Gina Rinehart is an honorary life member of the IPA and'a generous contributor to many causes,' IPA executive director, Scott Hargreaves, says. Gina Rinehart is an honorary life member of the IPA and'a generous contributor to many causes,' IPA executive director, Scott Hargreaves, says. Australia's richest person, Gina Rinehart has previously donated to Institute of Public Affairs but thinktank won't say if she remains a donor A thinktank known for its rejection of the climate crisis and a conservation group that has opposed renewable energy projects refused to identify their funders during a fiery Senate inquiry into climate and energy misinformation on Wednesday. Chair of the committee, Greens senator Peter Whish-Wilson, asked Rainforest Reserves Australia's vice-president, Steven Nowakowski, who had funded nine full-page newspaper advertisements promoting an open letter attacking a shift to renewable energy and promoting nuclear. Nowakowski said they were paid for by donations, some coming from the signatories of the letter, but would not name them.

Organisms in nature, such as Cephalopods and Pachyderms, exploit stiffness modulation to achieve amazing dexterity in the control of their appendages. In this paper, we explore the phenomenon of layer jamming, which is a popular stiffness modulation mechanism that provides an equivalent capability for soft robots. More specifically, we focus on mechanical layer jamming, which we realise through two-layer multi material structure with tooth-like protrusions. We identify key design parameters for mechanical layer jamming systems, including the ability to modulate stiffness, and perform a variety of comprehensive tests placing the specimens under bending and torsional loads to understand the influence of our selected design parameters (mainly tooth geometry) on the performance of the jammed structures. We note the ability of these structures to produce a peak change in stiffness of 5 times in bending and 3.2 times in torsion. We also measure the force required to separate the two jammed layers, an often ignored parameter in the study of jamming-induced stiffness change. This study aims to shed light on the principled design of mechanical layer jammed systems and guide researchers in the selection of appropriate designs for their specific application domains.

Modern slavery affects millions of people worldwide, and regulatory frameworks such as Modern Slavery Acts now require companies to publish detailed disclosures. However, these statements are often vague and inconsistent, making manual review time-consuming and difficult to scale. While NLP offers a promising path forward, high-stakes compliance tasks require more than accurate classification: they demand transparent, rule-aligned outputs that legal experts can verify. Existing applications of large language models (LLMs) often reduce complex regulatory assessments to binary decisions, lacking the necessary structure for robust legal scrutiny. We argue that compliance verification is fundamentally a rule-matching problem: it requires evaluating whether textual statements adhere to well-defined regulatory rules. To this end, we propose a novel framework that harnesses AI for rule-level compliance verification while preserving expert oversight. At its core is the Compliance Alignment Judge (CA-Judge), which evaluates model-generated justifications based on their fidelity to statutory requirements. Using this feedback, we train the Compliance Alignment LLM (CALLM), a model that produces rule-consistent, human-verifiable outputs. CALLM improves predictive performance and generates outputs that are both transparent and legally grounded, offering a more verifiable and actionable solution for real-world compliance analysis.

Soft Robotics presents a rich canvas for free-form and continuum devices capable of exerting forces in any direction and transforming between arbitrary configurations. However, there is no current way to tractably and directly exploit the design freedom due to the curse of dimensionality. Parameterisable sets of designs offer a pathway towards tractable, modular soft robotics that appropriately harness the behavioural freeform of soft structures to create rich embodied behaviours. In this work, we present a parametrised class of soft actuators, Programmable Telescopic Soft Pneumatic Actuators (PTSPAs). PTSPAs expand axially on inflation for deployable structures and manipulation in challenging confined spaces. We introduce a parametric geometry generator to customise actuator models from high-level inputs, and explore the new design space through semi-automated experimentation and systematic exploration of key parameters. Using it we characterise the actuators' extension/bending, expansion, and stiffness and reveal clear relationships between key design parameters and performance. Finally we demonstrate the application of the actuators in a deployable soft quadruped whose legs deploy to walk, enabling automatic adaptation to confined spaces. PTSPAs present new design paradigm for deployable and shape morphing structures and wherever large length changes are required.

In high-stakes information domains such as healthcare, where large language models (LLMs) can produce hallucinations or misinformation, retrieval-augmented generation (RAG) has been proposed as a mitigation strategy, grounding model outputs in external, domain-specific documents. Yet, this approach can introduce errors when source documents contain outdated or contradictory information. This work investigates the performance of five LLMs in generating RAG-based responses to medicine-related queries. Our contributions are three-fold: i) the creation of a benchmark dataset using consumer medicine information documents from the Australian Therapeutic Goods Administration (TGA), where headings are repurposed as natural language questions, ii) the retrieval of PubMed abstracts using TGA headings, stratified across multiple publication years, to enable controlled temporal evaluation of outdated evidence, and iii) a comparative analysis of the frequency and impact of outdated or contradictory content on model-generated responses, assessing how LLMs integrate and reconcile temporally inconsistent information. Our findings show that contradictions between highly similar abstracts do, in fact, degrade performance, leading to inconsistencies and reduced factual accuracy in model answers. These results highlight that retrieval similarity alone is insufficient for reliable medical RAG and underscore the need for contradiction-aware filtering strategies to ensure trustworthy responses in high-stakes domains.

Abstract--A wide variety of real-world data, such as sea measurements, e.g., temperatures collected by distributed sensors and multiple unmanned aerial vehicles (UA V) trajectories, can be naturally represented as graphs, often exhibiting non-Euclidean structures. These graph representations may evolve over time, forming time-varying graphs. Effectively modeling and analyzing such dynamic graph data is critical for tasks like predicting graph evolution and reconstructing missing graph data. In this paper, we propose a framework based on the Koopman autoencoder (KAE) to handle time-varying graph data. Specifically, we assume the existence of a hidden non-linear dynamical system, where the state vector corresponds to the graph embedding of the time-varying graph signals. T o capture the evolving graph structures, the graph data is first converted into a vector time series through graph embedding, representing the structural information in a finite-dimensional latent space. In this latent space, the KAE is applied to learn the underlying non-linear dynamics governing the temporal evolution of graph features, enabling both prediction and reconstruction tasks. A. Motivation Graphs are fundamental data structures for modeling the structure and interactions within complex systems [1] across a variety of domains, including, but not limited to, social networks [2], biological systems [3], transportation networks [4], and communication systems [5]. These data structures provide a versatile framework for representing relationships and dependencies, enabling insights into the organization and behavior of complex systems. In many real-world applications, the underlying graph data is not static; instead they evolve over time. Time-varying graphs [6] are a type of graph data characterized by temporal variations in their components or overall configuration. Unlike the commonly studied static graph structures, analyzing time-varying graph data introduces additional challenges. While the reconstruction of graph signals is necessary for recovering missing information, which is common in real-world sensor networks or data transmission scenarios, prediction, on the other hand, enables forecasting the future states of the systems and thus supports planning, decision-making, and control in dynamical environments. S. Krishnan and J. Choi are with the School of Electrical and Mechanical Engineering, The University of Adelaide, Australia (Emails:{jinho.choi,sivaram.krishan}@adelaide.edu.au), and J. Park is with the Information Systems Technology and Design Pillar, Singapore University of Technology and Design, Singapore (Email: jihong park@sutd.edu.sg).

Background: Large Language Models emerged with the potential of provoking a revolution in software development (e.g., automating processes, workforce transformation). Although studies have started to investigate the perceived impact of LLMs for software development, there is a need for empirical studies to comprehend how to balance forward and backward effects of using LLMs. Objective: We investigated how LLMs impact software development and how to manage the impact from a software developer's perspective. Method: We conducted 22 interviews with software practitioners across 3 rounds of data collection and analysis, between October (2024) and September (2025). We employed socio-technical grounded theory (STGT) for data analysis to rigorously analyse interview participants' responses. Results: We identified the benefits (e.g., maintain software development flow, improve developers' mental model, and foster entrepreneurship) and disadvantages (e.g., negative impact on developers' personality and damage to developers' reputation) of using LLMs at individual, team, organisation, and society levels; as well as best practices on how to adopt LLMs. Conclusion: Critically, we present the trade-offs that software practitioners, teams, and organisations face in working with LLMs. Our findings are particularly useful for software team leaders and IT managers to assess the viability of LLMs within their specific context.

'OK, so ChatGPT helps you write your grocery list. Does your individual convenience outweigh the societal harm it can cause?' 'OK, so ChatGPT helps you write your grocery list. Does your individual convenience outweigh the societal harm it can cause?' 'It shows such a laziness': why I refuse to date someone who uses ChatGPT It's the ultimate ick: trying to form a deep, lasting connection with a person who outsources original thought The Guardian's journalism is independent. We will earn a commission if you buy something through an affiliate link. I t was a setting fit for a Nancy Meyers film.

Newsom blasts'pathetic' Democrats for'surrendering' to Trump as'gang of eight' senators join Republicans to end longest government shutdown in US history Olympics set to ban ALL transgender athletes and Imane Khelif'DSD' competitors from female events after'finding scientific evidence of advantages to being born male' The REAL story of how Meghan lost her best friend: They've not spoken in years... but now insiders reveal'aggravation' and tensions that go'deeper than anyone knows' Scientists are baffled to discover mysterious'voids' in the third-largest pyramid of Giza - as scans suggest they could be a secret entrance Jordon Hudson appears to dodge encounter with Bill Belichick's daughter-in-law at UNC game after social media dig PayPal billionaire delivers chilling warning about spread of Communism as eerily prescient comment comes to light in wake of Mamdani's win Has Sydney Sweeney become too toxic for Hollywood? Star suffers box office flop with new film Christy after THAT controversial ad, Zendaya'feud' and backlash over her political views Dark side of Danielle Bernstein: She is America's most hated influencer... but now insiders reveal claims of behavior so outrageous they'kind of respect her' for getting away with it My brother was ALIVE on the operating table as surgeons tried to harvest his organs. Donald Trump launches new broadside at'corrupt' BBC journalists as director-general Tim Davie and news boss both quit in disgrace over doctored video of US President Meghan Markle wealthy pal's bookshop'is reported to council for serving her As Ever wine without a licence' after duchess used it as promotional pop-up Sussexes attended charity gala with Serena Williams before Kris Jenner's birthday party - while Royal Family marked Remembrance Sunday NFL announcer Tony Romo slammed by fans after outrageous'DTF' sexual reference live on air Donald Trump makes stunning flyover for first NFL visit of the season... hours after it emerged he wants $3.7bn new stadium named after him Jay Leno makes touching remark about caring for wife Mavis after 45 years of marriage amid heartbreaking'advanced' dementia diagnosis Barbara Bach captured America's hearts as a Bond girl... see her now after 44 years as a Beatle's wife Humanoid robot moves so smoothly, its inventor is forced to cut it open to prove there's not a person hiding inside READ MORE: Nike launches the world's first powered footwear A humanoid robot has reached new depths of the uncanny valley with its smooth, humanlike movements. Chinese electric vehicle manufacturer, Xpeng, revealed its latest robot dubbed the Xpeng IRON, at an event last week. The bot proved so eerily lifelike that its inventors were forced to cut it open on stage to prove there wasn't a person hiding inside.

At seventy-three, the former front man of Talking Heads is still asking questions about what it means to be alive. "When you step onstage, it's a very artificial situation," Byrne said. "To pretend it's not--that isn't being authentic." If you spend enough time wandering around downtown Manhattan, the odds are that you'll eventually encounter the musician David Byrne riding a bicycle. One day this past June, pedalling alongside Byrne from his apartment in Chelsea to the Governors Island ferry, I watched at least a dozen New Yorkers clock his profile, whipping around to squint, softly pinching the arm of their companion and whispering, "Was that . . . By then, Byrne was gone, a tuft of white hair whizzing toward the horizon. Spotting Byrne on two wheels has become a New York City rite of passage, like sussing out the best halal cart in midtown, or dropping something important onto the subway tracks. During the few months that Byrne and I spent together, I never saw him traverse the ...