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The distributed consensus mechanism is the backbone of the rapidly developing blockchain network. Blockchain platforms consume vast amounts of electricity based on the current consensus mechanism of Proof-of-Work (PoW). Here, we point out a different consensus mechanism named Proof-of-Stake (PoS) that can eliminate the extensive energy consumption of the current PoW-based blockchain. We comprehensively elucidate the current and projected energy consumption and carbon footprint of the PoW- and PoS-based Bitcoin and Ethereum blockchain platforms. The model of energy consumption of PoS-based Ethereum blockchain can lead the way toward the prediction of other PoS-based blockchain technologies in the future. With the widespread adoption of blockchain technology, if the current PoW mechanism continues to be employed, the carbon footprint of Bitcoin and Ethereum will push the global temperature above 1.5 °C in this century. However, a PoS-based blockchain can reduce the carbon footprint by 99% compared to the PoW mechanism. The small amount of carbon footprint from PoS-based blockchain could make blockchain an attractive technology in a carbon-constrained future. The study sheds light on the urgency of developing the PoS mechanism to solve the current sustainability problem of blockchain.

Based on the characteristic of doubly salient electromagnetic machines (DSEMs) that the incremental inductance varies with the rotor position, a sensorless startup strategy is proposed in this article. First, the pulse injection based method is adopted to estimate the initial rotor sector. The influence of the field current on the position estimation error is analyzed. Second, the startup method with no test pulse is introduced to start DSEM. Two key strategies are proposed: the commutation strategy based on the series incremental inductance detection and the anti-out-of-step control strategy based on the circulating current detection. The series incremental inductance is estimated in a chopping period and is compared with a preset threshold to obtain the commutation signal. The circulating current of the nonconducting phase is detected to monitor whether the DSEM is out of step. Furthermore, the current chopping mode is optimized, which has influence on the circulating current of the nonconducting phase. The proposed strategy can avoid the discontinuity of phase current caused by the test pulse in the existing technique. Finally, the effectiveness and the feasibility of the proposed method are verified by a series of experiments on the 9-kW 12/8 pole DSEM prototype.

Sulfur vacancy (SV) engineering is an evolving approach to improve the performance of metal sulfides for hydrogen evolution reactions (HER); however, a simple and universal method for creating SV i...

BackgroundIntestinal ischemia/reperfusion (I/R) injury is a common tissue-organ damage occurring in surgical practice. This study aims to comprehensively review the collaboration and impact of countries, institutions, authors, subject areas, journals, keywords, and critical literature on intestinal I/R injury from a bibliometric perspective, and to assess the evolution of clustering of knowledge structures and identify hot trends and emerging topics.MethodsArticles and reviews related to intestinal I/R were retrieved through subject search from Web of Science Core Collection. Bibliometric analyses were conducted on Excel 365, CiteSpace, VOSviewer, and Bibliometrix (R-Tool of R-Studio).ResultsA total of 1069 articles and reviews were included from 2004 to 2022. The number of articles on intestinal I/R injury gradually plateaued, but the number of citations increased. These publications were mainly from 985 institutions in 46 countries, led by China and the United States. Liu Kx published the most papers, while Chiu Cj had the largest number of co-citations. Analysis of the journals with the most outputs showed that most journals focused on surgical sciences, cell biology, and immunology. Macroscopic sketch and microscopic characterization of the entire knowledge domain were achieved through co-citation analysis. The roles of cell death, exosomes, intestinal flora, and anesthetics in intestinal I/R injury are the current and developing research focuses. The keywords “dexmedetomidine”, “proliferation”, and “ferroptosis” may also become new trends and focus of future research.ConclusionThis study comprehensively reviews the research on intestinal I/R injury using bibliometric and visualization methods, and will help scholars better understand the dynamic evolution of intestinal I/R injury and provide directions for future research.

We propose an integrated path planning method for multiple automated guided vehicles performing logistics delivery within a real-world warehouse environment considering obstacles. By applying it on each vehicle, this proposed method enables the vehicle the vehicles have the capabilities for autonomous path planning. The path planning consists of three parts, K-means algorithm based task points clustering, genetic algorithm based task points ordering, and the probabilistic road map based best path search. Vehicle conflict resolution is depending on implementing the probabilistic road map construction considering the realistic map with obstacles. The simulations result validate that the clustering and ordering are necessary for the path planning, both the path planning time and the Automated guided vehicles (AGVs) running time can be dramatically reduced.

Background: As a kind of sliding bearing with liquid as a lubricant, Hydrostatic journal bearing can be shown from tribology, mechanics, optimization method and structural design in engineering practice. Hydrostatic bearing characterized by high precision, high rigidity, and long life has drawn people's attention and been widely adopted. As progress has been made in science and technology, people will have a better understanding of the principles and characteristics of the hydrostatic journal bearing. Objective: The development of hydrostatic bearing in recent years is studied and analyzed. Methods: More than 70 recently published patents and journal and conference papers related to the developments in air traffic flow management are reviewed, and the outcomes in temperature field, pressure field, deformation, lubrication, bearing capacity and friction are studied. Results: Through these research results, the current research status of hydrostatic bearings is summarized, and the three aspects of flow field characteristics, lubrication characteristics and tribology are explained, and solutions and feasibility measures for existing outstanding problems in each aspect are mentioned. Conclusion: Based on this article, the design and optimization of hydrostatic bearings are of guiding significance. Finally, the current problems and challenges of hydrostatic bearings are analyzed, and future research directions and research priorities are prospected.

A hybrid flame retardant, of excellent stability in aqueous media, was designed to develop flame-retarded polyethyleneimine (PEI) foam. In this case, iron phosphonate (FeP) with carboxyl group and hydroxyl group was first designed and synthesized. The carboxyl group could be hydrogen bonded with the water-soluble ammonium polyphosphate (APP) in aqueous media, and then dispersed as nano-sized particles. Subsequently, the well-dispersed nano-hybrid of FeP and APP (FeP/APP) was blended with hydrophilic PEI to prepare a kind of composite foam through a freeze-drying process. For FeP/APP, the transition metal iron showed excellent catalytic carbonization performances. Meanwhile, APP could also catalyze the degradation of polymers to form a protective char layer. The thermogravimetric analysis coupled with Fourier transform infrared analysis (TG-FTIR) test disclosed that the improvement of flame retardancy for PEI-based foams was ascribed to the synergistic effect of FeP and APP in the condensed phase. The composite foam containing 30 wt% FeP/APP could self-extinguish and reach V-1 rating in UL-94 test. When the loading level of 45% FeP/APP reached 45%, the composite foam could elevate up to V-0 rating, and the peak of heat release rate and total heat release were reduced by 71.8% and 74.2%, respectively, compared to a neat PEI foam. It is worth noting that our work presents a promising way for preparation of stable aqueous flame retardant, and is expected to enhance the fire safety of aqueous foams, coatings, cotton textiles, and other flammable materials.

Semi-solid forging of iron-based alloys during solidification has unique characteristics distinct from those of the classical hot forging. With the aim of acquiring precise knowledge concerning the microstructural evolution of bearing steel Cr4Mo4V in this process, a series of semi-solid forging experiments were carried out in which samples were wrapped in a designed pure iron sheath. The effects of forging temperature and forging reduction on the grain morphology and liquid flow behavior were investigated, respectively. By forging solidifying metal (FSM), bulky primary dendrites were broken and spheroidal grains with an average shape factor of 0.87 were obtained at 1360 °C. With the decreasing forging temperature to 1340 °C, the microstructural homogeneity can be improved. On the other hand, it shows that a higher forging reduction (50%) is essential for the spheroidization of grains and elimination of liquid segregation. Those microstructural characteristics are related to different motion mechanisms of solid and liquid phases at different forging temperatures. Additionally, the effect of semi-solid forging on the eutectic carbides was also investigated, and the results demonstrate that the higher diffusion capacity and less liquid segregation jointly lower the large eutectic carbides and consequently cause its uniform distribution during FSM.

Additional file 1: Table S1. Description of Cis-elements.

Additional file 4: Figure S3. Characterization of tissue injury and the gut microbiota in the Sen and Res mice. a The mRNA levels of proinflammatory factors in the ileum, liver, lung and kidney. b, c The total bacterial load and the level of Firmicutes and Bacteroidetes as well as the Firmicutes/Bacteroidetes ratio in the feces. d Relative bacteria abundance at the class level in the feces. e Heatmap of the expression values of 20 signaling pathways in each sample. f. Relative mRNA levels of ZO-1 and occludin in the ileum g Relative levels of ALT and AST in the plasma of GF mice. The results are expressed as the mean �� SEM. n = 6-8. ***p

Additional file 5: Figure S4. Lactobacillus murinus improves intestinal I/R-induced intestinal injury in antibiotic-treated mice. a. Experimental design. The WT mice were randomly divided into the following groups. Group ABX + I/R, in which ABX was administered 1w before intestinal ischemia; Group ABX + I/R + L. murinus, treatment of mice with ABX for a week, and then mice were gavaged daily for 7 days with L. murinus. b Relative abundance of L. murinus in the cecum after ABX clearance experiment. c-e HE staining and ZO-1 and occludin immunofluorescent staining in the ileum. Representative quantification on the right. Scale bar=100 ��m. f Tight junction mRNA levels in the ileum. g FD-4 level in the plasma. The results are expressed as the mean �� SEM. n = 8. ***p

Additional file 7: Figure S5. The level of IFABP and citrulline in serum before surgery between low L. murinus abundance group and high L. murinus abundance group.

Additional file 2: Figure S2. Experimental design. a L. murinus pretreatment experiment design. b Macrophage depletion experiment design.

Pre-Training (PT) of text representations has been successfully applied to low-resource Neural Machine Translation (NMT). However, it usually fails to achieve notable gains (sometimes, even worse) on resource-rich NMT on par with its Random-Initialization (RI) counterpart. We take the first step to investigate the complementarity between PT and RI in resource-rich scenarios via two probing analyses, and find that: 1) PT improves NOT the accuracy, but the generalization by achieving flatter loss landscapes than that of RI; 2) PT improves NOT the confidence of lexical choice, but the negative diversity by assigning smoother lexical probability distributions than that of RI. Based on these insights, we propose to combine their complementarities with a model fusion algorithm that utilizes optimal transport to align neurons between PT and RI. Experiments on two resource-rich translation benchmarks, WMT'17 English-Chinese (20M) and WMT'19 English-German (36M), show that PT and RI could be nicely complementary to each other, achieving substantial improvements considering both translation accuracy, generalization, and negative diversity. Probing tools and code are released at: https://github.com/zanchangtong/PTvsRI., Comment: COLING 2022

Additional file 6: Table S2. Characteristics of patients with cardiopulmonary bypass.

Additional file 8. Figure abstract.

Additional file 3: Table S1. Primers sequence.

Few-shot learning (FSL), purposing to resolve the problem of data-scarce, has attracted considerable attention in recent years. A popular FSL framework contains two phases: (i) the pre-train phase employs the base data to train a CNN-based feature extractor. (ii) the meta-test phase applies the frozen feature extractor to novel data (novel data has different categories from base data) and designs a classifier for recognition. To correct few-shot data distribution, researchers propose Semi-Supervised Few-Shot Learning (SSFSL) by introducing unlabeled data. Although SSFSL has been proved to achieve outstanding performances in the FSL community, there still exists a fundamental problem: the pre-trained feature extractor can not adapt to the novel data flawlessly due to the cross-category setting. Usually, large amounts of noises are introduced to the novel feature. We dub it as Feature-Extractor-Maladaptive (FEM) problem. To tackle FEM, we make two efforts in this paper. First, we propose a novel label prediction method, Isolated Graph Learning (IGL). IGL introduces the Laplacian operator to encode the raw data to graph space, which helps reduce the dependence on features when classifying, and then project graph representation to label space for prediction. The key point is that: IGL can weaken the negative influence of noise from the feature representation perspective, and is also flexible to independently complete training and testing procedures, which is suitable for SSFSL. Second, we propose Graph Co-Training (GCT) to tackle this challenge from a multi-modal fusion perspective by extending the proposed IGL to the co-training framework. GCT is a semi-supervised method that exploits the unlabeled samples with two modal features to crossly strengthen the IGL classifier.

Additional file 1: Figure. S1. Phylogenetic analysis of LGK ,AnmK and LGK-like proteins. Figure S2. Intracellular levoglucosan accumulation of CEN.PK113-5D and hxt-null strain EBY.VW4000. CEN.PK113-5D and EBY.VW4000 were cultured in YPD and YPM medium, respectively, for 12 h at 30 °C, then transferred into 20 mL fresh medium for another 12 h cultivation. The cells were then collected by centrifugation, washed twice with ddH2O, and resuspended in 30 mL YP medium supplemented with 5 gL−1 levoglucosan. After 30 min, 60 min, and 120 min incubation in 30 °C, respectively, cells were harvested and quickly washed with ice-cold ddH2O twice, then resuspended with ddH2O and placed at 37 °C overnight to extract the intracellular levoglucosan. The accumulation amounts were represented as mg levoglucosan per g dry cell weight (DCW). *, p

Currently, deep learning (DL) algorithms have achieved great success in many applications including computer vision and natural language processing. Many different kinds of DL models have been reported, such as DeepWalk, LINE, diffusionconvolutional neural networks, graph convolutional networks (GCN), and so on. The GCN algorithm is a variant of convolutional neural network and achieves significant superiority by using a one-order localised spectral graph filter. However, only a one-order polynomial in the Laplacian of GCN has been approximated and implemented, which ignores undirect neighbour structure information. The lack of rich structure information reduces the performance of the neural networks in the graph structure data. In this study, the authors deduce and simplify the formula of two-order spectral graph convolutions to preserve rich local information. Furthermore, they build a layerwise GCN based on this two-order approximation, i.e. two-order GCN (TGCN) for semi-supervised classification. With the two-order polynomial in the Laplacian, the proposed TGCN model can assimilate abundant localised structure information of graph data and then boosts the classification significantly. To evaluate the proposed solution, extensive experiments are conducted on several popular datasets including the Citeseer, Cora, and PubMed dataset. Experimental results demonstrate that the proposed TGCN outperforms the state-of-art methods.

Biosynthesis of TCA cycle-derived C4 chemicals through glyoxylate shunt is an attractive metabolic route because it can be drived by TCA-glyoxylate cycle force under aerobic conditions. However, yield of this route is low with at least 1/3 carbon loss from glucose. FAs could sufficiently provide acetyl-CoA by β-oxidation without carbon loss and directly enter the TCA-glyoxylate cycle, which is acknowledged as a promising alternative feedstock. Here β-alanine was selected as the target TCA cycle-derived chemical, of which the theoretical yield is 1.391 g/g FAs, much higher than that of glucose(0.49 g/g). By adopting multi-metabolic engineering strategies and relieving the active oxygen damage caused by FAs utilization, β-alanine production reached 78.05 g/L with a yield of 1.2 g/g, about 86% of theoretical yield. Our study establish a promising bioproduction route of β-alanine from waste FAs (such as gutter oil, palm fatty acid distillate etc.), and more importantly, provide an efficient platform for TCA cycle-derived C4 chemicals biosynthesis.

A sensorless control method based on the terminal voltage for doubly salient electro-magnetic motor (DSEM) is researched here. The negative-going zero-crossing point (NGZCP) of the fundamental component of terminal voltage is detected to obtain the rotor position. Firstly, a fourth Butterworth filter is introduced to extract the fundamental component of the terminal voltage. The ratio of signal frequency to cut-off frequency f/f c is optimised to acquire good filtering effect and good dynamic performance. Moreover, on this basis, the speed range is divided into several intervals to match the filters with different cut-off frequencies. Secondly, the coordinate transformation is adopted to compensate for the phase difference between the NGZCPs of the extracted voltages with the ideal commutation points. The transformation angle is obtained by offline simulation and test. An 18 kW DSEM prototype is tested to verify the feasibility of the proposed method.

To clarify the gel formation mechanism of isolated proteins recovered from blue round scads by isoelectric solubilization/precipitation, the physiochemical, conformational and gelation properties of the major protein myosin treated by acidic-(AM) or alkaline-(KM) pH-shifting were investigated and compared with native myosin (NM). The solubility in all myosin samples dropped significantly at 40 °C, with remarkable increases of particle size, turbidity and surface hydrophobicity. Among the samples, AM exhibited the lowest solubility and highest turbidity than NM and KM as the temperature was higher than 40 °C, indicating that AM is easily to be denatured and aggregated. Circular dichroism (CD) analysis showed that both acidic and alkaline pH treatments led to conformational changes of myosin, together with α-helix content variations. When pH was readjusted to neutral, KM recovered its structure similar to NM, while AM failed to refold to its native state. NM exhibited the highest storage modulus (G′) at 90 °C, while AM revealed the lowest G′ value. Furthermore, AM did not change obviously during heating, especially at the gelling temperature range (60–90 °C). These results strongly suggested that acidic treatment led to an irreversible conformational change in myosin, consequently induced a fierce denaturation and aggregation at the initial stage of heating, and eventually led to a complete loss of gel-forming ability. Alkaline pH-shifting, on the other hand is thus more feasible for protein recovery from blue round scads.

This article presents a sensorless control strategy based on the line-to-line excitation flux linkage for doubly salient electro-magnetic machine. The negative-going zero-crossing points of the line-to-line excitation flux linkage are detected to estimate the position and speed. To solve the problems of direct current (DC) bias and error accumulation in pure integrator, a combination of first-order low-pass filter and first-order high-pass filter is adopted to estimate the line-to-line flux linkage. Considering that the self-inductance obviously varies with the position and the phase current, an equivalent inductance is introduced to calculate the line-to-line excitation flux linkage in the whole period. The commutation error caused by the filter and the armature reaction is analysed and proved to be within ±6°. The proposed method can be applied to either the three-state standard angle control or the six-state advanced angle control. The experiment platform based on a 9-kW/3000-rpm DSEM is built, and the validity and feasibility of the proposed strategy are proved.

The titanium-based electrodes with MnOx nanoparticles coating (MnOx/Ti) and MnOx nanoparticles mixed with multi-walled carbon nanotubes (MnOx–CNTs/Ti) were fabricated by spraying–calcination method. The physicochemical properties of electrodes were investigated by SEM, XRD and XPS, which indicated that the surface coating of MnOx–CNTs/Ti, with MnOx nanoparticles dispersed uniformly on the CNTs, was smoother and with higher integrity than MnOx/Ti. Acid Red B was used as model pollutant to investigate the electro-catalytic activity of the electrodes, and the results revealed that the removal efficiency of Acid Red B reached 93.6% and 98.0% by MnOx/Ti and MnOx–CNTs/Ti, respectively, and the cell potential during the process of degradation by MnOx–CNTs/Ti was relatively low and stable. The electrochemical results confirmed that MnOx–CNTs/Ti possessed smaller charge transfer resistance and higher oxygen evolution current compared with MnOx/Ti, which can enhance the electro-catalytic activity and reduce the energy consumption by accelerating the transfer of electrons on the electrode surface. The accelerated lifetime tests of electrodes were carried out and showed that actual service lifetimes of MnOx–CNTs/Ti were 38 times of that for MnOx/Ti calculated by the experienced formula, which demonstrated that the durability of MnOx-based electrode was significantly promoted by addition of CNTs on Ti substrate.

The authors present a platform for measuring the electrostatic attractive force that is key in the manufacturing process, i.e., for designing and modeling. —Jorg Henkel, Karlsruhe Institute of Technology

In order to solve the problem that the accuracy of transformer condition assessment based on oil chromatographic data is not high, this paper adopts random forest to evaluate transformer state. In order to prevent the attribute values carried by the decision tree of the basic unit in the evaluation model from being too few and thus affecting the evaluation accuracy. The ratio of H2, CH4, C2H6, C2H4, C2H2, total hydrocarbon and various characteristic gases is used as the characteristic quantity, a stochastic forest optimization model for oil chromatography state assessment was constructedimmediately following the heading. It is compared with BP neural network and SVM, the test results of field oil chromatogram data show that the accuracy of random forest state assessment is 88.5%, which is better than BP and SVM, and the random forest assessment model has faster assessment speed, This paper provides technical support for the fast and accurate condition assessment of transformer.

Additional file 2: Table S1. The primers used in this study.

Additional file 1: Figure S1. The relative GFP intensity of the Pfrd3 promoter at different OD conditions. Figure S2. OD optimization and rotation speed optimization. (A) Production comparison between different OD conditions. (B) Production comparison between different rotation speeds. Figure S3. Remaining soybean oil of Fed-batch fermentation in 1-L bioreactors for RK production.

Additional file 2: Table S1. The primers used in this study.

Additional file 1: Figure S1. Identification of germacrene A by GC-MS analysis. (A, B) GC analyses of the ß-elemene standard (A) and the culture extract of the yeast strain SGAS5. (C) GC-MS spectra of the chromatographic peak corresponding to ß-elemene in (B). Figure S2. List of pairwise protein sequence identity (%) comparison between ten GAS candidates applied for screening in this study. Figure S3. Extracellular farnesol production of yeast strains SGAS5, SMVA1, SMVA2, and SMVA3. Figure S4. Sequence alignment of AvGAS with NsGAS, NcGAS, and bLinS from Streptomyces clavuligerus (5NX6). Two conserved regions within the active site, the aspartate-rich (DDXX(X)(D,E)) motif and the NSE (NDXXSXX(R,K)(E,D)) triad, required for binding catalytically essential Mg2+ ions, were indicated with boxes. Figure S5. Extracellular germacrene A production of yeast cells expressing the indicated GASs, respectively. GASs were expressed in S. cerevisiae CEN.PK2-1D wherein tHMGR1 was overexpressed and ERG9 was downregulated via promoter replacement, as described in the main text. Figure S6. Extracellular farnesol production of yeast strain SHEF and SHEF strains expressing LsGAS, AvGAS, and AvGAS-F23W, respectively. Figure S7. Extracellular and intracellular germacrene A accumulation in the yeast strain SHEF after cultivation for 72 h. Figure S8. Location of Phe23 in the modelled structure of AvGAS. The substrate FPP is represented as cyan sticks and Phe23 is shown as purple sticks. Table S1. Growth analyses of yeast cells expressing Phe23 mutants of AvGAS after cultivation for 72 h.

Additional file 1: Table S1. Primers used in this study. Table S2. Amino acid sequence identities (%) between α-1, 2-FTs tested in the present study and selected characterized α-1, 2-FTs in literatures. Figure S1. Lactose importing analysis by strain FL01 and FL02. Figure S2. Phylogenetic analysis and alignment of α-1, 2-FTs of different organisms including α-1, 2-FTs tested in the present study and selected α-1, 2-FTs reported in the literatures. Figure S3. Western blot assay of His-tagged FutBc and FutC expressed in yeast cells. Figure S4. 2′-FL production by FL06 with different initial lactose concentration. Figure S5. Cell wall stability test of strains producing 2′-FL. Figure S6. Effect of overexpression Pmi40 and sPos5 on 2′-FL production.

This paper focus on the state estimation, number of targets estimation and target type estimation of mixed targets and propose a mixed target tracking algorithm with type probability using the GLMB filter. The mixed targets include point target, extended target and group target (indistinguishable). The tracking algorithm mainly includes three aspects: mixed target dynamic modeling, type analysis and tracking estimation. Firstly, measurement model of mixed target is established with the generalized label multi-Bernoulli filter. Secondly, the probability of targets type are calculated. Finally, the parameters of finite mixture models (FMM) are derived by using Gibbs sampling and BIC criterion to track the mixed target. Then the equivalent measurement method is used to replace the measurement of extended target and group target. The shape of the mixed target is estimated by the ellipse approximation modeling method. Simulation experiments are provided to show the effectively of track mixed targets.

Numerous studies have reported that hydroxyapatite nanoparticles (nano-HAPs) can inhibit the proliferation of a variety of tumor cells and this effect is different in different carcinoma cells. However, the effect of nano-HAPs on osteosarcoma cell proliferation has not been well understood thus far. In this study, we first showed that our synthesized nano-HAPs reduced cell viability and inhibited migration and invasion of OS-732 cells in a concentration-dependent manner. Using a BALB/c nude mouse tumor model, we demonstrated that nano-HAPs could effectively suppress tumor growth in vivo. We also performed RNA-seq analysis to investigate the underlying mechanism of these effects and discovered that treatment of OS-732 cells with nano-HAPs significantly downregulated the FAK/PI3K/Akt signaling pathway. Collectively, our study suggests that treatment with nano-HAPs can inhibit osteosarcoma cell growth, migration and invasion in vitro and suppress osteosarcoma in vivo.

In this paper, the author introduces the interference sources in the field PD test of transformer pulse current method in detail, and comments on the principle, advantages and disadvantages of the existing anti-interference technology of each interference source. Finally, the author puts forward the ultra wide band PD intelligent detection technology of transformer, which provides a more advanced means for the detection and evaluation of the insulation state of the electric transformer and the rheological oil paper.

Regarding the earthing system and foundation heating problem of 66kV dry-type hollow reactor in a 750kV substation ,In order to accurately analyze the reason and take corresponding measures,firstly infrared temperature measurement was used to identify and determine the source of heat, then we replaced the grounding system metal,Analyzed structure of the reactor infrastructure,tested the conducting performance of steel reinforcement inside the foundation,simulated the earthing system of the reactor,analyzed the effects of circulation heating and eddy current heating comprehensively,the causes of heat were identified and corresponding measures were put forward.Finally, it was concluded that the eddy current of the conductive material in the magnetic field was the cause of the heating of the flat iron grounded in the reactor,the heating of the reactor foundation was caused by the metal ring in the raft.

Because of the mismatch between poles of permanent magnet synchronous motor (PMSM) and rotating transformer, the PMSM is difficult to start smoothly. Under this condition, the motor’s zero position is not unique and the detection is not accurate. A method of measuring rotor position is proposed to solve this problem. Taking the three-phase six-state control as example, a series of sets of angle data are premeasured in sequence at different position and different rotating speed. Before the motor start, the rotor is fixed to a given position, which is included in the pre-measured data. Then the accurate angle of the rotor is defined. By the proposed method, the motor can start smoothly, as well as the accuracy and the fluctuation of angle data obtained will be improved. Therefore the stability of the system can be enhanced which will meet the high requirement of PMSM system because of the simplified control system. The correctness of the analysis is verified by the experiment.

We present a new concept of synthesis for preparation of molecularly imprinted polymers using a functionalized initiator to replace the traditional functional monomer. Using propranolol as a model template, a carboxyl functionalized radical initiator was demonstrated to lead to high-selectivity polymer particles prepared in a standard precipitation polymerization system. When a single enantiomer of propranolol was used as template, the imprinted polymer particles exhibited clear chiral selectivity in an equilibrium binding experiment. Unlike the previous molecular imprinting systems where the active free radicals can be distant from the template-functional monomer complex, the method reported in this work makes sure that the actual radical polymerization takes place in the vicinity of the template-associated functional groups. The success of using functional initiator to synthesize molecularly imprinted polymers brings in new possibilities to improve the functional performance of molecularly imprinted synthetic receptors.

In recent years, the attention mechanism contributes significantly to hypergraph based neural networks. However, these methods update the attention weights with the network propagating. That is to say, this type of attention mechanism is only suitable for deep learning-based methods while not applicable to the traditional machine learning approaches. In this paper, we propose a hypergraph based sparse attention mechanism to tackle this issue and embed it into dictionary learning. More specifically, we first construct a sparse attention hypergraph, asset attention weights to samples by employing the $\ell_1$-norm sparse regularization to mine the high-order relationship among sample features. Then, we introduce the hypergraph Laplacian operator to preserve the local structure for subspace transformation in dictionary learning. Besides, we incorporate the discriminative information into the hypergraph as the guidance to aggregate samples. Unlike previous works, our method updates attention weights independently, does not rely on the deep network. We demonstrate the efficacy of our approach on four benchmark datasets.

The traditional (bio)electrochemical sensors for hydrogen peroxide (H2O2) detection require expensive external power sources which restricts their practicability. In this research, a novel self-powered bioelectrochemical sensor using bioanode as the electrical supplier and CoMn2O4 nanoparticle modified graphite cathode (CoMn2O4@GE) as the sensing element was developed for H2O2 determination. Electrochemical tests revealed that the CoMn2O4@GE exhibited attractive electrocatalytic activity towards H2O2 reduction, due to the large catalyst surface area and abundant Mn3+/Mn2+ and Co3+/Co2+ electroactive sites. Under the optimized conditions (flow rate 5 mL min−1, pH 7.0) and external load of 300 Ω, the proposed sensor demonstrated a wide linear detection range between 1 and 1000 mM with a high sensitivity of 13.2 μA mM−1, a detection limit of 40.2 μM (S/N = 3) and a fast response time within 5 s. Furthermore, the sensor presented good reproducibility, acceptable selectivity and excellent long-time stability. This study will provide a new approach for sensitive, rapid, in situ, and real-time monitoring of H2O2 for wide range applications.

Disciplinarians of hydraulic fractures propagation direction can make engineering decisions and suggestions for shale gas reservoir reformation. Based on the strain energy density factor theory, the relationships of fracture surface water pressure, fracture dip, and confining pressure ratio on hydraulic fracture propagation angle are studied. The extended finite element method is used to analysis the influences of bedding plane, natural fracture and horizontal stress difference on fracture propagation characteristics. When water pressure is less than maximum horizontal principal stress (σH), there is a critical fracture surface inclination angle, and fractures propagation direction is reversed along the original fracture line. When the pressure is equal to σH, fracture propagation angle increases with dip angle of the fracture surface, and is independent of the stress state. When water pressure is greater than σH, fracture propagation angle increases first and then decreases. When the angle between bedding plane and σH is small, hydraulic fractures propagation direction extends along the σH, conversely, along the bedding plane. The smaller horizontal stress difference is, the easier hydraulic fracture tends to be perpendicular to natural fracture, and the hydraulic fractures propagation direction easier to parallel to natural fracture in natural fracture.

Wi-Fi, which enables convenient wireless access to Internet services, has become integral to our modern lives. With widely-deployed Wi-Fi infrastructure, modern people can enjoy a variety of online services such as web browsing, online shopping, social interaction, and e-commerce almost at any time and any place. Traditionally, the most significant functionality of Wi-Fi is to enable high-throughput data communication between terminal devices and the Internet. However, beyond that, we observe that a novel type of system based on commodity Wi-Fi is increasingly attracting intense academic interest. Without hardware modification and redeployment, researchers are exploiting channel state information output by commodity Wi-Fi and transforming existing Wi-Fi systems into radar-like ones that can recognize human behavior along with data communication. This fancy functionality is tremendously expanding the boundaries of Wi-Fi to a new realm and triggering revolutionary applications in the context of the Internet of Things. In this article, we provide a guide to and introduce the impressive landscape of this new realm.

We propose that clusters interconnected with network topologies having minimal mean path length will increase their overall performance for a variety of applications. We approach our heuristic by constructing clusters of up to 36 nodes having Dragonfly, torus, ring, Chvatal, Wagner, Bidiakis and several other topologies with minimal mean path lengths and by simulating the performance of 256-node clusters with the same network topologies. The optimal (or sub-optimal) low-latency network topologies are found by minimizing the mean path length of regular graphs. The selected topologies are benchmarked using ping-pong messaging, the MPI collective communications, and the standard parallel applications including effective bandwidth, FFTE, Graph 500 and NAS parallel benchmarks. We established strong correlations between the clusters' performances and the network topologies, especially the mean path lengths, for a wide range of applications. In communication-intensive benchmarks, clusters with optimal network topologies out-perform those with mainstream topologies by several folds. It is striking that a mere adjustment of the network topology suffices to reclaim performance from the same computing hardware.

In this paper, Cu 2 ZnSn(S x Se 1 − x ) 4 precursor films were produced by doctor blade process from SnS-Cu 2 O-ZnS slurry. To prepare the slurry, SnS, ZnS and Cu 2 O precipitates, which are outgrowths of stacked layer ZnS/Cu/SnS by CBD (chemical bath deposition)-annealing route, were dissolved in the mixture solvent of ethanol and NH 3 ·H 2 O. Synthesized precursor films were then annealed at different conditions. The post-annealed films were characterized by means of scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Raman measurements and UV–vis–NIR spectroscopy. SEM studies reveal that the rough and relatively compact absorber thin films are obtained via the sulfidation and sulfidation-selenization processes. X-ray diffraction and Raman spectrum results verify that the obtained films are composed of Cu 2 ZnSnS 4 and Cu 2 ZnSnSe 4 phases, which have high absorbance in visible range and direct band gap energy of 1.01–1.47 eV. The best devices yield total area power conversion efficiency of 1.99% and 2.95% corresponding to Cu 2 ZnSnS 4 and Cu 2 ZnSn(S x Se 1 − x ) 4 thin film solar cells under AM1.5 illumination without any anti-reflection layer.

Based on the finding that the line-to-line flux linkage of wound-excited doubly salient machine (WEDSM) varies with the rotor position, a new method to estimate the initial rotor position without any pulse injection is proposed. This method detects the line-to-line flux linkage to determine the sector where the rotor locates in the building-up procedure of the excitation field. The drawbacks, including cogging torque ripple and magnetic saturation and asymmetry have effect on the accuracy of the estimation. And the effects are analyzed in detail. Further simulations and experiments verify the feasibility of the proposed method.