ATLANTA , Dec. 23, 2024 /PRNewswire/ -- KORE Group Holdings, Inc. (NYSE: KORE) ("KORE" or the "Company"), the global pure-play Internet of Things ("IoT") hyperscaler and provider of IoT Connectivity, Solutions, and Analytics, today announced it has received notification (the "Acceptance Letter") from the New York Stock Exchange (the "NYSE") that the NYSE has accepted the Company's previously-submitted plan (the "Plan") to regain compliance with the NYSE's continued listing standards set forth in Section 802.01B of the NYSE Listed Company Manual relating to minimum market capitalization and stockholders' equity. In the Acceptance Letter, the NYSE granted the Company an 18-month period from September 12, 2024 (the "Plan Period") to regain compliance with the continued listing standards. As part of the Plan, the Company is required to provide the NYSE quarterly updates regarding its progress towards the goals and initiatives in the Plan. In the Plan, Kore included details regarding previously reported operational restructuring activities, as well as an outlook on the Company's business. The Company expects its common stock will continue to be listed on the NYSE during the Plan Period, subject to the Company adherence to the Plan and compliance with other applicable NYSE continued listing standards. The Company's receipt of such notification from the NYSE does not affect the Company's business, operations or reporting requirements with the U.S. Securities and Exchange Commission. Cautionary Note on Forward-Looking Statements This press release includes certain statements that are not historical facts but are forward-looking statements for purposes of the safe harbor provisions under the United States Private Securities Litigation Reform Act of 1995. Forward-looking statements generally are accompanied by words such as "believe," "guidance," "project," "may," "will," "estimate," "continue," "anticipate," "intend," "expect," "should," "would," "plan," "predict," "potential," "seem," "seek," "future," "outlook," and similar expressions that predict or indicate future events or trends or that are not statements of historical matters. These forward-looking statements include, but are not limited to, statements regarding expected progress with the Company's compliance plan submitted to the NYSE, expected compliance with continued listing standards of the NYSE and expected continued listing of the Company's common stock on the NYSE. These statements are based on various assumptions and on the current expectations of KORE's management. These forward-looking statements are provided for illustrative purposes only and are not intended to serve as and must not be relied on by any investor or other person as, a guarantee, an assurance, a prediction or a definitive statement of fact or probability. Actual events and circumstances are difficult or impossible to predict and will differ from assumptions. Many actual events and circumstances are beyond the control of KORE. These forward-looking statements are subject to a number of risks and uncertainties, including general economic, financial, legal, political and business conditions and changes in domestic and foreign markets; the potential effects of COVID-19; risks related to the rollout of KORE's business and the timing of expected business milestones; risks relating to the integration of KORE's acquired companies, including the acquisition of Twilio's IoT business, changes in the assumptions underlying KORE's expectations regarding its future business; our ability to negotiate and sign a definitive contract with a customer in our sales funnel; our ability to realize some or all of estimates relating to customer contracts as revenue, including any contractual options available to customers or contractual periods that are subject to termination for convenience provisions; the effects of competition on KORE's future business; and the outcome of judicial proceedings to which KORE is, or may become a party. If the risks materialize or assumptions prove incorrect, actual results could differ materially from the results implied by these forward-looking statements. There may be additional risks that KORE presently does not know or that KORE currently believes are immaterial that could also cause actual results to differ materially from those contained in the forward-looking statements. In addition, forward-looking statements reflect KORE's expectations, plans or forecasts of future events and views as of the date of this press release. KORE anticipates that subsequent events and developments will cause these assessments to change. However, while KORE may elect to update these forward-looking statements at some point in the future, KORE specifically disclaims any obligation to do so. These forward-looking statements should not be relied upon as representing KORE's assessments as of any date subsequent to the date of this press release. Accordingly, undue reliance should not be placed upon the forward-looking statements. KORE Investor Contact: Vik Vijayvergiya Vice President, IR, Corporate Development and Strategy vvijayvergiya@korewireless.com (770) 280-0324 View original content to download multimedia: https://www.prnewswire.com/news-releases/kore-announces-nyse-acceptance-of-plan-to-regain-listing-compliance-302338621.html SOURCE KORE Group Holdings, Inc.AI is a game changer for students with disabilities
Aston Villa return to winning ways by blowing away Brentford
No Family Present, But 2 Dozen Women Support Luigi Mangione In NYC CourtroomInterim Intel Co-CEO: ‘The Core Strategy Remains Intact’ - CRNKanthan vegetable farmers compensated last month for agreeing to move out FORMER farmers cultivating on state land illegally for decades in Kanthan near Ipoh, Perak, have been paid compensation after moving out to make way for the Silver Valley Technology Park (SVTP) project. State tourism, industry, investment and corridor development committee chairman Loh Sze Yee said work on the first phase of SVTP could now start as the farmers had moved out last month. He said the state economic development arm Perbadanan Kemajuan Negeri Perak (PKNPk) together with the developer of the project held a ceremony to hand over the payment on Nov 21. “The 20-year-old issue has been resolved without any untoward incidents. “The developer is now carrying out land clearance work on a 131.5ha site for Phase I,” he said in reply to Mohd Hafez Sabri (PN-Manjoi) during the Perak State Assembly sitting at Bangunan Perak Darul Ridzuan in Ipoh yesterday. Mohd Hafez had asked about the development status of SVTP. Loh said the developer was expected to commence preliminary infrastructure works on the site in the first quarter of next year. “The industrial sector plays an important role in the economic development of the state, and based on the Market and Property Report, the performance of the property market in Perak was encouraging in 2023. “Market activity showed an upward movement,” he said, highlighting that the state government was committed to providing initiatives to drive Perak’s economy. Among them were infrastructure empowerment, investment incentives, trade and investment promotions to China and Taiwan as well as skills development institutions to grow talent. Under the leadership of Mentri Besar Datuk Seri Saarani Mohamad, Loh said Perak had been taking a new approach namely “thinking out of the box”. “In the 13th Malaysia Plan engagement session, the Economy Minister had praised the Perak government for being the only state that applied for a RM50mil loan for the SVTP project. “This is in contrast to the approach of other states that are likely to apply for direct allocations,” Loh added.
A user manual for yeast's genetic switches December 19, 2024 Kobe University When introducing genes into yeast to make it produce drugs and other useful substances, it is also necessary to reliably switch the production on or off. Researchers have found three gene regulation design principles that provide a flexible guideline for the effective control of microbiological production. Facebook Twitter Pinterest LinkedIN Email When introducing genes into yeast to make it produce drugs and other useful substances, it is also necessary to reliably switch the production on or off. A Kobe University team found three gene regulation design principles that provide a flexible guideline for the effective control of microbiological production. It's said that DNA is the blueprint of life, telling our cells what to produce. But DNA also contains the switches telling those cells when to produce something and how much of it. Therefore, when introducing new genes into cells to produce useful chemicals such as drugs or raw materials for chemical production, it is also necessary to include a genetic switch, a piece of DNA called a "promoter," that tells the cells to start production as needed. Kobe University bioengineer TOMINAGA Masahiro says: "The problem is that these promoters cannot be used in a plug-and-play manner unless researchers deeply understand how they interact with other genetic elements. Indeed, there are not so many cases in which researchers use artificial promoters to precisely control the cellular production and achieve their research purpose." Sometimes the production is too low, sometimes it is "leaky," meaning that it cannot be turned off at will. This is especially true for bioengineering yeast, which is more complex in its genetic regulation compared to bacteria. But this increased complexity also enables its use to produce many useful chemicals. As experts in modifying yeast cells, Tominaga and colleagues from the team led by ISHII Jun took a systematic approach to working out how to design effective promoters. "We came up with the idea that by carefully describing our process of improving a prototype promoter, we could prepare a 'user manual' for how to achieve high-performance and precise control so that these genetic systems could be more widely used," Tominaga explains. In a paper now published in the journal Nature Communications , they describe three design principles for yeast promoters. First, if researchers not only need large amounts of the product but also the ability to switch the production on or off at will, they should introduce multiple copies of the regulatory elements enabling this within the promoter. This reduces leakiness and increases the productivity. Second, the distance between promoter elements should be as small as possible to enhance the productivity even more. And third, the promoter should be insulated from surrounding DNA by including extra DNA before it to further reduce leakiness. Tominaga says: "We showed that a promoter's performance can be improved more than 100-fold by simply modifying its surrounding sequence. This is the first study to clearly propose a solution to the problem why potent yeast promoters work in some environments and not in others." The Kobe University bioengineers demonstrated the usefulness of their system by showcasing the production of two pharmaceutically useful proteins, so-called "biologics." Not only could they produce these two biologics in separate yeast strains but also in the same strain and with the ability to independently control which biologic is produced at any time. The latter is important because it has potential applications in hospitals, as the team explains in the study: "In addition to the conventional fermentation of single biologics, the rapid and single-dose production of multiple biologics with a single yeast strain at the point of care is crucial for emergencies that require production speed and flexibility rather than purity and productivity." They also achieved the notoriously difficult production of a coronavirus protein that can be used for the production of treatments, further showcasing both the usefulness and the flexibility of their design principles. Tominaga explains his wider outlook on the implications of this study: "Synthetic biology advocates creating new biological functions by rewriting genome sequences. The reality is however that we are often confused by unexpected changes resulting from our edits. We hope that our study is the first step towards the ability to design every single base in the genome with clear intentions." This research was funded by the Japan Agency for Medical Research and Development (grants JP21ae0121002, JP21ae0121005, JP21ae0121006, JP21ae0121007, JP20ae0101055 and JP20ae0101060), the Japan Science and Technology Agency (grants JPMJCR21N2 and JPMJGX23B4) and the Japan Society for the Promotion of Science (grants JP23K26469, JP23H01776 and JP18K14374). It was conducted in collaboration with researchers from the Pharma Foods International Co. Ltd and National Institute of Health Sciences. Story Source: Materials provided by Kobe University . Note: Content may be edited for style and length. Journal Reference : Cite This Page :ACLU of Kansas prepares for second Trump term and ‘attacks on civil liberties’
LOS ANGELES — After a protracted legal battle — involving dismissals, appeals and extradition from Romania — the co-founder of a California white supremacist group accused of inciting violence across the state will be freed from federal custody, a judge ruled Friday. U.S. District Judge Josephine L. Staton sentenced Robert Rundo to time served, which his federal public defender said totals 725 days in custody. Rundo was originally arrested and charged in October 2018 for his role in the Rise Above Movement, or RAM, a group accused of brawling at political rallies throughout the state, according to a federal court filing. A federal court judge twice dismissed the case, but it was revived by appeals courts, leading to Rundo's extradition from Romania last year to face charges in California. Rundo pleaded guilty in September to conspiracy to riot. During the sentencing hearing Friday, Rundo stood before the judge, arms crossed behind his back. He told the judge that this did not only ruin his own life, "but ruined everyone's life that was close to me." He said his mother and sister had to hide photos of him and that old friends lost their careers for being associated with him. "I hope to be able to move on from that time period and that mindset," Rundo told the judge. "This process has taken nearly a decade out of my life. It's a strong reminder to think before I speak and to think before I act." The judge said of Rundo: "Even he sems to acknowledge that the white supremacist views that he had led him to violence." "The court does have to consider whether his present claim that he in some respects rejects those views is genuine, and I do hope he's sincere about that, and I think he should be given the benefit of the doubt," Staton said. Staton gave Rundo two years of supervised release with conditions that include electronic monitoring and an order to stay away from RAM gatherings and known members. In a sentencing memo, Rundo's public defenders called the case "extremely unusual" and said it "has hung over Mr. Rundo like a dark cloud." Prosecutors acknowledged in a sentencing memo that years had passed since the criminal conduct in the case but maintained Rundo "has not renounced the violent extremist ideology that motivated that conduct." Prosecutors and public defenders laid out Rundo's path from Queens, N.Y., to co-founder of RAM in Southern California. At 19, Rundo pleaded guilty to gang assault and was sentenced to two years in prison, according to sentencing memos. While incarcerated, prosecutors said, he tattooed the numbers "88" — a neo-Nazi symbol signifying "HH" or "Heil Hitler," which he later referred to as a "symbols of white pride." Rundo's attorneys said he covered up the tattoo several years ago. After he moved to California in 2016, Rundo's attorneys wrote that he found a new community among members of the "alt right" and went on to co-found RAM. According to Rundo's plea agreement, the group "represented itself as a fighting group of a new nationalist white supremacy and identity movement." "While their views would be described as militant, white nationalist, racist, and "alt right," it should be remembered that Mr. Rundo is not charged with a hate crime," Rundo's attorneys wrote in their memo. Rundo and other members attended rallies "with the intent to provoke and engage in violent physical conflicts," according to the plea agreement. Rundo admitted to attending a Huntington Beach rally on March 25, 2016, where he and others "pursued and assaulted" people, including one protester he tackled and punched multiple times. Rundo also admitted to attending two other rallies, one in Berkeley on April 15, 2017, and another in San Bernardino on June 10, 2017, according to the agreement. Rundo was originally charged and arrested in October 2018, alongside two other alleged members, Boman and Tyler Laube of Redondo Beach. Judge Cormac J. Carney at least twice dismissed charges against Rundo and Boman, at one point finding that the men were being selectively prosecuted, while "far-left extremist groups, such as Antifa" were not. The U.S. 9th Circuit Court of Appeals in July rejected that finding. ©2024 Los Angeles Times. Visit at latimes.com . Distributed by Tribune Content Agency, LLC.
ACLU of Kansas prepares for second Trump term and ‘attacks on civil liberties’
NEW YORK (AP) — U.S. stocks are stabilizing Thursday following one of their worst days of the year . The S&P 500 rose 0.2% in late trading, a day after tumbling 2.9% when the Federal Reserve said it may deliver fewer cuts to interest rates next year than earlier thought. The Dow Jones Industrial Average was up 136 points, or 0.3%, with less than an hour remaining in trading, following Wednesday’s drop of more than 1,100 points. The Nasdaq composite rose 0.3%. Wednesday’s drop took some of the enthusiasm out of the market, which critics had already been warning was overly buoyant and would need everything to go correctly for it to justify its high prices. But indexes remain near their records , and the S&P 500 is still on track for one of its best years of the millennium . Traders are now expecting the Federal Reserve to deliver just one or maybe two cuts to interest rates next year, according to data from CME Group. Some are even betting on none. A month ago, the majority saw at least two cuts in 2025 as a safe bet. Wall Street loves lower interest rates because they give the economy a boost and goose prices for investments, but they can also provide fuel for inflation. Darden Restaurants, the company behind Olive Garden and other chains, helped lift the market after leaping 15.1%. It delivered profit for the latest quarter that edged past analysts’ expectations. The operator of LongHorn Steakhouses also gave a forecast for revenue for this fiscal year that topped analysts’. Accenture rose 6.7% after the professional services company likewise topped expectations for profit in the latest quarter. CEO Julie Sweet said it saw growth around the world, and the company raised its forecast for revenue this fiscal year. Amazon shares added 1.8%, even as workers at seven of its facilities went on strike Thursday in the middle of the online retail giant’s busiest time of the year. Amazon says it doesn’t expect an impact on its operations during what the workers’ union calls the largest strike against the company in U.S. history. They helped offset a tumble for Micron Technology, which fell 16.7% despite reporting stronger profit than expected. The computer memory company’s revenue fell short of Wall Street’s forecasts, and CEO Sanjay Mehrotra said it expects demand from consumers to remain weaker in the near term. It gave a forecast for revenue in the current quarter that fell well short of what analysts were thinking. Lamb Weston, which makes French fries and other potato products, dropped 22.6% after falling short of analysts’ expectations for profit and revenue in the latest quarter. It also cut its financial targets for the fiscal year, saying demand for frozen potatoes is continuing to soften, particularly outside North America. The company replaced its chief executive. In the bond market, yields were mixed a day after shooting higher on expectations that the Fed would deliver fewer cuts to rates in 2025. Reports on the U.S. economy came in mixed. One showed the overall economy grew at a 3.1% annualized rate during the summer, faster than earlier thought. The economy has remained remarkably resilient even though the Fed held its main interest rate at a two-decade high for a while before beginning to cut them in September. A separate report showed fewer U.S. workers applied for unemployment benefits last week, an indication that the job market also remains solid. But a third report said manufacturing in the mid-Atlantic region is unexpectedly contracting again despite economists’ expectations for growth. The yield on the 10-year Treasury rose to 4.57% from 4.52% late Wednesday and from less than 4.20% earlier this month. But the two-year yield, which more closely tracks expectations for action by the Fed in the near term, eased back to 4.31% from 4.35%. The rise in longer-term yields has put pressure on the housing market by keeping mortgage rates higher. Homebuilder Lennar fell 4.8% after it reported weaker profit and revenue for the latest quarter than analysts expected. CEO Stuart Miller said that “the housing market that appeared to be improving as the Fed cut short-term interest rates, proved to be far more challenging as mortgage rates rose” through the quarter. “Even while demand remained strong, and the chronic supply shortage continued to drive the market, our results were driven by affordability limitations from higher interest rates,” he said. A report on Thursday may have offered some encouragement for the housing industry. It showed a pickup in sales of previously occupied homes. In stock markets abroad, London’s FTSE 100 fell 1.1% after the Bank of England paused its cuts to rates and kept its main interest rate unchanged on Thursday. The move comes as inflation there moved further above the central bank’s 2% target rate, while the British economy is flatlining at best. The Bank of Japan also kept its benchmark interest rate unchanged, and Tokyo’s Nikkei 225 fell 0.7%. Indexes likewise sank across much of the rest of Asia and Europe. AP Business Writers Matt Ott and Elaine Kurtenbach contributed.Need a research hypothesis? Ask AI December 19, 2024 Massachusetts Institute of Technology Engineers have developed AI frameworks to identify evidence-driven hypotheses that could advance biologically inspired materials. Facebook Twitter Pinterest LinkedIN Email Crafting a unique and promising research hypothesis is a fundamental skill for any scientist. It can also be time consuming: New PhD candidates might spend the first year of their program trying to decide exactly what to explore in their experiments. What if artificial intelligence could help? MIT researchers have created a way to autonomously generate and evaluate promising research hypotheses across fields, through human-AI collaboration. In a new paper, they describe how they used this framework to create evidence-driven hypotheses that align with unmet research needs in the field of biologically inspired materials. Published today in Advanced Materials , the study was co-authored by Alireza Ghafarollahi, a postdoc in the Laboratory for Atomistic and Molecular Mechanics (LAMM), and Markus Buehler, the Jerry McAfee Professor in Engineering in MIT's departments of Civil and Environmental Engineering and of Mechanical Engineering and director of LAMM. The framework, which the researchers call SciAgents, consists of multiple AI agents, each with specific capabilities and access to data, that leverage "graph reasoning" methods, where AI models utilize a knowledge graph that organizes and defines relationships between diverse scientific concepts. The multi-agent approach mimics the way biological systems organize themselves as groups of elementary building blocks. Buehler notes that this "divide and conquer" principle is a prominent paradigm in biology at many levels, from materials to swarms of insects to civilizations -- all examples where the total intelligence is much greater than the sum of individuals' abilities. "By using multiple AI agents, we're trying to simulate the process by which communities of scientists make discoveries," says Buehler. "At MIT, we do that by having a bunch of people with different backgrounds working together and bumping into each other at coffee shops or in MIT's Infinite Corridor. But that's very coincidental and slow. Our quest is to simulate the process of discovery by exploring whether AI systems can be creative and make discoveries." Automating good ideas As recent developments have demonstrated, large language models (LLMs) have shown an impressive ability to answer questions, summarize information, and execute simple tasks. But they are quite limited when it comes to generating new ideas from scratch. The MIT researchers wanted to design a system that enabled AI models to perform a more sophisticated, multistep process that goes beyond recalling information learned during training, to extrapolate and create new knowledge. The foundation of their approach is an ontological knowledge graph, which organizes and makes connections between diverse scientific concepts. To make the graphs, the researchers feed a set of scientific papers into a generative AI model. In previous work, Buehler used a field of math known as category theory to help the AI model develop abstractions of scientific concepts as graphs, rooted in defining relationships between components, in a way that could be analyzed by other models through a process called graph reasoning. This focuses AI models on developing a more principled way to understand concepts; it also allows them to generalize better across domains. "This is really important for us to create science-focused AI models, as scientific theories are typically rooted in generalizable principles rather than just knowledge recall," Buehler says. "By focusing AI models on 'thinking' in such a manner, we can leapfrog beyond conventional methods and explore more creative uses of AI." For the most recent paper, the researchers used about 1,000 scientific studies on biological materials, but Buehler says the knowledge graphs could be generated using far more or fewer research papers from any field. With the graph established, the researchers developed an AI system for scientific discovery, with multiple models specialized to play specific roles in the system. Most of the components were built off of OpenAI's ChatGPT-4 series models and made use of a technique known as in-context learning, in which prompts provide contextual information about the model's role in the system while allowing it to learn from data provided. The individual agents in the framework interact with each other to collectively solve a complex problem that none of them would be able to do alone. The first task they are given is to generate the research hypothesis. The LLM interactions start after a subgraph has been defined from the knowledge graph, which can happen randomly or by manually entering a pair of keywords discussed in the papers. In the framework, a language model the researchers named the "Ontologist" is tasked with defining scientific terms in the papers and examining the connections between them, fleshing out the knowledge graph. A model named "Scientist 1" then crafts a research proposal based on factors like its ability to uncover unexpected properties and novelty. The proposal includes a discussion of potential findings, the impact of the research, and a guess at the underlying mechanisms of action. A "Scientist 2" model expands on the idea, suggesting specific experimental and simulation approaches and making other improvements. Finally, a "Critic" model highlights its strengths and weaknesses and suggests further improvements. "It's about building a team of experts that are not all thinking the same way," Buehler says. "They have to think differently and have different capabilities. The Critic agent is deliberately programmed to critique the others, so you don't have everybody agreeing and saying it's a great idea. You have an agent saying, 'There's a weakness here, can you explain it better?' That makes the output much different from single models." Other agents in the system are able to search existing literature, which provides the system with a way to not only assess feasibility but also create and assess the novelty of each idea. Making the system stronger To validate their approach, Buehler and Ghafarollahi built a knowledge graph based on the words "silk" and "energy intensive." Using the framework, the "Scientist 1" model proposed integrating silk with dandelion-based pigments to create biomaterials with enhanced optical and mechanical properties. The model predicted the material would be significantly stronger than traditional silk materials and require less energy to process. Scientist 2 then made suggestions, such as using specific molecular dynamic simulation tools to explore how the proposed materials would interact, adding that a good application for the material would be a bioinspired adhesive. The Critic model then highlighted several strengths of the proposed material and areas for improvement, such as its scalability, long-term stability, and the environmental impacts of solvent use. To address those concerns, the Critic suggested conducting pilot studies for process validation and performing rigorous analyses of material durability. The researchers also conducted other experiments with randomly chosen keywords, which produced various original hypotheses about more efficient biomimetic microfluidic chips, enhancing the mechanical properties of collagen-based scaffolds, and the interaction between graphene and amyloid fibrils to create bioelectronic devices. The system was able to come up with these new, rigorous ideas based on the path from the knowledge graph," Ghafarollahi says. "In terms of novelty and applicability, the materials seemed robust and novel. In future work, we're going to generate thousands, or tens of thousands, of new research ideas, and then we can categorize them, try to understand better how these materials are generated and how they could be improved further." Going forward, the researchers hope to incorporate new tools for retrieving information and running simulations into their frameworks. They can also easily swap out the foundation models in their frameworks for more advanced models, allowing the system to adapt with the latest innovations in AI. "Because of the way these agents interact, an improvement in one model, even if it's slight, has a huge impact on the overall behaviors and output of the system," Buehler says. Since releasing a preprint with open-source details of their approach, the researchers have been contacted by hundreds of people interesting in using the frameworks in diverse scientific fields and even areas like finance and cybersecurity. "There's a lot of stuff you can do without having to go to the lab," Buehler says. "You want to basically go to the lab at the very end of the process. The lab is expensive and takes a long time, so you want a system that can drill very deep into the best ideas, formulating the best hypotheses and accurately predicting emergent behaviors. Our vision is to make this easy to use, so you can use an app to bring in other ideas or drag in datasets to really challenge the model to make new discoveries." Story Source: Materials provided by Massachusetts Institute of Technology . Original written by Zach Winn. Note: Content may be edited for style and length. Journal Reference : Cite This Page :