Meta, who owns and operates FaceBook and Instagram, has enabled a setting automatically that allows anyone to use your public Instagram photos, profile picture, and/or reels for AI purposes. This includes everything from your posts, stories, stickers, reels, and even your profile photo. Some users may not like this, whether they’re opposed to AI in ... Read More
Após três meses em fase de testes, o recurso de nome de usuário do WhatsApp finalmente parece estar funcionando entre os usuários que já haviam reservado seu username, ampliando a disponibilidade da funcionalidade.
Aos que efetuaram a reserva, o WhatsApp começou a exibir um banner no topo da lista de conversas, informando que ele já está ativo e explicando que agora ele pode ser compartilhado com outras pessoas. Caso você queira verificar o nome de usuário de algum dos seus contatos, basta abrir a conversa com ele para conferi-lo.
De acordo com o WABetaInfo, o recurso está sendo liberado de forma gradual para quem já reservou um nome de usuário. Se esse for o seu caso, basta tocar no botão de adicionar (na aba Conversas) para abrir a lista de contatos, e em seguida, digitar o nome de usuário na barra de pesquisa.
Vale lembrar que isso não afetará a visualização dos números de telefone nos contatos com os quais você já iniciou uma conversa anteriormente. Nos moldes de rivais como o Telegram, os nomes de usuário apenas introduzem uma nova opção de acionar um determinado contato, alterando a primeira interação dos usuários, já que o número de telefone deixa de ser a única forma de iniciar uma conversa.
O WhatsApp está liberando o recurso completo de nomes de usuário para “uma fração muito limitada da sua base instalada no iOS e Android”, incluindo tanto versões betas quanto estáveis do aplicativo.
NASA Pushes New Wing Design to Find Structural Limits
The 15-foot Structural Wing Experiment Evaluating Truss-bracing test article is fully installed in the Flight Loads Laboratory at NASA’s Armstrong Flight Research Center in Edwards, California, on Wednesday, May 20, 2026. The model is part of NASA’s research to develop technologies for future ultra-efficient aircraft.
Credits: NASA/Carla Escamilla
NASA researchers recently put a new wing design, appearing long and thin with a lightweight structural design, through a series of grueling tests to find its structural limits. What they found left them encouraged about the wing’s potential, even when they pushed it past its intended limits.
The 15-foot Structural Wing Experiment Evaluating Truss-bracing (SWEET-15) test article is part of NASA’s research to develop future ultra-efficient aircraft. The design incorporates a long wing supported by an aerodynamic strut, based on NASA’s earlier Transonic Truss‑Braced Wing concept.
The research team is working to understand whether SWEET-15’s design and its new lightweight structural designs could help commercial airliners save fuel. But first, they need to understand how it behaves under the kinds of force wings experience in flight.
Lab technicians Phil Tofts, Chris McLain, and Jeff Howell and NASA engineers Erin Anderson and Richard Larson prepare the 15-foot Structural Wing Experiment Evaluating Truss-bracing model in the Flight Loads Laboratory at NASA’s Armstrong Flight Research Center in Edwards, California, on Thursday, Dec. 11, 2025. The model is part of NASA’s research to develop technologies for future ultra-efficient aircraft.
NASA/Christopher LC Clark
The SWEET-15 design originated with combining five different advanced composite manufacturing and assembly technologies that enabled the novel structural design. The 15-foot-long test article was then designed and fabricated at NASA’s Langley Research Center in Hampton, Virginia, before traveling to NASA’s Armstrong Flight Research Center in Edwards, California, for testing.
Over several months, NASA engineers intentionally bent the test wing in the Flight Loads Laboratory at NASA Armstrong. Numerous strain and load sensors, including fiber-optic strain sensors, were placed throughout the structure to track how the wing responded as forces increased.
The data from the sensors confirmed the predictions made by NASA’s computer models. According to initial findings, the wing withstood the anticipated in-flight forces without issue. The results provided the team with confidence in the new manufacturing approaches and methods for connecting wing parts used in SWEET-15, which could support future efficient aircraft designs. The manufacturing approach, developed at NASA Langley used the Integrated Structural Assembly of Advanced Composites robot, aims to produce lighter and stronger composite structures for aerospace vehicles.
Lab technicians Jeff Howell, left and Chris Mount install the 15-foot Structural Wing Experiment Evaluating Truss-bracing model in the Flight Loads Lab at NASA’s Armstrong Flight Research Center in Edwards, California, Wednesday, February 11, 2026. The model is part of NASA’s research to develop technologies for future ultra-efficient aircraft.
NASA/Christopher LC Clark
The test concluded with a deliberate test-to-failure, where engineers increased loads beyond the wing’s design limits to determine how and where it would fail. The structure ultimately failed at roughly 127% of its design limit load, with visible damage appearing near the back edge of the wing and in the upper wing cover. This element of testing provided valuable insight into how the joints connecting the wing to its main strut and a secondary one, called a jury strut, behave under forces beyond the expected flight envelope.
This marks the first time a representative composite truss-braced wing configuration has undergone this type of structural evaluation. It was made possible only through NASA collaboration across centers and projects, with researchers utilizing agency resources such as the Fiber Optic Sensing System developed to gather data on both aircraft and spacecraft.
NASA research engineer Walter Hargis regulates the 15-foot Structural Wing Experiment Evaluating Truss-bracing model in the Flight Loads Laboratory at NASA’s Armstrong Flight Research Center in Edwards, California, on Tuesday, March 31, 2026. The model is part of NASA’s research to develop technologies for future ultra-efficient aircraft.
NASA/Ryan Kline
To prepare for the testing, engineers at NASA Langley designed, analyzed, and manufactured the wing and completed safety preparations and lab setup.
Researchers will now analyze the data collected during testing to inform future airframe designs and support NASA’s ongoing efforts to develop more efficient aviation technologies.
The work is being conducted through NASA’s Subsonic Flight Demonstrator project in the agency’s Research Technology Mission Directorate. The successful testing of multiple innovative components marks a milestone in NASA’s aeronautics research.
A nova ferramenta Muse Image, da Meta, vem ativada por defeito em todos os perfis públicos de adultos no Instagram, e qualquer pessoa pode usar as suas fotos para gerar imagens com inteligência artificial sem que seja avisado. Eis como travar isto em menos de um minuto.
Reset PRAM on Mac is one of those troubleshooting steps that has survived decades of Apple hardware, old support forums and emergency calls to the family member who “knows computers.” The name sounds far more technical than the procedure, which involves restarting an Intel-based Mac while holding four keys.
The reset can help when a Mac remembers the wrong basic settings. It may select an unexpected startup disk, return to an incorrect display resolution, use an unusual sound level or keep other hardware-related preferences that refuse to behave normally.
It is not a speed boost, a deep system repair or a magical cure for every Mac problem. Resetting PRAM will not clear storage, repair a damaged app or make an aging MacBook suddenly feel new. It is a focused fix for a small collection of settings stored outside the usual macOS preferences.
There is also one major limitation: the familiar keyboard shortcut applies only to Intel-based Macs. Apple silicon models handle this memory differently and do not require the same manual reset.
What PRAM Actually Is
PRAM stands for Parameter Random-Access Memory. It was the small amount of memory older Macs used to preserve certain settings while the computer was turned off.
Apple later moved to NVRAM, or nonvolatile random-access memory, but the two names remain closely connected in Mac troubleshooting. Users still search for PRAM reset, while Apple’s current documentation usually calls the procedure an NVRAM or PRAM reset.
The stored information can include the selected startup disk, speaker volume, screen resolution and other low-level settings. When that information becomes incorrect or behaves unpredictably, resetting it allows the Mac to rebuild the relevant preferences.
Nothing dramatic happens to personal data. Documents, photos, apps, emails and user accounts remain untouched. Some settings may return to their defaults, which is the point of the reset.
Reset PRAM on Mac Only When the Symptoms Fit
Reset PRAM on Mac when the problem appears connected to startup or hardware preferences rather than normal app use.
A Mac that repeatedly chooses the wrong startup disk is a good candidate. So is an Intel Mac that starts with an unexpected sound level or returns to a strange display resolution after every restart.
The procedure may also help when the date, time zone or other basic startup settings act strangely, although modern macOS versions usually manage those automatically.
It is less useful when Safari is slow, an app keeps crashing or the Mac is nearly out of storage. Those problems have different causes. Closing apps, installing updates or freeing storage will usually do more than resetting a small bank of startup memory.
The distinction keeps the old troubleshooting step useful without turning it into Mac folklore prescribed for every symptom.
Check Which Mac You Own
Before using the shortcut, confirm whether the Mac has an Intel processor or Apple silicon.
To check:
Apple menu > About This Mac
Look for a line labeled Chip or Processor. An M-series chip identifies Apple silicon. A processor name containing Intel means the traditional reset applies.
This check prevents a common misunderstanding. Holding Option, Command, P and R during startup on an Apple silicon Mac does not perform the old PRAM reset. The shortcut belongs to Intel startup behavior. Apple’s current startup-key guide lists it specifically among key combinations for Intel-based Macs.
Apple silicon Macs check and manage stored startup information through their newer boot system. A normal shutdown and restart is usually the first step when one develops unusual basic behavior.
Image Credit: AppleMagazine
How to Reset PRAM on an Intel Mac
The useful guidance is brief:
Shut down the Mac completely.
Press the power button, then immediately hold:
Option + Command + P + R
Keep the four keys pressed for approximately 20 seconds, then release them and allow the Mac to start normally.
Older Macs may play the startup sound more than once. On some newer Intel models, the Apple logo may appear and disappear during the process.
The timing is the only slightly awkward part. The keys need to be pressed immediately after the Mac begins starting. Waiting until the login window appears is too late.
After the Mac starts, check the setting that caused the problem. The startup disk, volume or display configuration may need to be selected again because the reset cleared the previous preference.
What Changes After the Reset
Most users will notice nothing beyond the original problem hopefully disappearing. The Mac does not present a dramatic confirmation screen or announce that PRAM has been purified.
Instead, a few stored settings may return to their defaults. The speaker volume may change. The preferred startup disk may need to be chosen again. A display may return to its standard resolution. Time-zone information may need a moment to update.
That understated behavior is normal. A successful reset is less like reinstalling macOS and more like asking the Mac to forget a handful of stubborn instructions.
Apple also uses an NVRAM reset as one of the preparation steps for certain Intel Macs before they are sold or transferred, since the procedure clears stored user settings from memory.
Image Credit: Apple Inc.
Why Apple Silicon Macs Do Not Need the Shortcut
Apple silicon changed the Mac startup process along with performance, power efficiency and system security. The older Intel keyboard combination no longer controls the same reset behavior.
For an M-series Mac showing unusual startup settings, begin with a full shutdown rather than repeatedly trying the old shortcut.
Use:
Apple menu > Shut Down
Wait briefly after the screen turns completely black, then turn the Mac back on.
If the problem involves selecting a startup disk or reaching recovery tools, hold the power button while the Mac starts until startup options appear. Apple documents this power-button process as the route into startup options on Apple silicon models. (Apple Support)
That is usually enough guidance for a light troubleshooting article. Recovery, diagnostics and deeper repair steps belong to more serious startup problems, not every incorrect volume level or display setting.
When the Reset Does Nothing
A PRAM reset can fail to change anything because the problem was never stored in PRAM or NVRAM.
A slow Mac may be running too many apps. A browser may have dozens of heavy tabs. A startup disk may be almost full. A damaged cable may cause display problems. A weak battery may cause shutdowns. A broken speaker will not repair itself because four keys were held during startup.
If the symptom continues, return to the problem itself rather than repeating the reset indefinitely.
Check the related setting in System Settings. Install macOS updates. Restart the affected app. Disconnect unnecessary accessories. Confirm that enough storage is available. Persistent hardware behavior may require Apple Diagnostics or professional support.
The reset should be treated as one useful step, not an annual Mac ritual.
Image Credit: AppleMagazine
An Old Mac Fix With a Narrow Purpose
Reset PRAM on Mac remains relevant because Intel models are still in use across homes, schools and businesses. Many continue to work well, and their owners may eventually encounter the sort of odd startup preference that this procedure was designed to clear.
The method is simple, safe for personal files and quick enough to try when the symptoms fit. Its usefulness comes from being specific.
An Intel Mac remembering the wrong startup disk or display setting may benefit. A Mac with an unrelated software or hardware problem will need another answer.
The four-key shortcut has survived because it occasionally solves a strange problem in about 20 seconds. That is a good troubleshooting tool. It just should not be asked to perform miracles.
Siri Wolfram helped define the original promise of Apple’s voice assistant. When Siri debuted on the iPhone 4S in 2011, it could answer factual and computational questions without sending users through a list of search results. Ask about a mathematical calculation, scientific quantity, historical statistic or unit conversion, and Wolfram Alpha could provide a structured answer.
That partnership gave early Siri something many modern AI assistants still struggle to guarantee: a source designed to compute answers rather than produce plausible sentences. Wolfram Alpha was not a chatbot. It was a computational knowledge engine built around curated data, symbolic mathematics and algorithms.
Siri AI enters a far more ambitious era. Apple now wants its assistant to hold natural conversations, understand personal context, interpret images, find information across apps and complete actions. Yet the old Siri Wolfram relationship remains useful for understanding what Apple gained, what was lost as assistants became more conversational and why verified computation may become even more valuable in the generative AI age.
Siri Wolfram Was Built Around Answers
The original Siri Wolfram integration reflected a straightforward idea: users wanted direct answers without manually searching, opening websites and comparing sources.
Wolfram Alpha was particularly effective for questions with a computable result. It could solve equations, compare financial data, convert measurements, retrieve astronomical information, calculate dates and present structured scientific facts. Siri provided the voice interface, while Wolfram supplied the knowledge engine behind selected responses.
A user could ask how many days remained until a date, calculate a percentage, compare populations or request information about a mathematical concept. Siri translated the spoken request and delivered the result in a format suitable for the iPhone.
The experience was narrow compared with modern generative AI, but it had a valuable discipline. Wolfram Alpha attempted to determine an answer from structured information. It did not need to improvise an explanation every time.
That made Siri Wolfram especially useful for mathematics, science, education and quick factual calculations. The assistant could sound intelligent because it was connected to a system built to compute.
Image Source: Google
What Siri Wolfram Alpha Could Do Well
Siri Wolfram Alpha worked best when the request had a definable structure. Arithmetic, percentages, conversions, equations and statistics were natural categories. The system could also retrieve information about weather history, geography, nutrition, astronomy, transportation and other data-rich subjects.
The integration helped make Siri feel different from ordinary web search. Instead of showing several links, the assistant could present one answer with supporting figures or charts.
That approach had limitations. Wolfram Alpha could only respond effectively when it understood the request and had the relevant data or computational method. It was not designed for open-ended conversation, personal writing, emotional nuance or the countless informal questions users ask assistants.
Siri also relied on several external services, with Wolfram Alpha handling only certain knowledge categories. The experience could therefore feel inconsistent. One request produced a polished computational response, while another returned a web search or a limited canned answer.
Still, the partnership demonstrated a principle Apple has never fully abandoned: the best assistant does not need to create every answer itself. It needs to route each request to the system most qualified to handle it.
Generative AI Changed the Definition of an Assistant
Modern AI assistants are expected to do far more than retrieve facts. Users want them to explain ideas, write messages, summarize documents, analyze images, brainstorm projects and remember the direction of a conversation.
Siri AI is Apple’s response to that expanded expectation. Powered by Apple Intelligence and Apple Foundation Models, the new assistant can handle open-ended requests and continue natural conversations. It can use personal context from supported apps, understand onscreen content and connect requests with app actions.
This is a dramatic expansion from the Siri Wolfram era. The old model was largely transactional: ask a question, receive an answer. Siri AI is intended to interpret intent, understand relationships between information and help complete a larger task.
A user may ask Siri AI to find a restaurant recommendation buried in Messages, locate a hotel confirmation in Mail and add the details to a travel note. That request involves personal context and several system services rather than one public factual answer.
The assistant becomes less like a talking search box and more like an operating-system layer.
Image Credit: Apple Inc.
Conversation Creates a Reliability Problem
Generative AI makes assistants more flexible, but it also introduces uncertainty. A language model can produce an elegant response even when the underlying information is incomplete or wrong. The same fluency that makes the assistant enjoyable can make an inaccurate answer sound convincing.
The old Siri Wolfram model avoided much of that risk within its strongest categories. A mathematical calculation came from a computational engine. A unit conversion followed a defined relationship. A data query could be tied to structured information.
Siri AI needs both capabilities. It needs conversational intelligence for requests that cannot be reduced to a formula, while retaining access to reliable tools for tasks that demand precision.
Apple can use specialized systems for calculations, calendars, maps, weather, app actions and personal information rather than asking one generative model to invent every result. Foundation models can understand the request, then direct the work to an appropriate source.
That structure would preserve the strongest lesson from Siri Wolfram: intelligence also means knowing when not to guess.
Personal Context Is the New Knowledge Engine
Wolfram Alpha gave Siri access to public computational knowledge. Siri AI adds a second knowledge source: the user’s own information.
Apple says Siri AI can understand personal context across messages, emails, photos, notes and other supported content. It can help retrieve a detail without requiring the user to remember which app contains it.
This changes the assistant’s value. Wolfram Alpha could explain the distance between two cities. Siri AI could find the hotel reservation, identify the arrival time and retrieve the message where a friend recommended a nearby restaurant.
That personal layer also requires stricter privacy. Apple uses on-device processing for many requests and Private Cloud Compute when more processing power is required. The company has designed the system so personal data does not become part of an ordinary cloud AI profile.
Siri Wolfram answered questions about the world. Siri AI is being designed to answer questions about the user’s place within it.
Image Credit: Apple Inc.
Apps Complete the Transition
Siri AI also moves beyond knowledge by connecting directly with apps through App Intents. Developers can expose content and actions so the assistant can help users complete tasks instead of only describing how to do them.
That could include editing a photo, retrieving a document, starting a workout, updating a task or sending information through a supported app. Onscreen awareness adds another route, allowing users to ask about content already visible without explaining every detail again.
Wolfram Alpha remains valuable because some questions require specialized computation. App Intents extend the same routing philosophy into actions. Siri does not need to contain every capability internally. It needs to understand the request and connect it with the correct tool.
This may become the defining structure of Siri AI: one conversational interface backed by models, apps, services, personal context and specialized knowledge engines.
The Old Siri Still Has a Lesson for the New One
Siri Wolfram belonged to a more limited assistant era, but its underlying approach was disciplined. The system used a specialized source for questions that demanded structured knowledge and computation.
Siri AI has a wider assignment. It must converse naturally, interpret images, understand personal information and complete actions across Apple devices. That breadth can make Siri far more useful, but only if Apple preserves dependable pathways for calculations and factual tasks.
The future assistant should not choose between Wolfram-style precision and generative flexibility. It should combine them. A conversational model can understand what the user wants. A computational engine can provide the numerical answer. Personal context can supply relevant details. App Intents can complete the task.
The old Siri Wolfram integration showed that a voice assistant could make expert knowledge accessible through one spoken request. Siri AI now aims to place conversation, personal context and action around that foundation.
The assistant has become larger, more personal and more capable. Its credibility will still depend on something the 2011 version understood well: when a question has a correct answer, intelligence should calculate before it speaks
Spin Signatures in Horizon-Resolved Images of LLAGN
Speaker
Dr. Daniel Palumbo, Harvard University
Abstract
With the advent of the Event Horizon Telescope (EHT), near-horizon black hole imaging with sub-mm very-long-baseline interferometry (VLBI) is now routine for the two sources for which terrestrial VLBI is sufficient to resolve the black hole shadow: Messier 87* and Sagittarius A*. Since the first images of M87*, the theoretical analysis of these images has advanced a broad class of black hole spin tracers in horizon-resolving observations, all of which have complex interplay with the astrophysical conditions near the horizon. Meanwhile, space VLBI mission concepts such as the Black Hole Explorer aim to drastically improve the angular resolution available via sub-mm VLBI, resolving out the primary accretion disk image to isolate the strongly lensed “photon ring,” which more robustly exposes black hole mass, spin, and viewing inclination to distant observers. In this talk, I will detail the spin signatures in both of these angular resolution regimes, and how they work together to build a “robustness ladder” for spin measurement with which the spins of many more low-luminosity AGN will soon become accessible as sub-mm VLBI sensitivity, frequency coverage, angular resolution improves. The resulting local “spin census” will help fill in missing pieces of the history of accretion and merging in the broader AGN population.
Coupling Driven H2 Excitation in Seyferts: GATOS JWST/MRS
Speaker
Daniel Delaney, University of Alaska
Abstract
We utilize James Webb Space Telescope/Mid Infrared Instrument (JWST/MIRI) Integral Field Unit observations from the Galaxy Activity, Torus and Outflow Survey to investigate the diverse range of ionized outflow rates of obscured active galactic nuclei (AGN) with similar bolometric luminosity and explore potential associations with AGN feedback. We explore spatial correlations between ionized emission potentially associated with fast shocks ([Fe II]5.34μm) and the excitation of H2. We further constrain our investigation to the inner 400 pc (the nuclear and circumnuclear regions r < 200 pc), and estimate the excitation temperature and column density of H2 assuming local thermodynamic equilibrium and using the S(1)–S(8) rotational H2 emission lines visible to JWST/MIRI spectroscopy. We report the molecular gas temperature of the deprojected 400 pc nuclear region to correlate with the ionized mass outflow rate. We also observe a stronger degree of spatial correlation between [Fe II]5.34μm emission and H2 gas temperature. We observe regions of enhanced [Fe II]5.34μm/[Ar II]6.99μm spatially coincident with the ionization cones of objects with higher ionized outflow rates and [Fe II]5.34μm/[Ar II]6.99μm in the deprojected 400 pc nuclear region to scale positively with both the ionized outflow rate and the estimated molecular gas temperature. We do not observe the estimated jet cavity power within the central 400 pc as strongly correlated with the ionized mass outflow rate or molecular gas temperature of the nuclear region. We take the preceding observations to suggest a higher degree of interaction between AGN outflows and the circumnuclear disk.
Seminar Connection
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From Micro to Macro: Connecting the Physics of Galaxy Formation Across Scales
Speaker
Drummond Fielding, New York University
Abstract
Galaxy formation is controlled by the cycling of diffuse gas through the ISM, CGM, and larger-scale environment, but predictive models remain limited by unresolved microphysics. I will discuss how sub-pc processes—including cosmic-ray transport, magnetic reconnection, and turbulent mixing—regulate multiphase structure, energy and momentum transport, and the launching of galactic winds. I will then describe how simulations, analytic models, and new multi-scale numerical methods can connect these processes to kpc-scale feedback and Mpc-scale galaxy evolution. The aim is to build physically grounded models of gas cycling that can sharpen our interpretation of observations and move galaxy formation theory beyond phenomenological feedback prescriptions.
How NASA’s Artemis III Lander Test Will Pave Way for Moon Landings
Before Artemis astronauts land on the Moon’s surface in 2028, NASA will conduct the Artemis III demonstration mission in 2027, allowing teams on Earth and in orbit to practice rendezvous and docking operations between commercial human landing systems and the Orion spacecraft. Data from that mission, along with future uncrewed demonstration missions at the Moon, will support astronaut safety and mission success for crewed lunar landings.
NASA is working with two American companies to develop the human landing systems that will safely transport astronauts from lunar orbit to the Moon’s surface and back for future Artemis missions. For Artemis III, both SpaceX and Blue Origin will fly test versions, or test articles, of the crewed landers that will be used for future Moon landings. The lander test articles will launch by commercial rockets, while the Artemis III crew will launch to low Earth orbit in Orion atop the agency’s SLS (Space Launch System) rocket.
Stage setting for crewed flights
NASA and the human landing system providers have been working closely together to plan and determine capabilities for the Artemis III mission. With missions fast approaching, both SpaceX and Blue Origin are optimizing hardware availability and capability. SpaceX plans to use the company’s latest version of Starship and basis of the future Starship HLS, called Version 3, while Blue Origin will test their planned HLS crew cabin, allowing each company to apply lessons learned prior to uncrewed and crewed missions on the Moon.
“Each human landing system provider has taken a different approach to the Artemis III mission,” said Steve Creech, program manager, Human Landing System Program, NASA’s Marshall Space Flight Center in Huntsville, Alabama. “Ultimately, SpaceX and Blue Origin have put forward a list of aggressive objectives and goals intended to complement upcoming uncrewed demonstration missions at the Moon so that we can gain both understanding and confidence in the spacecraft and launch vehicles prior to a crewed landing. The lander prototype designs will inform future development efforts and will continue to mature over the next year.”
For the Artemis III mission, the Blue Moon test lander will be based on Blue Origin’s current architecture for its Mark 2 crew lander, incorporating all the major avionics and flight software and control systems to ensure flight operations from this demonstration mission can directly translate to crewed lunar flights. Up to two crew members, donning orange Orion crew survival system suits, will open the hatch to enter the Blue Origin test lander. The production hardware must incorporate many of the same systems and subsystems, including an Environmental Control and Life Support System (ECLSS), a crew cabin, and avionics.
These artist’s concepts depict Blue Origin’s Blue Moon Mark 2 human landing system test article in Earth orbit and docked with NASA’s Orion spacecraft as part of NASA’s upcoming Artemis III demonstration mission in low Earth orbit.
Blue Origin
These artist’s concepts depict Blue Origin’s Blue Moon Mark 2 human landing system test article in Earth orbit and docked with NASA’s Orion spacecraft as part of NASA’s upcoming Artemis III demonstration mission in low Earth orbit.
Blue Origin
The Blue Origin lander also will fly with an instrumented lunar surface spacesuit mass simulator. Like the suited “Moonikin” manikin that flew aboard Orion during the uncrewed Artemis I test flight, the low-fidelity spacesuit mass simulator will provide real-time feedback about the environment within the Blue Moon crew cabin.
SpaceX’s Starship lander test article will use a Starship Version 3, currently in production and testing, with an added docking system installed on the nose of the 171-foot (52-m) spacecraft, enabling NASA and SpaceX to evaluate how the entire integrated stack of Orion and the Starship test lander interact. NASA and SpaceX are identifying controllability and communications tests for the Artemis III mission. Astronauts will not enter the Starship test lander during Artemis III.
These artist’s concepts depict NASA’s Orion spacecraft and SpaceX’s Starship human landing system test article during docking operations as part of NASA’s upcoming Artemis III demonstration mission in low Earth orbit.
SpaceX
These artist’s concepts depict NASA’s Orion spacecraft and SpaceX’s Starship human landing system test article during docking operations as part of NASA’s upcoming Artemis III demonstration mission in low Earth orbit.
SpaceX
Launch cadence
NASA, SpaceX, and Blue Origin will launch three of the world’s most powerful rockets within a short timeframe of one another, exercising ground processing, launch crews, and facilities as well as control centers, networking, and data exchange at key sites across the country during two separate, back-to-back rendezvous and docking maneuvers between Orion and the lander test articles, before a safe splashdown of the Artemis III crew in Orion.
“Artemis III will be a highly choreographed dance with a demanding launch sequence across multiple launch pads and equally demanding mission operations for our ground and flight crews, making it one of the most complex and ambitious missions NASA has ever undertaken,” said Jeremy Parsons, Artemis program manager. “The demonstration mission will set the stage before our next giant leap. NASA’s expertise in systems engineering and integration, as well as launch and mission operations in low Earth orbit, will bring the mission together.”
For future crewed missions to the Moon, NASA and one of the commercial lander partners will execute a “dual launch campaign,” prepositioning the lander in orbit to await a crewed Orion, launched on SLS. Launching the three rockets in succession of one another for Artemis III offers a unique opportunity to practice launch processing and operations.
Blue Origin’s lander test article is planned to launch first and will be able to loiter in space for up to 30 days, allowing for checkouts in orbit prior to the launch of SLS and Orion from Launch Complex 39B at NASA’s Kennedy Space Center in Florida. The Blue Origin test article will launch at a set trajectory to meet a designated “parking” orbit for these systems checks.
Artemis III will be a highly choreographed dance with a demanding launch sequence across multiple launch pads and equally demanding mission operations for our ground and flight crews, making it one of the most complex and ambitious missions NASA has ever undertaken.
Jeremy Parsons
Artemis program manager
Following the completion of Blue Origin’s rendezvous and docking operations testing and the Artemis III crewed launch on SLS, SpaceX will launch its Starship lander test article to rendezvous with Orion and its crew for its phase of on-orbit testing.
Throughout the Artemis III mission, Orion will fly in a circular orbit. All three rockets will have more launch opportunities than are available for a lunar mission and will be able to reach the designated mission altitude in a single launch.
Docking operations
During docking and undocking operations, Orion and the Artemis III crew will use the lander test articles as the targets, while Orion will operate as the chaser spacecraft. This is the same configuration planned for future crew landing mission to the Moon.
NASA will ensure both test landers are mission ready and crew safe prior to Artemis III. These verifications will be based on functional and performance requirements for the test lander designs and hazard controls for hardware and software, ensuring the Artemis III astronauts inside Orion are safe throughout both docking phases of the mission.
SpaceX and Blue Origin have already tested their docking capabilities for their respective landers on the ground. SpaceX’s docking capability was qualified in 2023; Blue Origin conducted development ground testing on its pressurized docking system earlier this year.
A key difference between the docking capabilities of both lander test articles will be the location of docking. Orion will dock along the side of the Blue Moon test lander, adjacent to the crew cabin. Later, Orion will dock nose-to-nose with the giant SpaceX test lander.
Software testing between spacecrafts will help demonstrate that the commercial human landing system prototypes and Orion can meet at a precise time and location in space. When Orion docks with the Blue Moon test lander, the Orion spacecraft’s software will control the docked spacecraft. Meanwhile, the SpaceX test article will control the docked spacecraft for the second portion of the mission. During the docking phases, teams with NASA and the commercial partners will be able to test hardware and software interoperability, as well as dynamics of how the integrated lander-Orion spacecraft moves in space.
Through the Artemis program, NASA will send astronauts to explore the Moon for scientific discovery, economic benefits, and to build the foundation for the first crewed missions to Mars – for the benefit of all.
All the young people the Guardian spoke to disagreed with aspects of the government’s proposed block
Sixteen- and 17-year-olds in Britain are to be encouraged to observe a midnight to 6am social media curfew but will be able to opt out by changing their account settings.
From next spring, they will be urged to refrain from using certain apps, with the block being switched on by default. But the curfew will not be mandatory and can be overridden.
Using the Yebes 40-m and IRAM 30-m radio telescopes, astronomers have discovered erythrulose, a four-carbon sugar commonly found in raspberries and sunless tanning cosmetics, in the molecular cloud G+0.693-0.027.
The feature was part of the new AI image generator, Muse Image, and allowed AI-generated images to be created using content from public Instagram accounts. By specifying a public account with an @mention, users could let the AI model use the person’s images as a reference without informing the account holder.
The launch quickly prompted concerns about privacy and the risk of abuse, with critics saying the feature could be used to create manipulated or offensive images based on other people’s public content.
Meta said its the goal was to give users a creative tool where they could decide for themselves whether their public content could be used. But it removed the feature after feedback that the feature did not meet expectations.
Wally Funk, who in 2021 became the oldest woman to fly into space—60 years after she and 12 other women sought the same opportunity as NASA's original astronauts—died on Wednesday at 87 years old.
Funk was the last living member of the First Lady Astronaut Trainees (FLATs, or as they were later dubbed by the media, the Mercury 13), a group of women pilots who volunteered to go through the same physical and psychological tests as the United States' first spacemen.
Despite performing as well or better than their male counterparts, though, the Lovelace Woman in Space Program was conducted separately from NASA, and the space agency required that its astronauts be test pilots with jet time. The US military, however, did not accept women into its flight programs.
A recent groundbreaking study published in The Lancet’s eClinical Medicine reveals that a culturally tailored continuity of midwifery care model significantly improves perinatal outcomes for First Nations families in Victoria, Australia. This innovative approach, known as the Baggarrook Yurrongi or “Women’s Journey” model, ensures that women expecting First Nations babies receive consistent care from a known midwife throughout pregnancy, birth, and the early postnatal period.
Developed collaboratively with First Nations health organizations and maternity services, the Baggarrook Yurrongi model addresses the unique cultural needs of Aboriginal and Torres Strait Islander families. The study analyzed over 164,000 births from three major hospitals, including outcomes for more than 2,000 First Nations babies. Researchers utilized a prospective, non-randomized design, comparing data before (2012–2017) and after (2017–2022) the model’s implementation to assess its real-world efficacy.
The findings demonstrated monumental improvements: there was a 45% increase in the rate of healthy births among First Nations babies. Additionally, the likelihood of low birthweight decreased by 33%, preterm births by 36%, and neonatal intensive care admissions by 30%. Mothers were also 86% more likely to initiate breastfeeding, underscoring enhanced postnatal engagement and infant health support.
Lead researcher Professor Della Forster emphasized the significance of culturally informed midwifery continuity care, highlighting its role in bridging healthcare disparities. By fostering trust and cultural safety, the model encourages better health practices and outcomes, marking a notable stride toward closing the persistent gap in Indigenous perinatal health.
Key to the success of this approach is the trusted relationship a known midwife builds with expectant mothers—crucial for communities historically wary of healthcare systems. Programs like Mercy Hospital for Women’s Nangnak Baban Murrup and Joan Kirner Women’s and Children’s Hospital’s Galinjera have demonstrated both high uptake and satisfaction levels among clients and midwives alike, indicating sustainable integration into standard maternity care.
Clinical Midwife Specialist Evelyn Burns remarked that this continuity of care model profoundly impacts women’s confidence and connection during pregnancy. The study’s robust dataset and positive qualitative feedback from both families and clinicians provide compelling evidence for broader adoption across Australian maternity services.
This research not only validates the efficacy of culturally tailored care models but advocates for their expansion nationwide to ensure equitable and effective maternity healthcare for all First Nations families. The findings represent a pivotal shift in perinatal care paradigms, blending cultural competence with clinical excellence to improve long-term maternal and infant health outcomes.
Subject of Research: People
Article Title: The effect of culturally tailored continuity of midwifery care on perinatal outcomes for women having a first Nations baby in Victoria, Australia: a prospective non-randomised translational study
News Publication Date: 24-Jun-2026
Web References: https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(26)00281-6/fulltext
References: 10.1016/j.eclinm.2026.104028
Image Credits: La Trobe University
Keywords: Health care, First Nations, midwifery continuity, perinatal outcomes, culturally tailored care
1 July 2026 2:00pm -3:00pm ET 11:00am – 12:00 pm PT
community
Cosmic Origins
Type
Seminar
Why and Where Do We Want to Put Telescopes on the Moon?
Speaker
Nivedita Mahesh, CU Boulder
Abstract
The Moon is emerging as a uniquely valuable platform for astrophysics, enabling observations that neither Earth nor free-flying spacecraft can support. This talk surveys the scientific motivation across four complementary regimes. At low radio frequencies, the radio-quiet lunar farside opens a window onto the cosmological Dark Ages and the magnetospheres of exoplanets. In the mid-band gravitational-wave regime, the Moon’s low seismic activity bridges the sensitivity gap between terrestrial and space-based detectors. At ultraviolet wavelengths, its natural vacuum and long coherence times allow high-resolution stellar imaging beyond what is possible on Earth. And in the far-infrared, the cold, stable conditions of permanently shadowed regions offer a naturally cryogenic, absorption-free site for probing star and planet formation and the obscured Universe.
For each regime, I will share updates from the mission concept leads on the efforts now developing within the Astrophysics from the Moon, Mars & Beyond (AMMB) Science Interest Group. Together, these cases point to a paradigm shift: astrophysics from the Moon is becoming not just desirable but necessary.
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