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The advent of various additive manufacturing technologies, such as 3D printing, has changed the structural design and preparation process of rocket fuels. In order to investigate the combustion properties of various common polymer materials that can be additively manufactured by fused deposition, the combustion tests of hybrid rocket fuels prepared by 3D printing were carried out. These materials include polylactic acid (PLA), wood-like polylactic acid (Wood), acrylonitrile-butadiene-styrene (ABS), acrylonitrile-styrene-acrylate (ASA), copolymers of nylon 6 and nylon 6,6 (CoPA), polycarbonate-polybutylene terephthalate (PC-PBT), flame retardant polycarbonate (PC-FR) and polyethylene terephthalateco-1,4-cylclohexylenedimethylene terephthalate (PETG). Thermogravimetric-differential scanning calorimetry (TG-DSC) analysis was carried out on these materials, the printing effect of the fuel grains was observed by three-dimensional X-ray microscopy (µCT) and the combustion performance of these fuels in gaseous oxygen flow (GOX) was recorded by high-speed photography at a constant pressure of 1 MPa. The results show that ASA and ABS exhibit good printing results. The regression rates of PC-PBT, PETG, ABS, ASA, CoPA and PLA are 0.792 mm/s, 0.592 mm/s, 0.536 mm/s and 0.477 mm/s, 0.368 mm/s, 0.339 mm/s (AtGOX=220kg/(m2·s)), respectively.

Recently, the Mg–Ag binary alloy has gained much attention as an antibacterial biomaterial. However, the relationships between the extrusion parameters, microstructure, and mechanical properties of Mg–Ag alloys haven't been clearly established. Therefore, in this paper, the effects of silver (Ag) content (0, 3, 6 wt%) and extrusion (as cast, extrusion ratio (ER) 7.1 and 72.2) on the microstructure and mechanical properties of Mg–Ag alloys are systematically investigated. The results indicate that for the Mg–Ag alloys with the same extrusion ratio, as the Ag increased from 0 to 3 wt%, Mg4Ag and Mg54Ag17 precipitated, leading to significant precipitation strengthening and an increase in the yield strength by over 137%. As the Ag increased to 6 wt%, the yield strength increased by only ∼20%, attributable to Ag promoting dynamic recrystallization, resulting in less grain refinement, a slower amount increase and a smaller size reduction of the precipitate. For the Mg–Ag alloys with the same Ag content, as the extrusion ratio increased to 7.1, the yield strength increased significantly by over 37%, since the grain boundary strengthening and precipitation strengthening were significantly enhanced as the grains were refined, a large number of precipitates appeared, and their sizes significantly reduced. When the extrusion ratio increased to 72.2, the yield strength increased by only ∼10%, due to the weakening of both grain boundary strengthening and precipitation strengthening as the recrystallization further improved, leading to an increase in grain sizes, the redissolution of precipitates, and a lesser reduction in their sizes.

PurposeFibroblast activation protein (FAP) is highly expressed in the mesenchyme of most malignant epithelial tumors, while its expression is low in normal tissues. FAP inhibitors (FAPIs) bind specifically to FAP and are used for tumor-targeted diagnosis and therapy. The aim of this study was to radiosynthesize a novel molecular probe 131I-FAPI and evaluate its in-vitro targeting and biological characteristics.MethodsThe structurally modified FAPI was labelled with 131I through the chloramine-T method. The radiolabeling rate was then detected by thin-layer chromatography (TLC). The stability of 131I-FAPI was determined at PBS (room temperature) and serum (37°C). Its hydrophilicity was calculated by measuring its lipid-water partition coefficient. Pancreatic cancer PANC-1 cell line and glioma U87 cell line were cultured in vitro. Cell uptake assay was used to show the binding ability of 131I-FAPI. The CCK-8 assay was used to calculate the inhibitory effects of 131I-FAPI at different time points (4h, 8h, 12h, 24h, 48h) after comparing with the 131I and FAPI. The before-and-after-24h scratch areas of the two cells were determined in order to verify the effect of 131I-FAPI on the migration ability of the cells.ResultsThe radiolabeling rate was (84.9 ± 1.02) %. The radiochemical purity of 131I-FAPI remained over 80% in both 25°C PBS and 37°C serum. The value of the lipid-water partition coefficient was -0.869 ± 0.025, indicating the hydrophilic of the probe. The cellular uptake assay showed that U87 cells had a specific binding capacity for 131I-FAPI. In cell inhibition assays, the inhibitory effect of 131I-FAPI on U87 cells increased with time. The results of cell scratch assay showed that 131I-FAPI had the strongest inhibitory effect on the migratory ability of U87 cells compared with 131I and FAPI (P

Water hammer protection is one of the key factors for the safe operation of the long-distance water delivery systems, which has lots of useful results. However, the protection experiences for bidirectional water delivery systems using the same pipeline are lacking. In this study, the protection method with one-way surge tanks in the bidirectional water delivery system is investigated. The theoretical formula for one-way surge tank setting is derived based on the theory of water hammer propagation, and the pump head and bidirectional water hammer protection constraints. Subsequently, the pump trip transient processes in an actual system are simulated. Finally, different kinds of one-way surge tank protection schemes are compared. The results show that the pressure along the pipeline after the pump trip can meet the standard when using the one-way surge tank protection scheme calculated by the theoretical formula. The proposed method can provide the effective protection strategy for the bidirectional water delivery systems. HIGHLIGHTS Negative pressure protection for the bidirectional water delivery systems in the same pipeline is studied.; The theoretical formula for one-way surge tank setting in bidirectional water delivery system is presented.; The proposed one-way surge tank setting strategy can provide effective water hammer protection for the system.;

The penetration of new energy sources such as wind power is increasing, which consequently increases the occurrence rate of subsynchronous oscillation events. However, existing subsynchronous oscillation source-identification methods primarily analyze fixed-mode oscillations and rarely consider time-varying features, such as frequency drift, caused by the random volatility of wind farms when oscillations occur. This paper proposes a subsynchronous oscillation source-localization method that involves an enhanced short-time Fourier transform and a convolutional neural network (CNN). First, an enhanced STFT is performed to secure high-resolution time-frequency distribution (TFD) images from the measured data of the generation unit ports. Next, these TFD images are amalgamated to form a subsynchronous oscillation feature map that serves as input to the CNN to train the localization model. Ultimately, the trained CNN model realizes the online localization of subsynchronous oscillation sources. The effectiveness and accuracy of the proposed method are validated via multimachine system models simulating forced and natural oscillation events using the Power Systems Computer Aided Design platform. Test results show that the proposed method can localize subsynchronous oscillation sources online while considering unpredictable fluctuations in wind farms, thus providing a foundation for oscillation suppression in practical engineering scenarios.

As an important component of the deep tunnel drainage system for dealing with urban waterlogging, the rotating stepped dropshaft has been proposed due to its small air entrainment. However, the hydraulic characteristics inside the shaft still need to be fully studied. In this study, the flow patterns, water velocity, and pressure in the rotating stepped dropshaft under different flow rates and geometric parameters were studied using a three-dimensional numerical model. The results show that increasing the central angle of the step and reducing the step height can both reduce the terminal velocity. A theoretical formula for predicting the terminal velocity was established and well validated. The connection between the shaft and the outlet pipe poses a severe threat to the structural safety due to alternating positive and negative pressures. Wall-attached swirling flow generates a circular high-pressure zone at the bottom of the dropshaft and the larger the flow rate, the greater the pressure gradient at the center of the bottom. By using the momentum theorem and considering the impact pressure range of the swirling flow, the shaft bottom pressure can be predicted reasonably well. HIGHLIGHTS The hydraulic characteristics of rotating stepped dropshafts are analyzed and the terminal velocity is evaluated theoretically and well validated.; The pressure distribution inside rotating stepped dropshafts and the impact effect of the wall-attached swirling flow on the shaft bottom are determined.; A simplified theoretical model is established to predict the impact pressure of the shaft.;

Arbuscular mycorrhizal fungi (AMF) play a key role in regulating the carbon cycle in terrestrial ecosystems. However, there is little information on how AMF inoculation affects the carbon fluxes of paddy fields, which are major sources of global carbon emissions. We, therefore, designed an experiment to study the effects of AMF inoculation on methane and carbon dioxide emissions from a paddy field. Results showed that: (1) Among the tested factors, the C/N ratio was the main environmental determinant of microbial community structure in the investigated soil; (2) compared with traditional fertilisation (control), the soil C/N ratio increased by 2.1~15.2% and 1.4~10.5% as a result of AMF application alone (M) or in combination with mineral fertiliser (FM) throughout the growing season, respectively. This change shifted microbial community composition to higher G+/G- bacterial and fungal/bacterial ratios; (3) the microbial community change favoured soil carbon retention. Methane (CH4) emission peaks were reduced by 59.4% and 76.0% versus control in the M treatment and by 52.5% and 29.4% in the FM treatment in the midseason and end-of-season drainage periods, and CO2 emission peaks were reduced by 70.1% and 52.3% in the M plots and by 55.4% and 66.4% in the FM plots.

The protection of negative pressures generated by the hydraulic transient process in the water supply system is crucial to safe and stable operation. In this study, a mathematical model of a pipeline hydraulic transient system with multi-undulating terrain was established based on the method of characteristics (MOC). The generation and development of water hammer negative pressures were analyzed, and double one-way surge tank protection schemes were proposed. It proved that the first surge tank should be located at the initial negative pressure point, and the second surge tank should be located at the second-highest point rather than the highest point. Additionally, compared with the theoretical minimum height, there was an optimization margin for the total surge tank height, which was reduced by 21% in this study. Meanwhile, the applicability of protection schemes and the influence of the one-way surge tank number on the total height were analyzed. The total height reduced with the increase of one-way surge tank number and tended to a minimum value. By comprehensively considering the engineering investment and negative pressure protection effect, the optimal surge tank number could be determined. This research represents an advance in negative pressure protection in multi-undulating terrain and provides support for further engineering studies. HIGHLIGHTS Double one-way surge tank schemes can fully protect negative pressures in water supply systems with multi-undulating terrain. The optimal locations are revealed.; Compared with the theoretical minimum surge tank height, the total surge tank height can be further reduced.; The total height reduces with the increase of surge tank number and tends to a minimum value.;

Due to the high detection efficiency of the airborne time-domain electromagnetic method, it can quickly collect electromagnetic response data for large area-wide regions, but it also brings great challenges to the inversion interpretation of the data because there are numerous survey data that need to be inverted. Conventional optimal inversion and fast imaging methods still take a long time to obtain conductivity and depth information, which affect the efficiency of real-time data interpretation. In this paper, we present a deep learning inversion method that can be used to solve the fast inversion problem of airborne time-domain electromagnetic data; the method uses a one-dimensional convolutional neural network. The network structure consists of two parts containing different numbers of convolutional and pooling layers. The training sample dataset was generated via two ways of constructing geoelectric models through forward modelling. To check the effectiveness of our deep learning inversion strategy, we tested it on synthetic data and two types of survey data. The experimental results show that this inversion method is effective and that it can be applied to airborne time-domain electromagnetic data collected using different observation systems. The proposed inversion method can obtain better inversion results for both simple and complex stratigraphic structures and requires significantly less computation time compared to conventional optimal inversion methods.

A large language model refers to a deep learning model characterized by extensive parameters and pretraining on a large-scale corpus, utilized for processing natural language text and generating high-quality text output. The increasing deployment of large language models has brought significant attention to their associated privacy and security issues. Recent experiments have demonstrated that training data can be extracted from these models due to their memory effect. Initially, research on large language model training data extraction focused primarily on non-targeted methods. However, following the introduction of targeted training data extraction by Carlini et al., prefix-based extraction methods to generate suffixes have garnered considerable interest, although current extraction precision remains low. This paper focuses on the targeted extraction of training data, employing various methods to enhance the precision and speed of the extraction process. Building on the work of Yu et al., we conduct a comprehensive analysis of the impact of different suffix generation methods on the precision of suffix generation. Additionally, we examine the quality and diversity of text generated by various suffix generation strategies. The study also applies membership inference attacks based on neighborhood comparison to the extraction of training data in large language models, conducting thorough evaluations and comparisons. The effectiveness of membership inference attacks in extracting training data from large language models is assessed, and the performance of different membership inference attacks is compared. Hyperparameter tuning is performed on multiple parameters to enhance the extraction of training data. Experimental results indicate that the proposed method significantly improves extraction precision compared to previous approaches.

Abstract Novel prophylactic drugs and vaccination strategies for protection against influenza virus should induce specific effector T-cell immune responses in pulmonary airways and peripheral lymphoid organs. Designing approaches that promote T-cell-mediated responses and memory T-cell differentiation would strengthen host resistance to respiratory infectious diseases. The results of this study showed that pulmonary delivery of MENK via intranasal administration reduced viral titres, upregulated opioid receptor MOR and DOR, increased the proportions of T-cell subsets including CD8+ T cells, CD8+ TEM cells, NP/PA-effector CD8+ TEM cells in bronchoalveolar lavage fluid and lungs, and CD4+/CD8+ TCM cells in lymph nodes to protect mice against influenza viral challenge. Furthermore, we demonstrated that, on the 10th day of infection, the proportions of CD4+ TM and CD8+ TM cells were significantly increased, which meant that a stable TCM and TEM lineage was established in the early stage of influenza infection. Collectively, our data suggested that MENK administered intranasally, similar to the route of natural infection by influenza A virus, could exert antiviral activity through upregulating T-cell-mediated adaptive immune responses against influenza virus.

Hyperspectral image (HSI) classification is a vital part of the HSI application field. Since HSIs contain rich spectral information, it is a major challenge to effectively extract deep representation features. In existing methods, although edge data augmentation is used to strengthen the edge representation, a large amount of high-frequency noise is also introduced at the edges. In addition, the importance of different spectra for classification decisions has not been emphasized. Responding to the above challenges, we propose an edge-aware and spectral–spatial feature learning network (ESSN). ESSN contains an edge feature augment block and a spectral–spatial feature extraction block. Firstly, in the edge feature augment block, the edges of the image are sensed, and the edge features of different spectral bands are adaptively strengthened. Then, in the spectral–spatial feature extraction block, the weights of different spectra are adaptively adjusted, and more comprehensive depth representation features are extracted on this basis. Extensive experiments on three publicly available hyperspectral datasets have been conducted, and the experimental results indicate that the proposed method has higher accuracy and immunity to interference compared to state-of-the-art (SOTA) method.

4-nitrophenol (4-NP) is a frequently encountered toxic phenolic organic pollutant in water. It is important to develop a simple method to treat 4-NP. Small and monodispersed gold nanoparticles often have good catalytic performance of 4-NP. Hemoglobin (Hb) is a kind of common and important protein in organisms. Herein, highly biocompatible bovine hemoglobin-stabilized gold nanoparticles (Aun-Hb NPs) were synthesized using hemoglobin as a biological template. Then, the size, zeta potential, and composition of Aun-Hb NPs were investigated by transmission electron microscopy, dynamic light scattering, and X-ray photoelectron spectroscopy. The Aun-Hb NPs with small gold nanoparticles of about 1.4–2.4 nm had good catalytic capabilities in reducing 4-NP to form 4-aminophenol. Au20-Hb NPs demonstrated superior catalytic efficiency in the reduction of 4-NP when compared to other nanoparticles. Moreover, as-synthesized Au20-Hb NPs exhibited excellent biocompatibility through the MTT experiment. The method of preparation of gold nanoparticles offers one way to prepare metal nanoparticles for good potential catalytic applications of gold nanoparticles.

Recently, magnesium (Mg) alloys have attracted extensive attention as biodegradable implant materials. However, cyclic loading and the corrosive environment of the body are significant challenges for the practical use of alloys, and there are few studies on this topic. In this study, we conducted a four-point bending fatigue test for 86,400 cycles (12 h) in simulated body fluid (SBF), plasma, and whole blood with an AZ series alloy Mg-9Al-0.5Zn-0.27Mn-0.12Ag, to examine the effects of inorganic ions, organic particles, blood cells, and cyclic loading on Mg alloy corrosion. The Mg2+ concentration and solution pH were measured before and after experimentation, and the sample surfaces were characterized by 3D digital microscopy, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS).Our results showed that in the non-loading condition, a porous and weak inorganic product layer (mainly Mg/Ca phosphate and carbonate) formed on the surface of the Mg alloy sample immersed in SBF, which hardly had a protective effect on Mg alloy corrosion. For the samples immersed in plasma, the organic particles promoted the formation of an organic and more compact product layer, which protected the Mg alloy from severe corrosion. For the sample immersed in whole blood, the blood cells affected organic particle deposition on the product layer and thus interfered with the formation of an organic compact product layer, which slightly accelerated the corrosion process. Furthermore, cyclic loading damaged the layer integrity and significantly increased the corrosion rates of all the studied materials compared to the samples not subjected to cyclic loading. Nonetheless, under cyclic loading, blood cells adsorbed on the Mg alloy surfaces, and formed films, which protected the Mg alloy substrate and delayed Mg alloy corrosion.

When installed in deep tunnel systems, the cover of the vortex dropshaft may be partially or fully sealed. With air exchange restricted through the cover, the air supply to the dropshaft through the inflow channel might not be adequate. Hence, further investigation is required to examine the effect of the restricted air passage through the cover on the flow regimes and hydraulic performance of the scroll vortex dropshaft. This study aims to quantify the head-discharge relationship, air-water distribution, and minimum air core size with different cover opening conditions. The 3D model of a fully open scroll vortex dropshaft is constructed, and numerical simulations are carried out and validated using experiment data. The results show that the effect is generally small when the ratio of the opening and dropshaft area is larger than 1%. When the cover is fully sealed, the minimum air core size reduces by ~5% of the dropshaft area which can have a serious implication to the design of the scroll vortex dropshaft. The present study provides a practical evaluation of the effect of the opening condition in the cover of the vortex chamber on the performance of scroll vortex dropshafts for underground water drainage systems..

Abstract Here, a sucrose non‐fermenting‐1‐related protein kinase alpha subunit (TaSnRK1α‐1A) is identified as associated with cold stress through integration of genome‐wide association study, bulked segregant RNA sequencing, and virus‐induced gene silencing. It is confirmed that TaSnRK1α positively regulates cold tolerance by transgenes and ethyl methanesulfonate (EMS) mutants. A plastid‐lipid‐associated protein 6, chloroplastic‐like (TaPAP6L‐2B) strongly interacting with TaSnRK1α‐1A is screened. Molecular chaperone DJ‐1 family protein (TaDJ‐1‐7B) possibly bridged the interaction of TaSnRK1α‐1A and TaPAP6L‐2B. It is further revealed that TaSnRK1α‐1A phosphorylated TaPAP6L‐2B. Subsequently, a superior haplotype TaPAP6L‐2B30S/38S is identified and confirmed that both R30S and G38S are important phosphorylation sites that influence TaPAP6L‐2B in cold tolerance. Overexpression (OE) and EMS‐mutant lines verified TaPAP6L positively modulating cold tolerance. Furthermore, transcriptome sequencing revealed that TaPAP6L‐2B‐OE lines significantly increased jasmonic acid (JA) content, possibly by improving precursor α‐linolenic acid contributing to JA synthesis and by repressing JAR1 degrading JA. Exogenous JA significantly improved the cold tolerance of wheat plants. In summary, TaSnRK1α profoundly regulated cold stress, possibly through phosphorylating TaPAP6L to increase endogenous JA content of wheat plants.

Abstract Fibroblast activation protein (FAP) is higher expressed on cancer-associated fibroblasts (CAFs) in most malignant epithelial neoplasms, which is lower expressed in normal tissues. As a promising small molecular probe, FAP inhibitor (FAPI) shows the specific binding to FAP. This study aimed to explore a novel molecular probe [99mTc]Tc-HYNIC-FAPI targeting CAFs. The in vitro characteristics of the probe were also evaluated. The FAPI targeting FAP was designed, synthesized and conjugated with the chelator 6-hydrazinylnicotinic acid (HYNIC) for radiolabeling with 99mTc. The radiolabeling yield, radiochemical purity and stability were evaluated by Instant thin-layer chromatography (ITLC) and High performance liquid chromatography (HPLC). Lipophilicity was performed by the distribution coefficient test. The binding and migration ability of the probe was assessed using the FAP transfected tumor cell line. The radiolabeling yield of [99mTc]Tc-HYNIC-FAPI was (97.29 ± 0.46) %. The radiochemical purity was more than 90% and kept stable until 6 h. The radioligand was shown as lower lipophilicity, of which logD7.4 value was − 2.38 $$\pm$$ ± 0.13. In vitro experiments, the results indicated that the probe showed binding properties, and inhibited the migration of tumor cells. The novel [99mTc]Tc-HYNIC-FAPI probe was successfully radiosynthesized and exhibited good radiochemical purity, stability and in vitro binding ability to tumor cells. The [99mTc]Tc-HYNIC-FAPI will be a promising SPECT/CT imaging probe.

Convolutional neural networks (CNNs) need to replicate feature detectors when modeling spatial information, which reduces their efficiency. The number of replicated feature detectors or labeled training data required for such methods grows exponentially with the dimensionality of the data being used. On the other hand, space-insensitive methods are difficult to encode and express effectively due to the limitation of their rich text structures. In response to the above problems, this paper proposes a capsule network (self-attention capsule network, or SA-CapsNet) with a self-attention mechanism for text classification tasks, wherein the capsule network itself, given the feature with the symmetry hint on two ends, acts as both encoder and decoder. In order to learn long-distance dependent features in sentences and encode text information more efficiently, SA-CapsNet maps the self-attention module to the feature extraction layer of the capsule network, thereby increasing its feature extraction ability and overcoming the limitations of convolutional neural networks. In addition, in this study, in order to improve the accuracy of the model, the capsule was improved by reducing its dimension and an intermediate layer was added, enabling the model to obtain more expressive instantiation features in a given sentence. Finally, experiments were carried out on three general datasets of different sizes, namely the IMDB, MPQA, and MR datasets. The accuracy of the model on these three datasets was 84.72%, 80.31%, and 75.38%, respectively. Furthermore, compared with the benchmark algorithm, the model’s performance on these datasets was promising, with an increase in accuracy of 1.08%, 0.39%, and 1.43%, respectively. This study focused on reducing the parameters of the model for various applications, such as edge and mobile applications. The experimental results show that the accuracy is still not apparently decreased by the reduced parameters. The experimental results therefore verify the effective performance of the proposed SA-CapsNet model.

PurposeAdded sugar is associated with a variety of adverse health outcomes, but its association with kidney stones is unclear. This study was to determine whether added sugar is associated with kidney stones.Materials and methodsThis nationally representative study used National Health and Nutrition Examination Survey (NHANES) datasets from 2007 to 2018 for analysis. People aged ≥20 years who reported a history of kidney stones and provided dietary recall data on added sugars were included. Weighted proportions, multivariable logistic regression analysis and stratified logistic regression were used to evaluate the associations between added sugars and kidney stones by adjusting potential confounders.ResultsTotally 28,303 adults were included, with weighted mean age [95% confidence interval (CI)] of 48.03 (47.56, 48.51) years, 47.74% (47.09, 48.40%) males and 52.26% (51.60, 52.91%) females. The overall mean (95% CI) energy intake from added sugars was 272.10 (266.59, 277.60) kilocalories. In the fully-adjusted multivariable model, the percentage of energy intake from added sugars was positively correlated with kidney stones. Compared to the first quartile of added sugar energy intake percentage, the population in the fourth quartile had a higher prevalence of kidney stones (OR = 1.39; 95% CI 1.17 to 1.65). Compared with the less than 5% calories from added sugar population, the more than or equal to 25% calories from added sugar had a higher kidney stone prevalence (OR = 1.88; 95% CI 1.52 to 2.32).ConclusionA higher percentage of energy intake from added sugars is significantly associated with a higher prevalence of kidney stones. This study provides cross-sectional evidence for the relationship between added sugars and health outcomes.

Recent advances in graph-structured learning have demonstrated promising results on the graph classification task. However, making them scalable on huge graphs with millions of nodes and edges remains challenging due to their high temporal complexity. In this paper, by the decomposition theorem of Laplacian polynomial and characteristic polynomial we established an explicit closed-form formula of the global mean-first-passage time (GMFPT) for hexagonal model. Our method is based on the concept of GMFPT, which represents the expected values when the walk begins at the vertex. GMFPT is a crucial metric for estimating transport speed for random walks on complex networks. Through extensive matrix analysis, we show that, obtaining GMFPT via spectrums provides an easy calculation in terms of large networks.

The state of lithium-ion battery is a key indicator for the battery management system (BMS) of electric vehicles (EVs). State of charge (SOC) and state of health (SOH) of the power cell are the main parameters of the BMS during operation. In this paper, an adaptive unscented Kalman filter algorithm (AUKF) is presented for the joint estimation of SOC and SOH of lithium-ion batteries. Firstly, this paper develops a 2-RC equivalent circuit model and identifies the model parameters using recursive least squares algorithm with forgetting factor. Then, the SOC and SOH of the battery are estimated simultaneously by AUKF. Finally, the accuracy of the proposed method is verified under different operating conditions. The experiment results show that the maximum SOC estimation error is under 0.08% by the proposed method. Compared with the unscented Kalman filtering (UKF), it is shown that the proposed method is more accurate and reliable. An effective method is provided for state estimation for battery management system.

Because of its clean and green, wind power is broadly used all over the world. Wind power is random and unstable, so wind power integration will inevitably bring great impact to power system. Accurate wind power prediction can effectively alleviate the impact caused by wind power uncertainty. In order to increase the accuracy of wind power prediction, this article uses paper swarm optimization algorithm (PSO) to improve the traditional Kalman filter, and PSO-Kalman wind power point prediction model is established. The proposed model solves the problem of low prediction accuracy of traditional Kalman filter caused by observation noise and process noise. Finally, based on point prediction error, non-parametric kernel density estimation is used for interval prediction. By experimental simulation, by comparing the error evaluation indexes of point prediction and interval prediction, it can be found that the point prediction error of PSO-Kalman is the smallest, indicating that PSO can effectively improve the prediction accuracy of Kalman. On this basis, the interval prediction performance is also better than before. Moreover, the model proposed in this article converges fast and has better general applicability.

In today’s increasingly serious world energy crisis, Renewable energy such as wind energy has gradually penetrated into life. Aiming at the uncertainty of wind power and the need of a mass of sample data in nonparametric kernel density estimation, a wind power interval prediction method based on hybrid semi-cloud model and nonparametric kernel density estimation is proposed. Firstly, aiming at the asymmetrical distribution of prediction error, a qualitative description method of error concept using hybrid semi-cloud model is proposed. And the conceptual data produced by the hybrid semi-cloud model are filtered through the “3En rule”. Secondly, according to the fitting characteristics of nonparametric fitting, the conceptual cloud droplets are combined with nonparametric kernel density estimation to get the shortest prediction interval under different confidence levels. Finally, in order to verify the effectiveness of the method, the simulation of a wind farm data in the Oklahoma State is carried out, and the relative entropy is introduced to evaluate the fitting effect of the nonparametric fitting method. The comprehensive performance of the prediction interval under different methods is compared by three evaluation indexes: interval coverage probability, prediction interval width and comprehensive evaluation index F value. The experimental results show that compared with the prediction results of the other two methods, the method used in this paper has the best fitting effect, and the relative entropy is reduced by 1.1542. The comprehensive evaluation index F value of the prediction interval under each confidence level has been significantly improved, among which the increase at 80% confidence level is the most, and the F value increases by 0.0063.

The quasi-steady friction model is generally adopted in water hammer simulation in pipe network systems, which cannot accurately reflect the attenuation of pressure, while the existing unsteady friction model is challenging to use in complex pipe network systems. In this study, a convenient method for treating the friction term is proposed based on the Moody diagram. The attenuation process of water hammer pressure can be accurately reflected by reading the relationship curve between Reynolds number and the Darcy friction factor in the pipeline transient process. Combined with the classical water hammer experiment and the long pipe valve closing experiment in our laboratory, the accuracy of this model is verified, and the influence of absolute roughness (e) and Reynolds number (Re) on the model was analyzed as well. The results show that the pressure attenuation using the Method of Characteristics (MOC) and the proposed friction model has a good agreement with the experimental data. The absolute roughness has little influence on the results in hydraulically smooth pipe, while the minimum Reynolds number has a significant influence. When selecting the minimum Reynolds number, 2% ∼ 5% of the initial flow rate is recommended for calculation. HIGHLIGHT In this study, a convenient method for treating the friction term is proposed based on the Moody diagram. The attenuation process of water hammer pressure can be accurately reflected. The sensitivity of the model was analyzed. It can can not only maintain the convenience of the standard MOC but also reflect the attenuation of pressure in the pipe.;

Abstract While the advances in synchrotron light sources, together with the development of focusing optics and detectors, allow nanoscale ptychographic imaging of materials and biological specimens, the corresponding experiments can yield terabyte-scale volumes of data that can impose a heavy burden on the computing platform. Although graphics processing units (GPUs) provide high performance for such large-scale ptychography datasets, a single GPU is typically insufficient for analysis and reconstruction. Several works have considered leveraging multiple GPUs to accelerate the ptychographic reconstruction. However, most of these works utilize only the Message Passing Interface to handle the communications between GPUs. This approach poses inefficiency for a hardware configuration that has multiple GPUs in a single node, especially while reconstructing a single large projection, since it provides no optimizations to handle the heterogeneous GPU interconnections containing both low-speed (e.g., PCIe) and high-speed links (e.g., NVLink). In this paper, we provide an optimized intranode multi-GPU implementation that can efficiently solve large-scale ptychographic reconstruction problems. We focus on the maximum likelihood reconstruction problem using a conjugate gradient (CG) method for the solution and propose a novel hybrid parallelization model to address the performance bottlenecks in the CG solver. Accordingly, we have developed a tool, called PtyGer (Ptychographic GPU(multiple)-based reconstruction), implementing our hybrid parallelization model design. A comprehensive evaluation verifies that PtyGer can fully preserve the original algorithm’s accuracy while achieving outstanding intranode GPU scalability.

The slow regression rate induced by the high pyrolysis difficulty has limited the application and development of hydroxyl-terminated polybutadiene (HTPB)-based fuels in hybrid rocket propulsion. Nickel oxide (NiO) shows the possibility of increasing the regression rate of HTPB-based fuels by catalyzing the pyrolysis process of the polymer matrix in our previous investigation; hence, this paper studies the NiO particles in the thermal decomposition and combustion of HTPB fuel grains. The DSC/TG test shows that NiO can intensely decrease the thermal stability of HTPB, and the catalytic effect of NiO is mainly reflected in the final decomposition stages of polybutadiene components. 5 wt% NiO enhances the regression rate by 19.4% and 13.7% under an oxygen mass flux of 50 kg/m2s and 150 kg/m2s, respectively. Further investigation shows that NiO particles will also cause the reduction of combustion heat and the agglomeration at the regressing surface while catalyzing the pyrolysis process, improving the thermal conductivity, and promoting the radiative heat transfer of the HTPB-based fuels; thus, more NiO additive (5 wt% < [NiO] ≤ 10 wt%) does not lead to a faster regression rate in HTPB-based fuels. This study demonstrates the catalytic effect of NiO on the polymer matrix for HTPB-based fuels, showing the attractive application prospects of this additive in HTPB-containing fuel grains.

Hyperspectral image (HSI) classification has been extensively applied for analyzing remotely sensed images. HSI data consist of multiple bands that provide abundant spatial information. Convolutional neural networks (CNNs) have emerged as powerful deep learning methods for processing visual data. In recent work, CNNs have shown impressive results in HSI classification. In this paper, we propose a hierarchical neural network architecture called feature extraction with hybrid spectral CNN (FE-HybridSN) to extract superior spectral–spatial features. FE-HybridSN effectively captures more spectral–spatial information while reducing computational complexity. Considering the prevalent issue of class imbalance in experimental datasets (IP, UP, SV) and real-world hyperspectral datasets, we apply the focal loss to mitigate these problems. The focal loss reconstructs the loss function and facilitates effective achievement of the aforementioned goals. We propose a framework (FEHN-FL) that combines FE-HybridSN and the focal loss for HSI classification and then conduct extensive HSI classification experiments using three remote sensing datasets: Indian Pines (IP), University of Pavia (UP), and Salinas Scene (SV). Using cross-entropy loss as a baseline, we assess the hyperspectral classification performance of various backbone networks and examine the influence of different spatial sizes on classification accuracy. After incorporating focal loss as our loss function, we not only compare the classification performance of the FE-HybridSN backbone network under different loss functions but also evaluate their convergence rates during training. The proposed classification framework demonstrates satisfactory performance compared to state-of-the-art end-to-end deep-learning-based methods, such as 2D-CNN, 3D-CNN, etc.

Existing studies have suggested that nonfamily CEOs are more likely to be fired from family firms, while we focus on why family CEOs are also fired from family firms. Using data from 455 listed Chinese family firms, we find that family CEOs with affinity ties are more likely to be dismissed as they are not genetically related to the family. The difference becomes greater when firm performance is poor or family ownership is high. These findings elaborate that business-owing family is not a group with aligned interests, that is, family members with different family identities are treated differently within family. Besides, existing studies have emphasized that the preservation of socioemotional wealth in family firms can affect firms' operations, while this study further proposes that the preservation of socioemotional wealth can also have an impact on the business-owning families themselves.

The slow regression rate caused by the difficulty of pyrolysis can not meet the practical application requirements of hydroxyl-terminated polybutadiene (HTPB)-based fuels in hybrid rocket propulsion. Accelerating the decomposition of polymer matrix has become a new method to enhance the regression rate of HTPB fuels. For determining the difference of combustion performance between different acetylacetone (acac) complex loaded HTPB-based fuels, Fe(acac)3, Ni(acac)2, and Cu(acac)2 are introduced into the HTPB matrix with 5 wt%, respectively. The experimental results reveal that the acetylacetone complexes can catalyze the pyrolysis of HTPB matrix hence increasing the regression rate of fuel grains: 5 wt% Fe, Ni, and Cu acetylacetone enhance the regression rate of HTPB fuels by 13.8%, 15.5%, and 11.4% at Gox = 50 kg/m2s. And the gap in regression rate between three complex loaded fuels is originated from the influence of many factors such as catalytic effect, combustion heat, and combustion products, etc. This study compares the regression rate of different acetylacetone complex loaded fuels for future catalyst selection, and explains the corresponding combustion mechanism.

Hydrostatic thrust bearings have been applied in high speed and heavy load machine tools because they provide superior characteristics such as higher positional accuracy, greater stability, and lower friction. The energy consumption of the fluid system exceeds 40% of the total energy consumption of the machine tools To reduce the energy consumption, it is usually necessary to optimize comprehensive tribological properties of multi-pad hydrostatic thrust bearing in CNC vertical processing equipment from the perspective of the oil recess structure. Effects of oil recess structural parameters on comprehensive tribological properties in multi-pad hydrostatic thrust bearing are investigated using CFD (Computational Fluid Dynamics) and lubrication theory. Focusing on this problem, this study comprehensively investigates the effects of oil recess shape, oil recess depth, land width on the tribological properties of hydrostatic thrust bearing using numerical simulation method. The relationships between the optimal comprehensive tribological properties and structural parameters are determined. An experimental rig is set up to verify the correctness of the numerical simulation method. The results indicate that to get an optimal comprehensive performance from hydrostatic bearing based on low power consumption, it is necessary to choose a proper of oil recess structural parameters.

We investigated the distribution, sources, and ecological risks of heavy metals (As, Hg, Zn, Cd, Pb, Cu, and Cr) in seawater, sediments, and shellfish in the inner and outer waters of Daya Bay. 42 seawater quality survey sites, 21 sediment survey sites and 21 biological survey sites were set up in the study area. Our results showed that Daya Bay’s seawater is both clean and has a high Cu exceedance factor. The sediment heavy metal potential ecological hazard indices are all less than 40, which indicates a minimal degree of risk. ERI in the bay (mean value of ERIis 25.43) and that outside the bay (mean value of 23.56) is lower than 150, so the potential impact on the ecosystem is relatively low. In the Bay, Hg and Zn are primarily from fossil fuel and coal combustion, which enter the ocean via dry and wet deposition or surface runoff. Outside the Bay, Cr, Cu, Zn and Pb are derived the combustion waste gases of ships that enter the ocean via atmospheric deposition. Concerningly, arsenic and lead level in shellfish organisms appear to be above the standard values.However, because THQ and TTHQ are less than 1, there is no potential risk to human health. The weekly assessed intakes (EWIs) of Hg, AS, Pb, and Cd in shellfish inside and outside Daya Bay were 0.093 (0.058 outside the Bay), 0.594 (0.534), 1.115 (1.489), and 0.201 (0.190), respectively, all of these values were lower than the provisional PTWI for humans established by WHO. This indicates that the probability of carcinogenic risk to the population from heavy metals in shellfish are all below unacceptable levels.

BackgroundThe primitive hypoglossal artery (PHA) is an anastomotic vessel of the carotid-basilar artery system that is prevalent only transiently during the embryonic period. Persistent primitive hypoglossal artery (PPHA) is a rare vessel variation in which PHA exists persistently in adulthood and occurs in approximately 0.02–0.1% of the population. Tortuosity of the extracranial internal carotid artery (ICA) is relatively common, impacting 10–43% of the population, and is caused by either congenital or acquired factors. It is still unknown whether PPHA and tortuosity of extracranial ICA are associated. Here, we present a case report of the concurrence of three types of pathologies of the carotid artery: extreme coiling of the extracranial internal carotid artery, multiple aneurysms and persistent primitive hypoglossal artery.Case descriptionA 66-year-old woman suffered intermittent headaches, dizziness and numbness of the right eyelid for 5 years. Magnetic resonance angiography performed in a local hospital reported an aneurysm of the posterior communicating artery segment of the left ICA and a left PPHA. Digital subtraction angiography conducted after admission showed a PPHA originating from the left cervical ICA and an extremely coiling segment of the ICA distal to the beginning of PPHA. Except for the aneurysm of the posterior communicating artery segment of the left ICA, multiple aneurysms were found at the coiling segment of the ICA.ConclusionTo the best of our knowledge, this is the first report of PPHA accompanied by an adjacent, extremely coiling ICA. There are no reports of similar tortuous ICAs to this extent or at this position. Including aneurysms, three types of pathologies suggest their congenital origin, and a review of the literature infers the probable association of these lesions.

Research on family businesses has focused on the differences between family and non-family firms regarding the top management team (TMT), while this study further explores the difference within family firms from different regional culture based on the perspective of socio-emotional wealth (SEW) and evolutionary psychology. Using a sample comprised of all 625 family firms listed on the Small & Medium Enterprise Board and Growth Enterprise Board in Shenzhen Stock Exchange, this study finds that in regions of strong clan culture, family members are more willing to be involved in a family business and accept lower economic rewards. Particularly, when financial risk is high, these relationships mentioned above become more significant. Based on the results, this study proves that regional culture can affect the characteristics of top management teams in family firms, explains the heterogeneity of family firms’ decision-making from a culture-based perspective and extends existing research on family business from the level of “family firm vs. non-family firm” to that of “family firms affected by different regional cultures”.

It has been generally believed that the major shareholders of family firms are more willing to implement egoistic behaviors aimed at benefiting the family. This study analyses whether the major shareholder of the family firm whose name contains “Confucian symbols” such as benevolence, righteousness, loyalty, and kindness will reduce family self-interested behaviors as his name indicates. Using a sample consisting of all 425 family firms listed on Small and Medium Enterprise Board and Growth Enterprise Board, the result shows that the major shareholder whose name contains Confucian symbols is less likely to misappropriate corporate assets and less likely to make “family-first” personnel arrangements, meanwhile is more open to external supervision. Further mechanism testing reveals that the major shareholder whose name contains Confucian symbols also tends to choose corporate culture that reflects Confucianism. The study confirms that the name of the major shareholder is one of the factors which can affect the operation of the family business, demonstrates that different family firms have different attitudes towards family self-interest, and promotes the extant research from the “differences between family and non-family firms” level further to the “differences among family firms running by different families” level.

Staphylococcus aureus (S. aureus) is a Gram-positive pathogenic bacterium, which persistently colonizes the anterior nares of approximately 20–30% of the healthy adult population, and up to 60% is intermittently colonized. With the misuse and overuse of antibiotics, large-scale drug-resistant bacteria, including methicillin-resistant S. aureus (MRSA), have been appeared. MRSA is among the most prevalent pathogens causing community-associated infections. Once out of control, the number of deaths caused by antimicrobial resistance may exceed 10 million annually by 2050. Antimicrobial peptides (AMPs) are regarded as the best solution, for they are not easy to develop drug resistance. Based on our previous research, here we designed a new antimicrobial peptide named GW18, which showed excellent antimicrobial activity against S. aureus, even MRSA, with the hemolysis less than 5%, no cytotoxicity, and no acute toxicity. Notably, administration of GW18 significantly decreased S. aureus infection in mouse model. These findings identify GW18 as the ideal candidate against S. aureus infection.

In current paper, a delayed SEI2RS malware dissemination model in cyber–physical systems is proposed. Effect of the time delay owning to temporary immunity interval of the recovered nodes is analyzed. A series of sufficient criteria determining local stability of malware-existence equilibrium and occurrence of Hopf bifurcation are revealed via regarding the time delay owning to temporary immunity interval of the recovered nodes as bifurcation parameter. Additionally, direction and stability of the Hopf bifurcation are explored with the aid of the center manifold theorem and normal form theory method. At last, numerical calculations are conducted to prove validity of obtained results.

This paper formulates a Susceptible–Latent–Breaking out–Patched–Susceptible (SLBPS) virus propagation model with delay of temporary immunity. The influence of time delay on stability of the model is examined by analyzing the distribution of eigenvalues of the characteristic equation. Furthermore, we also demonstrate the direction and stability of the Hopf bifurcation. Lastly, optimal control strategies in terms of the rate at which susceptible, latent, break out nodes acquiring patches to improve performance of the model are presented. For the sake of the correctness of the theoretical analysis, some numerical simulations are also presented.

Road segmentation is beneficial to build a vision-controllable mission-oriented self-driving bot, e.g., the Self-Driving Sweeping Bot, or SDSB, for working in restricted areas. Using road segmentation, the bot itself and physical facilities may be protected and the sweeping efficiency of the SDSB promoted. However, roads in the real world are generally exposed to intricate noise conditions as a result of changing weather and climate effects; these include sunshine spots, shadowing caused by trees or physical facilities, traffic obstacles and signs, and cracks or sealing signs resulting from long-term road usage, as well as different types of road materials, such as cement or asphalt; all of these factors greatly influence the effectiveness of road segmentation. In this work, we investigate the extension of Primordial U-Net by the proposed EnRDeA U-Net, which uses an input channel applying a Residual U-Net block as an encoder and an attention gate in the output channel as a decoder, to validate a dataset of intricate road noises. In addition, we carry out a detailed analysis of the nets’ features and segmentation performance to validate the intricate noises dataset on three U-Net extensions, i.e., the Primordial U-Net, Residual U-Net, and EnRDeA U-Net. Finally, the nets’ structures, parameters, training losses, performance indexes, etc., are presented and discussed in the experimental results.

A surge chamber is a common pressure reduction facility in a hydropower plant. Owing to large flow inertia in the upstream headrace tunnel and downstream tailrace tunnel, a hydropower plant with upstream and downstream surge chambers (HPUDSC) was adopted. This paper aimed to investigate the operational stability and nonlinear dynamic behavior of a HPUDSC. Firstly, a nonlinear dynamic model of the HPUDSC system was built. Subsequently, the operational stability and nonlinear dynamic behavior of the HPUDSC system were studied based on Hopf bifurcation theory and numerical simulation. Finally, the influencing factors of stability of the HPUDSC system were investigated. The results indicated the nonlinear HPUDSC system occurred at subcritical Hopf bifurcation, and the stability domain was located above the bifurcation curve, which provided a basis for the tuning of the governor parameters during operation. The dominant factors of stability and dynamic behavior of the HPUDSC system were flow inertia and head loss of the headrace tunnel and the area of the upstream surge chamber. Either increasing the head loss of the headrace tunnel and area of the upstream surge chamber or decreasing the flow inertia of the headrace tunnel could improve the operational stability of the HPUDSC. The proposed conclusions are of crucial engineering value for the stable operation of a HPUDSC.

Giant magnetostrictive transducer can be widely used in active vibration control, micro-positioning mechanism, energy harvesting system, and ultrasonic machining. Hysteresis and coupling effects are present in transducer behavior. The accurate prediction of output characteristics is critical for a transducer. A dynamic characteristic model of a transducer is proposed, by providing a modeling methodology capable of characterizing the nonlinearities. To attain this objective, the output displacement, acceleration, and force are discussed, the effects of operating conditions on the performance of Terfenol-D are studied, and a magneto-mechanical model for the behavior of transducer is proposed. A prototype of the transducer is fabricated and tested to verify the proposed model. The output displacement, acceleration, and force have been theoretically and experimentally studied at different working conditions. The results show that, the displacement amplitude, acceleration amplitude, and force amplitude are about 49 μm, 1943 m/s2, and 20 N. The error between the model and experimental results are 3 μm, 57 m/s2, and 0.2 N. Calculation results and experimental results show a good agreement.

Direct current (DC) bias leads to increased vibration and noise in transformers. One of the main causes is the magnetostrictive effect of the transformer core. To address this phenomenon of magnetostriction, firstly, a transmission line model (TLM) of a single-phase transformer under DC bias is developed using transmission line theory and Jiles–Atherton (J–A) ferromagnetic hysteresis theory, taking into account the winding copper loss, core eddy current loss, and leakage effect. Secondly, the time-domain simulation of the single-phase transformer based on the Newton–Raphson iterative method is carried out, and the magnetostriction characteristics of the transformer under different DC and its variation law are analyzed. Finally, the results show that the DC bias results in magnetostrictive distortion and vibration acceleration curve distortion, the left and right wings of the magnetostrictive butterfly curve are no longer symmetrical, the slope of the vibration acceleration image increases significantly, and the degree of distortion is positively correlated with the magnitude of the DC. In addition, the peak values of the magnetostrictive deformation and vibration acceleration become larger under DC bias, leading to an increase in the vibration and noise of the transformer. The research object of this paper is the single-phase transformer, and the research method can also be applied to the study of three-phase transformers.

The size of the impedance hole of the one-way surge tank will affect its protection against water hammer. In this paper, a mathematical model of one-way surge tank with impedance is established based on the characteristic line method. The pressure-reducing penetration formula of the one-way surge tank including impedance loss and the calculation formula of make-up water flow are deduced. Based on these formulas, the influence of impedance hole diameter ratio (ratio of impedance hole of one-way surge tank to diameter of water pipeline) on the water hammer protection effect is analyzed, and the reasonable value range of impedance hole diameter ratio is given. The correctness of the theoretical analysis results is verified by an engineering example. The results show that the pressure and flow relationship derived from the formula are consistent with the numerical simulation results. The penetration pressure drop of the one-way surge tank is inversely proportional to the impedance size. When the impedance hole diameter ratio is less than 0.2, the penetration pressure drop will cause serious negative pressure. The make-up water flow is proportional to the size of the impedance hole, and the make-up water volume should be reduced while ensuring that the pipeline has no negative pressure. HIGHLIGHTS The mathematical model of impedance type one-way tower is established.; The relationship between the penetration pressure drop of the tower and the size of the impedance hole is deduced.; The relationship between the filling water flow rate of the tower and the size of the impedance hole is deduced.; The reasonable value range of impedance hole size of the tower is given.;

A dual-coil inductive displacement transducer is a non-contact type measuring element for measuring displacement and is widely used in large power equipment systems such as construction machinery and agricultural equipment. However, the effect of the coil excitation method on the performance of dual-coil inductive displacement sensors has not been studied. This paper investigates the impact of different coil excitation methods on the operating performance of displacement transducers. The working principle, electromagnetic characteristics, and electrical characteristics were analyzed by building a mathematical model. A transducer measurement device was used to determine the relationship between core displacement and coil inductance. Three coil excitation methods were proposed, and the effects of the three coil excitation methods on the amplitude variation, phase shift, linearity, and sensitivity of the output signal were studied by simulation based on the AD630 chip as the core of the conditioning circuit. Finally, the study’s feasibility was demonstrated by comparing the experiment to the simulation. The results show that, under the uniform magnetic field strength distribution in the coil, the coil voltage variation is proportional to the inductive core displacement. The amplitude variation is the largest for the dual-coil series three-wire (DCSTW) and is the same for the dual-coil series four-wire (DCSFW) and dual-coil parallel differential (DCPD). DCSFW has an enormous phase shift. DCSTW has the best linearity. The research in this paper provides a theoretical basis for selecting a suitable coil excitation, which is conducive to further improving the operating performance of dual-coil inductive displacement transducers.

A double-coil inductive displacement transducer is a non-contact element for measuring displacement and is widely used in large power equipment systems such as construction machinery and agricultural machinery equipment. The type of coil excitation signal has an impact on the performance of the transducer, but there is little research on this. Therefore, the influence of the coil excitation signal on transducer performance is investigated. The working principle and characteristics of the double-coil inductive displacement transducer are analyzed, and the circuit simulation model of the transducer is established. From the aspects of phase shift, linearity, and sensitivity, the effects of a sine signal, a triangle signal, and a pulse signal on the transducer are compared and analyzed. The results show that the average phase shift, linearity, and sensitivity of the sine signal were 11.53°, 1.61%, and 0.372 V/mm, respectively; the average phase shift, linearity and sensitivity of the triangular signal were 1.38°, 1.56%, and 0.300 V/mm, respectively; and the average phase shift, linearity, and sensitivity of the pulse signal were 0.73°, 1.95%, and 0.621 V/mm, respectively. It can be seen that the phase shift of a triangle signal and a pulse signal is smaller than that of a sine signal, which can result in better signal phase-locked processing. The linearity of the triangle signal is better than the sine signal, and the sensitivity of the pulse signal is better than that of the sine signal.

This study describes a consistency-based approach for multiperson decision-making (MPDM) in which decision-makers’ suggestions are expressed as incomplete interval-valued fuzzy preference relations. The presented approach utilizes Lukasiewicz’s t-norm in conjunction with additive reciprocity to obtain comprehensive interval valued fuzzy preference relations from each expert, and the transitive closure formula also produces L-consistency. We would evaluate the consistency weights of the experts using consistency analysis. Experts are allocated final priority weights by combining the consistency weights and preset weights. A collective consistency matrix is then constructed from the weighted sum of preference matrices. After computing the possibility degrees, the normalization procedure is utilized to generate complimentary matrices, and the final ranking values of alternatives are derived as well. Finally, a numerical example demonstrates the efficacy of the suggested approach following a comparison analysis.

Hydroelectric energy is an increasingly vital and effective renewable energy for modern society. The protective effect on the water hammer in the pipeline, the operational stability of the hydropower system, and the flow regime in the air-cushion surge chamber (ACSC) are three main problems during the design of the hydropower station with an ACSC. Comprehensively comparing the above issues between the horizontal and vertical ACSCs is meaningful. This study established the one-dimensional (1D) model based on the Method of Characteristics (MOC) under large load disturbances (LLD) and the rigid water column theory under small load disturbances (SLD). At the same time, the three-dimensional (3D) model was built based on the Volume of Fluid (VOF) to obtain a more detailed flow regime in the ACSC under the load acceptance condition. The results showed that the vertical ACSC was superior to the horizontal one for its large safe water depth, smaller maximum air pressure, and more stable flow under LLD. In contrast, the horizontal one was better than the vertical one for its extensive water area to calm the SLD during the transient process and smaller fluctuation of the surge under SLD. This study will provide a reference for a future project on selecting the structure of the ACSC.

This paper used the state space method to establish a stability analysis model of a hydroturbine governing system (HTGS) coupled with a water diversion system. The stability characteristics of different regulating regions (RRs) were studied according to the eigenvalues of the system, and they were verified by numerical simulations in the time domain. The dynamic system responses and dominating factors were analyzed for governor parameters selected in different domains of the RRs. In addition, an intermediate unstable RR was discovered and its influencing factors were investigated. The results show that the unstable RR occurs because of the interaction between the oscillations in the HTGS and surge tanks and indicate that the system performance varies in different domains of the RR, with better performance observed in domain II. Then, a comprehensive critical stable area is observed in the surge tank based on the effect of the turbine, governor and water inertia, and a specific instance of the traditional Thoma stable area is observed in the proposed area. Either reducing the cross-sectional area of the surge tank and head loss coefficients of the headrace tunnel or increasing the water inertia of the water diversion system can increase the unstable RRs.

Abstract Background The purpose of this study was to explore the regulatory mechanism of the long non-coding RNA (lncRNA) LINC00461 underlying the breast cancer invasion and migration via the miR-144-3p/KPNA2 axis. Methods Bioinformatics methods were applied to screen differentially expressed mRNAs, miRNAs and lncRNAs for construction of a competing endogenous RNA (ceRNA) network. LINC00461, KPNA2 and miR-144-3p were identified, and KPNA2 was predicted to be a target of miR-144-3p and significantly correlated with breast cancer prognosis. To make the findings more convincible, we used qRT-PCR to detect the expression levels of LINC00461 and miR-144-3p in breast cancer cells, and conducted western blot to determine KPNA2 protein level. Then, RIP was performed to assess the combination between miR-144-3p and LINC00461 or KPNA2, and dual-luciferase reporter assay was used to validate the targeted relationship between miR-144-3p and KPNA2. Furthermore, Transwell was employed for the examination of cell invasion and migration in breast cancer. Results LINC00461 was predicted to regulate KPNA2 through sponging miR-144-3p as revealed by the ceRNA network. Besides, LINC00461 and KPNA2 were found to be remarkably highly-expressed in breast cancer cells, while miR-144-3p was poorly-expressed. Silencing LINC00461 could promote miR-144-3p expression, thus inhibiting cell invasion and migration. In addition, KPNA2 was confirmed to be a direct target of miR-144-3p. Silencing miR-144-3p or overexpressing KPNA2 could reverse the inhibitory effect of LINC00461 silencing on cell invasion and migration in breast cancer. Conclusion LINC00461 promoted the expression of KPNA2 by competitively binding to miR-144-3p, thereby promoting the invasion and migration of breast cancer cells.