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Accurately identifying the stage of the excavator working cycle is the prerequisite to achieve the staged energy-saving control. However, current identification methods often overlook the influence of hydraulic system latency on identification results and depend on a single model, resulting in poor generalization performance of the identification approaches. Moreover, expert calibration system remains a necessary factor for improving identification accuracy. Aiming at these issues, a hybrid multi-scale feature extractor and a decision-level data fusion classifier approach (HMSFE-DFC) is proposed to identify the working cycle stages of excavator. The input signal employs mixed signals from the main pump pressure and the control current of the proportional solenoid valve to reduce the response delay caused by the single main pump pressure signal. A hybrid multi-scale feature extractor is constructed using a convolutional neural network temporal self-attention feature extraction mechanism and one-dimensional ResNet-50 architecture to extract multiscale features. To prevent overfitting, a decision-level data fusion classifier is used to fuse the decisions information of numerous classifiers. The accuracy of stage identification for 10 consecutive working cycles reaches 95.21%, which verifies its effectiveness. • A hybrid multiscale feature extractor and decision level data fusion classifier approach is presented. • The main pump pressure and control current of the proportional solenoid valve are mixed to reduce the response delay. • The proposed approach can achieve an identification accuracy of 95.21% for 10 consecutive working cycles of an excavator. [ABSTRACT FROM AUTHOR]

Solar interfacial evaporation is an effective and sustainable strategy to solve the shortage of fresh water. Nowadays, fully converting the near-infrared light with significant thermal effect, and reducing the energy loss in evaporation stage are the key factors to achieve higher evaporation rate. Herein, the nano cesium tungsten bronze (Cs 0.32 WO 3) with exceptional near-infrared absorption property was loaded on reduced graphene oxide-carbon nanotubes (rGO-CNTs) composite aerogel, drastically enhancing the evaporation efficiency from 61.0% to 85.9%, which can be explained by the remarkable synergistic effect between rGO-CNTs and nano Cs 0.32 WO 3 in improving the photothermal conversion performance. As a result, the solar evaporators assembled by the fabricated rGO-CNTs-Cs 0.32 WO 3 aerogels and corn straw grooves achieved an evaporation rate of 1.93 kg m−2 h−1, exceeding the previously-investigated carbon aerogels/foams, natural plants and tungsten-based compound systems. The characterization results reveal that the loading of nano Cs 0.32 WO 3 contributes to the partial restoration of π-conjugated structure in rGC, increasing solar absorption and the corresponding thermal energy released by the lattice vibration. Meanwhile, the oxygen vacancies and carrier density of Cs 0.32 WO 3 nanoparticles increase after compositing with rGC, which further enhances the local surface plasma resonances (LSPR) effect. Significantly, the hydrophilic functional groups and excellent wettability of composite aerogel and corn straw play crucial effect in accelerating water transport, activating water molecules and reducing evaporation energy consumption. In a word, the unique construction of rGO-CNTs-Cs 0.32 WO 3 aerogels presents a novel approach for the design of solar-driven freshwater production system, the application expansion of nano tungsten bronze and carbon aerogels. [Display omitted] • Novel carbon-supported nano cesium tungsten bronze aerogels are successfully fabricated and achieve higher evaporation efficiency of 85.9%. • rGO-CNTs-Cs 0.32 WO 3 porous aerogels exhibit higher NIR absorption performance of 97.2% and evaporation rate of 1.93 kg m−2h−1. • The synergy between rGO-CNTs and nano Cs 0.32 WO 3 significantly enhances the photothermal conversion performance of composite aerogel. • Abundant hydrophilic groups and excellent wettability of carbon aerogel and corn straw are beneficial for reducing the energy consumption of evaporation. [ABSTRACT FROM AUTHOR]

• A novel data-driven hydraulic excavator fuel consumption prediction system is proposed. • The effect of mode superposition in the original signal on the prediction accuracy can be better solved by VMD. • VMD-Informer is compared with other five popular prediction models. • The performance evaluation shows the superiority of the proposed system. With the aggravation of the global energy crisis, fuel consumption has become a key indicator for excavator manufacturers and policymakers. However, traditional experimental and theoretical approaches, which are complicated to calculate and dependent on the laboratory environment, are difficult to be applied in engineering. A data-driven prediction system consisting of data acquisition, feature decomposition, fuel consumption prediction, and performance evaluation modules, is developed to achieve excavator fuel consumption prediction during operation. The characteristic parameters of excavator energy consumption are collected through the established data acquisition module and the superfluous noise is eliminated by the feature decomposition module. A prediction model based on Informer is proposed in the fuel consumption prediction module to solve the drawback that the neural network model cannot capture key information in long series data in parallel, thus improving the prediction accuracy. Finally, the effectiveness of different prediction methods is verified by the performance prediction module. [ABSTRACT FROM AUTHOR]

Abstract: The transport properties of the molecular-scale B2C and BC3 electronic devices are investigated with an ab initio method combined with a nonequilibrium Green function technique. The effects of different BC graphenes and ribbon lengths on the transport properties of the devices are significant. The results show that the devices with different BC graphenes and sizes have unusual transmission coefficients, which leads to special current transport mechanisms for the devices. Notably, the current strength of the device with the shortest ribbon length is the largest in three B2C devices, but the current strength of the device with the shortest ribbon length is the smallest for BC3 device. [Copyright &y& Elsevier]

Ethnopharmacological relevance Aristolochia manshuriensis Kom (AMK), belonging to the Aristolochia family, is traditionally used in China to remove heart fire, promote dieresis, restore menstruation, and enhance milk secretion. The active constitutes of AMK are aristolochic acids (AAs, I and II) that are reported to cause serious side effects including nephrotoxicity and carcinogenicity. Aim of the study The tumorigenic role of AMK is far to be understood. We analyzed the toxicity reactions after long-term exposure of AMK in rats. Materials and Methods Sprague–Dawley rats underwent gavage with AMK doses of 51 mg/kg (AMK-1), 253 mg/kg (AMK-2), 508 mg/kg (AMK-3), 1029 mg/kg (AMK-4) or AAs of 15 mg/kg (AAs), and then sacrificed at the 6th, 10th, 14th, 18th, 22th, 26th and 30th weeks. Endpoint measurements included clinical observations, body weights, blood biochemistry, haematology and histomorphological observations. Results Body weight decreased after AMK or AAs treatment in rats. AMK destroyed renal function, and induced anemia in rats. AMK caused kidney, stomach, bladder and subcutaneous tumors in rats. In addition, primary hepatic carcinoma was not observed in rats. Conclusions AMK had significant toxic effects in rats with regard to decreased body weight, diminished renal function, increased anemia and tumor incidence. Kidney, stomach, bladder and subcutaneous tissue are carcinogenic target organs of AMK or AAs, however liver is no- carcinogenic target organ of AMK or AAs in rats. AMK is carcinogenic in rats, and not be safe for humans. [ABSTRACT FROM AUTHOR]

Ethnopharmacological relevance Geniposide, the major active constituent of Fructus Gardeniae (FG), has been widely used to treat various diseases in China. Aim of the study This chronic toxicity study was conducted to investigate the safety of geniposide. Materials and methods Geniposide was administered to Sprague-Dawley (SD) rats of both sexes by oral gavage at dosages of 25, 50, or 100 mg/kg in a volume of 10 mL/kg once daily for 26 weeks. Endpoints included clinical observations, food consumption, body weights, blood biochemistry, haematology, and histomorphological observations. Results The administration of geniposide did not influence animal mortality, the general conditions of the animals, body weights or food consumption. After 4 weeks of administration, significant toxicity was not observed. However, in the 13th week of the toxicity study, a few haematological parameters and some relative organ weights of male rats in the 50 and 100 mg/kg geniposide groups were significantly increased. The percentage of reticulocytes (Retic %) was significantly increased in male and female rats administered 100 mg/kg geniposide. In addition, two female rats in the 100 mg/kg geniposide group showed slight pathological changes in hepatic and renal tissues. Furthermore, in a chronic (26 weeks) toxicity study, differences were detected in alanine aminotransferase (ALT), aspartate aminotransferase (AST), sodium (Na + ), potassium (K + ), white blood cell (WBC), red blood cell (RBC), and haemoglobin (HGB) levels and the relative weights of the liver and spleen in male rats administered 100 mg/kg geniposide. In addition, differences were detected in Retic % and the relative weights of the liver, thymus, and kidneys in female rats administered 100 mg/kg geniposide. Urinalysis results from male and female rats in the 100 mg/kg geniposide group revealed noticeable changes. The histopathological structures of hepatic and renal tissues in the high-dose geniposide group exhibited serious abnormalities and pigment deposition. Conclusion Geniposide affected serum biochemistry, urinalysis, and haematological parameters as well as relative organ weights. The treatment also caused noticeable pathological abnormalities in liver and kidney tissues. Therefore, administration of a high dose of geniposide (100 mg/kg) for 26 weeks could induced obvious liver and kidney damage. [ABSTRACT FROM AUTHOR]

Energy conservation is an important strategy for low-carbon development. With utilizing stage recognition and control strategies, engineering machinery can achieve energy savings, and reduce carbon emissions. The traditional machine learning approach requires a large amount of data to train models. In addition to many cases where the available data is limited, even if the data volume is sufficient, it often means that a large amount of testing is required, which is difficult for users who are not professionals and may cause further waste, it is necessary to develop methods that can achieve high accuracy even with limited data. This paper proposes an intelligent recognition method based on library for support vector machine (LIBSVM), which uses the relationship between working stages and pressure waveforms of working cycle. Initially, the pressure waveforms are carefully extracted and subjected to a robust filtering process to effectively eliminate noise artifacts. Subsequently, relevant features are extracted from the waveforms, which include important characteristics such as the amplitude and frequency of the pressure waves, then the extracted features are normalized using appropriate techniques. The LIBSVM model is carefully trained using the aforementioned extracted features and label data. Finally, to further enhance the accuracy of the proposed method, an intelligent calibration system is utilized. This system plays a crucial role in ensuring that the results obtained from the machine learning algorithm are effectively calibrated, thereby improving the overall accuracy of the method. A series of experiments have verified the accuracy of the proposed identification method, and the effectiveness of using this method for energy-saving design has been verified through real machine validation. [ABSTRACT FROM AUTHOR]

The study of the interaction mechanism between bacteriophage and host is helpful in promoting development of bacteriophage applications. The mechanism of the interaction with the phage was studied by constructing the rfbN gene deletion and complemented with strains of Salmonella enterica subspecies enterica serovar Typhimurium (Salmonella Typhimurium, S. Typhimurium) D6. The rfbN gene deletion strain could not be lysed by phage S55 and led to a disorder of lipopolysaccharide (LPS) biosynthesis, which changed from the smooth type to rough type. Also, the RfbN protein lacking any of the three-segment amino acid (aa) sequences (90−120 aa, 121−158 aa, and 159−194 aa) produces the same result. Transmission electron microscopy and confocal microscopy assays demonstrated that phage S55 dramatically reduced adsorption to the rfbN deletion strain as compared to the wild strain D6. After co-incubation of the S55 with the purified smooth LPS, D6 could not be lysed, indicating that the smooth LPS binds to the S55 in vitro and then inhibits the cleavage activity of the S55. To sum up, the rfbN gene affects phage adsorption by regulating LPS synthesis. Furthermore, the functioning of the RfbN protein requires the involvement of multiple structures. To the best of our knowledge, this study is the first report of the involvement of the bacterial rfbN gene involved in the phage-adsorption process. [ABSTRACT FROM AUTHOR]