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The translational sprinkler irrigation machine is widely used because of its high degree of automation, less manual investment, and convenient movement. However, when using the sprinkler irrigation machine, the power supply is difficult to be guaranteed in some remote power shortage areas. Solar energy has become one of the best choices for the power source of sprinkler irrigation machines. An important issue is the optimal sizing of the stand-alone photovoltaic system for a solar-powered translational sprinkler irrigation machine. This work conducts the optimal sizing of the stand-alone photovoltaic system for a solar-powered translational sprinkler irrigation machine considering the loss of power supply probability. Firstly, the self-developed translational sprinkler irrigation machine is introduced. The load power, which includes the driving power of the translational sprinkler irrigation machine, water intake pressure driving power, and the loss power of the controller and sensors, is considered in the calculation process. Subsequently, the photovoltaic generator model and the battery storage model are established. Then, the stand-alone photovoltaic system is optimized considering the loss of power supply probability (LPSP) and the life cycle cost (LCC). After the solar irradiance and ambient temperature of a typical sunny day in the test area are given, the optimal combination of the PV module and battery is obtained. The optimal sizing result is verified using the PV power, state of charge (SOC), and load power. The presented optimal sizing method is also compared with an existing method. Besides, the operation test of the sprinkler irrigation machine is also carried out to verify the optimal sizing result. The optimal sizing result is proved to be effective and applicable.

This paper investigates a discrete-time (DT) adaptive optimal control policy based on broad learning system (BLS) and adaptive dynamic programming (ADP) for dynamic positioning (DP) of marine vessels, focusing on the unknown system dynamics, fuel saving and pollution reduction. Firstly, a BLS-based model structure in ADP is utilized to identify the unknown system dynamics. The weights of this flat architecture can be calculated without the process of iteration. Then, critic and action structures in ADP are established by two BLSs to solve the optimal problems of fuel saving and pollution reduction. These two structures are utilized to approximate the optimal performance index function and controller, respectively. The weights of these two structures are updated with the current and historical data. The proposed adaptive optimal controller is proved to be able to hold the vessel at a fixed position and heading in a more energy-saving and time-saving way than traditional neural network (NN)-based ADP method. It is proved that all the signals in the closed-loop DP system guarantee the uniform ultimate boundedness (UUB) simultaneously. Finally, simulations and comparisons are provided to illustrate the validity of the proposed adaptive optimal control scheme.

In this paper, a robust adaptive output feedback optimal tracking control design based on fuzzy logic systems (FLSs) is proposed for dynamic positioning (DP) of marine vessels with unknown environmental disturbances and uncertain dynamics. Firstly, a fuzzy state observer (FSO) is developed to obtain the unmeasured velocities and approximate the uncertain dynamics of the DP system. Then, the vectorial backstepping technique is adopted to design a feedforward controller. A FLS-based single critic structure is established to approximate the performance index function. Subsequently, an adaptive optimal feedback controller is presented by utilizing adaptive dynamic programming (ADP) method. Furthermore, the unknown environmental disturbances are estimated by a disturbance observer (DO) via the FSO to make the DP system robust. Therefore, the entire DP optimal control scheme is comprised of a feedforward controller, a feedback controller and an estimation of disturbances. The proposed robust adaptive optimal tracking control method can track the desired trajectory, and it is proved that all signals in the closed-loop DP system are uniformly ultimately bounded (UUB). Finally, simulation results are presented to illustrate the validity of the proposed DP control scheme.

Background Plants synthesize metabolites to adapt to a continuously changing environment. Metabolite biosynthesis often occurs in response to the tissue-specific combinatorial developmental cues that are transcriptionally regulated. Polyphyllins are the major bioactive components in Paris species that demonstrate hemostatic, anti-inflammatory and antitumor effects and have considerable market demands. However, the mechanisms underlying polyphyllin biosynthesis and regulation during plant development have not been fully elucidated. Results Tissue samples of P. polyphylla var. yunnanensis during the four dominant developmental stages were collected and investigated using high-performance liquid chromatography and RNA sequencing. Polyphyllin concentrations in the different tissues were found to be highly dynamic across developmental stages. Specifically, decreasing trends in polyphyllin concentration were observed in the aerial vegetative tissues, whereas an increasing trend was observed in the rhizomes. Consistent with the aforementioned polyphyllin concentration trends, different patterns of spatiotemporal gene expression in the vegetative tissues were found to be closely related with polyphyllin biosynthesis. Additionally, molecular dissection of the pathway components revealed 137 candidate genes involved in the upstream pathway of polyphyllin backbone biosynthesis. Furthermore, gene co-expression network analysis revealed 74 transcription factor genes and one transporter gene associated with polyphyllin biosynthesis and allocation. Conclusions Our findings outline the framework for understanding the biosynthesis and accumulation of polyphyllins during plant development and contribute to future research in elucidating the molecular mechanism underlying polyphyllin regulation and accumulation in P. polyphylla.

This paper addresses the berthing control problem for automatic ships by using a virtual guide system based on heuristic dynamic programming (HDP) method. Firstly, by introducing an automatic virtual guide system, the berthing control problem can be transformed into a tracking control problem, and then can be further transformed into an optimal regulation problem. Secondly, the HDP method is used to solve the optimal regulation control problem of the marine surface ship with unknown ship model. Then, it is proven that the tracking error, the adaptation laws and the control inputs are uniformly bounded on the basis of the Lyapunov theory. Finally, simulations are carried out on an automatic model ship and the HDP method is compared with the backstepping control to verify the effectiveness of the developed control scheme.

The Anthropocene proposal suggested that the Earth may have entered a new geological epoch, in which human activity and climate change are influencing the environment at global scale. Arrival of the Anthropocene is bringing an unprecedented challenge to the biodiversity that is essential to humans, and enhancing many benefits of nature to human being. However, biodiversity loss is aggravating in the rhythm of inevitable change in the Anthropocene, and the adaptation of biodiversity to the anthropogenic disturbance seems unable to keep pace with the human activity and climate change. Therefore, re-examination of the assumptions and practices upon the current conservation endeavor are needed. We suggested that biodiversity conservation should be paid more attention to the response from biodiversity to the human activity and climate change in the Anthropocene. Thus, the concept of biodiversity arks in the Anthropocene is proposed, that is, biodiversity arks in the Anthropocene are the areas where vulnerable biodiversity is sheltered to alleviate human activity and buffered from climate change under the anthropogenic disturbance. The concept should be implemented for biodiversity conservation to fill gaps between our knowledge and build on successful conservation and sustainability in the Anthropocene. It will be certainly important to conservation policy instruction and management under climate change, especially the implementation of climate buffering zones preserving biodiversity in the face of warming climate.

BackgroundLow-pass genome sequencing (LP GS) is an alternative to chromosomal microarray analysis (CMA). However, validations of LP GS as a prenatal diagnostic test for amniotic fluid are rare. Moreover, sequencing depth of LP GS in prenatal diagnosis has not been evaluated.ObjectiveThe diagnostic performance of LP GS was compared with CMA using 375 amniotic fluid samples. Then, sequencing depth was evaluated by downsampling.ResultsCMA and LP GS had the same diagnostic yield (8.3%, 31/375). LP GS showed all copy number variations (CNVs) detected by CMA and six additional variant of uncertain significance CNVs (>100 kb) in samples with negative CMA results; CNV size influenced LP GS detection sensitivity. CNV detection was greatly influenced by sequencing depth when the CNV size was small or the CNV was located in the azoospermia factorc(AZFc) region of the Y chromosome. Large CNVs were less affected by sequencing depth and more stably detected. There were 155 CNVs detected by LP GS with at least a 50% reciprocal overlap with CNVs detected by CMA. With 25 M uniquely aligned high-quality reads (UAHRs), the detection sensitivity for the 155 CNVs was 99.14%. LP GS using samples with 25 M UAHRs showed the same performance as LP GS using total UAHRs. Considering the detection sensitivity, cost and interpretation workload, 25 M UAHRs are optimal for detecting most aneuploidies and microdeletions/microduplications.ConclusionLP GS is a promising, robust alternative to CMA in clinical settings. A total of 25 M UAHRs are sufficient for detecting aneuploidies and most microdeletions/microduplications.

This study reports the development of a new, pH-sensitive, mitochondria-targeting two-photon ratiometric probe (Mito-BNO) for real-time tracking of mitophagy, a process that can be accelerated in brain tissue during stroke. Mito-BNO shows excellent capability for mitochondrial localisation (Pearson's correlation coefficient, r = 0.91), and can also effectively distinguish mitochondria from other subcellular organelles such as lysosomes and the endoplasmic reticulum (r = 0.40 and r = 0.33, respectively). Meanwhile, a rewarding pKa value (5.23 ± 0.03) and the pH reversibility suggest that Mito-BNO can track mitophagy in real time via confocal imaging. Most importantly, the relationship between mitophagy and neuroinflammation during stroke has been successfully demonstrated by evaluating the fluorescence of PC12 cells stained with Mito-BNO during an oxygen-glucose deprivation/reperfusion (OGD/R) process with and without anti-inflammatory treatment. The results indicate that the occurrence of mitophagy during stroke is caused by oxidative stress induced by neuroinflammation. This study will help further understanding stroke pathogenesis, can provide potential new targets for early diagnosis and treatment, and can also help to develop therapeutic drugs for stroke.

This paper investigates the problem of path following of underactuated marine surface vessels (MSVs) with uncertain nonlinear dynamics. First, the tracking target of the vessel is reduced from tracking the earth-fixed position to tracking the line-of-sight (LOS) angle by LOS method. Then, by employing the radial basis function neural network (RBFNN) to deal with the uncertain nonlinear dynamics, an adaptive NN fast power reaching law is developed for the path following problem based on the backstepping design methodology. Thereafter, the event-triggered technique is incorporated into the control design to synthesize an adaptive NN event-triggered controller with the fast power reaching convergence rate. By combining with the presented event-triggered mechanism, the controller is only updated when the triggering condition is satisfied. Therefore, both the update frequency of the controller and actuator loss are greatly reduced comparing with the traditional time-triggered controller. Theoretical analysis via Lyapunov method indicates that the tracking error can converge to zero within a finite time, meanwhile it also shows that Zeno behavior can be avoided. Simulation results with comparations illustrate the validity and superiority of the proposed controller.

Paris polyphylla Smith is a perennial medicinal herb with records from around 2000 years ago. Polyphyllins are the main bioactive compounds of this herb, which are found to have remarkable effects on bacteriostatic, antiphlogistic, sedative, and antitumor. However, the market demand for P. polyphylla is sharply increasing, and the wild resources are threatened by plundering exploitation. Integrating molecular data of P. polyphylla can benefit the sustainable resource exploitation. Here, we constructed PPDP (Paris polyphylla Data Portal) to provide a data platform for polyphyllin biosynthesis and germplasm resource research. PPDP integrates related molecular data resources, functional genomics analysis, and morphological identification. The database provides abundant data (transcriptome, CDS, lncRNA, alternative splicing, gene family, SSR, and chloroplast genome) and practical analytical tools (network construction, heatmap of expression profiles, enrichment, and pathway search) with a user-friendly interface. So far, PPDP is the first biomolecular database for the genus Paris plants. In the future, we will gradually add genomic data and other necessary molecular biological information to improve the database.

Lateral organ boundaries domain (LBD) proteins are plant-specific transcription factors that play important roles in organ development and stress response. However, the function of LBD genes has not been reported in Euphorbiaceae. In this paper, we used Jatropha curcas as the main study object and added rubber tree (Hevea brasiliensis), cassava (Manihot esculenta Crantz) and castor (Ricinus communis L.) to take a phylogenetic analysis of LBD genes. Of LBD, 33, 58, 54 and 30 members were identified in J. curcas, rubber tree, cassava and castor, respectively. The phylogenetic analysis showed that LBD members of Euphorbiaceae could be classified into two major classes and seven subclasses (Ia-Ie,IIa-IIb), and LBD genes of Euphorbiaceae tended to cluster in the same branch. Further analysis showed that the LBD genes of Euphorbiaceae in the same clade usually had similar protein motifs and gene structures, and tissue expression patterns showed that they also have similar expression profiles. JcLBDs in class Ia and Ie are mainly expressed in male and female flowers, and there are multiple duplication genes with similar expression profiles in these clades. It was speculated that they are likely to play important regulatory roles in flower development. Our study provided a solid foundation for further investigation of the role of LBD genes in the sexual differentiaion of J. curcas.

Germline mosaicism should be suspected when the same de novo mutations are identified in a second pregnancy with asymptomatic parents. Our study aims to find a feasible approach to reveal the existence of germline mosaicism. Multiplex Ligation-dependent Probe Amplification was performed on a Duchenne muscular dystrophy affected pedigree to detect deletion mutations. Then gap-polymerase chain reaction was performed to amplify the breakpoints junction sequence. Droplet digital polymerase chain reaction was utilized to identify the mutation frequencies in healthy parents. The same deletion in the exon 51 of the dystrophin gene, which was 50,035 bp in size, was detected in the proband and the fetus but not in their parents. Droplet digital polymerase chain reaction analysis of peripheral blood samples revealed mutant alleles of 3.53% in maternal blood cells. We here report a case of maternal low-level mosaicism confirmed by droplet digital polymerase chain reaction in peripheral blood samples, which reveals the existence of germline mosaicism. Gap-polymerase chain reaction combined with droplet digital polymerase chain reaction provide insights into the detection of germline mosaicism.

Life detection radar is widely applied in life detection, especially in situations that demand searching life signal through ruins after disasters. In these circumstances, weak signal feature extraction and analysis are vital technologies. Because of the clutter of environment objects, life signal that received by radar is seriously weak. Traditional methods cannot separate life signal from clutter and noise. This paper propose an algorithm combined with feedback pulse canceller, multiple autocorrelation and synchronous squeeze S-transform (SSST). This method can effectively suppress the clutter and remove the environment noise, then obtain a high-resolution time-frequency distribution. In this way we can make best of life signal feature and classify the type of living target.

Learning in automated negotiations, while successful for many tasks in recent years, is still hard when coping with different types of opponents with unknown strategies. It is critically essential to learn about the opponents from observations and then find the best response in order to achieve efficient agreements. In this paper, we propose a novel framework named Deep BPR+ (DBPR+) negotiating agent framework, which includes two key components: a learning module to learn a new coping policy when encountering an opponent using a previously unseen strategy, and a policy reuse mechanism to efficiently detect the strategy of an opponent and select the optimal response policy from the policy library. The performance of the proposed DBPR+ agent is evaluated against winning agents of ANAC competitions under varied negotiation scenarios. The experimental results show that DBPR+ agent outperforms existing state-of-the-art agents, and is able to make efficient detection and optimal response against unknown opponents.

The Totem-pole rectifier working in Continuous Conduction Mode (CCM) suffers the obvious current distortion at the zero-crossing area. The traditional closed-loop current controller design tries to reduce the zero-crossing distortion by making a tradeoff between the low-frequency reference tracking effect and high-frequency disturbance suppression, resulting in the harmonics increase. To solve this problem, this research analyzes the distortion from a different view and proposes the Precise Correction method. The distorted condition of current is extracted in the zero-crossing vicinity. And then an additional nonlinear compensation is added outside the original current control loop, which can eliminate the current distortion without introducing extra harmonics. The proposed control strategy is verified by simulation and experiment. With the Precise Correction method, the current distortion is eliminated and the unity power factor is achieved.

The monocot family Melanthiaceae with varying genome sizes in a range of 230-fold is an ideal model to study the genome size fluctuation in plants. Its family member Paris genus demonstrates an evolutionary trend of bearing huge genomes characterized by an average c-value of 49.22 pg. Here, we report a 70.18 Gb genome assembly out of the 82.55 Gb genome of Paris polyphylla var. yunnanensis (PPY), which represents the biggest sequenced genome to date. We annotate 69.53% repetitive sequences in this genome and 62.50% of which are long-terminal repeat (LTR) transposable elements. Further evolution analysis indicates that the giant genome likely results from the joint effect of common and species-specific expansion of different LTR superfamilies, which might contribute to the environment adaptation after speciation. Moreover, we identify the candidate pathway genes for the biogenesis of polyphyllins, the PPY-specific medicinal saponins, by complementary approaches including genome mining, comprehensive analysis of 31 next-generation RNA-seq data and 55.23 Gb single-molecule circular consensus sequencing (CCS) RNA-seq reads, and correlation of the transcriptome and phytochemical data of five different tissues at four growth stages. This study not only provides significant insights into plant genome size evolution, but also paves the way for the following polyphyllin synthetic biology.

Paris polyphylla var. yunnanensis can synthesize Paris saponins with multiple effective therapies, and its rhizome has become an indispensable ingredient in many patented drugs. However, how Paris saponin content changes in tissues at different stages and the molecular mechanisms underlying the production and accumulation of the bioactive compounds are unclear. This study aimed to uncover the mechanisms underlying the biosynthesis and accumulation by integrating transcriptome sequencing and phytochemical investigation of the leaves and rhizomes at different growth stages. Paris saponin content in leaves was lower during the fruiting stage than the vegetative stage, whereas the content in rhizomes increased during the fruiting stage. The candidate genes related to Paris saponin biosynthesis were determined by transcriptome analyses. Most biosynthetic genes were found to be abundantly expressed in the leaves during the vegetative stage in the light of expression profiles and functional enrichment results. The expression patterns of the differentially expressed genes related to the biosynthesis were positively correlated with the accumulation of saponins in tissues. These findings suggest that both leaves and rhizomes are capable of biosynthesizing Paris saponins, and that aerial plant parts can be used to extract them. The different patterns of biosynthesis and accumulation in the leaves and rhizomes were also determined here. This study will help improve our understanding of the mechanisms underlying the biosynthesis and accumulation of Paris saponins, and aid in the comprehensive development and utilization of this medicinal plant.

Additional file 3: Fig. S2: The synteny relationships among Euphorbiaceae and A. thaliana.

This paper is concerned with secure synchronization of multi-agent systems under deception attacks in the impulsive control framework. False data is injected into sensor-to-controller channels, which causes the transmittal signals being changed. Some stochastic variables obeying the Bernoulli distribution associated with communication channels between neighbouring agents are proposed to describe the case whether channels are suffered from the attack. A distributed impulsive controller is proposed and bounded synchronization, caused by false data injection is studied. Several mean-square bounded synchronization conditions are derived and the error bound is also given. Finally, two examples are provided to verify the theoretical results.

Background Euphorbiaceae is one of the largest families of flowering plants. Due to its exceptional growth form diversity and near-cosmopolitan distribution, it has attracted much interest since ancient times. SBP-box (SBP) genes encode plant-specific transcription factors that play critical roles in numerous biological processes, especially flower development. We performed genome-wide identification and characterization of SBP genes from four economically important Euphorbiaceae species. Results In total, 77 SBP genes were identified in four Euphorbiaceae genomes. The SBP proteins were divided into three length ranges and 10 groups. Group-6 was absent in Arabidopsis thaliana but conserved in Euphorbiaceae. Segmental duplication played the most important role in the expansion processes of Euphorbiaceae SBP genes, and all the duplicated genes were subjected to purify selection. In addition, about two-thirds of the Euphorbiaceae SBP genes are potential targets of miR156, and some miR-regulated SBP genes exhibited high intensity expression and differential expression in different tissues. The expression profiles related to different stress treatments demonstrated broad involvement of Euphorbiaceae SBP genes in response to various abiotic factors and hormonal treatments. Conclusions In this study, 77 SBP genes were identified in four Euphorbiaceae species, and their phylogenetic relationships, protein physicochemical characteristics, duplication, tissue and stress response expression, and potential roles in Euphorbiaceae development were studied. This study lays a foundation for further studies of Euphorbiaceae SBP genes, providing valuable information for future functional exploration of Euphorbiaceae SBP genes.

This paper proposes a multi-robot formation control algorithm. The controller is designed by the difference between the distance and the angle of the two robots. It is proved that the algorithm can guarantee the stability of the formation. Furthermore, the obtained formation control algorithm is tested on the software platform and Pioneer3-DX platform. According to the multi-robot formation control algorithm, a control method of adaptive parameters is proposed. The existing parameters are replaced by fitting equations, which improves the efficiency of parameter adjustment. Simulation and experimental results verify the feasibility and effectiveness of the proposed method.

In this paper, a discrete-time online optimal control via time-based adaptive dynamic programming is developed for dynamic positioning (DP) of vessels in the presence of unknown system dynamic, energy conservation and wastage decrease of equipment. Firstly, a model network is established by a neural network (NN) to identify the DP system. And then, a NN optimal control scheme is developed, in which current and recorded data of DP vessel are utilized to train the critic network and action network. The optimal cost and control law are updated once at the sampling instant. The designed DP optimal control policy can maintain the vessel at desired position and heading angle, and guarantee the uniform ultimate boundedness of all the signals in the closed-loop system simultaneously. Finally, simulation results involving a supply vessel demonstrate the effectiveness of the proposed DP optimal control law.

Spinal muscular atrophy (SMA) is a severe motor neuron degenerative disease caused by loss-of-function mutations in the survival motor neuron gene SMN1. It is widely posited that defective gene expression underlies SMA. However, the identities of these affected genes remain to be elucidated. By analyzing the transcriptome of a Caenorhabditis elegans SMA model at the pre-symptomatic stage, we found that the expression of numerous nuclear encoded mitochondrial genes and vacuolar H+-ATPase genes was significantly down-regulated, while that of histone genes was significantly up-regulated. We previously showed that the uaf-1 gene, encoding key splicing factor U2AF large subunit, could affect the behavior and lifespan of smn-1 mutants. Here, we found that smn-1 and uaf-1 interact to affect the recognition of 3′ and 5′ splice sites in a gene-specific manner. Altogether, our results suggest a functional interaction between smn-1 and uaf-1 in affecting RNA splicing and a potential effect of smn-1 on the expression of mitochondrial and histone genes.

In this paper, a time-space fractional advection diffusion equation is considered for the natural extension of the convection diffusion equation. An explicit difference scheme and an implicit difference scheme are presented. The stability and convergence of the two difference schemes are discussed. It is shown that the explicit difference scheme is conditionally stable and convergent, and the implicit difference scheme is unconditionally stable and convergent. The convergence order of the two methods is $O (\tau+h)$ .

Additional file 1. This file contains the additional tables (Table S1-S5) associated with the manuscript. Table numbers and titles were listed as follows: Table S1: The information of Euphorbiaceae SBP genes. Table S2: The protein physicochemical properties of Euphorbiaceae SBP proteins. Table S3: The parallel table of scaffold IDs and serial number. Table S4: The information of duplications. Table S5: The identified synteny relationships between Euphorbiaceae species.

In order to explore the in vitro giant magnetoresistive (GMR) biodetection procedure, exchange-biased GMR sensors with a Wheatstone bridge were adopted to detect a series of concentrations of MnFe2O4 magnetic microparticle alcohol solution using a direct current in-plane magnetic field measuring method. It is revealed that the output voltage $V_{\text {out}}$ of the transfer curve in the GMR sensor is sensitive to the magnetic microparticles and the maximum $V_{\text {out}}$ appears at a bias field around 2 Oe. The $V_{\mathrm {out}}$ difference between with and without magnetic particles, $\vert \Delta V\vert $ , linearly increases with particle concentration $x$ undergoing a relationship of $\vert \Delta V\vert =11.84x-93$ .30, indicating that the unknown concentration $x$ of MnFe2O4 particles can be deduced from the measurement of $V_{\mathrm {out}}$ . A lower detectable concentration limit of 12.5 $\mu \text{g}$ /mL is available in the device at this moment, and it can be further improved by reducing the size of magnetic particles.

Fully epitaxial FeCo/MgO/Fe magnetic tunnel junctions on silicon substrates were fabricated using in situ shadow-masks in an electron-beam deposition system. An inverse tunneling magnetoresistance (TMR) of −39% was observed at 77 K after annealing, which was not obtained in MTJs grown in better vacuum with the same device structure. This inverse TMR is attributed to the oxidation of the FeCo/MgO interface, which provides a negative spin polarization. Our work highlights the importance of interfacial properties on tunneling magnetoresistance and points to a simple processing route to achieve inverse TMR by carefully controlling the oxidation condition of the bottom layer.

A key step in pre-mRNA splicing is the recognition of 3’ splicing sites by the U2AF large and small subunits, a process regulated by numeroustrans-acting splicing factors. How thesetrans-acting factors interact with U2AFin vivois unclear. From a screen for suppressors of the temperature-sensitive (ts) lethality of theC. elegansU2AF large subunit geneuaf-1(n4588)mutants, we identified mutations in theRNAbindingmotif generbm-5, a homolog of the tumor suppressorRBM5.rbm-5mutations can suppressuaf-1(n4588)ts-lethality by loss of function and neuronal expression ofrbm-5was sufficient to rescue the suppression. Transcriptome analyses indicate thatuaf-1(n4588)affected the expression of numerous genes andrbm-5mutations can partially reverse the abnormal gene expression to levels similar to that of wild type. Thoughrbm-5mutations did not obviously affect alternative splicing per se, they can suppress or enhance, in a gene-specific manner, the altered splicing of genes inuaf-1(n4588)mutants. Specifically, the recognition of a weak 3’ splice site was more susceptible to the effect ofrbm-5. Our findings provide novelin vivoevidence that RBM-5 can modulate UAF-1-dependent RNA splicing and suggest that RBM5 might interact with U2AF large subunit to affect tumor formation.Author summaryRNA splicing is a critical regulatory step for eukaryotic gene expression and has been involved in the pathogenesis of multiple diseases. How RNA splicing factors interactin vivoto affect the splicing and expression of genes is unclear. In studying the temperature-sensitive lethal phenotypes of a mutation affecting the splicing factor U2AF large subunit geneuaf-1in the nematodeCaenorhabditis elegans, we isolated suppressive mutations in therbm-5gene, a homolog of the human tumor suppressor geneRBM5.rbm-5is broadly expressed in neurons to enhance the lethality of theuaf-1mutants. We found that the uaf-1 mutation causes aberrant expression of genes in numerous biological pathways, a large portion of which can be corrected byrbm-5mutations. The abnormal splicing of multiple genes caused by theuaf-1mutation is either corrected or enhanced byrbm-5mutations in a gene-specific manner. We propose that RBM-5 interacts with UAF-1 to affect RNA splicing and the tumor suppressor function of RBM5 might involve U2AF-dependent RNA splicing.

In air defense operation, the target identification of air is an important part. The BP network is more commonly used for target identification, but it has a slow convergence speed and easy to fall into local optimal disadvantages. Immune algorithm clone and mutation operation in reference to the wolves in the update mechanism improve the convergence speed of wolves in the algorithm, using immune wolf pack algorithm to optimize initial weights and threshold value of BP network, improve the defect of easily plunged into local optimum and improve the convergence speed of BP network, the optimized BP network is used to solve the problem of target recognition. The simulation results show that the algorithm is efficient and effective.

Electrochemical impedance spectroscopy (EIS) is an effective method for studying electrochemical systems. The interpretation of EIS is the biggest challenge in this technology, which requires reasonable modeling. To overcome the subjectivity of human analysis, this work uses machine learning to carry out EIS model recognition. Raw EIS data and their equivalent circuit models are collected from the literature, and the support vector machine (SVM) is used to analyze these data. Comparing with other machine learning algorithms, SVM achieves the best comprehensive performance in this database. As a result, the optimized SVM model can efficiently figure out the most suitable equivalent circuit model of the given EIS spectrum. This study demonstrates the great potential of machine learning in electrochemical researches.

Physic nut (Jatropha curcas L.) is a species of flowering plant with great potential for biofuel production and as an emerging model organism for functional genomic analysis, particularly in the Euphorbiaceae family. DNA binding with one finger (Dof) transcription factors play critical roles in numerous biological processes in plants. Nevertheless, the knowledge about members, and the evolutionary and functional characteristics of the Dof gene family in physic nut is insufficient. Therefore, we performed a genome-wide screening and characterization of the Dof gene family within the physic nut draft genome. In total, 24 JcDof genes (encoding 33 JcDof proteins) were identified. All the JcDof genes were divided into three major groups based on phylogenetic inference, which was further validated by the subsequent gene structure and motif analysis. Genome comparison revealed that segmental duplication may have played crucial roles in the expansion of the JcDof gene family, and gene expansion was mainly subjected to positive selection. The expression profile demonstrated the broad involvement of JcDof genes in response to various abiotic stresses, hormonal treatments and functional divergence. This study provides valuable information for better understanding the evolution of JcDof genes, and lays a foundation for future functional exploration of JcDof genes.

Table S5. ANKDD1B PCR and sequencing primers. (PPTX 40 kb)

Figure S1. Venn diagram analysis for gene composition from chloroplast genomes of Sect. Marmorata via different assembly methods and reference genomes. Figure S2. Six kinds of SSR motifs in fifteen Paris chloroplast genomes. P. polyphylla var. yunnanensis0 was sequenced by Song et al (2015). P. marmorata0, P. luquanensis0, P. polyphylla var. yunnanensis were sequenced by Huang et al (2016). P. marmorata and P. luquanensis were sequenced in this study. Figure S3. Phylogenetic trees of genes spacer regions harbored repeat sequence, using NJ (bootstrap values on the left of slashes) and ML (bootstrap values on the right of slashes) algorithms. Figure S4. The Ka/Ks ratios of 71 protein-coding genes from chloroplast genome of Sect. Marmorata. Red bars and blue bars denote P. marmorata (PMa) and P. luquanensis (PLa) sequenced previously; green bars and yellow bars denote P. marmorata (PMb) and P. luquanensis (PLb) sequenced in this study. Figure S5. Comparison of Ka, Ks, and Ka/Ks ratios of Sect. Marmorata chloroplast genes. (A-C) denote Ka, Ks, and Ka/Ks, respectively. Red highlight boxplots indicate photosynthesis genes, green ones indicate genes involved in self-replication, and blue ones indicate other genes. SR: small subunit of ribosome, LR: large subunit of ribosome, DR: DNA-dependent RNA, TF: translational initiation factor, ND: NAPH dehydrogenase, PI: photosystem I, PII: photosystem II, CC: cytochrome b/f complex, AS: ATP synthase gene, LS: large subunit of rubisco, SA: subunit of acetyl-CoA, CS: cytochrome synthesis, CT: c-type cytochrome synthesis, PR: protease, MA: maturase, CO: conserved ORF. (PDF 793 kb)

Table S6. PCR primers for haplotype genotyping. (PPTX 41 kb)

Table S1. Summary of chloroplast genome characteristics of Sect. Marmorata. Table S2. List of gene function in the chloroplast genomes. Table S3. Distribution of tandem repeats from the chloroplast genomes. Table S4. Distribution of dispersed, forward and inverted/palindromic repeats from chloroplast genomes. Table S5. Type and number of SSRs in the chloroplast genomes. (PDF 396 kb)

Table S4. List of candidate genes. (PPTX 46 kb)

Table S6. PCR primers for haplotype genotyping. (PPTX 41 kb)

Table S1. List of patients from the AS9 pedigree and sAS_P1. (PPTX 45 kb)

Table S4. List of candidate genes. (PPTX 46 kb)

Figure S1. Venn diagram analysis for gene composition from chloroplast genomes of Sect. Marmorata via different assembly methods and reference genomes. Figure S2. Six kinds of SSR motifs in fifteen Paris chloroplast genomes. P. polyphylla var. yunnanensis0 was sequenced by Song et al (2015). P. marmorata0, P. luquanensis0, P. polyphylla var. yunnanensis were sequenced by Huang et al (2016). P. marmorata and P. luquanensis were sequenced in this study. Figure S3. Phylogenetic trees of genes spacer regions harbored repeat sequence, using NJ (bootstrap values on the left of slashes) and ML (bootstrap values on the right of slashes) algorithms. Figure S4. The Ka/Ks ratios of 71 protein-coding genes from chloroplast genome of Sect. Marmorata. Red bars and blue bars denote P. marmorata (PMa) and P. luquanensis (PLa) sequenced previously; green bars and yellow bars denote P. marmorata (PMb) and P. luquanensis (PLb) sequenced in this study. Figure S5. Comparison of Ka, Ks, and Ka/Ks ratios of Sect. Marmorata chloroplast genes. (A-C) denote Ka, Ks, and Ka/Ks, respectively. Red highlight boxplots indicate photosynthesis genes, green ones indicate genes involved in self-replication, and blue ones indicate other genes. SR: small subunit of ribosome, LR: large subunit of ribosome, DR: DNA-dependent RNA, TF: translational initiation factor, ND: NAPH dehydrogenase, PI: photosystem I, PII: photosystem II, CC: cytochrome b/f complex, AS: ATP synthase gene, LS: large subunit of rubisco, SA: subunit of acetyl-CoA, CS: cytochrome synthesis, CT: c-type cytochrome synthesis, PR: protease, MA: maturase, CO: conserved ORF. (PDF 793 kb)