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Scientists Turn Wet Coffee Grounds Into Coal-Like Fuel in Just 90 Seconds
A new process skips energy-intensive drying for recycling coffee waste.
Strategy Of Employing AI Mental Health Chatbots As School Psych Counselors For Teens
Teens increasingly have mental health issues, schools are trying to keep up. School psychologists are costly. LLMs can be an amplifier as a tool. An AI Insider scoop.
Health officials warn against swimming at Avocado Lake after elevated E. coli levels
Health officials are advising people to avoid swimming at Avocado Lake after elevated levels of E. coli bacteria were detected at the lake's swim beach.Accordin
Asthma, maternal health, climate disasters: How Detroit’s health director is tackling city’s health disparities
Detroit health director discusses tackling childhood asthma, maternal health, climate disasters through Health in All Policies approach.
Making Our Own Luck
We are cross-posting a piece that former NIH official Kris Willis wrote for Macroscience. Kris is now the President and Founder of the Woodley Park Institute, for which I’m a board member. Picking winners or hedging bets? Federal science agencies have long wrestled with the question of how to ensure their billions of dollars of grants and contracts result in maximum benefits for Americans. On the surface, it might seem that a goal-oriented, interventionist style of management would be the best policy: prioritize our most pressing problems and distribute funding accordingly.This top-down strategy creates a unique hazard, though: bad choices can send resources in the wrong direction, resulting in slow progress that impedes the delivery of tangible benefits to citizens. Moreover, if decision makers pursue an applied advance when the underlying scientific principles remain poorly understood, they risk costly failures and a loss of support for the research enterprise at large. Examples include Nixon’s 1971 War on Cancer, undertaken on the premise that a cure could be achieved in less than a decade, the drive to build an operational commercial fusion plant by the mid-1990s, and the National Plan to Address Alzheimer’s Disease, which failed to produce the effective treatments and prevention strategies promised by 2025. The contrasting laissez-faire approach is to hedge your bets. If the path to an advance is impossible to predict, then the wisest choice might be to distribute funding to as widely as possible. The main risk of this strategy is that spreading funding thinly may limit the resources available to the most promising research, resulting in the same negative outcomes as the interventionist approach: limited support for the most promising topics, slow progress, and delayed returns. In reality, at science agencies like the National Science Foundation and National Institutes of Health, program managers navigate between these two extremes, setting some funds aside to target high-priority areas and using the rest to cover the widest possible range of meritorious proposals. This middle path seems like the most rational way to proceed, but it still requires making choices. How much should be set aside for high priority topics? What should those topics be? How should we define merit? Expert opinion can provide a helpful guide, but leading experts can have remarkably different opinions about what matters and what should be prioritized. Moreover, experts and administrators alike can be risk averse, giving an edge to high-profile, well-established concepts. What’s really needed is a data-driven framework to help guide decision-making, one that doesn’t simply repackage prestige or incumbency. Recognizing breakthroughs years in advance Many breakthroughs fail to attract funding or recognition at the earliest stages of development. Katalin Karikó, for example, spent years struggling to win grants for work on mRNA that would eventually win her and Drew Weissman a Nobel Prize. Similar stories can be told about Jim Allison’s groundbreaking studies leading to the development of cancer immunotherapy, Stan Pruisner’s demonstration that prions can self-replicate without DNA, or Robin Warren and Barry Marshall’s proof that Helicobacter pylori, not stress, causes ulcers. Yet at some point, the scientific community recognizes and responds to transformative breakthroughs like these. How does that change happen? And what if science funders could identify the areas that are on the cusp of a breakthrough? Those questions led my collaborators and me to study how scientists responded to past breakthroughs. Based on patterns in that data, we developed a means of predicting future breakthroughs, using biomedicine as a proof of concept. It’s worth taking a moment to describe how our approach works. Briefly, our prediction process begins by grouping the 18 million or so peer-reviewed papers in PubMed, the authoritative database of biomedical research, into roughly 50,000 unique topics. A small subset of these topics are so widely acclaimed as breakthroughs that they have been recognized with a major prize like a Nobel or a Lasker Award. We theorized that studying the development of these outliers over time, especially before they gained acclaim, was the key to identifying future instances of them. After defining topics, we chose 21 representative breakthroughs and asked what they looked like before they won prestigious prizes. To answer that question, we re-ran our topic-mapping algorithm repeatedly, winding back the clock one year each time, stringing together the years to follow the progress of each field as it grew and advanced. We found that in each case, the years leading up to a discovery followed a pattern: a burst of papers on a new, rapidly evolving topic, many of which quickly became influential. These characteristics—the percent of papers that are new, the percentage of papers that are brought in from other topics, and the influence of each individual paper—can all be measured separately for any given topic. Together, they act as a predictive signal that is detectable an average of five years before a transformative discovery is made, and up to thirty years before the discovery receives a major prize. Scanning the current research landscape for topics that display this signal allows us to predict what work will likely produce a future breakthrough. Each year we analyzed includes four or five signals, a number that appears to have remained constant across a twenty year time frame. In their classic work on the sociology of science, Bruno Latour and Steve Woolgar established that the desire to participate in a major discovery is an important motivator for scientists as they consider whether they should take up (or abandon) a research problem. Although further work is needed, the simplest explanation for our results is that this behavior is widespread enough to detect at scale. A foundational advance, or something like it, draws the attention of scientists and causes them to change the direction of their research. They vote with their feet, staking their own reputation and careers by publishing on and citing the new idea. That upswell of interest is the foundation of our breakthrough signal. What kind of research does our model identify as a breakthrough? After building a model based on the patterns in our 21 preselected breakthroughs, we tested it by identifying all early signals of discovery from 1994 through 1997. Of the 18 signals we found in that time period, 17 can be traced forward in time to a breakthrough. Examples include super-resolution fluorescence microscopy (see the image above), the directed evolution of proteins and enzymes (Chemistry Nobel, 2018), and sequencing the human genome (National Medal of Science, 2008). The discovery of the role of leptin signaling in obesity is a particularly interesting case study. Around 1950, scientists noticed the existence of a type of lab mouse that suffered from a unique inherited form of obesity. When given the freedom to choose their own diet, these mice ate more than normal and preferred food that was high in fat. Researchers had few clues as to why the animals overate; early experiments pointed to the existence of a soluble ob factor found circulating in the bloodstream that regulated appetite, but its identity was unknown. In 1994, Jeffrey Friedman and colleagues identified and sequenced the ob gene, noting that the protein it encoded appeared to fit the profile of a circulating factor. A year later, a trio of high-profile publications demonstrated that ob was a hormone that regulated body weight and fat deposition by regulating appetite. One of these was co-authored by Friedman, who christened it leptin from the ancient Greek word for thin. Using our model, the data from 1996 make it clear this advance would become a breakthrough. Scientists had flocked to study the biology of the new hormone, generating the flurry of new papers and citations required to produce a signal. One of these demonstrated that serum leptin concentrations reflected the amount of adipose tissue in the human body, providing clinical validation of the earlier mouse studies. Before the identification of leptin, scientists were unable to point to a specific molecule that controlled appetite and adiposity, so that it was impossible to rule out non-physiological causes of obesity; its characterization fundamentally changed our concept of weight gain. In 2010, Friedman and fellow pioneer Douglas Coleman were awarded a Lasker for the discovery. Our work also identifies breakthroughs in clinical practice and behavioral and social sciences, even though these areas are less likely to draw the attention of major prize committees. One example that falls into this category is the introduction of endovascular aneurysm repair, a minimally invasive surgical procedure for the treatment of abdominal aortic aneurysm, a leading cause of death among Americans over the age of 65. Relative to the previous standard of care, it reduces in-hospital mortality by almost four-fold. In 2017, Timothy Chuter received the American College of Surgeons’ prestigious Jacobsen Innovation award for his multiple refinements to the technique. Another under-recognized breakthrough identified by our model is the development of standardized survey instruments to assess the quality of life for HIV+ patients. The antiretroviral cocktails introduced in the mid-1990s reduced AIDS mortality, but treatment came with serious side effects. The new evaluations showed that patients whose disease progressed had worse physical functioning than Americans with other chronic diseases, while those who were asymptomatic maintained a health-related quality of life on par with the overall US population. This evidence made it possible for patients and activists to argue that even in the absence of a total cure, and in spite of the side effects, alleviation of symptoms was a worthwhile priority for clinicians. My colleagues and I have failed to identify any significant recognition for the physicians and health policy experts who pioneered this advance, although in 2016, researchers called for the World Health Organization to set targets for good health-related quality of life as part of its framework to end the AIDS pandemic. From forecasting to funding How should science funders use our predictions? Any serious discussion of what we should do with this new capability needs to begin with an understanding of its limitations. We can’t (and shouldn’t) invest all of our resources in the small number of topics predicted to produce breakthroughs. Innovative new fields are born from existing ones; they rarely arise de novo. If funders don’t maintain a diverse portfolio, the breakthroughs of tomorrow will have no antecedents. Think of this as eating the seed corn, or killing the goose that lays the golden egg. There are also multiple goals of funding beyond basic scientific discovery, including translating discoveries into clinical practice, developing new technologies, supporting economic development, and training new scientists. The investments needed to accomplish these goals are likely different from those required to support emerging breakthroughs. Finally, we must be aware that we may not capture every instance of a breakthrough. The concept is fuzzy, and not every significant discovery is recognized with a major award. Further, breakthroughs are rare, meaning that our dataset is, by necessity, small. This makes formal estimates of accuracy challenging. Although our overall success rate appears to be high, any one signal may turn out to be a false positive. We found one apparent example: the development of the third generation COX-2 inhibitors, Vioxx and Celebrex, which were much celebrated in the early 2000s as effective but non-addictive pain relievers, meets all the algorithmic criteria of a breakthrough. Five years after it received FDA approval, researchers demonstrated that Vioxx was associated with serious cardiovascular complications, and the manufacturer voluntarily pulled the drug from the market. Celebrex remains available, although like other NSAIDs, it carries an FDA warning for increased cardiovascular risk. Decision makers who were overly focused on the breakthrough potential of this research might have wasted substantial resources nurturing an area that ultimately proved to be a failure—but so would those who relied on expert opinion at the time. That said, the potential benefits of funding the next mRNA vaccine or cancer immunotherapy years earlier than we might have are large. When we can’t assume the outcome of an action, it’s worth conducting an experiment. Can targeted support for areas that are poised to produce a breakthrough increase the return on scientific investment without cannibalizing future advances? With the necessary administrative infrastructure in place, conducting this experiment would be straightforward. First, identify all the breakthrough signals between 2018 and 2023, select half at random, and commit to a decade of investment. For biomedicine, a six year window should yield about 30 topics with the potential to produce a breakthrough. Providing strong support to half of these might be accomplished for $300 million a year. That’s roughly half of the recent annual budget of the NIH Common Fund or around 20% of the fiscal year 2025 budget for ARPA-H. After five years, then again at ten, compare to see which group — the one that was actively managed, or the control — produced more breakthroughs, and on what timescale. Although we used biomedicine as an example, the same experiment could just as well be run for physics, materials science, or any other discipline. Any attempt to undertake such an experiment should keep three points top of mind. First, we can predict the topic of future breakthroughs, but the people and vision for how to move the work forward are still important. In practice, this means success requires active program managers with the expertise to develop the science and the authority to do so, including by recruiting investigators. Second, we would be wise to learn from the failures of past attempts to fund transformative research. High among these are funding modestly repackaged work, confusing the genuinely novel with the merely unfamiliar, and relying too much on incumbent investigators. All of these risks can be mitigated by thoroughly and intelligently integrating high quality data into portfolio management. Finally, we need to have patience. Even with strong funding support, producing a breakthrough takes time. If supporting breakthroughs is the best way to nurture the birth of new fields, we also need to accurately describe and properly manage the other two stages, so that we invest wisely throughout the productive lifetime of ideas and divest once they reach the point of diminishing returns. We would benefit from more study of all of these phases, especially the transition from one to another. More research could answer questions like: When does a breakthrough become an established field? How do the availability of funding, the size and characteristics of the available workforce, and the accumulation of evidence that disagrees with prevailing models affect a field’s decline? Exactly how do old ideas give birth to new ones, and can we speed up the process? The more we understand about the dynamics of scientific progress, the better we can maximize the odds that our curiosity leads to results. I’d call that finding a way to make our own luck.
Three RWJBarnabas Health Hospitals Recognized Among Newsweek's Best Hospitals for Specialized Care for 2026
Robert Wood Johnson University Hospital (RWJUH), Cooperman Barnabas Medical Center (CBMC) and Robert Wood Johnson University Hospital Somerset (RWJUH Somerset), all RWJBarnabas Health facilities, have been recognized among Newsweek's America’s Best Hospitals for Specialized Care 2026.
Breaking down EA Sports' College Football 27 team ratings: who's too high, who's too low?
EA Sports College Football 27 team ratings spark debate, with Georgia, Alabama, and Clemson among teams arguably rated too low for their talent.
How Caesars’ Expanded Tribal iGaming and Community Partnership Could Shape Caesars Entertainment (CZR) Investors’ Outlook
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$10 Million Gift to UAB Aims to Improve Rural Health Care Across Alabama
A $10 million gift to the University of Alabama at Birmingham will help train more primary care physicians in rural communities and encourage them to stay and p
How should European scientists respond to the US AI kill switch?
Earlier in June, Europe’s worst fears of technological dependence were confirmed when the White House ordered the AI firm Anthropic to stop non-US citizens using its leading models. This kill-switch moment crystalised anxieties in Brussels that the continent, lagging the US on the creation of leading-edge AI models, is now a technological of vassal of Washington. The shock has specific implications for European scientists and universities. Some governments are now worried that with AI being integrated into labs, Donald Trump now has his finger hovering over an off switch for European science. “Having restrictions on this tool, it can have an impact on our own research,” said France’s research minister, Philippe Baptiste, at the VivaTech conference in Paris on June 18.Baptiste, himself a former academic, said that colleagues in mathematics had recently warned him they were now cut off from leading-edge US models, risking their work. “This model is not available anymore now because of the US restriction, and for the first time this had an impact on mathematics,” a field where large language models (LLMs) are making a significant contribution, said Baptiste. So, should European scientists avoid relying on US models in the future? Or would this be a self-harming overreaction? And how is AI being used in science, anyway? What happened?On June 12, it emerged that Washington, citing cybersecurity concerns, had ordered Anthropic to stop non-US citizens using two models: Claude Mythos 5, and Claude Fable 5, a version of Mythos but with guardrails to prevent abuse. Anthropic said Washington’s concerns were overblown. But forced to follow the order, yet with no way to check who was using the models, the company suddenly shut down access for everyone, US citizens included. There’s still no agreement on how to restore broad access. But last week, Bloomberg reported that select US companies, and the US government, still had access to Mythos despite the ban, but the EU’s cybersecurity agency Enisa had been shut out. Class division of researchersIn the longer term, access outside the US should be restored, said Marcel Salathé, co-director of the AI centre at the Federal Polytechnic School of Lausanne (EPFL), because a permanent restriction would be financially ruinous to US AI firms. “Even Trump will eventually budge to economic pressure,” he said.However, US AI firms might end up operating rather like banks, doing due diligence on users of their leading-edge AI models, he went on.European scientists are unlikely to fall foul of such checks, he said. But having a Chinese postgraduate in their lab, or doing a type of research the US disapproved of, could potentially result in access being denied. “It will create a sort of class division of researchers,” he said. More than frontier modelsHowever, successfully deploying AI in science is about far more than just having access to leading LLMs such as Mythos.Instead, many science-specific tools, most famously Alphafold, which predicts protein folding structures, require “far less” computing power to train than frontier models, well within the capabilities of European supercomputers, according to a recent analysis by the Arq Foundation, a Brussel-based AI think tank. Instead, tools such as Alphafold are possible because certain fields, like protein folding, weather prediction or astronomy, have large, clean, standardised datasets that can be used to train predictive models. Rather than compute, “data is the central constraint for AI for science,” the report says. For example, a less powerful physics model trained on CERN’s data “will be more valuable than the best model without certain data,” said Bengüsu Özcan, author of the report. European advantage?Europe could therefore steal a march by using its scientific data and infrastructure to create models US digital giants cannot. “They might actually match or go even beyond what these big [US] companies are doing,” said Özcan.Indeed, some European start-ups hope to create automated testing labs to create the kind of standardised data that could speed up the discovery of new materials. Materials scientists say there’s currently too little data to train models. AI scientistsHowever, even if the bottleneck for AI in science is often data, rather than compute, being at the mercy of the US for LLM access could still become a problem for European scientists. A new class of “AI scientists” based on leading LLMs is also emerging, Özcan’s report says.Unlike domain-specific tools like Alphafold, these try to automate day-to-day scientific work, by providing an overarching tool that coordinates specific models to synthesise existing literature, generate hypotheses or run analysis of data. The problem for Europe, however, is that these tools are sometimes based on US leading models. Google Deepmind’s AI Co-Scientist, for example, is built on Google’s Gemini LLM. Systematic failureThese scientific automation tools are still in their early stages, and still exhibit “systematic failures on scientific tasks,” Özcan’s report says. One of the problems is that the messy, day-to-day process of scientific discovery is largely not documented, meaning LLMs don’t have a good source of data to learn how scientists actually work. Meanwhile, some tasks, such as literature synthesis, don’t typically require access to leading edge models.However, the performance of AI scientific assistants could improve as companies such as Google pour resources into developing them. Rely on US“Unfortunately, for scientific assistants, there is not much we can do right now except rely on US frontier AI,” said Antoine Bosselut, a natural language processing expert based at EPFL. Chinese-built open models, which can run on local computers, lessening the risk of a shutdown, are touted as one alternative to US dependence. There’s also Mistral, once seen as Europe’s main AI hope, but the Paris-based company has seen its recent models fall behind in performance. But the Chinese alternatives are generally not as capable as US frontier AI models, said Bosselut, unless paired with fiddly, custom tools that allows them to act as independent agents. “Most scientists do not have the time,” he said. Don’t jump ship yetAlthough the kill switch moment is seen a warning shot for European scientists, it doesn’t mean labs should abandon US AI tools immediately. “I do not think the right response is simply to abandon US-based models and systems under the banner of sovereignty or independence,” said Mattias Björnmalm, secretary general of the Cesaer university association. “That would be an overreaction.”Related articlesEuropean sovereignty in AI requires ‘ugly trade-offs,’ say experts Robotic lab start-up makes case for €500M EU-funded materials testing facilityAI in science: is it useful? Instead, European researchers need to ask themselves whether they’re becoming dependent on technology that could be turned off in Washington, said Özcan. “They might not see this today, but they should really start asking this question,” she said. European researchers need a plan B, said Salathé. “I would recommend to every researcher, very proactively explore alternatives.”Own toolsIn addition, Björnmalm and others want European research institutions to develop their own scientific AI tools.Instead of signing AI deals with US digital giants, European universities should be using this money to create their own models, which may end up being superior for research, said Sabine Leonelli, an expert on the use of AI in science at the Technical University of Munich. “Universities in Europe seem to be happy to sign commercial contracts with US companies on the assumption [their AI tools] are better,” she said. But US frontier LLMs are typically opaque, and have been developed without independent scientific input, she said. “This is not good enough for science.”Last year, Swiss researchers released Apertus, an LLM designed to be completely transparent, from its development methods to its training data. The idea is that this makes scientific tools built on top of the model far more reproducible than with closed, commercial alternatives.“Europe needs more of this: serious capacity-building that gives researchers, universities and companies credible options,” said Björnmalm.
Anthropic accused Alibaba of exploiting its AI models
Anthropic said the Chinese company interacted with Claude millions of times through 25,000 fraudulent accounts in recent months.
Samsung confirms the existence of the Galaxy S27 Pro
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Cited 23 June: Project Cosmos launch | Science ‘under attack’ at Bonn | Emissions inequality
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Judge blocks use of database to check citizenship in voting
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Judge blocks use of database to check citizenship in voting
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GOP runoff wins, Tuberville lawsuit reshape Alabama politics
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“Criminal Approach to Politics”: Trump Ally Abelardo de la Espriella Wins Colombian Presidency
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Monday morning observations about JJ Wetherholt, Masyn Winn
Folks, I don’t think I got it today. I spent all of Thursday getting ready for a weekend trip, of course not giving myself enough time to do everything I wanted to do, so the entire day was hectic. I arrived at my destination that night, and then drank heavily for three straight nights. I […]
Celtic move for defenders Smajlovic & Saracchi
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Fish consumption advisory raises concerns over ‘Sound Science’ law |…
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2026 NBA draft profiles: Philadelphia 76ers prospect Labaron Philon
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Another look at Oyarzabal's first goal for Spain 🇪🇸
Another look at Oyarzabal's first goal for Spain 🇪🇸
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Colombia's presidential runoff election will decide how the country continues to tackle drug trafficking
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The business secretary knows about jobs, and seems pretty sure Keir is out of one
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🚨 Now it’s getting serious! Oranje tear Sweden apart
The emphatic 5-1 win in the opener briefly made Sweden’s problems in qualifying for the World Cup fade into the background. But the Netherlands are now exposing them in impressive fashion in the sec...
‘Influence isn’t just about entertainment’: Olandria Carthen’s platform goes global in new Rolling Stone Africa cover story
The “Love Island USA” breakout takes her story from Alabama to Lagos, showing what can happen when reality TV fame
At marine science camp, Pinellas teens get firsthand look at Gulf life
Oceanography Camp Especially for Girls has long aimed to steer young women into STEM.
New research casts doubt on cannabis benefits, cites mental health risks
Fox News senior medical analyst Dr. Marc Siegel discusses new research on modern marijuana’s high THC potency and increased mental health risks on ‘Fox & Friends Weekend.’
What Democrats want: New York congressional race showcases fight over party’s future
In NY-12, four Democrats, including one Kennedy, are vying to replace Jerry Nadler – and potentially shake things up
Way-too-early SEC softball power rankings for 2027 season
Teams such as Texas, Alabama, and Oklahoma headline the early 2027 SEC softball power rankings. Here is how the conference currently looks for 2027.
Citizen Science Lab’s new home brings hope to Herron Avenue corridor
The Citizen Science Lab expanded into the newly renovated, previously long-abandoned Martin Luther King, Jr. Reading and Cultural Center in the Hill District.
Colman Domingo explains his 'wild' theory about Hitchcock classic 'Rear Window'
Colman Domingo doesn't play about his favorite films, but he does hold one playful theory about the best of his best — 'Rear Window,' which blew the mind of TCM host Ben Mankiewicz.
Colts star Sauce Gardner clears up confusion about his date of birth: Why almost everyone got his age wrong
Sauce Gardner weirdly had to confirm his age after years of confusion regarding the colts star defensive back.
New Mexico lawmakers press Presbyterian Health Plan over changes
"When the need is great but the money’s not, there’s an exodus," said Rep. Patricia Roybal Caballero, D-Albuquerque.
K-Beauty's New Frontier: Microbiome Science Hits U.S. Retail Shelves
South Korean brand Lactomedi’s nationwide CVS launch signals a major shift in feminine care, blending K-Beauty innovation with advanced microbiome science.
Mangione lawyers abandon psychiatric defense over health CEO’s killing
Legal team of alleged gunman, 28, reverses position on ‘extreme emotional disturbance’ defense after one day
The Politics Hour: A historic D.C. primary election and Montgomery County voting on new leadership
We break down D.C. primary elections with Democratic nominee for D.C. Delegate Robert White, At-Large Councilmember-elect Elissa Silverman, and WAMU's D.C. politics reporter Alex Koma. Plus, we preview Maryland's primaries with WAMU's Maryland reporter Jenny Abamu.
RWJBarnabas Health Invests $1.5 Million to Support Local Community Health Initiatives in New Brunswick, Middlesex County
RWJBarnabas Health today announced a combined $1.5 million investment to support local organizations working to address barriers to care, food insecurity and economic stability among underserved communities in New Brunswick and Middlesex County.
Stanley Cup cash flow: Downtown Raleigh businesses prepare for big crowds during Saturday's parade
Before Saturday's Stanley Cup championship parade, downtown Raleigh businesses are stocking up for what could be the busiest day of the year.
The Carry-On Essentials Female Founders Pack For Business Travel
The best carry-on essentials for business travel take you from a flight to the boardroom with ease. We spoke with top female executives to get their favorite picks.
Africa Is Essential To 'Global' Business Education
Rabat Business School's Nicolas Arnaud argues that true internationalization means treating African institutions as knowledge creators – not just emerging-market field trips.
Analyst Perspectives on Oracle’s Strategy to Help Customers Secure Business Data against AI Threats
Oracle today announced its AI security strategy based on three principles: secure at source, secure at speed, and secure through resilience. To help customers accelerate and strengthen their security posture Oracle is making several of its most widely deployed and battle-tested database security, patching, testing, and lifecycle management tools available at no cost for a limited time, or at a 90% discount on one-year term licenses. This move has been positively received by leading industry analysts and reaffirms Oracle’s leadership in equipping enterprises to maximize their resilience in the face of increasing AI-era security threats.
RWJBarnabas Health Invests $1.7 Million to Support Local Community Health Initiatives in Jersey City, Hudson County
RWJBarnabas Health today announced a combined $1.7 million investment to support local organizations working to address barriers to care, food insecurity, and economic stability among underserved communities in Jersey City and Hudson County.
Deep-red state wrapped race calls before DC started counting, despite same poll deadline
Alabama called races within an hour of polls closing while D.C. officials didn't begin counting ballots until nearly three hours later Tuesday.
Abarca Health and LucyRx Announce Strategic Combination to Create the Only Modern PBM Built for Commercial and Government Scale
Abarca Health and LucyRx today announced a strategic combination to create the only modern, independent pharmacy benefit manager with the scale, technology, and track record to credibly serve commercial and government clients of any size. Combined, Abarca and LucyRx will provide prescription services to more than 9 million members across the United States.
Abarca Health And LucyRx To Merge Into Alternative To Big Three PBMs
Abarca Health and LucyRx - two independent pharmacy benefit managers - have agreed to merge asregulators and the public seek a better price on prescription drugs.
Yankees news: Injury updates and painful prospect news
Bad injury news on Grisham, Stanton, and Lombard; Caballero and the pitch clock remain a story; Yanks release Brown
Trump wins two, loses one: Georgia billionaire delivers rare blow to endorsement machine
Trump-backed candidates won two of three key GOP runoffs in Georgia and Alabama, but lost the gubernatorial race to billionaire Rick Jackson.
Trump-backed U.S. Rep. Barry Moore battles ex-Navy SEAL Jared Hudson in GOP Senate runoff in Alabama
The Alabama race will be another test of Trump's endorsement powers, as his picks have largely prevailed in Republican primaries this year.
The places to watch in Alabama and Georgia tonight: From the Politics Desk
Plus, Trump starts shifting his focus back to Ukraine.
Fox Frustrated by ESPN’s Lack of World Cup Coverage
Fox took over from ESPN as the World Cup rightsholder in 2018.
Live results: Alabama midterm primary runoffs
Alabama voters will return to the polls Tuesday to finalize nominees for an open U.S. Senate seat and a handful of other contests in which no candidate received a majority of votes in the May 19 primary.
Play Chaos Cubed Today
Chaos Cubed has landed in Minecraft! Explore a striking cave biome filled with bubbling sulfur pools, build with sulfur and cinnabar, and discover the sulfur cube’s curious appetite for blocks! From bouncing and sliding to explosive surprises, this unpredictable mob unlocks exciting new ways to build, compete, and survive. Play Chaos Cubed today in Minecraft!
What to watch in midterm primaries and runoffs in Alabama, Georgia, D.C. and more
President Donald Trump has been at the center of this year's midterm campaigns, and his influence will be tested in different ways Tuesday as four states and the District of Columbia hold primaries.
Oracle champions sustainable and responsible AI at the Global Data Science and AI Summit, iLabAfrica Centre at Strathmore University, Nairobi
Oracle champions sustainable and responsible AI at the Global Data Science and AI Summit, iLabAfrica Centre at Strathmore University, Nairobi
Yankees news: Rice, Caballero go deep to take Toronto series
Yanks win first series in Toronto since 2023; no catching “yet” for Rice; Dominguez’s long day ends in long ball; remembering Al Closter.
What to watch in Tuesday’s primaries in Georgia, Alabama, Oklahoma and Washington, DC
Georgia Gov. Brian Kemp survived President Donald Trump’s bid to oust him in a Republican primary four years ago. Kemp’s hand-picked candidate in a Senate primary on Tuesday might not be as lucky.
Trump-backed US Rep. Barry Moore battles ex-Navy SEAL Jared Hudson in GOP Senate runoff in Alabama
Alabama voters are deciding party nominations for an open U.S. Senate seat
Can $100 Million Overcome a Trump Endorsement? What to Watch in Tuesday's Elections
WASHINGTON (AP) — An endorsement from President Donald Trump is worth a lot in Republican primaries. But is it worth more than $100 million in Georgia? Can it propel a sitting congressman past an insurgent outsider in Alabama? Can it transform a candidate into a front-runner in Oklahoma? Trump has ...
Fowler Packing's Kiah Ruvalcaba recognized among produce industry leaders
Three professionals with deep Central Valley roots have been named to Produce Business magazine's 2026 "40 Under Forty" list, which recognizes emerging leaders across the fresh produce industry — with Fresno-based Fowler Packing Company's