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Aiming at the low exploration level, slow speed and repeated exploration of UAVs in unknown environments, this paper improves the selection of boundary points based on the boundary driving method, and proposes a method suitable for UAVs to quickly explore in unknown environments. Planning method: while using the depth image (RGBD) sensor to receive environmental information, the octree map of the known environment is constructed in real time, and the common indoor environment is divided into six local environmental types. The drone observes according to the RGBD camera on board. The local environment type generates instantaneous speed commands, and designs composite boundary points, from which the point with the largest information gain and the smallest yaw angle is weighed as the boundary guide point. Finally, a simulation experiment was carried out and comparing with the existing methods. The time required to explore the apartment environment in the next best viewpoint (NBV) in Document with the present method is 68.7% less than the exploration time in the paper. In addition, this paper designs There are four types of environments. In these environments, the present method reduces the average exploration time by 97.1% comparing with the method in Document. The experimental results show that the present method can effectively improve the exploration efficiency and has strong feasibility.

Polyethylene oxide (PEO) based polymer electrolytes have been widely used in solid-state lithium batteries (SSBs) owing to the high solubility of lithium salt, favourable ionic conductivity, flexibility for improved interfacial contact and scalable processing. In this work, we summarize the main limitations remaining to be solved before the large-scale commercialization of PEO-based SSBs, including (1) improving ionic conductivity toward high-rate performance and lower operating temperature, (2) enhancing mechanical strength for improved lithium dendrite resistance and large-scale processing, (3) strengthening electrochemical stability to match high energy density electrodes with high voltage, and (4) achieving high thermal stability toward safe operation. Meanwhile, the characterization methods to investigate the ion transportation mechanism, lithium dendrite growth and decomposition reaction are also discussed.

Chromatin immunoprecipitation sequencing (ChIP-seq) is a powerful and widely used molecular technique for mapping whole genome locations of transcription factors (TFs), chromatin regulators, and histone modifications, as well as detecting entire genomes for uncovering TF binding patterns and histone posttranslational modifications. Chromatin-modifying activities, such as histone methylation, are often recruited to specific gene regulatory sequences, causing localized changes in chromatin structures and resulting in specific transcriptional effects. The rice blast is a devastating fungal disease on rice throughout the world and is a model system for studying fungus-plant interaction. However, the molecular mechanisms in how the histone modifications regulate their virulence genes in Magnaporthe oryzae remain elusive. More researchers need to use ChIP-seq to study how histone epigenetic modification regulates their target genes. ChIP-seq is also widely used to study the interaction between protein and DNA in animals and plants, but it is less used in the field of plant pathology and has not been well developed. In this paper, we describe the experimental process and operation method of ChIP-seq to identify the genome-wide distribution of histone methylation (such as H3K4me3) that binds to the functional target genes in M. oryzae. Here, we present a protocol to analyze the genome-wide distribution of histone modifications, which can identify new target genes in the pathogenesis of M. oryzae and other filamentous fungi.

Chromatin immunoprecipitation sequencing (ChIP-seq) is a powerful and widely used molecular technique for mapping whole genome locations of transcription factors (TFs), chromatin regulators, and histone modifications, as well as detecting entire genomes for uncovering TF binding patterns and histone posttranslational modifications. Chromatin-modifying activities, such as histone methylation, are often recruited to specific gene regulatory sequences, causing localized changes in chromatin structures and resulting in specific transcriptional effects. The rice blast is a devastating fungal disease on rice throughout the world and is a model system for studying fungus-plant interaction. However, the molecular mechanisms in how the histone modifications regulate their virulence genes in Magnaporthe oryzae remain elusive. More researchers need to use ChIP-seq to study how histone epigenetic modification regulates their target genes. ChIP-seq is also widely used to study the interaction between protein and DNA in animals and plants, but it is less used in the field of plant pathology and has not been well developed. In this paper, we describe the experimental process and operation method of ChIP-seq to identify the genome-wide distribution of histone methylation (such as H3K4me3) that binds to the functional target genes in M. oryzae. Here, we present a protocol to analyze the genome-wide distribution of histone modifications, which can identify new target genes in the pathogenesis of M. oryzae and other filamentous fungi.

IEF, a novel plasma plasma membrane protein, is important for exine formation in Arabidopsis. Exine, an important part of pollen wall, is crucial for male fertility. The major component of exine is sporopollenin which are synthesized and secreted by tapetum. Although sporopollenin synthesis has been well studied, the transportation of it remains elusive. To understand it, we analyzed the gene expression pattern in tapetal microdissection data, and investigated the potential transporter genes that are putatively regulated by ABORTED MICROSPORES (AMS). Among these genes, we identified IMPERFECTIVE EXINE FORMATION (IEF) that is important for exine formation. Compared to the wild type, ief mutants exhibit severe male sterility and pollen abortion, suggesting IEF is crucial for pollen development and male fertility. Using both scanning and transmission electron microscopes, we showed that exine structure was not well defined in ief mutant. The transient expression of IEF-GFP driven by the 35S promoter indicated that IEF-GFP was localized in plasma membrane. Furthermore, AMS can specifically activate the expression of promoterIEF:LUC in vitro, which suggesting AMS regulates IEF for exine formation. The expression of ATP-BINDING CASSETTE TRANSPORTER G26 (AGCB26) was not affected in ief mutants. In addition, SEM and TEM data showed that the sporopollenin deposition is more defective in abcg26/ief-2 than that of in abcg26, which suggesting that IEF is involved in an independent sporopollenin transportation pathway. This work reveal a novel gene, IEF regulated by AMS that is essential for exine formation.

Histone H3K4 methylation is catalysed by the multi-protein complex known as the Set1/COMPASS or MLL/COMPASS-like complex, an element that is highly evolutionarily conserved from yeast to humans. However, the components and mechanisms by which the COMPASS-like complex targets the H3K4 methylation of plant pathogenic genes in fungi remain elusive. Here we present a comprehensive analysis combining biochemical, molecular, and genome-wide approaches to characterize the roles of the COMPASS-like family in Magnaporthe oryzae, a model plant fungal pathogen. We purified and identified six conserved subunits of COMPASS from the rice blast fungus M. oryzae, i.e., MoBre2 (Cps60/ASH2L), MoSpp1 (Cps40/Cfp1), MoSwd2 (Cps35), MoSdc1 (Cps25/DPY30), MoSet1 (MLL/ALL) and MoRbBP5 (Cps50), using an affinity tag on MoBre2. We determined the SPRY domain of MoBre2 can recognize directly with DPY30 domain of MoSdc1 in vitro. Furthermore, we found that deletion of the genes encoding COMPASS subunits of MoBre2, MoSpp1 and MoSwd2 caused similar defects regarding invasive hyphal development and pathogenicity. Genome-wide profiling of H3K4me3 revealed that the it has remarkable co-occupancy at the TSS regions of target genes. Significantly, these target genes are often involved in spore germination and pathogenesis. Decreased gene expression caused by the deletion of MoBre2, MoSwd2 or MoSpp1 gene was highly correlated with decrease in H3K4me3. Taken together, these results suggest that MoBre2, MoSpp1, and MoSwd2 function as a whole COMPASS complex, contributing to fungal development and pathogenesis by regulating H3K4me3-targeted genes in M. oryzae.

In order to reduce the changing times of battery’s output power loads and currents, a novel energy management strategy was developed for hybrid power system including a battery pack and an ultracapacitor (UC) pack. The strategy is utilizing wavelet-transform algorithm to allocate power components with different frequency contents among the on-board energy sources. The models of hybrid power system were developed and simulated in MATLAB/Simulink. Simulation results show that: Compared with the logic threshold strategy, the wavelet control method can avoid battery to receive chaotic high-frequency components more effectively. Meantime, the utilization of ultra-capacitor can be improved. Thus battery can be protected and the efficiency of electric vehicles can be increased.

We have demonstrated that a supersonic beam of methyl radicals (CH$_3$) in the ground rotational state of both $para$ and $ortho$ species has been slowed down to standstill with a magnetic molecular decelerator, and successfully captured spatially in an anti-Helmholtz magnetic trap for $>$ 1 s. The trapped CH$_3$ radicals have a mean translational temperature of about 200 mK with an estimated density of $>5.0\times10^7$ cm$^{-3}$. The methyl radical is an ideal system for the study of cold molecules not only because of its high reactivities at low temperatures, but also because further cooling below 1 mK is plausible via sympathetic cooling with ultracold atoms. The demonstrated trapping capability of methyl radicals opens up various possibilities for realizing ultracold ensembles of molecules towards Bose-Einstein condensation of polyatomic molecules and investigations of reactions governed by quantum statistics.

Credit risk has been a widespread and deep penetrating problem for centuries, but not until various credit derivatives and products were developed and novel technologies began radically changing the human society, have fraud detection, credit scoring and other risk management systems become so important not only to some specific firms, but to industries and governments worldwide. Frauds and unpredictable defaults cost billions of dollars each year, thus, forcing financial institutions to continuously improve their systems for loss reduction. In the past twenty years, amounts of studies have proposed the use of data mining techniques to detect frauds, score credits and manage risks, but issues such as data selection, algorithm design, and hyperparameter optimization affect the perceived ability of the proposed solutions and it is difficult for auditors and researchers to explore and figure out the highest level of general development in this area. In this survey we focus on a state of the art survey of recently developed data mining techniques for fraud detection and credit scoring. Several outstanding experiments are recorded and highlighted, and the corresponding techniques, which are mostly based on supervised learning algorithms, unsupervised learning algorithms, semisupervised algorithms, ensemble learning, transfer learning, or some hybrid ideas are explained and analysed. The goal of this paper is to provide a dense review of up-to-date techniques for fraud detection and credit scoring, a general analysis on the results achieved and upcoming challenges for further researches.

We have demonstrated that supersonic beams of oxygen molecules $({\text{O}}_{2})$ in the ground rotational state were slowed to a near standstill by a linear Zeeman decelerator and successfully confined spatially in an anti-Helmholtz magnetic trap. The translational temperature of the decelerated ${\text{O}}_{2}$ molecules was about 800 mK. The demonstrated trapping capability of paramagnetic species opens up various possibilities for the investigation of cold collisions and reactions of various radicals in the sub-kelvin regime by spatially confining them in a magnetic trap.

Conventional Zeeman decelerator, consisting of 80 stages, was constructed and tested. The experimental setup was characterized using O₂ as the reference molecule. Known results of deceleration of O₂ were reproduced. As an extension, detailed REMPI analysis of deceleration of O₂ was carried out, this REMPI analysis was conducted in parallel with ref [1]. Numerical simulation was successful in reproducing the TOF and REMPI spectra of deceleration of O₂. The extension of using Zeeman decelerator to decelerate a polyatomic radical, CH₃, was successful: from initial velocity of 480m/s to a final velocity of 368m/s, corresponding to a removal of 41.2% of the initial translational energy. The decelerator’s efficiency at final velocity of 368m/s is around ~10%. The limiting factor of further deceleration is the signal to noise ratio. Hence, optimization of DC discharge conditions of CH₃ were attempted, but the attempt was with limited success.

With the continuous development of recommender systems technology, people's reliance and demand on recommender systems is increasing, while traditional recommendation models have been unable to meet this increasingly diversified demand. This paper designs a general improved model to take advantage of the additional information, especially the essential information of objective product category, other than the traditional rating information contained in data, in order to improve the performance of recommender systems and meet the demand. This improved model is to optimize the results of recommendation based on traditional recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide controllable adjustment range, which thereby makes it possible to provide optional modes of recommendation aiming different kinds of users.

Control of the translational motion of methyl radicals is demonstrated by using pulsed magnetic fields created by a series of solenoid coils. By synchronously switching the magnetic fields corresponding to the motion of the radicals, we have observed the deceleration and focusing of a supersonic radical beam. The present result shows that Zeeman deceleration of polyatomic free radicals in the doublet state can be realized. This opens possibilities for trapping cold polyatomic free radicals in a spatially confined area leading to further studies of cold collisions and reactions.

A practical and chromatography-free synthesis of vinamidinium salts and their use as diene precursors in Diels–Alder reactions is reported. Additionally, 1,3-dipyrrolidino-1,3-butadiene was shown to be significantly more reactive than Rawal’s diene in a competition experiment.

A practical and chromatography-free synthesis of vinamidinium salts and their use as diene precursors in Diels–Alder reactions is reported. Additionally, 1,3-dipyrrolidino-1,3-butadiene was shown to be significantly more reactive than Rawal’s diene in a competition experiment.

Based on the standard theory of the firm, a dynamic model for the study of R&D management in a strategic alliance is presented. The model provides insight into the firm's behavior in a strategic alliance with R&D activity. By using this dynamic model, the optimal level of technology for a firm can be determined from the profit maximization viewpoint. The model indicates that firms with complementary skills and resources in a strategic alliance will be better off in terms of R&D cost, profit and competitiveness.

A new aggregation method-Minimum Distance Method (MDMJ)-was developed to support the group decision process and to help decision makers achieve consensus under the framework of AHP. MDM employs the general distance concept, and is proven to be very appealing to the compromise nature of a group decision making. It preserves all characteristics of the functional equations approach proposed by Aczel and Saaty (1987). MDM is based on a goal programming model, which is easy to solve by using optimization software such as LINDO. Using the goal programming model, MDM provides the weighted membership capability. Sensitivity analysis can be performed to investigate the effect of varying the decision makers' relative importance in terms of weights in the goal programming model. Sensitivity analysis also allows us to make robust decisions.