Optimal Design of Energy System Based on the Forecasting Data with Particle Swarm Optimization

Renewable energy source has developed rapidly and attracted considerable attention. The integration of renewable energy into the energy supply chain requires precise forecast of the output of energy supply chain, thereby reducing energy resource waste and greenhouse gas emissions. In this study, a coupled model system is developed to forecast energy supply chain for the design optimization of distributed energy system, which can be divided into two parts. In the first part, long short-term memory (LSTM) and particle swarm optimization algorithm (PSO) contribute to energy supply chain forecast considering time series, and particle swarm optimization is used to optimize the parameters of the long short-term memory model to improve the forecast accuracy. Results show that the mean absolute error and root mean squared error are 8.7 and 16.3 for the PSO-LSTM model, respectively. In the second part, the forecast results are used as input of the distributed energy system to further optimize the design and operation schemes, so as to achieve the coupling optimization of forecast and design. Finally, a case study is carried out to verify the effectiveness of the proposed method

Adaptive Neural Network Robust Control for Space Robot with Uncertainty

The trajectory tracking problems of a class of space robot manipulators with parameters and non-parameters uncertainty are considered. An adaptive robust control algorithm based on neural network is proposed by the paper. Neutral network is used to adaptive learn and compensate the unknown system for parameters uncertainties, the weight adaptive laws are designed by the paper, System stability base on Lyapunov theory is analysised to ensure the convergence of the algorithm. Non-parameters uncertainties are estimated and compensated by robust controller. It is proven that the designed controller can guarantee the asymptotic convergence of tracking error. The controller could guarantee good robust and the stability of closed-loop system. The simulation results show that the presented method is effective

Thermodynamic and kinetic study of CO2 adsorption/desorptionon amine-functionalized sorbents

The thermodynamic and kinetic characteristics of CO2 adsorption of SBA-16 loaded with pentaethylenehexamine (PEHA) have been investigated using adsorption column system. The Langmuir isotherm model fitts the CO2 adsorption isotherms well, and the average isosteric heat of adsorption is 59.6 kJ/mol, indicating that the CO2 adsorption on PEHA-loaded SBA-16 is chemisorption. The Avrami fractional dynamics model is very suitable for illustrating the adsorption behaviour of CO2 adsorption, and the results of kinetic analysis show that increasing the partial pressure of CO2 or the working temperature is beneficial to the adsorption of CO2. Three desorption methods were evaluatedto achieve the optimal desorption method. The results show that VTSA and steam stripping method are effective methods for industrial CO2 desorption. Steam stripping may be more suitable for plants that already have low-cost steam. The activation energy Ea of CO2 adsorption/desorption is calculated using Arrhenius equation. The activation energy Ea of CO2 adsorption/desorption was calculated using the Arrhenius equation. The results show that the absolute value of Ea (adsorption) decreases with the increase of CO2 partial pressure. In addition, the Ea value of vacuum rotary regeneration method and steam stripping method is smaller than the Ea value of temperature swing regeneration

LRPPRC: A Multifunctional Protein Involved in Energy Metabolism and Human Disease

The pentatricopeptide repeat (PPR) family plays a major role in RNA stability, regulation, processing, splicing, translation, and editing. Leucine-rich PPR-motif-containing protein (LRPPRC), a member of the PPR family, is a known gene mutation that causes Leigh syndrome French–Canadian. Recently, growing evidence has pointed out that LRPPRC dysregulation is related to various diseases ranging from tumors to viral infections. This review presents available published data on the LRPPRC protein function and its role in tumors and other diseases. As a multi-functional protein, LRPPRC regulates a myriad of biological processes, including energy metabolism and maturation and the export of nuclear mRNA. Overexpression of LRPPRC has been observed in various human tumors and is associated with poor prognosis. Downregulation of LRPPRC inhibits growth and invasion, induces apoptosis, and overcomes drug resistance in tumor cells. In addition, LRPPRC plays a potential role in Parkinson's disease, neurofibromatosis 1, viral infections, and venous thromboembolism. Further investigating these new functions of LRPPRC should provide novel opportunities for a better understanding of its pathological role in diseases from tumors to viral infections and as a potential biomarker and molecular target for disease treatment

Thermodynamic and kinetic study of CO2 adsorption/desorptionon amine-functionalized sorbents

473-482The thermodynamic and kinetic characteristics of CO2 adsorption of SBA-16 loaded with pentaethylenehexamine (PEHA) have been investigated using adsorption column system. The Langmuir isotherm model fitts the CO2 adsorption isotherms well, and the average isosteric heat of adsorption is 59.6 kJ/mol, indicating that the CO2 adsorption on PEHA-loaded SBA-16 is chemisorption. The Avrami fractional dynamics model is very suitable for illustrating the adsorption behaviour of CO2 adsorption, and the results of kinetic analysis show that increasing the partial pressure of CO2 or the working temperature is beneficial to the adsorption of CO2. Three desorption methods were evaluatedto achieve the optimal desorption method. The results show that VTSA and steam stripping method are effective methods for industrial CO2 desorption. Steam stripping may be more suitable for plants that already have low-cost steam. The activation energy Ea of CO2 adsorption/desorption is calculated using Arrhenius equation. The activation energy Ea of CO2 adsorption/desorption was calculated using the Arrhenius equation. The results show that the absolute value of Ea (adsorption) decreases with the increase of CO2 partial pressure. In addition, the Ea value of vacuum rotary regeneration method and steam stripping method is smaller than the Ea value of temperature swing regeneration

Knowledge-Driven Semantic Segmentation for Waterway Scene Perception

Semantic segmentation as one of the most popular scene perception techniques has been studied for autonomous vehicles. However, deep learning-based solutions rely on the volume and quality of data and knowledge from specific scene might not be incorporated. A novel knowledge-driven semantic segmentation method is proposed for waterway scene perception. Based on the knowledge that water is irregular and dynamically changing, a Life Time of Feature (LToF) detector is designed to distinguish water region from surrounding scene. Using a Bayesian framework, the detector as the likelihood function is combined with U-Net based semantic segmentation to achieve an optimized solution. Finally, two public datasets and typical semantic segmentation networks, FlowNet, DeepLab and DVSNet are selected to evaluate the proposed method. Also, the sensitivity of these methods and ours to dataset is discussed

Recent Advances in Hypertrophic Cardiomyopathy: A System Review

Hypertrophic cardiomyopathy (HCM) is a common genetic cardiovascular disease present in 1 in 500 of the general population, leading to the most frequent cause of sudden death in young people (including trained athletes), heart failure, and stroke. HCM is an autosomal dominant inheritance, which is associated with a large number of mutations in genes encoding proteins of the cardiac sarcomere. Over the last 20 years, the recognition, diagnosis, and treatment of HCM have been improved dramatically. And moreover, recent advancement in genomic medicine, the growing amount of data from genotype-phenotype correlation studies, and new pathways for HCM help the progress in understanding the diagnosis, mechanism, and treatment of HCM. In this chapter, we aim to outline the symptoms, complications, and diagnosis of HCM; update pathogenic variants (including miRNAs); review the treatment of HCM; and discuss current treatment and efforts to study HCM using induced pluripotent stem cell–derived cardiomyocytes and gene editing technologies. The authors ultimately hope that this chapter will stimulate further research, drive novel discoveries, and contribute to the precision medicine in diagnosis and therapy for HCM

Penaeid shrimp genome provides insights into benthic adaptation and frequent molting

Crustacea, the subphylum of Arthropoda which dominates the aquatic environment, is of major importance in ecology and fisheries. Here we report the genome sequence of the Pacific white shrimp Litopenaeus vannamei, covering similar to 1.66 Gb (scaffold N50 605.56 Kb) with 25,596 protein-coding genes and a high proportion of simple sequence repeats (>23.93%). The expansion of genes related to vision and locomotion is probably central to its benthic adaptation. Frequent molting of the shrimp may be explained by an intensified ecdysone signal pathway through gene expansion and positive selection. As an important aquaculture organism, L. vannamei has been subjected to high selection pressure during the past 30 years of breeding, and this has had a considerable impact on its genome. Decoding the L. vannamei genome not only provides an insight into the genetic underpinnings of specific biological processes, but also provides valuable information for enhancing crustacean aquaculture

Proteomic analysis of PBMCs: characterization of potential HIV-associated proteins

<p>Abstract</p> <p>Background</p> <p>The human immunodeficiency virus type 1 (HIV-1) pandemic has continued unabated for nearly 30 years. To better understand the influence of virus on host cells, we performed the differential proteome research of peripheral blood mononuclear cells (PBMCs) from HIV-positive patients and healthy controls.</p> <p>Results</p> <p>26 protein spots with more than 1.5-fold difference were detected in two dimensional electrophoresis (2DE) gels. 12 unique up-regulated and one down-regulated proteins were identified in HIV-positive patients compared with healthy donors. The mRNA expression of 10 genes was analyzed by real time RT-PCR. It shows that the mRNA expression of talin-1, vinculin and coronin-1C were up-regulated in HIV positive patients and consistent with protein expression. Western blotting analysis confirmed the induction of fragments of vinculin, talin-1 and filamin-A in pooled and most part of individual HIV-positive clinical samples. Bioinformatic analysis showed that a wide host protein network was disrupted in HIV-positive patients.</p> <p>Conclusions</p> <p>Together, this work provided useful information to facilitate further investigation of the underlying mechanism of HIV and host cell protein interactions, and discovered novel potential biomarkers such as fragment of vinculin, filamin-A and talin-1 for anti-HIV research.</p