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Pleiotropic drug resistance (PDR) transporters, which are part of the ABCG subfamily of ATP-binding cassette (ABC) transporters, have been found to be involved in heavy metal tolerance. Salix species (willow) is widely regarded as a perfect candidate for phytoremediation of heavy metals because of its substantial biomass, strong tolerance, and remarkable capacity to accumulate heavy metals. However, the phylogeny and mechanisms underlying the response to heavy metals within the PDR family in willow have yet to be determined. In this study, we discovered and valuated a total of 21 PDR genes in the genome of Salix purpurea. The phylogenetic relationships of these genes were used to classify them into five major clades. The SpPDRs exhibited variations in exon-intron distribution patterns and gene lengths across different branches. Cis-acting elements linked to stress response, drought induction, low temperature, and defense response were discovered in the promoters of PDRs. Significant variations in the transcription levels of various PDR genes were observed across different tissues under heavy metal stress, with distinct heavy metals regulating different PDR members. In roots, PDR4 and PDR21 exhibited high expression levels. Meanwhile, PDR7 and PDR17 showed similar transcription patterns across all analyzed tissues. Furthermore, there was a significant and positive correlation between PDR5 and PDR16, whereas a significant and negative correlation was detected between PDR3 and PDR9, suggesting that the response of PDR members to heavy metals is complex and multifaceted. These findings will establish a vital basis for comprehending the biological functionalities of PDR genes, specifically their involvement in the regulation of willow's tolerance to heavy metals. [ABSTRACT FROM AUTHOR]

The leaf area index (LAI) is a crucial parameter for analyzing terrestrial ecosystem carbon cycles and global climate change. Obtaining high spatiotemporal resolution forest stand vegetation LAI products over large areas is essential for an accurate understanding of forest ecosystems. This study takes the northwestern part of the Inner Mongolia Autonomous Region (the northern section of the Greater Khingan Mountains) in northern China as the research area. It also generates the LAI time series product of the 8-day and 30 m forest stand vegetation growth period from 2013 to 2017 (from the 121st to the 305th day of each year). The Simulated Annealing-Back Propagation Neural Network (SA-BPNN) model was used to estimate LAI from Landsat8 OLI, and the multi-period GaoFen-1 WideField-View satellite images (GF-1 WFV) and the spatiotemporal adaptive reflectance fusion mode (STARFM) was used to predict high spatiotemporal resolution LAI by combining inversion LAI and Global LAnd Surface Satellite-derived vegetation LAI (GLASS LAI) products. The results showed the following: (1) The SA-BPNN estimation model has relatively high accuracy, with R2 = 0.75 and RMSE = 0.38 for the 2013 LAI estimation model, and R2 = 0.74 and RMSE = 0.17 for the 2016 LAI estimation model. (2) The fused 30 m LAI product has a good correlation with the LAI verification of the measured sample site (R2 = 0.8775) and a high similarity with the GLASS LAI product. (3) The fused 30 m LAI product has a high similarity with the GLASS LAI product, and compared with the GLASS LAI interannual trend line, it accords with the growth trend of plants in the seasons. This study provides a theoretical and technical reference for forest stand vegetation growth period LAI spatiotemporal fusion research based on high-score data, and has an important role in exploring vegetation primary productivity and carbon cycle changes in the future. [ABSTRACT FROM AUTHOR]

This article presents a systematic frequency-sweeping based method for fast and accurate determination of mutual coupling coefficient in a series–series wireless power transfer system. The novel contributions involve a sensitivity analysis to evaluate the robustness of the proposed method and an evaluation of several adaptive frequency step functions to minimize detection time with an accuracy of less than 1% error. It is found that the proposed method is the most sensitive when the frequency is swept from the lower frequency boundary in a weakly-coupled system. Several adaptive frequency step functions are evaluated and compared. A power factor reference and an adaptive frequency step function are designed in a systematic way to achieve the dual purposes of minimum detection time and high accuracy. The experimental results obtained from the hardware setups show that the mutual coupling coefficients under a range of conditions can be estimated within 7 ms and with errors typically less than 1.0%. [ABSTRACT FROM AUTHOR]

Tree species information is an important factor in forest resource surveys, and light detection and ranging (LiDAR), as a new technical tool for forest resource surveys, can quickly obtain the 3D structural information of trees. In particular, the rapid and accurate classification and identification of tree species information from individual tree point clouds using deep learning methods is a new development direction for LiDAR technology in forest applications. In this study, mobile laser scanning (MLS) data collected in the field are first pre-processed to extract individual tree point clouds. Two downsampling methods, non-uniform grid and farthest point sampling, are combined to process the point cloud data, and the obtained sample data are more conducive to the deep learning model for extracting classification features. Finally, four different types of point cloud deep learning models, including pointwise multi-layer perceptron (MLP) (PointNet, PointNet++, PointMLP), convolution-based (PointConv), graph-based (DGCNN), and attention-based (PCT) models, are used to classify and identify the individual tree point clouds of eight tree species. The results show that the classification accuracy of all models (except for PointNet) exceeded 0.90, where the PointConv model achieved the highest classification accuracy for tree species classification. The streamlined PointMLP model can still achieve high classification accuracy, while the PCT model did not achieve good accuracy in the tree species classification experiment, likely due to the small sample size. We compare the training process and final classification accuracy of the different types of point cloud deep learning models in tree species classification experiments, further demonstrating the advantages of deep learning techniques in tree species recognition and providing experimental reference for related research and technological development. [ABSTRACT FROM AUTHOR]

Forest carbon flux is critical to climate change, and the accurate modeling of forest carbon flux is an extremely challenging task. The remote sensing model (the MODIS MOD_17 gross primary productivity (GPP) model (MOD_17)) has strong practicability and is widely used around the world. The ecological process (the Biome-BioGeochemical Cycles Multilayer Soil Module model (Biome-BGCMuSo)) model can describe most of the vegetation's environmental and physiological processes on fine time scales. Nevertheless, complex parameters and calibrations pose challenges to the application and development of models. In this study, we optimized all the input parameters of the MOD_17 model for the calibration of the Biome-BGCMuSo model to obtain GPP with continuous spatiality. To determine the contribution of input parameters to the GPP of different forest types, an Extended Fourier Amplitude Sensitivity Test (EFAST) was performed on the Biome-BGCMuSo model firstly. Then, we selected the sample points of each forest type and its different ecological gradients (30 for each type), using the GPP simulation value of the optimized MOD_17 model corresponding to the time and space scale to calibrate the Biome-BGCMuSo model, to drive the calibrated Biome-BGCMuSo, and we simulated the different forest types' net primary productivity (NPP). According to dendrochronological measurements, the NPP simulation results were verified on the whole regional scale. The results showed that the GPP values of different forest types were highly sensitive to C:Nleaf (C:N of leaf), SLA1 (canopy average specific leaf area in phenological phase 1), and FLNR (fraction of leaf N in Rubisco). The coefficient of determination (R2) between the simulated forest NPP and the measured NPP was 0.64, and the root-mean-square (RMSE) was 26.55 g/C/m2/year. Our study aims to reduce uncertainty in forest carbon fluxes simulated by the Biome-BGCMuSo model, providing feedback for understanding forest ecosystem carbon cycling, vegetation productivity, and climate change. [ABSTRACT FROM AUTHOR]

To balance the phase output currents of a multiphase inverter, negatively coupled inductors (NCIs) can be used to achieve a larger differential mode (DM) loop impedance than the common mode (CM) loop impedance. For a good current sharing effect, the inductances of the NCIs should be large, leading to bulky size and cost ineffectiveness, which should be avoided in high-power applications. This article proposes a novel current balancing method based on parallel resonance. A parallel resonant network (PRN) is inserted between any two phases. With $\Delta $ -Y transform, the inductor common point and the capacitor common point are generated, either of which can be used as the CM output node. For a series–series compensated wireless power transfer system, part of the existing compensating capacitance can be employed to form PRNs with the added parallel inductors. The DM currents are suppressed by the large impedance of the PRNs. Compared with the existing method, the inductances of the NCIs can be greatly reduced to achieve better current balancing performance. The added parallel inductors are of small current ratings, which are only visible to DM currents. A prototype is implemented to validate the proposed method. [ABSTRACT FROM AUTHOR]

The model of bearings-only tracking is generally described by discrete–discrete filtering systems. Discrete robust methods are also frequently used to address measurement uncertainty problems in bearings-only tracking. The recently popular continuous–discrete filtering system considers the state model of the target to be continuous in time, and is more suitable for bearings-only tracking because of its higher mathematical solution accuracy. However, the sufficient evaluation of robust methods in continuous–discrete systems is not available. In addition, in the different continuous–discrete measurement environments, the choice of a robust algorithm also needs to be discussed. To fill this gap, this paper firstly establishes the continuous–discrete target tracking model, and then evaluates the performance of proposed robust square-root continuous–discrete cubature Kalman filter algorithms in the measurement of uncertainty problems. From the simulation results, the robust square-root continuous–discrete maximum correntropy cubature Kalman filter algorithm and the variational Bayesian square-root continuous–discrete cubature Kalman filter algorithm have better environmental adaptability, which provides a promising means for solving continuous–discrete robust problems. [ABSTRACT FROM AUTHOR]

To investigate forest resources, it is necessary to identify the tree species. However, it is a challenge to identify tree species using 3D point clouds of trees collected by light detection and ranging (LiDAR). PointNet++, a point cloud deep learning network, can effectively classify 3D objects. It is important to establish high-quality individual tree point cloud datasets when applying PointNet++ to identifying tree species. However, there are different data processing methods to produce sample datasets, and the processes are tedious. In this study, we suggest how to select the appropriate method by designing comparative experiments. We used the backpack laser scanning (BLS) system to collect point cloud data for a total of eight tree species in three regions. We explored the effect of tree height on the classification accuracy of tree species by using different point cloud normalization methods and analyzed the effect of leaf point clouds on classification accuracy by separating the leaves and wood of individual tree point clouds. Five downsampling methods were used: farthest point sampling (FPS), K-means, random, grid average sampling, and nonuniform grid sampling (NGS). Data with different sampling points were designed for the experiments. The results show that the tree height feature is unimportant when using point cloud deep learning methods for tree species classification. For data collected in a single season, the leaf point cloud has little effect on the classification accuracy. The two suitable point cloud downsampling methods we screened were FPS and NGS, and the deep learning network could provide the most accurate tree species classification when the number of individual tree point clouds was in the range of 2048–5120. Our study further illustrates that point-based end-to-end deep learning methods can be used to classify tree species and identify individual tree point clouds. Combined with the low-cost and high-efficiency BLS system, it can effectively improve the efficiency of forest resource surveys. [ABSTRACT FROM AUTHOR]

In wireless power transfer (WPT) systems, the relative position between the transmitting and receiving coils could change suddenly, which is one of the most significant distinctions between wireless and wired power transfer systems. To the best of the authors’ knowledge, no theoretical analysis has been reported on the dynamic behavior of the WPT systems under the relative position transient (RPT). This article proposes the concept of “coupling-coefficient susceptibility” to describe this dynamic behavior. The extended describing function method is applied to extract the mathematical model of the coupling-coefficient susceptibility. Finally, an RPT testing platform, composed of a series-series compensated WPT system and a coil motion mechanism is designed and fabricated to verify the theoretical analysis. The experimental results exhibit a good agreement with the proposed model. [ABSTRACT FROM AUTHOR]

Free positioning wireless charging for consumer electronics allows the devices to be charged at arbitrary positions and angles to improve user experience. However, a user-initiated sudden movement of the device during charging can cause hazards due to the abrupt variation of the coupling coefficient. To solve this issue, the coupling coefficient variation at different positions should be mitigated, which is also good for the design and high-efficiency operation of power electronics converters. This article proposes a design methodology to employ antiparallel windings to smooth the coupling coefficient variation over different positions by reducing the coupling coefficient at central positions and enhancing it at boundary positions. Two optimization methods are proposed: turn-by-turn optimization and winding-by-winding optimization. A design flow is offered. The hexagonal coil is compared with the square coil and proved to achieve better performance than the latter. An experimental prototype is implemented to validate the effectiveness of the proposed design methodology. [ABSTRACT FROM AUTHOR]

To increase the power density of a wireless power transfer (WPT) system, the coupling of coils can be strong. However, in a strongly coupled series–series WPT system with a diode rectifier, currents can be distorted and discontinuous, and first harmonic approximation is no longer valid. The inverter is likely to work in hard switching, leading to extra noise, decreased efficiency, and a potential hazard for a safe operation. Through time-domain analysis, this article reveals that with a dual-side 90° phase shift, the hard switching of the inverter can be avoided, the power level can be enhanced, and the discontinuous conduction mode can be avoided to eliminate noises. The factors impacting the soft switching operations of the inverter and the rectifier are analyzed. To achieve 90° dual-side phase shift, the conventional approach of using the receiver voltage/current, which can be distorted and discontinuous in strongly coupled WPT systems, for phase synchronization is no longer suitable. A new set of coils, namely driving coils, is used for phase synchronization so that dual-side phase shift can be implemented independent from power transfer. Experimental results have validated the effectiveness of the analysis. [ABSTRACT FROM AUTHOR]

Duty-cycle control is a widely used control method of resonant converters. In this article, the existing model of duty-cycle controlled resonant converters is found to have discrepancy compared with the simulation and experimental results. The reason behind is investigated, showing the phase change in the output voltage of the inverter bridge caused by the duty-cycle perturbation was ignored in the existing model. The phase change law is highly dependent on the duty-cycle scheme used, which is further determined by the forms of the carriers and the switching sequences of the resonant converters. With this consideration, improved models of both full-bridge and half-bridge resonant converters with different duty-cycle control schemes are rederived. It is revealed that different duty-cycle control schemes lead to different phase curves of the duty-cycle-to-output-voltage transfer functions, therefore care should be taken when selecting the appropriate duty-cycle control scheme. In the end, a series-series compensated wireless power transfer system is built to verify the validity of the proposed models. [ABSTRACT FROM AUTHOR]

The extended describing function (EDF) method is widely used in modeling the resonant converters. This article finds that the model of the phase-shift controlled resonant converter deduced by this method might be inaccurate especially when the duty-cycle is close to 1. The reason behind it is investigated, showing that derivation of the inverter bridge model based on its fundamental harmonic will cause error. A novel model of the inverter bridge by Fourier analysis is proposed. Incorporating the novel model into the EDF-based resonant model, the accuracy of the phase-shift controlled resonant converter is greatly improved. A series–series compensated inductive power transfer system is fabricated in the lab to verify the validity of the proposed model. [ABSTRACT FROM AUTHOR]

The isolated feature between primary and secondary sides in wireless power transfer requires dual-side communication, phase synchronization, and two controllers on both sides. The phase difference between dual-side ac voltages can be changed for output regulation or bidirectional power flow. Zero crossing detection of the secondary ac voltage or current is normally conducted for frequency locking and phase synchronization. However, it is inaccurate at light-load conditions for high-power applications due to a large sensing scale and much noise; also, it can generate undesired results with discontinuous or distorted waveforms having more than two zero crossing points in one cycle. To solve these issues, this letter proposes a dual-side phase-shift implementation method using driving windings to regulate the dual-side phase difference conducted only on the primary side. By controlling the phase difference between the primary-side power and driving windings, the phase difference between the dual-side power windings can be regulated. In this way, the dual-side regulation is independent from power transfer to get rid of the issues of the conventional phase synchronization method, and bidirectional power flow can be more easily realized. [ABSTRACT FROM AUTHOR]

The closed-loop control of wireless power transfer (WPT) systems requires a communication link between the power transmitter and the power receiver for dual-side cooperation. Near-field communication techniques that utilize the power link are preferred for this purpose due to high reliability and security. In this letter, we propose a frequency-modulated phase shift keying (FMPSK) communication technique for the closed-loop maximum efficiency point tracking (MEPT) control of WPT. The technique uses very shallow phase modulation depth to minimize the disturbance on power flow and reduce the efficiency drop caused by the PSK. Meanwhile, it ensures the signal accuracy and precision by multiple methods and precise frequency modulation and demodulation. In experiment, we obtained 82%–85% system efficiency with a 25–125 W load over a distance equal to the coil diameter, and 93% efficiency over a distance equal to the coil radius. The efficiency drop caused by FMPSK was less than 1%. The dynamic processes of voltage regulation and MEPT took only about 1 ms and 10 ms, respectively. [ABSTRACT FROM AUTHOR]

A wide operating region of inductive power transfer systems indicates a stable output against large load and coupling changes. In most of the published works, output regulation is achieved by single-side regulation that utilizes either primary-side or secondary-side power converters for load regulation. However, secondary-side regulation tends to have a relatively narrow operating region due to space and cost considerations. Meanwhile, although primary-side regulation may provide a larger operating region, system performance can be degraded due to the needs of secondary-side information. To overcome the drawbacks of single-side regulation, this article proposes a dual-side cooperative output regulation method implemented by burst-mode pulse density modulation. In the proposed method, dual-side cooperative control is established by sensing primary-side current drops caused by secondary-side burst operations and, hence, requires no communication devices. With the proposed method, the system operating region can be effectively extended without sacrificing steady-state performance. Experimental results are provided in this article to validate the proposed method. [ABSTRACT FROM AUTHOR]

In inductive power transfer systems, impedance matching is critical in obtaining high efficiency. However, since the load impedance is subject to variations in most applications, especially wireless charging, maintaining impedance matching is a challenge. One valid solution is to maintain the equivalent load impedance at the optimal value against load variations by controlling a load-side power converter. Nonetheless, the system overall cost, size, and complexity can be increased. In this article, based on a proper selection between full-bridge and half-bridge modes of the inverter and rectifier, an operation mode selection method is proposed that can achieve semi-impedance-matching with large load variations. In general, with the proposed method, high overall efficiency can be obtained while neither additional power converters nor complicated control is required. A 1-kW prototype has been developed and the experimental results have verified the proposed method. [ABSTRACT FROM AUTHOR]

Load-independent output characteristics of inductive power transfer (IPT) systems are increasingly popular in battery charging. This paper proposes a novel variable-parameter T-circuit (VT) for an IPT system charging a battery with constant current (CC) or constant voltage (CV) output. The VT can transfer a CC/CV input to a CC or CV output by using an ac switch and a passive component (inductor or capacitor). An IPT system with a VT for CC–CV charging can reduce the number of passive components and ac switches. Besides, the proposed VT merits more design freedom of charge current/voltage with the constraints imposed by the loosely coupled transformer parameters compared to that of the traditional one. In addition, there are three kinds of VTs for various IPT charging systems with different requirements. A 400 W laboratory-scale prototype with a 150 mm air gap was built to verify the theoretical analyses. Both electronic load and lead-acid battery are utilized to verify the charging profile of the proposed method. The experimental results of the IPT system indicate that the fluctuation of the charging current in CC mode is less than 2%, and the change rate of charging voltage in CV mode is within 2.9%. The maximum overall efficiency 93.93% of the charging system is achieved from a dc 110 V input to a dc 100 V output. [ABSTRACT FROM AUTHOR]

The pulse-density-modulation (PDM) zero-voltage-switching (ZVS) full-bridge converter is a promising power converter for wireless power transfer (WPT) systems. The converter has the advantages of both direct conversion ratio control and load-independent soft switching. These advantages reduce the overall system complexity and power loss. However, the converter suffers from the limitations of large low-frequency subharmonics, a narrowed modulation range, and a large modulation delay. These limitations are caused by the existing PDM strategy, which was designed to generate a symmetric ZVS current to ensure the ideal ZVS for minimizing the switching loss. This paper finds that even with an asymmetric ZVS current, the ideal ZVS can still be ensured by the negative feedback effect of the dead-time voltage. Based on this finding, a PDM strategy that allows asymmetric ZVS currents is proposed to overcome the aforementioned limitations. In experiments, a ZVS full-bridge converter was modulated by the existing and the proposed PDM strategies, respectively. The converter performances and responses were compared and the results showed that the proposed PDM strategy can overcome the limitations while achieving ZVS. The proposed PDM strategy was also tested in a WPT system for verification. [ABSTRACT FROM AUTHOR]

The optimal maneuver of observer for bearing-only tracking (BOT) in a threat environment is a complex problem which involves nonlinear filtering, threat avoidance, and optimal maneuver strategy. Under comprehensive consideration, the reward function comprised of the lower bound on detFIM and threat cost was established; the finite-horizon MDP principle was applied to obtain the optimal strategy. The quantization method was used to discretize the BOT process and calculate the transition matrix of Markov chain; to achieve quantization in the beginning of each period, CKF was applied to provide the initial state estimate and the corresponding error covariance. The numerical simulations illustrated the applicability and superior performance for static and dynamic target tracking in several scenarios in the threat environment. [ABSTRACT FROM AUTHOR]

Maximum efficiency point tracking (MEPT) control has been adopted in state-of-the-art wireless power transfer (WPT) systems to meet the power demands with the highest efficiency against coupling and load variations. Conventional MEPT implementations use dc/dc converters on both transmitting and receiving sides to regulate the output voltage and maximize the system efficiency at the expense of increased overall complexity and power losses on the dc/dc converters. Other implementations use phase-shift control or on–off control of the transmitting side inverter and the receiving side active rectifier instead of dc/dc converters but cause new problems, e.g., hard switching, low average efficiency, and large dc voltage ripples. This paper proposes a pulse density modulation (PDM) based implementation for MEPT to eliminate all the mentioned disadvantages of existing implementations. Delta-sigma modulators are used as an example to realize the PDM. A dual-side soft switching technique is proposed for the PDM. The ripple factor of the output voltage with PDM is derived. A 50 W WPT system is built to validate the proposed method. The system efficiency is maintained higher than 70% for various load resistances when the power transfer distance is 0.5 m, which is 1.67 times the diameter of the coils. [ABSTRACT FROM AUTHOR]

To further improve the filtering accuracy in nonlinear estimation systems, a nonlinear filter, called the orthogonal simplex Chebyshev-Laguerre cubature Kalman filter (OSCL-CKF), is proposed. The filter is built within the cubature Kalman filter framework, which transforms the multidimensional, Gaussian weighted integral into a spherical-radial coordinate system. In the spherical integral, an orthogonal method is introduced to the third-degree spherical simplex rule, and then the nonlocal sampling effects can be reduced by tuning the high order interference terms. In the radial integral, the quadrature points and corresponding weights are determined according to the Chebyshev-Laguerre (CL) equation, which enables the nonlinear filter to improve the precision by the order of the CL polynomial. Numerical results show that the proposed filter outperforms the conventional algorithms. [ABSTRACT FROM AUTHOR]

Background: In our previous study, mouse double minute 2 homolog (MDM2), insulin-like growth factor 1 (IGF1), signal transducer and activator of transcription 1 (STAT1), and Rac family small GTPase 1 (RAC1) were correlated with the recurrence of giant cell tumor of bone (GCT). The aim of this study is to use a large cohort study to confirm the involvement of these four genes in GCT recurrence.Methods: The expression of these four genes was detected and compared between GCT patients with or without recurrence. The correlation between the expression of these four genes and clinical characteristics was evaluated. Protein-protein interaction (PPI) network was constructed for functional enrichment analysis.Results: It showed that the expression levels of MDM2, IGF1, STAT1, and RAC1 in GCT patients with recurrence were significantly higher than those in GCT patients without recurrence (P < 0.05). Multivariate logistic regression analysis suggested that several clinical characteristics may influence prognosis. A PPI network was constructed using the four genes as hub genes. Functional enrichment analysis showed that this network involves many important biological progress mediated by these four genes, including immune response.Conclusion: MDM2, IGF1, STAT1, and RAC1 are associated with GCT recurrence, which might serve as biomarkers for GCT recurrence. [ABSTRACT FROM AUTHOR]

An experimental study was conducted to investigate the impact of cyclic loading on the mechanical performance and chloride diffusivity of RC beams exposed to seawater wet-dry cycles. To induce initial damage to RC beam specimen, cyclic loading controlled by max load and cycles was applied. Then beam specimens underwent 240 wet-dry cycles of seawater. Results show that the chloride content increased as max load and cycle increased. The chloride content at steel surface increased approximatively linearly as average crack width increased. Moreover, the max load had more influence on chloride content at steel surface than cycle. The difference of average chloride diffusion coefficient between tension and compression concrete was little at uncracked position. Average chloride diffusion coefficient increased as crack width increased when crack width was less than 0.11 mm whereas the increasing tendency was weak when crack width exceeded 0.11 mm. The residual yield load and ultimate load of RC beams decreased as max load and cycle increased. Based on univariate analysis of variance, the max load had more adverse effect on yield load and ultimate load than cycle. [ABSTRACT FROM AUTHOR]

In this study, a non‐linear filter named the range‐parameterised orthogonal simplex cubature Kalman filter (RPOSCKF) is proposed to further improve the accuracy of bearings‐only tracking. The filter combines the simplex spherical radial numerical rule with an orthogonal method, and thus the standard cubature points are transformed into the orthogonal simplex cubature points (OSCPs). It is proved that the filter using the OSCPs can tune the high order terms of the highly non‐linear measurement function and therefore alleviate problems due to the non‐local sampling effects. On the other hand, the fuzzy initial estimation problem is handled by an improved range‐parameterised (IRP) strategy. The IRP strategy divides the filter into some weighted orthogonal simplex CKFs each with different initial estimate, where the initial weights are based on the length of the estimate interval. Also, the sub‐filters with small updated weights will be removed and the computational complexity can be reduced. Simulations show that the proposed algorithm provides improved performance over the conventional algorithms. [ABSTRACT FROM AUTHOR]

A new method for the determination of oxytetracycline (OTC) has been established by coupling the catalytic amplification reaction of copper nanoclusters (CuNCs) with the aptamer reaction. CuNCs prepared by a wet chemical method have the catalytic activity for the formation of gold nanoparticles (AuNPs) resulting from a HAuCl4-ethanol (En) reaction. The experimental results showed that OTC aptamer (Apt) can be adsorbed on the surface of CuNCs in a non-specific way, thus inhibiting its catalytic activity. When OTC was added to the solution, the OTC-Apt complex was generated by a specific reaction, which made the CuNCs desorb and restore their catalytic activity. With the increase of OTC, the recovery of the catalytic activity of CuNCs is strengthened, the reaction speed is accelerated, and the number of AuNPs is increased. The generated AuNPs exhibited surface enhanced Raman scattering (SERS) signals at 1615 cm−1 in the presence of Vitoria blue 4R (VB4R) molecular probes, and a resonance Rayleigh scattering (RRS) peak at 586 nm. There is a good linear relationship between the intensities of SERS, or RRS, and OTC concentration at the range of 37.5–300 ng/L or 37.5–225 ng/L, respectively. A new SERS and RRS assay for the determination of trace OTC based on the regulation of CuNCs catalysis was established. [ABSTRACT FROM AUTHOR]

Bearings-only tracking only adopts measurements from angle sensors to realize target tracking, thus, the accuracy of the state prediction has a significant influence on the final results of filtering. There exist unpredictable approximation errors in the process of filtering due to state propagation, discretization, linearization or other adverse effects. The idea of online covariance adaption is proposed in this work, where the post covariance information is proved to be effective for the covariance adaption. With theoretical deduction, the relationship between the posterior covariance and the priori covariance is investigated; the priori covariance is modified online based on the feedback rule of covariance updating. The general framework integrates the continuous-discrete cubature Kalman filtering and the feedback rule of covariance updating. Numerical results illustrated that the proposed method has advantages over decreasing unpredictable errors and improving the computational accuracy and efficiency. [ABSTRACT FROM AUTHOR]

The gut microbiota and their metabolites are closely linked to obesity-related diseases, such as type 2 diabetes, but their causal relationship and underlying mechanisms remain largely elusive. Here, we found that dysbiosis-induced tyramine (TA) suppresses high-fat diet (HFD)-mediated insulin resistance in both Drosophila and mice. In Drosophila, HFD increases cytosolic Ca2+ signaling in enterocytes, which, in turn, suppresses intestinal lipid levels. 16 S rRNA sequencing and metabolomics revealed that HFD leads to increased prevalence of tyrosine decarboxylase (Tdc)-expressing bacteria and resulting tyramine production. Tyramine acts on the tyramine receptor, TyrR1, to promote cytosolic Ca2+ signaling and activation of the CRTC-CREB complex to transcriptionally suppress dietary lipid digestion and lipogenesis in enterocytes, while promoting mitochondrial biogenesis. Furthermore, the tyramine-induced cytosolic Ca2+ signaling is sufficient to suppress HFD-induced obesity and insulin resistance in Drosophila. In mice, tyramine intake also improves glucose tolerance and insulin sensitivity under HFD. These results indicate that dysbiosis-induced tyramine suppresses insulin resistance in both flies and mice under HFD, suggesting a potential therapeutic strategy for related metabolic disorders, such as diabetes. [ABSTRACT FROM AUTHOR]

Highlights: [•] We synthesized a group of newly designed phenanthrene-bridged photochromic diarylethenes. [•] We examined their absorption and fluorescence changes in various solvents. [•] Single crystal X-ray diffraction analysis was carried out to determine the structure of one diarylethene derivative. [•] We found their fluorescent non-destructive readout capability. [•] DFT theoretical calculation results indicated the photocyclization of open forms was carried out at the second excited. [ABSTRACT FROM AUTHOR]

The determination of heavy metal ions has always been a hot topic in the field of environmental analysis. In this study, a new covalent organic framework-loaded gold nanoparticle (AuCOF) nanocatalytic amplification signal strategy was developed to determine trace Co 2+ in water. The COF of BtPD was synthesized from 1,3,5-benzene tricarboxaldehyde and p -phenylenediamine, and a new kind of AuBtPD nanosol was prepared by reduction of HAuCl 4 to AuNPs on the BtPD carrier. It has strong catalysis of the new indicator reaction of sodium formate reducing HAuCl 4 to AuNP sol with strong resonance Rayleigh scattering (RRS) at 370 nm and surface enhanced resonance Raman scattering (SERS) activity at 1614 cm -1 in the presence of a Victoria blue 4R (VB4R) molecular probe. Combining the nanocatalytic reaction to amplify the dual-scattering signals and specific aptamer (Apt) of cobalt ions, a new, fast, stable, sensitive and specific dual mode method for detecting Co 2+ was established; the RRS signal I 370nm and SERS signal I 1614cm -1 show a linear relationship with the concentration of 0.033-1 nmol L -1 Co 2+ and with a limit of detection (LOD) of 0.02 nmol L -1 . The two methods have been applied to the determination of Co 2+ in industrial wastewater, tap water and river water, and the results are satisfactory., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

In multi-target tracking, the outliers-corrupted process and measurement noises can reduce the performance of the probability hypothesis density (PHD) filter severely. To solve the problem, this paper proposed a novel PHD filter, called Student's t mixture PHD (STM-PHD) filter. The proposed filter models the heavy-tailed process noise and measurement noise as a Student's t distribution as well as approximates the multi-target intensity as a mixture of Student's t components to be propagated in time. Then, a closed PHD recursion is obtained based on Student's t approximation. Our approach can make full use of the heavy-tailed characteristic of a Student's t distribution to handle the situations with heavy-tailed process and the measurement noises. The simulation results verify that the proposed filter can overcome the negative effect generated by outliers and maintain a good tracking accuracy in the simultaneous presence of process and measurement outliers., Competing Interests: The authors declare no conflict of interest.

The direction of arrival (DOA) tracking problem based on an angle sensor is an important topic in many fields. In this paper, a nonlinear filter named the feedback M-estimation based robust cubature Kalman filter (FMR-CKF) is proposed to deal with measurement outliers from the angle sensor. The filter designs a new equivalent weight function with the Mahalanobis distance to combine the cubature Kalman filter (CKF) with the M-estimation method. Moreover, by embedding a feedback strategy which consists of a splitting and merging procedure, the proper sub-filter (the standard CKF or the robust CKF) can be chosen in each time index. Hence, the probability of the outliers' misjudgment can be reduced. Numerical experiments show that the FMR-CKF performs better than the CKF and conventional robust filters in terms of accuracy and robustness with good computational efficiency. Additionally, the filter can be extended to the nonlinear applications using other types of sensors.