Response load prediction of demand response users based on parallel CNN

YAs China advances its transition towards green and low-carbon energy, the proportion of new energy generation in the power grid is gradually increasing, leading to a significant rise in the demand for power resource scheduling. However, due to the scarcity of historical load response data from users, it is challenging to effectively predict user-responsive loads. To address this issue, this study proposes a method of augmenting historical load response data in a weakly supervised manner. Taking into account the unique circumstances of high-voltage users, a sparse CNN for anomaly detection is introduced, along with a multi-branch parallel CNN model capable of weighted output of prediction results from both global and local perspectives. Subsequently, effective iterative training of the model is performed using the EM algorithm. Ultimately, accurate prediction of user-responsive loads is achieved. Based on historical 96-point load data and load response data from high-voltage users in a specific city in China, the predicted results are compared with actual load response data, validating the rationality and accuracy of this method in predicting user-responsive loads

Catalytic removal of 1,2-dichloroethane over LaSrMnCoO6/H-ZSM-5 composite: insights into synergistic effect and pollutant-destruction mechanism

LaxSr2−xMnCoO6 materials with different Sr contents were prepared by a coprecipitation method, with LaSrMnCoO6 found to be the best catalyst for 1,2-dichloroethane (DCE) destruction (T90 = 509 °C). As such, a series of LaSrMnCoO6/H-ZSM-5 composite materials were rationally synthesized to further improve the catalytic activity of LaSrMnCoO6. As expected, the introduction of H-ZSM-5 could remarkably enlarge the surface area, increase the number of Lewis acid sites, and enhance the mobility of the surface adsorbed oxygen species, which consequently improved the catalytic activity of LaSrMnCoO6. Among all the composite materials, 10 wt% LaSrMnCoO6/H-ZSM-5 possessed the highest catalytic activity, with 90% of 1,2-DCE destructed at 337 °C, which is a temperature reduction of more than 70 °C and 170 °C compared with that of H-ZSM-5 (T90 = 411 °C) and LaSrMnCoO6 (T90 = 509 °C), respectively. Online product analysis revealed that CO2, CO, HCl, and Cl2 were the primary products in the oxidation of 1,2-DCE, while several unfavorable reaction by-products, such as vinyl chloride, 1,1,2-trichloroethane, trichloroethylene, perchloroethylene, and acetaldehyde, were also formed via dechlorination and dehydrochlorination processes. Based on the above results, the reaction path and mechanism of 1,2-DCE decomposition are proposed

Characteristics of Wild Cherry Beverage Co-fermented by Hanseniaspora uvarum and Saccharomyces cerevisiae

One strain of Hanseniaspora uvarum YT-35 was screened from fermented sediment of wild cherry. Hanseniaspora uvarum YT-35 and commercial Saccharomyces cerevisiae were used as coculture for manufacture of fermented wild cherry beverage. The dynamics of microbial populations, reducing sugars and ethanol were analyzed at different stages of fermentation using single-strain fermentation with 2 strains of bacteria as a control. Meanwhile, the organic acids and volatile aromatic compounds of the fermented beverages were detected by high-performance liquid chromatography (HPLC) and headspace solid-phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS). The results showed that H. uvarum YT-35 dominated in the pre-fermentation stage of co-culture. Compared with single fermentation with S. cerevisiae, the coculture fermentation resulted in lower ethanol content (3.51 g/L). Notably, HPLC results revealed that coculture fermented beverage reduced the yield of citric, malic and quinic acids and increased the yield of glacial acetic acid. HS-SPME/GC-MS results revealed that coculture fermented beverage produced more volatile compounds of esters, such as ethyl caproate, methyl benzoate and isoamyl octanoate and showed enhanced contents of ethyl laurate, ethyl octanoate, phenyl ethyl alcohol, benzyl alcohol, octanoic acid and lauric acid. Meanwhile, clustering analysis revealed that coculture fermentation were correlated with the greatest number of volatile aroma compounds in the fermented wild cherry beverage. This study provides scientific basis and theoretical guidance for the research of coculture strains with different metabolic potential in improving the quality of fruit juice fermented beverage

A novel conducting nanocomposite obtained by p-anisidine and aniline with titanium(IV) oxide nanoparticles: Synthesis, Characterization, and Electrochemical properties

Nanocomposites were successfully synthesized by the oxidative polymerization of p-anisidine and/or aniline monomers (at initial “p-anisidine:aniline” mole ratios of “100 : 0,” 50 : 50,” and “0 : 100”) with titanium(IV) oxide nanoparticles, in the presence of hydrochloric acid as a dopant with ammonium persulfate as an oxidant. The morphological, structural, conductivity, and electrochemical properties of the synthesized nanocomposites were studied using Transmission Electron Microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and UV–vis spectroscopies. The presence of polymer on TiO2 nanoparticles in samples nanocomposites was confirmed by the Transmission Electron Microscopy coupled with Energy Dispersive X-ray Spectroscopy. The thermal stability of samples nanocomposites were evaluated using the Thermogravimetric Analysis. Electrical conductivity of nanocomposites obtained is in the range of 0.08 − 0.91 S cm−1. The electrochemical behavior of the polymers extracted from the nanocomposites has been analyzed by cyclic voltammetry. Good electrochemical response has been observed for polymer films; the observed redox processes indicate that the polymerization on TiO2 nanoparticles produces electroactive polymers. These composite microspheres can potentially be used in commercial applications as fillers for antistatic and anticorrosion coatings.National Assessment and Planning Committee of the University Research (CNEPRU); contract grant number: E-03720130015; contract grant sponsor: MINECO; contract grant number: MAT2013-42007-P; contract grant sponsor: Generalitat Valenciana; contract grant number: PROMETEO2013/038; contract grant sponsor: Directorate General of Scientific Research and Technological Development (DGRSDT) of Algeria

Digital twin-based multi-level task rescheduling for robotic assembly line

Abstract Assembly is a critical step in the manufacturing process. Robotic assembly technology in automatic production lines has greatly improved the production efficiency. However, in assembly process, dynamic disturbances such as processing time change and advance delivery may occur, which cause the scheduling deviation. Traditional scheduling methods are not sufficient to meet the real-time and adaptive requirements in smart manufacturing. Digital twin (DT) has the characteristics of virtual-reality interaction and real-time mapping. In this paper, we propose a DT-based framework of task rescheduling for robotic assembly line (RAL) and its key methodologies, thus to realize the timely and dynamic adjustment of scheduling plan under uncertain interferences. First, a DT model of RAL task rescheduling composed of physical entity (PE), virtual entity (VE), and virtual-reality interaction mechanism is proposed. Then, a mathematical model is established. By analyzing the adaptive objective thresholds from the perspectives of event trigger and user demand trigger, a DT-driven multi-level (production unit level and line level) rescheduling strategy is proposed. Taking both the computing time and solution quality into consideration, the precedence graph is introduced to propose a rescheduling approach based on an improved discrete fireworks algorithm. Finally, the effectiveness of the proposed model and approach are verified by task scheduling experiments of RAL

Identification and verification of a PANoptosis-related long noncoding ribonucleic acid signature for predicting the clinical outcomes and immune landscape in lung adenocarcinoma

PANoptosis is a type of programmed cell death (PCD) characterised by apoptosis, necroptosis and pyroptosis. Long non-coding ribonucleic acids (lncRNAs) are participating in the malignant behaviour of tumours regulated by PCD. Nevertheless, the function of PANoptosis-associated lncRNAs in lung adenocarcinoma remains to be investigated. In this work, a PANoptosis-related lncRNA signature (PRLSig) was developed based on the least absolute shrinkage and selection operator algorithm. The stability and fitness of PRLSig were confirmed by systematic evaluation of Kaplan–Meier, Cox analysis algorithm, receiver operating characteristic analysis, stratification analysis. In addition, ESTIMATE, single sample gene set enrichment analysis, immune checkpoints and the cancer immunome database confirmed the predictive value of the PRLSig in immune microenvironment and helped to identify populations for which immunotherapy is advantageous. The present research provides novel insights to facilitate risk stratification and optimise personalised treatment for LUAD