
Watch Twin Meteor Showers Reach Their Simultaneous Peak in Summer Skies
The latest observable meteor showers travel in tandem.
One, the Southern Delta Aquarids, has been active since July 18. The other, the Alpha Capricornids, got going on July 12. Both will reach their peak on Tuesday night into Wednesday morning, or July 29-30. Each shower peters out around Aug. 12.
The Southern Delta Aquarids, best seen in the Southern Hemisphere in the constellation Aquarius, while the Alpha Capricornids are visible from both hemispheres in Capricorn.
With the moon around 27 percent full, viewing opportunities could be favorable. But the Southern Delta Aquarids, sometimes spelled Aquariids, tend to be faint, and the Alpha Capricornids rarely create more than five meteors an hour.
A third meteor shower, the Perseids is also active. It is arguably the best sky show of the summer but doesn't achieve peak activity until Aug. 12-13.
To get a hint at when to watch, you can use a meter that relies on data from the Global Meteor Network showing when real-time fireball activity levels increase in the coming days.
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Forbes
26 minutes ago
- Forbes
Mastitis Costs The Dairy Industry $32 Billion A Year. Julia Somerdin Is Trying To Change That
J ulia Somerdin's test subjects line up for work before dawn, their tails swishing at flies as a robotic milking machine attaches to their udders to complete work once done by a farmer's hands. Somerdin has a particular interest in the robotic milking agents—and specifically, the ways in which this 21st century technology is still failing to solve a challenge to milk production as old as dairy farming itself: mastitis. The bacterial infection of the udder can spread through a herd, reducing milk supply and requiring milk be discarded. This not only causes pain for the animal but added expenses for farms. Somerdin is building a tool, via her agtech startup Labby, that can detect an infected cow from a rise in immune cells in her milk—often before the cow begins to show physical symptoms. Early detection is key on big, busy farms where farmers don't have the time to check on every cow, every day, Somerdin says. 'The really important thing is they give their time and resources to the cow who truly needs attention,' Somerdin tells Forbes . 'It's like a classroom; your teachers need to pay attention to the kids who need help, not to the kids who don't need help.' Each case of mastitis can cost as much as $500 in lower production and lost product per cow, and on any given month farmers will have two- to five percent of their cows suffering from the contagious infection. The condition affects 250 million cows each year, worldwide, costing the global dairy industry $32 billion. Somerdin, one of the listees on the 2025 Forbes 50 Over 50, is working to change these statistics, and she's doing so with Labby, the milk-testing startup she developed through MIT. Labby's system, MilKey (the dairy world loves a pun) uses a combination of advanced imaging technology and includes a device that looks like a handheld Game Boy to capture data from milk samples in real time. An AI-powered algorithm analyses the milk's composition for fat, protein and somatic cell count, which detects if the cow's immune system is responding to an infection. The data is then delivered to the farmer through a cell phone app, and the idea is to alert the farmer to an infection before a cow shows symptoms—and well before the current farming practice of batch testing milk after it's taken from a farm. 50 Over 50: 2025 Our fifth annual list of 200 women who are redefining what's possible in life's second half. VIEW THE FULL LISTST 'We all know in the past 20 years how big data has transformed human health,' Somerdin says. 'More and more we realize how animal health is connected to human health.' Somerdin has been clear on the need-case for her Rochester, New York-based company since she launched it in 2017. But the path from concept to market success has been neither fast nor smooth. In this way, she has much in common with the small dairy farmers struggling to keep their family enterprises going. 'I know exactly why I'm doing this: to make a real impact, to solve overlooked problems in agriculture, and to show what's possible when you don't give up — even when the odds say you should,' she says. Born in China and an electrical engineer by training, Somerdin spent the first half of her career building the business aspects of technology platforms that solve complex problems in telecommunications and defense. She earned an MBA at Northeastern University and in 2013 she started a graduate program in systems design and management at MIT. There she met cofounder Anshuman Das, a postdoc physicist with expertise in optics, imaging and materials science. Somerdin said she didn't know anything about dairy farming then—although she'd spent summers on her grandfather's farm in China—but wanted to pursue a mission-driven startup idea. Das and engineer Akshat Wahi were patenting a new mobile fluid testing technology that felt like a perfect fit for the $990 billion global dairy industry. From this, Labby was born. Out of the gate, Labby accumulated startup competition wins and modest investments from both in the U.S. and Europe. The company was selected for the Techstars Lisbon Accelerator program in 2020 and the Dairy Farmers of America innovation program. It's been awarded two non-dilutive U.S. Small Business Innovation Research grants totaling more than $1.25 million. But like farming, Labby was a lot of work without immediate returns; by 2022 Somerdin said the company used up its resources and had become a one-woman operation. 'Most startups fold under those conditions. But I didn't,' she says. Later that year, Labby won $250,000 in the Grow-NY competition and that opened the door to a prestigious hardware accelerator in Rochester. Somerdin relocated the company from Boston to Rochester to be closer to upstate dairy farmers. More grants followed and Labby now has a team of eight. Today, the company's business model is based on revenue streams from the hardware and a per cow/per day data collection and analysis subscription. Labby is prices its systems on a farm-by-farm basis depending on how milking parlors are set up and how many cows are to be monitored. 'It has that predictive capability, whether the problem is going to happen in a few hours or a few days. That can make a huge difference in economic return or resource allocation,' Somerdin explains, noting there is also industry-wide value in the collective data Labby eventually will amass. 'Why do I do this? Help the dairy, help the people, help the planet.' Julia Somerdin, Labby cofounder and CEO Labby has been testing and validating its system at the Cornell Agriculture Systems Testbed and Demonstration Site (CAST) for the Farm of the Future. CAST's director, Professor Julio Giordano, says that what makes Labby unique is it can be used in any milking parlor and integrate other data streams, such as environmental readings, farmers collect. There are other technologies that capture the same data as Labby's technology, he said, but much of that technology is specific to the milking parlor systems they're attached to. Labby's flexibility makes it unique. 'Data integration is one of the biggest challenges we are facing now,' Giordano says, referring to the wider dairy industry. 'There's so many diverse data streams on farms, from sensors to non-sensor systems, the challenge is putting them together in ways that can be truly useful.' In May, Labby's first commercial installation at the SmartHolstein Lab in Bowling Green, Kentucky, went live. Jeffrey Bewley, the executive director of genetics and innovation for Holstein Association USA and a partner in the SmartHolstein Lab, says that cows already are outfitted with a bovine version of a FitBit to monitor how much they are eating, ruminating and moving as markers of good health. But at more than 1,000 pounds each, cows can be clumsy and curious, nosing at wires and cameras installed in barns. Labby accounts for those challenges in its contactless design and housing, Bewley explains. 'There's no moving parts and no downside to measuring continuously,' he says. 'It can run as long as the milking parlor is running.' Bewley grew up on a dairy farm and went on to earn a PhD at Purdue University researching precision dairy farming technologies, so he's seen his fair share of dairy innovations. Labby's other value proposition, he says, is that it can essentially be 'always on,' accounting for the fact that at larger dairies, milking parlors can run as much as 22 hours a day. 'This allows us to have multiple eyes on the cows throughout the day and know when they are saying, 'Something is up with me,'' he says. 'It's about the health and well-being of the animal and everyone wants the animal to be well-cared for. This is a tool in the toolbox to do that.' As for Somerdin, she's focused on the bigger picture of how Labby might improve life at the dairy, not just in tending cows but for farmers who need more efficient systems to produce a high-quality product that keeps consumers satisfied and keeps farms financially viable while making supply chains more productive. 'When I started, a farmer in Massachusetts said, 'Julia, I don't need a toy,'' she said. 'Why do I do this? Help the dairy, help the people, help the planet.' More from Forbes Forbes 50 Over 50: Investment By Maggie McGrath Forbes 50 Over 50: Impact By Maggie McGrath Forbes 50 Over 50: Innovation By Maggie McGrath Forbes 50 Over 50: Lifestyle By Maggie McGrath Forbes 50 Over 50 Global: 2025 By Maggie McGrath Forbes Meet The Judges For The 2024 50 Over 50 List By Maggie McGrath Forbes The Age Of Disruption: Meet The 50 Over 50 2023 By Maggie McGrath


Medscape
an hour ago
- Medscape
Cirrhosis Mortality Prediction Boosted by Machine Learning
Among hospitalized patients with cirrhosis, a machine learning (ML) model enhanced mortality prediction compared with traditional methods and was consistent across country income levels in a large global study. 'This highly inclusive, representative, and globally derived model has been externally validated,' Jasmohan Bajaj, MD, professor of medicine at Virginia Commonwealth University in Richmond, Virginia, told Medscape Medical News . 'This gives us a crystal ball. It helps hospital teams, transplant centers, gastroenterology and intensive care unit services triage and prioritize patients more effectively.' The study supporting the model, which Bajaj said 'could be used at this stage,' was published online in Gastroenterology . The model is available for downloading at CLEARED Cohort Analyzed Wide variations across the world regarding available resources, outpatient services, reasons for admission, and etiologies of cirrhosis can influence patient outcomes, according to Bajaj and colleagues. Therefore, they sought to use ML approaches to improve prognostication for all countries. They analyzed admission-day data from the prospective Chronic Liver Disease Evolution And Registry for Events and Decompensation (CLEARED) consortium, which includes inpatients with cirrhosis enrolled from six continents. The analysis compared ML approaches with logistical regression to predict inpatient mortality. The researchers performed internal validation (75/25 split) and subdivision using World-Bank income status: low/low-middle (L-LMIC), upper middle (UMIC), and high (HIC). They determined that the ML model with the best area-under-the-curve (AUC) would be externally validated in a US-Veteran cirrhosis inpatient population. The CLEARED cohort included 7239 cirrhosis inpatients (mean age, 56 years; 64% men; median MELD-Na, 25) from 115 centers globally; 22.5% of centers belonged to LMICs, 41% to UMICs, and 34% to HICs. A total of 808 patients (11.1%) died in the hospital. Random-Forest analysis showed the best AUC (0.815) with high calibration. This was significantly better than parametric logistic regression (AUC, 0.774) and LASSO (AUC, 0.787) models. Random-Forest also was better than logistic regression regardless of country income-level: HIC (AUC,0.806), UMIC (AUC, 0.867), and L-LMICs (AUC, 0.768). Of the top 15 important variables selected from Random-Forest, admission for acute kidney injury, hepatic encephalopathy, high MELD-Na/white blood count, and not being in high income country were variables most predictive of mortality. In contrast, higher albumin, hemoglobin, diuretic use on admission, viral etiology, and being in a high-income country were most protective. The Random-Forest model was validated in 28,670 veterans (mean age, 67 years; 96% men; median MELD-Na,15), with an inpatient mortality of 4% (1158 patients). The final Random-Forest model, using 48 of the 67 original covariates, attained a strong AUC of 0.859. A refit version using only the top 15 variables achieved a comparable AUC of 0.851. Clinical Relevance 'Cirrhosis and resultant organ failures remain a dynamic and multidisciplinary problem,' Bajaj noted. 'Machine learning techniques are one part of multi-faceted management strategy that is required in this population.' If patients fall into the high-risk category, he said, 'careful consultation with patients, families, and clinical teams is needed before providing information, including where this model was derived from. The results of these discussions could be instructive regarding decisions for transfer, more aggressive monitoring/ICU transfer, palliative care or transplant assessments.' Meena B. Bansal, MD, system chief, Division of Liver Diseases, Mount Sinai Health System in New York City, called the tool 'very promising.' However, she told Medscape Medical News , 'it was validated on a VA [Veterans Affairs] cohort, which is a bit different than the cohort of patients seen at Mount Sinai. Therefore, validation in more academic tertiary care medical centers with high volume liver transplant would be helpful.' Furthermore, said Bansal, who was not involved in the study, 'they excluded those that receiving a liver transplant, and while only a small number, this is an important limitation.' Nevertheless, she added, 'Artificial intelligence has great potential in predictive risk models and will likely be a tool that assists for risk stratification, clinical management, and hopefully improved clinical outcomes.' This study was partly supported by a VA Merit review to Bajaj and the National Center for Advancing Translational Sciences, National Institutes of Health. No conflicts of interest were reported by any author.

Yahoo
9 hours ago
- Yahoo
Will the sturgeon moon blot out the Perseids? What to know about August's full moon
If you're hoping to catch the Perseid meteor shower as it streaks through the sky this summer, you'll have to plan your viewing around the sturgeon moon, which also is lighting up the sky in mid-August. While the next full moon will reach peak intensity on Aug. 9, the Perseids will offer their light show for several weeks. Viewing may be best this week while the moon is still beginning to wax toward fullness. Here's what to know about the sturgeon moon in August and how it could impact Perseid viewing. When will August's full moon peak? The sturgeon moon will peak in the early morning hours at 3:55 a.m. Aug. 9, 2025. The moon will appear full the night before, so astronomy buffs can look up into the evening sky Aug. 8 to spot the full moon. Full moon could disrupt peak Perseids viewing The Perseids, the year's best meteor shower, is set to peak overnight Aug. 12, three days after the full moon. The full moon will still appear bright, hindering observations of meteors, Robert Lunsford, the American Meteor Society's newsletter editor and fireball report coordinator, told USA TODAY. Lunsford recommended better viewing chances starting during the new moon, which took place July 24, because the skies will be darker overnight. One of the best days to watch for meteors will be July 30, because two other meteor showers, alpha Capricornids and Southern delta Aquariids, will be taking place at the same time, according to Lunsford. How far away from the Earth is the moon? The average distance between the Earth and the moon is 238,855 miles. At its farthest from the Earth, the moon is about 252,088 miles away and astronomers say it's at apogee. When the moon is at perigee, it's 225,623 miles away. How did the sturgeon moon get its name? The name sturgeon moon comes from the lake sturgeon, native to the Great Lakes and traditionally a key food source for Indigenous tribes during this summer season, according to the Old Farmer's Almanac. Michigan is home to lake sturgeon, one of the oldest species on the Great Lakes, though human efforts to eradicate the fish led to a steep decline since the 19th and 20th centuries. Statewide efforts are now working to increase the population with support from state, tribal and federal institutions. Michigan features an annual sturgeon fishing season on Black Lake in Cheboygan and Presque Isle counties, with the February 2025 season taking just 17 minutes to fill the statewide limit. What phase of the lunar cycle is the moon in now? The moon is currently in its waxing crescent phase, at 16% illumination, according to The moon's phases in August 2025 are: First Quarter: Aug. 1 Full Moon: Aug. 9 Last Quarter: Aug. 16 New Moon: Aug. 23 Is the sturgeon moon a supermoon. No, the sturgeon moon is not a supermoon. What are the full moon names in 2025? Here are all the full moons of 2025: Wolf Moon: January Snow Moon: February Worm Moon: March Pink Moon: April Flower Moon: May Strawberry Moon: June Buck Moon: July Sturgeon Moon: August Corn Moon: September Harvest Moon: October Beaver Moon: November Cold Moon: December When will the corn moon peak? The corn moon will peak Sept. 7, 2025. The full moon will feature a total lunar eclipse, though it won't be visible in Michigan, per The Detroit Free Press and USA TODAY contributed. Contact Jenna Prestininzi: jprestininzi@ This article originally appeared on Detroit Free Press: Sturgeon moon, Perseids to light up Michigan skies in August. Dates, times, viewing locations Solve the daily Crossword