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To address the problem that the performance of the detector in airborne magnetic anomaly detection (MAD) is terrible, a stochastic resonance (SR) detection algorithm based on orthonormalized basis function (OBF-SR) is proposed for MAD under low signal-to-noise ratio conditions. The signal contaminated by noise is first preprocessed by the OBF method, where the sum of the three components in the OBF space is selected as the SR system input. Then, a parallel SR system with different initial states is designed to detect the signal. Finally, the simulation analysis of MAD methods is performed to draw a comparison between the OBF-SR method, the typical SR method, and the OBF method. The results show that the OBF-SR method outperforms the SR and OBF methods in the detection probability and detection range under the same conditions. [ABSTRACT FROM AUTHOR]

• Performance of object detection tends to degrade on low-quality images. • Choosing suitable enhancement algorithms can improve the detection performance. • Reinforcement learning can autonomously select algorithms based on the scenario. • Reinforcement learning avoid the issue of data labeling and retraining. The task of object detection for low-quality images in multiple scenarios remains a challenging task. To alleviate this problem, a novel approach to improve the detection performance of the model on low-quality images using deep reinforcement learning is proposed. The approach differs from methods that involve data labeling and retraining, as the detection results of the model are utilized to formulate a reward function. This enables deep reinforcement learning to transform low-quality images into high-quality images through image enhancement, ultimately leading to an improvement in the model's recognition performance on low-quality images. An image enhancement tool chain (IETC) has been prepared, offering a flexible and lightweight algorithm selection for the Dueling Deep Q-Network-based Tool Selector (DDQN-TS). By adding a "Pass" option, Enable DDQN-TS to learn the relative relationship between performing and not performing image enhancement. To mitigate the potential inconsistency between the output of the detection model and the actual situation caused by negative samples, which can lead to incorrect decisions made by DDQN-TS, the introduction of a "thresh" parameter regulates the level of intervention in target detection by DIE. The experimental results demonstrate the effectiveness and portability of the DIE model in environments with noise, fog, and uneven brightness. [ABSTRACT FROM AUTHOR]

• A newly-designed physical 2D simulator applied for dimethyl ether-steam-assisted gravity drainage. • Dimethyl ether-steam-assisted gravity drainage study with comprehensive experimental parameters and extreme conditions. • This study provides perfect implications for unconventional heavy oil practice. Steam-assisted gravity drainage (SAGD) is a mature heavy oil thermal recovery technology but inherently limited to low recovery efficiency at mid-late stage due to the increasing heat loss in the steam chamber. Here, the dimethyl ether (DME)-assisted SAGD technology and its relevant transport and interfacial properties are specifically investigated through physical 2D heavy oil simulation. A total of four-set physical experiments, with different DME injection ratios, were conducted and compared with the traditional SAGD. The experimental results indicate DME is capable of reducing the heavy oil's viscosity and interfacial tension at high temperatures. Three stages, rising, lateral expansion, and descending stages, are determined in the SAGD steam chamber's development; the mid-late SAGD stage is defined when the steam chamber extends to the caprock boundary. With DME additions at the mid-late SAGD stage, higher oil recovery factor and sweep efficiency could be reached and the dew point temperature of steam chamber's lead decreases by 0.7–1.8 °C. The optimum gas–water ratio is determined to be 3:1, with the fastest oil recovery growth and the highest final cumulative oil-vapor ratio of 0.163. This study provides reliable experimental bases and valuable analyses for the DME-SAGD technology and its application in heavy oil reservoirs. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of the reference signal being contaminated by target echoes due to factors such as wide beamwidths, beam pointing errors, or site errors in passive bistatic radar (PBR). Such contamination can lead to reference signal impurity and subsequently degrade the performance of traditional object detection methods. To overcome this challenge, a novel target detection method centered around the reference signal's purification is presented. The proposed method involves the modeling, analysis, localization, and purification of the impure reference signal. First, a new signal model incorporating the impure reference signal is established, followed by a comprehensive analysis of its impact on target detection. Then, leveraging the valuable information hidden in the impure reference signal, target echoes within the impure reference signal are localized and reconstructed. Finally, the reconstructed target echoes are subtracted from the original impure reference signal to purify the reference signal. Based on the purified reference signal, traditional target detection is performed to detect the expected targets. The core advantage of this method lies in its efficient reconstruction and removal of the impure terms within the reference signal. The effectiveness of the proposed method is demonstrated through a series of simulation results. [ABSTRACT FROM AUTHOR]

In this article, a new morphing method is proposed for two linear features at different scales, based on their entire structures ( MLBES in abbreviation). First, the bend structures of the linear features are identified by using a constrained Delaunay triangulation ( CDT in abbreviation) model and represented by binary bend-structure trees. By matching the independent bends represented by the bend-structure trees, corresponding independent bends are obtained. These corresponding independent bends are further used to match their child bends based on hierarchical bend structures so that corresponding bends are obtained. On this basis, the two linear features are split into pairs of corresponding subpolylines by the start and end points of the corresponding bends. Second, structures of the corresponding subpolylines are identified by the Douglas- Peucker algorithm and represented by binary line generalization trees ( BLG-trees in abbreviation). The corresponding subpolylines are split into smaller corresponding subpolylines by matching the nodes of the BLG-trees. Third, the corresponding points are identified by using the linear interpolation algorithm for every pair of corresponding subpolylines. Finally, straight-line trajectories are employed to generate a family of intermediate-scale linear features. By comparison with other methods, it is found that MLBES is accurate and efficient. [ABSTRACT FROM AUTHOR]

Effective removal of mercury (Hg) pollutants from contaminated water/wastewater to prevent severe environmental pollution is of great significance due to the extremely high toxicity of Hg. In this study, granular biochar and gravel (control) were packed into intermittently aerated constructed wetland (CW) microcosms to treat Hg(Ⅱ)-containing wastewater over 100 d. The results showed that the biochar-filled CWs exhibited notably better Hg(Ⅱ) removal than the gravel systems by facilitating chemical and microbial Hg(Ⅱ) reduction and volatilization and promoting plant growth and Hg assimilation. More than ten times more Hg was absorbed by the plants (L. salicaria) in biochar CWs than in the gravel systems, with the roots acting as the major sink. In contrast, substrate binding in a predominantly oxidizable fraction was the dominant pathway for Hg removal in the gravel CWs. Biochar substrates also exhibited higher levels of COD, N and P removal, and Hg(Ⅱ) import impacted the removal of these pollutants only slightly. Filling material played a more crucial role than Hg input in shaping the microbial communities in the CWs. The proportions of some dominant genera, including Arenimonas , Lysobacter , Micropruina and Hydrogenophaga , increased in the presence of Hg, implying their tolerance to Hg toxicity and potential roles in Hg detoxification in the CWs. Granular biochar-based CW has high potential for treating Hg(Ⅱ)-contaminated wastewater. [Display omitted] • Granular biochar-filled CWs were applied to treat Hg(Ⅱ)-containing wastewater. • Biochar substrates facilitated Hg volatilization and phytoremediation. • Biochar CWs were more effective in removing COD, N and P than gravel systems. • Hg(Ⅱ) input slightly decreased the nutrient removal efficiencies of CWs. • Effect of Hg on the microbial communities in CWs was related to substrate type. [ABSTRACT FROM AUTHOR]

In a traditional antenna array direction finding system, all the antenna sensors need to work or shut down at the same time, which often leads to signal crosstalk, signal distortion, and other electromagnetic compatibility problems. In addition, the direction-finding algorithm in a traditional system needs a tremendous spectral search, which consumes considerable time. To compensate for these deficiencies, a reconfigurable antenna array direction finding system is established in this paper. This system can dynamically load part or all of the antennas through microwave switches (such as a PIN diode) and conduct a fast direction of arrival (DOA) search. First, the hardware structure of the reconfigurable antenna is constructed. Then, based on the conventional spatial domain search algorithm, an improved transform domain (TD) search algorithm is proposed. The effectiveness of the system has been proven by real experiments, and the advantage of the system has been verified by detailed simulations. [ABSTRACT FROM AUTHOR]

Driver intention prediction allows drivers to perceive possible dangers in the fastest time and has become one of the most important research topics in the field of self-driving in recent years. In this study, we propose a driver intention prediction method based on multi-dimensional cross-modality information interaction. First, an efficient video recognition network is designed to extract channel-temporal features of in-side (driver) and out-side (road) videos, respectively, in which we design a cross-modality channel-spatial weight mechanism to achieve information interaction between the two feature extraction networks corresponding, respectively, to the two modalities, and we also introduce a contrastive learning module by which we force the two feature extraction networks to enhance structural knowledge interaction. Then, the obtained representations of in- and outside videos are fused using a ResLayer-based module to get a preliminary prediction which is then corrected by incorporating the GPS information to obtain a final decision. Besides, we employ a multi-task framework to train the entire network. We validate the proposed method on the public dataset Brain4Car, and the results show that the proposed method achieves competitive results in accuracy while balancing performance and computation. [ABSTRACT FROM AUTHOR]

In X-ray pulsar-based navigation (XPNAV), the appearance of Doppler effects caused by the dynamic motion of the spacecraft would severely degrade the navigation accuracy. In this paper, we develop a new XPNAV method based on a two-stage estimation method of Doppler frequency and phase delay to overcome the Doppler effects. Based on the pre-established phase model of the pulsar at the SSB and the predicted states of the spacecraft, the real-time phase model at the spacecraft is modeled with respect to the initial position and velocity errors of the spacecraft. It turns out that within an observation interval, a constant Doppler frequency can be estimated to overcome the effect of the initial velocity error, and then the phase delay caused by the initial position error can be estimated by using the computationally efficient methods based on epoch folding. Under this frame, the H-test for uniformity, which needs no prior knowledge of the light curve, is used to estimate the Doppler frequency and the fast maximum likelihood method is used to estimate the phase delay. The dynamic model and measurement model of the proposed navigation method are also given. Photon-level simulation results obtained by using the ground-based semi-physical simulation system for X-ray pulsar signals show a significant improvement over the traditional XPNAV method. [ABSTRACT FROM AUTHOR]

This paper investigates the multi-sensor distributed fusion with memory configuration for multi-target automatic tracking (MTAT) in clutter. Aimed at fully addressing the problems of both track origin ambiguity and the strong-correlation among system track and its paired local tracks in the framework, this paper derives an Exact Unified Multisensory Tracks Fusion with Memory (EU-MTFwM) method that fuses the system track with enumerated combinatorial tracks to achieve fusing all sensors' local tracks at once. It deploys track-to-track probabilistic association (T2TPA) and target-existence based track automatic management (TAM) to mitigate track origin ambiguity caused by clutter disturbance and the presence of multiple targets. Additionally, it implements the exact distributed kinematic state estimation (exact DKSE) to remove strong correlation stemming from common historical measurements and process noise. However, as the number of sensors to be fused increases, the proposed EU-MTFwM suffers from the combinatorial explosion. An Implementable Unified Multisensory Tracks Fusion with Memory (IU-MTFwM) method is then derived to sequentially fuse the system track with origin-ambiguous local tracks from multiple sensors one-by-one, providing a unified but computationally efficient alternative to the EU-MTFwM. Furthermore, a novel system track initialization technology is proposed to trigger the multisensory tracks fusion recursion. Numerical results show the proposed two unified methods achieve comparable tracking performance to the centralized fusion benchmark but with significantly reduced communication consumption, and demonstrate intensive improvement over the enhanced state-of-the-art that incorporates our proposed system track initialization into its fusion recursion. [ABSTRACT FROM AUTHOR]

Semi-supervised learning has been proven to be effective in utilizing unlabeled samples to mitigate the problem of limited labeled data. Traditional semi-supervised learning methods generate pseudo-labels for unlabeled samples and train the classifier using both labeled and pseudo-labeled samples. However, in data-scarce scenarios, reliance on labeled samples for initial classifier generation can degrade performance. Methods based on consistency regularization have shown promising results by encouraging consistent outputs for different semantic variations of the same sample obtained through diverse augmentation techniques. However, existing methods typically utilize only weak and strong augmentation variants, limiting information extraction. Therefore, a multi-augmentation contrastive semi-supervised learning method (MAC-SSL) is proposed. MAC-SSL introduces moderate augmentation, combining outputs from moderately and weakly augmented unlabeled images to generate pseudo-labels. Cross-entropy loss ensures consistency between strongly augmented image outputs and pseudo-labels. Furthermore, the MixUP is adopted to blend outputs from labeled and unlabeled images, enhancing consistency between re-augmented outputs and new pseudo-labels. The proposed method achieves a state-of-the-art performance (accuracy) through extensive experiments conducted on multiple datasets with varying numbers of labeled samples. Ablation studies further investigate each component's significance. [ABSTRACT FROM AUTHOR]

• Interfacial tension value can judge whether the liquid and gas system can be foamed. • Compound surfactant with concentration of 2 wt% has excellent foaming performance. • CO 2 oil-based foam stability deteriorates with increasing temperature and pressure. • Interfacial tension varies with temperature in different pressure ranges. Gas channeling easily occurs in CO 2 flooding, leading to lower oil production efficiency. CO 2 oil-based foam can effectively control gas channeling, so it is particularly important to study the stability of CO 2 oil-based foam to improve oil recovery. In this paper, an oil-based foam system was constructed by evaluating many different surfactants, and then the viscosity of the base oil and the type of gas were changed to study their influence on the stability of the oil-based foam. The stability of CO 2 oil-based foam under high temperature and high pressure was analyzed. Finally, the influence of CO 2 -oil interfacial tension (IFT) on the stability of oil-based foam was investigated. The results show that the CO 2 oil-based foam system composed of compound foaming agent FS with a total concentration of 2 wt% and a ratio of FCO-80 to Span 20 of 3:7 and an oil phase with a viscosity of 2.98 mPa·s have excellent foaming performance. In Zones I and II, the CO 2 -oil IFT is too low, a miscible or near miscible system is formed, and the system cannot generate foam. Although the IFT in Zone III is low, the film's strength is low, which leads to no foam in the system. The temperature and pressure conditions in zone IV are suitable for an oil-based foam system to generate foam. Under the same foam system, there is a critical CO 2 -oil IFT at different temperatures, which can be used as a standard to criterion whether the system can foam. This paper has meaningful guiding significance for improving the stability mechanism of CO 2 oil-based foam under different temperatures and pressures and controlling gas channeling in the process of CO 2 flooding. [ABSTRACT FROM AUTHOR]

The modeling of channel and temporal information is of crucial importance for action recognition tasks. To build a high-performance action recognition network by effectively capturing channel and temporal information, we propose CLS-Net: an action recognition algorithm based on channel-temporal information modeling. The proposed CLS-Net characterizes channel and temporal information by inserting multiple modules to an end-to-end backbone network, including a channel attention module (CA module) for modeling channel information, a long-term temporal module (LT module) and a short-term temporal module (ST module) for modeling temporal information. Specifically, the CA module extracts the correlation between feature channels so the network can learn to selectively strengthen the features containing useful information and suppress the useless features through global information. The LT module moves some channels in the temporal dimension to realize information interaction across time domains and model global temporal information. The ST module enhances the motion-sensitive features by calculating the feature-level frame difference information and realizes the representation of local motion information. Since the multi-module insertion mode directly affects the whole model's final performance, we propose a novel multi-module insertion mode instead of a simple series or parallel connection to ensure that the multiple modules can complement one another and cooperate with each other more efficiently. CLS-Net achieves SOTA performance on the EgoGesture and Jester dataset in the same type of network and achieves competitive results on the Something-Something V2 dataset. [ABSTRACT FROM AUTHOR]

Sodium metal batteries (NMBs) have attracted increasing attention as next‐generation rechargeable batteries. How to improve their cycling stability and safety under limited sodium excess conditions, ideally zero sodium excess (i.e., anode‐free architecture), is highly desired yet remains challenging. Herein, it is demonstrated that sodium formate (HCOONa), one component of the solid electrolyte interphase (SEI) naturally formed on sodium metal anode, is a promising candidate for designing high‐performance artificial SEI layers, which can suppress the sodium dendrite formation and reduce the side reactions between sodium and the electrolyte. Profiting from the HCOONa interface, the Na|Na3V2(PO4)3 battery with a high mass loading of Na3V2(PO4)3 (10 mg cm−2) exhibits a superior cycling stability with an ultralow decay rate of 0.004% per cycle over 800 cycles. More impressively, a single molecular layer of HCOONa in situ formed on commercial copper current collector helps to extend the lifespan of the anode‐free Cu|Na3V2(PO4)3 battery to 400 cycles with 88.2% capacity relation, representing the longest cycle lifetime reported in anode‐free NMBs. [ABSTRACT FROM AUTHOR]

The segmentation of pulmonary lobes is important in clinical assessment, lesion location, and surgical planning. Automatic lobe segmentation is challenging, mainly due to the incomplete fissures or the morphological variation resulting from lung disease. In this work, we propose a learning-based approach that incorporates information from the local fissures, the whole lung, and priori pulmonary anatomy knowledge to separate the lobes robustly and accurately. The prior pulmonary atlas is registered to the test CT images with the aid of the detected fissures. The result of the lobe segmentation is obtained by mapping the deformation function on the lobes-annotated atlas. The proposed method is evaluated in a custom dataset with COPD. Twenty-four CT scans randomly selected from the custom dataset were segmented manually and are available to the public. The experiments showed that the average dice coefficients were 0.95, 0.90, 0.97, 0.97, and 0.97, respectively, for the right upper, right middle, right lower, left upper, and left lower lobes. Moreover, the comparison of the performance with a former learning-based segmentation approach suggests that the presented method could achieve comparable segmentation accuracy and behave more robustly in cases with morphological specificity. [ABSTRACT FROM AUTHOR]

Organic room‐temperature long‐persistent luminescent materials are promising light‐emitting materials for encryption, architectural decoration, organic solar cells, and biomedical applications. However, their unstable structures and thermal‐ and humidity‐induced emission quenching have greatly limited their utility and reliability. Here, we report a metal‐free nonconjugated copolymer that possesses stable photoluminescence at both high temperature and humidity. The room‐temperature long‐persistent luminescence (LPL) of this copolymer lasts for more than 15 s and can be recovered in high humidity conditions by heating to remove moisture. Copolymer LPL can be achieved with various excitation wavelengths, ranging from ultraviolet to near‐infrared, and the LPL color can be adjusted accordingly. The high initial LPL intensity and ultrafast filling time of the copolymer makes it suitable for low flicker alternating current‐driven light‐emitting diodes (AC‐LEDs). [ABSTRACT FROM AUTHOR]

Organic room‐temperature long‐persistent luminescent materials are promising light‐emitting materials for encryption, architectural decoration, organic solar cells, and biomedical applications. However, their unstable structures and thermal‐ and humidity‐induced emission quenching have greatly limited their utility and reliability. Here, we report a metal‐free nonconjugated copolymer that possesses stable photoluminescence at both high temperature and humidity. The room‐temperature long‐persistent luminescence (LPL) of this copolymer lasts for more than 15 s and can be recovered in high humidity conditions by heating to remove moisture. Copolymer LPL can be achieved with various excitation wavelengths, ranging from ultraviolet to near‐infrared, and the LPL color can be adjusted accordingly. The high initial LPL intensity and ultrafast filling time of the copolymer makes it suitable for low flicker alternating current‐driven light‐emitting diodes (AC‐LEDs). [ABSTRACT FROM AUTHOR]

Attention mechanisms have demonstrated great potential in improving the performance of deep convolutional neural networks (CNNs). However, many existing methods dedicate to developing channel or spatial attention modules for CNNs with lots of parameters, and complex attention modules inevitably affect the performance of CNNs. During our experiments of embedding Convolutional Block Attention Module (CBAM) in light-weight model YOLOv5s, CBAM does influence the speed and increase model complexity while reduce the average precision, but Squeeze-and-Excitation (SE) has a positive impact in the model as part of CBAM. To replace the spatial attention module in CBAM and offer a suitable scheme of channel and spatial attention modules, this paper proposes one Spatio-temporal Sharpening Attention Mechanism (SSAM), which sequentially infers intermediate maps along channel attention module and Sharpening Spatial Attention (SSA) module. By introducing sharpening filter in spatial attention module, we propose SSA module with low complexity. We try to find a scheme to combine our SSA module with SE module or Efficient Channel Attention (ECA) module and show best improvement in models such as YOLOv5s and YOLOv3-tiny. Therefore, we perform various replacement experiments and offer one best scheme that is to embed channel attention modules in backbone and neck of the model and integrate SSAM into YOLO head. We verify the positive effect of our SSAM on two general object detection datasets VOC2012 and MS COCO2017. One for obtaining a suitable scheme and the other for proving the versatility of our method in complex scenes. Experimental results on the two datasets show obvious promotion in terms of average precision and detection performance, which demonstrates the usefulness of our SSAM in light-weight YOLO models. Furthermore, visualization results also show the advantage of enhancing positioning ability with our SSAM. [ABSTRACT FROM AUTHOR]

Abstract: For the bearings-only tracking (BOT) problem with signal propagation time delay, a recursive algorithm is proposed. Based on the analysis of signal time delay effect, an online parameter estimation (OPE) method is presented, which can be embedded in nonlinear filters to recursively estimate the target state with delayed measurements. The nonlinear filter used in this paper is a combination of the kernel-based filter (KBF) with an improved range parameterized (IRP) method, which manages subintervals according to their corresponding weights. The effectiveness and advantages of our proposed method compared with two existing methods are demonstrated by simulation examples. [Copyright &y& Elsevier]

[Display omitted] • FeN x -HDC@Ru nanocomposites are designed for the LOBs. • The internal network-like hollow structure can enhance the charge transfer kinetics. • A low impedance Li 2 O 2 /catalysts contact interface could be earned by the Ru nanoparticles. • The formation and decomposition of Li 2 O 2 could be improved with the nanocomposites during the cycling. Owing to their high energy density, lithium-oxygen batteries (LOBs) have been drawn great attention as one of the promising electrochemical energy sources. However, the sluggish kinetics of oxygen reduction/evolution reaction (ORR/OER) hamper the widespread application of LOBs. Herein, an elaborate designed catalysts which are constructed by FeN x moieties dispersed on the network-like hollow dodecahedral carbon and then decorated with Ru nanoparticles (FeN x -HDC@Ru). Since the homogeneously dispersed FeN x moieties could promote ORR performance, and the Ru nanoparticles could facilitate OER capability, the FeN x -HDC@Ru nanocomposites used as cathode catalysts can significantly improve LOBs performance. A lower discharge and charge overpotentials of 0.15 V and 0.78 V can be detected in the first cycle, respectively, and an excellent cycle performance of 90 cycles at 200 mA g−1 and 89 cycles at 500 mA g−1 can be demonstrated. Herein, the charge transfer kinetics has been enhanced with the internal network-like hollow structure and a low impedance Li 2 O 2 /catalysts contact interface could be earned by the constructed Ru nanoparticles, these factors would lead to an efficient acceleration to the formation and decomposition of Li 2 O 2 during discharge and charge process. [ABSTRACT FROM AUTHOR]

Solid‐state lithium batteries (SSLBs) are promising owing to enhanced safety and high energy density but plagued by the relatively low ionic conductivity of solid‐state electrolytes and large electrolyte–electrode interfacial resistance. Herein, we design a poly(vinylidene fluoride‐co‐hexafluoropropylene) (PVDF‐HFP)‐based polymer‐in‐salt solid electrolyte (PISSE) with high room‐temperature ionic conductivity (1.24×10−4 S cm−1) and construct a model integrated TiO2/Li SSLB with 3D fully infiltration of solid electrolyte. With forming aggregated ion clusters, unique ionic channels are generated in the PISSE, providing much faster Li+ transport than common polymer electrolytes. The integrated device achieves maximized interfacial contact and electrochemical and mechanical stability, with performance close to liquid electrolyte. A pouch cell made of 2 SSLB units in series shows high voltage plateau (3.7 V) and volumetric energy density comparable to many commercial thin‐film batteries. [ABSTRACT FROM AUTHOR]

Solid‐state lithium batteries (SSLBs) are promising owing to enhanced safety and high energy density but plagued by the relatively low ionic conductivity of solid‐state electrolytes and large electrolyte–electrode interfacial resistance. Herein, we design a poly(vinylidene fluoride‐co‐hexafluoropropylene) (PVDF‐HFP)‐based polymer‐in‐salt solid electrolyte (PISSE) with high room‐temperature ionic conductivity (1.24×10−4 S cm−1) and construct a model integrated TiO2/Li SSLB with 3D fully infiltration of solid electrolyte. With forming aggregated ion clusters, unique ionic channels are generated in the PISSE, providing much faster Li+ transport than common polymer electrolytes. The integrated device achieves maximized interfacial contact and electrochemical and mechanical stability, with performance close to liquid electrolyte. A pouch cell made of 2 SSLB units in series shows high voltage plateau (3.7 V) and volumetric energy density comparable to many commercial thin‐film batteries. [ABSTRACT FROM AUTHOR]

In this paper, we study the multi-sensor multi-target tracking problem in the formulation of random finite sets. The Gaussian Mixture probability hypothesis density (GM-PHD) method is employed to formulate the sequential fusing multi-sensor GM-PHD (SFMGM-PHD) algorithm. First, the GM-PHD is applied to multiple sensors to get the posterior GM estimations in a parallel way. Second, we propose the SFMGM-PHD algorithm to fuse the multi-sensor GM estimations in a sequential way. Third, the unbalanced weighted fusing and adaptive sequence ordering methods are further proposed for two improved SFMGM-PHD algorithms. At last, we analyze the proposed algorithms in four different multi-sensor multi-target tracking scenes, and the results demonstrate the efficiency. [ABSTRACT FROM AUTHOR]

A predefined permission source region (PSR) is commonly used in bioluminescence tomography (BLT) as a priori information to reduce the ill-posedness of source reconstruction. However, the PSR is usually hard to determine and may miss the actual source region. Simultaneously, a linear or nonlinear based reconstruction method commonly have a relatively poor performance in the terms of low photon rate and strong noise. Here, we propose an alternative statistical-based-reconstruction framework with a cluster-algorithm-optimized PSR for BLT. In the alternative reconstruction framework, a global reconstruction is first conducted overall the solving domain to generate a rough estimation of source distribution by using a global based maximum likelihood expectation maximum (MLEM) method. Subsequently, a k-means cluster method is used to learn and find likely source support regions, which generates the optimal PSR. Finally, a local MLEM based reconstruction is performed to refine the source distribution on the optimal PSR. We first verify the performance of the proposed method with a series of numerical simulations, and then explore the potential by imaging in situ liver cancer in living mouse. [ABSTRACT FROM AUTHOR]

Abstract: To address the serious capacity fading in lithium–sulfur batteries, a 3D ferroconcrete‐like aminated carbon nanotubes network with polyaniline coating as an effective sulfur host to contain polysulfide dissolution is presented here. In this composite, the cross‐linked aminated carbon nanotubes framework provides a fast charge transport pathway and enhancement in the reaction kinetics of the active material to greatly improve the rate capability and sulfur utilization. The ethylenediamine moieties provide strong adhesion of polar discharge products to nonpolar carbon surfaces and thus efficiently prevent polysulfide dissolution to improve the cycle stability, confirmed by density functional theory calculations. The outside polyaniline layers structurally restrain polysulfides to prevent the shuttle effect and active material loss. Benefiting from these advantages, the synthesized composite exhibits a high initial capacity of 1215 mAh g−1 and a capacity of 975 mAh g−1 after 200 cycles at 0.2 C. Even after 200 cycles at 0.5 C, a capacity of 735 mAh g−1 can be maintained, among the best performance reported. The strategy in this work can shed some light on modifying nonpolar carbon surfaces via the amination process to chemically attach sulfur species for high‐performance lithium–sulfur batteries. [ABSTRACT FROM AUTHOR]

The Zn 1.8 SiO 3.8 (ZS) ceramics with BaCu(B 2 O 5 ) (BCB) additive were synthesized by the conventional solid-state reaction route and the effect of BCB additive on the microwave dielectric properties of the ceramics was investigated. The results demonstrate that BCB could effectively decrease the sintering temperature from 1300 °C to 930 °C and does not induce obviously degradation of the microwave dielectric properties. The 6.wt% BCB added ZS ceramics exhibited a low sintering temperature (~ 930 °C) and excellent dielectric properties of ε r = 6.79, Q×f = 33,648 GHz, and τ f = −30 ppm/°C. To compensate the negative τ f value of this system, TiO 2 powders were introduced. Particularly when 10.wt% TiO 2 was added, good microwave dielectric properties of ε r = 8.175, Q×f = 21,252 GHz, and τ f = 1.2 ppm/°C were obtained for the 6.wt% BCB added ZS ceramic sintered at 930 °C for 3 h. Moreover, BCB added ZS-TiO 2 ceramics have a chemical compatibility with silver, which indicate that the BCB added ZS ceramics are promising candidate for LTCC applications. [ABSTRACT FROM AUTHOR]

Robust Anode-Free Sodium Metal Batteries Enabled by Artificial Sodium Formate Interface (Adv. Anode-free batteries, sodium dendrites, sodium formate, sodium metal anodes, sodium metal batteries Keywords: anode-free batteries; sodium dendrites; sodium formate; sodium metal anodes; sodium metal batteries EN anode-free batteries sodium dendrites sodium formate sodium metal anodes sodium metal batteries 1 1 1 06/13/23 20230609 NES 230609 B Sodium Metal Batteries b In article number 2204125, Xiaoliang Fang and co-workers develop an artificial formate sodium interface with rapid ion conduction and high mechanical strength for constructing high-performance sodium metal batteries. [Extracted from the article]

On-chip integrated solenoid inductors with nanogranular FeCoTiO magnetic cores have been fabricated. Both single-layered and multilayered magnetic cores with different geometries were studied. An inductance of 14.2 nH was achieved when using a multilayered core structure and keeping the device area of 0.14 mm2. The inductance of the magnetic core inductor is $\sim 14$ times that of the air core inductor, and the quality factor is 7.5. The permeability trends calculated from inductance were compared with the permeability spectra of the patterned FeCoTiO films measured by an improved shorted microstrip transmission line perturbation method. Consistent results have been obtained after considering the demagnetization effect of the magnetic core with high permeability. [ABSTRACT FROM PUBLISHER]

A series of soft magnetic nanogranular FeCo–Ti–O films with different Ti contents were fabricated on Si substrates by co-sputtering. By adjusting the Ti content, it appears that the imaginary part of the permeability spectra of FeCo–Ti–O films changes from a single peak to double peaks then to a single peak. Frequency conversion ferromagnetic resonance (FMR) analysis evidences that double FMR peaks can be found in all three films, which were attributed to local anisotropy or two magnetic phases embedded in amorphous TiO x matrix. Structural and temperature dependent resistivity analysis support such three component microstructure. The overlapping double FMR peaks provide a wide absorption frequency band over 3 GHz, which is critical for the design of electromagnetic interference suppressor. [ABSTRACT FROM AUTHOR]

A high performance strontium silicate phosphor has been successfully synthesized though a facile vapor-phase deposition method. The product consists of single crystal whiskers which are smooth and uniform, and with a sectional equivalent diameter of around 5 μm; the aspect ratio is over 50 and no agglomeration can be observed. X-ray diffraction result confirmed that the crystal structure of the whisker was α’-Sr 2 SiO 4 . The exact chemical composition was Sr 1.98 Eu 0.02 SiO 4 which was analyzed by energy dispersive spectrometer and inductively coupled plasma-mass spectrometer. The whisker shows broad green emission with peak at 523 nm ranging from 470 to 600 nm (excited at 370 nm). Compared with traditional Sr 2 SiO 4 :Eu phosphor, durability (at 85% humidity and 85 °C) and thermal stability of the whisker are obviously improved. Moreover, growth mechanism of the Sr 1.98 Eu 0.02 SiO 4 whiskers is Vapor–Liquid–Solid. On a macro-scale, the product is still powder which makes it suitable for the current packaging process of WLEDs. [ABSTRACT FROM AUTHOR]

The phase equilibria of Co–V binary system were experimentally investigated, and the magnetically induced phase separation in the fcc phase was observed in a Co/V diffusion couple. Based on previous research and present work, a thermodynamic reassessment in the Co–V binary system was carried out by means of the CALPHAD method. The calculated results are consistent with the experimental data. The metastable miscibility gap of the hcp phase in the Co–V binary system was thermodynamically calculated. According to the calculation, the Co–V thin films with three concentrations were designed and deposited by magnetron sputtering. The transmission electron microscope (TEM) results prove that the metastable phase separation in the hcp phase exists in the Co–V system. The determined magnetic properties of the thin films reveal that the values of coercivity and remanence ratio are function of V content. [ABSTRACT FROM AUTHOR]

Abstract: The Co3O4/AAO composite with novel morphology was successfully prepared by the solution-dipping method and the calcination of cobalt acetate precursor at 400°C for 2h in air. Porous anodic alumina (AAO) thin film was selected as new substrate to support colloidal monolayer template. Scanning electron microscopy (SEM) analysis indicated that the morphology of the as-prepared product could be controlled by changing the concentration of precursor. Catalytic test shows that the obtained Co3O4/AAO composite has a high decolorization ratio in the degradation of methylene blue (MB), which reaches 97.79% in 140min in the presence of sodium borohydride (NaBH4). Comparative experiments show that this nanomaterial has enhanced catalytic performance. [Copyright &y& Elsevier]

This paper investigates a novel distributed fusion system for target tracking in three dimensional surveillance using multiple asynchronous BO sensors by simultaneously addressing the problems of target mis-detection and clutter disturbance as well as the out-of-sequence (OOS) information fusion. The proposed distributed fusion architecture consists of the local tracking and distributed fusion, wherein, the refined BO measurements output from the local tracking in each BO sensor are transmitted to the fusion center for subsequent distributed fusion. In the local tracking, instead of kinematic state, the target pseudo state is defined and tracked by operating the proposed pseudo state-integrated probabilistic data association (PS-IPDA) algorithm with an approximately linear pseudo state evolution model, resulting in greatly refined BO sensor measurements. In the fusion center, the sequential asynchronous IPDA-general one-step retrodiction update (SAIPDA-GORU) algorithm is proposed to effectively fuse the transmitted origin-unknown OOS refined measurements (OOSRMs) with the central tracks. The SAIPDA-GORU propagates the central track hybrid state to the OOS time by deploying a general one-step retrodiction technique, and mathematically formulates the OOSRMs-to-retrodicted central track association probabilities utilized to facilitate the fusing of currently filtered central track with OOSRMs. Numerical results show that the proposed PS-IPDA algorithm reduces the errors of target bearings measurement by around a half and eliminates more than 60% of the clutter measurements contained in raw detections, saving significant communication bandwidth between local sensors and fusion center. Furthermore, the proposed SAIPDA-GORU method tangibly improves the estimation accuracy and false track discrimination over the existing discarding method, with the potential to be implemented in real-time. [ABSTRACT FROM AUTHOR]

The grain size and the ferroelectric morphology are the two most important factors in the research and development of advanced dielectric devices. It is important to synthesize nanostructures in order to achieve optimal grain size and inhibit grain growth while controlling the sintering parameters. It is also important to find new methods to study the grain growth during densification. BaTiO3 films were successfully obtained via the sol-gel spin coating method. In this paper, we report the deposition of nanostructured BaTiO3 thin film by spin coating of sol-gel precursors. The densification, grain growth and microstructure evolution have been studied. Moreover, a novel physical and mathematical fractal analysis have been applied successfully to the densification and nano grain growth of BaTiO3 thin film. The discrepancy between the fractal dimension and the grain growth with increasing temperatures and soaking time are presented and discussed. Image 1062 • Analisy BaTiO3 nanograin growth with the sintering parameters influence on kinetics. • All of these sintering analysis we are enriching with fractal nature approach. • New approach enlight consolidation and morphology by fractal nature analysis. • The fractal dimension characterisation is included to complete analysis. • Here, we introduce the fractal nature correction influence on sintering temperature. [ABSTRACT FROM AUTHOR]

The accuracy of X-ray pulsar-based navigation is greatly affected by the Doppler effect caused by the spacecraft orbital motion and the systematic biases introduced by the pulsar directional error, spacecraft-borne clock error, etc. In this paper, an innovative navigation method simultaneously employing the pulse phase (PP), the difference of two neighbor PPs (DPP) and the Doppler frequency (DF) of X-ray pulsars as measurements is proposed to solve this problem. With the aid of the spacecraft orbital dynamics, a single pair of PP and DF relative to the spacecraft's state estimation error can be estimated by using the joint probability density function of the arrival photon timestamps as the likelihood function. The systematic biases involved to the PP is proved to be nearly invariant over two adjacent navigation periods and the major part of it is eliminated in the DPP; therefore, the DPP is also exploited as additional navigation measurement to weaken the impact of systematic biases on navigation accuracy. Results of photon-level simulations show that the navigation accuracy of the proposed method is remarkably better than that of the method only using PP, the method using both PP and DF and the method using both PP and DPP for Earth orbit. [ABSTRACT FROM AUTHOR]

A localization and tracking algorithm for an early-warning tracking system based on the information fusion of Infrared (IR) sensor and Laser Detection and Ranging (LADAR) is proposed. The proposed Kalman filter scheme incorporates Out-of-Sequence Measurements (OOSMs) to address long-range, high-speed incoming targets to be tracked by networked Remote Observation Sites (ROS) in cluttered environments. The Rauch–Tung–Striebel (RTS) fixed lag smoothing algorithm is employed in the proposed technique to further improve tracking accuracy, which, in turn, is used for target profiling and efficient filter initialization at the targeted platform. This efficient initialization increases the probability of target engagement by increasing the distance at which it can be effectively engaged. The increased target engagement range also reduces risk of any damage from debris of the engaged target. Performance of the proposed target localization algorithm with OOSM and RTS smoothing is evaluated in terms of root mean square error (RMSE) for both position and velocity, which accurately depicts the improved performance of the proposed algorithm in comparison with existing retrodiction-based OOSM filtering algorithms. The effects of assisted target state initialization at the targeted platform are also evaluated in terms of Time to Impact (TTI) and true track retention, which also depict the advantage of the proposed strategy. [ABSTRACT FROM AUTHOR]

Multitarget tracking in clutter using bearings-only measurements is a challenging problem. In this paper, a performance improved nonlinear filter is proposed on the basis of the Random Finite Set (RFS) theory and is named as Gaussian mixture measurements-based cardinality probability hypothesis density (GMMbCPHD) filter. The GMMbCPHD filter enables to address two main issues: measurement-origin-uncertainty and measurement nonlinearity, which constitutes the key problems in bearings-only multitarget tracking in clutter. For the measurement-origin-uncertainty issue, the proposed filter estimates the intensity of RFS of multiple targets as well as propagates the posterior cardinality distribution. For the measurement-origin-nonlinearity issue, the GMMbCPHD approximates the measurement likelihood function using a Gaussian mixture rather than a single Gaussian distribution as used in extended Kalman filter (EKF). The superiority of the proposed GMMbCPHD are validated by comparing with several state-of-the-art algorithms via intensive simulation studies. [ABSTRACT FROM AUTHOR]

The phase evolution, thermal stability, structure and magnetic properties of the melt-spun Fe 70− x Pt x B 30 ( x = 0–20) alloys have been investigated. Addition of small amounts of Pt to the Fe 70 B 30 alloy increases the amorphous-forming ability, leading to the formation of an amorphous phase in the alloys with x = 5 and 10. Further increase in Pt content results in the formation of the fcc-FePt + Fe 2 B or fcc-FePt + L 1 0 -FePt + Fe 2 B crystalline phases. After appropriate annealing, the homogeneous nano-sized structure consisting of hard L 1 0 -FePt and soft Fe 2 B magnetic phases were formed for the alloys with x = 10–20, which exhibited good hard magnetic properties. As the Pt content increase, the coercivity ( i H c ) of the L 1 0 -FePt/Fe 2 B nanocomposite alloys significantly increased, while the remanence ( B r ) decreased. The B r , reduced remanence ( M r / M s ), i H c , and energy product ( BH ) max of the alloys are in the range of 0.81–1.20 T, 0.76–0.84, 173.2–523.1 kA/m, and 64.0–88.3 kJ/m 3 , respectively. [ABSTRACT FROM AUTHOR]