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Everything You Need To Know About Tuesday’s Special Elections In Rhode Island And Utah

ABC News Photo Illustration Usually, Labor Day is considered the traditional start of campaign season — but here in 2023, it marks the end of the competitive phase of two heated special elections. Neither Rhode Island’s 1st Congressional District nor Utah’s 2nd is expected to be very competitive in November’s general elections, so Tuesday’s primaries will likely determine their new representatives. And whoever wins will have really worked for it; both primaries have had no shortage of drama. Races to watch: 1st Congressional District Polls close: 8 p.m. Eastern When Rep. David Cicilline resigned at the end of May to become president of the Rhode Island Foundation, he left behind a rare opening in a deep-blue district that President Biden carried 64 percent to 35 percent, according to Daily Kos Elections — and ambitious Democrats rushed in to fill the void. Twelve names are on the Democratic primary ballot on Tuesday, and the race has been so chaotic that at least four of them have a legitimate shot at winning. The early favorite was Lt. Gov. Sabina Matos, whose name recognition gave her a decent base of support (albeit only around 20 percent) in early polls of the race, while most other candidates were stuck in single digits. But in July, election officials in several towns flagged certain signatures on Matos’s nomination papers as potentially fraudulent — for example, they were from dead people or living people who said they never signed them. Matos still had enough valid signatures to make the ballot, but in the end, 559 of the 1,285 signatures she submitted were disqualified, and the state attorney general and state police are conducting a criminal investigation into whether fraud was committed (in Rhode Island, it is illegal to forge nomination signatures). Matos has blamed a campaign vendor for the snafu, but the scandal may have turned voters against her. According to internal polling from a rival campaign (so take it with a grain of salt), Matos’s net favorability rating among Democratic primary voters fell from +20 percentage points in June to -20 points in mid-August. Another early contender was businessman Don Carlson, who — thanks in large part to a $600,000 loan to his own campaign — had raised the most money of any candidate in the race as of Aug. 16 (nearly $970,000). But in late August, local news reported that Carlson had made romantic overtures to a student while a faculty member at Williams College. Carlson eventually admitted that the report was true, and he dropped out of the race on Aug. 27. In the wake of these scandals, two other candidates have emerged as possible front-runners. Former state Rep. Aaron Regunberg, who might be the governor of Rhode Island right now if 2,466 people had voted a different way,2 But Maloy, who has Stewart’s endorsement, won the party convention on June 24 to garner a spot on the primary ballot, an indication of her potential appeal to conservatives, as Utah GOP convention delegates tend to be more right-leaning than the primary electorate as a whole. Edwards and Hough each gathered enough signatures to qualify for the primary despite being eliminated at the convention. Limited polling and fundraising numbers do suggest Edwards has a potential edge. Edwards led an early August poll from Dan Jones & Associates/Deseret News/Hinckley Institute of Politics with 32 percent, while Hough and Maloy sat well back at 11 percent and 9 percent, respectively. But with about half of voters undecided, the survey may have said more about Edwards’s name recognition advantage than her final vote percentage in this race. She also raised the most money from individual contributors, tallying $368,000 compared to Maloy’s $250,000 and Hough’s $202,000, as of Aug. 16. On top of that, Edwards has loaned her campaign $300,000, allowing her to outdistance Hough in total fundraising (he’s loaned himself around $335,000). She entered the home stretch of the campaign with $228,000 in the bank, about two and a half times what Hough and Maloy each had. But the ideological divisions in this race could provide opportunities for Maloy or Hough to outdistance Edwards, who clearly occupies the moderate lane. After all, Edwards voted for Biden in 2020 — she did say in a recent debate that she regretted her vote — and worked to pass a resolution recognizing climate change in 2018. Meanwhile, Maloy and Hough have both criticized the indictments of Trump as politically motivated and taken firmly anti-abortion positions, although Maloy said she would potentially vote for a federal ban while Hough said it should be left to the states. Hough has also argued that he’d be the most reliable Republican in the race because he voted for Trump in both 2016 and 2020, a dig at Edwards’s Biden vote and a shot at Maloy for having failed to vote in 2020 or 2022. And similar to the Rhode Island primary, this race also has its own ballot drama. After Maloy won at the GOP convention, it was revealed that her failure to vote in the past two statewide elections had caused Utah’s election officials to mark her as an inactive voter and begin the process of deleting her from the voting rolls. In fact, Maloy had only updated her Utah voter registration three days after she filed her candidacy. She has argued that because she moved to Virginia while working for Stewart on Capitol Hill, she did not want to cast a potentially fraudulent ballot in the past two elections. Still, this revelation prompted one of the eliminated Republican candidates at the convention to sue to have Maloy removed from the ballot. But a state court denied that request, and Republican Lt. Gov. Deidre Henderson, the state’s chief elections officer, said Maloy properly filed for office. The state GOP also lacked any mechanism under party rules to undo Maloy’s convention victory, reported The Salt Lake Tribune, even as her credentials came under scrutiny. Despite her troubles, Maloy may have a shot at winning

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TUSMO : Solutions, quels sont les mots du 17 août 2025 ?

Entertainment Retrouvez les solutions TUSMO du 17 août 2025 afin de trouver plus facilement le Mot du Jour et la Suite du Jour. Entertainment Solution TUSMO du Mot du Jour du 17 août 2025 ? Tous les jours, à minuit, l’excellent site TUSMO.xyz vous propose de trouver le « MOT DU JOUR », lequel sera composé de six à onze lettres. Pour le 17 août 2025, le mot à trouver comprend huit lettres et commence par la lettre « A ».  Si vous voulez un indice pour le mot du jour, cliquez sur une lettre manquante. Si vous ne voulez pas chercher ou êtes à court d’idées, cliquez sur l’œil pour voir la solution TUSMO du 17 août 2025. Entertainment Solutions TUSMO de la Suite du Jour du 17 août 2025 ? La « SUITE DU JOUR » est un autre jeu proposé de manière quotidienne, cependant, à l’instar du « MOT DU JOUR » qui vous demandera de trouver un seul et unique mot, la suite, quant à elle, vous donnera l’occasion de chercher quatre mots de six, sept, huit et neuf lettres. Pour les amateurs de TUSMO qui auraient quelques difficultés à trouver l’un des quatre mots présents dans la Suite du Jour, voici les solutions TUSMO du 17 août 2025. Mot n°1 Mot n°2 Mot n°3 Mot n°4 Entertainment TUSMO, qu’est-ce que c’est ? Le jeu TUSMO reprend le concept de la très célèbre émission télévisée Motus, laquelle a été diffusée sur France 2 du début des années 1990 jusqu’à 2019. Pour celles et ceux qui n’auraient jamais entendu parler de Motus et de tous les dérivés apparus dernièrement sur Internet, les règles sont assez simples puisque les joueurs ont pour objectif de trouver un mot avec un nombre de lettres définies, en ayant pour seul et unique indice la première lettre de ce même mot. Bien entendu, les mots à deviner sont en français et doivent exister dans les dictionnaires courants. Les participants auront six essais pour tenter de trouver le mot. Chacune des propositions ne peut commencer que par la lettre imposée du jour. Une fois, la première proposition soumise, des lettres de couleurs apparaîtront. Les lettres ROUGES sont bien placées et au bon endroit. Les lettres JAUNES existent dans le mot mais sont mal placées. Les autres lettres ne sont pas présentes dans le mot du jour. Les plus perspicaces l’auront compris, mais ces indications sont primordiales pour trouver les mots le plus rapidement possible. Vous n’avez plus qu’à vous remuer les méninges ou alors à utiliser la solution donnée Read More

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All-star DB Jamal Peters, three other key players out for Hamilton Tiger-Cats vs Riders

Photo courtesy: Bob Butrym/RFB Sport Photography The Hamilton Tiger-Cats will be without several key starters when they face the Saskatchewan Roughriders on Saturday, including lockdown cornerback Jamal Peters. Peters (neck) is one of four players who have been placed on the one-game injured list this week. The 28-year-old has appeared in all nine games for the team this year at boundary corner, recording 36 defensive tackles and three interceptions. He was named an East Division all-star during his first season with Hamilton in 2024 after recording 38 defensive tackles and four interceptions. Also missing from the defensive side of the ball this week will be weak-side linebacker Ray Wilborn, who appears to have been made a healthy scratch after not being listed on the injury report. The Ball State product has made 38 defensive tackles and five special teams tackles this year. Safety Stavros Katsantonis (calf) has been listed as a game-time decision after missing practice all week. Kyler Fisher will step up into the starting linebacking unit after making five defensive tackles and seven special teams tackles in seven games as a backup. Rookie Zamari Walton will make his debut at boundary corner, while 2025 fourth-round pick Ty Anderson will dress for depth at defensive tackle. The biggest loss could be that of returner Isaiah Wooden (shoulder), who leads the CFL in both punt and kick return average while scoring three total touchdowns. Defensive back Quavian White will dress for the first time and handle those duties. On offence, Canadian running back Johnny Augustine (hip) will sit out, with American Kevin Brown making his first appearance for Hamilton after stops in Edmonton and Toronto. The Hamilton Tiger-Cats (6-3) will visit the Saskatchewan Roughriders (7-1) at Mosaic Stadium on Saturday, August 16 with kickoff slated for 3:00 p.m. EDT. The Tiger-Cats had their six-game winning streak snapped by the B.C. Lions this past week, while the Roughriders were on a bye. The weather forecast in Regina calls for a high of 25 degrees with a mix of sun and cloud. The game will be broadcast on TSN and CTV in Canada, CBS Sports Network in the United States, and CFL+ internationally. Radio listeners can tune-in on the Ticats Audio Network in Hamilton and 620 CKRM in Regina. Graphic courtesy: Hamilton Tiger-Cats Read More

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Markram moves up to accommodate destructive Brevis and Stubbs in batting order

South Africa captain Aiden Markram has moved to the openers’ slot in the T20Is. The move is aimed at supporting more destructive options in the middle order. Aiden Markram opens up on his position shift in T20I cricket. (Courtesy: AP) New Delhi, UPDATED: Aug 16, 2025 12:37 IST South Africa T20I captain Aiden Markram has

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Best Practices for Building Agentic AI Systems

I’ve been experimenting with adding AI agents to UserJot, our feedback, roadmap, and changelog platform. Not the simple “one prompt, one response” stuff. Real agent systems where multiple specialized agents communicate, delegate tasks, and somehow don’t crash into each other. The goal was to analyze customer feedback at scale. Find patterns across hundreds of posts. Auto-generate changelog entries. Things that were basically impossible to do manually. I spent weeks reverse engineering tools like Gemini CLI and OpenCode, running experiments, breaking things, fixing them, breaking them again. Just pushed a basic version to production as beta. It’s working. Mostly. Here’s what I learned about building agent systems from studying what works in the wild and testing it myself. The Two-Tier Agent Model That Actually Works Forget complex hierarchies. You need exactly two levels: Primary Agents handle the conversation. They understand context, break down tasks, and talk to users. Think of them as project managers who never write code. Subagents do one thing well. They get a task, complete it, return results. No memory. No context. Just pure function execution. I tried three-tier systems. Four-tier systems. Agents talking to agents talking to agents. It all breaks down. Two tiers is the sweet spot. Here’s what I landed on: User → Primary Agent (maintains context) ├─→ Research Agent (finds relevant feedback) ├─→ Analysis Agent (processes sentiment) └─→ Summary Agent (creates reports) Each subagent runs in complete isolation. The primary agent handles all the orchestration. Simple. Stateless Subagents: The Most Important Rule Every subagent call should be like calling a pure function. Same input, same output. No shared memory. No conversation history. No state. This sounds limiting until you realize what it gives you: Parallel execution: Run 10 subagents at once without them stepping on each other Predictable behavior: Same prompt always produces similar results Easy testing: Test each agent in isolation Simple caching: Cache results by prompt hash Here’s how I structure subagent communication: // Primary → Subagent { “task”: “Analyze sentiment in these 50 feedback items”, “context”: “Focus on feature requests about mobile app”, “data”: […], “constraints”: { “max_processing_time”: 5000, “output_format”: “structured_json” } } // Subagent → Primary { “status”: “complete”, “result”: { “positive”: 32, “negative”: 8, “neutral”: 10, “top_themes”: [“navigation”, “performance”, “offline_mode”] }, “confidence”: 0.92, “processing_time”: 3200 } No conversation. No “remember what we talked about.” Just task in, result out. Task Decomposition: How to Break Things Down You’ve got two strategies that work: Vertical decomposition for sequential tasks: “Analyze competitor pricing” → 1. Gather pricing pages 2. Extract pricing tiers 3. Calculate per-user costs 4. Compare with our pricing Horizontal decomposition for parallel work: “Research top 5 competitors” → ├─ Research Competitor A ├─ Research Competitor B ├─ Research Competitor C ├─ Research Competitor D └─ Research Competitor E (all run simultaneously) The trick is knowing when to use which. Sequential when there are dependencies. Parallel when tasks are independent. Mix them when needed. I’m using mixed decomposition for feedback processing: Phase 1 (Parallel): Categorize feedback, extract sentiment, identify users Phase 2 (Sequential): Group by theme → Prioritize by impact → Generate report Works every time. Communication Protocols That Don’t Suck Your agents need structured communication. Not “please analyze this when you get a chance.” Actual structured protocols. Every task from primary to subagent needs: Clear objective (“Find all feedback mentioning ‘slow loading’”) Bounded context (“From the last 30 days”) Output specification (“Return as JSON with id, text, user fields”) Constraints (“Max 100 results, timeout after 5 seconds”) Every response from subagent to primary needs: Status (complete/partial/failed) Result (the actual data) Metadata (processing time, confidence, decisions made) Recommendations (follow-up tasks, warnings, limitations) No ambiguity. No interpretation. Just data. Agent Specialization Patterns After studying OpenCode and other systems, I’ve found three ways to specialize agents that make sense: By capability: Research agents find stuff. Analysis agents process it. Creative agents generate content. Validation agents check quality. By domain: Legal agents understand contracts. Financial agents handle numbers. Technical agents read code. By model: Fast agents use Haiku for quick responses. Deep agents use Opus for complex reasoning. Multimodal agents handle images. Don’t over-specialize. I started with 15 different agent types. Now I have 6. Each one does one thing really well. Orchestration Patterns We Actually Use Here are the four patterns that handle 95% of cases: Sequential Pipeline Each output feeds the next input. Good for multi-step processes. Agent A → Agent B → Agent C → Result I use this for report generation: gather data → analyze → format → deliver. MapReduce Pattern Split work across multiple agents, combine results. Good for large-scale analysis. ┌→ Agent 1 ─┐ Input ─┼→ Agent 2 ─┼→ Reducer → Result └→ Agent 3 ─┘ This is my go-to for feedback analysis in UserJot. When someone’s feedback board gets 1000+ posts (happens more than you’d think), I split them across 10 agents, each processes 100, then combine results. Takes 30 seconds instead of 5 minutes. Users get instant insights about what their customers actually want. Consensus Pattern Multiple agents solve the same problem, compare answers. Good for critical decisions. ┌→ Agent 1 ─┐ Task ─┼→ Agent 2 ─┼→ Voting/Merge → Result └→ Agent 3 ─┘ I use this for sentiment analysis on important feedback. Three agents analyze independently, then we take the majority vote. Catches edge cases single agents miss. Hierarchical Delegation Primary delegates to subagents, which can delegate to sub-subagents. Good for complex domains. Primary Agent ├─ Subagent A │ ├─ Sub-subagent A1 │ └─ Sub-subagent A2 └─ Subagent B Honestly, I rarely use this. Sounds good in theory, becomes a debugging nightmare in practice. Stick to two levels max. In my beta version, I mostly use MapReduce for feedback analysis and Sequential for report generation. The fancy stuff rarely gets used. Context Management Without the Mess How much context should subagents get? Less than you think. Level 1: Complete Isolation: Subagent gets only the specific task. Use this 80% of the time. Level 2: Filtered Context: Subagent gets curated relevant background. Use when

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Rabid fox attacks 2 people in same day in North Carolina

Please upgrade your browser to view usatoday.com usatoday.com wants to ensure the best experience for all of our readers, so we built our site to take advantage of the latest technology, making it faster and easier to use. Unfortunately, your browser is not supported. Please download one of these browsers for the best experience on usatoday.com Google Chrome Mozilla Firefox Opera Microsoft Edge Safari Read More

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Battlefield 6 Open Beta Sees Strong Second Weekend Despite Early Issues

Battlefield 6 Is Going Strong The second weekend of Battlefield 6 open beta is underway, drawing in massive numbers of players while the development team works to iron out a few early issues. Battlefield Studios confirmed that some players have faced “ongoing matchmaking issues” in certain playlists. The team said, “We’re actively investigating this and working towards a solve as soon as possible. Hang tight while we dig into this!”   Those using the EA App can try pressing the “Repair” button as a temporary fix while a broader solution is in progress. Another issue affects PC players, as DLSS/DLAA features are currently unavailable. The developers have pinpointed the problem and are working on a resolution. Technical snags have not dampened enthusiasm on Steam, where the open beta reached a peak of more than 300,000 concurrent players on August 14. The test period will continue until August 17, giving fans more time to explore the latest additions. For its second weekend, the beta introduces Empire State, a new map that brings fresh scenery and tactical possibilities. A “Custom Search” option has also been added, allowing players to refine their matchmaking preferences for a more tailored experience. With such high engagement numbers, the beta is offering the developers valuable feedback ahead of launch. The full release of Battlefield 6 is on October 10, arriving on PlayStation 5, Xbox Series X|S, and PC. If the open beta’s reception is any indication, the game is on track for a strong debut, provided the remaining technical hurdles are cleared in time. If you want to find out what we think about its multiplayer features, check out our article on it, along with the videos right here! SOURCE Read More

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Grayscale Launches DeepBook and Walrus Trusts to Tap Sui Ecosystem Growth

The Grayscale DeepBook Trust and Grayscale Walrus Trust offer accredited investors direct exposure to two core Sui blockchain protocols. DeepBook has processed over US$10B (AU$15.35B) in trades, while Walrus raised US$140M (AU$214.84M) for scalable, privacy-focused on-chain data storage. Sui’s DeFi activity reached a record US$2.3B (AU$3.53B) TVL in July, with both tokens carrying volatility and technical risk warnings. Crypto asset manager Grayscale has launched two new single-asset trusts designed to give accredited investors direct exposure to DeepBook (DEEP) and Walrus (WAL), both native protocols of the Sui blockchain. Named the Grayscale DeepBook Trust and Grayscale Walrus Trust, the products will hold only DEEP and WAL tokens, respectively. The trusts can be subscribed to daily via private placement by eligible investors. Rayhaneh Sharif-Askary, Grayscale’s head of product and research, said the trusts “offer investors exposure to two key protocols driving innovation within the Sui ecosystem.” DeepBook and Walrus provide infrastructure designed for high-performance on-chain liquidity and data, helping power the next wave of scalable, real-world blockchain applications. Rayhaneh Sharif-Askary, Head of Product and Research at Grayscale Related: Grayscale: Bitcoin ETF Approval Is a ‘Matter of When, Not If’ Protocol capabilities DeepBook acts as a central limit order book within the Sui network, providing a liquidity foundation for decentralised finance services. It has processed more than US$10 billion (AU$15.35 billion) in trades.  Walrus is a data storage system built for on-chain scalability and privacy, with applications in gaming, social media, and AI data hosting. The Walrus Foundation raised US$140 million (AU$214.84 million) in March 2025. Since its May 2023 debut by Mysten Labs, Sui has been built to handle high transaction throughput and low latency through parallel processing. Its DeFi activity hit a record total value locked (TVL) of US$2.3 billion (AU$3.53 billion) on 28 July before dropping to US$2.2 billion (AU$3.37 billion). Grayscale warned that DEEP and WAL are relatively new and subject to significant risks, including extreme volatility and technical issues. At present, DEEP is valued at US$0.15 (AU$0.23) with a US$372 million (AU$570.88 million) market capitalisation, while WAL is priced at US$0.40 (AU$0.61) and capitalised at US$559 million (AU$857.84 million). Grayscale, founded in 2013, oversees more than US$35 billion (AU$53.71 billion) across a range of crypto investment products. Related: Sui Hits All-Time High Amid Strategic Partnership Announcement Read More

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