained, it is far from obvious how “the alleged removal of CMI in an internal database [could] enable infringement.” Tremblay, 2024 WL 557720, at *4 (dismissing claim).[44] 3. The Output-Based Section 1202 Claim Fails The second category of Section 1202 violation in the Complaint alleges that (1) OpenAI violated Section 1202(b)(1)’s removal prohibition by failing to include the Times’s CMI in model outputs, Compl. ¶¶ 185–86; and (2) by displaying those outputs via ChatGPT or its API, OpenAI violated Section 1202(b)(3)’s prohibition on “distribut[ing]” works “knowing that [CMI] has been removed,” Compl. ¶ 189. Neither theory states a claim for relief. As a preliminary matter, the Times’s Section 1202(b)(3) claim fails because the Complaint does not allege that OpenAI “distribute[d]” any outputs. In this context, “distribution” requires a “sale or transfer of ownership extending beyond that of a mere public display.” Wright v. Miah, No. 22-cv-4132, 2023 WL 6219435, at *7 (E.D.N.Y. Sept. 7, 2023) (emphasis added).[45] But “mere public display” of outputs is all the Complaint alleges. See, e.g., Compl. ¶ 102. Regardless, this “output” theory fails because the outputs alleged in the Complaint are not wholesale copies of entire Times articles. They are, at best, reproductions of excerpts of those articles, some of which are little more than collections of scattered sentences. Supra 12. If the absence of CMI from such excerpts constituted a “removal” of that CMI, then DMCA liability would attach to any journalist who used a block quote in a book review without also including extensive information about the book’s publisher, terms and conditions, and original copyright notice. See supra note 22 (example of the Times including 200-word block quote in book review). To avoid such anomalous results, courts have cabined applications of Section 1202(b)(1) and (3) to circumstances in which the works in question were “substantially or entirely reproduced.” Fischer v. Forrest, 286 F. Supp. 3d 590, 609 (S.D.N.Y. 2018). As such, failure to include original CMI in anything less than an identical reproduction of all (or almost all) of the work does not qualify as CMI removal. Tremblay, 2024 WL 557720, at *5 (dismissing claim because “Plaintiffs have not alleged that [OpenAI] distributed their books or copies of [them]”).[46] As the Times has not alleged that OpenAI reproduced entire articles, the output-based claim fails. Even setting that aside, the Times’s output-based CMI claim fails for the independent reason that there was no CMI to remove from the relevant text. The Exhibit J outputs, for example, feature text from the middle of articles. Ex. J. at 2–126. As shown in the exhibit, the “Actual text from NYTimes” contains no information that could qualify as CMI. See, e.g., id. at 3; 17 U.S.C. § 1202(c) (defining CMI). So too for the ChatGPT outputs featured in the Complaint, which request the “first [and subsequent] paragraph[s]” from Times articles. See, e.g., Compl. ¶¶ 104, 106, 118, 121. None of those “paragraphs” contains any CMI that OpenAI could have “removed.” 4. The Times Fails to Allege a CMI-Based Injury Count V separately fails for lack of standing. “[T]o have standing” to sue for a DMCA violation, the Times “must show that [it] was injured by that violation.” Steele v. Bongiovi, 784 F. Supp. 2d 94, 97–98 (D. Mass. 2011); see also 17 U.S.C. § 1203(a). Here, the Complaint’s “Harm to the Times” section relates entirely to its inability to receive speculative licensing revenue, see Compl. ¶¶ 155–56, and the possibility that ChatGPT will “divert readers,” see id. ¶ 157. Neither injury has any nexus to CMI. Nor is there any imaginable harm here: because all of the Complaint’s outputs were either generated using the original Times article itself, see Ex. J, or referenced the Times by name, see, e.g., Compl. ¶ 104, any user who encountered those outputs would have no doubt as to the provenance of the text and could easily find it on the Times’s website (as ChatGPT often invites them to do, see id. ¶¶ 106, 134). Cf. Kelly, 77 F. Supp. 2d at 1122 (DMCA claim failed because users who encounter images are “given the name of the Web site from which Defendant obtained the image, where any associated [CMI] would be available”). Continue Reading . Here [36] Design Pics Inc. v. PBH Network, Inc., No. 20-cv-1096, 2020 WL 8413512, at *4 (E.D.N.Y. Oct. 27, 2020) (dismissing CMI claim based on “conclusory, boilerplate parroting of the statutory text”). [37] See, e.g., John Branch, Snow Fall: The Avalanche at Tunnel Creek, N.Y. Times, https://www.nytimes.com/projects/2012/snow-fall/index.html#/?part=tunnel-creek (last accessed Feb. 11, 2024); see also Compl. ¶¶ 104–05 & n.28 (citing this article). [38] See, e.g., Pete Wells, As Not Seen on TV, N.Y. Times (Nov. 13, 2012), https://www.nytimes.com/2012/11/14/dining/reviews/restaurant-review-guys-american-kitchen-bar-in-timessquare.html; see also Compl. ¶¶ 106–07 & n.29 (citing and quoting this article). [39] See also Wood v. Observer Holdings, LLC, No. 20-cv-07878, 2021 WL 2874100, at *8 (S.D.N.Y., July 8, 2021) (terms on “separate website” not CMI); GC2 Incorporated v. Int’l Game Tech. PLC, 255 F. Supp. 3d 812, 821–22 (N.D. Ill. 2017) (“terms of use notice near a copyrighted work” not “conveyed in connection with” work). [40] See, e.g., Compl. ¶ 106 (ChatGPT responding to query naming “Pete Wells” with a completion correctly identifying the publication date of Wells’ article); see also id. ¶ 104 (same, for title). [41] Kelly v. Arriba Soft Corp., 77 F. Supp. 2d 1116, 1122 (C.D. Cal. 1999), rev'd on other grounds by 336 F.3d 811 (9th Cir. 2003) (no Section 1202 liability vs. search engine “crawler [that] did not include [CMI]”). [42] The Times suggests that OpenAI’s “Browse with Bing” feature “scrap[es] Times Works from The Times’s websites,” Compl. ¶ 185, but the Complaint does not include a single allegation supporting that conclusion, see supra 13 & n.32 (noting that Browse with Bing fetched content from third-party sites, not the Times’s website). [43] OpenAI cannot have removed CMI from datasets that “contained no such [CMI]” in the first place. McGucken v. Shutterstock, Inc., No. 22-cv-00905, 2023 WL 6390530, at 11 (S.D.N.Y. Oct. 2, 2023) (rejecting DMCA claim). [44] See Victor Elias Photography, LLC v. Ice Portal, Inc., 43 F.4th 1313, 1325 (11th Cir. 2022) (requiring “some identifiable connection between the defendant’s actions and the infringement or the likelihood of infringement.”). [45] Id. at *10 (endorsing Section 1202(b)(3) claim where defendant distributed artwork on Etsy); MyPlayCity, Inc. v. Conduit Ltd., No. 10-cv-1615, 2012 WL 1107648, at *12 (S.D.N.Y. Mar. 30, 2012) (“distribution” means “actual dissemination of copies”); FurnitureDealer.Net, Inc v. Amazon.com, Inc, No. 18-cv-232, 2022 WL 891473, at *23 (D. Minn. Mar. 25, 2022) (“[P]ublic display does not constitute distribution, and thus is not a [DMCA] violation.”). [46] See also Doe 1 v. GitHub, Inc., No. 22-cv-06823, 2024 WL 235217, *9 (N.D. Cal. Jan. 22, 2024) (dismissing Section 1202(b) claim against OpenAI because outputs were “not identical” to originals); A’Lor Int’l, Ltd. v. Tapper Fine Jewelry, Inc., No. 12-cv-02215, 2012 WL 12921035, at *10 (C.D. Cal. Aug. 8, 2012) (“the plain language of the statute encompasses only removal and alteration;” does not “include [mere] omissions”); Faulkner Press, L.L.C. v. Class Notes, L.L.C., 756 F. Supp. 2d 1352, 1358–59 (N.D. Fla. 2010) (rejecting claim where “word for word” text was “copied into a different form and [] incorporated into” commercial materials); Kelly, 77 F. Supp. 2d at 1121–22 (“displaying thumbnails of Plaintiffs’ images without [] the corresponding [CMI]” was not CMI “removal”). About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on February 26, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. fingfx.thomsonreuters.com

ChatGPT Never Produced "Wholesale Copies" of NYT's Articles

There has been a lot of talk about chatbots these days. You come across them quite often in Facebook Messenger. In fact, right now, there are more than on Facebook Messenger. For a technology that has gained momentum just a few years ago, this number is huge. 300,000 active chatbots Not only on Facebook Messenger, chatbots are also showing up on a lot of business websites. That’s because the barriers that prevented people from using chatbots are breaking down. According to a recent customers are becoming increasingly comfortable interacting with chatbots. Only 38% of people said that they prefer to talk to humans when engaging with a brand in 2019, compared to 43% of people who said the same last year. survey by Drift, The remaining 62% of consumers are happy and satisfied with chatbot support. Why are Chatbots So Popular? One of the primary reasons behind this surge in the popularity of chatbots is the development of AI-powered chatbots. AI-powered chatbots are easy to build and can interact with humans with astonishing accuracy. Chatbots are bringing in significant structural changes in many organizations. They are proving to be an integral part of sales and customer support. They empower businesses to provide excellent customer service around the clock without the need to hire additional employees. In fact, chatbots are now being deployed in almost all aspects of customer support. People like to use chatbots for a variety of purposes, including: Image via Drift Benefits of Using Chatbots for Your Business Let’s take a look at some of the and how they can contribute to the growth of your business. benefits of using chatbots 1. Using Chatbots is Better and Cheaper Than Building a New App A users actively use social media apps such as Facebook, Instagram, and Whatsapp. They like the comfort of using these apps and are very less likely to replace them with any new apps. majority of smartphone Therefore, integrating chatbots into one of the platforms that your consumers already use is better and cheaper than building a new app. For example, Lyft, a ride-sharing app, allows you to request a ride via a chatbot integrated into Facebook Messenger. The chatbot also updates you about the vehicle number and the current location of the driver. Image source: Social Media Today 2. Chatbots Can Provide Extensive Customer Support Shopping online may seem easy but it isn’t always. Many online shoppers need assistance while shopping. From dealing with navigation issues to seeking help during registration, payment, and checkout processes, your customers may need support. In such situations, chatbots can assist them just like a salesperson would if they were in a retail store. Along with solving basic customer issues, chatbots can also ask questions to understand the buying preferences of your customers and recommend relevant products to them accordingly. The best part about using chatbots is that they can provide round-the-clock customer support. You don’t need to hire more executives as chatbots can handle multiple requests at one time. This ensures that your customers don’t have to wait very long. customer support Also, these bots can be programmed to give predefined answers to common questions. They can also forward requests to a real human in case a customer asks any complicated question. Starbucks’ chatbot is an amazing example. The bot makes it extremely easy for customers to place an order using either voice command or text messaging. The chatbot also tells you the amount of time required for your order to be ready and the total bill amount. And if you want to repeat your past order, all you have to do is to just ask the bot. Image source: GeekWire 3. Chatbots are Cost-Effective Integrating a chatbot is cheaper and easier than creating a cross platform app or hiring people to perform each task manually. Since chatbots are automated programs, they can handle multiple customer requests at once. This means that you can save on repetitive employee costs by investing in a chatbot. Using chatbots can also enable you to prevent issues caused due to human errors. 4 Steps to Make a Chatbot for Your Business If you are wondering how to make a chatbot with minimal or no coding knowledge, you shouldn’t worry. There are various chatbot platforms such as , , and that let you create a customized chatbot without any coding knowledge. Aivo ManyChat Botsify You can follow this guide to learn the step-by-step process to make a chatbot as a beginner. Step 1: Understand Your Goal Behind Making the Chatbot Before you start to make a chatbot, it is important to understand what you want your chatbot to do. Determining this can help you select the right chatbot platform for your business. This information will also guide you to create conversations that can address your end goals. For example, if your end goal is to engage your customers until a real human takes over, you can design a simple chatbot with some predefined text. You don’t need to leverage artificial intelligence for this. However, if your end goal is to pitch products and engage customers to increase sales, then you need to make an AI-powered chatbot. Your chatbot should have the ability to deliver the right solutions to a variety of questions that your customers may ask. A brilliant example of this is Dom, Domino’s interactive chatbot integrated with Facebook Messenger. Dom allows you to place orders and repeat previous orders without you having to create an account. You can place an order from the entire restaurant menu without having to leave the comfort of your favorite app. Image source – Digital Marketing Institute Step 2: Examine the Communication Habits of Your Customers They way your customers interact with your business serves as a primary factor for deciding how you should design and develop your chatbot conversations. To understand how your customers interact with your business, you should answer the questions below: Which communication channels do your customers use the most? Do they contact you via chat, phone calls, emails, or any social media channels?What kind of questions do they usually ask? How often do your customers contact you? These customer interaction habits will put you in a better place to set up effective conversations for your chatbot through integration with the out there, which can lead to more automatic conversations. best VoIPs Step 3: Design a Chatbot Conversation Chatbot conversations need to be accurate, interesting, and engaging. The way your chatbot communicates is the differentiating factor that decides the quality of customer engagement it can deliver. Due to advancements in natural language processing (NLP), chatbots are now able to understand user intent. They are emerging as intelligent, conversation-driven, virtual assistants for businesses. Image Source – IMPACT Broadly, chatbot conversations can be divided into two segments: Structured Interaction Structured interaction is a logical flow of information that works similar to the FAQs section on a website. It takes menus, choices, and forms into account and can be designed easily based on your analysis. In this case, you collect commonly-asked questions from your customers and then set their answers in your channel. Unstructured Interaction This involves freestyle conversation such as one that may happen with family, colleagues, and friends. Developing a script for unstructured interactions mainly depends on AI. AI uses natural language processing (NLP) to find the intent of the communication and then provide suitable responses. Designing chatbot conversations is not only about providing correct responses but also about creating a conversational user interface. It is important to keep the conversation topics close to your goals. To meet your end goals, designers need to develop both close-ended and open-ended chatbot conversations. Close-ended conversations are for customers who want specific answers whereas open-ended conversations are for customers who are looking for assistance and natural conversations. Step 4: Choose Between Non-Coding and Code-Based Framework If your product is not extremely complicated and you are clear about what your visitors expect, you can create your chatbot using a non-coding framework. There are many chatbot applications which allow you to make a chatbot using a simple drag-and-drop builder. You can design simple conversations and upload them to a cloud-based platform and you are done. However, if your product is extremely complicated and you want your chatbot to handle unstructured conversations, you need to use a code-based framework. This kind of conversation is usually not addressed by default templates. You may need advanced knowledge of programming languages, machine learning, and AI. Also, if you want to store and analyze customer data, making a code-based chatbot will be your best bet. Design Elements to Use in Chatbots In order to ensure that the chatbot offers a smooth and interactive user experience, it is important to include the right design elements. Of course, the design elements will depend on the platform you choose to build your bot on. Let’s take a look at the top design elements you can use when you make your chatbot. 1. Buttons Buttons enable users to take action. When a user clicks any button, it prompts an action. It is a good idea to include interactive buttons to help users make decisions faster. You can add buttons to ask users to choose one of the multiple options you have to offer. Image source: Chatbots Magazine You can also add a “Get Started” button to encourage users to start a conversation. 2. Cards If there is any additional information (apart from the conversation) that you want to serve users, you can leverage cards. You can enter text, links, images, and buttons into cards which the user can view as a side column during their conversation. Users can click the cards relevant to them or they can choose to hide them. Image source: Zumata 3. Smart Reply Smart reply is a feature that allows users to respond to questions asked by the chatbot without actually typing anything. You can use this design element when you can give a list of available options to the user. This can make it easier for users to interact with your chatbot. Gmail’s smart reply is a brilliant example of this. In addition to offering three responses to choose from, Gmail provides you an option to auto-complete your sentences without typing anything. The GIF below shows how this smart reply feature simplifies the lives of Gmail users. GIF source: Google Blog 4. Persistent Menu Users can opt for this feature when they want to browse another feature of your chatbot that is not otherwise readily available. Tips to Make a Chatbot That Has an Engaging Personality If you want to make a chatbot that users would love to interact with, you should keep a few points in mind. 1. The Chatbot Should Be Able to Direct Users To give continuity and direction to any conversation, a chatbot should ask questions that are relevant to the conversation. They should also offer options that are easy to select with a “tap.” If a user does not know what they want, the chatbot should be able to provide directional cues to help them. For example, instead of asking the user what they would like to do, the bot can give a list of things it can do for the user. This way, the user can easily figure out all of the options that the bot has for them. 2. The Chatbot Should Connect with Users on a Personal Level You should make a chatbot that effectively incorporates personalization. Your bot should address users by their names, greet them when the conversation begins, and give personalized suggestions based on previous conversations. Adding a personalized in your chatbot conversations can help you break the ice and give your users a feeling that they are talking to a real human. 3. The Chatbot Should Use Fillers for Time Gaps If the bot needs a certain amount of time to process a request, it is a good idea to use fillers to keep the user engaged for that time. If you leave a user waiting, it can break the flow of the conversation and, in the worst case, the user may also leave the conversation. It is a good idea to use random trivia facts as fillers during conversations. 4. The Chatbot Should Understand Emotions The capability to include emotions in chat is what makes humans different. If you want to make your chatbots more human-like, it is important that they are able to understand the emotions behind a conversation and respond accordingly. If a user accomplishes a task, your chatbot should respond with a cheerful reply. Similarly, if the chatbot can’t help a user the right way, it should be able to convey an apology for the inconvenience caused. A good idea is to use emoticons. You should try to integrate the most basic and commonly used emoticons in your chatbot conversations. Image source: Singularika Conclusion Today, when customers seek instant responses to their queries, chatbots are a popular solution. They are already all over Facebook Messenger and are steadily making their way to other messaging mediums as well. What’s interesting is that users have grown fond of chatbots and they don’t mind interacting with them to improve their shopping experiences. The real challenge, though, lies in building a chatbot that is engaging, interactive, and is able to provide real value to users. With easy-to-use , making a chatbot is now quick and hassle-free. And with unprecedented technological advancements in artificial intelligence and machine learning, the future of chatbots looks bright. chatbot platforms This article published on Shane Barker ’s blog. About The Author is the Founder and CEO of and . You can connect with him on , , , and . Shane Barker Content Solutions Gifographics Twitter Facebook LinkedIn Instagram

The Beginner’s Guide to Making a Chatbot

Matej Michalko is the CEO of DECENT , a decentralized blockchain platform revolutionizing data distribution In the digital age, modern technologies are increasingly forcing government officials to move processes from behind closed doors, into the public sphere. From , to logging public information on , new technologies are improving transparency and increasing accountability in an an area which has traditionally been endemic with corruption. live streaming court cases in China open data ecosystems However, experts suggest that it will be — the decentralized digital ledger on which information can be stored and shared, but not deleted or tampered with — which has the potential to make the most long lasting change. To date applications have been rolled out with varying levels of success in processes such as , but a recent says that public procurement — the buying of works, goods or services by public bodies — is one of the government activities most vulnerable to corruption, and is most suited to the application of the blockchain. the blockchain blockchain recording election results report from the OECD So how can blockchain clean up the traditionally dirty area of public funds management? technology Problems with traditional management of public procurement Governments employ large amounts of staff with varying levels of responsibility, across a huge range of different departments, bodies and agencies. The US government hires , while the . upwards of 21 million people UK public sector employed 5.4 million people in 2017 As such, even when buying seemingly small, inexpensive items like stationary, costs can spiral into staggering figures. And when dealing with more expensive costs like transport fleets, maintenance and upkeep on all government assets, and new buildings contracts can cost in the hundreds of millions of dollars. According to recent figures, public procurement accounts for more than 14% of GDP in the EU, and as high as . And with costs running as high as $7 trillion dollars per year in the US, there is plenty of space for sticky fingers, and dodgy backhanders. 15% in the US 20% in China Traditionally, the most common forms of corruption have included withholding funds (embezzlement), overestimating costs and needs for personal gain, bribery of public officials involved in the awarding of government contracts, or fraud in bid evaluations, invoices or contract obligations. And while public procurement is monitored and regulated by global governing bodies like , to ensure that member states respect the 3 key principles of equal treatment, non-discrimination and transparency, cases of mismanagement are estimated to be much higher in ‘emerging’ economies like former USSR states, and African countries, which are comparatively less regulated by external watchdogs. the EU commision As such, it’s not surprising to see that according to , “nine in ten government organisations say they plan to invest in blockchain technology to help manage financial transactions, assets, contracts and regulatory compliance” by the end of 2018. The Economist How blockchain helps To best understand how blockchain can make public procurement more transparent, it is important to first look at the most common forms of corruption: Preferential treatment for bids Generally, government bodies will receive a number of ‘bids’ from suppliers, and in a fair scenario would choose the best deal in terms of price. However, one of the most common forms of corruption in procurement, is when officials give preferential treatment to certain suppliers after receiving bribes. Some common forms of unfair bidding include: Collusion among bidders to cut out outside competition. Officials offering bidders with advance “inside” information. Choosing “sole source” contracts rather than using multiple suppliers. However, the blockchain can act as a deterrent to this type of behaviour, by adding a new level of traceability which can track all bids, and terms from suppliers on the blockchain, which in turn makes it easier for fraudulent behaviour to be noticed. Put simply, if the figures don’t add up, and the best deal financially is not chosen, all this information will be saved. Smart contracts can be coded, which require more than one official to ‘sign off’ on a deal and using these same smart contracts, funds can also be put in escrow until a transaction is verified by someone who is designated to this purpose. This ‘approval’ system is likely to deter officials from trying to make a quick buck by offering preferential treatment. Inflated orders/invoices Another common type of fraud is when officials overestimate or falsify invoices for work or services which have already been completed. In the pre-digital age, when orders and invoices were stored on paper, it was extremely easy for officials to change or delete invoices and order information to cover up corruption. Common forms include: Submitting falsified or inflated invoices for services or products that have not been delivered or work that has not actually been completed. Creating bogus “Shadow vendors” and then billing them for large sums for work/services which did not take place. However, using the blockchain it would be simple to eradicate this type of behaviour. By creating unique identity management, and creating a ‘personal key’ for each supplier, and also for each official who submits invoices, it would be easy to trace who had filed for expenses, and which company had allegedly completed the work. And when the purchase of physical goods were in questions, it would be easier to trace costs back to the source, and also record how many units of materials were used, thanks to easily scannable and recordable barcodes, and shipment codes being saved on the blockchain. Using low standard goods/materials Another common issue, which is particularly dangerous to the public and other government employees, is when official contractors invoice for certain materials, but in fact use cheaper or lower quality materials to complete the job. However, thanks to information being stored on the blockchain, officials can ‘track and trace’ products from production to sale, offering more visibility about where a product was created and with what materials. Blockchain’s innovative qualities of immutability, transparency and security can be used for the whole supply and value chain of suppliers and sub-suppliers, to ensure that the right materials or services are provided to the right place at the right time. Current government applications on the blockchain Blockchain technology is already being used to improve accountability by government officials across the world. In South Africa, in light of accusations that former from local government departments, a number of South African financial institutions have rolled out a blockchain technology called , which . Using the SpringBlock technology, government employees, suppliers and contractors could be assigned with public and personal keys, which would record exactly who was spending what, and also securely monitor the management of public funds across the board. president Zuma has syphoned off billions Springblock supports Ethereum, Hyperledger, Chain Core, Corda, and Quorum In Estonia, the government has rolled out an . If Estonians or foreigners need to sign any official form, or register a business, everything can be done easily and quickly online, and information is stored on the blockchain. Whether it be for official forms, tax returns or land ownership records, using these digital identities makes the process safer and more transparent for users, and allows them to track the progress of these processes at any moment in time. By making processes quicker and easier, this also reduces space for fraudulent behaviour from officials who may have previously accepted bribes to speed up the process. e-residency program that harnesses the blockchain With procurement costs in the trillions, blockchain technology offers a streamlined manner for governments to ensure that rules are followed, and corners are not cut by public employees. Aside from improving public trust in governing institutions, this should help governments improve their money management which in turn, should provide more available funding for important public projects, which can really help citizens, rather than filling the pockets of corrupt officials.

Breaking the Chains of Corruption

After a relatively calm late summer, SpaceX kicked up the cadence again in October 2017 — closing out the month with three successful missions. This uptick in cadence follows a remarkable year that has left many astounded at the capabilities and durability of the company that was, until recently, considered an underdog in the aerospace industry. On October 9, SpaceX launched the Iridium-3 mission from Vandenberg AFB in California. This launch carried the third set of 10 satellites into their target orbits. The Iridium NEXT constellation is a state of the art constellation of satellites that orbit in a low earth orbit around the planet and provide services including air and maritime tracking as well as Internet of Things and sat phone communications. It will consist of 72 individual satellites (6 of which are on-orbit spares) that are launched 10 at a time. Following the early October launch, the Falcon 9 booster returned to Earth and landed successfully on the “Just Read the Instructions” in the Pacific. [EDIT: As per this , Iridium has added 3 satellites to their constellation, bringing their on orbit spare count to 9 and total satellite count to 75.] January 2017 Press Release Two days later, on October 11, SpaceX launched the EchoStar 105/SES-11 satellite to Geostationary Transfer Orbit (GTO) from Launch Complex 39A at NASA’s Kennedy Space Center in Florida. This launch utilized a flight proven booster that had previously taken SpaceX’s 10th ISS resupply Dragon capsule to the International Space Station earlier in 2017. EchoStar 105/SES-11 is a dual-mission satellite that is operated by both US-based EchoStar and Luxembourg based SES. It provides TV and other communication capabilities to the North American continent. Following delivery of the second stage and payload into space, the booster once again returned to earth to land on the “Of Course I Still Love You” in the Atlantic ocean. The Falcon 9 carrying the EchoStar 105/SES-11 satellite prior to launching (SpaceX) Closing out October, SpaceX launched the Koreasat-5A satellite from Launch Complex 39A at NASA’s Kennedy Space Center in Florida on October 30. Koreasat-5A replaces the aging Koreasat-5 satellite and will provide TV, Broadband, and other communications services across Asia and parts of the Middle East. It will also provide maritime coverage of the Persian Gulf, Indian Ocean, South China Sea, and East China Sea — a feature unique to this satellite in the Koreasat fleet. Following the delivery of the second stage and payload into space, the booster landed on the “Of Course I Still Love You” in the Atlantic ocean after a high energy return through the Earth’s atmosphere. This marked the 16th successful mission this year — doubling the company’s previous annual launch record. Falcon 9 lifting the Koreasat-5A satellite into orbit (SpaceX) In fact, 2017 has been a banner year for SpaceX, and arguably for the future of spaceflight, in many ways. Here is a list of the notable milestones that have happened in 2017: January 14 — Iridium-1 Satellite. Return to Flight after AMOS-6 test anomaly on September 1, 2016. After a 4 month stand-down to investigate the loss of the Falcon 9 during static fire test preparations, this flight from Vandenberg marked the start of the Iridium NEXT deployment and resulted in the first successful landing attempt on the automated support drone ship “Just Read the Instructions” in the Pacific ocean. This booster would go on to fly again in June. February 19 — CRS-10 ISS resupply mission. This was the first private use of the LC-39A launch complex which had been used to send humans to the moon and launch the Space Shuttle. This booster would return to land at LZ-1 and fly once again in October. March 30 — The SES-10 communication satellite became the first satellite launched to orbit on a flight proven booster. The booster was originally used to send the Dragon cargo capsule to the ISS for CRS-8 and was the first booster to land on a drone ship. Following delivery of the second stage and payload to orbit, this booster once again returned to earth to land successfully. This was also the first time that SpaceX launched two payloads in the same month with just 2 weeks between the previous launch of EchoStar and this one on the same pad. May 1 — SpaceX launches their first National Reconnaissance Office payload (NROL_76). For the first time, the general public got to see footage of the booster separation and return to Landing Zone 1 from the ground. Due the secretive nature of the payload, viewers of the web cast were not able to watch the second stage burn or deployment. NROL-76 Booster Separation as seen from the ground June 3 — CRS-11 ISS Resupply mission. This mission marked the first reuse ( ) of an orbital class commercial spacecraft. The pressure vessel for this mission was previously flown on the CRS-4 mission in September 2014. The ability to reuse at least the pressure vessel portion of the Cargo Dragon spacecraft allowed for greater focus to be spent on the Crew Dragon program. partial June 23 — BulgariaSat-1. This mission was the second reflight of a flight proven booster. The booster had previously been used in January to launch the Iridium-1 satellite. Following successful delivery of the second stage to orbit, this booster returned to earth to become the first to land on both droneships. June 25 — Iridium-2. The second set of 10 satellites for the Iridium NEXT constellation was also the third launch for June and the second launch in the same weekend (from opposite sides of the country). This booster landed safely on the “Just Read the Instructions” despite very challenging weather and ocean conditions that necessitated re-positioning the JRTI just before launch. July 6 — Intelsat satellite. Weighing in at 6 761 kg (14,900 lbs), this was the heaviest GTO mission ever flown by SpaceX. The Falcon 9 launched in expendable mode (no legs or grid fins) in order to deliver the payload to a very challenging altitude of at least 31 230 km (19,405 miles). The Falcon 9 exceeded that minimum and placed the payload into a better than expected orbit. August 24 — Formosat 5 satellite. Shortly after breaking their record for heaviest launch, SpaceX launched the lightest payload the F9 has ever carried. The Formosat 5 was a legacy launch that was . intended to be carried on a smaller Falcon variant September 7 — USAF OTV-5 Spacecraft. In their second classified mission of the year, SpaceX, for the first time ever, launched the Boeing built X-37 spacecraft for the US Air Force’s OTV-5 mission. This mission also debuted a new fairing/payload support attachment on the transporter erector launcher (TEL), presumably to protect the rather heavy and delicate X-37 spacecraft. As with the previous NROL mission, footage of the 2nd stage operations and payload delivery was not made available to the public. OTV-5 mission rolling out to the launch pad featuring new payload support brace (Ken Kramer) October 9 & 11 — Iridium-3 and EchoStar 105/SES-11 Satellite. These launches marked the second double header (of a sort) of 2017 with Iridium-3 launching from Vandenberg, CA and EchoStar 105/SES-11 launching from Launch Complex 39A at NASA’s Kennedy Space Center in Florida just 2 days later. In addition, as mentioned earlier, the SES-11 booster had already flown earlier in this year for CRS-10. October 30 — KoreaSat-5a Satellite. This launch marked the 16th successful launch for 2017, doubling the previous annual record for launches by SpaceX. It was also the 13th landing of the Falcon 9 first stage this year (3 flights this year were in expendable mode). One could be excused for thinking that after such an eventful year and with the holidays rapidly approaching, SpaceX might be ready to stand down for a a couple of months until the new year. However, they are still going strong through the end of 2017. Next up on their launch manifest is the rather mysterious Zuma launch. While it could be presumed that SpaceX was well aware of this launch for many months, the general public only recently became aware of this launch when the FCC launch license became available. Even then, the client was not known for a while. Ultimately, it was revealed that the provider of the payload was Northrop Grumman and that this was a government payload. The launch is scheduled for November 15 at 8 pm EST from LC-39A. Given the clandestine nature of the payload, it would be reasonable to expect that, again, the second stage cameras will not be made public. Falcon Heavy hold downs visible on the TEL with F9 booster (nasaspaceflight.com) Zuma will be the last launch this year from LC-39A which will shutdown immediately afterwards for some final modifications to support the new Falcon Heavy rocket. Originally, it was expected that once SLC-40 came back online, the LC-39A complex would have to be offline for about 60 days to complete modifications. SpaceX has, however, been doing everything they can in between launches to eliminate this down time. Recent photos have indicated that most of the hold downs for the FH are in place. Final modifications involve welding work on the TEL and additional plumbing and wiring. In December, SpaceX will return to SLC-40 for the launch of the CRS-13 ISS resupply mission. Once this pad is operational, it is expected that most single core missions will launch from there, with the exception of crew missions. If scheduling conflicts happen, though, the LC-39A TEL will be capable of supporting any single core launch. JCSAT-16 launching from SLC-40 in August 2016. This was the last launch from the pad before the testing anomaly ( Michael Seeley for We Report Space) At some point in late November, SpaceX hopes to raise the FH at the LC-39A launch pad for initial fitting tests. Following fit tests, SpaceX will perform a wet dress rehearsal of the maiden launch of the vehicle. This rehearsal will involve activating all of the launch systems and fueling the vehicle, with the option of continuing into a static fire test — a test where the engines are started and brought to full thrust and then shut down without releasing the rocket. These tests are vital for the success of the launch because much of the FH is new ground. The Falcon Heavy is in many ways three Falcon 9 rockets strapped together (although, there are many structural enhancements to the center core). The fueling, communications, and operation of the rocket systems as a single unit, though, has never been performed before. In fact, no US based company has ever started 27 rocket engines at the same time. Currently, the LC-39A launch pad is the only place where the FH can be assembled and tested, which necessitated that SLC-40 be back online before they proceeded with the FH launch. With the understanding of the complexity of the FH systems, SpaceX has budgeted enough time to perform at least two wet dress rehearsals to allow for any necessary corrections. The goal is to launch the Falcon Heavy this year with the current earliest date (NET) for launch being December 29. There is a possibility that it could “pull left” to an earlier date is everything goes better than expected, but many predict it will slip into early January. Artists conceptual image of Falcon Heavy launch (SpaceX) Regardless of the launch date, there is a lot of anticipation for a great maiden voyage. With 3–4 additional missions on their manifest for the Falcon Heavy, a lot is riding on the success what will be the most powerful operational rocket on the planet. What a better way to herald a new year full of crewed flights, multiple Falcon Heavy launches, and an anticipated 30 overall launches than to watch 2 (boosters) land by land and one (booster) land by sea. Chris Rogers is a SpaceX enthusiast and over all fan of privatized space flight. His goal is to author articles that make space related news and events approachable by lay persons and people just starting to follow the New Space industry. Would you like to learn more? Here are some great resources for SpaceX information: SpaceX Official Website / SpaceX Twitter Elon Musk Twitter SpaceX Instagram UNOFFICIAL Facebook SpaceX Enthusiast Group Fan-run SpaceX subreddit NASASpaceFlight.com SpaceX Forum

Rocketing ahead with SpaceX

Acknowledgments This post continues my exploration of concepts and techniques related to both the way so-called “Jewish times” (zmanim) are calculated; as well as the techniques needed to use the – a library of functions that let you easily calculate Jewish times. PHP Zmanim library Once again, I owe a huge debt of gratitude to several folks – including Eliyahu Hershfeld, creator of the , Zachary Weixelbaum (owner of the PHP Zmanim library, a port of Kosher Java), Elyahu Jacobi (who built with those tools and patiently explained so many concepts to me), and Maor Neim, who offered explanations that turned theory into practice. Kosher Java library RoyZmanim.com Introduction , I explored both the foundational concepts of Jewish time calculations (zmanim) and also the initial steps needed to install and use PHP Zmanim. We got as far as calculating sunrise with that library. In my last post By itself, this isn’t particularly impressive. The fact is that with the same information (latitude, longitude, time zone, and a specific date) you can get the same information using PHP’s built-in functions. In this post, we’re going to get into the types of calculations you CAN’T get with built-in PHP tools, not only because they require some “interesting” time manipulations, but because there are so many ways to calculate the same religiously significant moment, based on various Rabbinic opinions and traditions. The Answer to Every Jewish Question Starts With “Well, It Depends…” Let me take a minute to unpack that idea in a little more detail. In the last post, I started to get into this idea: Dawn is the moment when light (but not the sun) is visible over the horizon. Unfortunately, whether or not there is or isn’t “light” is highly subjective, and therefore the way it’s come to be calculated ranges all over the map. Some traditions use a fixed number of clock minutes before sunrise or after sunset. Others will use astronomy to identify the time when the sun is below the horizon by a specific number of degrees. Others will use a formula, such as taking the amount of daylight (from sunrise to sunset), dividing that into 10 equal parts, and then subtracting that amount from sunrise or adding it to sunset. Still others will take the time the sun is below the horizon on an “equal” day (meaning the spring or fall equinox, when the amount of sunshine and darkness are exactly the same), calculate the difference (in clock minutes) between that time and sunrise, normalize those minutes against “seasonal minutes” (“sha’ot zmaniyot”) for the specific day in question, and finally subtract that amount from sunrise (or add THAT to sunset) for the day in question. One moment of the day, but a wide variety of ways to determine it. It may be hard for those outside of mainstream orthodox Judaism to understand and is definitely the subject of a completely different type of blog post, but the answer is to embrace the understanding that all of the calculations above (and many others) are capital-T “True.” Not just in a “well, it’s how I feel about it so it’s true to me” kind of way, but as being absolutely, factually, empirically true even when one method stands in opposition to another (or several others). Like I said, THAT is the topic of a completely different blog post. For now, I mention this to explain why, in creating the , Eliyahu Hershfeld took the route of enabling the ability to easily calculate times using ANY of those methods, rather than trying to espouse a single method and coding exclusively for that. Kosher Java library And ports – such as Zachary Weixelbaum’s – simply continue with that ideal. PHP Zmanim library Which brings us back to the nitty-gritty of using the PHP Zmanim library. Making Time Pretty , we left off with this snippet of code: In the last post <?php
require 'vendor/autoload.php';
use PhpZmanim\Zmanim;
use PhpZmanim\Calendar\ComplexZmanimCalendar;
use PhpZmanim\Geo\GeoLocation;


# Set variables:
#41.4939407, -81.516709;
$locname = "Beit Knesset Chochmat Shlomo, Beachwood, OH";
$lat = 41.4939407;
$long = -81.516709;
$elev = 0;
$tz = 'America/New_York';

$getyear = 2024;
$getday = 20;
$getmonth = 12;
$testzmanim = Zmanim::create($getyear, $getmonth, $getday, $locname, $lat, $long, $elev, $tz);
$sunrise = $testzmanim->sunrise;
echo "$sunrise\n";
?> Which produced a result that looked something like this: 2024-12-20 07:48:52 It works, but it’s not what I’d want to see on a page when I’m just expecting a simple “7:48 am”. Which brings me to the next interesting insight for the PHP Zmanim library: You can format the output using another function, rather than hammering through PHP’s built-in options. You’ll still use the but getting what you want is easier. PHP time/date formatting codes Let’s say I want to only display the hour, minute, and am/pm for the sunrise output. I’d add a line like this: $sunrise = $zmanim->sunrise;
$sunrise = $sunrise->format('g:i a'); Which would look like this when printed on the screen: 7:48 am Getting Your First Actual real-time – Mincha Gedola The problem with using sunrise/sunset as an example is that PHP has built-in options to do the exact same thing. So, let’s look at getting a time that is more relevant to Jewish religious times: the earliest time for afternoon prayers (Mincha Gedola). Once again, it’s somewhat anti-climactic in that it’s a single command: $gedolah = $zmanim->minchaGedola; Which outputs a time like this: 2024-12-20 12:46:55 HOWEVER, as I mentioned earlier in this post, there are several ways to calculate this time. Here are all the methods supported by the PHP Zmanim library: minchaGedola: Returns a time of 6.5 halachic hours (shaos zmaniyos) after sunrise. minchaGedola30Minutes: Returns the time 30 standard (clock) minutes after the half-day calculation (chatzot). minchaGedola72Minutes: Calculates according to the Magen Avraham (Abraham Abele Gombiner, 1635-1682) with the day starting 72 minutes before sunrise and ending 72 minutes after sunset. minchaGedola16Point1Degrees: Calculated according to the Magen Avraham with the day starting and ending when the sun is 16.1 degrees below the horizon. minchaGedolaAhavatShalom: Calculated based on the opinion of as half a seasonal hour (shaah) after mid-day (chatzos) with seasonal minutes (shaos zmaniyos) calculated based on a day starting 72 minutes before sunrise and ending 13.5 minutes after sunset. Rabbi Yaakov Moshe Hillel minchaGedolaGreaterThan30: This is a convenience method that returns the later of the standard “minchaGedola” function or ‘minchaGedola30Minutes. In the winter when 1/2 of a seasonal hour (sha’ah) is less than 30 minutes, then minchaGedola30Minutes will be returned, otherwise, the regular minchaGedola will be returned. minchaGedolaAteretTorah: This method returns the time of according to the Magen Avraham with the day starting and ending when the sun is 16.1 degrees below the horizon. mincha ketana minchaGedolaBaalHatanya: This calculation is based on the opinion of the . Baal Hatanya minchaGedolaBaalHatanyaGreaterThan30: This is a convenience method that returns the later of either minchaGedolaBaalHatanya or minchaGedola30Minutes. In the winter when 1/2 of a seasonal hour (sha’ah) is less than 30 minutes, then minchaGedola30Minutes will be returned, otherwise minchaGedolaBaalHatanya will be returned. minchaGedolaGRAFixedLocalChatzos30Minutes: This method returns a time based on opinion. Rav Moshe Feinstein’s As you can see, there are a number of opinions. Determining which one you want/need to use is outside the scope of this blog post and will likely require some conversations with the users of the app or website, as well as a Rabbi. Or two. Or several. But the good news is that to use any of them, it’s as simple as: $gedolah = $zmanim->minchaGedola16Point1Degrees;
$gedolah = $gedolah->format('g:i a'); Getting Something Complicated – Nightfall (Tzais Hakochavim) Now that you’ve seen how we get one time, you should understand that even times that my previous post labeled as “complicated” aren’t that complicated. Furthermore, it should reinforce your understanding of just how powerful a tool like PHP Zmanim is because of what it enables you to do in such a short time. Calculating nightfall (tzais hakochavim) is as simple as the command $tzais = $zmanim->tzais; If there is any challenge at all, it’s the sheer number of variations to consider. I’m listing them here without explanation, just so you have a sense of how many there are. That’s right, there are 32 different options for calculating this one time. I list them here without detailed explanation simply to underscore my point: tzais tzais72 tzaisGeonim3Point7Degrees tzaisGeonim3Point8Degrees tzaisGeonim5Point95Degrees tzaisGeonim3Point65Degrees tzaisGeonim3Point676Degrees tzaisGeonim4Point61Degrees tzaisGeonim4Point37Degrees tzaisGeonim5Point88Degrees tzaisGeonim4Point8Degrees tzaisGeonim6Point45Degrees tzaisGeonim7Point083Degrees tzaisGeonim7Point67Degrees tzaisGeonim8Point5Degrees tzaisGeonim9Point3Degrees tzaisGeonim9Point75Degrees tzais60 tzaisAteretTorah tzais72Zmanis tzais90Zmanis tzais96Zmanis tzais90 tzais120 tzais120Zmanis tzais16Point1Degrees tzais26Degrees tzais18Degrees tzais19Point8Degrees tzais96 tzaisBaalHatanya tzais50 Time (and This Blog Series) Marches On Armed with the information in this post, you could probably make decent headway simply by looking through the main README on Zachary’s page itself, and selecting the best (for your purposes) calculations for: PHP Zmanim Sunrise and Sunset (no, do not sing ) That Song A “seasonal” hour (Sha’ah Zmanim) Dawn (alos hashachar) The earliest time to put on tallit and tefillin (misheyakir) The latest time to say Shema (sof zman kria shema) The latest time for morning prayers (sof zman tefillah) When Passover begins Halfway through the day (chatzos) The earliest time for afternoon prayers (mincha gedola) The “best” time for afternoon prayers (mincha ketana) The latest time for afternoon prayers (plag hamincha) The time to light Shabbat candles Dusk – the time between sunset and night (bain hashmashot) Night (tzais hakochavim) Halfway through the night (chatozs halayla) But there is still more to cover. In upcoming articles, I’ll talk about: Taking these standard times and adjusting them for synagogue specific needs (“Mincha starts 25 minutes before Shkia each day”). Using the PHP Zmanim library to display non-time calculations such as the weekly Torah Portion, Rosh Chodesh, and the Molad. Leveraging the build-in astronomy functions for time calculations that aren’t built into the library itself. I hope you’ll continue on this journey with me. As always if you have questions, comments, or kudos, please leave them in the comments.

Time Data Series: How to Work With PHP Zmanim

Time Data Series: Getting Started with PHP Zmanim - AdatoSystems Acknowledgments In this blog, I’m explaining concepts and techniques related to both the way so-called “Jewish times” (zmanim) are calculated, as well as the techniques needed to use the – a library of functions that let you easily calculate Jewish times. PHP Zmanim library The PHPZmanim library is maintained by Zachary Weixelbaum. As with so many things in tech today, PHP Zmanim is itself based on the foundational Kosher Java library by Eliyahu Hershfeld. I owe a huge debt of gratitude to both Zachary and Eliyahu – not only for the work they put into developing those libraries but also for the support they have given me as I came up to speed on both the technical and Jewish religious guidelines (halacha) needed to use them. Introduction “What time will afternoon prayers (Mincha) be this week?” is a deceptively complex question. It’s deceptive because “afternoon prayers” seems to be self-explanatory, but (as with so many things related to Jewish religious rules (halacha) there’s a vast amount of background, commentary, and specificity required. NOTE: If you are already comfortable with Jewish time concepts (zmanim), feel free to skip to the section labeled “Installing PHP Zmanim.” I won’t be insulted nor hold it against you. It’s difficult to understand the importance of accurate time calculations on the Jewish religious day, week, and life. It figures into everything from when a fast starts and ends to when it’s too late (or too early) to say certain prayers to the moment when simply owning (let alone eating) bread is forbidden. To put it another way, I’ll share a quote from Rabbi Abraham Joshua Heschel in his book “The Sabbath”, The meaning of the Sabbath is to celebrate time rather than space. Six days a week we live under the tyranny of things of space; on the Sabbath we try to become attuned to holiness in time. Rabbi Abraham Joshua Heschel, “The Sabbath” Even with that explanation, some readers may still wonder, “Why make such a big deal about it? Are you telling me God is going to hold it against you if you’re 5 minutes off?” It’s a valid question and worth a moment of discussion because otherwise, the need for, let alone the impact of, this blog (and the techniques and technologies it describes) is diminished. No, of course, God doesn’t care. Just like my track coach doesn’t “care” if I warm up before running, do my off-season workouts, or drink enough water. Let’s face it: no matter how hard I train, my coach won’t be any healthier. However, my coach – who cares for me beyond my performance in the next race, wants ME to care. They want me to be fully committed, if only because they know my experience will be more fulfilling because of it. In the same way, God doesn’t “care.” But we know (through the texts of the Torah and Talmud) that God wants the US to care. And so Jewish scholars through the millennia have attempted – using the evidence presented in the text – to eschew simple and simplistic answers and dig deeper to uncover the details. Back to the question at hand: “What time are afternoon prayers?” To understand that, we have to first understand what defines “day” (versus “night”), how to understand what demarcation separates “morning” from “afternoon,” how to effectively divide the day into parts, and so much more. While this blog will introduce some of these concepts and terms as needed, it should not be considered exhaustive by any stretch of the imagination. It comes as no surprise that computers have made quick work of calculating these times, and now there’s a wide array of websites and applications ready to do the job for us. Even for those who want to create their own programs to do these calculations, there are time-saving solutions in the form of code libraries like and its many ports, including , , , , , and many more. KosherJava PHP Swift .Net JavaScript Python Nevertheless, it’s important to understand the theory behind the tools. Anyone who wants to create a website or app has to be certain their program isn’t inadvertently giving the wrong times. While, as mentioned earlier, nobody will “go to hell” (so to speak) for praying at the wrong time, there is a strict commandment: וְלִפְנֵ֣י עִוֵּ֔ר לֹ֥א תִתֵּ֖ן מִכְשֹׁ֑ל וְיָרֵ֥אתָ מֵּאֱלֹהֶ֖יךָ“lifnei iver lo titein michshol v’yareita mei-elohecha”“Don’t put a stumbling block before the blind” (Leviticus 19:14) It’s one thing if an individual gets something wrong by accident. It’s quite another to provide bad information that causes someone (or worse, LOTS of folks) to make a mistake, believing the information they got (from your app) was accurate and trustworthy. The Basic Times With that in mind, we’ll start with understanding the times that are fairly straightforward and the least affected by variations in Jewish tradition: Sunrise (Netz Hachma) is a good old nautical sunrise – the moment when the top edge of the disk of the sun touches the horizon. Sunset (Shkia) is the other side of the daily coin – the moment when the top edge of the sun drops just below the horizon. A “seasonal hour” (sha’ah) refers to the even division of daylight, the time between sunrise and sunset. There are always 12 seasonal hours, but they may be longer or shorter than a regular (on your clock) hour because the amount of daylight fluctuates with the season. Note that some traditions calculate a sha’ah as 12 divisions of the time from dawn (alot hashachar, or just “alot” when light is visible over the horizon, but before sunrise itself) to night (tzeis hakochavim, or just “tzeis”, when NO light is visible over the horizon, after sunset). We’ll get more into both dawn (a lot) and night (tzeit) later in the blog. Seasonal minutes (sha’ot zmaniyot) is 1/60 of a seasonal hour and, just like a seasonal hour, may be larger or smaller than a minute on your clock. As you can see, sunrise and sunset form the fundamental core of all other time calculations, and a great number of important Jewish times during the day are derived directly from those. For example, in some traditions, you’ll find: Shabbat begins on Friday night, 18 minutes before sunset (shkia) Shabbat ends on Saturday night 45 (or 50, or 72) minutes after sunset (shkia) …and so on. Calculations where “It’s Complicated” Once you have sunrise and sunset nailed down, the next step is to identify the two critical times of dawn and night. Dawn (Alot haShachar, or just “Alot”) and night (Tzeis hakochavim, or just “Tzeis”) mirror each other the way sunrise and sunset do. Dawn is the moment when light (but not the sun) is visible over the horizon. Night is the moment when light is no longer visible. Unfortunately, whether or not there is or isn’t “light” is highly subjective, and therefore, the way it’s calculated ranges all over the map. Some traditions use a fixed number of clock minutes before sunrise or after sunset. Others will use astronomy to identify the time when the sun is below the horizon by a specific number of degrees. Others will use a formula, such as taking the amount of daylight (from sunrise to sunset), dividing that into 10 equal parts, and then subtracting that amount from sunrise or adding it to sunset. Still, others will take the time the sun is below the horizon on an “equal” day (meaning the spring or fall equinox, when the amount of sunshine and darkness are exactly the same), calculate the difference (in clock minutes) between that time and sunrise, normalize those minutes against “seasonal minutes” (“sha’ot zmaniyot”) for the specific day in question, and finally subtract that amount from sunrise (or add THAT to sunset) for the day in question. Sound confusing? As the title of this section says, “It’s complicated.” My point in describing these isn’t to settle on a single “correct” calculation but rather to help you understand the ultimate goal of each type of calculation – as well as for you to understand that there are multiple ways different Jewish traditions arrive at each calculation. The Complex times Once you have dawn (alot), sunrise (netz), sunset (shkia), and night (tzeis), it becomes possible to calculate other important daily times. These include: The earliest time for afternoon prayers (Mincha Gedola), which is often calculated as a certain number of seasonal hours (sha’ah) after either dawn or sunrise. The point of this time is that it is the earliest moment when “afternoon” (literally, after mid-day) happens. The preferable time for afternoon prayers (Mincha ketana), which is calculated as a larger number of seasonal hours (sha’ah) after either sunrise (netz) or dawn (alot). The point here is that it’s more than 3/4 of the way through the day, when it’s CLEARLY afternoon – but without the risk of it accidentally being night (tzeis). The latest time for afternoon prayers (Plag haMincha, or “plag”) , which is often calculated as the time between the best time for afternoon prayers (mincha ketana) and night (tzeis). While there are several other key times that we’ll get to in a different blog, these are enough to get us started. Installing the PHP Zmanim Library With those technical details taken care of, we can now move on to… some technical details! Except this time, they are TECHNICAL technical details. ( ) and for those people who skipped all the way from the introduction to this section, WELCOME! It’s great to have you back! PHP Zmanim is a complex library that comprises not just the import of Kosher Java into the PHP language but also some supporting modules like (a tool that helps make date and time conversions faster, easier, and more accurate); (a web design framework); and a few other smaller utilities. Carbon Symfony The point is that all those modules work in concert with PHP Zmanim, and you need all of them installed for anything to work. The easiest way to get them all installed is using the PHP utility that manages dependencies. “composer” If you need to run PHP Zmanim on a web server and don’t have access to run installers at the command line, you’re still in luck. Simply copy the ./vendor directory from a local installation, and – with some caveats – it will work. What are those caveats? The main one is to make sure the version of PHP supported by your hosting provider matches the one you use when installing via Composer. This brings me to the actual composer install command. I know we haven’t gotten to actually coding anything yet, but let’s set up a directory where the scripts are going to go. For this blog, I’m going to call it /phpzmanim_test. In a terminal window, move to that directory: cd /php zmanim_test Now type the command: composer -V (note that’s a capital V) This will confirm whether composer is installed or not. If not, do a quick search to find out the best way to get it installed on your operating system. Next, type the command: composer require zachweix/php-zmanim This will do two things: First, it will create the file in the current directory, with instructions that PHP Zmanim should be installed. composer.json It actually installs PHP Zmanim for you, into a ./vendor directory inside the current directory. No extra steps are needed. The only other “composer” related item to note is that if you ever need to update, you can do so easily by going into the /phpzmanim_test directory (or whatever you called yours) and typing the command . This will read the information in the composer.json file and update everything it finds there. composer update (SPOILER: this means you should NOT delete the composer.json file. You don’t, however, have to copy it to your remote site with the rest of your application if you don’t want to.) Once this is done, you need to include the following line in every PHP script that will use the PHP Zmanim library: require 'vendor/autoload.php'; Getting Started with PHP Zmanim Now that PHP Zmanim is installed, you’re ready to start writing some code with it. To do this, you’ll first create a php object – a collection (array, really) of data that are passed into various functions. This object contains both the specific date for the times you’ll want to pull and also the precise location information. Creating an object with “Zmanim::create()” Before you start, you’ll need to know a few things about the location where you are asking for times: The latitude and longitude. The time zone is formatted using the tz database format. (example: “America/New_York”). The elevation of that location, if you choose to use it. (SPOILER: very rarely does elevation factor into these calculations.) The year, month, and day of the times you’ll be calculating. The format for creating your object is: $VARNAME = Zmanim::create(YEAR, MONTH, DAY, "NAME OF LOCATION", LATITUDE, LONGITUDE, ELEVATION, "TIME ZONE"); Here’s a specific example: $zmanim = Zmanim::create(2019, 2, 21, "New York City", 40.850519, -73.929214, 200, "America/New_York"); What that looks like as a script with some variables in place of the literal input: <?php
require 'vendor/autoload.php';
use PhpZmanim\Zmanim;
use PhpZmanim\Calendar\ComplexZmanimCalendar;
use PhpZmanim\Geo\GeoLocation;

$getdate = date('Y-m-d');
$getyear = date('Y', strtotime($getdate));
$getmonth = date('m', strtotime($getdate));
$getday = date('d', strtotime($getdate));

$locname = "Beit Knesset Chochmat Shlomo, Beachwood, OH";
$lat = 41.4939407;
$long = -81.516709;
$elev = 0;
$tz = 'America/New_York';

$zmanim = Zmanim::create($getyear, $getmonth, $getday, $locname, $lat, $long, $elev, $tz); With that code in place, you have an object for today’s date, for the specified location. You can even print it out using PHP’s function: print_r() print_r($zmanim); Which should give you output that looks something like this: PhpZmanim\Zmanim Object
(
    [calendar:PhpZmanim\Calendar\AstronomicalCalendar:private] => Carbon\Carbon Object
        (
            [endOfTime:protected] => 
            [startOfTime:protected] => 
            [constructedObjectId:protected] => 00000000000000080000000000000000
            [localMonthsOverflow:protected] => 
            [localYearsOverflow:protected] => 
            [localStrictModeEnabled:protected] => 
            [localHumanDiffOptions:protected] => 
            [localToStringFormat:protected] => 
            [localSerializer:protected] => 
            [localMacros:protected] => 
            [localGenericMacros:protected] => 
            [localFormatFunction:protected] => 
            [localTranslator:protected] => 
            [dumpProperties:protected] => Array
                (
                    [0] => date
                    [1] => timezone_type
                    [2] => timezone
                ) (there’s more, but you get the idea). Getting your first real-time – Sunrise (Netz HaHachma) Once you have an object created, using it to get specific times through PHP Zmanim is almost anti-climactic. Getting sunrise is as simple as: $sunrise = $zmanim->sunrise; If you aren’t familiar with it or haven’t used it before, the indicates you’re querying an object (again, a collection of data elements) or using a built-in method. -> This will return something that looks like this: 2024-12-20 07:48:52 For those following along, the complete code so far looks like this: <?php
require 'vendor/autoload.php';
use PhpZmanim\Zmanim;
use PhpZmanim\Calendar\ComplexZmanimCalendar;
use PhpZmanim\Geo\GeoLocation;


# Set variables:
#41.4939407, -81.516709;
$locname = "Beit Knesset Chochmat Shlomo, Beachwood, OH";
$lat = 41.4939407;
$long = -81.516709;
$elev = 0;
$tz = 'America/New_York';

$getyear = 2024;
$getday = 20;
$getmonth = 12;
$testzmanim = Zmanim::create($getyear, $getmonth, $getday, $locname, $lat, $long, $elev, $tz);
$sunrise = $testzmanim->sunrise;
echo "$sunrise\n";
?> Summary There is a lot more to cover in PHP Zmanim, which I plan to do in the coming weeks. But this should at least get you started with building a PHP-based script or website and displaying accurate times for Jewish moments. As always, I welcome questions, corrections, and kudos in the comments below. Also published . here

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