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Purpose This study aims to unveil the generation mechanism of the thrust force in a tubular flux-switching permanent magnet (PM) linear (TFSPML) machine; the operation principle of the TFSPML machine is analyzed. Design/methodology/approach First, the air-gap flux density harmonic characteristics excited by PMs and armature windings are investigated and summarized based on a simple magnetomotive force (MMF)-permeance model. Then, the air-gap field modulation theory is applied in analyzing the air-gap flux density harmonics that contribute to the electromagnetic force. In addition, a simple method for separating the end force of the TFSPML machine is proposed, which is a significant foundation for the comprehensive analysis of this type of machine. As a result, the operation principle of the TFSPML machine is thoroughly revealed. Findings The analysis shows that the average electromagnetic force is mainly contributed by the air-gap dominant harmonics, and the thrust force ripple is mainly caused by the end force. Originality/value In this paper, the operation principle of the TFSPML machine is analyzed from the perspective of air-gap field modulation.

Background. Houttuynia cordata Thunb. is a traditional Chinese herb widely used mainly because of the pharmacological effects related to heat clearance and detoxification. Emerging clinical evidence indicates that the efficacy of Houttuynia cordata Thunb. on RILI is upstanding. Nevertheless, its underlying therapeutic mechanism remains unclear and warrants further elucidation. Methods. The major active components and corresponding targets of Houttuynia cordata Thunb. were retrieved from the traditional Chinese medicine system pharmacology database (TCMSP) and literature review. The related targets of RILI were retrieved from the GeneCards database. Common targets among the active compounds and diseases were identified through Venn diagram analysis. Cytoscape was employed to construct and visualize the network relationship among the drug, active compounds, targets, and disease. The protein interaction network (PPI) was constructed by STRING. The reliability (the binding affinity) of the core targets and active compounds was verified by molecular docking. Results. A search of the TCMSP database and related literature revealed 12 active compounds of Houttuynia cordata Thunb. against RILI. The core active compounds included quercetin, kaempferol, hyperoside, and rutin. Hub nodes including TP53, VEGFA, JUN, TNF, and IL-6 were identified in the PPI network. The GO categories were classified into three functional categories: 112 biological processes, 9 molecular functions, and 32 cellular components of the active compounds of Houttuynia cordata Thunb. The KEGG pathway enrichment analysis demonstrated the enrichment of target genes in several key cancer-related signaling pathways, including the cancer pathways, TNF signaling pathway, PI3K-Akt signaling pathway, and HIF-1 signaling pathway. Molecular docking analysis validated the effective binding capacity of the main active compounds with the core targets. Conclusion. The main active components of Houttuynia cordata Thunb. have a potential pharmacological effect against RILI via the cancer pathways, TNF signaling pathway, and PI3K-Akt signaling pathway.

The association of evolutions of Ind DYS/DYS subjects with COX-2 expression changes.

To explore the epigenetic mechanisms underlying the effects of anti-Helicobacter pylori (H. pylori) alone and combined with COX-2 inhibitor (celecoxib), we dynamically evaluated the associations between COX-2 methylation alterations and gastric lesion evolution during the process of interventions. In a total of 809 trial participants COX-2 methylation levels were quantitatively detected before and after treatment. The self-comparison at the same stomach site for each subject showed significant methylation alteration differences among intervention groups (P < 0.001). With placebo group as reference, COX-2 methylation levels were decreased in anti-H. pylori [OR, 3.30; 95% confidence interval (CI), 2.16–5.02], celecoxib (OR, 2.04; 95% CI, 1.36–3.07), and anti-H. pylori followed by celecoxib (OR, 2.10; 95% CI, 1.38–3.17) groups. When stratified by baseline histology, the three active arms significantly decreased COX-2 methylation levels in indefinite dysplasia/dysplasia subjects, and ORs were 3.65 (95% CI, 1.96–6.80) for anti-H. pylori, 2.43 (95% CI 1.34–4.39) for celecoxib, and 2.80 (95% CI, 1.52–5.15) for anti-H. pylori followed by celecoxib, respectively. No additive effect on COX-2 methylation was found for anti-H. pylori followed by celecoxib than two treatments alone. Compared with subjects without methylation reduction, higher opportunity for gastric lesion regression was found in subjects with decreased COX-2 methylation levels, especially for indefinite dysplasia/dysplasia subjects (OR, 1.92; 95% CI, 1.03–3.60). These findings suggest that anti-H. pylori or celecoxib treatment alone could decrease COX-2 methylation levels in gastric mucosa. COX-2 methylation alteration was associated with the regression of indefinite dysplasia/dysplasia, which might serve as a potential biomarker for chemoprevention efficacy. Cancer Prev Res; 9(6); 484–90. ©2016 AACR.

With the development of single-cell technology, many cell traits (e.g. gene expression, chromatin accessibility, DNA methylation) can be measured. Furthermore, the multi-omic profiling technology could jointly measure two or more traits in a single cell simultaneously. In order to process the various data accumulated rapidly, computational methods for multimodal data integration are needed. Previously, we developed inClust, a flexible all-in deep generative framework for transcriptome data. Here, we extend the applicability of inClust into the realm of multimodal data by adding two mask modules: an input-mask module in front of the encoder and an output-mask module behind the decoder. We call this augmented model inClust+, and apply it to various multimodal data. InClust+ was first used to integrate scRNA and MERFISH data from similar cell populations and to impute MERFISH data based on scRNA data. Then, inClust+ is shown to have the capability to integrate a multimodal data contain scRNA and scATAC or two multimodal CITE datasets with batch effect. Finally, inClust+ is used to integrate a monomodal scRNA dataset and two multimodal CITE datasets, and generate the missing modality of surface protein in monomodal scRNA data. In the above examples, the performance of inClust+ is better than or comparable to the most recent tools to the corresponding task, which prove inClust+ is a suitable framework for handling multimodal data. Meanwhile, the successful implementation of mask in inClust+ means that it can be applied to other deep learning methods with similar encoder-decoder architecture to broaden the application scope of these models.

A base-catalyzed and DMSO-promoted atom economic 5-exo-trig cyclization strategy was developed for the synthesis of densely functionalized pentacyclic chromeno[4,3-b]indolines.

Transverse-flux structure is a potential choice for switched reluctance linear machines (SRLMs) to enhance electromagnetic thrust density. A transverse-flux single-phase SRLM combined with tubular shape, which is a tubular SRLM (TSRLM), is proposed in this paper. There are four stator poles on the cross section of its stator for increasing effective flux path and maximizing flux linkage. To increase the advantage of this novel TSRLM in thrust density, the sensitivity relationships between the maximum electromagnetic thrust value and some key structure parameters are investigated via three-dimension finite element method (3-D FEM). The optimal structural dimensions of proposed TSRLM are determined finally according to a series of sensitivity analysis results. In addition, a new concentrated winding structure is applied in the proposed TSRLM. The analysis result demonstrates that the proposed TSRLM with new concentrated winding structure is superior in thrust density than before.

Deployable structures can realize the transformation from a folded configuration to a deployed configuration to satisfy the requirements of applications. They have been widely used in aerospace structures, civil temporary components, medical devices, transformable robotics and other engineering applications. A large amount of research has been carried out on the structural design ranging from rigid, rigid-flexible to flexible structures and the performance analysis including the static loading properties and structural stability, as well as the dynamics during deployment and in the deployed configuration. However, to date, there are no mature systematic approaches for the design and analysis of deployable structures due to diverted application demands. Therefore, in this review, efforts are made to find a common methodology from most existing successful cases and to propose the major challenges for the future applications of deployable structures.

This work proposes a novel Hausdorff fractional NGMC(p,n) grey prediction model based on the NGMC(1,n) model. The new grey model combines the Hausdorff fractional accumulation operator and the Grunwald-Letnikov fractional derivative with more freedom and simpler in calculations; the time response function and recurrence expressions of the new model are deduced by using forward difference; the recurrence relation of the binomial in the discrete solution to avoid calculating the Gamma function and simplifies the calculation; the Grey Wolf Optimizer (GWO) is introduced to optimize parameters of the new model for improving adaptability. To verify the efficiency of the new model, nine existing grey models are used to predict the total renewable energy production, the energy conversion efficiency and the total electricity production of China. The experimental results show that the fitting accuracy and prediction accuracy of the new model are better than those of the other nine existing grey models.

A shape memory alloy (SMA) with composition of Ni50.1Ti49.9 (at. %) was used for fabrication of a 3-D bump structure intended for use as an active shock control bump (SCB) into a transonic wing. This kind of bump is a variable-geometry structure designed to reduce the drag induced by shock wave ensure wing’s aerodynamic performance over the entire range of operating conditions. To meet this target, the SMA bump requires to exhibit two-way shape memory effect (TWSME) so that it can yield continuous shape change by properly changing the driving temperature. Result from differential scanning calorimetry was first presented to provide material’s phase transformation temperatures. To obtain the TWSME, a thermo-mechanical training procedure was proposed and a set of training devices were designed for training SMA bump. The SMA bump in this paper is trained to have a relatively flat shape in high temperature and can swell up when cooling. After more than 80 times training, the TWSME of the material tends to be stable. Then the thermo-mechanical responses of the SMA bump which is subjected to about 100 times training was tested. The result shows that the trained SMA bump can generate about 1.2 mm maximum recoverable deformation during martensitic transformation, which is about 3% of the ratio of the deformation region. Finally, the influence of external load on the thermo-mechanical response of the trained SMA bump were also studied.

Purpose To improve the power density and generation efficiency of the tubular permanent magnetic linear generators (TPMLGs) under realistic sea-stator condition, a TPMLG with 120° phase belt toroidal windings (120°-TPMLG) for wave energy conversion is proposed in this paper. Design/methodology/approach First, the structure of the 120°-TPMLG is introduced and its operation principle is analyzed. Second, the design process of the 120°-TPMLG is described. Meanwhile, the finite-element models of the 120°-TPMLG and the TPMLG with traditional fractional pitch windings (T-TPMLG) are established based on the similar overall dimensions. Then, the electromagnetic characteristics of the 120°-TPMLG are analyzed, such as air gap flux density, back electromotive force and load voltage. Finally, a comparative analysis of the magnetic flux density, flux linkage, load and no-load performance of the two generators are conducted. Findings The result shows that the 120°-TPMLG has higher power density and generation efficiency than the T-TPMLG. Originality/value This paper proposes a TPMLG with 120° phase belt toroidal windings (120°-TPMLG) to improve the power density and generation efficiency.

Understanding the performance of fuel elements, particularly defective ones, in the reactor core quickly and accurately is essential as most radioactive nuclides are produced in the fuel elements and released into the primary circuit. Radioactivity in the primary circuit may result in potential radiation hazards to the maintenance workers and the environment near the nuclear power plant. Therefore, fuel element damage monitoring technology has received wide attention in the field of nuclear fission reactors. Few reviews focus on fuel element damage monitoring technology to facilitate the development of high-temperature gas-cooled reactors (HTGRs). In this study, we investigated the state of fuel element damage monitoring technology in HTGRs and pressurized water reactors (PWRs), summarized their characteristics and parameters, and compared their advantages and disadvantages. The radioactive source terms in HTGRs and PWRs were listed, and the typical nuclides in the primary circuit adopted for the fuel element damage monitoring were illustrated. This study can provide a good reference for developing fuel element damage monitoring technology in HTGRs in the future.

A novel efficiency optimization strategy combined with a position estimation method is proposed for switched reluctance generators (SRGs) in this article. This practical performance improvement strategy can expand the application of SRGs small-scale wind energy generation system, which is a good solution for mitigating the fossil energy crisis. First, the position estimation method based on current injection of the idle phase is presented. The angle error caused by sampling in this method aggravates with speed. Accordingly, an error compensation strategy in the linear range of inductance is suggested. Second, a method for improving the efficiency of SRG system current is proposed. It determines the range of turn- off angle with the minimum root-mean-square value of phase current, and further obtains the optimal turn- on angle by the fitting expression to improve the efficiency. This efficiency optimization strategy combined with the new position estimation method can greatly enhance the efficiency and reliability of SRG system and eliminate the position sensor. There are many simulation and experiment results that validate the effectiveness of the proposed schemes.

Plate frame structure with holes is a novel candidate to reduce the weight and strengthen the architectural structures to fulfill the requirements of practical engineering applications. The designed periodic hole structure can generate a band gap from the perspective of the frequency spectrum. In this study, a new band gap calculation method was proposed under the basic energy method framework for the analysis of hole periodic structures. Gaussian wavelet function with a good localization characteristic was adopted to overcome the inaccurately assumed displacement filed function due to the introduced hole issue. The entire plate structure was divided into cell elements and an artificial spring model was introduced to satisfy the cell coupling conditions. The coupling constraints were converted into elastic potential energy to be added to the energy functional for the entire system. The dispersion curves obtained by this method are in excellent agreement with the results of the finite element method. It was observed that periodic hole plates lead to the generation of complete and directional flexural wave band gaps. By introducing bi-directionally orthogonal stiffeners, the band gap of periodic hole plates could be significantly lengthened and complete band gaps could be successfully generated. Furthermore, geometrical parametric studies on flexural wave band gaps were analyzed. A wide and complete band gap could be realized by increasing the width of the stiffener to a certain extent, but not fully proportional.

Background With the rapid accumulation of scRNA-seq data, more and more automatic cell type identification methods have been developed, especially those based on deep learning. Although these methods have reached relatively high prediction accuracy, many issues still exist. One is the interpretability. The second is how to deal with the non-standard test samples that are not encountered in the training process. Results Here we introduce scCapsNet-mask, an updated version of scCapsNet. The scCapsNet-mask provides a reasonable solution to the issues of interpretability and non-standard test samples. Firstly, the scCapsNet-mask utilizes a mask to ease the task of model interpretation in the original scCapsNet. The results show that scCapsNet-mask could constrain the coupling coefficients, and make a one-to-one correspondence between the primary capsules and type capsules. Secondly, the scCapsNet-mask can process non-standard samples more reasonably. In one example, the scCapsNet-mask was trained on the committed cells, and then tested on less differentiated cells as the non-standard samples. It could not only estimate the lineage bias of less differentiated cells, but also distinguish the development stages more accurately than traditional machine learning models. Therefore, the pseudo-temporal order of cells for each lineage could be established. Following these pseudo-temporal order, lineage specific genes exhibit a gradual increase expression pattern and stem cell associated genes exhibit a gradual decrease expression pattern. In another example, the scCapsNet-mask was trained on scRNA-seq data, and then used to assign cell type in spatial transcriptomics that may contain non-standard sample of doublets. The results show that the scCapsNet-mask not only restored the spatial map but also identified several non-standard samples of doublet. Conclusions The scCapsNet-mask offers a suitable solution to the challenge of interpretability and non-standard test samples. By adding a mask, it has the advantages of automatic processing and easy interpretation compared with the original scCapsNet. In addition, the scCapsNet-mask could more accurately reflect the composition of non-standard test samples than traditional machine learning methods. Therefore, it can extend its applicability in functional analysis, such as fate bias prediction in less differentiated cells and cell type assignment in spatial transcriptomics.

Clustering is one of the most commonly used methods in single-cell RNA sequencing (scRNA-seq) data analysis and other fields of biology. Traditional clustering methods usually use data from a single source as the input (e.g. scRNA-seq data). However, as the data become more and more complex and contain information from multiple sources, a clustering method that could integrate multiple data is required. Here, we present inClust (integrated clustering), a clustering method that integrates information from multiple sources based on variational autoencoder and vector arithmetic in latent space. inClust perform information integration and clustering jointly, meanwhile it could utilize the labeling information from data as regulation information. It is a flexible framework that can accomplish different tasks under different modes, ranging from supervised to unsupervised. We demonstrate the capability of inClust in the tasks of conditional out-of-distribution generation under supervised mode; label transfer under semi-supervised mode and guided clustering mode; spatial domain identification under unsupervised mode. inClust performs well in all tasks, indicating that it is an excellent general framework for clustering and task-related clustering in the era of multi-omics.

The aim of this study was to well understand the dynamic changes of physicochemical properties of polysaccharides from loquat leaves (LLP) during in vitro simulated saliva-gastrointestinal digestion and fecal fermentation and its related impacts on human gut microbiota. Results showed that the contents of reducing sugar of LLP slightly increased during the gastrointestinal digestion, and its molecular weight also slightly decreased, suggesting that LLP could be slightly degraded under the gastrointestinal digestion conditions. Moreover, during the fecal fermentation, the molecular weight of the indigestible LLP (LLP-I) significantly decreased, and the molar ratio of constituent monosaccharides of LLP-I, such as glucuronic acid, galacturonic acid, galactose, and arabinose, significantly changed, indicating that LLP-I could be degraded and consumed by human gut microbiota. Indeed, some beneficial bacteria such as Megasphaera, Megamonas, Bifidobacterium, Phascolarctobacterium, and Desulfovibrio significantly increased, suggesting that LLP-I could change the composition and abundance of gut microbiota. LLP-I could also promote the production of health-promoting short chain fatty acids. Results from this study are benefical to well understand the in vitro digestion and fecal fermentation behaviors of LLP, and LLP can be developed as a potential prebiotic in the functional food industry.

BACKGROUND Carotid body tumor (CBT) is a chemoreceptor tumor located in the carotid body, accounting for approximately 0.22% of head and neck tumors. Surgery is the main treatment method for the disease. CASE SUMMARY We reviewed the diagnosis and treatment of one patient who had postoperative secondary aggravation of obstructive sleep apnea–hypopnea syndrome (OSAHS) and hypoxia after surgical resection of bilateral CBTs. This patient was admitted, and relevant laboratory and imaging examinations, and polysomnography (PSG) were performed. After the definitive diagnosis, continuous positive airway pressure (CPAP) treatment was given, which achieved good efficacy. CONCLUSION This case suggested that aggravation of OSAHS and hypoxemia is possibly caused by the postoperative complications after bilateral CBTs, and diagnosis by PSG and CPAP treatment are helpful for this patient.

Single-cell RNA sequencing (scRNA-seq) technologies are used to characterize the heterogeneity of cells in cell types, developmental stages and spatial positions. The rapid accumulation of scRNA-seq data has enabled single-cell-type labelling to transform single-cell transcriptome analysis. Here we propose an interpretable deep-learning architecture using capsule networks (called scCapsNet). A capsule structure (a neuron vector representing a set of properties of a specific object) captures hierarchical relations. By utilizing competitive single-cell-type recognition, the scCapsNet model is able to perform feature selection to identify groups of genes encoding different subcellular types. The RNA expression signatures, which enable subcellular-type recognition, are effectively integrated into the parameter matrices of scCapsNet. This characteristic enables the discovery of gene regulatory modules in which genes interact with each other and are closely related in function, but present distinct expression patterns. The wealth of data gathered from single-cell RNA sequencing can be processed with deep learning techniques, but often those methods are too opaque to reveal why a single cell is labelled to be a certain cell type. Lifei Wang and colleagues present an RNA-sequencing analysis method that uses capsule networks and is interpretable enough to allow for identification of cell-type-specific genes.

PurposeThe purpose of this paper is to propose a theoretical framework to illustrate the archival knowledge applied by archivists in their personal archiving (PA) and the mechanism of the application of archival knowledge in their PA.Design/methodology/approachThe grounded theory methodology was adopted. For data collection, in-depth interviews were conducted with 21 archivists in China. Data analysis was performed using the open coding, axial coding and selective coding to organise the archival knowledge composition of PA and develops the awareness-knowledge-action (AKA) integration model of archival knowledge application in the field of PA, according to the principles of the grounded theory.FindingsThe archival knowledge involved in the field of PA comprises four principal categories: documentation, arrangement, preservation and appraisal. Three interactive factors involved in archivists' archival knowledge application in the field of PA behaviour: awareness, knowledge and action, which form a pattern of awareness leading, knowledge guidance and action innovation, and archivists' PA practice is flexible and innovative. The paper underscored that it is need to improve archival literacy among general public.Originality/valueThe study constructs a theoretical framework to identify the specialised archival knowledge and skills of PA which is able to provide solutions for non-specialist PA and develops an AKA model to explain the interaction relationships between awareness, knowledge and action in the field of PA.

Several tubular switched reluctance linear machines (TSRLMs) with transverse flux are proposed for improving thrust density recently. Owing to the particularity of the structure of transverse-flux TSRLMs, how to maximize the electrical utilization becomes a key to improve these machines’ performance. A novel three-phase transverse-flux TSRLM is proposed in this paper, whose stator sleeve is composed of six ferromagnetic rings and five spacer rings. And the mover is composed of an aluminum tube and several fan-shaped poles. The adjacent fan-shaped poles are placed at 120 degree intervals. In the novel structure, each half of the windings corresponding to a phase constitute a single coil without the need of intermediate connections. This winding way avoids the limitation of stator ferromagnetic ring spacing, and increases the space for wire placement compared with the other existing transverse-flux TSRLMs. In order to verify the superiority of the novel TSRLM, a conventional transverse-flux TSRLM which has the same volume and main dimensions is presented to compare their performances. Finally, the finite element calculation results show that the average thrust per unit core mass of proposed TSRLM is greater than conventional TSRLM, which shows its superiority for speed control systems. It proves that the novel structure can help increasing the use of TSRLMs.

Traditional linear machines are under great influence of longitudinal end effect because of their finite stacking lengths in transverse and longitudinal directions. Longitudinal end effect causes imbalance of phase performance so that linear machine's force fluctuation is aggravated. The negative impact of longitudinal end effect on a flat type switched reluctance linear machine (SRLM) is verified in this paper. In order to avoid this problem, a novel tubular switched reluctance linear machine (TSRLM) is proposed, which can shield from unexpected impact of end effect. In structure, there is no transverse cut in tubular linear machines, so tubular linear machines can evade the influence of the transverse end effect. The equivalent magnetic circuit of this TSRLM is analyzed in this paper, which proves that the TSRLM is also not influenced by longitudinal end effect. A prototype is manufactured, and its corresponding hardware platform is established. A series of simulations and experiments verify that there is no deviation performance among phases in the proposed TSRLM. Accordingly, the traditional longitudinal end effect in linear machines caused by longitudinal cuts can be thoroughly evaded in proposed TSRLM.

A novel single phase tubular permanent magnet linear generator (TPMLG) for Stirling engines is proposed in this paper. It has an outer-stator, an inner-stator, a mover and a bread type winding which has no cutting. The mover consists of four ring-shaped permanent magnets, all of which are polarized radially. The polarization direction of the outer two permanent magnets is opposite to that of the inner two to form more magnetic circuits and achieve higher power generation density. The polarized directions of the two adjacent permanent magnets of both the outside and inside are opposite. The structure, dimensional parameters and operation characteristics of the generator are illustrated in detail. One of the structural advantages of this generator is that it is easy to control. The 3-D finite element (FE) model of proposed TPMLG is established. The model and its boundary conditions are presented and explained in detail. Through the FE model, its electromagnetic analysis is carried out. The performance of this generator under reciprocating frequency 75 Hz is investigated and analyzed. The simulation results show that the generator has the advantages of high power density.

The Ca0.85(LiCe)0.075Bi4Ti4−xZnxO15 ceramics are prepared via solid‐state reaction method with lower sintering temperature. The influence of lower sintering temperatures (Ts) on structural and electrical properties is investigated. The repressed volatilization of Bi3+ reduces the impurity phase proportion and oxygen vacancies content in ceramics, which might lead to increased TC value (~ 800 °C), piezoelectric constant d33 value (20 pC/N), high resistivity (6.32 × 105 Ω·cm at 600 °C), and good thermal stability up to 600 °C. Therefore, the Zn-modified ceramics are perceived to be one of promising candidates for high-temperature piezoelectric devices.

The longitudinal end effect (LEE) has a negative influence on the performance of the flat-type switched-reluctance linear machines (SRLMs). For example, it can give rise to the imbalance of peak currents of different phases and the aggravation of the force ripple. This study proposes a modified current estimation model and an adaptive adjustment method (AAM) of turn-on position to compensate for the LEE of SRLMs. The modified current estimation model considers not only the self-inductance characteristics but also the mutual inductance characteristics. Some simulation results demonstrate that this modified estimation model has better estimation accuracy than a previous one. Then, the AAM of turn-on position is proposed based on this modified current estimation model. It can balance the peak currents of different phases so that the negative impact of the LEE is greatly reduced. This new control method is easy to implement and requires little test, and its effectiveness in compensating for the peak currents and reducing force ripple is experimentally verified.

Phenolic compounds are considered the main bioactive components in kiwifruit. In order to well understand the accumulation pattern of health-beneficial phenolics, and to obtain high-quality kiwifruits with health-promoting characteristics, the changes of physicochemical properties, phenolic compounds, antioxidant capacities, and inhibitory effects on digestive enzymes of “Donghong” kiwifruits during maturation were systematically investigated. Noticeable variations in physicochemical properties and phenolic profiles were observed throughout the maturation stages of “Donghong” kiwifruit. According to the HPLC analysis, phenolic compounds, including chlorogenic acid, (−)-epicatechin, procyanidin B2, quercetin-3-O-rhamnoside, gallic acid, neochlorogenic acid, and caffeic acid, were found in “Donghong” kiwifruit, while chlorogenic acid was the most abundant phenolic compound. Considering the accumulation patterns of both total phenolics and soluble solids content, the optimum harvest time of kiwifruit with relatively high level of health-beneficial components was determined. Furthermore, “Donghong” kiwifruit exerted remarkable antioxidant capacities, and inhibitory effects on pancreatic lipase and α-glucosidase. Indeed, the Pearson’s correlation showed that chlorogenic acid, caffeic acid, (−)-epicatechin, and quercetin-3-O-rhamnoside could be major contributors to the antioxidant activity and inhibitory effects on digestive enzymes. Results are beneficial for better understanding of the accumulation patterns of health-beneficial phenolic compounds, which can aid in the targeting of specific developmental stages with an optimal phenolic profile for the production of health-beneficial products.

This study presents a non-linear modelling method for a switched reluctance linear machine (SRLM), which achieves high modelling precision while requiring no prior knowledge regarding the specific structural dimensions of an SRLM. The proposed modelling method provides accurate flux linkage data based on limited experimental measurements through an interpolation process using a variant sigmoid function. The accuracy of the interpolation process is further increased by considering mutual coupling among the three phases. The performance of the proposed method is validated experimentally by comparing it with the performances of the Fourier series method and the two-dimensional finite element method. The results demonstrate that the proposed method achieves greater modelling precision than the other methods considered in modelling an SRLM.

Axial flux permanent magnet (AFPM) motors are widely applied in many applications due to their performance advantages. A novel AFPM which owns a special winding form (120-degree phase belt toroidal windings) and a distinct rotor structure (sinusoidal rotor segments) is proposed in this paper to further improve the torque density of this kind of machine. First, the structure and working principle of the 120-degree phase belt toroidal windings sinusoidal rotor segments AFPM interior synchronous motor (120D-TWSRSAFPMISM) are clarified. Then, the design formula and crucial parameters of the motor are presented. Subsequently, the cogging torque is optimized by dividing the magnet grouping. Finally, the characteristics of the 120D-TWSRSAFPMISM are analyzed and compared with those of the traditional toroidal windings sinusoidal rotor segments AFPMISM (T-TWSRSAFPMISM) and another T-TW motor without the sinusoidal rotor segments (T-TWAFPMISM) by finite element method (FEM). The results show that the 120D-TW can significantly increase the back electromotive force (EMF) compared with the T-TW, and the sinusoidal rotor segments can increase the air-gap flux density compared with the traditional interior rotor. Therefore, the 120D-TW and sinusoidal rotor segments are combined in the AFPM motor. This combination can further increase the torque density compared with the contrast motors.

The ideal acoustic black hole (ABH) can achieve wave gathering and zero reflection of elastic waves. In practice, ABHs have to be truncated, limiting their application in lower frequency range. Aiming at improving the ABH beam's vibration suppression ability at low frequencies, this study proposes a shunt damping-ABH composite beam by pasting shunt damping instead of ordinary damping on the ABH tip. The energy method is employed to solve the vibration equation of the ABH beam. The admissible function is the Mexican hat wavelet. The proposed method is verified by the finite element method. Compared with the uniform beam, the numerical results show the ABH beam has a noticeable attenuating effect in high-frequency range due to the ABH effect, but almost has no attenuating effect in the low-frequency range. Therefore, we introduce shunt damping to enhance the low-frequency vibration control. The shunt damping is composed of circuits connected to a piezoelectric patch. The effects of different circuits connected to the piezoelectric patch are discussed. The R–L shunt circuit and L–C parallel blocking circuit can simultaneously suppress the multimode vibration peak of the ABH beam at the low frequency successfully. Finally, a vibration experiment of ABH beam combined with shunt damping is implemented to verify the present method's feasibility and the shunt damping effect. The proposed shunt damping-ABH composite beam could improve the suppressing ability in both the low and high-frequency ranges.

Pimprinine and streptochlorin are indole alkaloids derived from marine or soil microorganisms. In our previous study, they were promising lead compounds due to their potent bioactivity in preventing many phytopathogens, but further structural modifications are required to improve their antifungal activity. In this study, pimprinine and streptochlorin were used as parent structures with the combination strategy of their structural features. Three series of target compounds were designed and synthesized. Subsequent evaluation for antifungal activity against six common phytopathogenic fungi showed that some of thee compounds possessed excellent effects, and this is highlighted by compounds 4a and 5a, displaying 99.9% growth inhibition against Gibberella zeae and Alternaria Leaf Spot under 50 μg/mL, respectively. EC50 values indicated that compounds 4a, 5a, 8c, and 8d were even more active than Azoxystrobin and Boscalid. SAR analysis revealed the relationship between 5-(3′-indolyl)oxazole scaffold and antifungal activity, which provides useful insight into the development of new target molecules. Molecular docking models indicate that compound 4a binds with leucyl-tRNA synthetase in a similar mode as AN2690, offering a perspective on the mode of action for the study of its antifungal activity. These results suggest that compounds 4a and 5a could be regarded as novel and promising antifungal agents against phytopathogens due to their valuable potency.

The major active components and corresponding targets ofA search of the TCMSP database and related literature revealed 12 active compounds ofThe main active components of

Conventional offshore wind power and wave power generation are independent, and their power and efficiency for electricity generation may be restricted by low input energy. To overcome the shortcomings above, a double-stator linear-rotary flux-switching permanent magnet (FSPM) generator (DSLR-FSPMG), which incorporates the merits of both high power of permanent magnet machines and simple structure of reluctance switching machines, is proposed for offshore wind-wave energy conversion. In order to achieve the optimum performance of the proposed generator, the Taguchi method of multi-objective optimization design is carried out. Firstly, the topology and operating principles of the proposed generator are analyzed, and initial design is given. Secondly, the Taguchi method is employed and the optimal design combination is determined. Finally, the optimal generator is simulated where the results are compared with the initial generator. The results indicate that both the back electromotive forces (back EMFs) and corresponding total harmonic distortion (THD) are improved.

The latest progresses of experimental biology have generated a large number of data with different formats and lengths. Deep learning is an ideal tool to deal with complex datasets, but its inherent “black box” nature needs more interpretability. At the same time, traditional interpretable machine learning methods, such as linear regression or random forest, could only deal with numerical features instead of modular features often encountered in the biological field. Here, we present MultiCapsNet (https://github.com/wanglf19/MultiCapsNet), a new deep learning model built on CapsNet and scCapsNet, which possesses the merits such as easy data integration and high model interpretability. To demonstrate the ability of this model as an interpretable classifier to deal with modular inputs, we test MultiCapsNet on three datasets with different data type and application scenarios. Firstly, on the labeled variant call dataset, MultiCapsNet shows a similar classification performance with neural network model, and provides importance scores for data sources directly without an extra importance determination step required by the neural network model. The importance scores generated by these two models are highly correlated. Secondly, on single cell RNA sequence (scRNA-seq) dataset, MultiCapsNet integrates information about protein-protein interaction (PPI), and protein-DNA interaction (PDI). The classification accuracy of MultiCapsNet is comparable to the neural network and random forest model. Meanwhile, MultiCapsNet reveals how each transcription factor (TF) or PPI cluster node contributes to classification of cell type. Thirdly, we made a comparison between MultiCapsNet and SCENIC. The results show several cell type relevant TFs identified by both methods, further proving the validity and interpretability of the MultiCapsNet.

Ferroelectric materials have been widely studied for applications in numerous devices due to their controllable ferroelectric/ferroelastic properties under electric field or mechanical stress. Recently, a type of bismuth layer-structured ferroelectrics, W/Cr co-doped BIT ceramics, has attracted much attention due to its high Curie temperature, large spontaneous polarization, and particularly enhanced ferroelectric properties. Nevertheless, as a significant consideration for the reliability and durability of devices, the mechanical properties associated with ferroelastic behaviors of this type of ceramics are generally ignored. In this study, a type of W/Cr co-doped BIT ceramics with optimal chemical composition of Bi4Ti2·95W0·05O12.05+0.2 wt% Cr2O3 (BTWC) was synthesized via the solid-reaction technology. Ferroelastic domain structures and ferroelastic switching behaviors together with mechanical failure properties of the sintered ceramics were investigated in details. PFM observations reveal the existence of pseudo-90° and -180° ferroelastic domain structures in BTWC ceramics. The nonlinear deformation of stress-strain curve originates from ferroelastic domain switching induced by mechanical stress of sufficient magnitude. Moreover, the ferroelastic switching plays a significant role in improving the fracture toughness of BTWC ceramics. Additionally, the ceramics sintered at higher temperature are expected to exhibit a better ferroelastic switching behavior yet lower failure stress. The work can provide design consideration of loading conditions for practical applications of BTWC ceramics.

The longitudinal end effect of switched reluctance linear machine (SRLM) makes the electromagnetic characteristics of different phases unbalanced, especially in magnetic flux distributions. These discrepancies unbalance phase currents and aggravate the force ripple of SRLM, which are verified on a double-sided SRLM. This study aims to analyse the influence of the longitudinal end effect on SRLMs and to investigate simple but practical compensation methods for the performance improvement of linear machines. Through magnetic circuit analysis, a new compensation method which is widening stator end poles is proposed for the first time. Three-dimensional finite element analysis (3D FEA) shows that this new method can decrease the force factor by about 93.9%, while the previously used method which is adding auxiliary stator poles can decrease the force ripple factor by only about 27.5%. In addition, the proposed method needs less extra space than the previous method. Hence, the new compensation method is more practical and more efficient. Furthermore, the theoretical value of optimal width of stator end poles is expressed, and its effectiveness is confirmed by sensitivity analysis.