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Fluorescence microscopic images of cells contain a large number of morphological features that are used as an unbiased source of quantitative information about cell status, through which researchers can extract quantitative information about cells and study the biological phenomena of cells through statistical and analytical analysis. As an important research object of phenotypic analysis, images have a great influence on the research results. Saturation artifacts present in the image result in a loss of grayscale information that does not reveal the true value of fluorescence intensity. From the perspective of data post-processing, we propose a two-stage cell image recovery model based on a generative adversarial network to solve the problem of phenotypic feature loss caused by saturation artifacts. The model is capable of restoring large areas of missing phenotypic features. In the experiment, we adopt the strategy of progressive restoration to improve the robustness of the training effect and add the contextual attention structure to enhance the stability of the restoration effect. We hope to use deep learning methods to mitigate the effects of saturation artifacts to reveal how chemical, genetic, and environmental factors affect cell state, providing an effective tool for studying the field of biological variability and improving image quality in analysis. [ABSTRACT FROM AUTHOR]

This paper proposes a new type of composite box beam combined with cold-formed thin-walled steel and glued laminated timber to develop green building structures while improving the load-carrying capacity of a single steel girder and glued timber girder. Two composite beams composed of laminated timber and Q235 cold-formed thin-walled steel were designed and fabricated. Then, the shear performance test with quadratic loading was carried out to analyze the load carrying capacity, damage modes, and deformation characteristics of the test beams, as well as their influencing factors. Subsequently, a finite element model of the composite beam was established, and the loading mode was the same as that of the test to further study the parameters affecting the shear performance of the composite beam. The results of the study indicate that steel and glued timber in composite beams connected by adhesive bonding can work and deform together under load and each give full play to its material properties, especially the composite beams, which exhibit higher shear strength than a steel or timber beam. The effects of parameters such as steel cross-sectional area, shear span ratio, steel skeleton form, and steel cross-sectional strength on the shear capacity of the composite beams were observed, among which the shear span ratio had the greatest effect on the shear capacity of the composite beams. The shear capacity decreased by 14.3% and 19.5% when the shear span ratio was increased from 1.5 to 2.0 and 2.5, respectively. The shear capacity of the combined composite beams increased by 10.6%, 6.3%, and 5.8% when the thickness was increased from 1.5 mm to 2.0 mm, 2.5 mm, and 3.0 mm, respectively. When the combination of the steel cross-section was a box beam, the overall shear-bearing capacity could be increased by 12% compared with the "I" type composite beam, although its shear stiffness was close to that of the "I" section composite beam. [ABSTRACT FROM AUTHOR]

Rule-based energy management strategies not only make little use of the efficient area of engines and generators but also need to perform better planning in the time domain. This paper proposed a multi-signal vehicle speed prediction model based on the long short-term memory (LSTM) network, improving the accuracy of vehicle speed prediction by considering multiple signals. First, various signals were collected by simulating the vehicle model, and a Pearson correlation analysis was performed on the collected multiple signals in order to improve the model's prediction accurate, and the appropriate signal was selected as the input to the prediction model. The experimental results indicate that the prediction method greatly improves the predictive effect compared with the support vector machine (SVM) vehicle speed prediction method. Secondly, the method was combined with the model predictive control-equivalent consumption strategy (MPC-ECMS) to form a control strategy suitable for power maintenance conditions enabling the equivalent factor to be adjusted adaptively in real-time and the target state of charge (SoC) value to be set. Pontryagin minimum principle (PMP) enables the battery to calculate the range extender output power at each moment. PMP, as the core algorithm of ECMS, is a common real-time optimal control algorithm. Then, taking into account the engine's operating characteristics, the calculated range extender power was filtered to make the engine run smoothly. Finally, hardware-in-the-loop simulation (HIL) was used to verify the model. The simulation results demonstrate that this method uses less fuel than the equivalent fuel consumption minimum strategy (ECMS) by 1.32%, 9.47% when compared to the power-following control strategy, 15.66% when compared to the SVM-MPC-ECMS, and only 3.58% different from the fuel consumption of the dynamic programming (DP) control algorithm. This shows that this energy management approach can significantly improve the overall vehicle fuel economy. [ABSTRACT FROM AUTHOR]

This study aims to improve the vehicle vertical dynamics performance in the sprung and unsprung state for in-wheel-motor-driven electric vehicles (IWMD EVs) while considering the unbalanced electric magnetic force effects. An integrated vibration elimination system (IVES) is developed, containing a dynamic vibration-absorbing structure between the IWM and the suspension. It also includes an active suspension system based on a delay-dependent H ∞ controller. Further, a novel frequency-compatible tire (FCT) model is constructed to improve IVES accuracy. The mechanical-electrical-magnetic coupling effects of IWMD EVs are theoretically analyzed. A virtual prototype for the IVES is created by combining the CATIA, ADAMS, and MatLab/Simulink, resulting in a high-fidelity multi-body model, validating the IVES accuracy and practicability. Simulations for the IVES considered three different suspension structure types and time delay considerations were performed. Analyses in frequency and time domains for the simulation results have shown that the root mean square of sprung mass acceleration and the eccentricity are significantly reduced via the IVES, indicating an improvement in ride comfort and IWM vibration suppression. [ABSTRACT FROM AUTHOR]

In engineering practice, longitudinal brace systems for column-braced systems are designed to resist both horizontal and vertical loads. In previous experimental research on horizontal brace forces for column-braced systems of intermediate height, only vertical loads were considered. Hence, this paper presents a numerical simulation of numerous column-braced systems subjected to horizontal and vertical loads. In the numerical simulation, second-order analysis was adopted, and the Monte Carlo method was used to incorporate the randomness of initial imperfections in the horizontal brace and column. From the finite element (FE) analyses and probability model statistics, the normal probability density equation for intermediate-height horizontal brace forces under horizontal and vertical loads was obtained, and the corresponding design intermediate-height horizontal brace forces were determined and compared with those under vertical loads only. The results indicate that the design intermediate-height horizontal brace forces under horizontal and vertical loads are significantly greater than those under only vertical loads, and that the design intermediate-height horizontal brace forces under horizontal and vertical loads are also greater than the simple superposition results of horizontal loads and intermediate-height horizontal brace forces under only vertical loads. [ABSTRACT FROM AUTHOR]

Intelligence is a direction of development for vehicles and transportation. Accurate vehicle positioning plays a vital role in intelligent driving and transportation. In the case of obstruction or too few satellites, the positioning capability of the Global navigation satellite system (GNSS) will be significantly reduced. To eliminate the effect of unlocalization due to missing GNSS signals, a collaborative multi-vehicle localization scheme based on GNSS and vehicle networks is proposed. The vehicle first estimates the location based on GNSS positioning information and then shares this information with the environmental vehicles through vehicle network communication. The vehicle further integrates the relative position of the ambient vehicle observed by the radar with the ambient vehicle position information obtained by communication. A smaller error estimate of the position of self-vehicle and environmental vehicles is obtained by correcting the positioning of self-vehicle and environmental vehicles. The proposed method is validated by simulating multi-vehicle motion scenarios in both lane change and straight-ahead scenarios. The root-mean-square error of the co-location method is below 0.5 m. The results demonstrate that the combined vehicle network communication approach has higher accuracy than single GNSS positioning in both scenarios. [ABSTRACT FROM AUTHOR]

The NES (nonlinear energy sink) is a new type of nonlinear tuned mass damper that is connected to the shock-absorbing main structure through strong nonlinear stiffness and viscous damping. The vibrational energy in the main structure is transferred to the NES oscillator by means of target energy transfer. A shaking table test of a 1:4 scaled RC (Reinforced Concrete) frame structure model with a new type of NES shock absorber was conducted to study the damping effect of the NES shock absorber, especially for the influence of joint strength and deformation. The NES used in this experiment has a relatively large nonlinear stiffness and a wide vibration absorption frequency band. The variation of reinforcement strains, node failure mode, and structural natural frequency of 1 story and two-layer joints of the model frame structure with NES were studied. The test results showed that NES could effectively reduce the strains of longitudinal reinforcement and stirrup in beams and columns and delay the plastic hinge development at the bottom and the top of the column. The frame model with NES installed has failures at the beam ends and shear failures at the nodes, realizing the seismic mechanism of solid columns and weak beams. Compared with ordinary seismic structures, the NES can effectively reduce the shear stress of concrete at the joints and alleviate the shear failure of joints. The final failure of the NES shock absorbing structure was the yielding of the steel bars at the bottom of the column and the crushing of the concrete at the foot of the column, and the connection between the column foot and the backplane became loose simultaneously. The decreasing rate of the vibration frequency declined due to the NES with varied broadband absorbing capability. It can be seen that the NES shock absorber not only has a good effect on reducing the seismic response of the structure, but more importantly, the damage of the structural nodes is greatly reduced, and therefore, the seismic capacity of the structure improved. [ABSTRACT FROM AUTHOR]