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[Objective] To improve the drying quality of pumpkins. [Methods] This study conducted experiments on hot air drying, vacuum drying, and combined hot air-vacuum drying, these drying characteristics were evaluated and compared based on unit energy consumption, rehydration ratio, and color difference indicators. Combining BP neural network model with genetic algorithm, combined with entropy weight and weighted scoring method, a multi-objective comprehensive optimization was carried out for the combined hot air-vacuum drying of pumpkins. [Results] Under the same conditions, the highest drying efficiency was hot air drying; And the findings revealed that at drying temperatures was 55 ℃, with a moisture content transition point of 30%, the combined drying method reduced the drying time by 52.63%, compared to vacuum drying. The lowest unit energy consumption was vacuum drying; The worst rehydration performance was hot air drying. The best color was vacuum drying. The optimal drying parameters determined by the genetic algorithm combined with a BP neural network model were a hot air drying temperature of 65 ℃, conversion point moisture content of 50%, and vacuum drying temperature of 56.050 9 ℃. Verification experiments demonstrated that the average relative errors between the genetic algorithm optimized values and the experimental values for unit energy consumption, rehydration ratio, and color difference were 2.5%, 5.53%, and 4.84%, respectively, all lower than 6%. [Conclusion] The combined hot air-vacuum drying of pumpkin integrates the advantages of both hot air drying and vacuum drying, and combined with BP neural network genetic algorithm model can optimize the process parameters for pumpkin hot air vacuum drying.

Identifying key road segments and prioritizing their protection to enhance the resilience of road networks against crisis events remains a pressing issue. In this paper, complex network theory is adopted to determine the importance ranking of road segments and analyse how to select the road segments that need to be rehabilitated in the case of insufficient budget. This study will provide three different methods to assess the importance of road segments, and with the help of user equilibrium model for traffic demand allocation, calculate the system travel time after rehabilitation to evaluate, compare, and analyse different rehabilitation schemes, and then get the rehabilitation scheme with better performance. Meanwhile, it is investigated whether the optimal road segment rehabilitation combination will change under different budget levels. The results of the case study finally show that the rehabilitation set determined by the Clustering Coefficient and the betweenness is better, which can provide practical guidance on how to select the prioritized rehabilitation segments.

A flapping foil, which mimics the flapping wings of birds and the locomotion of aquatic organisms, is an alternative to a conventional turbine for the harvesting of renewable energy from ubiquitous flows in the atmosphere, oceans, and rivers. In this work, the energy harvesting performance of flapping foils with attached flaps at the trailing edge is numerically studied by using an immersed boundary–lattice Boltzmann method (IB-LBM) at a Reynolds number of 1100. Three different configurations are considered, namely, a clean NACA0015 foil, a NACA0015 foil with a single flap, and a NACA0015 foil with two symmetric flaps. The results show that the flap attached to the trailing edge is able to enhance the energy harvesting efficiency, and the two symmetric flaps can achieve more enhancements than its single-flap counterpart. The mechanism of such enhancements is attributed the separation of the interactions of vortexes generated at the upper and bottom surfaces of the foil. To further obtain the optimal configurations of the two symmetric flaps, the angle between the two flaps (α) and the length ( l f ) of the flap are systematically studied. The results show that the optimal energy harvesting performance is achieved at α = 60 ∘ and l f = 0.1 c (c denotes the chord length of the foil). Compared with the baseline case, namely, the clean NACA foil, the optimal configuration can achieve an improvement of efficiency up to 19.94%. This study presents a strategy by adding two symmetric flaps at the trailing edge of the foil to enhance the energy harvesting performance of a flapping foil, which contributes to advancing the development of simple and efficient clean energy harvesting by using a flapping foil. [ABSTRACT FROM AUTHOR]

To locate all local optimum of the black box function, such as the simulation function, a method based on fitness landscape analysis is proposed. Firstly, the fitness distance correlation (FDC) is modified according to the characteristics of our problem, and the relationship between the modified FDC and the roughness grade of the fitness landscape is explored. Based on the relationship, an FDC based repeated spitt region method (FRsR) is designed to breakdown the whose feastbee region into several acceptable sub-region according to the FDC value, and a certain number of initial search points are assigned in each sub-region based on the FDC value of the sub-region, followed by an optimization procedure using the pattern search algorithm. Experimental results show that the proposed method can locate all local optimum with feuer initial points, and comparison study shows that it performs better than traditional methods, such as the uniformly generating initial points method and other known methods, both in speed and in quality of the solution. [ABSTRACT FROM AUTHOR]

A wireless remote‐query disposable magnetoelastic biosensor is developed for the assay of acid phosphatase (ACP). The sensor was fabricated by applying a layer of pH‐sensitive polymer to a magnetoelastic ribbon and, on top of it, a sensing film containing bovine serum albumin and adenosine‐5′‐monophosphate (5′‐AMP), the substrate of ACP. In response to an externally applied time‐varying magnetic field, the magnetoelastic sensor mechanically vibrates at a characteristic frequency that is inversely dependent on the mass of the attached film. Because the magnetoelastic sensor is magnetostrictive, the mechanical vibrations of the sensor launch magnetic flux that can be detected remotely from the sensor using a pick‐up coil. The ACP‐catalyzed hydrolysis of 5′‐AMP decreases the solution pH, resulting in the polymer shrinking and, consequently, the resonance frequency of the magnetoelastic sensor increasing. The experimental condition was optimized to be 37°C, in 2.5 mM sodium citrate buffer solution (pH 6.5). Using citrate as buffer can enhance the ACP activity, partly offsetting the effect of the buffer capacity on the sensitivity. The kinetic parameter were measured to be: 1.64×10–3 M (Michaelis constant) and 130 Hz/min (maximum initial rate). This work provides a remote enzymatic assay of ACP. The relative standard deviation in the measurements of six sensors in parallel is 3.4%. The proposed sensor can determine 0.2∼⃒1.2 U/ml of ACP. [ABSTRACT FROM AUTHOR]

The social force model is widely used in the field of pedestrian modeling and simulation. However, it can only be applied to simple scenarios. When there are many obstacles in the environment, and the pedestrian cannot see the goal, the model will lead to problems such as obstacle penetrating and trajectory oscillation. We proposed a hybrid model composed of tactical layer and operation layer. The core concept of the tactical layer is detour point. We constructed a computational geometry method to find the detour point based on the criterion of shortest path, and solved the multiple occlusion problem. Then we designed a progressive route planning algorithm to guild pedestrian's movement. Finally, a simulation system is developed to verify the proposed model. The simulation results show that, both in single obstacle and multiple obstacle environments, pedestrian can avoid the obstacles naturally and the trajectory is realistic and reasonable. [ABSTRACT FROM AUTHOR]