Search

While vat photopolymerization has many advantages over soft lithography in fabricating microfluidic devices, including efficiency and shape complexity, it has difficulty achieving well-controlled micrometer-sized (smaller than 100 μm) channels in the layer building direction. The considerable light penetration depth of transparent resin leads to over-curing that inevitably cures the residual resin inside flow channels, causing clogs. In this paper, a 3D printing process — in-situ transfer vat photopolymerization is reported to solve this critical over-curing issue in fabricating microfluidic devices. We demonstrate microchannels with high Z-resolution (within 10 μm level) and high accuracy (within 2 μm level) using a general method with no requirements on liquid resins such as reduced transparency nor leads to a reduced fabrication speed. Compared with all other vat photopolymerization-based techniques specialized for microfluidic channel fabrication, our universal approach is compatible with commonly used 405 nm light sources and commercial photocurable resins. The process has been verified by multifunctional devices, including 3D serpentine microfluidic channels, microfluidic valves, and particle sorting devices. This work solves a critical barrier in 3D printing microfluidic channels using the high-speed vat photopolymerization process and broadens the material options. It also significantly advances vat photopolymerization’s use in applications requiring small gaps with high accuracy in the Z-direction.

Capabilities for continuous monitoring of pressures and temperatures at critical skin interfaces can help to guide care strategies that minimize the potential for pressure injuries in hospitalized patients or in individuals confined to the bed. This paper introduces a soft, skin-mountable class of sensor system for this purpose. The design includes a pressure-responsive element based on membrane deflection and a battery-free, wireless mode of operation capable of multi-site measurements at strategic locations across the body. Such devices yield continuous, simultaneous readings of pressure and temperature in a sequential readout scheme from a pair of primary antennas mounted under the bedding and connected to a wireless reader and a multiplexer located at the bedside. Experimental evaluation of the sensor and the complete system includes benchtop measurements and numerical simulations of the key features. Clinical trials involving two hemiplegic patients and a tetraplegic patient demonstrate the feasibility, functionality and long-term stability of this technology in operating hospital settings., Uninterrupted monitoring of pressure and temperature at skin interfaces can help to minimize the potential for pressure injuries in hospitalized or bedridden patients. Here, the authors introduce a soft, skin-mountable sensor that can continuously provide readings via antennas mounted under bedding, and demonstrate the functionality and robustness of the devices on patients.

The growing demand for bandwidth makes photonic systems a leading candidate for future telecommunication and radar technologies. Integrated photonic systems offer ultra-wideband performance within a small footprint, which can naturally interface with fiber-optic networks for signal transmission. However, it remains challenging to realize narrowband (∼MHz) filters needed for high-performance communications systems using integrated photonics. In this paper, we demonstrate all-silicon microwave-photonic notch filters with 50× higher spectral resolution than previously realized in silicon photonics. This enhanced performance is achieved by utilizing optomechanical interactions to access long-lived phonons, greatly extending available coherence times in silicon. We use a multi-port Brillouin-based optomechanical system to demonstrate ultra-narrowband (2.7 MHz) notch filters with high rejection (57 dB) and frequency tunability over a wide spectral band (6 GHz) within a microwave-photonic link. We accomplish this with an all-silicon waveguide system, using CMOS-compatible fabrication techniques.

Microglia are brain resident immune cells with multiple functions. However, little is known about microglia-vascular interactions. In a recent paper published in Nature Communications, Bisht et al. identify a signalling mechanism that attracts and maintains microglia at the capillary wall. Moreover, they show that microglia regulate capillary vascular tone, playing a more significant role in blood flow regulation than previously thought.

Urbanization and climate change are together exacerbating water scarcity—where water demand exceeds availability—for the world’s cities. We quantify global urban water scarcity in 2016 and 2050 under four socioeconomic and climate change scenarios, and explored potential solutions. Here we show the global urban population facing water scarcity is projected to increase from 933 million (one third of global urban population) in 2016 to 1.693–2.373 billion people (one third to nearly half of global urban population) in 2050, with India projected to be most severely affected in terms of growth in water-scarce urban population (increase of 153–422 million people). The number of large cities exposed to water scarcity is projected to increase from 193 to 193–284, including 10–20 megacities. More than two thirds of water-scarce cities can relieve water scarcity by infrastructure investment, but the potentially significant environmental trade-offs associated with large-scale water scarcity solutions must be guarded against., This paper quantifies global urban water scarcity in 2016 and 2050 and explores potential solutions. One third to nearly half of the global urban population is projected to face water scarcity problems.

Population fluctuations are widespread across the animal kingdom, especially in the order Rodentia, which includes many globally important reservoir species for zoonotic pathogens. The implications of these fluctuations for zoonotic spillover remain poorly understood. Here, we report a global empirical analysis of data describing the linkages between habitat use, population fluctuations and zoonotic reservoir status in rodents. Our quantitative synthesis is based on data collated from papers and databases. We show that the magnitude of population fluctuations combined with species' synanthropy and degree of human exploitation together distinguish most rodent reservoirs at a global scale, a result that was consistent across all pathogen types and pathogen transmission modes. Our spatial analyses identified hotspots of high transmission risk, including regions where reservoir species dominate the rodent community. Beyond rodents, these generalities inform our understanding of how natural and anthropogenic factors interact to increase the risk of zoonotic spillover in a rapidly changing world.

The bonding of copper ions to lattice oxygens dictates the activity and selectivity of copper exchanged zeolites. By 17O isotopic labelling of the zeolite framework, in conjunction with advanced EPR methodologies and DFT modelling, we determine the local structure of single site CuII species, we quantify the covalency of the metal-framework bond and we assess how this scenario is modified by the presence of solvating H216O or H217O molecules. This enables to follow the migration of CuII species as a function of hydration conditions, providing evidence for a reversible transfer pathway within the zeolite cage as a function of the water pressure. The results presented in this paper establish 17O EPR as a versatile tool for characterizing metal-oxide interactions in open-shell systems., The identification of catalytically active sites with atomic-scale precision occupies a central place in the theory and practice of heterogeneous catalysis. Here the authors assess the nature of the copper-oxygen bond in a Cu-CHA zeolite and recover the microscopic structure of single-metal sites.

Development of catalytic amide bond-forming methods is important because they could potentially address the existing limitations of classical methods using superstoichiometric activating reagents. In this paper, we disclose an Umpolung amidation reaction of carboxylic acids with nitroarenes and nitroalkanes enabled by the triplet synergistic catalysis of FeI2, P(V)/P(III) and photoredox catalysis, which avoids the production of byproducts from stoichiometric coupling reagents. A wide range of carboxylic acids, including aliphatic, aromatic and alkenyl acids participate smoothly in such reactions, generating structurally diverse amides in good yields (86 examples, up to 97% yield). This Umpolung amidation strategy opens a method to address challenging regioselectivity issues between nucleophilic functional groups, and complements the functional group compatibility of the classical amidation protocols. The synthetic robustness of the reaction is demonstrated by late-stage modification of complex molecules and gram-scale applications., Catalytic amide bond-forming methods is important because they could potentially address the existing limitations of classical methods using superstoichiometric activating reagents. Here the authors show an Umpolung amidation reaction of carboxylic acids with nitroarenes and nitroalkanes enabled by FeI2, P(V)/P(III) and photoredox catalysis that avoids the production of byproducts.

Active metasurfaces have been proposed as one attractive means of achieving high-resolution spatiotemporal control of optical wavefronts, having applications such as LIDAR and dynamic holography. However, achieving full, dynamic phase control has been elusive in metasurfaces. In this paper, we unveil an electrically tunable metasurface design strategy that operates near the avoided crossing of two resonances, one a spectrally narrow, over-coupled resonance and the other with a high resonance frequency tunability. This strategy displays an unprecedented upper limit of 4π range of dynamic phase modulation with no significant variations in optical amplitude, by enhancing the phase tunability through utilizing two coupled resonances. A proof-of-concept metasurface is justified analytically and verified numerically in an experimentally accessible platform using quasi-bound states in the continuum and graphene plasmon resonances, with results showing a 3π phase modulation capacity with a uniform reflection amplitude of ~0.65.

With vaccination against COVID-19 stalled in some countries, increasing vaccine accessibility and distribution could help keep transmission under control. Here, we study the impact of reactive vaccination targeting schools and workplaces where cases are detected, with an agent-based model accounting for COVID-19 natural history, vaccine characteristics, demographics, behavioural changes and social distancing. In most scenarios, reactive vaccination leads to a higher reduction in cases compared with non-reactive strategies using the same number of doses. The reactive strategy could however be less effective than a moderate/high pace mass vaccination program if initial vaccination coverage is high or disease incidence is low, because few people would be vaccinated around each case. In case of flare-ups, reactive vaccination could better mitigate spread if it is implemented quickly, is supported by enhanced test-trace-isolate and triggers an increased vaccine uptake. These results provide key information to plan an adaptive vaccination rollout.

The dynamic evolutions of fluid-mineral systems driving large-scale geochemical transformations in the Earth’s crust remain poorly understood. We observed experimentally that successive sodic and potassic alterations of feldspar can occur via a single self-evolved, originally Na-only, hydrothermal fluid. At 600 °C, 2 kbar, sanidine ((K,Na)AlSi3O8) reacted rapidly with a NaCl fluid to form albite (NaAlSi3O8); over time, some of this albite was replaced by K-feldspar (KAlSi3O8), in contrast to predictions from equilibrium reaction modelling. Fluorine accelerated the process, resulting in near-complete back-replacement of albite within 1 day. These findings reveal that potassic alteration can be triggered by Na-rich fluids, indicating that pervasive sequential sodic and potassic alterations associated with mineralization in some of the world’s largest ore deposits may not necessarily reflect externally-driven changes in fluid alkali contents. Here, we show that these reactions are promoted at the micro-scale by a self-evolving, kinetically-driven process; such positive feedbacks between equilibrium and kinetic factors may be essential in driving pervasive mineral transformations., This paper reveals that potassic alteration can be triggered by Na-rich fluids, indicating that pervasive sequential sodic and potassic alterations associated with mineralization in some of the world’s largest ore deposits may not necessarily reflect externally-driven changes in fluid alkali contents.

Complex dynamical fluctuations, from intracellular noise, brain dynamics or computer traffic display bursting dynamics consistent with a critical state between order and disorder. Living close to the critical point has adaptive advantages and it has been conjectured that evolution could select these critical states. Is this the case of living cells? A system can poise itself close to the critical point by means of the so-called self-organized criticality (SOC). In this paper we present an engineered gene network displaying SOC behaviour. This is achieved by exploiting the saturation of the proteolytic degradation machinery in E. coli cells by means of a negative feedback loop that reduces congestion. Our critical motif is built from a two-gene circuit, where SOC can be successfully implemented. The potential implications for both cellular dynamics and behaviour are discussed., This work was supported by the Botin Foundation by Banco Santander through its Santander Universities Global Division, the Spanish Ministry of Economy and Competitiveness, grant AEI-PID2019-111680GB-I00/AEI/10.13039/501100011033, an AGAUR FI 2018 grant, and the Santa Fe Institute (where the key idea was conceived). J.S. and A.G. have been partially funded by the CERCA Programme of the Generalitat de Catalunya. J.S. acknowledges support from Agencia Estatal de Investigación grant RTI2018-098322-B-I00 and Ramón y Cajal contract RYC-2017-22243. A.G. has been funded by the AGAUR grant 2017-SGR-1049 and by the MINECO-FEDER-UE grants PGC-2018-098676-B-100 and RTI2018-093860-B-C21.

Neuronal activity in sensory cortex fluctuates over time and across repetitions of the same input. This variability is often considered detrimental to neural coding. The theory of neural sampling proposes instead that variability encodes the uncertainty of perceptual inferences. In primary visual cortex (V1), modulation of variability by sensory and non-sensory factors supports this view. However, it is unknown whether V1 variability reflects the statistical structure of visual inputs, as would be required for inferences correctly tuned to the statistics of the natural environment. Here we combine analysis of image statistics and recordings in macaque V1 to show that probabilistic inference tuned to natural image statistics explains the widely observed dependence between spike count variance and mean, and the modulation of V1 activity and variability by spatial context in images. Our results show that the properties of a basic aspect of cortical responses—their variability—can be explained by a probabilistic representation tuned to naturalistic inputs., The neural sampling theory suggests that neuronal variability encodes the uncertainty of probabilistic inferences. This paper shows that response variability in primary visual cortex reflects the statistical structure of visual inputs, as required for inferences correctly tuned to the statistics of the natural environment.

Spin ice systems display a variety of very nontrivial properties, the most striking being the existence in them of magnetic monopoles. Such monopole states can also have nontrivial electric properties: there exist electric dipoles attached to each monopole. A novel situation is encountered in the moment fragmentation (MF) state, in which monopoles and antimonopoles are perfectly ordered, whereas spins themselves remain disordered. We show that such partial ordering strongly modifies the electric activity of such systems: the electric dipoles, which are usually random and dynamic, become paired in the MF state in (d, −d) pairs, thus strongly reducing their electric activity. The electric currents existing in systems with noncoplanar spins are also strongly influenced by MF. We also consider modifications in dipole and current patterns in magnetic textures (domain walls, local defects) and at excitations with nontrivial dynamics in a MF state, which show very rich behaviour and which could in principle allow to control them by electric field., Spin-ices can exhibit a variety of remarkable phenomena, not least the appearance of emergent magnetic monopoles. In this theory paper, Daniel Khomskii shows that in the moment fragmentation state, the electric dipoles associated with magnetic monopoles become ordered, leading to a change in electrical activity.

Microdevice integrating energy storage with wireless charging could create opportunities for electronics design, such as moveable charging. Herein, we report seamlessly integrated wireless charging micro-supercapacitors by taking advantage of a designed highly consistent material system that both wireless coils and electrodes are of the graphite paper. The transferring power efficiency of the wireless charging is 52.8%. Benefitting from unique circuit structure, the intact device displays low resistance and excellent voltage tolerability with a capacitance of 454.1 mF cm−2, superior to state-of-the-art conventional planar micro-supercapacitors. Besides, a record high energy density of 463.1 μWh cm−2 exceeds the existing metal ion hybrid micro-supercapacitors and even commercial thin film battery (350 μWh cm−2). After charging for 6 min, the integrated device reaches up to a power output of 45.9 mW, which can drive an electrical toy car immediately. This work brings an insight for contactless micro-electronics and flexible micro-robotics. Miniaturized energy storage devices integrated with wireless charging bring opportunities for next generation electronics. Here, authors report seamlessly integrated wireless charging micro-supercapacitors with high energy density capable of driving a model electrical car.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22487-4

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22763-3

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21494-9

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22104-4

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22031-4

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21969-9

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22014-5

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22149-5

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22119-x

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22151-x

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22085-4

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22037-y

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22026-1

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21726-y

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21706-2

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21490-z

The active sites for CO2 electroreduction (CO2R) to multi-carbon (C2+) products over oxide-derived copper (OD-Cu) catalysts are under long-term intense debate. This paper describes the atomic structure motifs for product-specific active sites on OD-Cu catalysts in CO2R. Herein, we describe realistic OD-Cu surface models by simulating the oxide-derived process via the molecular dynamic simulation with neural network (NN) potential. After the analysis of over 150 surface sites through NN potential based high-throughput testing, coupled with density functional theory calculations, three square-like sites for C–C coupling are identified. Among them, Σ3 grain boundary like planar-square sites and convex-square sites are responsible for ethylene production while step-square sites, i.e. n(111) × (100), favor alcohols generation, due to the geometric effect for stabilizing acetaldehyde intermediates and destabilizing Cu–O interactions, which are quantitatively demonstrated by combined theoretical and experimental results. This finding provides fundamental insights into the origin of activity and selectivity over Cu-based catalysts and illustrates the value of our research framework in identifying active sites for complex heterogeneous catalysts., The active sites over oxide-derived copper (OD-Cu) catalysts for CO2 electroreduction are unclear. Here, the authors show atom-level product-specific active sites on OD-Cu surface models, where planar and convex square sites are responsible for ethylene while the step square site favours alcohols generation.

Author(s): Coignard, Juliette; Lush, Michael; Beesley, Jonathan; O'Mara, Tracy A; Dennis, Joe; Tyrer, Jonathan P; Barnes, Daniel R; McGuffog, Lesley; Leslie, Goska; Bolla, Manjeet K; Adank, Muriel A; Agata, Simona; Ahearn, Thomas; Aittomaki, Kristiina; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Arnold, Norbert; Aronson, Kristan J; Arun, Banu K; Augustinsson, Annelie; Azzollini, Jacopo; Barrowdale, Daniel; Baynes, Caroline; Becher, Heko; Bermisheva, Marina; Bernstein, Leslie; Bialkowska, Katarzyna; Blomqvist, Carl; Bojesen, Stig E; Bonanni, Bernardo; Borg, Ake; Brauch, Hiltrud; Brenner, Hermann; Burwinkel, Barbara; Buys, Saundra S; Caldes, Trinidad; Caligo, Maria A; Campa, Daniele; Carter, Brian D; Castelao, Jose E; Chang-Claude, Jenny; Chanock, Stephen J; Chung, Wendy K; Claes, Kathleen BM; Clarke, Christine L; GEMO Study Collaborators; EMBRACE Collaborators; Collee, J Margriet; Conroy, Don M; Czene, Kamila; Daly, Mary B; Devilee, Peter; Diez, Orland; Ding, Yuan Chun; Domchek, Susan M; Dork, Thilo; Dos-Santos-Silva, Isabel; Dunning, Alison M; Dwek, Miriam; Eccles, Diana M; Eliassen, A Heather; Engel, Christoph; Eriksson, Mikael; Evans, D Gareth; Fasching, Peter A; Flyger, Henrik; Fostira, Florentia; Friedman, Eitan; Fritschi, Lin; Frost, Debra; Gago-Dominguez, Manuela; Gapstur, Susan M; Garber, Judy; Garcia-Barberan, Vanesa; Garcia-Closas, Montserrat; Garcia-Saenz, Jose A; Gaudet, Mia M; Gayther, Simon A; Gehrig, Andrea; Georgoulias, Vassilios; Giles, Graham G; Godwin, Andrew K; Goldberg, Mark S; Goldgar, David E | Abstract: A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-23162-4.

The publication of a paper on mentorship, now retracted, led us to reflect on our editorial processes and strengthened our determination in supporting diversity, equity and inclusion in research.

We study mentorship in scientific collaborations, where a junior scientist is supported by potentially multiple senior collaborators, without them necessarily having formal supervisory roles. We identify 3 million mentor–protege pairs and survey a random sample, verifying that their relationship involved some form of mentorship. We find that mentorship quality predicts the scientific impact of the papers written by proteges post mentorship without their mentors. We also find that increasing the proportion of female mentors is associated not only with a reduction in post-mentorship impact of female proteges, but also a reduction in the gain of female mentors. While current diversity policies encourage same-gender mentorships to retain women in academia, our findings raise the possibility that opposite-gender mentorship may actually increase the impact of women who pursue a scientific career. These findings add a new perspective to the policy debate on how to best elevate the status of women in science. Here, the authors study mentorship in scientific collaborations, and find that mentorship quality predicts the scientific impact of proteges post mentorship. Moreover, female proteges collaborating with male mentors become more impactful post mentorship than those who collaborate with female mentors.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20453-0

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20410-x

A preparation game is a task whereby a player sequentially sends a number of quantum states to a referee, who probes each of them and announces the measurement result. Many experimental tasks in quantum information, such as entanglement quantification or magic state detection, can be cast as preparation games. In this paper, we introduce general methods to design n-round preparation games, with tight bounds on the performance achievable by players with arbitrarily constrained preparation devices. We illustrate our results by devising new adaptive measurement protocols for entanglement detection and quantification. Surprisingly, we find that the standard procedure in entanglement detection, namely, estimating n times the average value of a given entanglement witness, is in general suboptimal for detecting the entanglement of a specific quantum state. On the contrary, there exist n-round experimental scenarios where detecting the entanglement of a known state optimally requires adaptive measurement schemes., Finding a general way to come up with optimal strategies for quantum information tasks is a matter of both fundamental and practical interest. Here, the authors tackle the problem using the formalism of quantum preparation games, finding applications for entanglement detection and quantification.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20105-3

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-19902-7

The Tafel slope is a key parameter often quoted to characterize the efficacy of an electrochemical catalyst. In this paper, we develop a Bayesian data analysis approach to estimate the Tafel slope from experimentally-measured current-voltage data. Our approach obviates the human intervention required by current literature practice for Tafel estimation, and provides robust, distributional uncertainty estimates. Using synthetic data, we illustrate how data insufficiency can unknowingly influence current fitting approaches, and how our approach allays these concerns. We apply our approach to conduct a comprehensive re-analysis of data from the CO2 reduction literature. This analysis reveals no systematic preference for Tafel slopes to cluster around certain "cardinal values” (e.g. 60 or 120 mV/decade). We hypothesize several plausible physical explanations for this observation, and discuss the implications of our finding for mechanistic analysis in electrochemical kinetic investigations., The Tafel slope in electrochemical catalysis is usually determined from experimental data and remains error-prone. Here, the authors develop a Bayesian approach for Tafel slope quantification, and apply it to study the prevalence of certain "cardinal" Tafel slopes in the electrochemical CO2 reduction literature.

The self-organization of strongly interacting electrons into superlattice structures underlies the properties of many quantum materials. How these electrons arrange within the superlattice dictates what symmetries are broken and what ground states are stabilized. Here we show that cryogenic scanning transmission electron microscopy (cryo-STEM) enables direct mapping of local symmetries and order at the intra-unit-cell level in the model charge-ordered system Nd1/2Sr1/2MnO3. In addition to imaging the prototypical site-centered charge order, we discover the nanoscale coexistence of an exotic intermediate state which mixes site and bond order and breaks inversion symmetry. We further show that nonlinear coupling of distinct lattice modes controls the selection between competing ground states. The results demonstrate the importance of lattice coupling for understanding and manipulating the character of electronic self-organization and that cryo-STEM can reveal local order in strongly correlated systems at the atomic scale., In this paper, the authors demonstrate that cryogenic scanning transmission electron microscopy allows for the direct mapping of the local arrangements and symmetries of electronic order, providing a useful method for studying strongly correlated systems. They show this using the example of Nd1/2Sr1/2MnO3, a model charge ordered material.

The α-type ADP-ribosylated peptides represent a class of important molecular tools in the field of protein ADP-ribosylation, however, they are difficult to access because of their inherent complicated structures and the lack of effective synthetic tools. In this paper, we present a biomimetic α-selective ribosylation reaction to synthesize a key intermediate, α-ADP-ribosyl azide, directly from native β-nicotinamide adenine dinucleotide in a clean ionic liquid system. This reaction in tandem with click chemistry then offers a two-step modular synthesis of α-ADP-ribosylated peptides. These syntheses can be performed open air in eppendorf tubes, without the need for specialized instruments or training. Importantly, we demonstrate that the synthesized α-ADP-ribosylated peptides show high binding affinity and desirable stability for enriching protein partners, and reactivity in post-stage poly ADP-ribosylations. Owing to their simple chemistry and multidimensional bio-applications, the presented methods may provide a powerful platform to produce general molecular tools for the study of protein ADP-ribosylation., ADP-ribosylated peptides are important molecular tools, however, the lack of effective synthetic methods hinders the access to their complex structures. Here, the authors present a biomimetic α-selective ribosylation reaction coupled with click chemistry ultimately providing a two-step modular synthesis of α-ADP-ribosylated peptides.

Generalization beyond a training dataset is a main goal of machine learning, but theoretical understanding of generalization remains an open problem for many models. The need for a new theory is exacerbated by recent observations in deep neural networks where overparameterization leads to better performance, contradicting the conventional wisdom from classical statistics. In this paper, we investigate generalization error for kernel regression, which, besides being a popular machine learning method, also includes infinitely overparameterized neural networks trained with gradient descent. We use techniques from statistical mechanics to derive an analytical expression for generalization error applicable to any kernel or data distribution. We present applications of our theory to real and synthetic datasets, and for many kernels including those that arise from training deep neural networks in the infinite-width limit. We elucidate an inductive bias of kernel regression to explain data with "simple functions", which are identified by solving a kernel eigenfunction problem on the data distribution. This notion of simplicity allows us to characterize whether a kernel is compatible with a learning task, facilitating good generalization performance from a small number of training examples. We show that more data may impair generalization when noisy or not expressible by the kernel, leading to non-monotonic learning curves with possibly many peaks. To further understand these phenomena, we turn to the broad class of rotation invariant kernels, which is relevant to training deep neural networks in the infinite-width limit, and present a detailed mathematical analysis of them when data is drawn from a spherically symmetric distribution and the number of input dimensions is large., Comment: Accepted for publication in Nature Communications. SI Eq.71 is corrected

Electrical pumping of organic semiconductor devices involves charge injection, transport, device on/off dynamics, exciton formation and annihilation processes. A comprehensive model analysing those entwined processes together is most helpful in determining the dominating loss pathways. In this paper, we report experimental and theoretical results of Super Yellow (Poly(p-phenylene vinylene) co-polymer) organic light emitting diodes operating at high current density under high voltage nanosecond pulses. We demonstrate complete exciton and charge carrier dynamics of devices, starting from charge injection to light emission, in a time scale spanning from the sub-ns to microsecond region, and compare results with optical pumping. The experimental data is accurately replicated by simulation, which provides a robust test platform for any organic materials. The universality of our model is successfully demonstrated by its application to three other laser active materials. The findings provide a tool to narrow the search for material and device designs for injection lasing., Though efforts toward electrically-pumped lasers based on simple organic light-emitting diode (OLED) structures have been reported, a comprehensive model is needed to elucidate key optoelectronic processes. Here, the authors report a model describing OLED operation under high current densities.

Recent studies conclude that the global coronavirus (COVID-19) pandemic decreased power sector CO$_2$ emissions globally and in the United States. In this paper, we analyze the statistical significance of CO2 emissions reductions in the U.S. power sector from March through December 2020. We use Gaussian process (GP) regression to assess whether CO2 emissions reductions would have occurred with reasonable probability in the absence of COVID-19 considering uncertainty due to factors unrelated to the pandemic and adjusting for weather, seasonality, and recent emissions trends. We find that monthly CO2 emissions reductions are only statistically significant in April and May 2020 considering hypothesis tests at 5% significance levels. Separately, we consider the potential impact of COVID-19 on coal-fired power plant retirements through 2022. We find that only a small percentage of U.S. coal power plants are at risk of retirement due to a possible COVID-19-related sustained reduction in electricity demand and prices. We observe and anticipate a return to pre-COVID-19 CO2 emissions in the U.S. power sector., Comment: 13 pages, 6 figures, preprint

Power laws are omnipresent and actively studied in many scientific fields, including plasticity of materials. Here, we report the power-law statistics in the second and subsequent pop-in magnitudes during load-controlled nanoindentation testing, whereas the first pop-in is characterized by Gaussian-like statistics with a well-defined average value. The transition from Gaussian-like to power-law is due to the change in the deformation mechanism from dislocation nucleation to dislocation network evolution in the sharp-indenter induced abruptly decaying stress and dislocation density fields. Based on nanoindentation testing on the (100) and (111) surfaces of body-centered cubic (BCC) iron and the (100) surface of face-centered cubic (FCC) copper, the scaling exponents of the power laws were determined to be 5.6, 3.9, and 6.4, respectively. These power-law exponents are much higher than those typically observed in micro-pillar plasticity (1.0–1.8), suggesting that the nanoindentation plasticity belongs to a different universality class than the micro-pillar plasticity., Although power laws are observed during nanoindentation and the power-law exponents are estimated to be approximately 1.5-1.6 for face-centered cubic metals, the origin of the exponent remains unclear. In this paper, we show the power-law statistics in pop-in magnitudes and unveil the nature of the exponent.

While conceptual definitions provide a foundation for the study of disasters and their impacts, the challenge for researchers and practitioners alike has been to develop objective and rigorous measures of resilience that are generalizable and scalable, taking into account spatiotemporal dynamics in the response and recovery of localized communities. In this paper, we analyze mobility patterns of more than 800,000 anonymized mobile devices in Houston, Texas, representing approximately 35% of the local population, in response to Hurricane Harvey in 2017. Using changes in mobility behavior before, during, and after the disaster, we empirically define community resilience capacity as a function of the magnitude of impact and time-to-recovery. Overall, we find clear socioeconomic and racial disparities in resilience capacity and evacuation patterns. Our work provides new insight into the behavioral response to disasters and provides the basis for data-driven public sector decisions that prioritize the equitable allocation of resources to vulnerable neighborhoods., Understanding how cities respond to extreme weather is critical; as such events are becoming more frequent. Using anonymized mobile phone data for Houston, Texas during Hurricane Harvey in 2017, the authors find that mobility behavior exposes neighborhood disparities in resilience capacity and recovery.

For the past decade, optical wavefront shaping has been the standard technique to control light through scattering media. Implicit in this dominance is the assumption that manipulating optical interference is a necessity for optical control through scattering media. In this paper, we challenge this assumption by reporting on an alternate approach for light control through a disordered scattering medium – optical-channel-based intensity streaming (OCIS). Instead of actively tuning the interference between the optical paths via wavefront shaping, OCIS controls light and transmits information through scattering media through linear intensity operations. We demonstrate a set of OCIS experiments that connect to some wavefront shaping implementations, i.e. iterative wavefront optimization, digital optical phase conjugation, image transmission through transmission matrix, and direct imaging through scattering media. We experimentally created focus patterns through scattering media on a sub-millisecond timescale. We also demonstrate that OCIS enables a scattering medium mediated secure optical communication application., Controlling light through disordered scattering media is traditionally done by manipulating optical interference for wavefront shaping. Here, the authors present optical-channel-based intensity streaming, an approach which controls light and transmits information through linear intensity operations.

Gold nanoparticles have been used for centuries, both for decoration and in medical applications. More recently, many of the major advances in cluster chemistry have involved well-defined clusters containing tens or hundreds of atoms, either with or without a ligand shell. In this paper we report the synthesis of two gold/lead clusters, [Au8Pb33]6− and [Au12Pb44]8−, both of which contain nido [Au@Pb11]3− icosahedra surrounding a core of Au atoms. Analogues of these large clusters are not found in the corresponding Ag chemistry: instead, the Ag-centered nido icosahedron, [Ag@Pb11]3−, is the only isolated product. The structural chemistry, along with the mass spectrometry which shows the existence of [Au2Pb11]2− but not [Ag2Pb11]2−, leads us to propose that the former species is the key intermediate in the growth of the larger clusters. Density functional theory indicates that secondary π-type interactions between the [Au@Pb11]3− ligands and the gold core play a significant part in stabilizing the larger clusters., Many Zintl ions with a single endohedrally encapsulated transition metal ion are known, but relatively few where clusters of two or more metals are present. Here, the authors report the synthesis and characterization of two clusters, [Au8Pb33]6− and [Au12Pb44]12−, which contain Au8 and Au12 cores surrounded by Pb shells.