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Abstract Conflicting evidence still exists regarding Vitamin B12’s involvement in coronary heart disease (CHD). There is no precedent for previous studies to include both Vitamin B12, Vitamin B6, as well as Vitamin E in the consideration of CHD associating factors. Our data derived from the National Health and Nutrition Examination Survey (NHANES), which covers the period 2003–2020. 33,640 samples were included in this cross-sectional study. We used an unadjusted covariates and three adjusted covariates. The intake percentage of Vitamins E, B6, and B12 was categorized into continuous and categorical variables using multivariate logistic regression analysis and subgroup logistic regression. To estimate these trends, we applied the percentage categories of Vitamin E, B6, and B12 intake as continuous variables. We recorded Vitamin E, B6, B12, age, race, BMI, gender, household annual income, education level, hypertension status, diabetes status, smoking status, and drinking status for included samples. Multivariate regression analysis revealed that Vitamin E and B6 were negatively associated with CHD and exerted protective effects, while Vitamin B12 had little correlation with CHD. Based on the quartiles of Vitamin E and Vitamin B6 percentage, the strongest protective effect was observed in the third quartile (Q3). Analyses of subgroups showed the effects of Vitamin B6 and Vitamin E on CHD were more noticeable in women, the participant’s BMI was in the 25–30 range, and participants who smoked. We identified the possible protective effect of Vitamin E and Vitamin B6 against CHD, especially in female, obese, and smoking populations, whereas income and education were also viewed as influencing factors that could be taken into account.

Cavity electro-opto-mechanical (EOM) systems enable the microwave-optical interaction via the mechanical intermedia. By driving the electromechanical and optomechanical beam splitter interactions simultaneously, the EOM system can coherently convert the photons between microwave and optical domains bidirectionally. Here, we use this property to study a tunable dual-mode radio frequency reception, which is achieved by coherent frequency up-conversion in a two-mechanical-mode EOM system, and signal processing in an all-optical manner. A comprehensive design of EOM based dual-mode radio frequency receiver is proposed and demonstrated. We systematically analyze the realization of dual-mode radio frequency reception and verification of the dual-mode tunability. The results suggest well performance in tunable dual-mode frequency up-conversion and noise suppression. In addition, it also shows the advantages in low-power consumption, miniaturization, and massive on-chip integration. Given the latest advances on cavity electro-opto-mechanics, our scheme is feasible and can be extended to tunable multichannel multimode radio frequency reception.

Microwaves exhibit superior performance in free-space transmission compared to optical waves, primarily due to their ability to penetrate fog and experience lower losses in the Earth’s atmosphere. Based on microwave–optical entanglement prepared by nano-cavity electro-opto-mechanic converters, we propose a scheme of a quantum positioning system using the distance-based positioning method. Principles of microwave–optical entanglement preparation and our QPS scheme are introduced in detail. The entanglement feature, system stability and positioning feature of the scheme are analyzed after simulations. Furthermore, we delve into the impact of key parameters, such as transmissivity and photon conversion efficiency, on positioning. Notably, the entanglement degrees for both microwave–optic entanglement at the transmitter and optic–optic entanglement at the receiver surpass one, affirming the efficiency of the scheme in preparing and maintaining entanglement. When transmissivity in beam-splitter models of both ground stations equals 0.5, our scheme achieves a minimal positioning error of 6.4×10−7m2 under ideal conditions. Additionally, we map out traces of a plane through continuous positioning using our scheme. These results demonstrate the theoretical efficiency and robustness of our proposed approach.

Rapid advancements in Internet of Things (IoT) technology have promoted numerous novel applications that are sensitive to information timeliness. With different applications coexisting in one wireless network, each of which has heterogeneous traffic characteristics, it is of paramount importance while challenging to address how to characterize and optimize the information freshness performance network-wide, particularly in the massive access scenario. This paper casts attention on the heterogeneous slotted Aloha network and uses the Peak Age of Information (PAoI) metric to quantify information freshness. By assuming that the sensors in each group are equipped with unit-sized buffers and Bernoulli packet arrival, we derive the network steady-state point and PAoI. Depending on whether one group or all groups are age-sensitive, we focus on single-group PAoI and global PAoI optimization respectively. When only one single group is age-sensitive, we derive its optimal transmission probability. When all groups are age-sensitive, we propose a heuristic algorithm based on the particle swarm optimization method, where the bi-stability of Aloha network is considered for avoiding the risk of rapid performance deterioration. Extensive simulation results are presented to verify our analysis and the effectiveness of the proposed algorithm.

Visual positioning is a basic component for UAV operation. The structure-based methods are, widely applied in most literature, based on local feature matching between a query image that needs to be localized and a reference image with a known pose and feature points. However, the existing methods still struggle with the different illumination and seasonal changes. In outdoor regions, the feature points and descriptors are similar, and the number of mismatches will increase rapidly, leading to the visual positioning becoming unreliable. Moreover, with the database growing, the image retrieval and feature matching are time-consuming. Therefore, in this paper, we propose a novel hierarchical visual positioning method, which includes map construction, landmark matching and pose calculation. First, we combine brain-inspired mechanisms and landmarks to construct a cognitive map, which can make image retrieval efficient. Second, the graph neural network is utilized to learn the inner relations of the feature points. To improve matching accuracy, the network uses the semantic confidence in matching score calculations. Besides, the system can eliminate the mismatches by analyzing all the matching results in the same landmark. Finally, we calculate the pose by using a PnP solver. Furthermore, we evaluate both the matching algorithm and the visual positioning method experimentally in the simulation datasets, where the matching algorithm performs better in some scenes. The results demonstrate that the retrieval time can be shortened by three-thirds with an average positioning error of 10.8 m.

We study a novel detection of radio frequency signal, which is realized by the coherent microwave-optical conversion and optical processing. An electro-opto-mechanical converter, which enables the bidirectional transduction of the information between microwave and optical domains, is performed to convert the radio frequency signal into optical photons. We demodulate the converted optical signal for the baseband information via homodyne detection. We propose a comprehensive design of radio frequency front end based on the electro-opto-mechanics, and investigate the noise characteristics, which is quantified by the noise figure. The results show that the total noise figure can be significantly suppressed to 3.155 dB. Our scheme can be extended to tunable multichannel multimode radio frequency reception with the latest advances on electro-opto-mechanics. This study opens up prospects for radio frequency sensing with coherent microwave-optical conversion.

Abstract Background Gibberellin (GA) and jasmonate (JA) are two essential phytohormones for filament elongation in Arabidopsis. GA and JA trigger degradation of DELLAs and JASMONATE ZIM-domain (JAZ) proteins through SCFSLY1 and SCFCOI1 separately to activate filament elongation. In JA pathway, JAZs interact with MYB21 and MYB24 to control filament elongation. However, little is known how DELLAs regulate filament elongation. Results Here we showed that DELLAs interact with MYB21 and MYB24, and that R2R3 domains of MYB21 and MYB24 are responsible for interaction with DELLAs. Furthermore, we demonstrated that DELLA and JAZ proteins coordinately repress the transcriptional function of MYB21 and MYB24 to inhibit filament elongation. Conclusion We discovered that DELLAs interact with MYB21 and MYB24, and that DELLAs and JAZs attenuate the transcriptional function of MYB21 and MYB24 to control filament elongation. This study reveals a novel cross-talk mechanism of GA and JA in the regulation of filament elongation in Arabidopsis.

Converting signals from the microwave to the optical domain has attracted great attention due to its potential applications in the field of quantum networks. Achieving efficient transduction is a significant yet challenging task, where a high efficiency at single photon level and low added noise are required. Electro-opto-mechanics have been proven to be efficient to convert microwave and optical photons bidirectionally. In this work, we propose and demonstrate an enhanced microwave-optical conversion in an electro-opto-mechanical system by introducing a mechanical ancilla attached the microwave resonator. Based on the ancillary electromechanical coupling, the damping rate of the microwave resonator is controlled and further leads to significant enhancement in conversion, such as the increase of conversion efficiency, broadening of conversion bandwidth and reduction of added noise. It provides a feasible approach to realize a broadband microwave-optical conversion with high efficiency. Moreover, the reduced added noise may break the limitation of quantum transduction due to the ancillary electromechanical coupling. Our scheme is also applicable and feasible for opto-mechanics and other systems to achieve practical quantum interface.

Pine wilt disease (PWD) has caused huge economic and environmental losses since it invaded China. Although early monitoring is an effective way to control this hazard, the monitoring window for the early stage is hard to identify, and varies in different hosts and environments. We used UAV-based multispectral images of Pinus thunbergii forest in East China to identify the change in the number of infected trees in each month of the growing season. We built classification models to detect different PWD infection stages by testing three machine learning algorithms—random forest, support vector machine, and linear discriminant analysis—and identified the best monitoring period for each infection stage (namely, green attack, early, middle, and late). From the obtained results, the early monitoring window period was determined to be in late July, whereas the monitoring window for middle and late PWD stages ranged from mid-August to early September. We also identified four important vegetation indices to monitor each infection stage. In conclusion, this study demonstrated the effectiveness of using machine learning algorithms to analyze multitemporal multispectral data to establish a window for early monitoring of pine wilt disease infestation. The results could provide a reference for future research and guidance for the control of pine wilt disease.

Pine wilt disease (PWD) is a global destructive threat to forests, having caused extreme damage in China. Therefore, the establishment of an effective method to accurately monitor and map the infection stage by PWD is imperative. Unmanned aerial vehicle (UAV)-based hyperspectral imaging (HI) and light detection and ranging (LiDAR) technique is an effective approach for forest health monitoring. However, few previous studies have used airborne HI and LiDAR to detect PWD and compared the capability for predicting PWD infection stage at the tree level. In this paper, PWD infection was divided into five stages (green, early, middle, heavy, and grey), and HI and LiDAR data were integrated to detect PWD. We estimated the power of the hyperspectral method (HI data only), LiDAR (LiDAR data only), and their combination (HI plus LiDAR data) to predict the infection stages of PWD using the random forest (RF) algorithm. We obtained the following results: (1) The classification accuracies of HI (OA: 66.86%, Kappa: 0.57) were higher than those of LiDAR (OA: 45.56%, Kappa: 0.27) for predicting PWD infection stages, and their combination had the best accuracies (OA: 73.96%, Kappa: 0.66); (2) LiDAR data had higher ability for dead tree identification than HI data; and (3) The combined use of HI and LiDAR data for estimation of PWD infection stages showed that LiDAR metrics (e.g., crown volume) were essential in the classification model, although the variables derived from HI data contributed more than those extracted from LiDAR. Therefore, we proposed a new approach combining the merits of HI and LiDAR data to precisely predict PWD infection stages at the tree level, allowing better PWD monitoring and control. The approach could also be employed for mapping and monitoring other forest disturbance issues.

Seed production is critical for watermelon production, which mostly involves first-generation hybrid varieties. However, watermelon hybrid seed production currently requires complex procedures, including artificial isolation and pollination. Therefore, the development and use of a male-sterile system to generate watermelon hybrids can simplify the process. The scarcity of male-sterile watermelon germplasm resources necessitates the use of molecular breeding methods. Unfortunately, the genes responsible for male sterility in watermelon have not been cloned. Thus, the genetic basis of the male sterility remains unknown. In this study, two DNA pools derived from male-sterile and normal plants in the F2 population were used for whole-genome resequencing. The Illumina high-throughput sequencing resulted in 62.99 Gbp clean reads, with a Q30 of 80% after filtering. On the basis of the SNP index association algorithm, eight candidate regions (0.32 Mb) related to specific traits were detected on chromosome 6. Expression pattern analyses and watermelon transformation studies generated preliminary evidence that Cla006625 encodes a pollen-specific leucine-rich repeat protein (ClaPEX1) influencing the male sterility of watermelon. The identification and use of genic male sterility genes will promote watermelon male sterility research and lay the foundation for the efficient application of seed production technology.

Microwave is widely used in present navigation system. It works well, yet it faces precision limit and other challenges. Quantum entanglement has been applied in various fields and resulted in quite remarkable improvements, especially in precision performance. Hence, we attempt to apply quantum entanglement to enhance merits of navigation system performed in microwave regime. This paper introduces principles of microwave-optical entanglement prepared by electro-opto-mechanical converters in detail. Meanwhile, a navigation ranging scheme exploiting this type of entanglement is proposed. The performance of the scheme is analyzed, and factors influencing entanglement feature and ranging feature are discussed. It shows that the ranging scheme has achieved quite precise results with help of microwave-optical entanglement, and it may be regarded as a promising candidate of new navigation ranging scheme.

Grid cells are important neurons related to spatial cognition and navigation in the animal brain and can respond to both external information and self-motion information. The existing models simulated these two types of responses separately, but how to simultaneously develop the two types of connection to respond to the different information has not been simulated. In this paper, first, we develop the connections from place cells to grid cells through improved nonnegative principal component analysis. Then, we construct a continuous attractor network model and an autoencoder network model of grid cell module and convert the parameter learning in the continuous attractor network into weight learning in the autoencoder network. Through parameter learning, the continuous attractor network model can spontaneously generate a hexagonal firing pattern. Ultimately, the grid cell firing fields driven by place cell inputs and self-motion information have the same spacing and direction, which means that the grid cell module can respond the same to these two types of information. This model can provide a reference for the construction of an unmanned agent brain-inspired navigation system.

A scheme of parametrically enhanced cavity electro-opto-mechanical converter is proposed in this paper, which utilizes Josephson parametric amplifier and optical parametric amplifier. Basic principles of typical cavity electro-opto-mechanical converter and parametrically enhanced version are introduced briefly. We have probed the squeezing and microwave-optical entanglement performance of the scheme with one or both of the amplifiers. The Wigner distribution of the optical output is obtained to analyze the squeezing effect. Meanwhile, quadrature variances and time domain waveforms of output signals are compared and discussed. The results show that microwave-optical entanglement has been enhanced via nonlinear parametric effects no matter when there is one or two amplifiers. However, single mode squeezing only occurs in the cavity which the amplifier is placed in, and this squeezing effect would not transmit to another cavity which hasn’t been amplified. When both amplifiers are introduced simultaneously, each output of cavity electro-opto-mechanical converter is squeezed independently. Our research provides another way to prepare squeezed microwave or optical signal and proves that microwave-optical entanglement can be well enhanced by introducing parametric amplifiers.

Pine wilt disease (PWD) is a global destructive threat to forests which has been widely spread and has caused severe tree mortality all over the world. It is important to establish an effective method for forest managers to detect the infected area in a large region. Remote sensing is a feasible tool to detect PWD, but the traditional empirical methods lack the ability to explain the signals and can hardly be extended to large scales. The studies using physically-based models either ignore the within-canopy heterogeneity or rely too much on prior knowledge. In this study, we propose an approach to retrieve PWD infected areas from medium-resolution satellite images of two phases based on the simulations of an extended stochastic radiative transfer model for forests infected by pests (SRTP). A small amount of prior knowledge was used, and a change of background soil was considered in this approach. The performance was evaluated in different study sites. The inversion method performs best in the three-dimensional model LESS simulation sample plots (R2 = 0.88, RMSE = 0.059), and the inversion accuracy decreases in the real forest sample plots. For Jiangxi masson pine stand with large coverage and serious damage, R2 = 0.57, RMSE = 0.074; and for Shandong black pine stand with sparse and a small number of single plant damage, R2 = 0.48, RMSE = 0.063. This study indicates that the SRTP model is more feasible for pest damage inversion over different regions compared with empirical methods. The stochastic radiative transfer theory provides a potential approach for future monitoring of terrestrial vegetation parameters.

Entangled microwave signal is a new quantum information resource generated in recent years. We present that entangled microwave signals can be used as the medium to realize quantum information transmission. Focusing on the divergent problem of propagation, a partial detection model based on beam splitter is established to investigate the detection efficiency and influence factors of entangled microwave signals. We analyze the relation between the entanglement degree of partial detection and detection ratio and discuss the reason that causes the reduction of entanglement degree. We give ameliorative designs of microwave signal generator and transmitter to increase the operating distance and pave the way for the application of entangled microwave signals. Keywords: Entangled microwave signals, Partial detection, Beam splitter, Entanglement degree

Abstract Background Low temperature is a major abiotic stress affecting the production of rapeseed in China by impeding plant growth and development. A comprehensive knowledge of small-RNA expression pattern in Brassica rapa under cold stress could improve our knowledge of microRNA-mediated stress responses. Results A total of 353 cold-responsive miRNAs, 84 putative novel and 269 conserved miRNAs, were identified from the leaves and roots of two winter turnip rape varieties ‘Longyou 7’ (cold-tolerant) and ‘Tianyou 4’ (cold-sensitive), which were stressed under − 4 °C for 8 h. Eight conserved (miR166h-3p-1, miR398b-3p, miR398b-3p-1, miR408d, miR156a-5p, miR396h, miR845a-1, miR166u) and two novel miRNAs (Bra-novel-miR3153-5p and Bra-novel-miR3172-5p) were differentially expressed in leaves of ‘Longyou 7’ under cold stress. Bra-novel-miR3936-5p was up-regulated in roots of ‘Longyou 7’ under cold stress. Four and five conserved miRNAs were differentially expressed in leaves and roots of ‘Tianyou 4’ after cold stress. Besides, we found two conserved miRNAs (miR319e and miR166m-2) were down-regulated in non-stressed roots of ‘Longyou 7’ compared with ‘Tianyou 4’. After cold stress, we found two and eight miRNAs were differentially expressed in leaves and roots of ‘Longyou 7’ compared with ‘Tianyou 4’. The differentially expressed miRNAs between two cultivars under cold stress include novel miRNAs and the members of the miR166 and miR319 families. A total of 211 target genes for 15 known miRNAs and two novel miRNAs were predicted by bioinformatic analysis, mainly involved in metabolic processes and stress responses. Five differentially expressed miRNAs and predicted target genes were confirmed by quantitative reverse transcription PCR, and the expressional changes of target genes were negatively correlated to differentially expressed miRNAs. Our data indicated that some candidate miRNAs (e.g., miR166e, miR319, and Bra-novel-miR3936-5p) may play important roles in plant response to cold stress. Conclusions Our work indicates that miRNA and putative target genes mediated metabolic processes and stress responses are significant to cold tolerance in B. rapa.

Sclerotinia sclerotiorum causes devastating diseases in many agriculturally important crops, including oilseed rape and sunflower. However, the mechanisms of Sclerotinia sclerotiorum pathogenesis remain poorly understood. In this study, we characterized a YML079-like cupin protein (SsYCP1) from Sclerotinia sclerotiorum. We showed that SsYCP1 is strongly expressed and secreted during Sclerotinia sclerotiorum infection. Sclerotinia sclerotiorum infection was promoted by SsYCP1 overexpression and inhibited by silencing this gene with synthetic double-stranded RNA. These results collectively indicate SsYCP1 as a putative effector protein that contributes to Sclerotinia sclerotiorum pathogenicity. These findings extend our understanding of effector-mediated Sclerotinia sclerotiorum pathogenesis and suggest a novel role for YML079-like cupin proteins in plant–pathogen interactions.

Focusing on the problem of vulnerable anti-deception and weak anti-jamming ability in classical pseudorandom code correlation ranging, we present a navigation ranging scheme with true random entangled microwave signals. One path of the entangled microwave signals uses for transmitting signal and another path of the signals preserves at locality. Firstly, the target that possesses the function of quantum repeater receives transmitting signal and forwards it to the locality. Then, correlation detection is implemented between the forwarded signal and the local delayed signal. Finally, the target distance can be calculated by delay measurement. We analyze the ranging precision and anti-deception ability. Results indicate that the scheme not only is superior to classical code correlation ranging precision, but also has very strong anti-multipath ability and anti-multipath interference ability, which will enhance the security of the navigation ranging system. Our investigation has significant application prospects.

Sclerotinia sclerotiorum is one of the most devastating pathogens in Brassica napus and causes huge economic loss worldwide. Though around one hundred putative effectors have been predicted in Sclerotinia sclerotiorum genome, their functions are largely unknown. In this study, we cloned and characterized a novel effector, SsERP1 (ethylene pathway repressor protein 1), in Sclerotinia sclerotiorum. SsERP1 is a secretory protein highly expressed at the early stages of Sclerotinia sclerotiorum infection. Ectopic overexpression of SsERP1 in plant leaves promoted Sclerotinia sclerotiorum infection, and the knockout mutants of SsERP1 showed reduced pathogenicity but retained normal mycelial growth and sclerotium formation, suggesting that SsERP1 specifically contributes to the pathogenesis of Sclerotinia sclerotiorum. Transcriptome analysis indicated that SsERP1 promotes Sclerotinia sclerotiorum infection by inhibiting plant ethylene signaling pathway. Moreover, we showed that knocking down SsERP1 by in vitro synthesized double-strand RNAs was able to effectively inhibit Sclerotinia sclerotiorum infection, which verifies the function of SsERP1 in Sclerotinia sclerotiorum pathogenesis and further suggests a potential strategy for Sclerotinia disease control.

The basic principles for preparation and detection of continuous variable polarization entanglement in quantum optics, as well as the generalized criterion of bipartite polarization entanglement, are briefly introduced. Based on theories and experiments in quantum optics, a scheme of bipartite quantum microwave polarization entanglement is proposed and simulated. Inseparability of Stokes vector as I(Ŝ1,Ŝ2) and I(Ŝ2,Ŝ3) are obtained in order to witness the polarization entanglement in 100 MHz operation bandwidth of Josephson mixer. Furthermore, relations between inseparability I and squeezing parameter r as well as amplitude ratio Q are discussed respectively. The results show that I(Ŝ1,Ŝ2) is sensitive of the variance of Q, while I(Ŝ2,Ŝ3) seems to be sensitive of the variance of r. Meanwhile, I(Ŝ1,Ŝ2) remains above 1 in the paper, while I(Ŝ2,Ŝ3) is on the contrary well below 1. It can be concluded that Ŝ2 and Ŝ3 of Stokes vectors are inseparable, which means that output signals Êa and Êb of the scheme exhibit bipartite entanglement in polarization. The best entanglement appears at 70 MHz or so with the minimum I(Ŝ2,Ŝ3) value of 0.25. Apart from these, precision of witness for polarization entanglement and quadrature entanglement is compared. Polarization entanglement appears to be easier and more precise to witness according to our research. Keywords: Quantum microwave, Bipartite polarization entanglement, Josephson mixer, Stokes vectors, Inseparability

A method for evaluating the entanglement efficiency of dual-path entangled microwaves based on second-order correlation detection is proposed in this paper. The relationship between the squeezing degree and the entanglement efficiency in the lossless case was analyzed using the second-order interference visibility as the indicator based on measurements of the signal field strength. A loss model was established to analyze the relationship between the average thermal photons, squeezing degree, and entanglement efficiency in the lossy case. The results show that in the lossless case, a larger squeezing degree leads to a lower percentage of entangled photons, giving a lower entanglement efficiency. The entanglement efficiency first increases and then decreases with the increase of the squeezing degree in the lossy case, where the maximum achievable entanglement efficiency depends on the average thermal photons. The lower number the average thermal photons, the higher the maximum achievable entanglement efficiency, and the lower the corresponding squeezing degree. The research results provide a theoretical reference to balance the entanglement degree and entanglement efficiency of industrially-prepared dual-path entangled microwaves. Keywords: Entangled microwaves, Second-order correlation detection, Entanglement efficiency

Jasmonates (JAs) regulate plant growth and defense responses. On perception of bioactive JAs, the JA receptor CORONATINE INSENSITIVE1 (COI1) recruits JA ZIM-domain (JAZ) proteins for degradation, and JAZ-targeted transcription factors are released to regulate JA responses. The subgroup IIId bHLH transcriptional factors, including bHLH17, bHLH13, bHLH3, and bHLH14, interact with JAZs and repress JA responses. In this study, we show that IIId bHLH factors form dimers via the C-terminus in yeast. N-terminus of bHLH13 is essential for its transcriptional repression function. bHLH13 overexpression inhibits Arabidopsis resistance to the necrotrophic fungi Botrytis cinerea and defense against the insect Spodoptera exigua . COI1 mutation disrupts the oversensitivity of the quadruple mutant bhlh3 bhlh13 bhlh14 bhlh17 in various JA responses, including anthocyanin accumulation, root growth inhibition, and defense against B cinerea and S exigua . Disruption of the TTG1/bHLH/MYB complex blocks anthocyanin accumulation of bhlh3 bhlh13 bhlh14 bhlh17 , whereas abolishment of MYC2 attenuates JA-inhibitory root growth of bhlh3 bhlh13 bhlh14 bhlh17 . These results genetically demonstrate that IIId bHLH factors function downstream of COI1 to inhibit distinctive JA responses via antagonizing different transcriptional activators.

In order to realize intelligent and autonomous navigation, a bio-inspired method of autonomous positioning using spatial association based on place cells firing is proposed. First, a vision sensor is used to get the landmarks in the environment and the distances between the agent and the different landmarks so as to construct an internal map of place cells. Then, we build a relationship between the distances and the activities of place cells using a radial basis function neural network, and further achieve the memory and association of spatial locations by comparing the activities of all place cells. Finally, we also provide a detailed analysis on the feasibility of this method for autonomous positioning and how the involved parameters in the model have an influence on the performance of positioning. The result of simulation shows that the method presented is effective and feasible for autonomous positioning.

Plants have evolved sophisticated systems for adaptation to their natural habitat. In response to developmental and environmental cues, plants produce and perceive jasmonate (JA) signals, which induce degradation of JASMONATE-ZIM-Domain (JAZ) proteins and derepress the JAZ-repressed transcription factors to regulate diverse aspects of defense responses and developmental processes. Here, we identified the bHLH subgroup IIId transcription factors (bHLH3, bHLH13, bHLH14 and bHLH17) as novel targets of JAZs. These bHLH subgroup IIId transcription factors act as transcription repressors and function redundantly to negatively regulate JA responses. The quadruple mutant bhlh3 bhlh13 bhlh14 bhlh17 showed severe sensitivity to JA-inhibited root growth and JA-induced anthocyanin accumulation, and exhibited obvious increase in JA-regulated plant defense against pathogen infection and insect attack. Transgenic plants overexpressing bHLH13 or bHLH17 displayed reduced JA responses. Furthermore, these bHLH factors functioned as transcription repressors to antagonize the transcription activators, such as MYC2 and the WD-repeat/bHLH/MYB complex, through binding to their target sequences. Coordinated regulation of JA responses by transcription activators and repressors would benefit plants by allowing fine regulation of defense and development, and survival in their frequently changing environment.