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Lifted Kramers spin degeneracy (LKSD) has been among the central topics of condensed-matter physics since the dawn of the band theory of solids 1 , 2 . It underpins established practical applications as well as current frontier research, ranging from magnetic-memory technology 3 – 7 to topological quantum matter 8 – 14 . Traditionally, LKSD has been considered to originate from two possible internal symmetry-breaking mechanisms. The first refers to time-reversal symmetry breaking by magnetization of ferromagnets and tends to be strong because of the non-relativistic exchange origin 15 . The second applies to crystals with broken inversion symmetry and tends to be comparatively weaker, as it originates from the relativistic spin–orbit coupling (SOC) 16 – 19 . A recent theory work based on spin-symmetry classification has identified an unconventional magnetic phase, dubbed altermagnetic 20 , 21 , that allows for LKSD without net magnetization and inversion-symmetry breaking. Here we provide the confirmation using photoemission spectroscopy and ab initio calculations. We identify two distinct unconventional mechanisms of LKSD generated by the altermagnetic phase of centrosymmetric MnTe with vanishing net magnetization 20 – 23 . Our observation of the altermagnetic LKSD can have broad consequences in magnetism. It motivates exploration and exploitation of the unconventional nature of this magnetic phase in an extended family of materials, ranging from insulators and semiconductors to metals and superconductors 20 , 21 , that have been either identified recently or perceived for many decades as conventional antiferromagnets 21 , 24 , 25 . Using photoemission spectroscopy and ab initio calculations, evidence is given of two distinct unconventional mechanisms of lifted Kramers spin degeneracy generated by the altermagnetic phase of centrosymmetric MnTe with vanishing net magnetization.

It has been known for decades that the observed number of baryons in the local Universe falls about 30–40 per cent short 1 , 2 of the total number of baryons predicted 3 by Big Bang nucleosynthesis, as inferred 4 , 5 from density fluctuations of the cosmic microwave background and seen during the first 2–3 billion years of the Universe in the so-called ‘Lyman α forest’ 6 , 7 (a dense series of intervening H  i Lyman α absorption lines in the optical spectra of background quasars). A theoretical solution to this paradox locates the missing baryons in the hot and tenuous filamentary gas between galaxies, known as the warm–hot intergalactic medium. However, it is difficult to detect them there because the largest by far constituent of this gas—hydrogen—is mostly ionized and therefore almost invisible in far-ultraviolet spectra with typical signal-to-noise ratios 8 , 9 . Indeed, despite large observational efforts, only a few marginal claims of detection have been made so far 2 , 10 . Here we report observations of two absorbers of highly ionized oxygen (O  vii ) in the high-signal-to-noise-ratio X-ray spectrum of a quasar at a redshift higher than 0.4. These absorbers show no variability over a two-year timescale and have no associated cold absorption, making the assumption that they originate from the quasar’s intrinsic outflow or the host galaxy’s interstellar medium implausible. The O  vii systems lie in regions characterized by large (four times larger than average 11 ) galaxy overdensities and their number (down to the sensitivity threshold of our data) agrees well with numerical simulation predictions for the long-sought warm–hot intergalactic medium. We conclude that the missing baryons have been found. Observations of two absorbers of highly ionized oxygen in the X-ray spectrum of a quasar account for the missing baryons in the Universe.

In chronic lymphocytic leukemia (CLL), TP53 gene defects, due to deletion of the 17p13 locus and/or mutation(s) within the TP53 gene, are associated with resistance to chemoimmunotherapy and a particularly dismal clinical outcome. On these grounds, analysis of TP53 aberrations has been incorporated into routine clinical diagnostics to improve patient stratification and optimize therapeutic decisions. The predictive implications of TP53 aberrations have increasing significance in the era of novel targeted therapies, i.e., inhibitors of B-cell receptor (BcR) signaling and anti-apoptotic BCL2 family members, owing to their efficacy in patients with TP53 defects. In this report, the TP53 Network of the European Research Initiative on Chronic Lymphocytic Leukemia (ERIC) presents updated recommendations on the methodological approaches for TP53 mutation analysis. Moreover, it provides guidance to ensure that the analysis is performed in a timely manner for all patients requiring treatment and that the data is interpreted and reported in a consistent, standardized, and accurate way. Since next-generation sequencing technologies are gaining prominence within diagnostic laboratories, this report also offers advice and recommendations for the interpretation of TP53 mutation data generated by this methodology.

Although a growing body of literature demonstrates negative effects of internalized weight bias (IWB), the relationships between IWB and relevant social, psychological, and behavioral variables have not yet been evaluated systematically. The purpose of the present study was to create and assess a model of hypothesized risks and outcomes of IWB. In an online survey, 650 adult males and females completed self-report measures of IWB, self-esteem, weight-related stigma experiences, body-related shame, body satisfaction, societal influence on body image, appearance comparisons, binge eating, distress, and weight-related quality of life. The originally hypothesized model did not provide an adequate fit to the data. Iterative modifications were undertaken, and the resulting model, in which social factors were associated with IWB and body image-related constructs which were in turn associated with psychological and behavioral outcomes, provided excellent fit to the data (CFI > .99, SRMR = .02, and RMSEA = .03). Most model paths were similar for underweight or normal weight participants versus participants with overweight or obesity. This study represents an initial effort at constructing a comprehensive model of IWB that can be further refined in future research and used to help guide the development of related interventions.

In recent years, the Industry 4.0 concept has gained considerable attention from professionals, researchers and decision makers. For its part, the COVID-19 pandemic has highlighted the importance of managing the agri-food supply chain to ensure the food that the population needs. Industry 4.0 and its extensions can address the needs of the agri-food supply chain by bringing new features such as security, transparency and traceability in line with sustainable development goals. This study aims to systematically analyze the literature to address the challenges and barriers against the application of industry 4.0 and its related technologies in the management of an agri-food supply chain. Currently, despite the large number of publications, there is no clear agreement on what Industry 4.0 is, and even less its extensions. The next revolution that includes new technologies and improves several existing technologies brings additional conceptual and practical complexity. Consequently, in this work we first determine the main components of I 4.0 and their extensions by studying the literature, and then, in the second step, define the agri-food supply chain on which I 4.0 technologies are applied. Two well-known databases—Web of Science and Scopus—were chosen to extract data for the systematic review of the literature. For the final evaluation, we identified 24 of 100 reviewed publications. The results provide an exhaustive analysis of the different I 4.0 technologies and their extensions that are applied in regards to the agri-food supply chain. In addition, we find 15 challenges that are classified into five major themes in the agri-food supply chain: technical, operational, financial, social and infrastructure. The four most important challenges identified are technological architecture, security and privacy, big data management and IoT (internet)-based infrastructure. Only a few articles addressed sustainability, which reaffirms and demonstrates a considerable gap in terms of the sustainable agri-food supply chain, with waste management being the one that has attracted the most attention. This review provides a roadmap for academics and practitioners alike, showing the gaps and facilitating the identification of I 4.0 technologies that can help address the challenges facing the efficient management of an agri-food supply chain.

Masting, the intermittent and synchronous production of large seed crops, can have profound consequences for plant populations and the food webs that are built on their seeds. For centuries, people have recordedmast crops because of their importance in managing wildlife populations. In the past 30 years, we have begun to recognize the importance of masting in conserving and managing many other aspects of the environment: promoting the regeneration of forests following fire or other disturbance, conserving rare plants, conscientiously developing the use of edible seeds as non-timber forest products, coping with the consequences of extinctions on seed dispersal, reducing the impacts of plant invasions with biological control, suppressing zoonotic diseases and preventing depredation of endemic fauna. We summarize current instances and future possibilities of a broad set of applications of masting. By exploring in detail several case studies, we develop new perspectives on how solutions to pressing conservation and land management problems may benefit by better understanding the dynamics of seed production. A lesson common to these examples is thatmasting can be used to timemanagement, and often, to do this effectively, we need models that explicitly forecast masting and the dynamics of seed-eating animals into the near-term future. This article is part of the theme issue 'The ecology and evolution of synchronized seed production in plants'.

Mountains are vital water sources for humans and ecosystems, continuously replenishing lowland aquifers through surface runoff and mountain recharge. Quantifying these fluxes and their relative importance is essential for sustainable water resource management. However, our mechanistic understanding of the flow and transport processes determining the connection between the mountain block and the basin aquifer remains limited. Traditional conceptualizations assume groundwater circulation within the mountain block is predominantly shallow. This view neglects the role of deep groundwater flowpaths significantly contributing to the water, solute, and energy budgets. Overcoming these limitations requires a holistic characterization of the multiscale nature of groundwater flow along the mountain‐to‐valley continuum. As a proof‐of‐concept, we use a coupled groundwater flow and transport model to design a series of numerical experiments that explore the role of geology, topography, and weathering rates in groundwater circulation and their resulting resistivity patterns. Our results show that accumulating solutes near stagnation zones create contrasting electrical resistivity patterns that separate local, intermediate, and regional flow cells, presenting a target for magnetotelluric observations. To demonstrate the sensitivity of magnetotelluric data to features in our resistivity models, we use the MARE2DEM electromagnetic modeling code to perform forward and inverse simulations. This study highlights the potential of magnetotelluric surveys to image the resistivity structure resulting from multiscale groundwater circulation through relatively impervious crystalline basement rocks in mountainous terrains. This capability could change our understanding of the critical zone, offering a holistic perspective that includes deep groundwater circulation and its role in conveying solutes and energy. Plain Language Summary Mountains are vital water sources for humans and ecosystems, continuously replenishing lowland aquifers through surface runoff and mountain recharge. Quantifying these fluxes and their relative importance is essential for sustainable water resource management. Here, we present a novel approach to characterize the nested nature of groundwater flow along the mountain‐to‐valley continuum by combining flow and transport models and magnetotelluric (MT) geophysical surveys. We assess the approach’s potential by creating virtual realities that mimic realistic patterns of subsurface electrical resistivity. Then, using an inverse modeling approach, we test the ability of different MT survey configurations to reconstruct the resistivity fields. Our analysis shows that the accumulation of solutes in subsurface low‐velocity zones (i.e., stagnation zones) results in resistivity fields with enough contrast to image the local, intermediate, and regional groundwater flow cells. While this study is conceptual in nature, we aim to offer a framework for geophysical exploration that can characterize the critical zone without neglecting deep groundwater circulation and its role in conveying solutes and energy. Key Points We use a coupled flow and transport model to explore the role of deep groundwater circulation in mountain‐to‐valley systems Regional groundwater circulation conveys significant amounts of water, energy, and solutes through relatively impervious depths Magnetotelluric surveys can potentially map the resistivity patterns created by the solute concentration patterns within the mountain block

Sulfate-reducing bacteria (SRB) colonize the guts of ∼50% of humans. We used genome-wide transposon mutagenesis and insertion-site sequencing, RNA-Seq, plus mass spectrometry to characterize genetic and environmental factors that impact the niche of Desulfovibrio piger , the most common SRB in a surveyed cohort of healthy US adults. Gnotobiotic mice were colonized with an assemblage of sequenced human gut bacterial species with or without D. piger and fed diets with different levels and types of carbohydrates and sulfur sources. Diet was a major determinant of functions expressed by this artificial nine-member community and of the genes that impact D. piger fitness; the latter includes high- and low-affinity systems for using ammonia, a limiting resource for D. piger in mice consuming a polysaccharide-rich diet. Although genes involved in hydrogen consumption and sulfate reduction are necessary for its colonization, varying dietary-free sulfate levels did not significantly alter levels of D. piger , which can obtain sulfate from the host in part via cross-feeding mediated by Bacteroides -encoded sulfatases. Chondroitin sulfate, a common dietary supplement, increased D. piger and H ₂S levels without compromising gut barrier integrity. A chondroitin sulfate-supplemented diet together with D. piger impacted the assemblage’s substrate utilization preferences, allowing consumption of more reduced carbon sources and increasing the abundance of the H ₂-producing Actinobacterium, Collinsella aerofaciens . Our findings provide genetic and metabolic details of how this H ₂-consuming SRB shapes the responses of a microbiota to diet ingredients and a framework for examining how individuals lacking D. piger differ from those who harbor it.

Electrified transportation systems are emerging quickly worldwide, helping to diminish carbon gas emissions and paving the way for the reduction of global warming possessions. Battery remaining useful life (RUL) prediction is gaining attention in real world applications to tone down maintenance expenses and improve system reliability and efficiency. RUL forms the prominent component of fault analysis forecast and health management when the equipment operation life cycle is considered. The uprightness of RUL prediction is vital in providing the effectiveness of electric batteries and reducing the chance of battery illness. In assessing battery performance, the existing prediction approaches are unsatisfactory even though the battery operational parameters are well tabulated. In addition, battery management has an important contribution to several sustainable development goals, such as Clean and Affordable Energy (SDG 7), and Climate Action (SDG 13). The current work attempts to increase the prediction accuracy and robustness with selected machine learning algorithms. A Real battery life cycle data set from the Hawaii National Energy Institute (HNEI) is used to evaluate accuracy estimation using selected machine learning algorithms and is validated in Google Co-laboratory using Python. Evaluated error metrics such as Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), R-Squared, and execution time are computed for different L methods and relevant inferences are presented which highlight the potential of battery RUL prediction close to the most accurate values.

Noroviruses are a leading cause of acute gastroenteritis (AGE) among adults and children worldwide. NoroSurv is a global network for norovirus strain surveillance among children <5 years of age with AGE. Participants in 16 countries across 6 continents used standardized protocols for dual typing (genotype and polymerase type) and uploaded 1,325 dual-typed sequences to the NoroSurv web portal during 2016-2020. More than 50% of submitted sequences were GII.4 Sydney[P16] or GII.4 Sydney[P31] strains. Other common strains included GII.2[P16], GII.3[P12], GII.6[P7], and GI.3[P3] viruses. In total, 22 genotypes and 36 dual types, including GII.3 and GII.20 viruses with rarely reported polymerase types, were detected, reflecting high strain diversity. Surveillance data captured in NoroSurv enables the monitoring of trends in norovirus strains associated childhood AGE throughout the world on a near real-time basis.