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Electronic digital convolutions could extract key features of objects for data processing and information identification in artificial intelligence, but they are time-cost and energy consumption due to the low response of electrons. Although massless photons enable high-speed and low-loss analog convolutions, two existing all-optical approaches including Fourier filtering and Green’s function have either limited functionality or bulky volume, thus restricting their applications in smart systems. Here, we report all-optical convolutional computing with a metasurface-singlet or -doublet imager, considered as the third approach, where its point spread function is modified arbitrarily via a complex-amplitude meta-modulator that enables functionality-unlimited kernels. Beyond one- and two-dimensional spatial differentiation, we demonstrate real-time, parallel, and analog convolutional processing of optical and biological specimens with challenging pepper-salt denoising and edge enhancement, which significantly enrich the toolkit of all-optical computing. Such meta-imager approach bridges multi-functionality and high-integration in all-optical convolutions, meanwhile possessing good architecture compatibility with digital convolutional neural networks.An ultra-compact metasurface-based imager with modified point spread function is demonstrated to realize arbitrary all-optical parallel picture convolution that is highly compatible to convolutional neural network.

Projected increases in greenhouse gas emissions could suppress marine biological productivity for a thousand years or more. As the climate warms, westerly winds in the Southern Hemisphere will strengthen and shift poleward, surface waters will warm, and sea ice will disappear. Moore et al. suggest that one effect of these changes will be a dramatic decrease in marine biological productivity (see the Perspective by Laufkötter and Gruber). This decrease will result from a global-scale redistribution of nutrients, with a net transfer to the deep ocean. By 2300, this could drive declines in fisheries yields by more than 20% globally and by nearly 60% in the North Atlantic. Science , this issue p. 1139 ; see also p. 1103 Multicentury climate warming could suppress marine biological productivity for a millennium. Climate change projections to the year 2100 may miss physical-biogeochemical feedbacks that emerge later from the cumulative effects of climate warming. In a coupled climate simulation to the year 2300, the westerly winds strengthen and shift poleward, surface waters warm, and sea ice disappears, leading to intense nutrient trapping in the Southern Ocean. The trapping drives a global-scale nutrient redistribution, with net transfer to the deep ocean. Ensuing surface nutrient reductions north of 30°S drive steady declines in primary production and carbon export (decreases of 24 and 41%, respectively, by 2300). Potential fishery yields, constrained by lower–trophic-level productivity, decrease by more than 20% globally and by nearly 60% in the North Atlantic. Continued high levels of greenhouse gas emissions could suppress marine biological productivity for a millennium.

Single-atom catalysts offer maximal atom utilization efficiencies and high-electronegativity heteroatoms play a crucial role in coordinating reactive single metal atoms to prevent agglomeration. However, these strong coordination bonds withdraw electron density for coordinated metal atoms and consequently affect their catalytic activity. Herein we reveal the high loading (11.3 wt%) and stabilization of moderately coordinated Cu-P 3 structure on black phosphorus support by a photochemical strategy with auxiliary hydrogen. Single-atom Cu sites with an exceptional electron-rich feature show the △ G H * close to zero to favor catalysis. Neighboring Cu atoms work in synergy to lower the energy of key water adsorption and dissociation intermediates. The reported catalyst shows a low overpotential of only 41 mV at 10 mA cm −2 and Tafel slope of 53.4 mV dec −1 for the alkaline hydrogen evolution reaction, surpassing both isolated Cu single atoms and Cu nanoclusters. The promising materials design strategy sheds light on the design and fabrication of high-loading single metal atoms and the role of neighboring single atoms for enhanced reaction kinetics. While atomically dispersed metals can maximize reaction catalytic sites, it is challenging to achieve high atomic densities without agglomeration. Here, authors prepared Cu single-atoms on black phosphorous using a photochemical strategy and auxiliary H 2 as proton reduction electrocatalysts.

Electrocatalytic CO 2 reduction to multi-carbon products is a promising approach for achieving carbon-neutral economies. However, the energy efficiency of these processes remains low, particularly at high current densities. Herein, we demonstrate that the low energy efficiencies are, in part, sometimes significantly, attributed to the high concentration overpotential resulting from the instability (i.e., flooding) of catalyst-layer during electrolysis. To tackle this challenge, we develop copper/gallium bimetallic catalysts with reduced activation energies for the formation of multi-carbon products. Consequently, the reduced activation overpotential allows us to achieve practical-relevant current densities for CO 2 reduction at low cathodic potentials, ensuring good stability of the catalyst-layer and thereby minimizing the undesired concentration overpotential. The optimized bimetallic catalyst achieves over 50% cathodic energy efficiency for multi-carbon production at a high current density of over 1.0 A cm − 2 . Furthermore, we achieve current densities exceeding 2.0 A cm − 2 in a zero-gap membrane-electrode-assembly reactor, with a full-cell energy efficiency surpassing 30%. Electroreduction of CO 2 to fuels and chemicals is promising but hindered by its low energy efficiency. Here, the authors develop Cu/Ga bimetallic catalysts with reduced activation energies to mitigate the high concentration overpotential, thereby achieving high energy efficiency for CO 2 reduction.

This study aimed to evaluate the impact of flight simulator training on the enhancement of perceptual-motor skills among flight cadets. Perceptual-motor skills act as a crucial link through which pilots translate their environmental perceptions into precise maneuvers, a capability that is particularly vital in dynamic and unpredictable flight environments. A total of forty cadets participated in the experiment and were randomly assigned to either the Traditional Training Group (TTG) or the Efficient Training Group (ETG). The TTG received individual training on training aircraft under the supervision of an instructor, while the ETG trained on expert aircraft using a full-scenario memory replay training system enhanced with multimodal information feedback. The simulations were conducted at the Aeronautical University simulation laboratory, configured as a self-developed Flight Skill Accelerated Training Simulator. Both groups completed eight weeks of simulated flight training, which included testing scenarios such as takeoff, flight control, landing, and carrier landing. Results indicated that the ETG outperformed the TTG in the takeoff, flight control, landing tasks, and carrier landing tasks. Furthermore, the ETG demonstrated a faster training pace across all tasks. These findings suggest that our independently developed accelerated flight skills training system can effectively expedite motor skill acquisition among flight cadets, enhance flight performance, and holds promising potential for broad application in various flight training contexts.

Ruminants are a diverse group of mammals that includes families containing well-known taxa such as deer, cows, and goats. However, their evolutionary relationships have been contentious, as have the origins of their distinctive digestive systems and headgear, including antlers and horns (see the Perspective by Ker and Yang). To understand the relationships among ruminants, L. Chen et al. sequenced 44 species representing 6 families and performed a phylogenetic analysis. From this analysis, they were able to resolve the phylogeny of many genera and document incomplete lineage sorting among major clades. Interestingly, they found evidence for large population reductions among many taxa starting at approximately 100,000 years ago, coinciding with the migration of humans out of Africa. Examining the bony appendages on the head—the so-called headgear—Wang et al. describe specific evolutionary changes in the ruminants and identify selection on cancer-related genes that may function in antler development in deer. Finally, Lin et al. take a close look at the reindeer genome and identify the genetic basis of adaptations that allow reindeer to survive in the harsh conditions of the Arctic. Science , this issue p. eaav6202 , p. eaav6335 , p. eaav6312 ; see also p. 1130 Ruminant phylogeny is resolved with representative genomes. The ruminants are one of the most successful mammalian lineages, exhibiting morphological and habitat diversity and containing several key livestock species. To better understand their evolution, we generated and analyzed de novo assembled genomes of 44 ruminant species, representing all six Ruminantia families. We used these genomes to create a time-calibrated phylogeny to resolve topological controversies, overcoming the challenges of incomplete lineage sorting. Population dynamic analyses show that population declines commenced between 100,000 and 50,000 years ago, which is concomitant with expansion in human populations. We also reveal genes and regulatory elements that possibly contribute to the evolution of the digestive system, cranial appendages, immune system, metabolism, body size, cursorial locomotion, and dentition of the ruminants.

Collective decision-making is important for coordination and synchronization of the activities among group-living animals and the mechanisms guiding such procedure involve a great variety of characteristics of behavior and motivation. This study provides some evidence investigating collective movement initiation in a multi-level social band of the golden snub-nosed monkeys ( Rhinopithecus roxellana ) located in the Mts. Qinling, China. We collect 1223 datum records relevant to decision initiation from six OMUs. The results indicate that collective movement initiation could be divided into two continual but relatively independent processes: decisions on moving direction and movement implementation. In both processes, adult individuals are more likely to initiate the decision-making, while other adults vote on initiator’s preference, with a threshold, a supporting number required for a success. Thus, voting behavior and quorum fulfillment contribute to a successful decision-making. Adult individuals play important role in making decisions for moving direction and implementation. For a successful collective movement initiation, the individuals being more central in grooming network initiate decisions more frequently than the others, and attract voters more easily. Furthermore, following the initiation, at least four positive voters are required for a direction decision and at least three positive voters are needed for the decision on movement implementation, which could be considered as the threshold of quorum numbers required for a successful decision. This study has provided some very interesting information and scientific evidence in understanding social structure and behaviors of the nonhuman primates with a social structure very similar to humans’. Thus, some results can directly be referred to the comprehension of human social structure and behavior.

The sirtuins (SIRTs), including seven family members, belong to class III histone deacetylase (HDAC) enzymes, which have been intensively investigated in cancers. Although the function of SIRTs in the cancer immunology is explored, SIRT-specific mechanisms regulating necroptosis-related innate immune response are not clear. In our present study, we found that both the mRNA and protein expression levels of SIRT3 and SIRT6 are significantly increased in the PCa tissues (HR, CI P=3.30E−03; HR, CI P=2.35E−08; and HR, CI P=9.20E−08) and were associated with patients’ Gleason score and nodal metastasis. Furthermore, multivariate analysis showed that the PCa patients with higher expression levels of SIRT3 and SIRT6 had shorter overall survival (OS). Mechanistically, we found that SIRT3 and SIRT6 promote prostate cancer progress by inhibiting RIPK3-mediated necroptosis and innate immune response. Knockdown of both SIRT3 and SIRT6 not only activates TNF-induced necroptosis but also refreshes the corresponding recruitment of macrophages and neutrophils. Overall, our study identified that SIRT3 and SIRT6 are key regulators of necroptosis during prostate cancer progression.

Optical holography has undergone rapid development since its invention in 1948, but the accompanying speckles with alternating dark and bright spots of randomly varying shapes are still untamed now due to the intrinsic fluctuations from irregular complex-field superposition. Despite spatial, temporal and spectral averages for speckle reduction, holographic images cannot yet meet the requirement for high-homogeneity, edge-sharp and shape-unlimited features in optical display and lithography. Here we report that holographic speckles can be removed by narrowing the probability density distribution of encoded phase to homogenize optical superposition. Guided by this physical insight, an Adam-gradient-descent probability-shaping (APS) method is developed to prohibit the fluctuations of intensity in a computer-generated hologram (CGH), which empowers the experimental reconstruction of irregular images with ultralow speckle contrast ( C  = 0.08) and record-high edge sharpness (~1000 mm −1 ). These well-behaved performances revitalize CGH for lensless lithography, enabling experimental fabrication of arbitrary-shape and edge-sharp patterns with spatial resolution of 0.54λ/ NA . The authors report lensless holography lithography with diffraction-limited resolution by proposing a phase-probability shaping mechanism to suppress speckle noise efficiently.

Gastric cancer is a leading cause of cancer-related mortality and highlights the need for early detection of gastric cancer and Helicobacter pylori (HP) infection, which is a major risk factor. Early non-invasive and convenient diagnostic tools capable of capturing the dynamic molecular alterations during carcinogenesis and HP infection is needed. In this study, we use Raman spectroscopy and machine learning algorithms to detect different gastric lesions and HP infection condition with gastric juice samples. 133 patients from Peking University Third Hospital were involved and categorized into groups based on histopathological diagnosis: early gastric cancer (EGC), dysplasia (DYS), intestinal metaplasia (IM), and chronic superficial gastritis (CSG), with further classification based on HP infection. The stacked machine learning model demonstrated high diagnostic performance, achieving 90% accuracy, 90% sensitivity, and 97% specificity in distinguishing pathological stages, along with 96% accuracy, 96% sensitivity, and 96% specificity in HP detection. The multilayer perceptron (MLP) model based on gastric juice Raman spectroscopy showed excellent discrimination capability, with an AUC of 0.98 for differentiating controls from patients with DYS and EGC. Additionally, Raman spectroscopy achieved an AUC of 0.95 in distinguishing control gastric mucosa from precancerous lesions (IM, DYS) and EGC. The approach offers a rapid, accurate, and minimally invasive diagnostic tool, demonstrating significant potential for clinical application in rapid and accurate detection of precancerous lesions, early gastric cancer, and HP infection.