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Starland business owners frustrated after new string of burglaries
'It can be the difference between staying open and closing your doors,' Starland business owners are on edge after another round of burglaries, with police asking for help identifying a suspect —
More Starland District break-ins leave business owners concerned
After a string of break-ins at Starland District’s small businesses, community members are speaking out about their concerns.
Texans third-string QB Graham Mertz leaves with injury
Backup quarterback Davis Mills was expected to play only one series in Thursday night's preseason opener for the Texans.
Palmetto Sports Daily: Chuba Hubbard out with hamstring injury, former Irmo WR begins second year at SC
PSD is back with thoughts on the Panthers playing starters in the preseason against Buffalo.
Jordyn Tyson exited Thursday's practice early with hamstring issue
The Saints have an injury concern with one of their key young offensive players.
Saints' Jordyn Tyson leaves practice early with worrying hamstring injury
This isn't good news for the Saints' first-round WR.
The Science of “Ramping Up”: Why Aaron Glenn Playing Starters is a Calculated Risk Worth Taking
For years, the conventional wisdom in NFL training camps was simple: wrap the starters in bubble wrap, hold them out of preseason games, save them for Week 1. And every September, like clockwork, the league watches soft-tissue injuries pile up anyway – hamstrings, calves, Achilles, all the non contact stuff that has nothing to do […]
The far left hits a wall
The movement had been riding high off a string of primary victories this cycle. But Francesca Hong’s loss Wednesday led to an immediate round of finger-pointing.
Hunter Biden’s viral interviews fuel speculation about possible political future
Hunter Biden has returned to the public eye with a string of high-profile and viral interviews, fueling renewed speculation about a political future.
The U.S. Healthcare System is Already Mostly Socialized
Now that Abdul El-Sayed is the Democratic nominee for Michigan’s open Senate seat, the outcome of this crucial race will depend mainly on two things: Whether Republicans succeed in demonizing El-Sayed because he’s brown and a Muslim, and whether they succeed in demonizing him as a left-wing radical. I will defer for the now the question of whether bigotry will be effective this year, although I will address it another day. What I want to address instead is El-Sayed’s signature issue — healthcare. Yes, El-Sayed advocates Medicare for All, a position the usual suspects denounce as “socialism.” I will get to the politics of his stance soon. Today, however, I want to talk about the substance. We should be clear that El-Sayed doesn’t even call himself a socialist. On the contrary, he explicitly disavows the label, saying “I’m a capitalist who just knows about capitalism”. In fact, as I explained in a previous post, the policies that El-Sayed advocates qualify him as a social democrat, not a socialist. Still, El-Sayed advocates a system under which the government would pay almost all medical expenses. Isn’t that socialism? Well, if that is the criterion then much of U.S. healthcare is already socialist. In fact, the government’s role is so large that U.S. healthcare is better described as partially privatized socialism than as anything resembling a free market. Let’s start with the raw numbers on health insurance, which pays the bulk of Americans’ medical expenses. Americans receive health insurance either from private companies or from public programs, overwhelmingly Medicare and Medicaid. Here’s what the breakdown of coverage and spending between private and public looked like in 2024: While a majority of Americans with health insurance get it from private companies, well over 100 million of us are covered by government programs instead. And these government programs pay more total dollars for medical bills than the private insurers do. Why do government programs that cover a minority of the population account for a majority of health insurers’ outlays? Mainly because Medicare covers seniors, and we’re expensive. Also, while Medicaid covers many younger Americans, disabled and elderly beneficiaries account for most of its spending. Even by the raw numbers, then, U.S. health insurance looks as much public as private. But that understates the government’s role: Private health insurance in the U.S. is both highly regulated and heavily subsidized. This is obviously true for the insurance coverage purchased by tens of millions of Americans through the exchanges established by the Affordable Care Act. But employment-based health insurance, which covers 161 million Americans, is far more of a government creation than most people realize. For employment-based insurance exists largely because of huge implicit government subsidies that come with major strings attached. Here’s how that works. If your employer pays you $10,000, that’s taxable income. But if your employer pays $10,000 toward a company health insurance plan that meets certain criteria, it isn’t taxable. That’s a huge effective subsidy, running at more than $300 billion a year. Take that subsidy into account, along with the more than $100 billion per year spent subsidizing policies purchased under the ACA, as well as the outlays on Medicare and Medicaid, and net effect is that the government pays for more than two-thirds of Americans’ health insurance. Granted, there are strings attached. Roughly speaking, employment-based health plans can’t discriminate based on medical history — that is, they can’t deny coverage to employees with pre-existing conditions — and they also can’t offer the plans only to highly compensated employees — a health plan that is only for the C-suite is considered taxable income. So given the restrictions of the federal tax code, employer-based health insurance is a lot like Obamacare, which also prohibits discrimination based on medical history and provides subsidies to make insurance affordable to lower-paid workers. The fact is that virtually all of private healthcare insurance is already well under some form of government control through regulation and tax subsidies. How should we think about this system? First of all, is Medicare socialist? Don’t tell anyone, but the way Medicare operates — it covers every senior’s medical expenses, whatever they turn out to be, while being funded by taxes that depend on one’s income — could be summarized by the old Marxist slogan “From each according to his ability, to each according to his need.” And back in 1961, when Ronald Reagan was the face of a last-ditch effort by the American Medical Association to block the creation of Medicare, he denounced Medicare as “socialized medicine” and warned that it would destroy our freedom. In reality, American freedom survived until Jan. 20, 2025, while Medicare is immensely popular, with an 82 percent favorable rating in the most recent KFF survey. Medicaid, government health insurance for lower-income Americans, comes in at 73 percent. This is in sharp contrast to public views about private insurers, who are widely disliked if not hated and accused of denying essential care. Furthermore, if Medicare is socialism, then the whole U.S. health insurance system, with the government paying most of the bills and placing conditions on private insurers, is almost equally socialist. If you insist on calling any program the government pays for and regulates socialist, then U.S. healthcare would best be described as a partially privatized form of socialism. And one must ask, what is the point of the part that is privatized? Do private insurers add anything positive? Or are they simply parasites, skimming off money that could have been paying for care? The case for viewing insurers as parasites is strong. Many Medicare benefits are now delivered via Medicare Advantage, that is, plans paid for by the government but run through insurance companies. MedPAC, an independent advisory commission, estimates that last year Medicare Advantage plans were overpaid by $84 billion, thanks to practices such as “upcoding,” in which patients’ health problems are overstated to get larger sums from Medicare. Assessing the waste from employer-based insurance is harder, but most evidence suggests that private insurers have substantially higher administrative costs than Medicare does. Furthermore, the complexity of private insurance, with multiple payers all trying to deny care when they can, is a huge burden both on providers — doctors, nurses, and hospitals — and on patients. What do private insurers offer to compensate for these costs? One must go through intellectual contortions to avoid the conclusion that they are, in fact, parasites. Which brings me back to El-Sayed. In supporting Medicare for All, he’s basically calling for an end to the partial, parasitic privatization of a healthcare system that is already hugely dependent on public funding. When one looks at it that way, it’s not at all a radical proposal. Admittedly, the political lift requires overcoming the opposition to higher taxes to pay for Medicare for All. Political realism rather than economics was the reason I and many other progressives supported Obamacare, with all its complexities, rather than demanding an immediate move to Medicare for All. But the political calculus may very well have shifted since the 2000s, as Americans are fed up with a system of unaffordable premiums, rampant claim denials, and byzantine claim administration. Moreover, funding healthcare insurance through taxation would allow for a much more progressive distribution of the cost. That is, compared to the present system, middle-income households would pay less as high-income households would pay more. And the U.S. would stop wasting large sums on pointless administrative costs. So let’s be clear: El-Sayed’s healthcare platform is perfectly reasonable on the merits of cost, fairness and health efficacy. And with private insurers never more hated, while millions of Americans are losing their health insurance, 2026 may be its time. MUSICAL CODA
The world's leading AI companies struggle to contain latest models
There's been a recent string of cybersecurity incidents among the world's leading AI models. Here's a look at what's happened.
Eagles preach patience as Makai Lemon continues to battle hamstring injury
The Eagles' 2026 first-round pick has missed four consecutive practices.
49ers' Luke Gifford: Dealing with hamstring injury
49ers' Luke Gifford: Dealing with hamstring injury
Report: Panthers are expected to sign QB Kyle Trask
Panthers quarterback Haynes King injured his hamstring in the Hall of Fame Game this week and they are set to add another quarterback to the roster for the coming practice week.
Detroit Lions Reach Injury Settlement With Young Wide Receiver
The Detroit Lions have reached an injury settlement with young wide receiver Lawrence Keys following his training camp hamstring injury.
With support for Israel roiling U.S. politics, Israelis fear a permanent shift
Abdul El-Sayed’s victory in Michigan’s Democratic Senate primary adds to a string of upsets that reflect growing criticism of Israel.
Nationals outlast Phillies after Painter exits post-deadline start early
Andrew Painter, who looked strong, exited early with left hamstring tightness as the Phillies’ post-deadline rotation picture grew more uncertain.
Google Contacts reveals what colors Pixel 11 HiLight will support
Ahead of the Pixel 11 launch, Google Contacts for Android has gained strings detailing upcoming support for HiLight.
Malaysia Says Investment Pipeline Holds Despite Political Angst
Malaysia continues to attract strong foreign investor interest despite growing political uncertainty following a string of local election setbacks for Prime Minister Anwar Ibrahim’s coalition.
Sony Music Appoints Stephanie Yu to General Counsel and Executive Vice President, Business and Legal Affairs
Sony Music today announced the appointment of Stephanie Yu to General Counsel and Executive Vice President, Business and Legal Affairs. She reports to Rob Stringer, Chairman, Sony Music Group and Kevin Kelleher, COO, Sony Music. Yu will be responsible for overseeing the business, legal and governmental affairs strategies and activities for the company globally. Stringer […]
Sony Music Appoints Stephanie Yu to General Counsel and Executive Vice President, Business and Legal Affairs
Sony Music today announced the appointment of Stephanie Yu to General Counsel and Executive Vice President, Business and Legal Affairs. She reports to Rob Stringer, Chairman, Sony Music Group and Kevin Kelleher, COO, Sony Music. Yu will be responsible for overseeing the business, legal and governmental affairs strategies and activities for the company globally. Stringer […]
Review: Lies Of P: Complete Edition (Switch 2) - No Strings On This Superb, Immersive Soulslike
Little puppet made of pine, awake
2026 Tobacco Heritage Day at L.W. Paul Living History Farm in Conway
For many in attendance of Tobacco Heritage Day on Saturday, Aug. 1, tobacco farming wasn't just history — it was part of their childhood. Generations of Horry County families made a living in the tobacco fields, where children often spent summers priming leaves, loading wagons or stringing tobacco by hand before it was cured in barns. Once the county's dominant cash crop, tobacco shaped the local economy and way of life for decades, with thousands of acres planted each year and warehouses bustling during auction season.
Yankees news: New York still in on Goodman, Ward
Yanks keeping tabs on Ward, Goodman; Chisholm sits Friday after dealing with hamstring cramps; Mets start sell-off
Carlton Davis' Hamstring Injury Exposes Patriots' Secondary Depth Concerns
The first minor warning sign of New England Patriots training camp 2026 has been illuminated. It is hardly a call for panic but ESPN's Mike Reiss noted on "X," late Friday afternoon that the team had brought in a pair of free agent defensive backs, Eric Butler and Tysheem Johnson, for tryouts. While this practice is commonplace from training camp through the regular season, the fact that a pair of defensive backs were in make the visits extremely timely.
One Chiefs player leaves Friday’s practice with a strained hamstring
Kansas City’s head coach provided an injury update after Friday’s training camp practice.
Packers' Nixon says hamstring tightness caused him to miss first practice
The 29-year-old Nixon started all 18 games (including playoffs) last season and was named to the NFC’s Pro Bowl team as an alternate.
Packers rookie OL Jager Burton missing practice with hamstring injury
The Packers are without rookie OL Jager Burton on Thursday due to a new hamstring injury suffered on Wednesday.
'Not alike any we've ever seen before': Three of the 12 galaxies in this cosmic string are missing a crucial component of the universe
Astronomers have discovered a third galaxy without dark matter in a strange string of a dozen dwarf galaxies. A violent collision is likely to blame.
Soros network rebuilds progressive prosecutor push after string of election losses
Soros family pumped more than $1 million into PACs backing progressive prosecutors for 2026 elections, despite recall elections and defeats that removed dozens of district attorneys.
Sammy Hagar invites David Lee Roth to Vegas after canceled shows
David Lee Roth is getting support from his former Van Halen replacement, Sammy Hagar, following a string of tour cancelations.
TotalEnergies to Appeal Court Order to Adapt Business to Climate Goals
TotalEnergies is appealing a French court ruling that held it responsible for climate change, joining Shell in a growing string of climate lawsuits.
Community searching for answers after several business burgarlized
Savannah police are seeking help identifying a suspect after a string of burglaries hit Starland Strange and Bazaar.
New York’s organized labor looks to regroup after string of political defeats
Canvassers talking to union members this year will be taking an extra beat when they knock on doors.
Health fears linger in a Brazilian neighborhood built over oil waste
SÃO SEBASTIÃO, Brazil — In front of the house where she has lived for decades, Cosma da Silva points to nearby homes in her Itatinga neighborhood and lists a string of cancer cases. “There’s a woman with cancer over there. Another one lives in that building. And yet another one there [points at the place]. People […]
Seattle Mariners Outfielder Exits Game Against Cincinnati Reds
Julio Rodriguez was pulled from Monday's game against the Reds after a throw hit him on the hamstring.
World-class quartet to perform Ives, Brahms
The DaPonte String Quartet will perform at St. Andrew Lutheran Church in Ellsworth on Friday, July 31, at 7 p.m.
Chicago police warn about string of South Side business robberies
The robberies occurred from Jun3 23 to July 18 in seven South Side neighborhoods, Chicago police say.
Entertainment briefs | Humboldt Folklife Festival runs from July 18 to 25 in Blue Lake
July 24’s “Barn Dance” features Lyndsey Battle and Cidermill Stringband at Prasch Hall in Blue Lake, starting at 7 p.m. No experience is needed to attend. Purchase tickets at
US Senate nominee Platner halts campaign after assault allegations
A string of high-profile Democrats have withdrawn support for Platner following sexual assault allegation.
Science on Target: Q2 Research Cores Update
Use the below jump links to navigate to each Research Core update. Postmortem Tissue (PMT) Core Longitudinal Biofluid Core Data Engine Stem Cell Core Postmortem Tissue (PMT) Core The Target ALS Postmortem Core has now collected 650 cases, making it the most comprehensive ALS tissue repository worldwide that is accessible with no-strings-attached to the global […]
These are the best things to do in Brevard this weekend, July 10-16
Find your weekend adventure: Concerts and outdoor fun top our list of Brevard's best things to do.
Lionel Richie reassures fans he is 'doing well' after dizzy spell forced concert cancellations
Lionel Richie shared concert photos and thanked fans for support after falling dizzy on stage in Minnesota forced him to cancel string of Midwest shows.
A Colorado primary defeat highlights a dangerous political environment for Democratic incumbents
Democratic socialist Melat Kiros defeated Rep. Diana DeGette in Denver on Tuesday night, the latest in a string of results heralding big change for the party in Washington.
How the Supreme Court just rewrote the rules of politics
After years of political party power players like Senator Mitch McConnell trying to take control of national party purse strings to which candidates to help and how to shape the party, all it took was one ruling by the Supreme Court to change the way campaign politics is funded. Jen Psaki talks with Jim Messina, former campaign manager for President Barack Obama about how the Supreme Court's ruling changes the game in terms of how political donations are spent.
Supreme Court upholds state transgender sports bans
In the latest of a string of losses for LGBTQ rights, the high court allowed states to bar transgender athletes from girls’ and women’s sports.
Henry Winkler says 'there's a string between' him and his 'Happy Days' costar Ron Howard
Winkler and Howard costarred on the '70s sitcom, and they've remained close in the decades since.
Netflix and Superheroes Are Having a Rough Stretch on Streaming....
(Welcome to my weekly streaming ratings report, the single best guide to what’s popular in streaming TV and what isn’t. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. If you were forwarded this email, please subscribe to get these insights each week.) I have a quick prediction before we start today’s article: You might see this data in future news articles. Not my specific charts or analysis, but the core trend I’ve been monitoring—Netflix is having a lackluster Q2—will become inescapable. Often, folks want to know “What does the data say?” Well, that’s what it says. I haven’t seen this analysis hit the trades really yet, but I have a feeling some other outlets are going to start making this case soon. Remember, you read it here first. You probably have read about the problems facing superhero films at the box office this weekend. Well, this week, I explore whether superheroes are dying on TV as well! And the data says: definitely maybe! We have a lot to cover in today’s Streaming Ratings Report, which covers the two weeks of 18-May and 25-May. Today, I’m just looking at TV, like Netflix’s disappointing Q2, superhero shows underwhelming, a few TV shows dropping off the charts, The Pitt finally ending its epic run on the viewership charts (and whether “view counts” change its status as one of the biggest shows of all time), all the flops, bombs and misses, and a whole lot more. Tomorrow, I’ve got a great rundown of the film side of things. Let’s dive right in! (Reminder: The streaming ratings report focuses on the U.S. market and compiles data from Nielsen’s weekly top ten viewership ranks, Luminate’s Top Ten Data, Showlabs, TV Time trend data, Samba TV household viewership, company datecdotes, Netflix hours viewed data, Google Trends, and IMDb to determine the most popular content. While most data points are current, Nielsen’s data covers the weeks of May 18th to May 31st, 2026. You can find a link to my terminology here.) Subscribe Television - Netflix’s Q2 Slump Continues Having analyzed streaming ratings for going on half a decade, I have learned to trust my gut, but I’m always relieved when I can find actual data to back it up. For example, after a string of very popular shows like Stranger Things, Bridgerton, The Lincoln Lawyer and The Night Agent came out, week after week, in January and February, my gut wondered if Netflix had enough new and returning TV shows to sustain them throughout the year. Since then, Netflix’s post-March slate of shows has not impressed me. This week seemed to feature a potential new hit, but then, like a classic Duffer Bros. TV show, there was a twist. I speak of The Boroughs, Netflix’s latest (and last) Duffer Bros. produced show. The pitch is “Stranger Things with older actors”. And it topped the Nielsen charts: With just two weeks of viewership, The Boroughs would have been a top 25 debut show last year: But here’s the twist: Netflix has already cancelled The Boroughs! What happened? Likely a few things. First, the show didn’t do as well globally as it did in the US. As What’s on Netflix showed, it lagged behind several other shows that got cancelled. Second, its completion rate was likely low; after an initial burst of interest, it quickly dropped off on the Samba TV and Luminate charts. Third, the Duffer Bros. left Netflix for Paramount, and that may have factored into Netflix’s decision here. (Though I tend to believe that if a show is doing well, Netflix would have kept greenlighting seasons.) Still, just because I can explain why Netflix may have cancelled this show doesn’t mean I’m justifying it. In particular, as I’ve noted before, Netflix is losing a lot of their bigger shows as they reach their natural ends, and they need to replace those shows. This show had the hallmarks of a big new genre show, and it’s their biggest hit of the last few months (in the US at least), but now it’s done. Netflix’s other show this week—The Four Seasons, the second season of the “hit” show from last year—definitely disappointed. Its sophomore season had about half the viewership of the first, only 12.7 million hours. It also only had a two week run on Samba TV, and its numbers were all down on Luminate too. In other words, even with two successes, the Q2 slump for Netflix looks real: I could add to the list of disappointments: Both Lord of the Files and Man on Fire had short runs on the Nielsen charts. Running Point’s sophomore season also opened to about half its viewership, similar to The Four Seasons. A Good Girl’s Guide to Murder’s second season—see below—didn’t even make any of the three viewership charts I track, unlike the first season. Netflix is absolutely having a dismal second three months of 2026. If this Nielsen data is any indication, and I think it is, I think this will show up in Netflix’s engagement report, and maybe even their financial outcomes. And the rest of June doesn’t look much better. We have two hit shows coming back—Sweet Magnolias, one of their quietest big shows, and Avatar: The Last Airbender, a big hit for them in 2024—but the other big swings are limited series crime thrillers i.e. no future season potential. Like I said above, sometimes when I uncover a juicy nugget like this, other outlets end up writing very similar articles mimicking the data without credit. We’ll see if that happens this time! Share Television - The State of Superhero Shows on Streaming When I first heard the pitch for Spider-Noir—a Sony TV show on Prime Video that binge-released eight episodes first on MGM+ then on Prime Video two days later—I had my doubts. It’s a live-action Spider-Man show set in the 1930s, starring Nicholas Cage, based on a cameo of a character in Spider-Man: Into the Spider-Verse. No, seriously, that’s the pitch. That could either go terrifically well or horribly wrong. Great because, Spider-Man. He’s the biggest superhero we have. I’ve seen tracking numbers that put the new _Spider-Man: Brand New Da_y as the blockbuster of the year and initial pre-sales back that up. And yet this Spider-Noir pitch feels very esoteric. (Also, the eight-episode binge release feels very “Amazon copying Netflix” again.) So what’s the data say? And what does this say about the future of superhero shows?
Dodgers Reinstate Teoscar Hernández from Injured List
The Los Angeles Dodgers brought back outfielder Teoscar Hernández from the injured list with a hamstring strain on Monday.
Dodgers getting stronger, planning to activate Teoscar Hernández
The Los Angeles outfielder has been on the IL since May 29 with a hamstring strain.
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.
Trio behind string of business burglaries caught after chase through Tucker
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Jeffrey Donaldson's first night in prison as downfall shakes NI politics
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Bardstown Road businesses call for change following fights, shootings
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Why Extreme Sports Enthusiasts Keep Jumping After a String of Tragedies
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World Cup 2026: Tino Livramento suffers hamstring injury and replaced by Trevoh Chalobah in England squad
State tries to shut down Evanston psychiatric facility after string of crimes and violations
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James Uthmeier files lawsuit against TikTok for violating state law protecting kids
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Mitch McConnell Is Hospitalized, His Spokesman Says
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Dodgers' Shohei Ohtani exits with knee, hamstring issue vs. Pirates
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Platner seeks Democratic nomination for US Senate
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Wisconsin Badgers pushing to complete another massive 2027 commitment flip
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Advocates say feds' Medicaid work rule could make qualifying for healthcare needlessly hard
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Hackers breach senior US Space Force official’s Instagram account and post Iranian propaganda
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Scientists Think They Just Accidentally Proved String Theory
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Minneapolis police believe string of business burglaries across the metro are connected
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String theory suddenly emerged from simple physics rules
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New MatterChat Model Helps AI to ‘See’ the Language of Science
From writing emails to generating computer code, much of the artificial intelligence prevalent in our daily lives has succeeded by mastering one domain: text. However, this leaves a major blind spot in the physical sciences, where models depend on the high-resolution, three-dimensional data of the physical world, like the intricate lattice of atoms in a crystal. Delivering on the promise of using AI for science requires teaching these data-driven text models to seamlessly “talk to” physics-based models. Now, a new AI framework from Lawrence Berkeley National Laboratory (Berkeley Lab), called MatterChat, solves this problem by creating a specialized “bridge.” It connects the conversational power of a Large Language Model (LLM) with a physics-based AI that models “interatomic potentials”: the complex physical forces between atoms. The resulting system already significantly outperforms general-purpose AI tools like GPT-4 at predicting material properties, and the team hopes it can accelerate scientific discovery by serving as a robust research partner that provides grounded insights and generates step-by-step instructions for synthesizing novel materials. A paper describing this work was recently published in Nature Machine Intelligence. “Traditional simulations can provide the physical rigor required for materials science, yet their computational cost remains prohibitive for high-throughput screening. Conversely, while LLMs excel at rapid knowledge synthesis, they inherently lack the ‘structural vision’ to interpret materials directly from their underlying atomic coordinates,” said Yingheng Tang, a postdoctoral researcher in Berkeley Lab’s Applied Math and Computational Research Division (AMCR) and lead author on the paper. “MatterChat was built to solve this dilemma, empowering LLMs with a structural ‘vision’ that allows researchers to leverage their full potential for solving complex, real-world materials challenges.” Empowering language models to solve complex challenges in materials science To build MatterChat, the Berkeley Lab team drew inspiration from technologies like Vision Question Answering (VQA) and Text-to-Image (T2I) generation. In these tasks, AI must translate high-level text concepts into visual images, or vice versa. Doing so requires developers to build tools that “bridge” two fundamentally different forms of data. The researchers adapted this concept to the physical sciences. With MatterChat, they created a “bridge model” that successfully connects an LLM’s general knowledge with the deep understanding of the atomic-scale world encoded in scientific interatomic potentials. Until now, researchers using LLMs to solve materials problems usually had to feed them raw data files as if they were just strings of text. It’s like asking an AI to understand a complex 3D engine based only on a parts list: the LLM can read the names, but it can’t “see” how the atoms fit together in space. MatterChat solves this by training a specialized AI bridge model, pre-trained on millions of crystal structures and an LLM, to align the LLM’s representation of the world with the interatomic potential’s representation of the world. The bridge model can translate physical insights into a format the LLM can actually understand. By giving the LLM these “scientific eyes”— a scientific “inductive bias” in the terminology of AI — the Berkeley Lab team has transformed it into a robust research tool capable of providing grounded scientific insights into complex materials challenges, such as predicting thermal stability or analyzing electronic band gaps. “We think of atoms as living in a physical space, but from a machine learning perspective, they are just vectors living in some very non-trivially structured manifold in a high-dimensional Euclidean space; and, of course, the same is true for the sentences and paragraphs that we use to express our ideas about those atoms,” said co-author Michael Mahoney, Berkeley Lab’s Scientific Data Division (SDD) AI Initiative Research Lead. “The bridge model basically gets those two structures to ‘talk with’ each other.” As a proof-of-concept of this general approach, the team trained their bridge model on a dataset curated by pairing nearly 143,000 stable atomic structures from the Materials Project with their corresponding physical properties. This training data was automatically assembled using the Materials Project’s API and deliberately enriched with properties fundamental to microelectronics design — like formation energy and bandgap — allowing MatterChat to learn the complex patterns connecting a material’s atomic blueprint to its functional performance. To validate their model, the researchers benchmarked MatterChat against a suite of other AI systems, from general-purpose LLMs to other specialized scientific AI methods. The results show that MatterChat consistently outperformed its competitors across a range of tasks. The model was more accurate in classifying material types and demonstrated superior precision in predicting numerical properties. For example, it excelled at predicting a material’s bandgap, a property critical for designing new electronics from high-capacity energy storage to next-generation computer chips. “Our design is significantly more efficient because we don’t have to build a massive AI model from the ground up,” said co-author Zhi (Jackie) Yao, a research scientist in Berkeley Lab’s AMCR. “Instead, we take two powerful, pre-trained models — a structural encoder for materials physics and an open-source LLM — and use them off-the-shelf. The only component we actually train is the lightweight ‘bridge model’ that translates between them. It’s the difference between building an entire car factory and simply designing a smart adapter that connects a world-class engine to a world-class navigation system. This approach is not only computationally efficient, but also makes the system modular, so we can easily upgrade components or adapt the bridge for other scientific domains in the future.” Crucially, this modular design highlights exactly how institutions like Berkeley Lab and the Department of Energy are carving out a highly valuable niche in the booming AI landscape. Rather than competing with Silicon Valley tech giants to build ever-larger language models from scratch, the lab is focusing on the specialized connective tissue that makes commercial AI useful for hardcore science. Because the bridge model approach underlying MatterChat is forward-compatible, it is perfectly positioned to leverage these parallel tracks of innovation. As Mahoney pointed out, “We expect that industry will continue to develop improved LLMs, and we expect domain scientists and facilities will continue to generate new data. An important part of scientific machine learning is not simply to solve problems on today’s data, but instead to develop general methods that will be forward-compatible with orders of magnitude more data, whether from scientific domains or from LLMs.” According to Yao, the MatterChat project, which was initially developed and enhanced with funding from a Berkeley Lab Laboratory Directed Research & Development (LDRD) Program, will now expand its capabilities. In a collaboration with Fermilab, MatterChat is already contributing to a U.S. Department of Energy Genesis Mission project — called Accelerating eXtreme Environment Specs-to-Silicon (AXESS) — that aims to speed up the development of next-generation, high-speed, radiation-hardened detectors for challenging particle physics experiments by using advanced 3D integrated circuits (chiplets) and AI-driven data analysis. In addition to the LDRD support, the team also credits supercomputing resources at the National Energy Research Scientific Computing Center (NERSC), located at Berkeley Lab, with MatterChat’s success. “We are incredibly grateful to NERSC; this research simply would not have happened without access to the Perlmutter supercomputer through their AI for Science program,” said Tang. Wenbin Xu, a NERSC postdoctoral fellow at the time, was also a major co-author of the work, as was Benjamin Erichson, a research scientist in Berkeley Lab’s SDD, highlighting the benefits of AMCR-SDD collaboration on AI for science. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.
What’s Next for Artemis II AVATARs
Organ chips from Artemis II's AVATAR investigation have arrived at the laboratory at Emulate, Inc. in Boston, Massachusetts for analysis. The AVATAR (A Virtual Astronaut Tissue Analog Response) investigation uses personalized organ chips made from each astronaut's own cells to study the impacts of space radiation and microgravity on human health.
Wolves 1-1 Fulham
The so-called best players could not hack it in the Premier League so we will sell them and buy real quality to play in the Championship. If Mr Edwards can't design and motivate the team that will most likely form the nucleus of next season's offering, how do we think the results will be any different in the Championship? Fulham were stringing passes together when attacking but we struggled.