Category: 7. Science

An unusual sort of gang violence gripped the city of Lopburi, Thailand, during the peak of the COVID-19 pandemic: Rival groups of macaque monkeys, whose appetites were typically satisfied by the generosity of now-absent tourists, began to fight over the scarce food available.

During the melees, the monkeys seemed to know which side they were fighting for, but to someone watching videos of the events—which Mark Laubach, professor of neuroscience at American University, did online—it was difficult to tell. “It would take 10 years of primatology and improved cameras” to figure it out, he says one of his colleagues who studies non-human primates told him. To Laubach, that assessment highlighted not only the complexity of monkey social dynamics, but also the limitations of the tools currently available to classify that behavior. “Those methods work for a single animal,” he says. “But when you get into multi-animal stuff, it becomes very challenging.”

Social neuroscientists, who frequently video record interacting animals for hours upon hours, are particularly interested in this sort of question. And although a proliferation of new tools—such as improved tracking and pose estimators—has helped researchers streamline their work, limitations remain, says Ann Kennedy, associate professor of neuroscience at the Scripps Research Institute.

One flaw in particular is that classifiers trained on data from one lab do not typically work for others, Kennedy says. In an attempt to solve that problem, she and her colleagues have organized a “Multi-Agent Behavior Challenge,” which launched today. The challenge is the third competition to come from Kennedy and her co-organizers.

The plan is for competitors to receive pose-tracking estimates from videos of interacting mice, as well as handmade annotations of the recorded behaviors, from 15 different labs, Kennedy says. Competitors then train bespoke algorithms on those pose estimates and test how well they can predict 36 behaviors—which include sniffing, attacking, mounting, chasing and freezing—in a new set of estimates from which the annotations have been withheld.

“We’re saying, in addition to learning representations that are good for arbitrary tasks, can you learn a common representation of behavior that’s invariant to all of these different lab-specific sources of noise?” Kennedy says.

The people who develop the model that can most accurately classify behaviors in the test dataset are slated to receive a cash prize of $20,000, with additional prizes for second through fifth place.

In creating the competition, the organizers can draw on the expertise of people outside of the social neuroscience field, says Laubach, who is not involved in the competition. “I don’t know how you would advance the field without this approach,” he says. “It is necessary, because the whole thing is collaborative. No [single] person knows how to do this.”

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hallenges like this one are common in the field of computer science, says competition co-organizer Jennifer Sun, assistant professor of computer science at Cornell University. “There are so many new models being developed,” she says. “If they’re all evaluated on different datasets, it becomes really, really hard to compare the models and understand, does this model work better because it was trained on a different dataset or because the architecture was better or [because] it was trained longer?”

For Sun and Kennedy’s first competition, which they launched in 2021, they drew inspiration from vision-science challenges, such as those that sought to improve algorithms for object recognition. The team asked participants to classify mouse behavior based on video tracking and pose estimation collected from a single lab. In 2022, their challenge involved creating representations of the behavior of multiple species, including mice, flies and ant beetles.

The results may help researchers decide which model to use for an experiment, Sun says. They can also establish benchmarks for where the field is and which issues still need to be addressed, she adds. “If a model works well, it lets us know what’s the best state-of-the-art method right now for tackling that task. And if things don’t work, then we know to invest more research resources from the computer science side into solving these problems.”

The challenges also help to reveal trends in the field, she says. For example, all of the top-performing models in the 2022 competition used transformers, a machine-learning tool also used in large language models. “There’s definitely this effect that we should disentangle,” Sun says. “Does that mean transformers are the best, or does it mean that more people try transformers?”

This year, the team framed the competition around the development of classifiers that work for multiple labs’ data, with certain constraints. “All of the datasets are top-down videos of interacting mice. And we’re giving people key points,” Kennedy says. But the winning approaches will still need to develop models that work for videos collected from different experiments and with different video frame rates, tracked body parts and mouse strains. “It’s representative of the variety of settings you see in social neuroscience labs studying mouse behavior. And so the hope is that people can learn representations not just within a lab, but across labs.”

Identifying a classifier that works across labs would be an improvement upon past competitions, says Nancy Padilla-Coreano, assistant professor of neuroscience at the University of Florida, who is not involved in the competition. “It’s a step towards it being useful for the field.”

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nother benefit of this and past challenges is that they bring together researchers from different fields, says Shreya Saxena, assistant professor of biomedical engineering at Yale University, who was not involved in the competitions. Computer scientists may not have the neuroscience background to know how to identify problems in the field. “They may want to actually solve or help address some of these issues, but they may not know where to start,” she says.

But neuroscientists should keep in mind that just because a model beats out the others does not necessarily mean that it advances the field, Saxena adds.

People who want to participate can make an account on Kaggle, the site that is hosting the competition. They can compete as individuals or as part of a team, using either a new or existing model. Participants will be asked to input their predictions based on their own model; but data, import code and submission code will be provided, Kennedy says.

The organizers plan to make the data and winning models freely available for researchers to use after the competition. For example, the dataset might help researchers better predict a mouse’s next behavior based on their past behavior, Kennedy says. And in the future, these improvements may help advance the field’s understanding of social behavior in other species, as well, she adds. “Once the dataset is curated and out there, the hope is that this can be used for all sorts of follow-up projects.”

Real-time footage of a human embryo implanting into an artificial uterus has been captured for the first time.

The remarkable feat, published in the journal Science Advances, offers an unprecedented view into one of the most critical steps in human development. 

Implantation failure in the uterus is one of the main contributors to infertility, accounting for 60 per cent of miscarriages. The researchers hope that a better understanding of the implantation process could help improve fertility outcomes, both in natural conception and in vitro fertilisation (IVF).

“Because implantation happens inside the mother, we can’t see it,” Dr Samuel Ojosnegros, head of bioengineering in reproductive health at the Institute for Bioengineering Catalonia (IBEC) and lead author of the new study, told BBC Science Focus. 

“So we needed a system where we could see how it works. That way, we can tackle the main roadblock in human fertility.” 

Implantation is the stage in early pregnancy when a fertilised egg, now a developing embryo, attaches itself to the lining of the uterus. This step allows the embryo to draw nutrients and oxygen from the mother, making it essential for a successful pregnancy.

To study the process, the team built a platform that mimics the lining of a real uterus, consisting of a scaffold made of collagen and a mixture of proteins necessary for development. 

They then studied how both human and mouse embryos implant on the platform, revealing some key differences. Unlike mouse embryos, which adhere to the surface of the uterus, human embryos penetrate the tissue completely before growing from the inside out. 

“The human embryo is very invasive,” Ojosnegros said. “It burrows into the matrix and embeds itself, and then grows inside.” 

The footage revealed that in order to do this, the embryo exerts a considerable force on the uterus. 

“We observe that the embryo pulls on the uterine matrix, moving and reorganising it,” Dr Amélie Godeau, co-first author of the study, said in a statement. “It also reacts to external force cues. It also reacts to external force cues. We hypothesise that contractions occurring in vivo may influence embryo implantation.” 

According to Ojosnegros, the force applied during this stage could explain the pain and bleeding many women experience during implantation, the reasons for which were not fully understood before.

The researchers are now developing ways to make the implantation platform more lifelike, including by integrating living cells. The hope is that by creating a realistic window into the implantation process, they will be able to improve the odds of success in IVF, for example, by selecting embryos with better implantation potential. 

“We know more about the development of flies and worms than of our own species,” Ojosnegros said. “So watch the movies, and enjoy.” 

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The human pelvis is rounded, like a basket, to enable us to walk and stand upright with ease. The ape pelvis is tall and narrow, with the upper hip bones appearing like blades, allowing apes to walk on all fours and effortlessly climb and swing in trees.

In the evolutionary story, we evolved from an apelike ancestor who would have had more apelike hips. How, exactly, this massive anatomical feat of evolution supposedly happened has remained a mystery. . . but has it now been solved?

A new study claims to have uncovered “some of the key genetic and developmental shifts that radically resculpted the quadrupedal ape pelvis into a bipedal one.” Using samples from human “embryonic tissues” (it’s unclear how these tissues, some of which were “collected by the Birth Defects Research Laboratory at the University of Washington,” were obtained—I certainly hope no unborn children made in the image of God were killed for this useless research!) and primate museum specimens, “they took CT scans and analyzed histology (the microscopic structure of tissues) to reveal the anatomy of the pelvis during early stages of development.”

They determined that:

Evolution reshaped the human pelvis in two major steps. First, it shifted a growth plate by 90 degrees to make the human ilium wide instead of tall. Later, another shift altered the timeline of embryonic bone formation. . .

In the early stages of development, the human iliac growth plate formed with growth aligned head-to-tail just as it did in other primates. But by day 53, the growth plates in humans evolved to radically shift perpendicularly from the original axis—thus shortening and broadening the hipbone.

So they observed how the pelvis develops in an unborn child and assumed evolution must somehow have radically changed up the developmental process. In other words, this is an interpretation based on evolutionary assumptions.

Shifting an entire pelvis isn’t just moving some bones around!

But think about that—shifting an entire pelvis isn’t just moving some bones around! If the pelvis dramatically changes shape, the muscle attachments must also change, as would the blood vessels, the ligaments and tendons, the nervous system, and so much more! It all must have happened together, or it wouldn’t work. The human body is incredibly complex and integrated, and any “small” change—let alone a radical change like what they are suggesting—has massive ripple effects throughout the whole body.

And, of course, development is controlled by genes. So they assume those must have changed too.

The team identified more than 300 genes at work, including three with outsized roles—SOX9 and PTH1R (controlling the growth plate shift), and RUNX2 (controlling the change in ossification). . .

The authors suggest that these changes began with reorientation of growth plates around the time that our ancestors branched from the African apes, estimated to be between 5 million and 8 million years ago.

So changes to three different genes supposedly drove the “reorientation of growth plates” that somehow magically allowed humans to evolve upright walking.

This is nothing but storytelling! It’s a fairy tale. None of this was observed—what they observed was clear differences between humans and apes. That’s it! They then applied their evolutionary storytelling to the evidence to suggest that they’ve figured out how humans evolved our unique pelvis. But all they really showed with their observations is that apes and humans are different! Essentially, their position is: Because human hips and ape hips are very different, evolution is true, because evolution happened.

Apes and humans are different—radically different—because we’re totally separate kinds with absolutely no relation to one another.

Apes and humans are different—radically different—because we’re totally separate kinds with absolutely no relation to one another. Apes were made as their own kind on day six of creation week. Humans were then made as their own kind—made in the image of God—later that day, man from the dust (not from an “ape-man”) and woman from his side (not from an “ape-woman”).

The Bible gives us the true history of humanity and of apes.

Thanks for stopping by and thanks for praying,

Ken

This item was written with the assistance of AiG’s research team.

The teenage pachycephalosaur was raring to go. Like many other bird-hipped Ornithischian dinosaurs and many a modern animal too, he had reached sexual maturity before his body finished growing – we monkeys do the same.

We can’t say whether being addled by puberty hormones messed with his mind and led to his premature passing, as happens with incautious apes. But somehow he died in what is today the Gobi Desert 108 million years ago before he could grow up, Tsogtbaatar Chinzorig of the Mongolian Academy of Sciences, Lindsay Zanno of North Carolina State University and colleagues reported in Nature on Wednesday.

The youthful pachycephalosaur was a previously unknown species of dome-skulled dinosaur and is the earliest of his kind found to date, pushing back the timeline of the group by as much as 22 million years to the Early Cretaceous.

His species is now named Zavacephale rinpoche, from zava, meaning “root” or “origin” in Tibetan, and cephal, meaning “head” in Latin. Rinpoche is “precious one” in Tibetan and refers to the domed skull, which Chinzorig observed exposed on a cliff like a cabochon jewel.

This took place in the Lower Cretaceous Khuren Dukh Formation in the Gobi Desert, Mongolia, the researchers say. Today the site is stark and arid but back then it was a pleasant valley.

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Young Zavacephale was wee, all of a meter long, and weighed about 5.9 kilograms, or 13 pounds, about the same as a Jack Russell Terrier. Other species of dome-headed dinosaurs in the Late Cretaceous could reach 4 to 5 meters long in adulthood and are estimated to have weighed between 370 and 450 kilograms (992 pounds).

No, from his remains, the researchers can’t extrapolate how big this one might have become, Zanno says. But at a meter tall in teen-hood, he probably wouldn’t have been a giant.

Though Zavacephale is the earliest pachycephalosaur ever found, there were earlier ones we haven’t found. Such are the vagaries of fossil hunting. His species isn’t ancestral to the group; they were already diverging, the authors say. Even so, his discovery sheds light on the evolutionary trajectory of dome-headed dinosaurs, and their personal maturation, which had been unclear due to a paucity of fossil evidence and the terrible shape of those clues.

This fossil is almost complete, so the team could deduce that his bony head-dome finished developing while the rest of him didn’t.

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How teenagers do it

How do we know he was sexually mature? “The dome evolved for social interactions, most likely involving mating or territorial behaviors, thus the timing of full-dome development should correspond to sexual maturity,” Zanno explains by email from Mongolia.

How do we know he was somatically immature? “We determined that it was not fully grown by examining a thin slice of its leg bones. The fossilized tissue confirms this animal was a juvenile when it died,” she says.

“We age dinosaurs by looking at growth rings in bones, but most pachycephalosaur skeletons are just isolated, fragmentary skulls. Z. rinpoche is a spectacular find because it has limbs and a complete skull, allowing us to couple growth stage and dome development for the first time.”

So why are we calling him a teenager? Because he was sexually mature but not full-grown, and if ever there was teenage territory, that’s it.

Are the scientists sure pachycephalosaurs weren’t born, or hatched really, with domes?

“We have not yet discovered any baby pachycephalosaurs, but the smallest skulls we have generally lack domes,” Zanno says. “The dome is thought to develop as the animal matures from baby to adult.”

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All about the bling

There are two base hypotheses behind the thickened skull roof of pachycephalosaurs, which have puzzled paleontologists since the discovery of the beast in 1859. Paleontology was young and the discoverer of pachycephalosaurs, Ferdinand Vandeveer Hayden, thought that the creature resembled an armadillo and named it Tylosteus, or “knob lizard.” Later, separately, other specimens would be found and named Pachycephalosaurus.

When the realization dawned that Tylosteus and Pachycephalosaurus were the same, the former name should have prevailed according to the laws of nomenclature, but the latter was better known.

The two base hypotheses are self-defense and sociosexual behavior or both. Self-defense is self-explanatory. Sociosexual behavior could have included displaying for the ladies and/or fighting with other males. It seems many of the behaviors exhibited these days on TikTok go very far back.

In short, this is exactly the same base theory for other elaborately blinged-out Ornithischian dinosaurs, including frilled and horned ceratopsians such as Triceratops and stegosaurias with their spinal plates, not to mention ankylosaurians with their body armor and mace-like tail.

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Among this group too, paleontologists have identified decoupling between skeletal maturity and the bling that plausibly served to seduce – and/or fight – a characteristic also evident in extant dinosaurs, the researchers write. “Extant dinosaurs” are birds, which can reach sexual maturity before they reach full adulthood.

It’s just that this hadn’t been demonstrated in pachycephalosaurs before. Now it has been – the cranial dome stops growing before the rest of the skeleton.

“The domes wouldn’t have helped against predators or for temperature regulation, so they were most likely for showing off and competing for mates,” Zanno says. As for the early sexuality: “If you need to head-butt yourself into a relationship, it’s a good idea to start rehearsing early.”

The teenager in question was also the first pachycephalosaur in which the paleontologists also discovered gastroliths, known in chickens as gizzard stones. He was a herbivore and swallowed stones to aid in food breakdown and digestion. Gastroliths have been discovered in other herbivorous dinosaurs too.

And this teenager may have had children, who would pass down the ancient feature of domes atop their heads that they would probably use to ram into other pachycephalosaurs when feeling frisky.

The search for atmospheres on rocky exoplanets is a crucial step in understanding the processes driving atmosphere formation, retention, and loss.

Past studies have revealed the existence of planets interior to the radius valley with densities lower than would be expected for pure-rock compositions, indicative of the presence of large volatile inventories which could facilitate atmosphere retention.

Here we present an analysis of the JWST NIRSpec/G395H transmission spectrum of the warm (T_eq,AB=0 = 569 K) super-Earth TOI-270 b (R_p = 1.306 R_⊕), captured alongside the transit of TOI-270 d. The JWST white light-curve transit depth updates TOI-270 b’s density to ρp = 3.7±0.5 g/cm³ , inconsistent at 4.4σ with an Earth-like composition. Instead, the planet is best explained by a non-zero, percentlevel water mass fraction, possibly residing on the surface or stored within the interior.

The JWST transmission spectrum shows possible spectroscopic evidence for the presence of this water as part of an atmosphere on TOI-270 b, favoring a H₂O-rich steam atmosphere model over a flat spectrum (ln B = 0.3−3.2, inconclusive to moderate), with the exact significance depending on whether an offset parameter between the NIRSpec detectors is included.

We leverage the transit of the twice-larger TOI270 d crossing the stellar disk almost simultaneously to rule out the alternative hypothesis that the transit-light-source effect could have caused the water feature in TOI-270 b’s observed transmission spectrum.

Planetary evolution modeling furthermore shows that TOI-270 b could sustain a significant atmosphere on Gyr timescales, despite its high stellar irradiation, if it formed with a large initial volatile inventory.

Broadband and spectroscopic light-curve fits of the NIRSpec/G395H transit of TOI-270 b, extracted with exoTEDRF. The top panel is a schematic of TOI-270 b (blue) and d (red) as they transit across the stellar disk at time t = 2460222.265 BJD, illustrating their trajectories (dashed lines) and the 1σ confidence region corresponding to their orbital inclination uncertainties. The broadband light-curve fits (white) are shown for the NRS1 and NRS2 detectors, along with eight systematics-corrected spectroscopic light curves (colored dots) and their best-fit transit models (black lines). The light curves are plotted with a relative flux offset and are binned in time in groups of 75 data points (corresponding to 13.6 minute bins). The best-fit model transit of TOI-270 d, whose position is indicated by the gray dashed lines, partially overlaps with that of TOI-270 b and is removed from the data and best-fit model for visual clarity. All light curves are well-behaved and show Gaussian distributions in their residuals (computed from the non-binned light curves, right). — astro-ph.EP

Louis-Philippe Coulombe, Björn Benneke, Joshua Krissansen-Totton, Alexandrine L’Heureux, Caroline Piaulet-Ghorayeb, Michael Radica, Pierre-Alexis Roy, Eva-Maria Ahrer, Charles Cadieux, Yamila Miguel, Hilke E. Schlichting, Elisa Delgado-Mena, Christopher Monaghan, Hanna Adamski, Eshan Raul, Ryan Cloutier, Thaddeus D. Komacek, Jake Taylor, Cyril Gapp, Romain Allart, François Bouchy, Bruno L. Canto Martins, Neil J. Cook, René Doyon, Thomas M. Evans-Soma, Pierre Larue, Alejandro Suárez Mascareño, Joost P. Wardenier

Comments: Published in The Astronomical Journal
Subjects: Earth and Planetary Astrophysics (astro-ph.EP); Solar and Stellar Astrophysics (astro-ph.SR)
Cite as: arXiv:2509.14224 [astro-ph.EP] (or arXiv:2509.14224v1 [astro-ph.EP] for this version)
https://doi.org/10.48550/arXiv.2509.14224
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Journal reference: Coulombe, L.-P., Benneke, B., Krissansen-Totton, J., et al. 2025, The Astronomical Journal, 170, 226
Related DOI:
https://doi.org/10.3847/1538-3881/adfc6a
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Submission history
From: Louis-Philippe Coulombe
[v1] Wed, 17 Sep 2025 17:55:16 UTC (5,758 KB)
https://arxiv.org/abs/2509.14224
Astrobiology,

NASA announced on Wednesday that the problem would prevent the spacecraft from reaching the ISS as scheduled. Engineers ultimately determined the engine’s early shutdown was caused by onboard software designed to protect the spacecraft from a potential problem.

Data transmitted from the spacecraft back to Northrop Grumman’s mission control center in Northern Virginia confirmed the engine itself operated normally. The premature engine shutdowns were triggered by a conservative software safeguard, according to NASA.

Operating under updated software parameters, the Cygnus spacecraft flew itself to within 30 feet of the space station early Thursday, close enough for Kim to use the robotic arm to reach out and grapple it.

This mission is the first flight of Northrop Grumman’s upgraded Cygnus XL spacecraft, with a cargo module 5.2 feet (1.6 meters) longer than the previous version of Cygnus. This translates to a capacity to carry 33 percent more cargo. The supply load on this mission totals 10,827 pounds (4,911 kilograms), a NASA spokesperson told Ars.

The cargo includes food, oxygen, and nitrogen, and spare parts for the station’s urine processor, which helps convert waste into fresh drinking water. The Cygnus spacecraft also delivered a new navigation aid to be mounted outside the space station to help future crew and cargo ships guide themselves toward the complex.

Among other things, research hardware aboard the Cygnus XL spacecraft will study the production of semiconductor crystals in microgravity and demonstrate a new way to keep cryogenic propellants properly conditioned during long-duration spaceflight.

Women, non-native English speakers and those from lower-income countries published fewer English-language peer-reviewed papers than men, native English speakers and those from higher-income countries, according to a study published September 18^th in the open-access journal PLOS Biology by Tatsuya Amano from The University of Queensland, Australia, and colleagues.

UNESCO posits that ” all scientists … have equal opportunity to access, contribute to and benefit from science, regardless of origin or circumstance .” However, research reports rampant inequities; for example, women are less likely to hold a tenured position, scientists from lower-income countries are less funded than their higher-income counterparts and non-native English speakers experience language-related rejection up to 2.6 times more often than native English speakers. While science undoubtedly benefits from diverse people, ideas and approaches, few studies have assessed how gender, language and income affect scientific productivity.

To quantify barriers faced by scientists identifying as women, non-native English speakers and those from low-income countries, Amano surveyed 908 environmental scientists at varying career stages across eight nationalities: Bangladeshi, Bolivian, British, Japanese, Nepali, Nigerian, Spanish, and Ukrainian. Amano measured each scientist’s productivity, defined as their total number of English and non-English publications.

Results revealed that women — especially early-career women — published 45% fewer English-language papers than men. Women with non-English first languages published 60% fewer papers, and women with non-English first languages from low-income countries published 70% fewer, compared to men with English as the first language from high-income countries.

When the researchers factored in English and non-English scientific publications, they noticed the proportions change. Non-native English speakers at early to mid-career stages published more peer-reviewed papers than native English speakers. Additionally, scientists from lower-income countries published more papers than those from higher-income countries. Even with English and non-English papers combined, women still published fewer articles than men.

The researchers write that these statistics could be erroneously used to position women, non-native English speakers and those from low-income countries as less scientifically productive. They call for an explicit effort to consider gender, income and native language and support incorporating non-English-language publications when assessing scientists’ performance.

The authors add, “This study highlights how language, economic status, and gender combine to create a significant and often overlooked productivity gap in science, especially when measured by English-language publications. We believe that this gap is not a true reflection of individual productivity. Rather, as a growing body of evidence shows, it stems from systemic barriers that continue to limit fair participation and full contribution to science by historically and currently underrepresented groups.”

In your coverage, please use this URL to provide access to the freely available paper in PLOS Biology: https://plos.io/4mJfCGw

Citation: Amano T, Ramírez-Castañeda V, Berdejo-Espinola V, Borokini I, Chowdhury S, Golivets M, et al. (2025) Language, economic and gender disparities widen the scientific productivity gap. PLoS Biol 23(8): e3003372. https://doi.org/10.1371/journal.pbio.3003372

Author countries: Australia, United States, Germany, Colombia, Nepal, United Kingdom

Funding: This work was supported by the following grants: Australian Research Council Future Fellowship FT180100354 (TA, V.B.-E.), Australian Research Council Discovery Project DP230101734 (TA, V.B.-E.), University of Queensland strategic funding (TA), and German Research Foundation (DFG-FZT 118, 202548816) (SC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.