Pontryagin's Minimum Principle based model predictive control of energy management for a plug-in hybrid electric bus

To improve computational efficiency of energy management strategies for plug-in hybrid electric vehicles (PHEVs), this paper proposes a stochastic model predictive controller (MPC) based on Pontryagin’s Minimum Principle (PMP), which differs from widely used dynamic programming (DP)-based predictive methods. First, short-time speed forecasting is achieved using a Markov chain model, based on real-world driving cycles. The PMP- and DP-based MPCs are compared under four preview horizons (5 s, 10 s, 15 s and 20 s), and the results show that the computational time of the DP-MPC is almost four times of that in the PMP-MPC. Moreover, the influence of predication horizon length on computational time and energy consumption is examined. Given a preview horizon of 5 s, the PMP-MPC holds a total energy consumption cost of 7.80 USD and computational time per second of 0.0130 s. When the preview horizon increases to 20 s, the total cost is 7.77 USD with the computational time per second increasing to 0.0502 s. Finally, DP, PMP, and rule-based strategies are contrasted to the PMP-MPC method, further demonstrating the promising performance and computational efficiency of the proposed methodology

Investigation of bio-aerosol dispersion in a tunnel-ventilated poultry house

Bio-aerosol concentrations in poultry houses must be controlled to provide adequate air quality for both birds and workers. High concentrations of airborne bio-aerosols would affect the environmental sustainability of the production and create environmental hazards to the surroundings via the ventilation systems. Previous studies demonstrate that several factors including the age of the birds, the housing configuration, the humidity and temperature would strongly affect the indoor concentration of bio-aerosols. However, limited studies are performed in the literature to investigate the bio-aerosol dispersion pattern inside poultry buildings. In order to fill a gap of the understanding of the bio-aerosol dispersion behavior, experimental measurements of the indoor bio-aerosol distribution are performed in a tunnel-ventilated poultry house in this paper. Meanwhile a three-dimensional computational fluid dynamics (CFD) model is built and validated to further investigate the effect of flow pattern, turbulence and vortex on the dispersion and deposition of the bio-aerosols. Furthermore, bio-aerosols with various diameters are also examined in the CFD model. It is found that higher concentrations of bio-aerosols are detected at the rear part of the house and strong turbulent flow resulting from the ventilation inlets enhances the diffusion and dispersion of bio-aerosols. Local vortex or disturbed flow is responsible for higher local concentration due to the re-suspension of settled bio-aerosols, which suggests that careful attentions should be paid to these locations during cleaning and disinfection. Results from present study contribute to the optimization of design and operation of the poultry houses from the standing point of reducing airborne bio-aerosol concentrations

Model predictive energy management for plug-in hybrid electric vehicles considering optimal battery depth of discharge

When developing an energy management strategy (EMS) including a battery aging model for plug-in hybrid electric vehicles, the trade-off between the energy consumption cost (ECC) and the equivalent battery life loss cost (EBLLC) should be considered to minimize the total cost of both and improve the life cycle value. Unlike EMSs with a lower State of Charge (SOC) boundary value given in advance, this paper proposes a model predictive control of EMS based on an optimal battery depth of discharge (DOD) for a minimum sum of ECC and EBLLC. First, the optimal DOD is identified using Pontryagin's Minimum Principle and shooting method. Then a reference SOC is constructed with the optimal DOD, and a model predictive controller (MPC) in which the conflict between the ECC and EBLC is optimized in a moving horizon is implemented. The proposed EMS is examined by real-world driving cycles under different preview horizons, and the results indicate that MPCs with a battery aging model lower the total cost by 1.65%, 1.29% and 1.38%, respectively, for three preview horizons (5, 10 and 15 s) under a city bus route of about 70 km, compared to those unaware of battery aging. Meanwhile, global optimization algorithms like the dynamic programming and Pontryagin's Minimum Principle, as well as a rule-based method, are compared with the predictive controller, in terms of computational expense and accuracy

Genome-wide Association Study (GWAS) of mesocotyl elongation based on re-sequencing approach in rice

Annotation of candidate genes anchored by associated SNPs. (XLSX 34 kb

16S rRNA gene sequencing reveals the correlation between the gut microbiota and the susceptibility to pathological scars

The gut microbiome profile in patients with pathological scars remains rarely known, especially those patients who are susceptible to pathological scars. Previous studies demonstrated that gut microbial dysbiosis can promote the development of a series of diseases via the interaction between gut microbiota and host. The current study aimed to explore the gut microbiota of patients who are prone to suffer from pathological scars. 35 patients with pathological scars (PS group) and 40 patients with normal scars (NS group) were recruited for collection of fecal samples to sequence the 16S ribosomal RNA (16S rRNA) V3-V4 region of gut microbiota. Alpha diversity of gut microbiota showed a significant difference between NS group and PS group, and beta diversity indicated that the composition of gut microbiota in NS and PS participants was different, which implied that dysbiosis exhibits in patients who are susceptible to pathological scars. Based on phylum, genus, species levels, we demonstrated that the changing in some gut microbiota (Firmicutes; Bacteroides; Escherichia coli, etc.) may contribute to the occurrence or development of pathological scars. Moreover, the interaction network of gut microbiota in NS and PS group clearly revealed the different interaction model of each group. Our study has preliminary confirmed that dysbiosis exhibits in patients who are susceptible to pathological scars, and provide a new insight regarding the role of the gut microbiome in PS development and progression

Synthesis and White-Light Emission of ZnO/HfO2: Eu Nanocables

ZnO/HfO2:Eu nanocables were prepared by radio frequency sputtering with electrospun ZnO nanofibers as cores. The well-crystallized ZnO/HfO2:Eu nanocables showed a uniform intact core–shell structure, which consisted of a hexagonal ZnO core and a monoclinic HfO2 shell. The photoluminescence properties of the samples were characterized. A white-light band emission consisted of blue, green, and red emissions was observed in the nanocables. The blue and green emissions can be attributed to the zinc vacancy and oxygen vacancy defects in ZnO/HfO2:Eu nanocables, and the yellow–red emissions are derived from the inner 4f-shell transitions of corresponding Eu3+ ions in HfO2:Eu shells. Enhanced white-light emission was observed in the nanocables. The enhancement of the emission is ascribed to the structural changes after coaxial synthesis

Data_Sheet_1_Justifications of emotional responses to eliciting situations: A narratological approach to the CAD hypothesis.docx

The CAD hypothesis holds that there is mapping between the three moral emotions (contempt, anger and disgust) and the three moral codes of community, autonomy and divinity. Different from previous designs to establish correlations between emotions and eliciting situations which instantiate moral codes, this paper takes a narratological approach to the CAD hypothesis by examining the relationships between the three moral emotions and moral judgment relating to the three moral codes in the context of eliciting situations. First, similarity data pertaining to eliciting situations were collected by using the Order k/n-1 with fixed K method. Second, the participants were instructed to write down both their responses and justifications of their responses to the eliciting situations. A narratological analysis of the justifications of responses show that they vary along three variables: narrator, character, and basis (mostly in the form of moral judgment). The descriptive statistics of participants’ responses and of their justifications show that more than a half of responses are in the categories of anger (24.8%), disgust (20.7), and contempt (7.7%) and that about 60% of justifications contain a component of moral judgment based on the three moral codes of autonomy (30.03%), divinity (18.1), and community (11.82%). Correspondence analyses among eliciting situations, emotional responses and the three variables of justifications, together with results from the Multidimensional Scaling analysis of the similarity data, show that the CAD hypothesis is largely supported if mappings are set between the emotions in question and moral judgment concerning the eliciting situations (the basis variable of justification) and that the hypothesis is conditioned by the variable of character.</p