Showing papers by "ETH Zurich published in 2021"

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

SwinIR: Image Restoration Using Swin Transformer

Abstract: Image restoration is a long-standing low-level vision problem that aims to restore high-quality images from low-quality images (e.g., downscaled, noisy and compressed images). While state-of-the-art image restoration methods are based on convolutional neural networks, few attempts have been made with Transformers which show impressive performance on high-level vision tasks. In this paper, we propose a strong baseline model SwinIR for image restoration based on the Swin Transformer. SwinIR consists of three parts: shallow feature extraction, deep feature extraction and high-quality image reconstruction. In particular, the deep feature extraction module is composed of several residual Swin Transformer blocks (RSTB), each of which has several Swin Transformer layers together with a residual connection. We conduct experiments on three representative tasks: image super-resolution (including classical, lightweight and real-world image super-resolution), image denoising (including grayscale and color image denoising) and JPEG compression artifact reduction. Experimental results demonstrate that SwinIR outperforms state-of-the-art methods on different tasks by $\textbf{up to 0.14$\sim$0.45dB}$, while the total number of parameters can be reduced by $\textbf{up to 67%}$.

Circuit quantum electrodynamics

Abstract: Quantum-mechanical effects at the macroscopic level were first explored in Josephson-junction-based superconducting circuits in the 1980s. In recent decades, the emergence of quantum information science has intensified research toward using these circuits as qubits in quantum information processors. The realization that superconducting qubits can be made to strongly and controllably interact with microwave photons, the quantized electromagnetic fields stored in superconducting circuits, led to the creation of the field of circuit quantum electrodynamics (QED), the topic of this review. While atomic cavity QED inspired many of the early developments of circuit QED, the latter has now become an independent and thriving field of research in its own right. Circuit QED allows the study and control of light-matter interaction at the quantum level in unprecedented detail. It also plays an essential role in all current approaches to gate-based digital quantum information processing with superconducting circuits. In addition, circuit QED provides a framework for the study of hybrid quantum systems, such as quantum dots, magnons, Rydberg atoms, surface acoustic waves, and mechanical systems interacting with microwave photons. Here the coherent coupling of superconducting qubits to microwave photons in high-quality oscillators focusing on the physics of the Jaynes-Cummings model, its dispersive limit, and the different regimes of light-matter interaction in this system are reviewed. Also discussed is coupling of superconducting circuits to their environment, which is necessary for coherent control and measurements in circuit QED, but which also invariably leads to decoherence. Dispersive qubit readout, a central ingredient in almost all circuit QED experiments, is also described. Following an introduction to these fundamental concepts that are at the heart of circuit QED, important use cases of these ideas in quantum information processing and in quantum optics are discussed. Circuit QED realizes a broad set of concepts that open up new possibilities for the study of quantum physics at the macro scale with superconducting circuits and applications to quantum information science in the widest sense.

Sustainable data analysis with Snakemake.

Abstract: Data analysis often entails a multitude of heterogeneous steps, from the application of various command line tools to the usage of scripting languages like R or Python for the generation of plots and tables. It is widely recognized that data analyses should ideally be conducted in a reproducible way. Reproducibility enables technical validation and regeneration of results on the original or even new data. However, reproducibility alone is by no means sufficient to deliver an analysis that is of lasting impact (i.e., sustainable) for the field, or even just one research group. We postulate that it is equally important to ensure adaptability and transparency. The former describes the ability to modify the analysis to answer extended or slightly different research questions. The latter describes the ability to understand the analysis in order to judge whether it is not only technically, but methodologically valid. Here, we analyze the properties needed for a data analysis to become reproducible, adaptable, and transparent. We show how the popular workflow management system Snakemake can be used to guarantee this, and how it enables an ergonomic, combined, unified representation of all steps involved in data analysis, ranging from raw data processing, to quality control and fine-grained, interactive exploration and plotting of final results.

Extracellular vesicles as a next-generation drug delivery platform.

Abstract: Extracellular-vesicle-based cell-to-cell communication is conserved across all kingdoms of life. There is compelling evidence that extracellular vesicles are involved in major (patho)physiological processes, including cellular homoeostasis, infection propagation, cancer development and cardiovascular diseases. Various studies suggest that extracellular vesicles have several advantages over conventional synthetic carriers, opening new frontiers for modern drug delivery. Despite extensive research, clinical translation of extracellular-vesicle-based therapies remains challenging. Here, we discuss the uniqueness of extracellular vesicles along with critical design and development steps required to utilize their full potential as drug carriers, including loading methods, in-depth characterization and large-scale manufacturing. We compare the prospects of extracellular vesicles with those of the well established liposomes and provide guidelines to direct the process of developing vesicle-based drug delivery systems. In this Review the authors discuss the biological role of extracellular vesicles and how they can be applied as drug carriers, focusing on the current state of their manufacturing and existing challenges.

State of the Art and Prospects for Halide Perovskite Nanocrystals.

Abstract: Metal-halide perovskites have rapidly emerged as one of the most promising materials of the 21st century, with many exciting properties and great potential for a broad range of applications, from photovoltaics to optoelectronics and photocatalysis. The ease with which metal-halide perovskites can be synthesized in the form of brightly luminescent colloidal nanocrystals, as well as their tunable and intriguing optical and electronic properties, has attracted researchers from different disciplines of science and technology. In the last few years, there has been a significant progress in the shape-controlled synthesis of perovskite nanocrystals and understanding of their properties and applications. In this comprehensive review, researchers having expertise in different fields (chemistry, physics, and device engineering) of metal-halide perovskite nanocrystals have joined together to provide a state of the art overview and future prospects of metal-halide perovskite nanocrystal research.

Application of subject-specific adaptive mechanical loading for bone healing in a mouse tail vertebral defect.

Abstract: Methods to repair bone defects arising from trauma, resection, or disease, continue to be sought after. Cyclic mechanical loading is well established to influence bone (re)modelling activity, in which bone formation and resorption are correlated to micro-scale strain. Based on this, the application of mechanical stimulation across a bone defect could improve healing. However, if ignoring the mechanical integrity of defected bone, loading regimes have a high potential to either cause damage or be ineffective. This study explores real-time finite element (rtFE) methods that use three-dimensional structural analyses from micro-computed tomography images to estimate effective peak cyclic loads in a subject-specific and time-dependent manner. It demonstrates the concept in a cyclically loaded mouse caudal vertebral bone defect model. Using rtFE analysis combined with adaptive mechanical loading, mouse bone healing was significantly improved over non-loaded controls, with no incidence of vertebral fractures. Such rtFE-driven adaptive loading regimes demonstrated here could be relevant to clinical bone defect healing scenarios, where mechanical loading can become patient-specific and more efficacious. This is achieved by accounting for initial bone defect conditions and spatio-temporal healing, both being factors that are always unique to the patient.

Accelerated global glacier mass loss in the early twenty-first century

Abstract: Glaciers distinct from the Greenland and Antarctic ice sheets are shrinking rapidly, altering regional hydrology1, raising global sea level2 and elevating natural hazards3. Yet, owing to the scarcity of constrained mass loss observations, glacier evolution during the satellite era is known only partially, as a geographic and temporal patchwork4,5. Here we reveal the accelerated, albeit contrasting, patterns of glacier mass loss during the early twenty-first century. Using largely untapped satellite archives, we chart surface elevation changes at a high spatiotemporal resolution over all of Earth’s glaciers. We extensively validate our estimates against independent, high-precision measurements and present a globally complete and consistent estimate of glacier mass change. We show that during 2000–2019, glaciers lost a mass of 267 ± 16 gigatonnes per year, equivalent to 21 ± 3 per cent of the observed sea-level rise6. We identify a mass loss acceleration of 48 ± 16 gigatonnes per year per decade, explaining 6 to 19 per cent of the observed acceleration of sea-level rise. Particularly, thinning rates of glaciers outside ice sheet peripheries doubled over the past two decades. Glaciers currently lose more mass, and at similar or larger acceleration rates, than the Greenland or Antarctic ice sheets taken separately7–9. By uncovering the patterns of mass change in many regions, we find contrasting glacier fluctuations that agree with the decadal variability in precipitation and temperature. These include a North Atlantic anomaly of decelerated mass loss, a strongly accelerated loss from northwestern American glaciers, and the apparent end of the Karakoram anomaly of mass gain10. We anticipate our highly resolved estimates to advance the understanding of drivers that govern the distribution of glacier change, and to extend our capabilities of predicting these changes at all scales. Predictions robustly benchmarked against observations are critically needed to design adaptive policies for the local- and regional-scale management of water resources and cryospheric risks, as well as for the global-scale mitigation of sea-level rise. Analysis of satellite stereo imagery uncovers two decades of mass change for all of Earth’s glaciers, revealing accelerated glacier shrinkage and regionally contrasting changes consistent with decadal climate variability.

Multi-Task Learning for Dense Prediction Tasks: A Survey.

Abstract: With the advent of deep learning, many dense prediction tasks, i.e. tasks that produce pixel-level predictions, have seen significant performance improvements. The typical approach is to learn these tasks in isolation, that is, a separate neural network is trained for each individual task. Yet, recent multi-task learning (MTL) techniques have shown promising results w.r.t. performance, computations and/or memory footprint, by jointly tackling multiple tasks through a learned shared representation. In this survey, we provide a well-rounded view on state-of-the-art deep learning approaches for MTL in computer vision, explicitly emphasizing on dense prediction tasks. Our contributions concern the following. First, we consider MTL from a network architecture point-of-view. We include an extensive overview and discuss the advantages/disadvantages of recent popular MTL models. Second, we examine various optimization methods to tackle the joint learning of multiple tasks. We summarize the qualitative elements of these works and explore their commonalities and differences. Finally, we provide an extensive experimental evaluation across a variety of dense prediction benchmarks to examine the pros and cons of the different methods, including both architectural and optimization based strategies.

Recent advances in carbon capture storage and utilisation technologies: a review

Abstract: Human activities have led to a massive increase in $$\hbox {CO}_{2}$$ emissions as a primary greenhouse gas that is contributing to climate change with higher than $$1\,^{\circ }\hbox {C}$$ global warming than that of the pre-industrial level. We evaluate the three major technologies that are utilised for carbon capture: pre-combustion, post-combustion and oxyfuel combustion. We review the advances in carbon capture, storage and utilisation. We compare carbon uptake technologies with techniques of carbon dioxide separation. Monoethanolamine is the most common carbon sorbent; yet it requires a high regeneration energy of 3.5 GJ per tonne of $$\hbox {CO}_{2}$$ . Alternatively, recent advances in sorbent technology reveal novel solvents such as a modulated amine blend with lower regeneration energy of 2.17 GJ per tonne of $$\hbox {CO}_{2}$$ . Graphene-type materials show $$\hbox {CO}_{2}$$ adsorption capacity of 0.07 mol/g, which is 10 times higher than that of specific types of activated carbon, zeolites and metal–organic frameworks. $$\hbox {CO}_{2}$$ geosequestration provides an efficient and long-term strategy for storing the captured $$\hbox {CO}_{2}$$ in geological formations with a global storage capacity factor at a Gt-scale within operational timescales. Regarding the utilisation route, currently, the gross global utilisation of $$\hbox {CO}_{2}$$ is lower than 200 million tonnes per year, which is roughly negligible compared with the extent of global anthropogenic $$\hbox {CO}_{2}$$ emissions, which is higher than 32,000 million tonnes per year. Herein, we review different $$\hbox {CO}_{2}$$ utilisation methods such as direct routes, i.e. beverage carbonation, food packaging and oil recovery, chemical industries and fuels. Moreover, we investigated additional $$\hbox {CO}_{2}$$ utilisation for base-load power generation, seasonal energy storage, and district cooling and cryogenic direct air $$\hbox {CO}_{2}$$ capture using geothermal energy. Through bibliometric mapping, we identified the research gap in the literature within this field which requires future investigations, for instance, designing new and stable ionic liquids, pore size and selectivity of metal–organic frameworks and enhancing the adsorption capacity of novel solvents. Moreover, areas such as techno-economic evaluation of novel solvents, process design and dynamic simulation require further effort as well as research and development before pilot- and commercial-scale trials.

Spread of a SARS-CoV-2 variant through Europe in the summer of 2020.

Abstract: Following its emergence in late 2019, the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)1,2 has been tracked via phylogenetic analysis of viral genome sequences in unprecedented detail3–5. While the virus spread globally in early 2020 before borders closed, intercontinental travel has since been greatly reduced. However, within Europe travel resumed in the summer of 2020. Here we report on a novel SARS-CoV-2 variant, 20E (EU1), that emerged in Spain in early summer, and subsequently spread across Europe. We find no evidence of increased transmissibility, but instead demonstrate how rising incidence in Spain, resumption of travel, and lack of effective screening and containment may explain the variant’s success. Despite travel restrictions, we estimate 20E (EU1) was introduced hundreds of times to European countries by summertime travelers, likely undermining local efforts to keep SARS-CoV-2 cases low. Our results demonstrate how a variant can rapidly become dominant even in absence of a substantial transmission advantage in favorable epidemiological settings. Genomic surveillance is critical to understanding how travel can impact SARS-CoV-2 transmission, and thus for informing future containment strategies as travel resumes.

Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices

Abstract: Mass spectrometry-based metabolomics approaches can enable detection and quantification of many thousands of metabolite features simultaneously. However, compound identification and reliable quantification are greatly complicated owing to the chemical complexity and dynamic range of the metabolome. Simultaneous quantification of many metabolites within complex mixtures can additionally be complicated by ion suppression, fragmentation and the presence of isomers. Here we present guidelines covering sample preparation, replication and randomization, quantification, recovery and recombination, ion suppression and peak misidentification, as a means to enable high-quality reporting of liquid chromatography- and gas chromatography-mass spectrometry-based metabolomics-derived data.

Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO2

Abstract: Atmospheric carbon dioxide concentration ([CO2 ]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO2 ] increase and thus climate change. However, ecosystem CO2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO2 ]-driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO2 ] (iCO2 ) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industrial times. Established theory, supported by experiments, indicates that iCO2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO2 responses are high in comparison to experiments and predictions from theory. Plant mortality and soil carbon iCO2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.

Global terrestrial water storage and drought severity under climate change

Abstract: Terrestrial water storage (TWS) modulates the hydrological cycle and is a key determinant of water availability and an indicator of drought. While historical TWS variations have been increasingly studied, future changes in TWS and the linkages to droughts remain unexamined. Here, using ensemble hydrological simulations, we show that climate change could reduce TWS in many regions, especially those in the Southern Hemisphere. Strong inter-ensemble agreement indicates high confidence in the projected changes that are driven primarily by climate forcing rather than land and water management activities. Declines in TWS translate to increases in future droughts. By the late twenty-first century, the global land area and population in extreme-to-exceptional TWS drought could more than double, each increasing from 3% during 1976–2005 to 7% and 8%, respectively. Our findings highlight the importance of climate change mitigation to avoid adverse TWS impacts and increased droughts, and the need for improved water resource management and adaptation.

A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition

Abstract: Wearable devices that monitor muscle activity based on surface electromyography could be of use in the development of hand gesture recognition applications. Such devices typically use machine-learning models, either locally or externally, for gesture classification. However, most devices with local processing cannot offer training and updating of the machine-learning model during use, resulting in suboptimal performance under practical conditions. Here we report a wearable surface electromyography biosensing system that is based on a screen-printed, conformal electrode array and has in-sensor adaptive learning capabilities. Our system implements a neuro-inspired hyperdimensional computing algorithm locally for real-time gesture classification, as well as model training and updating under variable conditions such as different arm positions and sensor replacement. The system can classify 13 hand gestures with 97.12% accuracy for two participants when training with a single trial per gesture. A high accuracy (92.87%) is preserved on expanding to 21 gestures, and accuracy is recovered by 9.5% by implementing model updates in response to varying conditions, without additional computation on an external device. A surface electromyography biosensing system that is based on a screen-printed, conformal electrode array and has in-sensor adaptive learning capabilities can classify human gestures in real time and with high accuracy.

Community-led, integrated, reproducible multi-omics with anvi'o.

Abstract: Big data abound in microbiology, but the workflows designed to enable researchers to interpret data can constrain the biological questions that can be asked. Five years after anvi’o was first published, this community-led multi-omics platform is maturing into an open software ecosystem that reduces constraints in ‘omics data analyses.

Magnetically Driven Micro and Nanorobots

Abstract: Manipulation and navigation of micro and nanoswimmers in different fluid environments can be achieved by chemicals, external fields, or even motile cells Many researchers have selected magnetic fields as the active external actuation source based on the advantageous features of this actuation strategy such as remote and spatiotemporal control, fuel-free, high degree of reconfigurability, programmability, recyclability, and versatility This review introduces fundamental concepts and advantages of magnetic micro/nanorobots (termed here as "MagRobots") as well as basic knowledge of magnetic fields and magnetic materials, setups for magnetic manipulation, magnetic field configurations, and symmetry-breaking strategies for effective movement These concepts are discussed to describe the interactions between micro/nanorobots and magnetic fields Actuation mechanisms of flagella-inspired MagRobots (ie, corkscrew-like motion and traveling-wave locomotion/ciliary stroke motion) and surface walkers (ie, surface-assisted motion), applications of magnetic fields in other propulsion approaches, and magnetic stimulation of micro/nanorobots beyond motion are provided followed by fabrication techniques for (quasi-)spherical, helical, flexible, wire-like, and biohybrid MagRobots Applications of MagRobots in targeted drug/gene delivery, cell manipulation, minimally invasive surgery, biopsy, biofilm disruption/eradication, imaging-guided delivery/therapy/surgery, pollution removal for environmental remediation, and (bio)sensing are also reviewed Finally, current challenges and future perspectives for the development of magnetically powered miniaturized motors are discussed

Sudden Stratospheric Warmings

Abstract: Sudden stratospheric warmings (SSWs) are impressive fluid dynamical events in which large and rapid temperature increases in the winter polar stratosphere (⁓10‐50km) are associated with a complete reversal of the climatological wintertime westerly winds. SSWs are caused by the breaking of planetary‐scale waves that propagate upwards from the troposphere. During an SSW, the polar vortex breaks down, accompanied by rapid descent and warming of air in polar latitudes, mirrored by ascent and cooling above the warming. The rapid warming and descent of the polar air column affects tropospheric weather, shifting jet streams, storm tracks, and the Northern Annular Mode, making cold air outbreaks over North America and Eurasia more likely. SSWs affect the atmosphere above the stratosphere, producing widespread effects on atmospheric chemistry, temperatures, winds, neutral (non‐ionized) particles and electron densities, and electric fields. These effects span both hemispheres. Given their crucial role in the whole atmosphere, SSWs are also seen as a key process to analyze in climate change studies and subseasonal to seasonal prediction. This work reviews the current knowledge on the most important aspects of SSWs, from the historical background to dynamical processes, modelling, chemistry, and impact on other atmospheric layers.

A stable low-temperature H2-production catalyst by crowding Pt on α-MoC.

Abstract: The water–gas shift (WGS) reaction is an industrially important source of pure hydrogen (H2) at the expense of carbon monoxide and water1,2. This reaction is of interest for fuel-cell applications, but requires WGS catalysts that are durable and highly active at low temperatures3. Here we demonstrate that the structure (Pt1–Ptn)/α-MoC, where isolated platinum atoms (Pt1) and subnanometre platinum clusters (Ptn) are stabilized on α-molybdenum carbide (α-MoC), catalyses the WGS reaction even at 313 kelvin, with a hydrogen-production pathway involving direct carbon monoxide dissociation identified. We find that it is critical to crowd the α-MoC surface with Pt1 and Ptn species, which prevents oxidation of the support that would cause catalyst deactivation, as seen with gold/α-MoC (ref. 4), and gives our system high stability and a high metal-normalized turnover number of 4,300,000 moles of hydrogen per mole of platinum. We anticipate that the strategy demonstrated here will be pivotal for the design of highly active and stable catalysts for effective activation of important molecules such as water and carbon monoxide for energy production. A stable, low-temperature water–gas shift catalyst is achieved by crowding platinum atoms and clusters on α-molybdenum carbide; the crowding protects the support from oxidation that would cause catalyst deactivation.

International Geomagnetic Reference Field: the thirteenth generation

Abstract: In December 2019, the International Association of Geomagnetism and Aeronomy (IAGA) Division V Working Group (V-MOD) adopted the thirteenth generation of the International Geomagnetic Reference Field (IGRF). This IGRF updates the previous generation with a definitive main field model for epoch 2015.0, a main field model for epoch 2020.0, and a predictive linear secular variation for 2020.0 to 2025.0. This letter provides the equations defining the IGRF, the spherical harmonic coefficients for this thirteenth generation model, maps of magnetic declination, inclination and total field intensity for the epoch 2020.0, and maps of their predicted rate of change for the 2020.0 to 2025.0 time period.

Optimization-Based Collision Avoidance

Abstract: This article presents a novel method for exactly reformulating nondifferentiable collision avoidance constraints into smooth, differentiable constraints using strong duality of convex optimization. We focus on a controlled object whose goal is to avoid obstacles while moving in an $n$ -dimensional space. The proposed reformulation is exact, does not introduce any approximations, and applies to general obstacles and controlled objects that can be represented as the union of convex sets. We connect our results with the notion of signed distance, which is widely used in traditional trajectory generation algorithms. Our method can be applied to generic navigation and trajectory planning tasks, and the smoothness property allows the use of general-purpose gradient- and Hessian-based optimization algorithms. Finally, in case a collision cannot be avoided, our framework allows us to find “least-intrusive” trajectories, measured in terms of penetration. We demonstrate the efficacy of our framework on an automated parking problem, where our numerical experiments suggest that the proposed method is robust and enables real-time optimization-based trajectory planning in tight environments. Sample code of our example is provided at https://github.com/XiaojingGeorgeZhang/OBCA .

Root traits as drivers of plant and ecosystem functioning: current understanding, pitfalls and future research needs

Abstract: The effects of plants on the biosphere, atmosphere and geosphere are key determinants of terrestrial ecosystem functioning. However, despite substantial progress made regarding plant belowground components, we are still only beginning to explore the complex relationships between root traits and functions. Drawing on the literature in plant physiology, ecophysiology, ecology, agronomy and soil science, we reviewed 24 aspects of plant and ecosystem functioning and their relationships with a number of root system traits, including aspects of architecture, physiology, morphology, anatomy, chemistry, biomechanics and biotic interactions. Based on this assessment, we critically evaluated the current strengths and gaps in our knowledge, and identify future research challenges in the field of root ecology. Most importantly, we found that belowground traits with the broadest importance in plant and ecosystem functioning are not those most commonly measured. Also, the estimation of trait relative importance for functioning requires us to consider a more comprehensive range of functionally relevant traits from a diverse range of species, across environments and over time series. We also advocate that establishing causal hierarchical links among root traits will provide a hypothesis-based framework to identify the most parsimonious sets of traits with the strongest links on functions, and to link genotypes to plant and ecosystem functioning.

Trends in Micro-/Nanorobotics: Materials Development, Actuation, Localization, and System Integration for Biomedical Applications.

Abstract: Micro-/nanorobots (m-bots) have attracted significant interest due to their suitability for applications in biomedical engineering and environmental remediation. Particularly, their applications in in vivo diagnosis and intervention have been the focus of extensive research in recent years with various clinical imaging techniques being applied for localization and tracking. The successful integration of well-designed m-bots with surface functionalization, remote actuation systems, and imaging techniques becomes the crucial step toward biomedical applications, especially for the in vivo uses. This review thus addresses four different aspects of biomedical m-bots: design/fabrication, functionalization, actuation, and localization. The biomedical applications of the m-bots in diagnosis, sensing, microsurgery, targeted drug/cell delivery, thrombus ablation, and wound healing are reviewed from these viewpoints. The developed biomedical m-bot systems are comprehensively compared and evaluated based on their characteristics. The current challenges and the directions of future research in this field are summarized.

A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya

Abstract: On 7 Feb 2021, a catastrophic mass flow descended the Ronti Gad, Rishiganga, and Dhauliganga valleys in Chamoli, Uttarakhand, India, causing widespread devastation and severely damaging two hydropower projects. Over 200 people were killed or are missing. Our analysis of satellite imagery, seismic records, numerical model results, and eyewitness videos reveals that ~27x106 m3 of rock and glacier ice collapsed from the steep north face of Ronti Peak. The rock and ice avalanche rapidly transformed into an extraordinarily large and mobile debris flow that transported boulders >20 m in diameter, and scoured the valley walls up to 220 m above the valley floor. The intersection of the hazard cascade with downvalley infrastructure resulted in a disaster, which highlights key questions about adequate monitoring and sustainable development in the Himalaya as well as other remote, high-mountain environments.

A trade-off between plant and soil carbon storage under elevated CO2.

Abstract: Terrestrial ecosystems remove about 30 per cent of the carbon dioxide (CO2) emitted by human activities each year1, yet the persistence of this carbon sink depends partly on how plant biomass and soil organic carbon (SOC) stocks respond to future increases in atmospheric CO2 (refs. 2,3). Although plant biomass often increases in elevated CO2 (eCO2) experiments4–6, SOC has been observed to increase, remain unchanged or even decline7. The mechanisms that drive this variation across experiments remain poorly understood, creating uncertainty in climate projections8,9. Here we synthesized data from 108 eCO2 experiments and found that the effect of eCO2 on SOC stocks is best explained by a negative relationship with plant biomass: when plant biomass is strongly stimulated by eCO2, SOC storage declines; conversely, when biomass is weakly stimulated, SOC storage increases. This trade-off appears to be related to plant nutrient acquisition, in which plants increase their biomass by mining the soil for nutrients, which decreases SOC storage. We found that, overall, SOC stocks increase with eCO2 in grasslands (8 ± 2 per cent) but not in forests (0 ± 2 per cent), even though plant biomass in grasslands increase less (9 ± 3 per cent) than in forests (23 ± 2 per cent). Ecosystem models do not reproduce this trade-off, which implies that projections of SOC may need to be revised. A synthesis of elevated carbon dioxide experiments reveals that when plant biomass is strongly stimulated by elevated carbon dioxide levels, soil carbon storage declines, and where biomass is weakly stimulated, soil carbon accumulates.

Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6

Abstract: . The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the primary future climate projections within the Coupled Model Intercomparison Project Phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models for concentration driven simulations. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century encompassing the Tier 1 experiments (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by 1.15 °C) reached at the upper end of the 5–95 % envelope of the highest scenario, SSP5-8.5. This is due to both the wider range of radiative forcing that the new scenarios cover and to higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensembles' spread, according to a set of initial condition ensemble simulations available under SSP3-7.0. The same experiments suggest a tendency for internal variability to decrease along the course of the century, a new result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP, but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades in mid-century, as represented in SSP5-3.4OS, does not affect the end outcome in terms of temperature and precipitation changes by 2100, which return to the same level as those reached by the gradually increasing SSP4-3.4. Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level show all scenarios reaching 1.5 °C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering 20–28 years from present. 2 °C of warming is reached as early as the late '30s by the ensemble mean under SSP5-8.5, but as late as the late '50s under SSP1-2.6. The highest warming level considered, 5 °C, is reached only by the ensemble mean under SSP5-8.5, and not until the mid-90s.

Anthropogenic intensification of short-duration rainfall extremes

Abstract: Short-duration (1–3 h) rainfall extremes can cause serious damage to societies through rapidly developing (flash) flooding and are determined by complex, multifaceted processes that are altering as Earth’s climate warms. In this Review, we examine evidence from observational, theoretical and modelling studies for the intensification of these rainfall extremes, the drivers and the impact on flash flooding. Both short-duration and long-duration (>1 day) rainfall extremes are intensifying with warming at a rate consistent with the increase in atmospheric moisture (~7% K−1), while in some regions, increases in short-duration extreme rainfall intensities are stronger than expected from moisture increases alone. These stronger local increases are related to feedbacks in convective clouds, but their exact role is uncertain because of the very small scales involved. Future extreme rainfall intensification is also modulated by changes to temperature stratification and large-scale atmospheric circulation. The latter remains a major source of uncertainty. Intensification of short-duration extremes has likely increased the incidence of flash flooding at local scales, and this can further compound with an increase in storm spatial footprint to considerably increase total event rainfall. These findings call for urgent climate change adaptation measures to manage increasing flood risks. Short-duration rainfall extremes are determined by complex processes that are affected by the warming climate. This Review assesses the evidence for the intensification of short-duration rainfall extremes, the associated drivers and the implications for flood risks.