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The ultra-homogeneous dense Ag nano layer is susceptible to alloy formation, and the formed AgLi alloy not only inhibits the corrosion of Li by SN molecules, but also induces plenty of uniform nucleation/deposition of Li.

The pursuit of high energy density in lithium batteries has driven the development of efficient electrodes with low levels of inactive components. Herein, a facile approach involving the use of π–π stacked nigrosine@carbon nanotube nanocomposites as an all-in-one additive for a LiFePO4cathode has been developed. This design significantly reduces the proportion of inactive substances within the cathode, resulting in a battery that exhibits a high specific capacity of 143 mAh g–1at a 1 C rate and shows commendable cyclic performance. Furthermore, the elimination of rigid current collectors endows the electrode with flexibility, offering avenues for future wearable energy storage devices.

Metallic Zn is considered as a promising anode material because of its abundance, eco-friendliness, and high theoretical capacity. However, the uncontrolled dendrite growth and side reactions restrict its further practical application. Herein, we proposed a β-cyclodextrin-modified multiwalled carbon nanotube (CD-MWCNT) layer for Zn metal anodes. The obtained CD-MWCNT layer with high affinity to Zn can significantly reduce the transfer barrier of Zn2+at the electrode/electrolyte interface, facilitating the uniform deposition of Zn2+and suppressing water-caused side reactions. Consequently, the Zn||Zn symmetric cell assembled with CD-MWCNT shows a significantly enhanced cycling durability, maintaining a cycling life exceeding 1000 h even under a high current density of 5 mA cm–2. Furthermore, the full battery equipped with a V2O5cathode displays an unparalleled long life. This work unveils a promising avenue toward the achievement of high-performance Zn metal anodes.

Single-frame infrared small target detection (SIRSTD) is in urgent demand for many practical tasks, such as fire rescue and urban management systems, benefiting from the excellent performance of infrared (IR) imaging in harsh climates and low-light environments. SIRSTD strives to segment small targets from the background as accurately as possible. However, in a real-world application, complex background environments with high brightness and strong edges have similar physical characteristics to small IR targets, which makes it extremely difficult to separate small targets. To address this challenge, we propose a novel Gaussian Curvature Inspired Network (GCI-Net). Inspired by the well-known Gaussian curvature, we develop a Gaussian curvature-based branch (GCB) to eliminate the smoothing noise and preserve the target structure texture information. In addition, we design a complementary patch-group attention (PGA) module that relies on the complementary relationship between low-level and high-level features to provide accurate guidance for GCB. The curvature information generated by the GCB is continuously optimized under the constraint of the curvature information of the ground truth. The proposed GCI-Net provides a reliable guarantee for accurate separation of small targets from the background. We conduct extensive experiments on the public IRSTD-1k and SIRST datasets. The experimental results demonstrate that the proposed GCI-Net outperforms the state-of-the-art (SOTA) methods.

The techniques of machine learning, as well as deep learning (DL) methods, have seen a wide application in the intelligent fault diagnosis field these years. However, contemporary methods are still restricted under some drawbacks: 1) conventional DL-based models always rely on the quality and amount of the data. However, there are usually insufficient samples in practical scenarios because of suddenly happened failures and 2) the existing DL models cannot be well implemented in different rotating components, which have different distributions and label space, such as from bearings to gears. To address these problems, a novel multiscale wavelet prototypical network (MWPN) is proposed in this study. It is designed to solve the few-shot fault diagnosis of the cross-component problem in rotating machines: the model is trained by one component with sufficient data and tested in another component with little data. First, a multiscale wavelet convolution module is designed to extract abundant features. Second, a metric meta-learner module is applied to measure the distance distribution between the labeled and unlabeled data. With the episode training strategy, the model is optimized and can adapt to similar tasks in a new machine and classify the unknown fault categories with few labeled samples. Experiments on three datasets are carried out to demonstrate the effectiveness of MWPN. Extensive experimental results show that MWPN outperforms many baseline methods on few-shot learning tasks in different working conditions and components.

Data-driven-based intelligent fault diagnosis (IFD) approaches have been broadly developed. In actual industry, not all data of mechanical equipment are accessible, especially in an era of increasing attention to data privacy protection. In addition, as the machine consistently operates, new data of various working conditions are continuously collected. The existence of these problems puts forward more stringent requirements for the application scenarios of algorithms, that is, how to train an intelligent model without source samples and how to preserve the diagnostic knowledge learned from the previous task as the new data are continually collected. To exploit the application range, a novel unsupervised continual source-free network (UCSN) is proposed for IFD of rotating machinery. A one dimension convolutional neural network is adopted as the feature extractor to extract invariant features. Based on the extracted features, a local structure clustering is used to process the target samples, which can cluster the same fault samples and separate the different fault samples simultaneously. Meanwhile, sparse domain attention is utilized to preserve the learned knowledge and to improve the generalization of the well-trained model. In this way, the application scenarios of the IFD can be significantly expanded. Extensive experiments on a popular public bearing dataset and an actual industry dataset are carried out to verify the effectiveness of the proposed UCSN. Comparisons with ablation methods on the same experimental circumstance validate the superiority of key techniques and the proposed UCSN. The experimental results indicate that the proposed UCSN provides a promising tool for IFD of rotating machinery.

Data privacy protection is a hot-button issue in the field of intelligent fault diagnosis (IFD). For this purpose, plenty of methods are recently proposed to adapt a machine learning model to a target domain without any labeled data from the target domain or access to the source domain’s data distribution, which is called source-free domain adaptation (SFDA). However, existing methods generally focus on SFDA with a single-source domain and the fault categories are often inconsistent between different working conditions. A natural idea is to derive the fault knowledge of different fault categories from multiple source domains. Therefore, a knowledge distillation based multiple SFDA framework (KD-MSFDA) is proposed in this study. To be specific, multiple source predictors are pretrained locally and transferred to the target domain. A KD with predictor confidence vote process is designed to filter the invalid source domains, which can extremely help extract more reliable unitive expert knowledge. Meanwhile, a knowledge contribution (KC)-based domain weight adaptation strategy is proposed to automatically assign the weight of each source domain. Extensive experiments on an automobile transmission (AT) dataset and a bearing dataset are designed to demonstrate the proposed framework. And the experimental performance verifies that the proposed framework is effective for multiple SFDA scenarios.

The objective of this study was to verify the applicability of the critical nitrogen concentration dilution curve of wheat under different nitrogen application rates in the field and discuss the feasibility of using the nitrogen nutrition index (NNI) to optimize nitrogen fertilizer application. Experiments with different wheat varieties were carried out in Xinxiang (Henan Province, China) for two consecutive years, using four nitrogen application rates: 0, 165, 247.5, and 288.75 kg ha−1. Values of aboveground dry matter (t ha−1) and nitrogen concentration (%) were measured at each sampling date to develop the critical nitrogen concentration (Nc) equation. The relationship between Ncand aboveground dry matter (DM) was respectively described by a power function for 2018 and 2019 (Nc= 5.25DM −0.47, R2= 0.931; and Nc= 5.30 DM −0.47, R2= 0.924). Differences in dilution model parameters between years indicated that the nitrogen accumulation capacity in 2019 was slightly higher than that in 2018 and the slope of the Ncdilution curve was the same under the same aboveground biomass. Based on the Ncdilution model, the NNI model was established, which can be used to objectively and quantitatively diagnose nitrogen status. The results of nitrogen fertilizer regulation based on Ncand NNI were consistent with results of the nitrogen application rate based on yield indicators. The best nitrogen level was the 247.5 kg ha−1. Since Nchas reasonable biological significance, the model was accurate, simple, and with clear biological significance. It can be directly used in assessing nitrogen demand of crops and also in complex models of crop nitrogen dynamics. This will provide new ideas for timely and accurate fertilization.

Lithium (Li) metal is widely recognized as a promising anode material for next-generation Li secondary batteries, owing to its exceptionally high theoretical specific capacity of 3860 mAh g−1and the lowest reduction potential (−3.04 V vs. standard hydrogen electrode). However, the instability of the native solid electrolyte interphase (SEI) leads to dendrite growth, which poses significant safety risks and contributes to battery degradation. To address this issue, numerous strategies have been proposed to construct artificial SEI with good physical and chemical properties. This paper provides a comprehensive overview of advancements in constructing artificial SEI from the perspective of precursor materials (i.e., inorganic and organic inducers) and construction methods (i.e., in situ and ex situ). It focuses on the compositional and nanostructural changes of SEI engineered by different strategies and explores their resulting functional differences. Based on the summary of various strategies, prospective research directions for the development of artificial SEI are finally envisioned.

1,3-Unsaturated fatty acid-2-palmitic acid triacylglycerol (UPU) is a key component of human milk fat substitutes. In this present study, a novel approach was employed to produce UPU by cell factory of Rhodococcus opacus. The resulting UPU displayed a remarkable fatty acid composition, with 37.6% docosahexaenoic acid (DHA), 26.3% palmitic acid (P) and 15.6% docosapentaenoic acid (DPA). Notably, palmitic acid dominated the sn-2 position with a content of 51.1%. Furthermore, 13C nuclear magnetic resonance analysis revealed the predominant presence of DHA at the sn-1,3 position and palmitic acid at the sn-2 position. Among the triacylglycerol species, β-DHA P DHA (6.6%) and β-DPA P DHA (6.6%) exhibited the highest levels. The fermentation process achieved a biomass of 2.1 g L-1and an oil content of 39.9% (DCW). The yield of UPU reached 0.89 g L-1. This study presented a novel method for manufacturing 1,3-unsaturated fatty acid-2-palmitic acid triacylglycerol enriched with DHA.

Precipitates, including silicides and Ti 3 Al (α 2) phase, and alloying elements distribution in a near α titanium alloy Ti65 (Ti-5.8Al-4.0Sn-3.5Zr-0.5Mo-0.3Nb- 1.0Ta-0.4Si-0.8W-0.05C) after solution treatment and aging process were characterized by using transmission electron microscopy (TEM) and atom probe tomography (APT). Quantitative composition analysis and TEM observation indicate that the silicides fit to (Ti, Zr) 6 (Si, Sn) 3. Zr exhibits a β-stabilizing effect in near α titanium alloys but is weaker than other β stabilizing elements. The enriching tendency of the alloying elements in the retained β phase is in the order of Zr < Nb < Ta < Mo < W. The experimental results are rationalized by the relative stability of alloying elements in the α and β phases and the mobility of these atoms in the matrix. An enrichment of Si in the α 2 phase over the α matrix phase is noticed, which is attributed to the lower formation energy of Si in the α 2 phase. [ABSTRACT FROM AUTHOR]

Aflatoxin B1 (AFB1) is an inevitable contaminant in animal feed and agricultural products, which seriously threatens the health of animals. However, there is currently no better diagnostic tool available than depending on clinical symptoms, pathophysiology, biochemical indicators, etc. Here, we profiled the fecal microbiomes of sheep exposed to and not exposed to AFB1 to identify potential non-invasive biomarkers of AFB1 intoxication by 16S rRNA gene sequencing technology, while measuring serum biochemical indexes. The results showed that the sheep exposed to AFB1 had significantly higher levels of the liver function indicators ALT (alanine transaminase) and AST (aspartate aminotransferase), and their microbial profiles were different from those of the CON (Control) group. In detail, the relative abundance of seven phyla and three genera were overrepresented in the AFB1 group from top 10 relative abundance. Importantly, we found that Prevotellaand Bifidobacteriumwere significantly different in the CON and AFB1 groups (p= 0.032 and p= 0.021, respectively) based on linear discriminant analysis effect size (LEfSe) and random forest analysis. Additionally, the area under curve (AUC) of ALT was 1 (95% CI 1.00–1.00; p< 0.001) and that of Bifidobacteriumwas 0.95 (95% CI 0.81–1.00; p= 0.0275), suggesting that Bifidobacteriumcorrelated with ALT (r= 0.783, p< 0.01) may be a potential biomarker for AFB1 exposure in sheep.

An interpenetrated indium pyridylcarboxylate framework, [NH2(CH3)2][In(L)2]·2.5DMF·5H2O (1), has been synthesized by employing a pyridylcarboxylate ligand, 4-(3-carboxylphenyl)picolinic acid (H2L), and an In3+ion, with both chemical stability and framework flexibility. The desolvated 1exhibits an uncommon breathing sorption behavior and shows highly selective adsorption for C2H2, C2H4, and CO2over CH4. Furthermore, 1shows rapid and higher adsorption efficiency for methylene blue and neutral red in aqueous solution.

With the aim of simulating the harsh temperature condition of space, a thallium-activated cesium iodide crystal (CsI:Tl) detector readout with a PIN photodiode (CsI:Tl(PD)) and with a silicon photomultiplier (CsI:Tl(SiPM)) is investigated over a temperature range from − 40 to 40 °C. With the increase in temperature, the output signal increases by ~ 24% with CsI:Tl(PD) and decreases by ~ 69% with CsI:Tl(SiPM). To reduce the effect of temperature in outer space, a method of bias voltage compensation is adopted for CsI:Tl(SiPM). Our study demonstrates that after correcting the temperature the variation in the analog-to-digital converter’s amplitude is < 3%.

By employing a pyridyl-decorated dicarboxylic acid ligand, 3-(2′,5′-dicarboxylphenyl)pyridine acid (H2dcpy), a three-dimensional In3+-based metal–organic framework, H3O[In3(dcpy)4(OH)2]·3DMF·4H2O (1), with a good chemical stability toward acid and base has been synthesized. The compound 1shows an uncommon (3,8)-connected tfz-d; UO3topological net based on linear In3(COO)4(OH)2clusters and also contains one-dimensional open channels. Particularly, 1contains two types of dcpy2–linkers, in which the pyridyl group in one participates in coordination with the In3+ion, whereas that in the other is uncoordinated but hangs in the inner sides of the channels as functionalized sites. Gas adsorption experiments demonstrate that 1is able to selectively adsorb C2H2, C2H4, and CO2over CH4. Simultaneously, 1shows a highly selective and sensitive fluorescence detection toward Fe3+ion in water with good recyclability.

UPU structured lipids refer to a class of functional lipids that are connected to palmitic acid (PA, 16:0) at the sn-2position and unsaturated fatty acid (UFA) at the sn-1,3positions. UPU structured lipids are ingredients of infant formula and are beneficial to fat absorption in infants and young children. At present, the research on UPU structured lipids is mainly focused on species identification, physiological functions and preparation methods. In this paper, we summarize the natural oils and fats enriched with PA at the sn-2position, which can be used as a substrate for the enzymatic preparation of UPU. In addition, the emerging fermentation method for the preparation of UPU structured lipids was briefly reviewed aiming to provide scientific reference for the in-depth investigation of UPU structured lipids.

A tracking system composed of three multi-wires proportional chambers (MWPCs) for the external target facility of the Cooler Storage Ring is reported in this paper. The active areas of the MWPCs are 518 mm × 400 mm, 582 mm × 450 mm, and 710 mm × 500 mm. Each MWPC consists of a series of alternately placed cathode and anode wire planes and can measure position along the directions of −30°, 0°, and 30° relative to horizontal. The construction and operation of the detectors are described, and a method for track reconstruction is introduced. A track-finding efficiency of about 62% and a spatial resolution of 1.21 mm have been achieved. The pion and proton can be identified clearly with the tracking system combined with a time-of-flight system.

Description: In this review, we emphasize the importance of advanced characterization techniques in relation to microstructures and properties of SPEs, especially emerging analysis technology such as cryo-TEM.

Beginning with the definition of autonomous time reference and its generation principle, the relativistic effects on the essential factors including satellite clock relativity and crosslink measurements relativity are analyzed in this paper, and calculated by taking GPS and BDS constellations for examples. The following conclusions are reached: 1) the satellite clock relativity effect has a constant part and a periodic part, and the constant part is compensated by terrestrial frequency adjustment, while the periodic clock error is corrected in real time according to the ephemeris; on the basis of the adjustment of the satellite clock, 2) the crosslink pseudo-range (PR) measurement relativity effect between satellites inview is mainly the relativity effect on the light time delay, and can reach cm-level for medium and high orbits satellite; 3) the crosslink Doppler measurement relativity effect is due to the period part of clock frequency offset, and its effect on radial velocity is around 1cm/s for medium and high orbits satellite with small eccentricity. The above-mentioned analyses can help to improve the accuracy of autonomous time reference, and provide certain reference significance for the research of deep-space measurement and space-based time reference establishment. [ABSTRACT FROM AUTHOR]

In view of the large dynamic and fast acquisition requirement of inter-satellite link ( ISL) signal in navigation constellation, signal acquisition is aided with ephemeris. The computational costs of serial search, code parallel search and frequency parallel search are analyzed. Calculation expressions of the corresponding search strategies are given according to different signal systems and ephemeris errors and for typical applications of the example analysis. Results show that the serial search strategy has the least amount of calculation when the ephemeris error is small and the code parallel search strategy has the least amount of calculation when the ephemeris error is large. [ABSTRACT FROM AUTHOR]

The paper proposes a new method for a targets trajectory, assumed to be linear and uniform, based on the observation of its speed and bearings. After introducing the new method based on assumed model, the paper analyzes the relative error of range estimation caused by speed and bearings estimations relative error; The results of target motion analysis (TMA) is optimized by linearizing the model and using kalman filter. Pond test shows that relative error of range estimation calculated by this method is less than 10-1.

Extended, continuous measuring and analysis for underwater ambient noise can find the objects like ships and submarine. It is important for passive detection of underwater object. A real-time processing method of one-third octave spectrum is presented. It is shown by tests that the method is steady and satisfy the real-time processing.

As the low-band is more and more crowded, moving to Ka-band for the satellite-ground measurement and communication is preferred in the literature. This paper aims to contribute to the understanding of the influence of the atmosphere on the range error and the attenuation in Ka-band. By adopting the method recommended by ITU-R, we analyze the delay range error and the attenuation induced by the ionosphere and troposphere for Ka-band. The result shows that the ionosphere delay range error is significantly reduced in Ka-band comparing with navigation band. The maximal ionosphere delay range error is about 1m in Ka-band. The troposphere delay range error in Ka-band is the same as that in navigation band. When the elevation angle is over 40º, the troposphere delay range error become flat and doesnt exceed approximately 4 m. With respect to atmospheric attenuation, two important findings are obtained: firstly, when the elevation angle is over 40º, the atmospheric attenuation doesnt change significantly and is generally below 2 dB. Secondly, the atmospheric attenuation reaches its peak at the frequency of approximately 22.5GHz in Ka-band. Finally, an important conclusion can be drawn that in the design of the Ka-band satellite-ground measurement system, it should be considered to make the system work at the elevation angle over 40º. Thus, in generally, the range error doesnt exceed 5 m and the attenuation doesnt exceed 2 dB, even though it doesnt make the model correction.

Two coordination polymers based on 1, 6‐bis(2‐methyl‐imidazole‐1‐yl)‐hexane (bimh), namely {[Zn3(BTC)2(bimh)]·(bimh)}n(1) and {[Zn(IPA)(bimh)]·(CH3CH2OH)0.5}n(2) (H3BTC = trimesic acid, H2IPA = isophthalic acid), were synthesized through hydrothermal reactions. In compound 1, the zinc(II) ions are bridged by BTC3–ligands to form an undulating infinite two‐dimensional (2D) polymeric network. The 3D networks of 1show a twofold interpenetrating net. In compound 2, zinc(II) ions are bridged by IPA2–ligands to form one‐dimensional (1D) helical structures. The 2D structures of 2are further assembled into 3D networks through aromatic π–π stacking interactions. Both compounds exhibit strong photoluminescence at room temperature and may be good candidates for potential luminescence materials.

Two new coordination polymers, [Zn(PyHBIm)2(IPA)]•3H2O (1), [Cd(PyHBIm)(IPA)(H2O)2]•2H2O (2), were synthesized under hydrothermal conditions based on 2-(3-pyridyl)benzimidazole (3-PyHBIm) and isophthalic acid (IPA). The complexes were characterized by single crystal X-ray diffraction. They contain simple 1D chains and can be assembled into a 3D network through aromatic π–π stacking interactions and hydrogen bonding interactions. Their luminescent properties were studied in the solid state at room temperature.

Abstract: Knockout reaction experiment was carried out by using the 6He beams at 61.2 MeV/u impinging on a CH2 target. The α core fragments at forward angles were detected in coincidence with the recoiled protons at larger angles. From this exclusive measurement the valence nucleon knockout mechanism and the core knockout mechanism can be distinguished by the relation between the polar angles of the core fragments and the recoiled protons, respectively. It is demonstrated that the core knockout mechanism may result in some strong contamination to the real invariant mass spectrum.