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Perovskite quantum dots (PeQDs) are seen as the credible alternative to traditional QDs ascolor converter in liquid crystal display (LCD). Unfortunately, PeQDs sufferfrom instability and color separation, and the prepared PeQDs enhanced films(PQDFs) need the protection of expensive barrier layers, which significantly increases price and limits their application. Herein, large‐area yellow monolithic PQDF is fabricated with both green CsPbBr3 and red CsPbBr1I2QDs encapsulated in the dual matrices of inorganic glass and polypropylene (PP) via an industrialized melt extruding & rolling method. The PQDF shows high photoluminescence quantum yield (PLQY) of 92% and narrow full width at half maximum (FWHM) of 19 nm (green) and 33 nm (red). Importantly, the bare PQDF without barrier layers can pass harsh aging test at 85 °C/85% RH and reach anoperating T90 lifetime over 1000 h. Finally, a white backlit unit is designed by coupling yellow monolithic PQDF with blue light guide panel, and the constructed prototype display shows superior color rendering performance forits narrow green/red emissions, reaching a color gamut of 110% National Television System Committee (NTSC). This work provides a novel and easy‐to‐industrialize route to prepare PQDFs to realize their commercial application in backlit display. [ABSTRACT FROM AUTHOR]

Malachite green (MG) is highly toxic, persistent, and carcinogenic, and its widespread use is a danger to the ecosystem and a threat to public health and food safety, making it necessary to develop new sensitive multimode molecular spectroscopy methods. In this work, a new copper-based nanomaterial (CuNM) was prepared by a high-temperature roasting using a copper metal–organic framework (CuMOF) as precursor. The as-prepared CuNM was characterized using X-ray diffraction (XRD), X-ray photoelectron spectroscopy, transmission electron microscopy (TEM), and BET surface area analysis. CuNM was found to catalyze the oxidation of 3,3′,5,5′-tetramethylbenzidine (TMB) by H2O2 to produce the oxidation product TMBOX; however, subsequently, the MG aptamer (Apt) could be adsorbed on the CuNM surface by intermolecular interaction, which would inhibit the catalytic performance. After the addition of MG to be tested, the CuNM previously adsorbed by the Apt was transformed into its free state, thus restoring its catalytic activity. This new nanocatalytic indicator reaction could be monitored by surface-enhanced Raman scattering (SERS)/resonance Rayleigh scattering (RRS)/fluorescence (FL)/absorption (Abs) quadruple-mode methods. The SERS determination range was 0.004–0.4 nmol L−1 MG, with a limit of detection of 0.0032 nM. In this way, a rapid, stable, and sensitive method for the determination of MG residues in the environment was established. [ABSTRACT FROM AUTHOR]

Robust amorphous glass protected CsPbBr3 (CsPbBr3@glass) perovskite quantum dots (PeQDs) with ultra‐pure green emission and superior long‐term stability are highly desirable for developing wide‐color‐gamut liquid crystal displays. However, most of the reported CsPbBr3@glass nanocomposites are subject to low external quantum efficiency (EQE). This work demonstrates that ZrO2 additive has an "accumulation" effect on the borosilicate glass network structure to promote in situ nucleation/growth of PeQDs inside glass rather than self‐crystallization. This effect is beneficial in reducing surface defects, improving the quality of PeQDs, and thus boosting radiative recombination of excitons. As a consequence, the as‐prepared CsPbBr3@glass shows a record EQE of up to 75% and can pass the accelerated aging tests at 85 °C/85% RH for 1000 h and blue light irradiation over 2000 h. Finally, a prototype display using CsPbBr3@glass‐based straight‐down backlit unit is designed and gains more favorable responses in blind selection tests for its high brightness of 2647 cd m−2 and high color purity of 88%. The findings will pave the way for realizing the commercial application of CsPbBr3@glass nanocomposite in PeQDs‐converted backlit display. [ABSTRACT FROM AUTHOR]

Introduction: Primary brainstem hemorrhage (PBSH) is the most fatal subtype of intracerebral hemorrhage and is associated with poor prognosis. We aimed to develop a prediction model for predicting 30-day mortality and functional outcome in patients with PBSH. Methods: We reviewed records of 642 consecutive patients with first-time PBSH from three hospitals between 2016 and 2021. Multivariate logistic regression was used to establish a nomogram in a training cohort. Cutoff points of the variables were determined by receiver operating characteristic curve analysis, and certain points were assigned to these predictors to produce the PBSH score. The nomogram and PBSH score were compared with other scoring systems for PBSH. Results: Five independent predictors, comprised of temperature, pupillary light reflex, platelet-to-lymphocyte ratio, Glasgow Coma Scale (GCS) score on admission, and hematoma volume, were incorporated to construct the nomogram. The PBSH score consisted of 4 independent factors with individual points assigned as follows: temperature, ≥38°C (=1 point), <38°C (=0 points); pupillary light reflex, absence (=1 point), presence (=0 points); GCS score 3–4 (=2 points), 5–11 (=1 point), and 12–15 (=0 points); PBSH volume >10 mL (=2 points), 5–10 mL (=1 point), and <5 mL (=0 points). Results showed that the nomogram was discriminative in predicting both 30-day mortality (area under the ROC curve [AUC] of 0.924 in the training cohort, and 0.931 in the validation cohort) and 30-day functional outcome (AUC of 0.887). The PBSH score was discriminative in predicting both 30-day mortality (AUC of 0.923 in the training cohort and 0.923 in the validation cohort) and 30-day functional outcome (AUC of 0.887). The prediction performances of the nomogram and the PBSH score were superior to the intracranial hemorrhage (ICH) score, primary pontine hemorrhage (PPH) score, and new PPH score. Conclusions: We developed and validated two prediction models for 30-day mortality and functional outcome in patients with PBSH. The nomogram and PBSH score could predict 30-day mortality and functional outcome in PBSH patients. [ABSTRACT FROM AUTHOR]

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]

Deep neural network (DNN) models have been widely used in many tasks due to their superior performance. However, DNN models are usually vulnerable to adversarial example attacks, which limits their applications in many safety-critic scenarios. How to effectively detect adversarial examples to enhance the robustness of DNN models has attracted much attention in recent years. Most adversarial example detection methods require modifying or retraining the model, which is impractical and reduces the classification accuracy of normal examples. In this paper, we propose an adversarial example detection approach that does not require modification of the DNN models and meanwhile retains the classification accuracy of normal examples. The key observation is that when we transform the input example with some operations (e.g., masking a pixel with a reference value), feed the transformed example to the target model, and use the output of the intermediate layers to predict the label of the example, the generated label sequences of adversarial examples will be extremely discrepant but the label sequences of normal examples keep nearly unchanged. Motivated by this observation, we design an approach to detect adversarial examples based on the label sequence discrepancy (LSD) of the given examples. The experimental results against five mainstream adversarial attacks on three benchmark datasets demonstrate that LSD outperforms the state-of-the-art solutions in the detection rate of adversarial examples. Moreover, LSD performs well at various confidence levels and exhibits good generalizability between different attacks. [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]

High‐quality backlit display puts forward urgent demand for color‐converting materials. Recently, metal halide perovskites (MHPs) with full spectral tunability, high photoluminescence quantum yields (PLQYs), and high color purity have found potential application in wide‐color‐gamut display. Regrettably, naked MHPs suffer from long‐term instable issue and cannot pass harsh stability tests. Herein, amorphous‐glass‐protected green/red CsPbX3 quantum dots (QDs) are prepared by elaborately optimizing glass structure, perovskite concentration, and in situ crystallization. PLQYs of green CsPbBr3@glass and red CsPbBr1.5I1.5@glass reach 94% and 78%, respectively, which are the highest ones of CsPbX3@glass composites reported so far and comparable to colloidal counterparts. Benefited from complete isolation of QDs from external environment by glass network, CsPbX3@glass can endure harsh commercial standard aging tests of 85 °C/85%RH and blue‐light‐irradiation, which are applied to construct white light‐emitting diodes (wLEDs) with high external quantum efficiency of 13.8% and ultra‐high luminance of 500 000 cd m−2. Accordingly, the perovskite wLED arrays‐based backlit unit and a prototype display device are designed for the first time, showing more vivid and wide‐color‐gamut feature benefited from narrowband emissions of CsPbX3 QDs. This work highlights practical application of CsPbX3@glass composite as an efficient and stable light color converter in backlit display. [ABSTRACT FROM AUTHOR]

For an inductive power transfer (IPT) system, mobility is one of the most attractive features, but coupling variations can dramatically affect the system's output. In this article, a reconfigurable rectifier-based detuned series-series (SS) compensated IPT system is proposed to tolerate an extensive coupling range and improve the system efficiency simultaneously. The reconfigurable rectifier, which can operate in a full-bridge rectifier mode or a half-bridge rectifier mode, is used to alter the equivalent ac load from one value to the other so the expected coupling range of the detuned SS topology can be extended. At the same time, the system efficiency is also partly improved because the ac load is changed to get closer to the optimal load of the IPT system. First, a detuned SS IPT system with the reconfigurable rectifier is presented and followed by the analysis of the working modes. Then, a detailed parameter design process and switching control of the reconfigurable rectifier are introduced. Finally, a 400-W prototype was constructed to verify the validity of the proposed method. The experimental results demonstrate that the output power fluctuation of the proposed IPT system is less than 17.5% and the lowest efficiency can be improved from 68.6% to 87.5% with the coupling coefficient varying from 0.1 to 0.4. The proposed method can implement significant antimisalignment and efficiency improvement simultaneously, and it is regarded as a potential solution for low-power IPT applications with high spatial mobility. [ABSTRACT FROM AUTHOR]

Laser‐driven projection display puts forward urgent demand for color converter materials to achieve wide‐color‐gamut and high‐quality image presentation. In this study, a hierarchical structure quantum dots‐in‐glass film (QiGF) is fabricated via co‐sintering stable green/red‐emitting CsPbX3@glass (X3 = Br3, Br1.5I1.5) and commercial low‐melting glass on the sapphire substrate. Benefiting from the well‐retained optical properties of CsPbX3 quantum dots in amorphous glass and high thermal conductivity, QiGF succeeded in inhibiting luminescence saturation after 20 W mm−2 blue laser irradiation. A brand‐new white‐lighting source designed by coupling a blue laser with a pattern "QiGF wheel" produced ultra‐narrow blue/green/red tri‐color emissions and total luminous flux of 146 lm. Accordingly, a QiGF‐converted laser projection system is successfully designed for the first time, showing more natural and real color restoration for its wide color gamut display feature (157% of conventional light‐emitting diode projection and 107% of NTSC standard). The present study highlights the practical application of CsPbX3 quantum dots composite as an efficient laser‐driven color converter in projection display. [ABSTRACT FROM AUTHOR]

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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]

Perovskite quantum dots are considered to be one of the most promising materials for next-generation backlight displays due to their narrow emission width, high color purity and tunable luminescence. However, the deterioration and failure of perovskite quantum dots under stimulation from the external environment (e.g., light, heat, and humid air) limit their practical applications. Herein, CsPbBr3@glass with excellent stability and optical properties was successfully prepared by optimizing the quantum dot nucleation/growth conditions. The CsPbBr3@glass@PDMS hierarchical structure film with a full width at half maximum of ∼17 nm and photoluminescence quantum yield of ∼80% was obtained via the physical dilution method to eliminate the internal filtering effect. Benefiting from the dual protection of the inorganic glass network and PDMS polymer matrix, the film exhibited excellent water/heat resistance. As an application demonstration, a white LED backlit unit was designed by coupling a CsPbBr3@glass@PDMS green film and Mn4+:K2SiF6 red film with a home-made blue light guide panel, endowing the LCD with a wide color gamut (a color gamut of 159% for commercial LCD, 108% for NTSC, and 81% for Rec. 2020), confirming its great potential in the display industry. [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]

According to the characteristics of ploughing extrusion forming and the theory of metal cutting, the wear and damage mechanism, common wear and damage forms and causes of multi-tooth tools in ploughing extrusion forming are analyzed. Then, the correctness of the analysis of tool wear and damage mechanism and common wear and damage forms is verified by field cutting experiments. At the same time, the phenomena and causes of workpiece stagnation and cracks in the process of ploughing and extrusion forming were obtained through experiments. Finally, the reasonable processing parameters of ploughing and extrusion forming multi-tooth cutting tool were obtained. [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]

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]

Halogen‐mixed CsPb(Br/I)3 perovskite quantum dots (PeQDs) embedded glass can address the issue of stability, but suffers from low photoluminescence quantum yields (PLQYs) for the hindered in situ nucleation/growth inside the robust glass network. Uncovering the exact mechanism is highly desirable to develop high‐performance CsPb(Br/I)3@glass for commercial applications, but the topic remains unexplored. Here, based on femtosecond transient (fs‐TA) absorption, temperature‐dependent PL spectra, and theoretical calculations, a comprehensive understanding on heat‐treatment (HT) temperature‐induced modification of microstructures and carrier dynamics in the CsPb(Br/I)3@glass is build. It is evidenced that high‐temperature HT will promote more I− ions diffusion from glass matrix into CsPb(Br/I)3 lattice, leading to the retarded hot carrier (HC) cooling, and improved exciton recombination. This is attributed to the synergistic effect of the reduced effect carrier mass, the weakened carrier‐phonon coupling, the inhibited Klemens channel, and the eliminated defect states. Revealing these underlying mechanisms will empower to exert precise control and optimize PLQY of CsPb(Br/I)3@glass up to near unity. [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]

Background: Coronary perfusion pressure (CPP) indicates spontaneous return of circulation and is recommended for high-quality cardiopulmonary resuscitation (CPR). This study aimed to investigate a method for non-invasive estimation of CPP using electrocardiography (ECG) and photoplethysmography (PPG) during CPR., Methods: Nine pigs were used in this study. ECG, PPG, invasive arterial blood pressure (ABP), and right atrial pressure (RAP) signals were simultaneously recorded. The CPPs were estimated using three datasets: (a) ECG, (b) PPG, and (c) ECG and PPG, and were compared with invasively measured CPPs. Four machine-learning algorithms, namely support vector regression, random forest (RF), K-nearest neighbor, and gradient-boosted regression tree, were used for estimation of CPP., Results: The RF model with a combined ECG and PPG dataset achieved better estimation of CPP than the other algorithms. Specifically, the mean absolute error was 4.49 mmHg, the root mean square error was 6.15 mm Hg, and the adjusted R 2 was 0.75. A strong correlation was found between the non-invasive estimation and invasive measurement of CPP (r = 0.88), which supported our hypothesis that machine-learning-based analysis of ECG and PPG parameters can provide a non-invasive estimation of CPP for CPR., Conclusions: This study proposes a novel estimation of CPP using ECG and PPG with machine-learning-based algorithms. Non-invasively estimated CPP showed a high correlation with invasively measured CPP and may serve as an easy-to-use physiological indicator for high-quality CPR treatment., Competing Interests: Declaration of competing interest None of the authors have any financial or personal relationship with other people or organizations that could inappropriately influence (bias) this work., (Copyright © 2024 Elsevier B.V. All rights reserved.)

We herein report the nickel-catalyzed enantioselective hydrofluoromethylation of enamides and enol esters with CH 2 FI as the fluoromethyl source to enable the diversity-oriented synthesis (DOS) of chiral α-fluoromethylated amides as well as esters with features of wide functional group compatibility as well as excellent enantioselectivity. The synthetic value of this protocol was demonstrated by transformations of the resulted α-fluoromethylated amides to different scaffolds including amine, oxazoline, thiazoline, and α-fluoromethylated tetrahydroquinoline.

Herein we report the first versatile and expeditious method for the site-selective C-H fluoromethylation of aryl iodides via Pd/norbornene cooperative catalysis, which could work as a robust toolbox for the diversity-oriented synthesis (DOS) of fluoromethylated arenes. This methodology features the use of the low-cost industrial raw material CH 2 IF as the fluoromethyl source, an excellent functional group tolerance, and a broad ipso termination scope and can be expanded to the late-stage modification of biorelevant molecules.