A study published in the journal PLOS Digital Health demonstrates the accuracy of an artificial intelligence system developed at USP in Ribeirão Preto for identifying teeth and detecting cavities in x-rays. Approximately 30 researchers from the Faculty of Philosophy, Sciences and Languages at Ribeirão Preto and the School of Dentistry of Ribeirão Preto are collaborating within the Interdisciplinary Research Group in Digital Dentistry (InReDD) on the project. According to professor Alessandra Alaniz Macedo, the technology is based on Convolutional Neural Networks (CNNs), a type of artificial intelligence specialized in image processing; she explained that the system aims to streamline diagnosis and treatment by assisting dentists in radiographic analysis. Convolutional Neural Networks Detect Cavities in Dental X-rays The University of São Paulo’s Ribeirão Preto campus has developed an artificial intelligence system capable of identifying cavities in dental x-rays with a high degree of accuracy, streamlining diagnostic workflows for dentists. This capability stems from the implementation of Convolutional Neural Networks, or CNNs, a specific type of artificial intelligence architecture designed for image processing and pattern recognition. According to professor Alessandra Alaniz Macedo, “Within artificial intelligence, different methods are used to analyze different types of data. Neural networks are one of these approaches and currently produce the best results for various types of problems.” Training the AI to reliably detect cavities requires a supervised learning process where the system is fed thousands of previously analyzed radiographs. Researchers create a dataset, essentially teaching the artificial intelligence to correlate specific image characteristics with the presence of lesions. The model then iteratively compares its own analysis of new radiographs against this established ground truth, correcting errors and refining its accuracy with each iteration. Researchers explained that the model continuously compares its output with the ground truth and corrects its own errors during training, gradually learning to
Aug 31, 2026 · via quantumzeitgeist.com
Facial recognition technology 'scope creep' is upon us, experts warn A shopper walks into a supermarket and grabs a basket. By that time, a camera has scanned their face. That is what experts warn could be the new normal for Australians. Supermarkets started with exit gates and bagging-area cameras. Now they are trialling facial recognition technology. In August, Coles and Woolworths rolled out facial recognition technology trials in a bid to combat crime with about a third of retail workers not feeling safe in their workplace, according to a union survey of about 3,000 staff. Last week, Coles reported that incidents of abuse towards retail staff had increased by 85 per cent over the past two years in Victoria. The technology scans the features of a person's face to create a unique digital code and identify them. Neither of the supermarket giants has said if it would be rolled out in their Australian stores. However, both companies said they were looking into improving protection for their customers and staff. Industry groups say the move is about safety, but experts warn once the technology is installed the "scope creep" does not stop. 'Scope creep' Scope creep, also known as function creep, is when society incrementally allows things to happen over time that people feel uncomfortable about. "We let it pass and all of a sudden you see a layering of the technology being used for more privacy-intrusive purposes," said responsible technology policy specialist Lauren Perry from the University of Technology Sydney. She is concerned face scans could shift from safety and security to customer experience in ways that could disadvantage and harm the consumer. The layering of new technologies such as face scan-enabled EFTPOS machines and the widespread rollout of digital price tags across supermarkets could tailor the real-life shopping experience.
Aug 31, 2026 · via abc.net.au
How China buried Tibet flood images after Nepal disaster August 31, 2026 When a catastrophic flash flood swept through the rugged China-Nepal border on August 26, the physical devastation was immediate. In Nepal, a black torrent of mud and rock tore through communities, leaving hundreds dead and thousands more missing along the borderlands. But across the frontier in Tibet, an autonomous region of China, the physical disaster was almost instantly followed by a digital one: the rapid, high-tech erasure of the catastrophe's visual evidence. As survivors tried to upload raw footage of the deluge, China's state-backed information control apparatus swung into action, executing a sophisticated, precision operation to shape the public narrative and bury inconvenient truths. The contrasting realities — a tragic humanitarian crisis in Nepal and a tightly sanitized, triumphant rescue narrative in China — reveal the evolving mechanics of Beijing's modern censorship machine. Rather than imposing a blunt, blanket blackout, authorities deployed advanced image-recognition technology and "saturated information" tactics to drown out domestic scrutiny while deflecting diplomatic friction abroad. Collapse of the border gate In the immediate aftermath of the flood-triggered mudslide, local residents captured dramatic footage of the torrent engulfing Gyirong Port, a critical overland trade hub between China and Nepal. The most striking video showed a black wall of water and debris crashing into and destroying the "national" border gate. In an article titled "An Unrecorded Mudslide Rushes into Gyirong Port" on China's WeChat, a universal app that combines messaging with payment options and social media functions, local blogger "Matou Qingnian" described the chaotic scene. "The most terrifying moment happened at the Gyirong Port," the author wrote, describing video footage of crowds, including children, fleeing in panic before a pitch-black torrent swallowed the camera's view. Within hours, both the article and the raw video footage had
Aug 31, 2026 · via dw.com
Figures Abstract Effective monitoring of desert rangeland ecosystems is of crucial significance to regional ecological security. Unmanned aerial vehicle (UAV) hyperspectral remote sensing provides an effective means for the fine identification of vegetation species. However, in practical applications, vegetation classification using hyperspectral images often faces the problem of limited labeled samples, which makes it difficult for traditional deep learning methods to obtain stable and accurate classification results. To address these issues, this study proposes a meta-learning with Mamba (MetaMamba) method for vegetation classification in desert rangeland. This method constructs a local-global dual-branch structure in the feature extraction stage to achieve effective fusion of local and global spatial context information. Specifically, the local branch uses convolutional neural networks (CNNs) to extract fine-grained spatial features, while the global branch models long-distance spatial dependencies based on the Mamba model. Additionally, a meta-learning strategy is introduced to enhance the feature learning and generalization abilities of the model under few-shot conditions. Experimental results show that the proposed method outperforms existing methods across multiple evaluation metrics. The overall classification accuracy (OA) reaches 90.85%, the average accuracy (AA) reaches 91.67%, and the Kappa coefficient reaches 87.77%. The method shows good stability and adaptability under different sample sizes. The MetaMamba model can achieve high-precision classification of desert rangeland vegetation species under few-shot conditions, providing an effective technical approach for ecological monitoring and rangeland resource management. Citation: Hao F, Gao X, Zhang T, Du J, Wang S, He X (2026) MetaMamba: Meta-learning with mamba for few-shot vegetation species classification using UAV-based hyperspectral imagery in desert rangeland. PLoS One 21(8): e0352744. https://doi.org/10.1371/journal.pone.0352744 Editor: Yaseen Al-Mulla, Sultan Qaboos University, OMAN Received: June 12, 2026; Accepted: August 14, 2026; Published: August 31, 2026 Copyright: © 2026 Hao et al. This is an open access article distributed under the terms of the Creative
Aug 31, 2026 · via journals.plos.org
Did you know that a number of smart TVs come equipped with cameras? While that idea may raise privacy concerns for many people, and rightfully so, these cameras offer several neat features you can explore. Cameras embedded inside a smart TV aren't extremely common, but we've seen them in select models by Samsung, LG, Sony, and others. Additionally, some manufacturers offer add-on cameras that buyers can plug into the TV's USB port for video calls or Zoom meetings. How to tell if a smart TV has a camera Give it a look To determine whether your smart TV has a camera, inspect it visually, check the user manual, look up the specifications list, and skim through the hardware section or software features. If your TV has features like gestures or video calling, it probably has a camera. Like most smartphones and laptops, the first place to look on your Smart TV is the top center bezel between the screen and the outer frame. It could also be slightly off-center or on the left or right side. Look for a small circle cutout or lens. They're almost as small as the front-facing camera on your phone, so look close. Check for a small camera on the frame or even near the base. Many TVs have infrared sensors on the bottom middle that interact with the remote control, and a camera could be there, but don't confuse the little red IR circle with a camera. Smart TV camera features you can try Exercise, video calls, and more It's kinda scary to think that your TV is spying on you and watching back as you watch it, and we'll talk more about that in a moment. If you're not worried and simply want to try some of the many features a camera provides,
Aug 31, 2026 · via howtogeek.com
The Joint Admissions and Matriculation Board (JAMB) has announced plans to introduce Facial Biometric Verification (FBV) in the conduct of the Unified Tertiary Matriculation Examination (UTME). According to the Board’s weekly bulletin released on Monday, the move was part of efforts to tackle impersonation, examination malpractice and restore greater integrity to the examination process. JAMB said the planned transition marks another major step towards strengthening biometric identification and tightening security around the UTME. This will feature the Board partnering with the National Identity Management Commission (NIMC) to verify candidates through live facial recognition before they are allowed to sit the UTME. The Board said candidates seeking to take the examination would undergo live facial verification through an application, with the verification result forwarded to NIMC. The identity management agency would subsequently return a code to JAMB to either affirm or reject the candidate’s identity claim. The Examination body informed that it would initially retain the existing 10-fingerprint biometric format alongside the live facial verification system. It however hinted that the facial verification technology would eventually replace the use of One-Time Passwords (OTPs), while fingerprint verification would be gradually phased out within the next two to three years. To facilitate the transition, JAMB said it was already putting measures in place to ensure that all accredited Computer-Based Test (CBT) centres were equipped with appropriate Closed-Circuit Television (CCTV) cameras and that personnel were adequately trained. The Board explained that facial biometric verification uses unique facial features to establish a person’s identity, offering advantages over conventional biometric methods such as fingerprint and iris scanning.
Aug 31, 2026 · via thefact.ng
How China buried Tibet flood images after Nepal disaster August 31, 2026 When a catastrophic flash flood swept through the rugged China-Nepal border on August 26, the physical devastation was immediate. In Nepal, a black torrent of mud and rock tore through communities, leaving hundreds dead and thousands more missing along the borderlands. But across the frontier in Tibet, an autonomous region of China, the physical disaster was almost instantly followed by a digital one: the rapid, high-tech erasure of the catastrophe's visual evidence. As survivors tried to upload raw footage of the deluge, China's state-backed information control apparatus swung into action, executing a sophisticated, precision operation to shape the public narrative and bury inconvenient truths. The contrasting realities — a tragic humanitarian crisis in Nepal and a tightly sanitized, triumphant rescue narrative in China — reveal the evolving mechanics of Beijing's modern censorship machine. Rather than imposing a blunt, blanket blackout, authorities deployed advanced image-recognition technology and "saturated information" tactics to drown out domestic scrutiny while deflecting diplomatic friction abroad. Collapse of the border gate In the immediate aftermath of the flood-triggered mudslide, local residents captured dramatic footage of the torrent engulfing Gyirong Port, a critical overland trade hub between China and Nepal. The most striking video showed a black wall of water and debris crashing into and destroying the "national" border gate. In an article titled "An Unrecorded Mudslide Rushes into Gyirong Port" on China's WeChat, a universal app that combines messaging with payment options and social media functions, local blogger "Matou Qingnian" described the chaotic scene. "The most terrifying moment happened at the Gyirong Port," the author wrote, describing video footage of crowds, including children, fleeing in panic before a pitch-black torrent swallowed the camera's view. Within hours, both the article and the raw video footage had
Aug 31, 2026 · via amp.dw.com
And how do I use artificial intelligence without getting in trouble with the state board?
The answers point to a simple conclusion: Artificial intelligence does not replace appraisers.
How Computer Vision Is Trained to “See” What We See Computer vision is a subset of artificial intelligence that enables computers to extract information from pictures.
USPAP Obligations in an Artificial Intelligence Assisted Appraisal While USPAP does not prohibit the use of artificial intelligence, it clearly assigns responsibility for results to the appraiser, not the technology.
Artificial intelligence is not a threat to professional valuation — it’s an opportunity to elevate it.
Aug 31, 2026 · via appraisalbuzz.com
The Federal Attorney-General Michelle Rowland is releasing draft legislation, to tackle new technologies including smart glasses and artificial intelligence.
The proliferation of cheap smart glasses have challenged the relevance of Australia's existing privacy laws.
Meanwhile, tech firms are gobbling up huge reams of data to help train AI models, often with little regard for people's privacy or copyright.
Labor plans to introduce the proposed new laws into parliament by the end of the year.
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Kimberlee Weatherall, Professor of Law at University of Sydney researching technology and the law
Aug 31, 2026 · via abc.net.au
Threads could soon offer another incentive to keep people posting, with a new post recognition screen recently added to the app’s back-end code. As shown in this image posted by app researcher Alessandro Paluzzi, Threads may soon give users a virtual gem for posting highly engaging content, as a means to recognize user contributions, and potentially gamify the process. Threads itself hasn’t offered any insight into this yet, so the reward could merely be visual, or it could include a monetary incentive. Incorporating a monetization element would make it similar to X’s efforts to guide posting behaviors by offering cash prizes for articles, videos and other kinds of posts. The post recognition process also seems similar to X’s Bangers promotion, in which X tried to recognize the most engaging posts in the app. Last November, X announced its Bangers promotion, which was meant to recognize the most engaging posts in the app each month by highlighting them in a dedicated Bangers account. Creators who received recognition also got a special badge that appeared on their profile. The idea, like this concept from Threads, was that this type of additional recognition would motivate the most engaging posters to keep sharing content in the app. But X seemed to lose interest in the concept pretty quickly. The @Bangers account has been dormant since November, after it recognized the first round of bangers. Maybe Threads will be more dedicated to the recognition. It looks like it might be easier because these gems would be awarded based on engagement thresholds, not on external judgment. Either way, it looks like Threads may soon have a new way to celebrate its most popular posts.
Aug 31, 2026 · via socialmediatoday.com
Subscribe to The Informer for monthly expert analysis, and to Events for advance notice of visiting world leaders and distinguished guests. You may unsubscribe from Lowy Institute newsletters at any time. For information on our privacy practices and how to unsubscribe, see our Privacy Policy. The most-pressing world events explained by Lowy Institute experts and global contributors, in your inbox, every Thursday. You may unsubscribe from The Interpreter at any time. For information on our privacy practices and how to unsubscribe, see our Privacy Policy. Artificial intelligence, explained. A staff member works on script refinement, on-location filming, AI post-production, and overseas translation and distribution at a micro drama production company on 21 July 2026 in Jiaxing, China (VCG via Getty Images) A face licensed for one AI advert can be reused indefinitely, and local laws have not caught up with that. Would you accept US$15 to let an AI company use your face in artificial intelligence generated content? In China, this is becoming a real proposition. A recent Rest of World (Opens in new window) article reports that people are paid from between US$15 to US$700 to license their facial likenesses for AI-generated microdramas and advertisements produced for mobile phone viewing. China’s mobile entertainment industry is already enormous – and the use of AI-generated content is growing. More than 95% of microdramas released in China during the first three months of 2026 reportedly used AI somewhere in their production. The industry needs more faces – celebrities and ordinary people – to meet the demand for fast-paced, audience-driven microdrama production (Opens in new window). One response has been straightforward: pay people for their faces. At the same time, regulators and platforms are cracking down on harmful and pirated content (Opens in new window),unauthorised digital likeness (Opens in new window), and homogeneous
Aug 31, 2026 · via lowyinstitute.org
Have you ever woken in the morning steeped in a sense of nonspecific dread? It’s undefined, and even though you have no idea what it’s about, it’s palpable. You recognize that it’s just a feeling, not a fact, yet the heaviness presses. You scan the night’s memories for a bad dream… nothing in jackboots chased you through a field, the mean girls didn’t take your coat. With dreams coming up empty, you look around. Did your psyche manage to bury something horrific, just to give you the mercy of sleep? Did yesterday bring a terminal illness diagnosis? An IRS audit? No. And yet. That foreboding sense, ominous and ill-defined, persists. Writing days don’t always go as planned That’s how I woke up one day last week: Marinating in apprehension worthy of a straightjacket. It was a planned writing day, and I had it all laid out: coffee, pickleball, then up to the rooftop sofa to write under a tattered pergola. The morning dreads smashed that. Scanning for the source of what woke me up scared for the world, I remembered. Of course. It was something I stupidly read right before bed the night before. It was a deep dive on Trump’s total dismantling of U.S. counterintelligence and counterterrorism efforts. Trump has systematically removed U.S. counterterrorism and counterintelligence assets, the professionals tracking communications and operations of adversarial governments and terrorist cells planning bombs, manipulating politics, and sowing dangerous division in the U.S., and reassigned them instead to monitor Trump’s domestic political adversaries. Trump gutted foreign risk monitoring functions under the DOJ, the FBI, and DHS, while deliberately elevating terrorism risks those divisions were created to track. The threat environment from Russia, China, Iran, Venezuela, Mexico, and Cuba is now at an all-time high, and we have a weakened detectionsystem in place.
Aug 30, 2026 · via dailykos.com
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Aug 30, 2026 · via youtube.com
Fair Observer’s operations chief of staff Cheyenne Torres and entrepreneur Dirk Lueth, co-founder and co-CEO of Upland, examine how artificial intelligence is reshaping economies, employment and the media. Lueth explains why today’s generative AI differs from traditional software and traces its development from an academic concept to a widely accessible technology. Although he acknowledges the risks of job displacement, concentrated corporate power and excessive investment, he expects AI to increase productivity and create new opportunities. He believes that human judgment, trusted institutions and energy infrastructure will become increasingly valuable as AI grows more powerful. From rigid rules to statistical models Torres begins by asking what AI actually means. Lueth distinguishes it from traditional software, which relied on programmers writing deterministic rules. Large language models instead analyze vast amounts of human-created material and identify statistical patterns in language. They can generate useful responses across fields ranging from medicine to law, but Lueth stresses that they have no consciousness or human understanding. He also distinguishes chatbots from AI agents. A chatbot usually responds to an individual request, much like a search engine. An agent can perform a continuing assignment, complete multiple steps and act more like a virtual worker. AI itself is not new. Researchers coined the term at Dartmouth College in 1956, but Lueth describes the following decades as a period of overpromising. Technical breakthroughs eventually brought AI closer to public expectations. AlexNet advanced image recognition in 2012, Google researchers introduced the transformer architecture in 2017 and ChatGPT made generative AI accessible to the public in 2022. Expertise gets cheaper Lueth considers AI revolutionary because it spreads knowledge and reduces the cost of accessing expertise. People can now ask an AI system for help with household repairs or basic financial and legal questions instead of immediately consulting a professional. Scientists and
Aug 30, 2026 · via fairobserver.com
The Royal Canadian Mounted Police are testing facial-recognition technology using booking photographs collected by Canadian police agencies as it considers a future national facial-identification service.
The project, disclosed in the RCMP’s departmental plan, says the force will “collaborate with multiple vendors” to review booking photographs collected from law-enforcement agencies across Canada.
According to the plan, competing algorithms will be tested for “quality, performance, accuracy and demographic bias in a Canadian context.” The RCMP says security and privacy protections will be in place to protect the test data.
But the plan does not say which private companies they’re collaborating with, how many booking photographs are being used in these tests, or which police agencies supplied them.
Aug 30, 2026 · via junonews.com
Dorset police have brought in facial recognition technology to spot wanted people Dorset Police have deployed live facial recognition technology for the first time to track down wanted people and sex offenders Dorset Police has deployed live facial recognition technology for the first time, scanning crowds in some of the county’s busiest areas for wanted people and individuals subject to court orders. The technology has been introduced in six designated hotspots across Dorset, including Bournemouth Pier, Bournemouth Square and Boscombe High Street. Live facial recognition, or LFR, uses cameras to analyse faces within a defined “zone of recognition” and compare them with photographs on a police watchlist. An officer operating the system can alert patrol officers nearby when a potential match is identified. Dorset Police’s watchlist contains about 5,000 people, including sex offenders, domestic abuse perpetrators, missing people and individuals subject to court orders. The technology is already used by police forces elsewhere in the country, including at major sporting events and football matches. The Dorset rollout follows a survey of 1,068 residents commissioned by Police and Crime Commissioner David Sidwick. It found that 74% supported the use of LFR, while 23% opposed it. Police say the technology is intended to identify people who may be of interest to officers rather than treat members of the public as suspects. The force said anyone entering an LFR zone would be alerted to its use through signage and stressed that it was operating the system in accordance with national guidance. However, the introduction of biometric surveillance has prompted concerns among critics who argue people should be able to go about their daily lives without being subjected to facial scans, potentially without their knowledge or consent. Dorset Police said the technology should not be viewed as a way of monitoring everyone passing through
Aug 30, 2026 · via hellorayo.co.uk
Dorset police have brought in facial recognition technology to spot wanted people Dorset Police have deployed live facial recognition technology for the first time to track down wanted people and sex offenders Dorset Police has deployed live facial recognition technology for the first time, scanning crowds in some of the county’s busiest areas for wanted people and individuals subject to court orders. The technology has been introduced in six designated hotspots across Dorset, including Bournemouth Pier, Bournemouth Square and Boscombe High Street. Live facial recognition, or LFR, uses cameras to analyse faces within a defined “zone of recognition” and compare them with photographs on a police watchlist. An officer operating the system can alert patrol officers nearby when a potential match is identified. Dorset Police’s watchlist contains about 5,000 people, including sex offenders, domestic abuse perpetrators, missing people and individuals subject to court orders. The technology is already used by police forces elsewhere in the country, including at major sporting events and football matches. The Dorset rollout follows a survey of 1,068 residents commissioned by Police and Crime Commissioner David Sidwick. It found that 74% supported the use of LFR, while 23% opposed it. Police say the technology is intended to identify people who may be of interest to officers rather than treat members of the public as suspects. The force said anyone entering an LFR zone would be alerted to its use through signage and stressed that it was operating the system in accordance with national guidance. However, the introduction of biometric surveillance has prompted concerns among critics who argue people should be able to go about their daily lives without being subjected to facial scans, potentially without their knowledge or consent. Dorset Police said the technology should not be viewed as a way of monitoring everyone passing through
Aug 30, 2026 · via planetradio.co.uk
Salt Lake City, UT - August 29, 2026 - Backstreet Surveillance, a commercial security company serving businesses across the United States, is highlighting mobile surveillance trailers as part of its broader commercial security offering. Based in Salt Lake City, Utah, the company works with organisations that need surveillance coverage across commercial properties, outdoor areas, temporary sites, and locations where permanent infrastructure may not be practical. Backstreet Surveillance offers mobile surveillance trailers that combine camera technology with flexible deployment. These systems can help businesses monitor locations where security needs may change over time. The company pairs these solutions with its wider focus on commercial surveillance systems, security consulting, and expert system design. Flexible Security for Changing Commercial Needs Commercial security requirements can vary widely from one site to another. A warehouse may need coverage around loading areas and entrances. A construction site may require temporary outdoor monitoring. A parking area may need cameras positioned to capture vehicle activity. Other businesses may need surveillance in locations where a permanent installation is difficult or unnecessary. Mobile surveillance trailers offer another option for those situations. Rather than treating every location as a fixed installation, businesses can use mobile systems in areas where coverage may need to move or change. This flexibility can be useful for commercial and industrial properties, construction environments, parking areas, and other large outdoor locations. System Design Remains Central to Commercial Surveillance Backstreet Surveillance approaches mobile surveillance as one part of a larger security strategy. Effective commercial surveillance depends on more than the number of cameras installed. Camera placement, image quality, lighting conditions, connectivity, recording requirements, and the purpose of the system all play a role. The company focuses on expert design and application to help determine how different technologies should work together. Its broader commercial security offering includes high-definition cameras,
Aug 30, 2026 · via mycarrollcountynews.com
As concerns grow over the pervasiveness that is AI-driven surveillance, a German game designer has built a shirt engineered to make AI cameras “blind” to the presence of a human. Berlin-based artist and technologist Simon Weckert’s design features a chaotic mix of colors and shapes printed across the fabric. The goal is not to fool the human eye but to break the outline detection software that artificial intelligence relies on to identify a body. “Digital Camouflage is a garment developed in response to the AI video surveillance planned for Berlin’s Kottbusser Tor,” Weckert notes on his website. “Its pattern is based on a so-called adversarial attack: it targets the features that object-recognition systems look for when searching for a human figure, so the wearer is no longer registered as a person by the machine,” he explains. Kottbusser Tor is a high-traffic Berlin U-Bahn (underground railway) station. It is part of Berlin’s Kreuzberg district and is currently the focal point of urban surveillance debates. Engineering visual confusion The shirt’s combination of pink, orange, and green shapes is meant to prevent detection software from binding the parts of a body into a single, recognizable figure. One could call the digital camouflage pattern a paradox of sorts, as Weckert used a specialized generative AI method known as TC-EGA (Toroidal-Cropping-based Expandable Generative Attack) to run an adversarial loop. Meaning he went through round after round of trial and error before the pattern stopped reading as a person at all. A shirt built to defeat AI, designed with the help of AI, is the kind of detail that would fit right into a William Gibson novel. And what do you know, one already did. Gibson’s 2010 sci-fi and thriller novel, Zero History, imagined something quite similar, where a garment was so aggressively patterned that it
Aug 29, 2026 · via geekspin.co
recovery image.jpg The Hope Dealer Project Aug 29, 2026 9 hrs ago 0 Facebook Twitter WhatsApp SMS Email Print Copy article link Save In recognition of National Recovery Month held each September, The Hope Dealer Project is raising awareness about substance use disorder with help from communities all across the state. The Hope Dealer Project As featured on Facebook Twitter WhatsApp SMS Email Print Copy article link Save × Post a comment as Anonymous Commenter Post As Emoticons [smile] [beam] [wink] [sad] [cool] [innocent] [rolleyes] [whistling] [lol] [huh] [tongue] [love] [sleeping] [yawn] [unsure] [angry] [blink] [crying] [ohmy] [scared] [sleep] [sneaky] [tongue_smile] [thumbdown] [thumbup] [censored] [happybirthday] [ban] [spam] [offtopic] [batman] [ninja] [pirate] [alien] Comment Text × Report × Watch this discussion. Stop watching this discussion. Watch this discussion Get an email notification whenever someone contributes to the discussion Notifications from this discussion will be disabled. (0) comments Welcome to the discussion. Log In Keep it Clean. Please avoid obscene, vulgar, lewd, racist or sexually-oriented language. PLEASE TURN OFF YOUR CAPS LOCK. Don't Threaten. Threats of harming another person will not be tolerated. Be Truthful. Don't knowingly lie about anyone or anything. Be Nice. No racism, sexism or any sort of -ism that is degrading to another person. Be Proactive. Use the 'Report' link on each comment to let us know of abusive posts. Share with Us. We'd love to hear eyewitness accounts, the history behind an article. Post a comment Watch this discussion. Stop watching this discussion. Latest e-Edition The Exponent Telegram Free Special Sections Economy - Progress To view our latest e-Edition click the image on the left. Click here to view more FREE Special Sections Newsletters Success! An email has been sent to with a link to confirm list signup. Error! There was an error processing your request. WV
Aug 29, 2026 · via wvnews.com