Repreve maker Unifi launches extremely durable recycled yarn Fortisyn
'Fabrics containing Fortisyn can withstand exposure to harsh elements and rough handling while maintaining their form, function and appearance over time,' states Unifi in a press release. 'In collaboration with mills and strategic partners, Fortisyn has undergone rigorous fabric testing to validate its exceptional performance. The launch marks a step forward in the scaling of recycled, circular technology yarns into the most durable applications,' adds Unifi CEO Eddie Ingle. 'A step forward in scaling recycled, circular technology yarns"
Fortisyn is available in nylon 6,6 and Repreve Nylon, a recycled type 6, circular nylon made from post-industrial yarn waste. The latter is fully traceable with FiberPrint technology and certified by U-Trust, along with Oeko-Tex, GRS and SCS certifications for recycled content.
In addition to its durability and abrasion resistance, Fortisyn comes with solution-dyed capability for enhanced colourfastness. It is available globally and in combination with other yarn technologies from Unifi.
The company is currently showcasing Fortisyn at Techtextil North America in Atlanta until 8th May.
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Geeky Gadgets
a day ago
- Geeky Gadgets
Build a Smarter Home Lab Without Breaking the Bank or the Planet
Have you ever wondered if your home network could do more—without guzzling electricity or breaking the bank? Imagine a setup where your devices hum along efficiently, your network is secure and segmented, and automation takes care of repetitive tasks—all while keeping your energy footprint minimal. The truth is, you don't need a sprawling, power-hungry server farm to achieve this. With the right mix of low-power hardware and smart configurations, you can build a home lab that's not only high-performing but also sustainable and cost-effective. Whether you're an AI enthusiast, a networking hobbyist, or simply someone who loves tinkering with tech, the possibilities are endless. In this overview, Hill Phantom explore how to design a home lab that balances efficiency, functionality, and scalability. You'll discover why energy-efficient devices like Raspberry Pis are fantastic options, how VLANs can boost your network's security and organization, and why repurposing old hardware is both practical and eco-friendly. We'll also touch on the UniFi ecosystem and its ability to simplify network management for users of all skill levels. By the end, you'll have a roadmap to create a setup that's as powerful as it is mindful—proof that practicality can outshine extravagance. What could your home lab achieve if it worked smarter, not harder? Energy-Efficient Home Lab Tips The Importance of Energy Efficiency Energy efficiency is a critical consideration when designing your home lab. High-power systems may deliver impressive performance, but they come with significant drawbacks, such as increased electricity costs and a larger carbon footprint. Instead of prioritizing raw power, adopting a more sustainable and practical approach can yield better long-term results. For example, low-power devices like Raspberry Pis are excellent for hosting applications without consuming excessive energy. These compact and versatile devices allow you to maintain a reliable and functional setup while reducing your environmental impact. By prioritizing energy-efficient hardware, you can achieve a balance between performance and sustainability. Smart Hardware Choices for a Cost-Effective Setup Building a home lab that is both cost-effective and efficient does not require sacrificing performance. Thoughtful hardware choices can help you achieve your goals while staying within budget. Consider the following options: Raspberry Pi: These compact devices are ideal for running self-hosted applications, such as media servers or home automation tools. Their low power consumption and affordability make them a popular choice for home labs. These compact devices are ideal for running self-hosted applications, such as media servers or home automation tools. Their low power consumption and affordability make them a popular choice for home labs. Repurposed Devices: Older hardware, such as outdated laptops or routers, can be reconfigured to serve specific roles in your network. This approach reduces e-waste and extends the lifespan of your devices. Older hardware, such as outdated laptops or routers, can be reconfigured to serve specific roles in your network. This approach reduces e-waste and extends the lifespan of your devices. UniFi Cloud Key Ultra: This device offers a balance between simplicity and performance, providing streamlined network management with robust features and a user-friendly interface. By using these options, you can create a home lab that is both practical and environmentally conscious. How to Build an Energy-Efficient Raspberry Pi Home Lab Watch this video on YouTube. Stay informed about the latest in Home Labs by exploring our other resources and articles. Enhancing Security and Performance with VLANs A well-structured network is essential for maintaining security and optimizing performance. VLANs (Virtual Local Area Networks) allow you to segment your network into distinct zones, improving both organization and security. Common VLAN configurations include: Trusted: Reserved for personal devices like laptops and smartphones. Reserved for personal devices like laptops and smartphones. Untrusted: Designated for guest devices or those requiring limited access. Designated for guest devices or those requiring limited access. IoT: Dedicated to smart home gadgets, which often have weaker security protocols. Dedicated to smart home gadgets, which often have weaker security protocols. Default LAN: Used for general-purpose devices. This segmentation isolates sensitive devices from less secure ones, reducing the risk of unauthorized access. Configuring firewall rules between VLANs can further enhance security by controlling how devices communicate across the network. For instance, you can restrict IoT devices from accessing your primary network, minimizing potential vulnerabilities. Maximizing the Utility of Your Hardware Dual-purpose hardware can significantly improve the efficiency of your home lab. For example, a gaming PC equipped with a powerful GPU can handle both gaming and computational tasks, such as training machine learning models or running simulations. This approach reduces the need for additional hardware, saving both money and energy. Repurposing existing devices is another effective strategy. Older routers, switches, or even laptops can often be reconfigured to perform specific roles within your network. By extending the usefulness of these devices, you can reduce waste and optimize your setup without incurring additional costs. The UniFi Ecosystem: Simplified Network Management The UniFi ecosystem provides a cohesive solution for managing your home network. With devices such as managed switches, access points, and the UniFi Cloud Key, you can create a streamlined and easily manageable setup. Key advantages of the UniFi ecosystem include: Intuitive Software: Simplifies tasks like monitoring traffic, configuring VLANs, and managing connected devices. Simplifies tasks like monitoring traffic, configuring VLANs, and managing connected devices. Advanced Gateway Features: Offers tools for optimizing network security and performance. Offers tools for optimizing network security and performance. Scalability: Enables you to expand your network as your needs evolve. By adopting the UniFi ecosystem, you can achieve a professional-grade network setup without the complexity of more advanced systems, making it an excellent choice for both beginners and experienced users. Practicality Over Extravagance High-end home labs may appear impressive, but they are often unnecessary for most users. Extravagant setups with excessive hardware can be intimidating, costly, and environmentally wasteful. Instead, focus on practicality and functionality. A modest, well-designed home lab can meet your needs without the expense or environmental impact associated with more elaborate systems. Future-Proofing Your Home Lab As technology continues to evolve, it is important to ensure your home lab remains adaptable and relevant. Here are some strategies for future-proofing your setup: Repurpose Older Hardware: Devices like a PFSense router can be reconfigured to extend their usefulness, reducing the need for new purchases. Devices like a PFSense router can be reconfigured to extend their usefulness, reducing the need for new purchases. Invest in Energy-Efficient Devices: Select hardware that aligns with your specific requirements while minimizing energy consumption. Select hardware that aligns with your specific requirements while minimizing energy consumption. Start Small and Scale: Begin with essential components, such as a Raspberry Pi or a UniFi access point, and expand your setup as your needs grow. This approach ensures your home lab remains practical, cost-effective, and capable of adapting to future demands. Building a Sustainable Home Lab Designing a low-power, high-performance home lab is entirely achievable with thoughtful planning and resourceful choices. By prioritizing energy efficiency, using VLANs for network segmentation, and repurposing existing devices, you can create a sustainable and functional setup. Avoid the temptation of extravagant systems and focus on practicality to build a home lab that meets your needs while remaining environmentally responsible. Media Credit: HillPhantom Filed Under: DIY Projects, Guides, Hardware Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Reuters
3 days ago
- Reuters
Japan's Topix hits record high on Wall Street rally, solid earnings
TOKYO, Aug 7 (Reuters) - Japan's Topix index touched a record high on Thursday, tracking strong overnight gains on Wall Street, while solid corporate earnings from domestic firms reinforced expectations of wage growth. The broader Topix (.TOPX), opens new tab was up nearly 1% at 2,993.14, as of 0206 GMT. Earlier in the session, the benchmark index hit an all-time peak of 2,993.21. The Nikkei (.N225), opens new tab climbed 0.9% to 41,151.07. Both indexes were on track for a third consecutive session of gains, provided the current momentum holds. The three-day rally follows a sharp decline on Monday, when the Nikkei posted its largest drop in two months amid growing concerns over the U.S. economy and trade. "The market is now convinced that the U.S. economy will not slow down," said Hiroyuki Ueno, chief strategist, Sumitomo Mitsui Trust Asset Management. "That is important for the Bank of Japan's decision process for raising interest rates. With solid corporate earnings results and a trend for wage increases, the market now expects the BOJ to raise rates by the end of the year," Ueno said. However, government data released on Wednesday indicated that Japan's real wages fell for a sixth consecutive month in June, as inflation continued to outpace pay growth. The trend clouded the outlook for a BOJ policy shift, with wage growth seen as a key indicator for sustainable inflation. There is growing expectation that the U.S. Federal Reserve could begin cutting interest rates as early as September to support the economy. Shares of Mitsubishi UFJ Financial Group (8306.T), opens new tab rose 1.8%, providing the biggest boost to the Topix, while Sumitomo Mitsui Financial Group (8316.T), opens new tab gained 1.56%. M3's shares surged 22% after Goldman Sachs raised the target price for the medical services platform operator to 2,300 yen from 2,250 yen. Cosmetic maker Shiseido (4911.T), opens new tab jumped 10%. Chip-making equipment maker Tokyo Electron (8035.T), opens new tab fell for a third day, falling 2.7% on Thursday to weigh on the Nikkei the most. Chip-testing equipment maker Advantest (6857.T), opens new tab fell 0.7%. Shares of chipmakers declined on concerns over a potential slowdown in global chip production after U.S. President Donald Trump said Washington would impose a tariff of about 100% on semiconductor chips imported from countries not producing in America or planning to do so. Of the more than 1,600 stocks trading on the Tokyo Stock Exchange's Prime Market, 70% advanced and 26% fell, and 3% were flat.
Coin Geek
3 days ago
- Coin Geek
AI automation: Navigating risks, preserving trust
Getting your Trinity Audio player ready... Blockchain enterprises are built on promises of trust, transparency, and decentralized integrity. However, the growing infusion of artificial intelligence (AI) automation into blockchain-based workflows presents unforeseen risks that can threaten these foundational principles. Recent incidents reveal how automation, while powerful, can inadvertently lead to ethical lapses, cognitive erosion, and trust degradation, especially in sectors that rely on blockchain for authenticity. The stakes are increasingly high: enterprises face a 50% increase in AI-powered cyberattacks in 2024 compared to 2021, with 93% of security leaders anticipating daily AI-driven attacks by 2025. AI's deceptive side meets blockchain's promise of integrity Blockchain technology's inherent strength lies in its immutability and decentralization—principles designed to bolster trust. Yet, integrating unchecked AI automation can inadvertently weaken the very fabric that blockchain technology aims to reinforce. A glaring example recently surfaced when a company accidentally sent a job rejection email containing raw AI prompts: 'warm but generic rejection email' that was 'polite yet firm.' While not blockchain-specific, this incident underscores the hidden dangers of automating sensitive interactions. For blockchain enterprises, even small breaches of authenticity risk substantial reputation damage—particularly when 73% of enterprises have experienced at least one AI-related security breach in 2025, costing an average of $4.8 million each. The challenge deepens when considering that the very capabilities making generative AI valuable—its ability to process and synthesize vast datasets—also create unique security vulnerabilities not addressed by traditional frameworks. Automation overreach: Blockchain & cognitive erosion Blockchain enterprises increasingly leverage platforms like n8n and Zapier for workflow automation—especially smart contract execution, token transfers, and data verification. While practical, excessive reliance can degrade human cognitive skills critical to effective decentralized governance. Recent MIT Media Lab research provides compelling evidence of this risk. In their study of 54 adults, researchers found that ChatGPT users showed the lowest neural activity and connectivity, indicating significant under-engagement in cognitive processes compared to Google search users or those writing unaided. Over time, ChatGPT users became increasingly reliant on copy-pasting generated content, reflecting a decline in independent effort and critical thinking. For blockchain enterprises built on transparency and collective decision-making, this cognitive erosion undermines governance quality, potentially introducing vulnerabilities or oversight gaps. The implications are particularly concerning for younger stakeholders, as early and frequent reliance on AI tools might stunt the development of essential cognitive skills such as critical thinking and problem-solving. Ethical automation in decentralized environments The emergence of controversial startups such as Cluely, which raised $5.3 million in seed funding and later secured $15 million from Andreessen Horowitz, spotlights ethical pitfalls in AI adoption. Cluely enables users to receive real-time, hidden assistance during exams, job interviews, and sales calls—essentially automating deception at scale. Co-founded by students suspended from Columbia University for developing an AI tool to help software engineers cheat on technical interviews, Cluely represents a troubling normalization of AI-enabled dishonesty. Enterprises must guard against similar misuses of AI within blockchain-based systems, particularly in trust-dependent contexts such as governance votes, decentralized autonomous organizations (DAOs), or blockchain audits. Blockchain is built on consensus and genuine participation. Introducing AI-driven 'shortcuts' or manipulations compromises the authenticity that blockchain guarantees, creating what researchers call 'garbage in, garbage forever' problems, where blockchain immutably records whatever data it receives, regardless of correctness. TrustTech: The blockchain antidote to AI deception Fortunately, solutions to AI deception are emerging, aligning closely with blockchain principles. A new market segment dubbed 'TrustTech' combines AI detection with blockchain verification to create authenticity verification platforms. These systems use advanced AI models to analyze and detect potential forgeries, synthetic data, or manipulated inputs before they are submitted to blockchain networks. TrustTech solutions create a 'trust bridge' between theoretical decentralized trust and real-world reliable verification by combining AI to verify the initial validity of data and blockchain to secure its integrity. Blockchain enterprises have a unique opportunity to leverage their own technology's transparent nature, coupling it with TrustTech tools to validate human authenticity and mitigate deception in decentralized workflows. Conscious stack design for blockchain enterprises To manage these complex risks, blockchain enterprises could benefit from frameworks like Conscious Stack Design™, focusing on intentional, ethical automation: Stack Mapping : Visualize every tool or automated process within your blockchain operations, understanding that blockchain technology is increasingly used for governance, risk, and compliance (GRC), providing unmatched transparency and security.⁷ : Visualize every tool or automated process within your blockchain operations, understanding that blockchain technology is increasingly used for governance, risk, and compliance (GRC), providing unmatched transparency and security.⁷ 5:3:1 Rule : Limit tools and automated processes strictly (5 per distinct category, 3 active, 1 anchor), ensuring human oversight and mastery. Particularly crucial given that AI adoption has grown by 187% (2023-2025) while security spending only increased by 43% in the same period. : Limit tools and automated processes strictly (5 per distinct category, 3 active, 1 anchor), ensuring human oversight and mastery. Particularly crucial given that AI adoption has grown by 187% (2023-2025) while security spending only increased by 43% in the same period. Stack Maturity Alignment : Understand what 'level' your tools or process stacks are at. Shift from fragmented automation towards strategic coherence and ethical integrity, supporting anti-money laundering (AML) and know-your-customer (KYC) protocols.⁷ : Understand what 'level' your tools or process stacks are at. Shift from fragmented automation towards strategic coherence and ethical integrity, supporting anti-money laundering (AML) and know-your-customer (KYC) protocols.⁷ Ethics Gateway: Prioritize ethical and authenticity audits alongside technical ones, as adoption of blockchain is not just optional but necessary for enterprises seeking to protect sensitive data and mitigate risk while building stakeholder trust. Enterprise opportunities: Preserving blockchain integrity Blockchain companies positioned to capitalize on emerging TrustTech and conscious automation markets can differentiate significantly: Human-in-the-Loop Solutions : Blend AI's capabilities with human oversight, enhancing transparency and accountability—essential given that AI transparency agents are emerging to enhance trust and accountability in AI systems. : Blend AI's capabilities with human oversight, enhancing transparency and accountability—essential given that AI transparency agents are emerging to enhance trust and accountability in AI systems. Blockchain-Backed Trust Verification : Develop products that leverage blockchain's immutable records and decentralized verification to combat AI deception directly, using cryptographic hashing and zero-knowledge proofs (ZKPs) for privacy and cross-platform compatibility. : Develop products that leverage blockchain's immutable records and decentralized verification to combat AI deception directly, using cryptographic hashing and zero-knowledge proofs (ZKPs) for privacy and cross-platform compatibility. Blockchain Automation Audits: Offer specialized services auditing automation stacks within decentralized enterprises, ensuring operational integrity while addressing the gap between rapid AI adoption and security controls. The strategic imperative: Maintaining trust in automation Blockchain enterprises face a strategic imperative to balance AI's efficiency with ethical rigor. With financial services facing the highest regulatory penalties (average $35.2 million per AI compliance failure), the cost of getting this balance wrong continues to escalate. Automation is an invaluable tool, but must remain consciously deployed to preserve the core principles blockchain represents: trust, transparency, and decentralization. Incorporating ethical oversight and transparent operational audits positions blockchain enterprises uniquely to thrive amidst growing automation skepticism. The future belongs to blockchain enterprises that consciously harness AI—not those blindly automated by it. In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system that ensures data input quality and ownership—allowing it to keep data safe while also guaranteeing the immutability of data. Check out CoinGeek's coverage on this emerging tech to learn more why Enterprise blockchain will be the backbone of AI. Watch: Onboarding enterprises onto BSV blockchain via AWS title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen>
