Spatial variation in aragonite saturation state and the influencing factors in Jiaozhou Bay, China

Both natural processes and human activities affect seawater calcium carbonate saturation state (Ωarag), while the mechanisms are still far from being clearly understood. This study analysed the seawater surface Ωarag during summer and winter in Jiaozhou Bay (JZB), China, based on two cruises observations performed in January and June 2017. The ranges of Ωarag values were 1.55~2.92 in summer and 1.62~2.15 in winter. Regression analyses were conducted to identify the drivers of the change of Ωarag distribution, and then the relative contributions of temperature, mixing processes and biological processes to the spatial differences in Ωarag were evaluated by introducing the difference between total alkalinity (TA) and dissolved inorganic carbon (DIC) as a proxy for Ωarag. The results showed that biological processes were the main factor affecting the spatial differences in Ωarag, with relative contributions of 70% in summer and 50% in winter. The contributions of temperature (25% in summer and 20% in winter) and the mixing processes (5% in summer and 30% in winter) were lower. The increasing urbanization in offshore areas can further worsen acidification, therefore environmental protection in both offshore and onshore is needed

A Robust Quantum Random Access Memory

A "bucket brigade" architecture for a quantum random memory of $N=2^n$ memory cells needs $n(n+5)/2$ times of quantum manipulation on control circuit nodes per memory call. Here we propose a scheme, in which only average $n/2$ times manipulation is required to accomplish a memory call. This scheme may significantly decrease the time spent on a memory call and the average overall error rate per memory call. A physical implementation scheme for storing an arbitrary state in a selected memory cell followed by reading it out is discussed.Comment: 5 pages, 3 figure

Research on Face Recognition Based on Embedded System

Because a number of image feature data to store, complex calculation to execute during the face recognition, therefore the face recognition process was realized only by PCs with high performance. In this paper, the OpenCV facial Haar-like features were used to identify face region; the Principal Component Analysis (PCA) was employed in quick extraction of face features and the Euclidean Distance was also adopted in face recognition; as thus, data amount and computational complexity would be reduced effectively in face recognition, and the face recognition could be carried out on embedded platform. Finally, based on Tiny6410 embedded platform, a set of embedded face recognition systems was constructed. The test results showed that the system has stable operation and high recognition rate can be used in portable and mobile identification and authentication

On Fast Simulation of Dynamical System with Neural Vector Enhanced Numerical Solver

The large-scale simulation of dynamical systems is critical in numerous scientific and engineering disciplines. However, traditional numerical solvers are limited by the choice of step sizes when estimating integration, resulting in a trade-off between accuracy and computational efficiency. To address this challenge, we introduce a deep learning-based corrector called Neural Vector (NeurVec), which can compensate for integration errors and enable larger time step sizes in simulations. Our extensive experiments on a variety of complex dynamical system benchmarks demonstrate that NeurVec exhibits remarkable generalization capability on a continuous phase space, even when trained using limited and discrete data. NeurVec significantly accelerates traditional solvers, achieving speeds tens to hundreds of times faster while maintaining high levels of accuracy and stability. Moreover, NeurVec's simple-yet-effective design, combined with its ease of implementation, has the potential to establish a new paradigm for fast-solving differential equations based on deep learning.Comment: Accepted by Scientific Repor

Study on the extraction method of transverse open crack’s information

For the fault rotor – bearing system caused by transverse open crack. The dynamic model of crack rotor system is established by the crack compliance coefficient matrix which is derived from the stress intensity factor and strain energy density function. The stiffness matrix of rotor system which contains transverse crack faults is different from the health rotor. So the surplus dynamics equation of cracked rotor system can be deduced by comparing the dynamics equations of the crack fault and health rotor system, which is on the basis of getting the compliance coefficient matrix. Furthermore, the information of open crack’s location and crack’s depth can be extracted from the vibration signal by analyzing force condition on both ends of the shaft segment where crack exist and combining with the residual dynamic equation. The extraction method for crack information only needs to collect the vibration signals of the three different node positions under two different speeds. Finally, the feasibility of the method can be verified with simulation and experiment

6-(4-Fluoro­pheneth­yl)-7-imino-3-phenyl-2,3,6,7-tetra­hydro-1,3-thia­zolo[4,5-d]pyrimidine-2-thione

In the title compound, C19H15FN4S2, the mean plane of the thia­zolopyrimidine makes a dihedral angle of 77.6 (1)° with the attached phenyl ring. The crystal packing is stabilized by inter­molecular C—H⋯N hydrogen bonds and weak C—H—π stacking inter­actions