Search

This paper proposes an analytical delay propagation model for single railway lines based on the max‐plus algebra theory. The scheduling measures taken by dispatchers, including re‐timing and re‐ordering, will be incorporated into our delay propagation model using a matrix transformation method. An analysis of delay propagation under some typical emergencies such as segment blockages and train speed limitation is performed. Numerical simulations show that the proposed train delay propagation model can predict emergency‐induced train delays under different scheduling strategies, thus may give a guidance to improve the traffic management. In the high‐speed railway train system, the scheduling measures taken by dispatchers, such as re‐timing and re‐ordering, can be formulated as a delay propagation model using a matrix transformation method.

The Nondestructive estimation method of nitrogen content level of rubber tree foliage was investigated utilizing near infrared (NIR) spectroscopy and Grünwald-Letnikov fractional calculus. Four models, including partial least squares discriminant analysis (PLS-DA), support vector machine (SVM), extreme learning machine (ELM) and convolutional neural networks (CNN) are applied to construct the nitrogen estimation model. The results show that models established by 0.6-order or 1.6-order spectra achieved better performance than models with integer-order spectra. Afterward, the successive projections algorithm (SPA) is applied to reduce the number of variables, which is critical for developing portable nitrogen-level detector devices for rubber trees. The PLS-DA method achieved the best performance with an optimal recognition rate (97.73%) using the 1.6-order spectra. The results suggest that nitrogen content of rubber trees could be reliably estimated by fractional calculus processed NIR spectra. The method proposed here has a wide range of applicability and can provide more useful information for NIR spectral analysis in agriculture as well as other fields.

Natural disasters or railway malfunctions usually cause some emergencies in high-speed railway operation. How to reduce the overall influence caused by such emergencies on the railway network is an important topic of high-speed railway operation. In this paper, we proposes a distributed scheduling approach to the railway network with fine granularity in case of emergencies, which handles the rescheduling problem of trains in each local area rather than in the global railway network. A mixed integer linear programming (MILP) model is proposed based on safety and timeliness of train operation. We also consider the constraints of station and line capacity to minimize traffic delays caused by emergencies on the overall railway network. In the case of small and medium-sized road networks, the model can be directly solved by commercial optimization software, which satisfies the real-time requirement.

Quality of Experience (QoE) models need good generalization that necessitates sufficient amount of user-labeled datasets associated with measurements related to underlying QoE factors. However, obtaining QoE datasets is often costly, since they are preferably collected from many subjects with diverse background, and eventually dataset sizes and representations are limited. Models can be improved by sharing and merging those collected local datasets, however regulations such as GDPR make data sharing difficult, as those local user datasets might contain sensitive information about the subjects. A privacy-preserving machine learning approach such as Federated Learning (FL) is a potential candidate that enables sharing of QoE data models between collaborators without exposing ground truth, but only by means of sharing the securely aggregated form of extracted model parameters. While FL can enable a seamless QoE model management, if collaborators do not have the same level of data quality, more iterations of information sharing over a communication channel might be necessary for models to reach an acceptable accuracy. In this paper, we present an ensemble based Bayesian synthetic data generation method for FL, LOO (Leave-One-Out), which reduces the training time by 30% and the network footprint in the communication channel by 60%.

Machine-transplanted rice with side-deep fertilization (MRSF) is a recommended strategy to reduce labor cost and nitrogen (N) fertilizer loss in sustainable double-cropping rice production in China. However, the effects of MRSF on double-cropping rice profitability and agronomic traits are unclear. Here, experiments were conducted in two sites at Dongting Lake to determine the yield and economic benefits of MRSF and the optimal N application rate. Six fertilization treatments for early- and late-season rice at various N rates (0/0, 90/99, 105/116, 120/132, 135/149, and 150/165 kg N ha−1) were tested. The grain yield of early-season rice (ESR) was the highest (8.7 t ha−1) under 70 % deep fertilization (DF), whereas that of late-season rice (LSR) was the highest (6.1 t ha−1) under 80 % DF treatment in Miluo. The grain yield of ESR and LSR (7.5 and 7.9 t ha−1, respectively) were the highest under 80 % DF treatment in Yiyang. Compared with conventional fertilization (CF), MRSF significantly enhanced grain yield by 0.5 %–20.2 % and 5.3 %–15.0 % in Miluo and Yiyang, respectively. The high grain yield under MRSF can be attributed to higher leaf area index, chlorophyll content, nutrient uptake, biomass accumulation, and spikelet number per m2. Relative to CF, MRSF increased the panicle bearing tiller rate by 8.4 %–24.6 % (Miluo) and 3.3 %–12.2 % (Yiyang), thereby improving dry matter accumulation and nutrient uptake. Furthermore, the economic benefit under MRSF increased by 9.9 %–31.8 % (Miluo) and 15.0 %–25.7 % (Yiyang) compared with that under CF. N reduction in the MRSF treatments resulted in fewer effective panicles than the 100 % DF treatment. Improved yield and nutrient uptake in double-cropping rice were associated with deep fertilizer placement rather than N application rate. The number of filled grains per panicle had the strongest influence on ESR and LSR grain yield. Overall, MRSF is recommended as an alternative approach to increase grain yield, profitability, and agronomic traits while lowering the N application rate in the double-cropped rice systems near Dongting Lake, southern China.

Glutamate transporter-1 (GLT-1), a major glutamate transporter expressed in astrocytes, takes up excess glutamate from the micro-environment in order to prevent excitotoxicity. Drugs that increase GLT-1 expression may have therapeutic effects in disorders associated with neuronal excitotoxicity. 2,3,4',5-tetrahydroxystilbene 2-O-β-D-glucoside (TSG), a monomer of stilbene from polygonummultiflorum, exerts neuroprotection in a range of experimental models such as Alzheimer's disease and brain ischemia. In this study, we evaluated the effect of TSG on GLT-1 protein expression in mouse primary-cultured astrocytes. Results showed that TSG markedly increased the GLT-1 protein expression level in mouse primary-cultured astrocytes in a dose- and time-dependent manner, and this increase was mediated by the activation of protein kinase B (Akt) but not by the activation of extracellular signal-regulated protein kinase 1/2. Furthermore, inhibition of cAMP response element-binding protein, but not nuclear factor kappa B, abolished the TSG-mediated increase in GLT-1 protein expression in cultured astrocytes. Collectively, these findings may provide novel insights into the mechanism for TSG in neuroprotection, and would help search new agents targeting neurodegenerative disorders associated with impaired astrocytic glutamate transporters.

Biological preservatives containing live microorganisms are environmentally friendly and non-toxic substances used to preserve the quality of fresh fruits. This study investigated whether a composite biological preservative containing live Lactobacillus plantarum (designated as DN003) could preserve the quality of postharvest litchi fruits at high temperature and in humid environment. Postharvest litchi fruits were briefly soaked in DN003, then dried and stored at 29-33°C with 95-98% relative humidity; prochloraz treatment was included as positive control and non-treatment as negative control. In comparison with negative control group, litchi fruits in both DN003-treated and positive control groups better retained their appearance with lower polyphenol oxidase and peroxidase activities and showed higher concentrations of vitamin C, titratable acids, and total sugar content. These data demonstrated that the new composite biological preservative containing L. plantarum is promising to be used in the preservation of postharvest litchi fruit, particularly in high-temperature and humid environment.

Ammonia (NH3) volatilization contributes to major nitrogen (N) fertilizer loss in rice fields. Deep fertilization can effectively mitigate NH3 volatilization and increase N use efficiency (NUE) in agroecosystems. However, the effects of machine-transplanted rice with side-deep fertilization (MRSF) on NUE and NH3 volatilization from paddy fields in double-cropping systems are still unknown. In this study, a field experiment was conducted with double-cropping rice fields in two regions in Southern China (Miluo and Yiyang). NH3 volatilization was measured during the rice growing seasons using the continuous airflow enclosed chamber method under different N application rates with MRSF treatments. The results show that NH3 fluxes in rice soil subjected to different N application rates varied. The ratio of total NH3 loss to applied N by conventional fertilization (CF) ranged from 41.2 to 45.3% in the early-season rice (ESR) and from 44.9 to 45.2% in the late-season rice (LSR). Unlike CF treatment, MRSF treatments significantly reduced the cumulative NH3 loss by approximately 24.8–26.9 % in Miluo and 20.1–20.8 % in Yiyang for ESR and by 18.6–23.0 % in Miluo and 20.2–21.8 % in Yiyang for LSR. MRSF treatments increased the content of available N in the soil by 0.2–8.8 % and 0.7–6.6 % in Miluo and Yiyang, respectively. Moreover, this mitigation effect is expected to be more effective with lower N application rates. An NH3 accumulation model described by the Elovich equation was established over the study period; notably, the field observations fitted the calculated values well. MRSF with a 20–30 % reduction in N application rate yielded a higher NUE in terms of N recovery efficiency (NRE), by 11.5–27.9 % and 11.7–23.7 % in Miluo and 8.2–17.0 % and 7.0–25.8 % in Yiyang relative to that of the CF treatment in ESR and LSR, respectively. Overall, MRSF can reduce the N loss through NH3 volatilization while improving content of available N in the soil and NUE; therefore, further maximizing the yield and simplifying fertilization practices for a cleaner rice production in Southern China.

Applying deep reinforcement learning (RL) on real systems suffers from slow data sampling. We propose an enhanced generative adversarial network (EGAN) to initialize an RL agent in order to achieve faster learning. The EGAN utilizes the relation between states and actions to enhance the quality of data samples generated by a GAN. Pre-training the agent with the EGAN shows a steeper learning curve with a 20% improvement of training time in the beginning of learning, compared to no pre-training, and an improvement compared to training with GAN by about 5% with smaller variations. For real time systems with sparse and slow data sampling the EGAN could be used to speed up the early phases of the training process.

The aim of this research is to investigate the effect of lactic acid bacteria (LAB) on color stability of fresh pork. Of the seven LAB strains isolated from the Chinese dry-cured hams, H strain was identified as Lactobacillus salivarius (CCTCC M2010374) by serial biochemical tests and 16S rRNA analysis. The fresh pork samples were immersed in the H strain and Lactobacillus fermentum extracts for 1min after ultrasonic cells disruption and samples immersed in sterile 0.9% (m/V) saline was served as a control group, then samples were vacuum packaged and stored at 4°C. Nitrate oxide synthase (NOS) and metmyoglobin (MetMb) reductase were found in the cells extracts of H strain. After 6 days of storage, H strain group was found to be associated with the highest CIE a* values (P

Because of the development of the technology, people's material and cultural conditions is developing faster and faster, life conditions is getting better and better living conditions. However, the improvement of inherent virtue of people has failed to match the growing material and cultural criteria. Many parents are busy in work, leading to many children cannot obtain a culture etiquette and upbringing at an early age, children cannot treat people how to do things correctly, this is more harm than good for children's emotional intelligence development and future life. But the growing material conditions has created a possibility for the popularity of computer games, children can come into contact with computers and other modern electronic products when they are very small, which also getting children premature contact with, even hooked on computer games. So game developers can combine computer games with children etiquette education, let the children play games, but also by the influence of culture and etiquette. This game is arranged two scenes which are sitting room scene and bus scene, the player can choose a scene casually. After entering the game scenes, there will be a plot unfolds, players need to react differently and politely according to different scenarios before clearance. Meanwhile, the game also leave interface for future game developers, the child's answer can be speech recognized in the future.

Recently the mobile games are becoming more and more popular, that is the reason why more and more people develop 2D game running on IOS platform. Using 2D development tools of Unity is the best choice, including colliders, triggers, and sprites. Nowadays, games in the market are simple, but that leads to a bad influence that such games can't exercise the mind. My idea is that people's mind could be exercised during the entertainment, this game needs players to predict the actions according to players' memory. It needs player to remember the role's regulation and predict the next move, so that to make the mind at the excited state. To improve the playability and difficulty of the game, I developed some scripts to make the baby move regularly and automatically. The regulation of the movement will change in a random time, which makes the game harder. Finally, I use touch control in this game, and release it in IOS platform.

It is a well known fact that the linear arboricity of ak-regular graph is [(k+1)/2] fork=3,4. In this paper, we prove that if the number of edges of ak-regular circulant is divisible by [(k+1)/2], then its edge set can be partitioned into [(k+1)/2] isomorphic linear forests, fork=3,4.