2D Graphene Oxide Films Expand Functionality of Photonic Chips.

On-chip integration of 2D materials with unique structures and properties endow integrated devices with new functionalities and improved performance. With high flexibility in ways to modify its properties and compatibility with integrated platforms, graphene oxide (GO) is an exceptionally attractive 2D material for hybrid integrated photonic chips. Here, by harnessing unique property changes induced by photothermal effects in 2D GO films, novel functionalities beyond the capability of photonic integrated circuits are demonstrated.

Thermo-Optic Response and Optical Bistablility of Integrated High-Index Doped Silica Ring Resonators.

The engineering of thermo-optic effects has found broad applications in integrated photonic devices, facilitating efficient light manipulation to achieve various functionalities. Here, we perform both an experimental characterization and a theoretical analysis of these effects in integrated microring resonators made from high-index doped silica, which have had many applications in integrated photonics and nonlinear optics. By fitting the experimental results with theory, we obtain fundamental parameters that characterize their thermo-optic performance, including the thermo-optic coefficient, the efficiency of the optically induced thermo-optic process, and the thermal conductivity.

The prediction of dynamical quantities in granular avalanches based on graph neural networks.

The study of granular avalanches in rotating drums is not only essential to understanding various complex behaviors of interest in granular media from a scientific perspective; it also has valuable applications in regard to industrial processes and geological catastrophes. Despite decades of research studies on avalanches, a proper understanding of their dynamic properties still remains a great challenge to scientists due to a lack of state-of-the-art techniques. In this study, we accurately predict the avalanche dynamic features of three-dimensional granular materials in rotating drums, by using graph neural networks on the basis of their initial static microstructures alone.

Multi-UAV Cooperative Trajectory Planning Based on the Modified Cheetah Optimization Algorithm.

The capacity for autonomous functionality serves as the fundamental ability and driving force for the cross-generational upgrading of unmanned aerial vehicles (UAVs). With the disruptive transformation of artificial intelligence technology, autonomous trajectory planning based on intelligent algorithms has emerged as a key technique for enhancing UAVs' capacity for autonomous behavior, thus holding significant research value. To address the challenges of UAV trajectory planning in complex 3D environments, this paper proposes a multi-UAV cooperative trajectory-planning method based on a Modified Cheetah Optimization (MCO) algorithm.

Implementation of energy-efficient convolutional neural networks based on kernel-pruned silicon photonics.

Silicon-based optical neural networks offer the prospect of high-performance computing on integrated photonic circuits. However, the scalability of on-chip optical depth networks is restricted by the limited energy and space resources. Here, we present a silicon-based photonic convolutional neural network (PCNN) combined with the kernel pruning, in which the optical convolutional computing core of PCNN is a tunable micro-ring weight bank.

Estimation of Particle Location in Granular Materials Based on Graph Neural Networks.

Particle locations determine the whole structure of a granular system, which is crucial to understanding various anomalous behaviors in glasses and amorphous solids. How to accurately determine the coordinates of each particle in such materials within a short time has always been a challenge. In this paper, we use an improved graph convolutional neural network to estimate the particle locations in two-dimensional photoelastic granular materials purely from the knowledge of the distances for each particle, which can be estimated in advance via a distance estimation algorithm.

Boosted Binary Quantum Classifier via Graphical Kernel.

In terms of the logical structure of data in machine learning (ML), we apply a novel graphical encoding method in quantum computing to build the mapping between feature space of sample data and two-level nested graph state that presents a kind of multi-partite entanglement state. By implementing swap-test circuit on the graphical training states, a binary quantum classifier to large-scale test states is effectively realized in this paper. In addition, for the error classification caused by noise, we further explored the subsequent processing scheme by adjusting the weights so that a strong classifier is formed and its accuracy is greatly boosted.

Dictionary Learning Based Scheme for Adversarial Defense in Continuous-Variable Quantum Key Distribution.

There exist various attack strategies in continuous-variable quantum key distribution (CVQKD) system in practice. Due to the powerful information processing ability of neural networks, they are applied to the detection and classification of attack strategies in CVQKD systems. However, neural networks are vulnerable to adversarial attacks, resulting in the CVQKD system using neural networks also having security risks.

Solvent engineering of MAPbI perovskite thick film for a direct X-ray detector.

The emergence of organic-inorganic hybrid perovskites with a high μτ product and a high absorption coefficient has made it possible to adopt an aerosol-liquid-solid technology for direct X-ray detectors. The film quality from the ALS process is often compromised, especially on the film surface, when deposited in ambient conditions with uncontrolled humidity. Herein we develop a solvent engineering strategy in the ALS process to obtain high-quality MAPbI thick films.

The prediction of contact force networks in granular materials based on graph neural networks.

The contact force network, usually organized inhomogeneously by the inter-particle forces on the bases of the contact network topologies, is essential to the rigidity and stability in amorphous solids. How to capture such a "backbone" is crucial to the understanding of various anomalous properties or behaviors in those materials, which remains a central challenge presently in physics, engineering, or material science. Here, we use a novel graph neural network to predict the contact force network in two-dimensional granular materials under uniaxial compression.

Kalman filter-enabled parameter estimation for simultaneous quantum key distribution and classical communication scheme over a satellite-mediated link.

An accurate estimation of system parameters is of significance for the practical implementation of the simultaneous quantum key distribution and classical communication (SQCC) over a satellite-mediated link when considering the finite-size effect. In this paper, we propose a Kalman filter (KF)-enabled parameter estimation method for the SQCC over a satellite-mediated link. The fast and slow phase drift can be both estimated by using the improved vector KF carrier phase estimation algorithm, and thus the phase estimation error can be tracked in real time and be almost approximate to the theoretical mean square error limit.

Short Forms of the Cross-Cultural (Chinese) Personality Assessment Inventory: Reliability, Validity, and Measurement Invariance Across Gender.

Filling out long questionnaires can be frustrating, unpleasant, and discouraging for respondents to continue. This is why shorter forms of long instruments are preferred, especially when they have comparable reliability and validity. In present study, two short forms of the Cross-cultural (Chinese) Personality Assessment Inventory (CPAI-2) were developed and validated.

Entrepreneur-Region Fit and Entrepreneurial Success in China: The Effect of "Confucian" Personality.

The personality of entrepreneurs is associated with their entrepreneurial success, and the regional personality plays a crucial role in the entrepreneurial ecosystem. Recently, scholars have called for an indigenous personality perspective and combining the personality of entrepreneurs with the regional personality. The current study aimed to investigate the indigenous Confucian personality (e.

Impact of social class on health: The mediating role of health self-management.

Background: Studies have explored the relationship between social class and health for decades. However, the underlying mechanism between the two remains not fully understood. This study aimed to explore whether health self-management had a mediating role between social class and health under the framework of Socio-cultural Self Model.

Continuous-variable quantum key distribution coexisting with classical signals on few-mode fiber.

Continuous-variable quantum key distribution (CVQKD) holds an advantage of well compatibility with classical coherent optical communications. However, there exists a performance trade-off between CVQKD and classical communication on single-mode fiber (SMF) because of the spontaneous Raman scattering. Space-division multiplexing (SDM) technique may provide a feasible way to mitigate this performance trade-off in short-distance communication while CVQKD coexisting with classical signals on few-mode fiber (FMF).

Improving the performance of ghost imaging via measurement-driven framework.

High-quality reconstruction under a low sampling rate is very important for ghost imaging. How to obtain perfect imaging results from the low sampling rate has become a research hotspot in ghost imaging. In this paper, inspired by matrix optimization in compressed sensing, an optimization scheme of speckle patterns via measurement-driven framework is introduced to improve the reconstruction quality of ghost imaging.

A structural approach to vibrational properties ranging from crystals to disordered systems.

Many scientists generally attribute the vibrational anomalies of disordered solids to the structural disorder, which, however, is still under intense debate. Here we conduct simulations on two-dimensional packings with a finite temperature, whose structure is tuned from a crystalline configuration to an amorphous one, then the amorphous from very dense state to a relatively loose state. By measuring the vibrational density of states and the reduced density of states, we clearly observe the evolution of the boson peak with the change of the disorder and volume fractions.

Indoor channel modeling for continuous variable quantum key distribution in the terahertz band.

Continuous-variable quantum key distribution (CVQKD) in an indoor scenario can provide secure wireless access for practical short-distance communications with high rates. However, a suitable channel model for implementing the indoor CVQKD system has not been considered before. Here, we establish an indoor channel model to show the feasibility of CVQKD in terahertz (THz) band.

Virtual zero-photon catalysis for improving continuous-variable quantum key distribution via Gaussian post-selection.

Quantum catalysis is a feasible approach to increase the performance of continuous-variable quantum key distribution (CVQKD), involving the special zero-photon catalysis (ZPC) operation. However, in the practical point of view, the improvement effect of this operation will be limited by the imperfection of the photon detector. In this paper, we show that the ZPC operation at the sender can be simulated by a post-selection method without implementing it in practical devices.

The effect of ecological environmental changes and mollusciciding on snail intermediate host of Schistosoma in Qianjiang city of China from 1985 to 2015.

Background: Schistosomiasis remains prevalent in Africa, Asia and South America with an estimated burden of 1.9 million disability-adjusted life years in 2016. Targeting snails as a key to success for schistosomiasis control has been widely approved, but the long-term quantitative effects of interventions on snail control that would inform and improve future control programmes are unclear.

Practical Security Analysis of Reference Pulses for Continuous-Variable Quantum Key Distribution.

By manipulating the reference pulses amplitude, a security vulnerability is caused by self-reference continuous-variable quantum key distribution. In this paper, we formalize an attack strategy for reference pulses, showing that the proposed attack can compromise the practical security of CVQKD protocol. In this scheme, before the beam splitter attack, Eve intercepts the reference pulses emitted by Alice, using Bayesian algorithm to estimate phase shifts.

Freeing the Polarons to Facilitate Charge Transport in BiVO from Oxygen Vacancies with an Oxidative 2D Precursor.

The BiVO photoelectrochemical (PEC) electrode in tandem with a photovoltaic (PV) cell has shown great potential to become a compact and cost-efficient device for solar hydrogen generation. However, the PEC part is still facing problems such as the poor charge transport efficiency owing to the drag of oxygen vacancy bound polarons. In the present work, to effectively suppress oxygen vacancy formation, a new route has been developed to synthesize BiVO photoanodes by using a highly oxidative two-dimensional (2D) precursor, bismuth oxyiodate (BiOIO ), as an internal oxidant.

Optical frequency comb-based multichannel parallel continuous-variable quantum key distribution.

Continuous-variable quantum key distribution (CVQKD) provides an approach for secure communication in optical fiber communication systems. However, its practical implementation has been hindered by low secret key bit rates that are usually limited to several bits/s to hundreds of kbits/s at distances of more than 25 kilometers. In this paper, we use a pair of optical frequency combs (OFCs) for both multiple parallel transmission and coherent reception, which assign multiple sub-channels involving multiple independent secret keys in a single fiber to increase the key bit rate.

Enhancing photoelectrochemical water splitting by combining work function tuning and heterojunction engineering.

We herein demonstrate the unusual effectiveness of two strategies in combination to enhance photoelectrochemical water splitting. First, the work function adjustment via molybdenum (Mo) doping significantly reduces the interfacial energy loss and increases the open-circuit photovoltage of bismuth vanadate (BiVO) photoelectrochemical cells. Second, the creation and optimization of the heterojunction of boron (B) doping carbon nitride (CN) and Mo doping BiVO to enforce directional charge transfer, accomplished by work function adjustment via B doping for CN, substantially boost the charge separation of photo-generated electron-hole pairs at the B-CN and Mo-BiVO interface.

Improvement of self-referenced continuous-variable quantum key distribution with quantum photon catalysis.

Quantum photon-catalysis operations can be utilized for improving the performance of continuous-variable quantum key distribution (CVQKD) systems. Motivated by characteristics of quantum photon-catalysis operations that can be implemented by the existing technologies, we consider the performance improvement of self-referenced (SR) CVQKD involving zero-photon catalysis operation. We find that the zero-photon catalysis can be regarded as a noiseless attenuation, and the numerical simulations show that the zero-photon catalysis (ZPC)-based SR-CVQKD scheme outperforms the original SR-CVQKD scheme.