Lifeboat Foundation: Safeguarding Humanity
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Blog – Page 4

Artificial intelligence could be affecting the scientific rigor of new research, according to a study from the University of Surrey.

The research team has called for a range of measures to reduce the flood of “low-quality” and “science fiction” papers, including stronger peer review processes and the use of statistical reviewers for complex datasets.

In a study published in PLOS Biology, researchers reviewed papers proposing an association between a predictor and a health condition using an American government dataset called the National Health and Nutrition Examination Survey (NHANES), published between 2014 and 2024.

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AI is a computing tool. It can process and interrogate huge amounts of data, expand human creativity, generate new insights faster and help guide important decisions. It’s trained on human expertise, and in conservation that’s informed by interactions with local communities or governments—people whose needs must be taken into account in the solutions. How do we ensure this happens?

Last year, Reynolds joined 26 other conservation scientists and AI experts in an “Horizon Scan”—an approach pioneered by Professor Bill Sutherland in the Department of Zoology—to think about the ways AI could revolutionize the success of global biodiversity conservation. The international panel agreed on the top 21 ideas, chosen from a longlist of 104, which are published in the journal Trends in Ecology and Evolution.

Some of the ideas extrapolate from AI tools many of us are familiar with, like phone apps that identify plants from photos, or birds from sound recordings. Being able to identify all the species in an ecosystem in real time, over long timescales, would enable a huge advance in understanding ecosystems and species distributions.

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In a test of the examinations system of the University of Reading in the UK, artificial intelligence (AI)-generated submissions went almost entirely undetected, and these fake answers tended to receive higher grades than those achieved by real students. Peter Scarfe of the University of Reading and colleagues present these findings in the open-access journal PLOS ONE on June 26.

In recent years, AI tools such as ChatGPT have become more advanced and widespread, leading to concerns about students using them to cheat by submitting AI-generated work as their own. Such concerns are heightened by the fact that many universities and schools transitioned from supervised in-person exams to unsupervised take-home exams during the COVID-19 pandemic, with many now continuing such models. Tools for detecting AI-generated written text have so far not proven very successful.

To better understand these issues, Scarfe and colleagues generated answers that were 100% written by the AI chatbot GPT-4 and submitted on behalf of 33 fake students to the examinations system of the School of Psychology and Clinical Language Sciences at the University of Reading. Exam graders were unaware of the study.

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Lately, there have been many headlines about scientific fraud and journal article retractions. If this trend continues, it represents a serious threat to public trust in science.

One way to tackle this problem—and ensure public trust in science remains high—may be to slow it down. We sometimes refer to this philosophy as “slow science.” Akin to the slow food movement, slow science prioritizes quality over speed and seeks to buck incentive structures that promote mass production.

Slow science may not represent an obvious way to improve science because we often equate science with progress, and slowing down progress does not sound very appealing. However, progress is not just about speed, but about basing important societal decisions on strong scientific foundations. And this takes time.

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Axions, hypothetical subatomic particles that were first proposed by theoretical physicists in the late 1970s, remain among the most promising dark matter candidates. Physics theories suggest that the interactions between these particles and regular matter are extremely weak, which makes them very difficult to detect using conventional experimental set-ups.

The HAYSTAC (Haloscope at Yale Sensitive to Axion Cold Dark Matter) experiment is a research collaboration between Yale, Berkeley and Johns Hopkins, aimed at detecting axions by searching for the small electromagnetic signals that they could produce within a strong magnetic field.

In a recent paper published in Physical Review Letters, the HAYSTAC collaboration has reported the results of the broadest search for axions performed to date, utilizing a technique known as quantum squeezing, which is designed to reduce quantum noise (i.e., random fluctuations that adversely affect their haloscope’s measurements).

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Vibrational sum-frequency generation (VSFG) is a nonlinear spectroscopic method widely used to investigate the molecular structure and dynamics of surface systems. However, in far-field observations, the spatial resolution of this method is constrained by the diffraction limit, which restricts its ability to resolve molecular details in inhomogeneous structures smaller than the wavelength of light.

To address this limitation, researchers, Atsunori Sakurai, Shota Takahashi, Tatsuto Mochizuki, and Toshiki Sugimoto, Institute for Molecular Science (IMS), NINS, developed a tip-enhanced VSFG (TE-SFG) spectroscopy system based on scanning tunneling microscopy (STM). Using this system, the team detected VSFG signals from molecules adsorbed on a gold substrate under ambient conditions.

The research is published in the journal Nano Letters.

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As demand for energy-intensive computing grows, researchers at the Department of Energy’s Oak Ridge National Laboratory have developed a new technique that lets scientists see—in unprecedented detail—how interfaces move in promising materials for computing and other applications. The method, now available to users at the Center for Nanophase Materials Sciences at ORNL, could help design dramatically more energy-efficient technologies.

The research is published in the journal Small Methods.

Data centers today consume as much energy as small cities, and that usage is skyrocketing. To counter the trend, scientists are studying such as ferroelectrics that could store and process information far more efficiently than silicon, which is traditionally used. But realizing the potential depends on understanding the processes occurring at dimensions thousands of times smaller than a —specifically, at the ferroelectric material’s , which are the boundaries between areas of the material that exhibit different magnetic or electric properties.

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The materials that make up all the structures and physical systems around us, including our own bodies, are not perfect—they contain flaws in the form of tiny cracks. When one of these cracks suddenly and rapidly spreads, it can be life-threatening, but the rich, intricate patterns formed by cracks can also be spectacular and intriguing.

Until now, physicists have struggled to provide a theoretical framework explaining why often branch out and deviate from their expected path, slowing down as a result.

Two recent studies from the Weizmann Institute of Science bring order to the disorderly propagation of cracks and show that, although each crack may seem unique, there are quantitative physical parameters that shape the propagation process and explain the formation of asymmetrical crack patterns.

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Researchers in Australia have found evidence that bacteria that live in the nose can make their way into the brain through nasal cavity nerves, setting off a series of events that could lead to Alzheimer’s disease. The work adds to the growing body of evidence that Alzheimer’s may be initially triggered through viral or bacterial infections.

Chlamydia pneumoniae is a common bacterium that, as its name suggests, is a major cause of pneumonia, as well as a range of other respiratory diseases. But worryingly, it’s also been detected in the brain on occasion, indicating it could cause more insidious issues.

For the new study, researchers at Griffith University and the Queensland University of Technology set out to investigate how C. pneumoniae might get into the brain, and whether it could cause damage once there. The team already had an inkling about how this nose-dwelling bug might make the trek.

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