The latest W boson mass measurement is consistent with the standard model; after talking with AI, people are less likely to believe in conspiracy theories | Technology Weekly

Compiled by Zhou Shuyi and Wang Xiang

Antibiotic resistance could kill 39 million people worldwide in the next 25 years

An international research team published a paper in The Lancet on September 16, saying that the number of deaths caused by antibiotic resistance will steadily increase in the coming decades, and the elderly face the greatest threat; more than 39 million people are expected to die from antibiotic resistance worldwide between 2025 and 2050. Researchers said that antibiotic resistance has become a major challenge to global public health and decisive action must be taken to address this threat.

Antibiotic resistance occurs when pathogenic bacteria change and no longer respond to the antibiotics that kill them, which can make infections more difficult to treat. In the latest study, researchers conducted a global survey of antibiotic resistance between 1990 and 2021, covering 520 million people in 204 countries and regions, evaluating 22 pathogens, 84 pathogen-drug combinations, and 11 infectious syndromes, and conducted the first global analysis of long-term trends in antibiotic resistance.

The results showed that between 1990 and 2021, more than 1 million people died each year worldwide directly from antibiotic resistance, with an average annual number of related deaths reaching 4.71 million. In 2021, an estimated 1.14 million people died directly from antibiotic resistance worldwide, and this number is expected to reach 1.91 million by 2050. The forecast also shows that by 2050, the number of deaths caused by antibiotic resistance among people aged 70 and above will more than double; the regions with the highest mortality rates due to antibiotic resistance for all age groups will be South Asia (including India, Pakistan, Bangladesh and other countries), Latin America and the Caribbean. The study estimates that a total of 92 million lives could be saved between 2025 and 2050 through improved health services and access to antibiotics.

Otia Gray, a researcher at the Karolinska Institute in Sweden who participated in the study, pointed out that antibiotic resistance poses the greatest threat to the elderly. Given that the global population is rapidly aging, the mortality rate caused by antibiotic resistance is expected to continue to rise over time. Several researchers called for immediate and decisive action to address the threat of antibiotic resistance, including improving access to drugs, controlling overuse of drugs, and strengthening infection prevention. (CCTV News, The Lancet)

Note: In this study, the term "antimicrobial resistance" (AMR) is mainly used to discuss bacterial resistance and is used interchangeably with "antibiotic resistance." However, AMR is a broader concept that includes resistance in various microorganisms such as bacteria, parasites, viruses and fungi.

What do the samples from the far side of the moon brought back by Chang'e-6 look like?

On September 17, Chinese scientists published the first research paper on the samples returned by Chang'e-6 in the National Science Review, revealing the physical, mineral and geochemical characteristics of the samples. The Chang'e-6 mission completed the feat of collecting samples from the far side of the moon for the first time, bringing back 1,935.3 grams of precious samples. Prior to this, all lunar samples obtained by humans came from the far side of the moon.

The Chang'e-6 sampling point is located at the edge of the Apollo crater inside the South Pole-Aitken Basin on the far side of the moon. The lunar crust in this area is extremely thin, and it is expected to reveal the original material of the early impact basin on the far side of the moon. According to reports, the Chang'e-6 lunar samples not only include basalts that record the history of volcanic activity at the sampling point, but also mix non-basaltic materials from other areas. Studies have shown that the Chang'e-6 lunar samples have a low density, indicating that their structure is relatively loose and their porosity is high. The particle size of the samples presents a bimodal distribution, suggesting that the samples may have experienced a mixture of different sources. Compared with the Chang'e-5 lunar samples, the plagioclase content in the Chang'e-6 lunar samples has increased significantly, while the olivine content has decreased significantly, indicating that the lunar soil in this area has been significantly affected by non-basaltic materials.

Typical images of samples returned by Chang'e-6. (a) Some rock debris particles larger than 1 mm selected from the samples scooped up by Chang'e-6. Backscatter images (BSE) of basalt debris with different structural characteristics (be), breccia, and cementite (fg). Microscope photos of typical basalt (i and j), cementite (k), light-colored rock debris (l), and glass (m and n). | National Astronomical Observatory of China, Chinese Academy of Sciences

The rock fragments collected by Chang'e-6 are mainly composed of basalt, breccia, cementite, light-colored rocks and glassy materials. Among them, basalt fragments account for 30% to 40% of the total, and breccia and cementite are composed of basalt fragments, glass beads, glass fragments, and a small amount of light-colored rock fragments such as plagioclase and syenite, further revealing the complexity of the source of the samples. Mineralogical analysis shows that the main phases of the Chang'e-6 lunar samples are plagioclase (32.6%), pyroxene (33.3%) and glass (29.4%). In addition, a small amount of orthopyroxene was detected in the samples, suggesting the presence of non-basaltic materials.

Further analysis shows that the Chang'e-6 lunar samples have high aluminum oxide and calcium oxide content, while the iron oxide content is relatively low, which is consistent with the characteristics of a mixture of lunar mare basalt and anorthite. In addition, the content of trace elements such as thorium, uranium and potassium in the samples is significantly lower than that of KREEP basalt, showing a huge difference from the lunar samples obtained by the Apollo mission and the Chang'e-5 mission.

The researchers said that these findings not only fill the historical gap in the study of the far side of the moon, provide direct evidence for our study of the early evolution of the moon, volcanic activity and impact history on the far side of the moon, but also open up new perspectives for understanding the geological differences between the far side and the front side of the moon.

After talking to AI, people are less likely to believe conspiracy theories

The earth is flat, lizard people control the world, there are 5G antennas in masks...conspiracy theories are endless and lingering. According to the definition of sociologist Goertzel, "conspiracy theories are interpretations of important events involving secret conspiracies and evil groups."

A study published in Science on September 13 showed that AI can help dispel conspiracy theories - conspiracy theorists are more likely to change their minds if fact-based arguments are made by AI chatbots rather than humans; communicating with AI can continuously reduce the impact of conspiracy theories.

Perhaps you have experienced that even with overwhelming evidence, attempts to refute conspiracy theorists are often a waste of effort. Schopenhauer was well aware of this, writing that argument is an "art of loudly asserting that one is right, whether justified or not." Human persuasion is ineffective, so what about AI? The research team recruited 2,190 participants who believed in at least one conspiracy theory, assessed their belief in the conspiracy theory, and asked them to communicate with a chatbot based on a large language model. The participants shared their conspiracy theories and the evidence supporting their views with the AI. The AI ​​refuted them with specific factual evidence. After three rounds of dialogue, the researchers assessed the participants' level of belief again. The results showed that communicating with AI reduced people's belief in conspiracy theories by an average of 20%, an effect that lasted for up to 2 months and seemed to work for all kinds of conspiracy theories.

Participants (yellow dialog box) first subjectively rated their degree of belief in the conspiracy theory, and then rated it again after three rounds of dialogue with the AI ​​(GPT-4 Turbo, purple dialog box).

Van Prooijen, a behavioral scientist who was not involved in the study, speculated that AI "rumor-busting" is effective in part because it is always "very polite," while conversations between people in similar situations can easily become "intense and rude." In addition, some people may worry that being persuaded in front of friends and family will "lose face," but there is no such concern in front of AI.

Factual evidence is crucial, and repeated experiments have shown that if AI talks in general terms and does not present specific evidence based on facts, it will not be persuasive. However, false information researcher Federico Germani said that the training corpus of large language models comes from real conversations, so they can "master" subtle rhetorical strategies to make arguments more convincing. "The author may have underestimated the ability of AI to manipulate between the lines."

New W boson mass measurement agrees with Standard Model

At a seminar held at the European Organization for Nuclear Research (CERN) on September 17, the Compact Muon Solenoid (CMS) collaboration reported that it had made the most accurate measurement of the mass of the W boson at the Large Hadron Collider (LHC) to date, with a result of 80360.2±9.9 MeV. This value is highly consistent with the standard model of particle physics.

A candidate CMS collision event, where a W boson decays into a muon (red line) and a neutrino (pink arrow) that escapes detection.

The W boson is an elementary particle that, together with the Z boson, mediates the weak force. This force governs the beta decay of atomic nuclei, as well as nuclear fusion reactions in the Sun. The W boson was discovered at CERN in 1983, but even today, 40 years later, its mass remains extremely challenging to measure. The W boson mass is one of the key predictions of the fundamental parameters of the Standard Model and is therefore an extremely important test of the model itself.

The W boson created at the heart of the CMS detector decays almost instantly into a muon and a neutrino. The muon is detected by the CMS detector, but the elusive neutrino escapes and cannot be detected. If both the muon and the neutrino can be detected, the mass of the W boson can be measured directly from the particle's energy and direction of flight, just as the Higgs boson was measured. To meet this challenge, the researchers took advantage of the famous equation that relates mass to energy, E=mc^2: the greater the mass, the greater the energy and momentum of the muon. Therefore, by studying the momentum of the muon, the research team inferred the mass of the W boson with extremely high precision.

On April 7, 2022, scientists from the Collider Detector (CDF) collaboration at the Fermi National Accelerator Laboratory in the United States reported the results of the measurement of the mass of the W boson with an accuracy of 0.01%. The measurement results deviated from the expected results of the Standard Model by 7 standard deviations, significantly deviating from the predictions of the Standard Model and the average of other measurements at CERN. The highly anticipated CMS results are not only as accurate as the CDF results, but also strongly support the values ​​of the Standard Model, further enhancing the credibility of the current model. (Science and Technology Daily)

Women's brains may shrink, become better connected during pregnancy

A study published in Nature Neuroscience on September 16 found that areas of the female brain may shrink during pregnancy, but their connectivity becomes better. The findings, based on brain scans of a single mother, are one of the first complete maps of neuroanatomical changes in humans before, during and after pregnancy.

Nearly 85% of women worldwide will become pregnant at least once in their lifetime, with 140 million women becoming pregnant each year. It is well known that during pregnancy, the mother's body undergoes dramatic physiological changes to support the growth and development of the fetus. However, we still know little about how the brain changes during this period.

The researchers tracked brain changes in a 38-year-old healthy woman from pre-pregnancy to postpartum. They conducted a total of 26 magnetic resonance imaging (MRI) scans and venipuncture blood assessments, with sampling periods ranging from 3 weeks before pregnancy (4 scans), 3 trimesters of pregnancy (15 scans), to 2 years after delivery (7 scans). The scan results were compared with brain changes in 8 control individuals.

The results showed that as the gestational weeks increased and the level of sex hormone secretion increased sharply, the gray matter volume (GMV) and cortical thickness (CT) of the woman's brain generally decreased, and few brain areas were unaffected. However, the integrity of white matter microstructure, ventricular volume, and cerebrospinal fluid increased. In other words, brain areas shrink during pregnancy, but connectivity becomes better. The study believes that these changes are related to increased levels of estradiol and progesterone. The reduction in gray matter volume and cortical thickness persisted until 2 years after delivery, while most other changes returned to prenatal levels about 2 months after delivery.

Although further research is needed to investigate the longer-term effects of pregnancy on the brain and to verify the consistency of these brain changes in the wider population, the new study advances our understanding of pregnancy-related neural changes. The authors believe that these results also have potential implications for perinatal mental health (such as neural effects related to preeclampsia or edema), parenting behaviors, and brain aging.

Scientists have detected the longest black hole jet, equivalent to 140 Milky Way galaxies connected together

When a supermassive black hole devours matter, it ejects a long, hot stream of matter at a relativistic speed (some even close to the speed of light), forming a black hole jet known as a "cosmic pillar of fire." An international astronomical research team recently reported that it had detected two high-speed streams of matter ejected from a supermassive black hole, with a length equivalent to 140 Milky Way galaxies connected end to end, making it the longest black hole jet known to date. The relevant paper was published in Nature on September 18.

Artist's conception of the Porphyrion

The researchers analyzed data from the LOFAR low-frequency array (a large radio telescope array mainly located in the Netherlands) and discovered the black hole jet, which they named "Porphyrion" after the giant in Greek mythology. The black hole is located in the center of a galaxy 7.5 billion light-years away from Earth. The two jets ejected in opposite directions have a total length of about 7 million parsecs, or about 23 million light-years. The longest span of black hole jets detected previously did not exceed 5 million parsecs.

To produce such a huge jet system, the black hole must swallow the equivalent of one sun's matter as "supply" every year for 1 billion years, and the jet cannot be significantly disturbed during its propagation. Since the universe is always expanding, the universe was relatively small and dense when "Porphyrion" was born, and the probability of the jet encountering a "traffic accident" should be high. Researchers are currently unclear why it can extend for so long and remain stable.

The researchers pointed out that the observation range of the low-frequency radio telescope array only covers 15% of the sky, which means that there may be more giant black hole jets to be discovered, and the role of such jets in the evolution of the universe may be more important than previously thought.

Starlink satellites make radio telescopes "blind"

Under the cover of technology, it may be difficult for us to look up at the stars. A new study found that SpaceX's Starlink satellites accidentally leak electromagnetic radiation, which hinders the observation of some ground-based radio telescopes and may eventually make them "blind." The relevant paper was published in Astronomy & Astrophysics on September 18.

The research team used the LOFAR low-frequency array for observations and reported that SpaceX's second-generation satellites, which began launching last year, leaked 32 times more electromagnetic radiation than the first-generation satellites, which may exceed international regulations. The frequency of the radio frequency leakage is far below the frequency band that Starlink satellites use to provide Internet services to customers and communicate with ground control personnel, so the study believes that this is unintentional.

The researchers said that compared with the dimmest astronomical light source observed by LOFAR, the radiation leaked by the Starlink satellites is 10 million times brighter. For astronomers, observing when there are satellites in the field of view is "like trying to see the dimmest star next to the full moon with the naked eye."

The interference will get worse. There are already more than 6,000 Starlink satellites in orbit, and SpaceX plans to launch tens of thousands of satellites. By then, a large-field telescope like LOFAR may not be able to find a "clean" sky.

SpaceX is revolutionizing access to space with low-cost, reusable launchers. The company, led by Elon Musk, has successfully launched a space internet business, and Starlink currently has more than 3 million users worldwide. Other companies are also eager to try. Researchers estimate that by the end of the 2020s, there may be nearly 100,000 satellites in orbit.

Clarivate Analytics announces 2024 Citation Laureates

On September 19, Clarivate Analytics announced the list of 2024 Citation Laureates. 22 outstanding researchers from 6 countries were selected, including 11 from the United States, 6 from the United Kingdom, 2 from Switzerland, and 1 each from Germany, Israel and Japan. Each winner has published groundbreaking research papers in their respective fields, which have a very high citation rate and have a wide social impact. The fields involve clean energy, nanotechnology, protein three-dimensional structure, the economic impact of corruption, heart disease, molecular dynamics, quantum computing, genomic imprinting (also known as genetic imprinting) and condensed matter physics. The Citation Laureate is selected by a team of experts from the Clarivate Analytics Institute for Scientific Information (ISI) and is known as the "Nobel Prize weathervane". Currently, 75 Citation Laureates have won the Nobel Prize.

Here is the full list of winners:

Physiology or medicine

Jonathan C. Cohen

C. Vincent Prothro Distinguished Chair in Human Nutrition Research, University of Texas Southwestern Medical Center

Helen H. Hobbs

Howard Hughes Medical Institute Investigator; Professor of Internal Medicine and Molecular Genetics, University of Texas Southwestern Medical Center

Reason for the award: Research on the genetics of lipid metabolism has led to the development of new drugs for the treatment of cardiovascular diseases

Ann M. Graybiel

Professor of Brain and Cognitive Sciences at MIT and researcher at McGovern Institute for Brain Research

Hikosaka Okihide

Laboratory of Sensory-Motor Research, National Eye Institute, NIH, Distinguished Investigator, NIH

Wolfram Schultz

Professor of Neuroscience and Professorial Research Fellow, Department of Physiology, Development and Neuroscience, Churchill College, University of Cambridge, UK; Visiting Associate Research Fellow, Division of Humanities and Social Sciences, California Institute of Technology, USA

Citation: For physiological studies of the basal ganglia, which play a central role in motor control and behavior, including learning.

Davor Solter

Honorary Director and Researcher, Department of Developmental Biology, Max Planck Institute of Immunobiology and Epigenetics, Germany

Azim Surani

Professor at the Cambridge Stem Cell Institute, University of Cambridge, UK; Director of Reproduction and Epigenetics Research at the Gurdon Institute, University of Cambridge

Reason for the award: For the discovery of genomic imprinting, which has advanced our understanding of epigenetics and mammalian development

Field of Physics

Rafi Bistritzer

Professor, School of Physics and Astronomy, Tel Aviv University, Israel

Pablo Jarillo-Herrero

Cecil and Ida Green Professor of Physics, Department of Physics, Massachusetts Institute of Technology

Allan H. MacDonald

Sid W. Richardson Foundation Regents Professor, Department of Physics, University of Texas at Austin

Reason for the award: For groundbreaking theoretical and experimental contributions to the physical study of magic-angle twisted bilayer graphene and related moiré quantum devices

David Deutsch
Honorary Research Fellow of Wolfson College, University of Oxford, UK, Visiting Professor of Physics at the Clarendon Laboratory Quantum Computing Centre

Peter W. Shor

Professor of Applied Mathematics, Massachusetts Institute of Technology

Reason for winning: Revolutionary contributions to quantum algorithms and computing

Christoph Gerber

Professor, Department of Physics, University of Basel, Switzerland, Swiss Nanoscience Institute (SNI)

Reason for winning: The invention and application of atomic force microscopy

Chemical field

David Baker
Professor of Biochemistry, University of Washington School of Medicine, Howard Hughes Medical Institute Investigator, and Director of the Institute for Protein Design

John M. Jumper

Director of Google DeepMind

Demis Hassabis

Founder and CEO of Google DeepMind

Reason for winning: Contributions to the prediction and design of protein three-dimensional structure and function

Kazunari Domen Distinguished Professor of the Institute of Water Reclamation, Shinshu University, Japan, Professor of the University of Tokyo

Reason for winning: Basic research on photocatalysts for water decomposition and the construction of solar hydrogen production systems

Roberto Car
Professor of Chemistry, Princeton University, Professor of Princeton Materials Research Institute, Director of Solution and Interface Chemistry Laboratory, Center for Computational Chemical Sciences

Michele Parrinello

Professor Emeritus of Computer Science, Faculty of Information, University of Ticino, Switzerland; Professor Emeritus of Chemistry and Applied Biosciences, ETH Zurich, Switzerland

Reason for the award: For his discovery of the Car-Parrinello method for ab initio molecular dynamics simulations, which has made revolutionary contributions to the field of computational chemistry.

Economics

Janet Currie

Henry Putnam Professor of Economics and Public Affairs, Princeton School of Public and International Affairs, Princeton University, USA

For groundbreaking economic analysis of child development

Partha Dasgupta

Frank Ramsey Professor Emeritus of Economics, Department of Economics, University of Cambridge, UK

Reason for winning: Integrating nature and natural resources into human economic research

Paolo Mauro

Director of Economic and Market Research, IFC

Reason for winning: Empirical research on the impact of corruption on investment and economic growth

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