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Large-scale, highly integrated and low-power-consuming hardware is becoming progressively more important for realizing optical neural networks (ONNs) capable of advanced optical computing. Traditional experimental implementations need N 2 units such as Mach-Zehnder interferometers (MZIs) for an input dimension N to realize typical computing operations (convolutions and matrix multiplication), resulting in limited scalability and consuming excessive power. Here, we propose the integrated diffractive optical network for implementing parallel Fourier transforms, convolution operations and application-specific optical computing using two ultracompact diffractive cells (Fourier transform operation) and only N MZIs. The footprint and energy consumption scales linearly with the input data dimension, instead of the quadratic scaling in the traditional ONN framework. A ~10-fold reduction in both footprint and energy consumption, as well as equal high accuracy with previous MZI-based ONNs was experimentally achieved for computations performed on the MNIST and Fashion-MNIST datasets. The integrated diffractive optical network (IDNN) chip demonstrates a promising avenue towards scalable and low-power-consumption optical computational chips for optical-artificial-intelligence. Here, we propose the integrated diffractive optical network for implementing parallel Fourier transforms, convolution operations and application-specific optical computing with reduced footprint and energy consumption.

Complex-valued neural networks have many advantages over their real-valued counterparts. Conventional digital electronic computing platforms are incapable of executing truly complex-valued representations and operations. In contrast, optical computing platforms that encode information in both phase and magnitude can execute complex arithmetic by optical interference, offering significantly enhanced computational speed and energy efficiency. However, to date, most demonstrations of optical neural networks still only utilize conventional real-valued frameworks that are designed for digital computers, forfeiting many of the advantages of optical computing such as efficient complex-valued operations. In this article, we highlight an optical neural chip (ONC) that implements truly complex-valued neural networks. We benchmark the performance of our complex-valued ONC in four settings: simple Boolean tasks, species classification of an Iris dataset, classifying nonlinear datasets (Circle and Spiral), and handwriting recognition. Strong learning capabilities (i.e., high accuracy, fast convergence and the capability to construct nonlinear decision boundaries) are achieved by our complex-valued ONC compared to its real-valued counterpart. Most demonstrations of optical neural networks for computing have been so far limited to real-valued frameworks. Here, the authors implement complex-valued operations in an optical neural chip that integrates input preparation, weight multiplication and output generation within a single device.

Whether the critical state friction angle of granular materials depends on grading is a fundamental question of both academic and practical interest. The present study attempts to address this question through a specifically designed experimental program where the influence of particle grading was carefully isolated from other influencing factors. The laboratory experiments show that under otherwise similar conditions, the angle of friction at critical state is a constant independent of grading, but, for a given grading, the angle of friction at critical state is highly dependent on particle shape. This finding suggests that the commonly adopted practice of separately allowing for the effect of particle shape and the effect of grading on critical state friction angle is conceptually inappropriate and, hence, should be taken with caution in geotechnical design to avoid the risk of underestimating safety requirements. The study also reveals that varying particle gradation can impose a marked impact on liquefaction susceptibility of granular soils: Under the same post-consolidation state in terms of void ratio and confining pressure, a well-graded soil tends to be more susceptible to liquefaction than a uniformly graded soil. This variation of liquefaction susceptibility is shown to be consistent with the variation of location of the critical state locus in the compression space and is explainable by the critical state theory.

Macroscopic fibres made up of carbon nanotubes exhibit properties far below theoretical predictions and even much lower than those for conventional carbon fibres. Here we report improvements of mechanical and electrical properties by more than one order of magnitude by pressurized rolling. Our carbon nanotubes self-assemble to a hollow macroscopic cylinder in a tube reactor operated at high temperature and then condense in water or ethanol to form a fibre, which is continually spooled in an open-air environment. This initial fibre is densified by rolling under pressure, leading to a combination of high tensile strength (3.76–5.53 GPa), high tensile ductility (8–13%) and high electrical conductivity ((1.82–2.24) × 10 4  S cm −1 ). Our study therefore demonstrates strategies for future performance maximization and the very considerable potential of carbon nanotube assemblies for high-end uses. There is strong interest in carbon nanotube assemblies for a variety of applications, many of which require combined high mechanical and electrical properties. Here, the authors demonstrate a rolling technique for performance improvement, reporting tensile strength of 4.34 GPa, ductility of 10% and electrical conductivity of 2.0 × 10 4  S cm −1 .

Postoperative recurrence and metastasis have crucial roles in the poor prognosis of gastric cancer patients. Previous studies have indicated that gastric cancer originates from cancer stem cells (CSCs), and some investigators have found that a particular subset of CSCs possesses higher metastatic capacity. However, the specific mechanism remains uncertain. In the present study, we aimed to explore the biological functions of the inflammatory cytokine interleukin-17 (IL-17) in gastric cancer metastasis and the distinct IL-17-induced transformation of quiescent gastric CSCs. Our results showed that invasive gastric CSCs were CD26+ and CXCR4+ and were closely associated with increased metastatic ability. The quiescent gastric CSCs, which were CD26− and CXCR4−, were exposed to appropriate concentrations of IL-17; this resulted in the decreased expression of E-cadherin and the increased expression of vimentin and N-cadherin. In addition, the upregulation of IL-17 both in vitro and in vivo resulted in a significant induction of invasion, migration and tumor formation ability in gastric CSCs compared with the control group, which was not treated with IL-17. Further experiments indicated that the activation of the downstream phosphorylated signal transducer and activator of transcription 3 (STAT3) transcription factor pathway was facilitated by IL-17. On the contrary, the downregulation of STAT3 by the specific inhibitor Stattic significantly reversed the IL-17-induced epithelial–mesenchymal transition (EMT)-associated properties of quiescent gastric CSCs. Moreover, tumorigenesis and metastasis were suppressed. Taken together, we suggest that IL-17 is positively correlated with the transformation of quiescent gastric CSCs into invasive gastric CSCs and that targeting IL-17 may emerge as a possible novel therapeutic strategy for gastric cancer.

Iron selenide superconductors exhibit a number of unique characteristics that are helpful for understanding the mechanism of superconductivity in high- T c iron-based superconductors more generally. However, in the case of A x Fe 2 Se 2 (A = K, Rb, Cs), the presence of an intergrown antiferromagnetic insulating phase makes the study of the underlying physics problematic. Moreover, FeSe-based systems intercalated with alkali metal ions, NH 3 molecules or organic molecules are extremely sensitive to air, which prevents the further investigation of their physical properties. It is therefore desirable to find a stable and easily accessible FeSe-based superconductor to study its physical properties in detail. Here, we report the synthesis of an air-stable material, (Li 0.8 Fe 0.2 )OHFeSe, which remains superconducting at temperatures up to ~40 K, by means of a novel hydrothermal method. The crystal structure is unambiguously determined by a combination of X-ray and neutron powder diffraction and nuclear magnetic resonance. Moreover, antiferromagnetic order is shown to coexist with superconductivity. This synthetic route opens a path for exploring superconductivity in other related systems, and confirms the appeal of iron selenides as a platform for understanding superconductivity in iron pnictides more broadly. Enhancing the superconducting temperature is often the main driver of synthetic studies of novel superconducting materials. Now, an approach yielding an air-stable iron selenide system that superconducts up to 40 K is reported.

Most patients with chronic obstructive pulmonary disease (COPD) suffer from at least one additional, clinically relevant chronic disease. To a degree, the high global prevalence and mortality rate of COPD is closely related to its extrapulmonary effects. Moreover, the various of comorbidities of COPD and itself interact with each other, resulting in diverse clinical manifestations and individual differences, and thus further influencing the prognosis as well as healthcare burden of COPD patients. This is closely related to the common risk factors of chronic diseases (aging, smoking, inactivity, etc.). Additionally, some pathophysiological mechanisms caused by COPD, including the systemic inflammatory response, hypoxia, oxidative stress, and others, also have an impact on other systems. But comprehensive management and medical interventions have not yet been established. The clinicians should improve their knowledge and skills in diagnosing as well as treating the comorbidities of COPD, and then aim to develop more individualized, efficient diagnostic and therapeutic strategies for different patients to achieve greater clinical benefits. In this article, we will review the risk factors, mechanisms, and treatment strategies for extrapulmonary comorbidities in chronic obstructive pulmonary disease, including cardiovascular diseases, diabetes, anemia, osteoporosis, emotional disorders, and gastroesophageal reflux disease.

El Niño/Southern Oscillation (ENSO) is the main climate mode that drives the interannual variability in climate and consequently vegetation greenness. While widespread green‐up has been reported and examined in tropical America during El Niño, it remains unclear how vegetation in tropical Asia changes during the period. Here, we used four remote sensing‐based leaf area index (LAI) products to investigate changes in vegetation greenness during the 2015/16 El Niño in tropical Asia. We found a strong green‐up during the 2015/16 El Niño in tropical Asia, with its regional average LAI stronger than that of tropical America. The drivers for the green‐up vary across the region, with radiation being the main driver for continental tropical Asia, and temperature and soil water anomalies in the west and east parts of maritime tropical Asia, respectively. These findings provide important insights into the response of tropical Asia's vegetation to extreme climate anomalies. Plain Language Summary El Niño is a climate pattern that is associated with warm and dry conditions in tropical forest regions. Significant climatic changes during El Niño thus affect vegetation greenness (i.e., growth, size of canopy, amount of leaves). While an increase in vegetation greenness has been reported in tropical America during El Niño, it remains unclear how vegetation in tropical Asia changes during the period. Here, we used satellite data to investigate changes in vegetation greenness during El Niño in 2015–2016 in tropical Asia. We found a strong increase in vegetation greenness in tropical Asia during this period. The cause of this increase in greenness varied across different parts of tropical Asia. In mainland tropical Asia, sunlight was the main driver, while in maritime Southeast Asia, temperature or soil moisture was the main driver. These findings help provide better understanding of how vegetation in tropical Asia responds to extreme climate events like El Niño. Key Points Tropical Asia experienced strong green‐up during the 2015/16 El Niño, stronger than that of tropical America In continental tropical Asia, green‐up was mostly driven by anomalously high shortwave radiation In maritime tropical Asia, green‐up was primarily driven either by anomalously warmer temperatures or drier soil moisture from the west to east

To quantify wave attenuation by (introduced) Spartina alterniflora vegetation at an exposed macrotidal coast in the Yangtze Estuary, China, wave parameters and water depth were measured during 13 consecutive tides at nine locations ranging from 10 m seaward to 50 m landward of the low marsh edge. During this period, the incident wave height ranged from <0.1 to 1.5 m, the maximum of which is much higher than observed in other marsh areas around the world. Our measurements and calculations showed that the wave attenuation rate per unit distance was 1 to 2 magnitudes higher over the marsh than over an adjacent mudflat. Although the elevation gradient of the marsh margin was significantly higher than that of the adjacent mudflat, more than 80% of wave attenuation was ascribed to the presence of vegetation, suggesting that shoaling effects were of minor importance. On average, waves reaching the marsh were eliminated over a distance of ~ 80 m, although a marsh distance of >100 m was needed before the maximum height waves were fully attenuated during high tides. These attenuation distances were longer than those previously found in American salt marshes, mainly due to the macrotidal and exposed conditions at the present site. The ratio of water depth to plant height showed an inverse correlation with wave attenuation rate, indicating that plant height is a crucial factor determining the efficiency of wave attenuation. Consequently, the tall shoots of the introduced S. alterniflora makes this species much more efficient at attenuating waves than the shorter, native pioneer species in the Yangtze Estuary, and should therefore be considered as a factor in coastal management during the present era of sea-level rise and global change. We also found that wave attenuation across the salt marsh can be predicted using published models when a suitable coefficient is incorporated to account for drag, which varies in place and time due to differences in plant characteristics and abiotic conditions (i.e., bed gradient, initial water depth, and wave action).

The importance of the spin-orbit coupling (SOC) effect in Fe-based superconductors (FeSCs) has recently been under hot debate. Considering the Hund’s coupling-induced electronic correlation, the understanding of the role of SOC in FeSCs is not trivial and is still elusive. Here, through a comprehensive study ofSe77andFe57nuclear magnetic resonance, a nontrivial SOC effect is revealed in the nematic state of FeSe. First, the orbital-dependent spin susceptibility, determined by the anisotropy of theFe57Knight shift, indicates a predominant role from the3dxyorbital, which suggests the coexistence of local and itinerant spin degrees of freedom in the FeSe. Then, we reconfirm that the orbital reconstruction below the nematic transition temperature (Tnem∼90K) happens not only on the3dxzand3dyzorbitals but also on the3dxyorbital, which is beyond a trivial ferro-orbital order picture. Moreover, our results also indicate the development of a coherent coupling between the local and itinerant spin degrees of freedom belowTnem, which is ascribed to a Hund’s coupling-induced electronic crossover on the3dxyorbital. Finally, because of a nontrivial SOC effect, sizable in-plane anisotropy of the spin susceptibility emerges in the nematic state, suggesting a spin-orbital-intertwined nematicity rather than a simple spin- or orbital-driven nematicity. The present work not only reveals a nontrivial SOC effect in the nematic state but also sheds light on the mechanism of nematic transition in FeSe.