Women’s health experts appointed to tackle ‘medical misogyny’
- health equity in healthcare and services
- health literacy for women in priority populations
- strengthening and diversifying medical research
- health workforce training and education
Elevating people with lived experience of mental ill-health to drive reform
2023 NSW Women of the Year Awards finalists announced
- Dr Rebecca Deans - Randwick
- Anne Dennis - Walgett
- Arabella Gibson - Mosman
- Unis Goh - Turramurra
- Jodie Ward - Heathcote
- Natalie Ahmat - Gladesville
- Debbie Barwick - Rutherford
- Jodi Edwards - Flinders
- Lynda Edwards - Narromine
- Kirsty Hargraves - Dubbo
- Naomi Moran - Lismore
- Elly Bird - Lismore
- Randa Habelrih - Maroubra
- Mary Hollingworth - Glen Innes
- Angela McCann OAM - Coolamon
- Emma Bracken - Suffolk Park
- Gayle Dunn - Ulladulla
- Dannielle Pickford - Banora Point
- Sally Rogers - Eatonsville
- Ashna Basu - Randwick
- Chanel Contos - Sydney
- Lua Pellegrini - Toongabbie
- Daniya Syed - Oran Park
- Jiahui Diana Zhang - Blacktown
- Abbie - Epping
- Matilda Gibson - Cessnock
- Jorja O’Brien - Young
- Grace Salkeld - Garthowen
- Jasmine Seidel - New Lambton Heights
- Coralie Smith - Ulladulla
- Haniya Syed - Oran Park
- Penelope Towney - Corrimal
- Lucy Trease - Alstonville
- Audrey Wood - Mount Kuring-gai
Antibiotics shortage in Australia
AI is helping us search for intelligent alien life – and we’ve found 8 strange new signals

Some 540 million years ago, diverse life forms suddenly began to emerge from the muddy ocean floors of planet Earth. This period is known as the Cambrian Explosion, and these aquatic critters are our ancient ancestors.
All complex life on Earth evolved from these underwater creatures. Scientists believe all it took was an ever-so-slight increase in ocean oxygen levels above a certain threshold.
We may now be in the midst of a Cambrian Explosion for artificial intelligence (AI). In the past few years, a burst of incredibly capable AI programs like Midjourney, DALL-E 2 and ChatGPT have showcased the rapid progress we’ve made in machine learning.
AI is now used in virtually all areas of science to help researchers with routine classification tasks. It’s also helping our team of radio astronomers broaden the search for extraterrestrial life, and results so far have been promising.
Discovering alien signals with AI
As scientists searching for evidence of intelligent life beyond Earth, we have built an AI system that beats classical algorithms in signal detection tasks. Our AI was trained to search through data from radio telescopes for signals that couldn’t be generated by natural astrophysical processes.
When we fed our AI a previously studied dataset, it discovered eight signals of interest the classic algorithm missed. To be clear, these signals are probably not from extraterrestrial intelligence, and are more likely rare cases of radio interference.
Nonetheless, our findings – published today in Nature Astronomy – highlight how AI techniques are sure to play a continued role in the search for extraterrestrial intelligence.

Not so intelligent
AI algorithms do not “understand” or “think”. They do excel at pattern recognition, and have proven exceedingly useful for tasks such as classification – but they don’t have the ability to problem solve. They only do the specific tasks they were trained to do.
So although the idea of an AI detecting extraterrestrial intelligence sounds like the plot of an exciting science fiction novel, both terms are flawed: AI programs are not intelligent, and searches for extraterrestrial intelligence can’t find direct evidence of intelligence.
Instead, radio astronomers look for radio “technosignatures”. These hypothesised signals would indicate the presence of technology and, by proxy, the existence of a society with the capability to harness technology for communication.
For our research, we created an algorithm that uses AI methods to classify signals as being either radio interference, or a genuine technosignature candidate. And our algorithm is performing better than we’d hoped.
What our AI algorithm does
Technosignature searches have been likened to looking for a needle in a cosmic haystack. Radio telescopes produce huge volumes of data, and in it are huge amounts of interference from sources such as phones, WiFi and satellites.
Search algorithms need to be able to sift out real technosignatures from “false positives”, and do so quickly. Our AI classifier delivers on these requirements.
It was devised by Peter Ma, a University of Toronto student and the lead author on our paper. To create a set of training data, Peter inserted simulated signals into real data, and then used this dataset to train an AI algorithm called an autoencoder. As the autoencoder processed the data, it “learned” to identify salient features in the data.
In a second step, these features were fed to an algorithm called a random forest classifier. This classifier creates decision trees to decide if a signal is noteworthy, or just radio interference – essentially separating the technosignature “needles” from the haystack.
After training our AI algorithm, we fed it more than 150 terabytes of data (480 observing hours) from the Green Bank Telescope in West Virginia. It identified 20,515 signals of interest, which we then had to manually inspect. Of these, eight signals had the characteristics of technosignatures, and couldn’t be attributed to radio interference.
Eight signals, no re-detections
To try and verify these signals, we went back to the telescope to re-observe all eight signals of interest. Unfortunately, we were not able to re-detect any of them in our follow-up observations.
We’ve been in similar situations before. In 2020 we detected a signal that turned out to be pernicious radio interference. While we will monitor these eight new candidates, the most likely explanation is they were unusual manifestations of radio interference: not aliens.
Sadly the issue of radio interference isn’t going anywhere. But we will be better equipped to deal with it as new technologies emerge.
Narrowing the search
Our team recently deployed a powerful signal processor on the MeerKAT telescope in South Africa. MeerKAT uses a technique called interferometry to combine its 64 dishes to act as a single telescope. This technique is better able to pinpoint where in the sky a signal comes from, which will drastically reduce false positives from radio interference.
If astronomers do manage to detect a technosignature that can’t be explained away as interference, it would strongly suggest humans aren’t the sole creators of technology within the Galaxy. This would be one of the most profound discoveries imaginable.
At the same time, if we detect nothing, that doesn’t necessarily mean we’re the only technologically-capable “intelligent” species around. A non-detection could also mean we haven’t looked for the right type of signals, or our telescopes aren’t yet sensitive enough to detect faint transmissions from distant exoplanets.
We may need to cross a sensitivity threshold before a Cambrian Explosion of discoveries can be made. Alternatively, if we really are alone, we should reflect on the unique beauty and fragility of life here on Earth.
Danny C Price, Senior research fellow, Curtin University
This article is republished from The Conversation under a Creative Commons license. Read the original article.
3 in 4 people experience abuse on dating apps. How do we balance prevention with policing?

A 2022 survey by the Australian Institute of Criminology found three in four app users surveyed had experienced online abuse or harassment when using dating apps. This included image-based abuse and abusive and threatening messages. A further third experienced in-person or off-app abuse from people they met on apps.
These figures set the scene for a national roundtable convened on Wednesday by Communications Minister Michelle Rowland and Social Services Minister Amanda Rishworth.
Experiences of abuse on apps are strongly gendered and reflect preexisting patterns of marginalisation. Those targeted are typically women and members of LGBTIQA+ communities, while perpetrators are commonly men. People with disabilities, Aboriginal and Torres Strait Islander people, and people from migrant backgrounds report being directly targeted based on their perceived differences.
What do these patterns tell us? That abuse on apps isn’t new or specific to digital technologies. It reflects longstanding trends in offline behaviour. Perpetrators simply exploit the possibilities dating apps offer. With this in mind, how might we begin to solve the problem of abuse on dating apps?
Trying to find solutions
Survivors of app-related abuse and violence say apps have been slow to respond, and have failed to offer meaningful responses. In the past, users have reported abusive behaviours, only to be met with a chatbot. Also, blocking or reporting an abusive user doesn’t automatically reduce in-app violence. It just leaves the abuser free to abuse another person.
Wednesday’s roundtable considered how app-makers can work better with law enforcement agencies to respond to serious and persistent offenders. Although no formal outcomes have been announced, it has been suggested that app users should provide 100 points of identification to verify their profiles.
But this proposal raises privacy concerns. It would create a database of the real-world identities of people in marginalised groups, including LGBTIQA+ communities. If these data were leaked, it could cause untold harm.
Prevention is key
Moreover, even if the profile verification process was bolstered, regulators could still only respond to the most serious cases of harm, and after abuse has already occurred. That’s why prevention is vital when it comes to abuse on dating apps. And this is where research into everyday patterns and understanding of app use adds value.
Often, abuse and harassment are fuelled by stereotypical beliefs about men having a “right” to sexual attention. They also play on widely held assumptions that women, queer people and other marginalised groups do not deserve equal levels of respect and care in all their sexual encounters and relationships – from lifelong partnerships to casual hookups.
In response, app-makers have engaged in PSA-style campaigns seeking to change the culture among their users. For example, Grindr has a long-running “Kindr” campaign that targets sexual racism and fatphobic abuse among the gay, bisexual and trans folk who use the platform.

Other apps have sought to build safety for women into the app itself. For instance, on Bumble only women are allowed to initiate a chat in a bid to prevent unwanted contact by men. Tinder also recently made its “Report” button more visible, and provided users safety advice in collaboration with WESNET.
Similarly, the Alannah & Madeline Foundation’s eSafety-funded “Crushed But Okay” intervention offers young men advice about responding to online rejection without becoming abusive. This content has been viewed and shared more than one million times on TikTok and Instagram.
In our research, app users told us they want education and guidance for antisocial users – not just policing. This could be achieved by apps collaborating with community support services, and advocating for a culture that challenges prevailing gender stereotypes.
Policy levers for change
Apps are widely used because they promote opportunities for conversation, personal connection and intimacy. But they are a for-profit enterprise, produced by multinational corporations that generate income by serving advertising and monetising users’ data.
Taking swift and effective action against app-based abuse is part of their social license to operate. We should consider stiff penalties for app-makers who violate that license.
The United Kingdom is just about to pass legislation that contemplates time in prison for social media executives who knowingly expose children to harmful content. Similar penalties that make a dent in app-makers’ bottom line may present more of an incentive to act.
In the age of widespread data breaches, app users already have good reason to mistrust demands to supply their personal identifying information. They will not necessarily feel safer if they are required to provide more data.
Our research indicates users want transparent, accountable and timely responses from app-makers when they report conduct that makes them feel unsafe or unwelcome. They want more than chatbot-style responses to reports of abusive conduct. At a platform policy level, this could be addressed by hiring more local staff who offer transparent, timely responses to complaints and concerns.
And while prevention is key, policing can still be an important part of the picture, particularly when abusive behaviour occurs after users have taken their conversation off the app itself. App-makers need to be responsive to police requests for access to data when this occurs. Many apps, including Tinder, already have clear policies regarding cooperation with law enforcement agencies.
Kath Albury, Professor of Media and Communication and Associate Investigator, ARC Centre of Excellence for Automated Decision-Making + Society, Swinburne University of Technology and Daniel Reeders, PhD Candidate, ANU School of Regulation and Global Governance (RegNet), Australian National University
This article is republished from The Conversation under a Creative Commons license. Read the original article.
Nope, coffee won’t give you extra energy. It’ll just borrow a bit that you’ll pay for later

Many of us want (or should I say need?) our morning coffee to give us our “get up and go”. Altogether, the people of the world drink more than two billion cups of coffee each day.
You might think coffee gives you the energy to get through the morning or the day – but coffee might not be giving you as much as you think.
The main stimulant in coffee is the caffeine. And the main way caffeine works is by changing the way the cells in our brain interact with a compound called adenosine.
Getting busy, getting tired
Adenosine is part of the system that regulates our sleep and wake cycle and part of why high levels of activity lead to tiredness. As we go about our days and do things, levels of adenosine rise because it is released as a by-product as energy is used in our cells.
Eventually adenosine binds to its receptor (parts of cells that receive signals) which tells the cells to slow down, making us feel drowsy and sleepy. This is why you feel tired after a big day of activity. While we are sleeping, energy use drops lowering adenosine levels as it gets shuffled back into other forms. You wake up in the morning feeling refreshed. Well, if you get enough sleep that is.
If you are still feeling drowsy when you wake up caffeine can help, for a while. It works by binding to the adenosine receptor, which it can do because it is a similar shape. But it is not so similar that it triggers the drowsy slow-down signal like adenosine does. Instead it just fills the spots and stops the adenosine from binding there. This is what staves off the drowsy feeling.
No free ride
But there is a catch. While it feels energising, this little caffeine intervention is more a loan of the awake feeling, rather than a creation of any new energy.
This is because the caffeine won’t bind forever, and the adenosine that it blocks doesn’t go away. So eventually the caffeine breaks down, lets go of the receptors and all that adenosine that has been waiting and building up latches on and the drowsy feeling comes back – sometimes all at once.
So, the debt you owe the caffeine always eventually needs to be repaid, and the only real way to repay it is to sleep.

Timing is everything
How much free adenosine is in your system, that hasn’t attached to receptors yet, and how drowsy you are as a consequence will impact how much the caffeine you drink wakes you up. So, the coffee you drink later in the day, when you have more drowsy signals your system may feel more powerful.
If it’s too late in the day, caffeine can make it hard to fall asleep at bedtime. The “half life” of caffeine (how long it takes to break down half of it) is about five hours). That said, we all metabolise caffeine differently, so for some of us the effects wear off more quickly. Regular coffee drinkers might feel less of a caffeine “punch”, with tolerance to the stimulant building up over time.

Caffeine can also raise levels of cortisol, a stress hormone that can make you feel more alert. This might mean caffeine feels more effective later in the morning, because you already have a natural rise in cortisol when you wake up. The impact of a coffee right out of bed might not seem as powerful for this reason.
If your caffeinated beverage of choice is also a sugary one, this can exacerbate the peak and crash feeling. Because while sugar does create actual energy in the body, the free sugars in your drink can cause a spike in blood sugar, which can then make you feel tired when the dip comes afterwards.
While there is no proven harm of drinking coffee on an empty stomach, coffee with or after a meal might hit you more slowly. This is because the food might slow down the rate at which the caffeine is absorbed.
What about a strong tea or fizzy cola?
Coffee, of course, isn’t the only caffeinated beverage that can loan you some energy.
The caffeine in tea, energy drinks and other beverages still impacts the body in the same way. But, since the ingredients mostly come from plants, each caffeinated beverage has its own profile of additional compounds which can have their own stimulant effect, or can interact with caffeine to change its impacts.
Caffeine can be useful, but it isn’t magic. To create energy and re-energise our bodies we need enough food, water and sleep.
Emma Beckett, Senior Lecturer (Food Science and Human Nutrition), School of Environmental and Life Sciences, University of Newcastle
This article is republished from The Conversation under a Creative Commons license. Read the original article.
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