Automatic modulation recognition of radio fuzes using a DR2D-based adaptive denoising method and textural feature extraction

The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.

Zn^(2+)和TiO_(2)合金化过程中不同成分占比对薄膜结构和光催化性能的影响

使用溶胶-凝胶法在单晶硅衬底上制备一批不同Zn^(2+)成分调节的TiO_(2)薄膜,观测Zn^(2+)和TiO_(2)合金化过程中光学和光催化性能的变化.X射线衍射光谱仪用于观测在合金化过程中薄膜的晶体结构变化并追踪ZnTiO_(3)化合物的形成.扫描电子显微镜、原子力显微镜用于观测合金化过程中因TiO_(2)晶格对Zn^(2+)溶解度有限而导致薄膜表面出现大量孔洞的现象.X射线光电子能谱和光学带隙用于观测Zn^(2+)与TiO_(2)合金化过程中电子结构层面的变化.最后,通过降解亚甲基蓝(MB)溶液,表明少量Zn^(2+)掺杂完全溶解在TiO_(2)中,并破坏TiO_(2)结晶质量.在Zn^(2+)的成分占比继续提高至15%的过程中,XPS峰形拟合结果验证了TiO_(2)对Zn^(2+)的溶解度有限,导致薄膜出现大量孔洞结构,薄膜的活性比表面积得以提升,同时Zn^(2+)可以有效地捕获光生e^(-)/h^(+).为了继续观察Zn^(2+)浓度对TiO_(2)的影响,将Zn^(2+)的浓度提升至40%,观察Zn^(2+)与TiO_(2)合金化过程中的现象.表明化合物ZnTiO_(3)的出现可以充当e^(-)/h^(+)的复合中心以及TiO_(2).占比的大幅下降导致合金化之后的薄膜光催化效率逐渐下降.

Plasma-assisted aerogel interface engineering enables uniform Zn^(2+)flux and fast desolvation kinetics toward zinc metal batteries

The poor reversibility of Zn anodes induced by dendrite growth,surface passivation,and corrosion,severely hinders the practical applicability of Zn metal batteries.To address these issues,a plasmaassisted aerogel(PAG)interface engineering was proposed as efficient ion transport modulator that can simultaneously regulate uniform Zn^(2+)flux and desolvation behavior during battery operation.The PAG with ordered mesopores acted as an ion sieve to homogenize Zn deposition and accelerate Zn^(2+)flux,which is favorable for corrosion resistance and dendrite suppression.Importantly,the plasma-assisted aerogel with abundant hydrophilic groups can facilitate the desolvation kinetics of Zn^(2+)due to the multiple hydrogen-bonding interaction with the activated water molecules,thus accelerating the Zn^(2+)migration kinetics.Consequently,the Zn/Zn cell assembled with PAG-modified separator demonstrates stable plating and stripping behavior(over 1400 h at 1 mA cm^(-2))and high Coulombic efficiency(99.8%at1 mA cm^(-2)after 1100 cycles),and the Zn‖MnO_(2)full cell shows excellent long-term cycling stability and maintains a high capacity of 154.9 mA h g^(-1)after 1000 cycles at 1 A g^(-1).This study provides a feasible approach for the large-scale fabrication of aerogel functionalized separators to realize ultra-stable Zn metal batteries.

基于不同荧光发色基团的Zn^(2+)荧光探针的研究进展

荧光光谱法具有灵敏度高、选择性好、检出限低以及操作简单等特点,设计合成特异性识别和检测Zn^(2+)的荧光探针对化学、生物学、临床医学等研究具有十分重要的意义。以近年来文献报道的Zn^(2+)荧光探针为例,综述了基于不同荧光发色基团的Zn^(2+)荧光探针的作用机制、应用与发展前景,为Zn^(2+)荧光探针研究提供了参考(引用文献44篇)。

Deep learning-based activity recognition and fine motor identification using 2D skeletons of cynomolgus monkeys

Video-based action recognition is becoming a vital tool in clinical research and neuroscientific study for disorder detection and prediction.However,action recognition currently used in non-human primate(NHP)research relies heavily on intense manual labor and lacks standardized assessment.In this work,we established two standard benchmark datasets of NHPs in the laboratory:Monkeyin Lab(Mi L),which includes 13 categories of actions and postures,and MiL2D,which includes sequences of two-dimensional(2D)skeleton features.Furthermore,based on recent methodological advances in deep learning and skeleton visualization,we introduced the Monkey Monitor Kit(Mon Kit)toolbox for automatic action recognition,posture estimation,and identification of fine motor activity in monkeys.Using the datasets and Mon Kit,we evaluated the daily behaviors of wild-type cynomolgus monkeys within their home cages and experimental environments and compared these observations with the behaviors exhibited by cynomolgus monkeys possessing mutations in the MECP2 gene as a disease model of Rett syndrome(RTT).Mon Kit was used to assess motor function,stereotyped behaviors,and depressive phenotypes,with the outcomes compared with human manual detection.Mon Kit established consistent criteria for identifying behavior in NHPs with high accuracy and efficiency,thus providing a novel and comprehensive tool for assessing phenotypic behavior in monkeys.

Using Speaker-Specific Emotion Representations in Wav2vec 2.0-Based Modules for Speech Emotion Recognition

Speech emotion recognition is essential for frictionless human-machine interaction,where machines respond to human instructions with context-aware actions.The properties of individuals’voices vary with culture,language,gender,and personality.These variations in speaker-specific properties may hamper the performance of standard representations in downstream tasks such as speech emotion recognition(SER).This study demonstrates the significance of speaker-specific speech characteristics and how considering them can be leveraged to improve the performance of SER models.In the proposed approach,two wav2vec-based modules(a speaker-identification network and an emotion classification network)are trained with the Arcface loss.The speaker-identification network has a single attention block to encode an input audio waveform into a speaker-specific representation.The emotion classification network uses a wav2vec 2.0-backbone as well as four attention blocks to encode the same input audio waveform into an emotion representation.These two representations are then fused into a single vector representation containing emotion and speaker-specific information.Experimental results showed that the use of speaker-specific characteristics improves SER performance.Additionally,combining these with an angular marginal loss such as the Arcface loss improves intra-class compactness while increasing inter-class separability,as demonstrated by the plots of t-distributed stochastic neighbor embeddings(t-SNE).The proposed approach outperforms previous methods using similar training strategies,with a weighted accuracy(WA)of 72.14%and unweighted accuracy(UA)of 72.97%on the Interactive Emotional Dynamic Motion Capture(IEMOCAP)dataset.This demonstrates its effectiveness and potential to enhance human-machine interaction through more accurate emotion recognition in speech.

An Activity Recognition System at Home Based on CO2 Sensors

Activity recognition of indoor occupants using indirect sensing with less privacy violation is one of the hot research topics. This paper proposes a CO2 sensor-based indoor occupant activity monitoring system. Using the IoT sensor node that contains CO2 sensors, the measured CO2 concentrations in three locations (laboratory, office, and bedroom) were stored in a cloud server for up to 35 days starting July 1, 2023. The CO2 measurements stored at 30-second intervals were statistically processed to produce a heat-mapped display of the hourly average or maximum CO2 concentration. From the heatmap visualizations of CO2 concentration, the proposed system estimated meeting, heating water using a portable stove, and sleep for the occupants’ activity recognition.

Zn^(2+)/Zn和Fe^(3+)/Fe^(2+)的电化学行为及其在液流电池中的应用

锌铁液流电池采用成本低廉的锌、铁元素作为活性物质,有望成为下一代高性价比储能电池。本文利用循环伏安法测试锌、铁离子在碳毡电极表面的电化学活性,计算Zn^(2+)/Zn与Fe^(3+)/Fe^(2+)的扩散系数与反应速率常数。结果表明,锌离子与铁离子在多孔碳毡上具有良好的电化学性能,可以作为锌铁液流电池的活性物质。充放电测试结果表明,锌铁液流电池的充放电性能良好,它具有较高的电流效率、电压效率和能量效率。

连续识别Zn^(2+)和草甘膦荧光探针的合成与应用

以2-巯基苯并噻唑为原料,设计合成了一种结构简单的苯并噻唑类荧光探针2-[2-(苯并噻吩-2-基亚甲基)肼基]苯并噻唑(简称NSS),并通过FTIR、HRMS、^(1)HNMR、^(13)CNMR对其结构进行了表征。荧光光谱表明,在二甲基亚砜中,探针NSS实现了Zn^(2+)的“关-开”型检测,具有响应时间短(30 s)、特异性强、抗干扰性强等优点。探针NSS荧光强度与Zn^(2+)浓度(0~11μmol/L)呈现良好的线性关系,检出限达19.1 nmol/L,并与Zn^(2+)形成物质的量比为1∶1的络合物。同时,络合物NSS-Zn^(2+)对草甘膦呈现特异性的荧光猝灭响应,猝灭率达99.4%,检出限16.0 nmol/L(2.71 ng/mL),且不受其他有机磷农药的干扰。

一种基于联萘酚和(R,R)-Salen的高分子荧光探针的合成及对Zn^(2+)的识别研究

利用Sonogashira偶联反应设计合成了一种含有联萘酚和(R,R)-Salen单元的共轭高分子荧光探针P-1,并通过核磁共振氢谱表征了其结构。荧光光谱分析实验结果表明,高分子荧光探针P-1对Zn^(2+)具有高选择性识别,表现出明显的荧光增强,检测限可达到28.11 nmol·L^(-1),因此,高分子荧光探针P-1也具有较高的灵敏度。

Zn^(2+)与腐殖酸钠组合抑制剂对萤石、方解石浮选分离的影响及机理研究

常见的方解石型萤石矿由于方解石与萤石表面物理化学性质相似,两者的浮选分离较为困难。本文研究了ZnSO_(4)·7H_(2)O与腐殖酸钠组合抑制剂对萤石和方解石选择性分离浮选的影响,通过吸附量测定、XPS检测、红外光谱分析以及溶液化学计算进行了机理分析。实验结果表明,相比于单一腐殖酸钠抑制剂,当使用腐殖酸钠与ZnSO_(4)·7H_(2)O质量比为3∶1的组合抑制剂且其用量为20 mg/L、油酸钠用量为1.5×10^(-4)mol/L、pH为7的条件下,可使萤石、方解石浮选回收率之差由41.8百分点提高到70.31百分点。腐殖酸钠与Zn^(2+)发生化学反应生成的腐殖酸锌与单一抑制剂相较方解石表面腐殖酸根吸附量有所提高;而萤石表面腐殖酸根吸附量减少,更多活性位点与油酸钠结合,油酸钠的吸附量提高,进而提高了组合抑制剂在两种矿物表面的选择性吸附,最终达到浮选分离的目的。

Zn^(2+)-Ni^(2+)-Al^(3+)-类水滑石@Al薄膜制备及其光催化性能

含过渡金属元素的类水滑石(LDHs)材料在可见光催化领域显示了广泛应用前景.然而LDHs粉末在催化反应中难回收、易流失,不利于材料的循环利用.以铝板为基体,通过原位生长技术在基体表面原位生长Zn^(2+)-Ni^(2+)-Al^(3+)-LDHs,开辟制备Zn^(2+)-Ni^(2+)-Al^(3+)-LDHs@Al材料的新方法.研究表明,Zn^(2+)-Ni^(2+)-Al^(3+)LDHs薄膜在铝基底纵向生长,具有高取向性.LDHs结晶度较高,片层结构规整,极大暴露了LDHs催化活性较高的层板边缘.该薄膜材料具有较低禁带宽度、较高可见光催化活性.Zn^(2+)-Ni^(2+)-Al^(3+)-LDHs@Al能够有效降解甲基橙(MO)有机染料废水,多次循环后对染料的降解率可达98%.该材料极大的增强了对光的利用率,促进了光生电子和空穴对的分离和转移,提高了材料光催化活性,推动和强化了LDHs材料的循环利用及综合处理废水的能力,提高了其应用价值和应用范围,为LDHs材料的开发、设计及应用提供了新思路.

Boosting Zn^(2+)kinetics via the multifunctional pre-desolvation interface for dendrite-free Zn anodes

Aqueous zinc ion batteries(AZIBs)are an advanced secondary battery technology to supplement lithiumion batteries.It has been widely concerned and developed recently based on the element abundance and safety advantages.However,AZIBs still suffer from serious problems such as dendrites Zn,hydrogen evolution corrosion,and surface passivation,which hinder the further commercial application of AZIBs.Herein,an in-situ ZnCr_(2)O_(4)(ZCO)interface endows AZIBs with dendrite-free and ultra-low polarization by realizing Zn^(2+)pre-desolvation,constraining H2O-induced corrosio n,and boosting Zn^(2+)transport/deposition kinetics.The ZCO@Zn anode harvests an ultrahigh cumulative capacity of~20000 mA h cm^(-2)(cycle time:over 4000 h)at a high current density of 10 mA cm^(-2),indicating excellent reversibility of Zn deposition,Such superior performance is among the best cyclability in AZIBs.Moreover,the multifunctional ZCO interface improves the Coulombic efficiency(CE)to 99.7%for more than 2600 cycles.The outstanding electrochemical performance is also verified by the long-term cycle stability of ZCO@Zn//α-MnO_(2) full cells.Notably,the as-proposed method is efficient and low-cost enough to enable mass production.This work provides new insights into the uniform Zn electrodeposition at the scale of interfacial Zn^(2+)predesolvation and kinetics improvement.

2DPCA versus PCA for face recognition

Dimensionality reduction methods play an important role in face recognition. Principal component analysis(PCA) and two-dimensional principal component analysis(2DPCA) are two kinds of important methods in this field. Recent research seems like that 2DPCA method is superior to PCA method. To prove if this conclusion is always true, a comprehensive comparison study between PCA and 2DPCA methods was carried out. A novel concept, called column-image difference(CID), was proposed to analyze the difference between PCA and 2DPCA methods in theory. It is found that there exist some restrictive conditions when2 DPCA outperforms PCA. After theoretical analysis, the experiments were conducted on four famous face image databases. The experiment results confirm the validity of theoretical claim.

Synthesis,Crystal Structure and Recognition Properties of a New Benzothiazole Derivative：C28H24N4O2S

A benzothiazole-based compound 1, C28H24N4O2S, has been synthesized and characterized by single-crystal X-ray diffraction. It crystallizes in monoclinic, space group P21/c with a = 9.6309（14）, b = 15.230（2）, c = 17.197（3）A, β = 105.222（2）°, V = 2433.9（6） A^3, Z = 4, F（000） = 1008, Dc = 1.311 Mg/m^3, Mr = 480.57, μ = 0.166 mm^-1, the final R = 0.0509 and wR = 0.1481 for 6643 observed reflections with I 〉 2σ（I）. The crystal structure of compound 1 is stabilized by C–H…O, N–H…N, N–H…O, O–H…N and C–H…N hydrogen bonds. The spectroscopic studies of the title compound toward various metal ions were also investigated in 25%（V/V） ethanol aqueous solution, and the result showed that it can selectively recognize Cu^2＋ with fluorescence quenching.

4-Tert-butyl-N′-((2-Hydroxynaphthalen-1-yl)methylene)Benzohydrazide:Synthesis,Crystal Structure and Recognition Properties

A new naphthol-based compound 1, C22 H22 N2 O2, has been designed and synthesized. The structure of the title compound 1 was confirmed by IR, 1 H NMR, 13 C NMR, H RMS, and X-ray single-crystal diffraction. The crystal belongs to the monoclinic system, space group P21/c, with a = 12.888（9）, b = 15.543（10）, c = 9.119（6） ？, β = 94.05（3）°, V = 1822（2） ？3, Z = 4, Dc = 1.263 g/cm3, Mr = 346.41, μ = 0.081 mm-1, F（000） = 736.0, the final R = 0.0452 and wR = 0.1142 for 3404 observed reflections with（I 〉 2σ（I））. The crystal structure of 1 is stabilized by O–H···N, N–H···O, C–H···O hydrogen bonds and π-π interactions. The spectroscopic studies of 1 toward various metal ions were also investigated in 25%（V/V） ethanol aqueous solution, and the result showed that it can selectively recognize Zn2＋ with fluorescence enhancement.

Sn-doped BiOCl nanosheet with synergistic H^(+)/Zn^(2+)co-insertion for“rocking chair”zinc-ion battery

The development of insertion-type anodes is the key to designing“rocking chair”zinc-ion batteries.However,there is rare report on high mass loading anode with high performances.Here,{001}-oriented Bi OCl nanosheets with Sn doping are proposed as a promising insertion-type anode.The designs of cross-linked CNTs conductive network,{001}-oriented nanosheet,and Sn doping significantly enhance ion/electron transport,proved via experimental tests and theoretical calculations(density of states and diffusion barrier).The H^(+)/Zn^(2+)synergistic co-insertion mechanism is proved via ex situ XRD,Raman,XPS,and SEM tests.Accordingly,this optimized electrode delivers a high reversible capacity of 194 m A h g^(-1)at 0.1 A g^(-1)with a voltage of≈0.37 V and an impressive cyclability with 128 m A h g^(-1)over 2500 cycles at 1 A g^(-1).It also shows satisfactory performances at an ultrahigh mass loading of 10 mg cm^(-2).Moreover,the Sn-Bi OCl//MnO_(2)full cell displays a reversible capacity of 85 m A h g^(-1)at 0.2 A g^(-1)during cyclic test.

基于长短期记忆网络的CO_(2)气层识别方法

CO_(2)监测是油气开采中的关键环节,传统的CO_(2)监测方法面临很多挑战,在人工智能逐渐兴起的当下,深度学习技术被广泛应用于地球物理测井。珠江口盆地恩平凹陷深层CO_(2)气藏发育,传统测井方法无法准确评价储层流体。构建了基于长短期记忆网络(LSTM)的CO_(2)气层识别模型,采用m×2正则化交叉验证优选CO_(2)敏感测井参数,并对模型进行训练。利用该模型对珠江口盆地恩平凹陷L2井CO_(2)气层进行识别,并与支持向量机和K近邻算法识别结果进行对比。结果表明,3种深度学习算法对CO_(2)气层的识别效果良好,其中LSTM算法对CO_(2)气层的识别效果最好,准确度达93.4%,为深层CO_(2)气层识别工作提供了新思路。

焙烧镁铝类水滑石对Cd^(2+)、Cu^(2+)、Zn^(2+)的吸附性能研究

通过控制变量法考察温度、浓度对焙烧镁铝类水滑石得到的层状双金属氧化物(LDO)吸附Cd^(2+)、Cu^(2+)、Zn^(2+)单一离子及其共存体系的影响。结果表明,LDO对单一离子吸附效果均较好,温度升高,有利于LDO吸附Cd^(2+)、Cu^(2+)、Zn^(2+);Cu^(2+)-Cd^(2+)、Cd^(2+)-Zn^(2+)共存时,LDO吸附效果为Cu^(2+)> Cd^(2+)、Zn^(2+)> Cd^(2+);三者共存时,LDO吸附效果为Cu^(2+)> Zn^(2+)> Cd^(2+)。

光谱法研究Zn^(2+)与TEVp之间的相互作用

为了探究金属离子对TEVp结构和功能的影响,促进TEVp在去除重组蛋白融合标签中的应用,采取荧光光谱、圆二色谱等光谱方法研究TEVp与Zn^(2+)之间的相互作用。紫外光谱及内源荧光实验结果表明,TEVp与Zn^(2+)的相互作用为静态淬灭机制。同步荧光光谱、三维荧光光谱以及圆二色谱实验结果表明,TEVp与Zn^(2+)的结合会引起蛋白构象发生改变,导致TEVp的β-折叠结构降低,α-螺旋结构增加,蛋白色氨酸残基微环境发生改变,造成疏水性增强、极性减弱。