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Abstract Developing unconsolidated sandstone reservoirs presents a formidable challenge due to their loose formation, which often triggers alterations in pore parameters and seepage characteristics during water injection processes. This study focuses on a specific reservoir, utilizing micro-CT scanning to examine the intricate relationship between permeability and pore throat structure. Leveraging a random forest model, we establish an empirical formula tailored for high permeability reservoirs. Furthermore, we conduct in-situ CT scanning experiments across various displacement multiples to analyze the pore structure of unconsolidated sandstone cores. The derived relationship curves elucidate the positive correlations between porosity and average pore throat radius with displacement multiples, while revealing a negative correlation with tortuosity. These findings enable the formulation of quantitative formulas for permeability and displacement multiples within the studied block. Such insights prove instrumental in devising effective water injection development strategies, predicting dynamic reserves, and projecting water drive development for analogous unconsolidated sandstone reservoirs undergoing high water cut phases.

Monostatic backscatter has garnered significant interest due to its distinct benefits in low-cost passive sensing. Observing and sensing with backscatter necessitates determining the phase and amplitude of the backscatter channel to identify the state of the target of interest. In the detection of multiple targets, colliding signals can distort the backscatter channel, complicating channel state recovery. It becomes even more challenging when multiple backscattering devices (BDs) are used. This paper proposes a novel channel estimation scheme to tackle the challenge, which is applied to a monostatic backscatter communication system with multiple reader antennas (RAs) and backscatter devices. Specifically, we propose a backscatter communication model and subsequently develop a de-interfering channel estimation framework that considers the ambient interference in the channel, named model-driven unfolded channel estimation (MUCE). To validate the effectiveness and advantages of the MUCE method, it is compared with the least square (LS) algorithm and convolutional neural network (CNN). The results prove that MUCE requires lower computational costs for the same channel estimation performance and achieves an optimal balance between estimation performance and computational expense.

Infill well location optimization poses significant challenges due to its complexity and time-consuming nature. Currently, determining the scope of infill wells relies heavily on field engineers’ experience, often using single indices such as the remaining oil saturation or abundance of remaining oil reserves to evaluate the potential of remaining oil. However, this approach lacks effectiveness in guiding the precise tapping of remaining oil in ultra-high water cut reservoirs. To address this, our study comprehensively considers the factors influencing the recoverable potential of remaining oil in such reservoirs. We characterize the differences in reservoir heterogeneity, scale of recoverable remaining oil reserves, water flooding conditions, and oil–water flow capacity to construct a quantitative evaluation index system for the recoverable potential of remaining oil. Recognizing the varying degrees of influence of different indices on the recoverable potential of remaining oil, we determine the objective weight of each evaluation index by combining an accelerated genetic algorithm with the projection pursuit model. This approach enables the construction of a recoverable potential index for remaining oil and forms a quantitative evaluation method for the recoverable potential of remaining oil in ultra-high water cut reservoirs. Subsequently, we establish a mathematical model for infill well location optimization, integrating and optimizing the infill well location coordinates, well length, well inclination angle, and azimuth angle. Using the main layer sand body of an oilfield in Bohai as a case study, we conducted evaluations of the remaining oil potential and infill well location optimization. Our results demonstrate that the assessment of the remaining oil potential comprehensively characterizes the influence of the reservoir’s physical properties and oil–water diversion capacity on the remaining oil potential across different regional positions. This evaluation can effectively guide the determination of infill well location ranges based on the evaluation results. Furthermore, infill well location optimization can effectively enhance reservoir development outcomes.

Ferrovalley materials are garnering significant interest for their potential roles in advancing information processing and enhancing data storage capabilities. This study utilizes first-principles calculations to determine that the Janus monolayer TiTeCl exhibits the properties of a ferrovalley semiconductor. This material demonstrates valley polarization with a notable valley splitting of 80 meV. Additionally, the Berry curvature has been computed across the first Brillouin zone of the monolayer TiTeCl. The research also highlights that topological phase transitions ranging from ferrovalley and half-valley metals to quantum anomalous Hall effect states can occur in monolayer TiTeCl under compressive strains ranging from −1% to 0%. Throughout these strain changes, monolayer TiTeCl maintains its ferromagnetic coupling. These characteristics make monolayer TiTeCl a promising candidate for the development of new valleytronic and topological devices.

AbstractVisual tracking is an essential process for performing automated cell manipulation tasks. However, Real-time accurate cell tracking in FluidFM is challenging due to probe occlusion during manipulation. This study presents a correlation filtering-based tracking method for real-time, high-precision position tracking of cells and probes. In this method, a target template update strategy is proposed to realize cell tracking under probe occlusion, which abandons the use of pixel values in the occlusion area and reduces the interference of the occlusion area in model learning. Cell tracking and automated manipulation experiments were carried out to validate the proposed method. The Experimental results show that the proposed tracking method can accurately measure the positions of occlusion cells and probe. Furthermore, combined with the precise force control of the FluidFM’s probe, the automated cell Pick & Place experiments was accomplished with high accuracy and robustness.

Abstract Based on the coupling res model of vehicular and road, the influences of surface layer modulus, surface layer thickness and equivalent modulus of elasticity on the spectrum of the acceleration, surface deflection under wheels, and surface strain at the distance of 0.4 m to 0.8 m away from wheels are analyzed. Results show that the fundamental frequency of the road pavement increases with the growth of surface layer modulus and equivalent modulus of elasticity, and decreases with the increase of surface layer thickness. Both surface deflections and surface strains decrease with the increase of equivalent modulus of elasticity as well as surface layer modulus and thickness. Moreover, when the equivalent modulus of elasticity is more than 2500 MPa and surface layer modulus is more than 4000 MPa, surface deflections and surface strains have a little variation with the enhance of the surface layer modulus and equivalent modulus of elasticity. The solution method of the spectrum of the acceleration and equivalent modulus of elasticity, surface deflection under wheels, surface strain at the distance of 0.4 m to 0.8 m away from wheels, and surface deflection based on surface strain are established. The load bearing capacity assessment method of the road pavement based on surface strain and the spectrum of the acceleration is provided. Finally, the feasibility and accuracy of this method is verified by comparing measured values in field testing. The method in this paper provides a theoretical support for the design, construction and maintenance of road engineering.

Aiming at the problem that depression detection is easily affected by subjective factors such as patient willingness, self-awareness, and doctor’s level, as well as inconvenient detection and high cost, a universal detection method with low cost and convenient deployment is proposed. A local optical flow tracking method is adopted, which is realized by eye region detection and optical flow estimation. Then, three experiments are designed to verify the accuracy of the method and the effectiveness of eye movement tracking. The formula for calculating the depression state is proposed, and the eye movement of one normal participant’s elliptical trajectory of the left and right pupils in the horizontal and vertical directions is 44.4805, 42.7013, 29.3571, and 31.1364 mm, respectively. To verify the effectiveness of the proposed method, three example points are selected. Among them, the fixation duration at P1 is 1.87 s, the eye movement direction at P2 and P3 is 1.168°, counterclockwise around the X axis, and the number of fixation times is 46. Finally, 18 normal participants and four depression-positive participants are tested by the exploratory eye movement paradigm. The results show that the accuracy rate of identifying depression patients using the NEF metric method can reach ∼81.8%, which can help quantify the detection of depression and provide the possibility for professionals to remotely diagnose individuals with depression.

Combining Terahertz (THz) and Orbital Angular Momentum (OAM) technologies has great potential in high-speed wireless communication. Theoretically, OAM with different modes has strict orthogonality. The communication capacity of the system will improve significantly if OAM technology is applied to the THz communication system. Thus, the manner to generate a high-quality and dynamically controllable THz-OAM beam has been of significant interest to researchers in related fields. In this study, a double-layer transmissive metasurface that uses 3D printing as the processing method with a low cost and processing difficulty is designed. Note that the height of the unit cell for constructing the metasurface is configurable. As the height changes continuously, the phase of the transmitted wave covers 0～2\begin{document}${\pi }$\end{document} within 90~110 GHz, while the transmittance of the units is always higher than 88%. At 100 GHz, which is fed by a WR-10 standard waveguide horn antenna, OAM beams with different modes are generated by changing the relative rotation angle between the double-layer metasurface. The simulation results show that the metasurface antenna designed in this study can achieve OAM beams of \begin{document}$ l=1, \mathrm{2,3} $\end{document}, and the two-dimensional amplitude and phase results correspond with the characteristics of the corresponding modes. When \begin{document}$ l=1,\mathrm{ }2,\mathrm{ }3 $\end{document}, the OAM beam’s modal purity is 85.4%, 84.9%, and 83.4%, respectively. The measurement results include the results at frequency points of 90, 100, and 110 GHz. The results show that the OAM beam has a high-quality bandwidth of 20 GHz, which indicates that the metasurface antenna designed in this study has a wide working bandwidth at a high frequency and can be applied to high-frequency OAM communication.

To deal with the challenges that the classical Bouc–Wen model fails to precisely characterize amplitude-dependent hysteresis and asymmetric hysteresis, an improved Bouc–Wen model with variable parameters is presented. The proposed model introduces asymmetric terms and parameter functions related to sinusoidal excitation amplitudes into the classical Bouc–Wen model. It has a relatively simple mathematic form and can be easily identified and applied for inverse feedforward compensation in real-time applications. By comparison with the classical Bouc–Wen model and other existing hysteresis models, the superiority of the proposed model has been verified. Furthermore, inverse hysteresis control and hybrid control combining the developed inverse control and proportional-integral feedback control are proposed. Several comparative experiments are conducted on a piezo-actuated micro-scanner. Results demonstrate that inverse control and hybrid control using the improved Bouc–Wen model with variable parameters can achieve better tracking performance and are meaningful in actual trajectory-tracking applications.

In this paper, a simple and effective self-adaptive material interpolation scheme is proposed to solve the numerical instability problem, which may occur in topology optimization considering geometrical nonlinearity when using density-based method. The primary concept of the proposed method revolves around enhancing the deformation resistance of minimum-density or intermediatedensity elements, thus avoiding numerical instability due to excessive distortion of these elements. The proposed self-adaptive material interpolation scheme is based on the power law method, and the stiffness of minimum-density or intermediate-density elements can be adjusted by a single parameter, α. During the optimization process, the parameter α will be changed according to an adaptive adjustment strategy to ensure that elements within the design domain are not excessively distorted, while the mechanical behavior of the structure can be approximated with acceptable accuracy. Numerical examples of minimizing compliance and maximizing displacement of structure are given to prove the validity of the proposed self-adaptive material interpolation scheme.