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Funder: Deutsche Forschungsgemeinschaft, A tetrahedral FeII4L4 cage assembled from the coordination of triangular chiral, face-capping ligands to iron(II). This cage exists as two diastereomers in solution, which differ in the stereochemistry of their metal vertices, but share the same point chirality of the ligand. The equilibrium between these cage diastereomers was subtly perturbed by guest binding. This perturbation from equilibrium correlated with the size and shape fit of the guest within the host; insight as to the interplay between stereochemistry and fit was provided by atomistic well-tempered metadynamics simulations. The understanding thus gained as to the stereochemical impact on guest binding enabled the design of a straightforward process for the resolution of the enantiomers of a racemic guest.

IntroductionSalbutamol (SAL) is a β2 adrenergic receptor agonist which has potential hazardous effects for human health. It is very important to establish a sensitive and convenient method to monitor SAL.MethodsHere we introduce a method to combine the information from docking and site specific phage display, with the aim to obtain scFv with high affinity to SAL. First, single chain variable fragment (scFv) antibodies against SAL were generated through phage display. By using molecular docking approach, the complex structure of SAL with antibody was predicted and indicated that H3 and L3 contribute to the binding. Then new libraries were created by randomization specific residues located on H3 and L3 according to the docking results.Results and discussionAnti-SAL scFv antibodies with high efficiency were finally identified. In addition, the selected scFv was fused with alkaline phosphatase and expressed in E coli to develop a rapid and low-cost one step ELISA to detect SAL.

The operation flexibility of the power system suffers great challenges due to the vigorously developing of renewable energy resources under the promotion of the carbon neutralization goal. To this end, this paper proposes an economical and flexible energy scheduling method for power system integrated with multiple generation resources while considering the operation of low-carbon. Specifically, flexibility evaluation indexes are constructed to describe the characteristics of the flexible generation units. Then they are connected with the flexibility of the power system in an economic and low-carbon flexible energy scheduling model. To coordinate the operation economy, flexibility, and carbon emission reduction, the model incorporates demand response, operational characteristics, and flexibility requirements. Further, the model is fully validated through the simulation on the modified IEEE 30-bus system. Results demonstrate that: the proposed method can reduce the system’s carbon emission and total operating costs and promote photovoltaic consumption.

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Additional file 2: Fig S1. Detailed steps of strain mutagenesis. TC: Tube cultivation; ARTP: Atmospheric and room temperature plasma; FACS: Fluorescence activated cell sorting; PC: Plate cultivation; 96-WMP: 96-Well microtiter plate; MMR: Multimode microplate reader; SFC: Shake flask cultivation; HPLC: High performance liquid chromatography. Fig S2. Trends of transcription levels of DEGs in different metabolic pathways. a. X16 vs. X24. b. X24 vs. X48.Red indicates significantly up, green indicates significantly down, and black indicates no significant difference. Fig S3. The Glu determination of supernatant of fermentation broth in different periods. Experiments were conducted in triplicate and measurements are represented as the means ± S.D.

Additional file 4: Figure S4. (A) Heatmap showing numbers of CNs across different ccRCC tissues. Scale bar represents the number of CNs, with a maximum limit of 10. (B) Comparison of the proportions of different cell components in CNs between the scattered-CN-cold and scattered-CN-hot phenotypes. (C) Representative IMC images showing the scattered-CN-cold ccRCC tissues (P15 and P14) with the characteristic CNs.

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SI Figures and Calculations

Additional file 2: Figure S2. (A) Heatmap representing the abundance of 7 major cells across different ccRCC tissues. The proportions were normalized by z-score for visualization. (B) Mean density curves showing the expression of 17 markers across total cells from 75 ccRCC tissues, respectively. The knee points are set as threshholds to determine the positive cells. (C) Comparison of survivals between high and low immune cell groups. High group, tissues with proportion of the immune cells ≥the third quartile (Q3); Low group, tissues with proportion of the immune cells ≤the first quartile (Q1). (D) Annotation rules for determining subtypes of T cells and macrophages.

Additional file 5: Figure S5. (A) Heatmap depicting the various immune CNs across the 5 cases with metastatic ccRCC. (B) The difference in CNs between the responder and non-responder groups. (C) Representative IMC images of non-responder (cases 4 and 5) showing the macrophage/T-clustered characteristics. (D) Representative IMC images of responders (cases 1, 2 and3) displaying the scattered-CN-hot characteristics. (E) Survival analysis between the responder and non-responder groups.

Additional file 3: Figure S3. (A) Survival analysis between the scattered and clustered groups. (B) Comparison of clinical characteristics between the TLS-like and macrophage/T-clustered phenotypes. (C) Comparison of clinical characteristics between the scattered-CN-hot and scattered-CN-hot phenotypes. (D) Survival analysis between scattered-CN-cold, scattered-CN-hot and macrophage/T-clustered phenotypes.

Additional file 1: Figure S1. (A) Combined tSNE plot illustrating the origin of the 27 cell clusters, which are colored according to tissues. The letter A reflects the paracancerous tissue, the letter T reflects the cancerous tissue. (B) Proportions of the 27 cell clusters in total cells from the 13 ccRCC and paired paracancerous tissues. (C) tSNE plots depicting the expression of 17 markers across the 27 cell clusters, respectively. (D) Comparison of the proportion of 27 cell clusters between the ccRCC and paired paracancerous tissues.

Compositionally complex ceramics (CCCs), including high-entropy ceramics (HECs) as a subclass, offer new opportunities of materials discovery beyond the traditional methodology of searching new stoichiometric compounds. Herein, we establish new strategies of tailoring CCCs via a seamless combination of (1) non-equimolar compositional designs and (2) controlling microstructures and interfaces. Using oxide solid electrolytes for all-solid-state batteries as an exemplar, we validate these new strategies via discovering a new class of compositionally complex perovskite oxides (CCPOs) to show the possibility of improving ionic conductivities beyond the limit of conventional doping. As an example (amongst the 28 CCPOs examined), we demonstrate that the ionic conductivity can be improved by >60% in (Li0.375Sr0.4375)(Ta0.375Nb0.375Zr0.125Hf0.125)O3-{\delta}, in comparison with the state-of-art (Li0.375Sr0.4375)(Ta0.75Zr0.25)O3-{\delta} (LSTZ) baseline, via maintaining comparable electrochemical stability. Furthermore, the ionic conductivity can be improved by another >70% via grain boundary (GB) engineering, achieving >270% of the LSTZ baseline. This work suggests transformative new strategies for designing and tailoring HECs and CCCs, thereby opening a new window for discovering materials for energy storage and many other applications.

Studying the impact of the environment on metal corrosion is of considerable significance for the safety assessment of buildings and the life prediction of equipment. We developed a new regional environmental corrosion model (RECM) to predict the atmospheric corrosion of Q235 carbon steel based on measured environmental data and corrosion rates obtained from one-year-long static coupon tests. The corrosion of metals varies depending on the environment; therefore, the ability of the model to distinguish such differences is crucial for accurately predicting corrosion. Herein, the regions in which the test sites were located were divided based on the basic principles of atmospheric corrosion. Furthermore, random forest was used to assess the importance of various environmental factors in the corrosion process within each region, which established a close relationship between corrosion and environmental conditions. Our results showed that the accuracy of the RECM is higher than that of the dose-response function of the ISO9223-2012 standard. The method of model construction can be realized automatically using a computer.

This work provides a data-oriented overview of the rapidly growing research field covering machine learning (ML) applied to predicting electrochemical corrosion. Our main aim was to determine which ML models have been applied and how well they performed depending on the corrosion topic considered. From an extensive review of corrosion articles presenting comparable performance metrics, a ‘Machine learning for corrosion database’ was created, guiding corrosion experts and model developers in their applications of ML to corrosion. Potential research gaps and recommendations are discussed, and a broad perspective for future research paths is provided.

A channel should be built to transmit information from one place to another. Imaging is 2 or higher dimensional information communication. Conventionally, an imaging channel comprises a lens and free spaces of its both sides. The transfer function of each part is known; thus, the response of a conventional imaging channel is known as well. Replacing the lens with a scattering layer, the image can still be extracted from the detection plane. That is to say, the scattering medium reconstructs the channel for imaging. Aided by deep learning, we find that different from the lens there are different channels in a scattering medium, i.e., the same scattering medium can construct different channels to match different manners of source encoding. Moreover, we found that without a valid channel the convolution law for a shift-invariant system, i.e., the output is the convolution of its point spread function (PSF) and the input object, is broken, and information cannot be transmitted onto the detection plane. In other words, valid channels are essential to transmit image information through even a shift-invariant system., Comment: 10 pages, 4 figures

Knowledge graph embedding~(KGE) aims to represent entities and relations into low-dimensional vectors for many real-world applications. The representations of entities and relations are learned via contrasting the positive and negative triplets. Thus, high-quality negative samples are extremely important in KGE. However, the present KGE models either rely on simple negative sampling methods, which makes it difficult to obtain informative negative triplets; or employ complex adversarial methods, which requires more training data and strategies. In addition, these methods can only construct negative triplets using the existing entities, which limits the potential to explore harder negative triplets. To address these issues, we adopt mixing operation in generating harder negative samples for knowledge graphs and introduce an inexpensive but effective method called MixKG. Technically, MixKG first proposes two kinds of criteria to filter hard negative triplets among the sampled negatives: based on scoring function and based on correct entity similarity. Then, MixKG synthesizes harder negative samples via the convex combinations of the paired selected hard negatives. Experiments on two public datasets and four classical KGE methods show MixKG is superior to previous negative sampling algorithms.

The idea of preparing a technical document for the repairs and interventions upon concrete structures goes back to the former fib COM 5: Structural Service Life Aspects, being the goal of the then TG 5.9. After a long period of reduced activity, and taking into account the reorganization of fib commissions that meanwhile took place, on June 2017 a different approach was proposed to push forward the task of TG 8.1 (formerly TG 5.9).The (new) goal of TG 8.1 was to deliver a ‘how-to-do’ guide, gathering together protection, repair, and strengthening techniques for concrete structures. Chapters are intended to provide both guidelines and case-studies, serving as support to the application of fib MC 2020 pre-normative specifications.Each chapter was written by an editorial team comprising desirably at least a researcher, a designer and a contractor. Templates have been prepared in order to harmonize the contents and the presentation of the different methods. Following the writing process, chapters were reviewed by experts and, after amendments by the authors, they underwent a second review process by COM 8 and TG 3.4 members, as well as by different practitioners.For each protection, repair and strengthening method addressed in this guide, readers have a description of when to adopt it, which materials and systems are required, which techniques are available, and what kind of equipment is needed. It then presents a summary of stakeholders’ roles and qualifications, design guidelines referring to most relevant codes and references, the intervention procedure, quality control measures and monitoring and maintenance activities. Due to the extent of the guide, it was decided to publish it as bulletin 102, addressing protection and repair methods, and bulletin 103, addressing strengthening methods.We would like to thank the authors, reviewers and members of COM 8 and TG 3.4 for their work in developing this fib Bulletin, which we hope will be useful for professionals working in the field of existing concrete structures, especially those concerned with life-cycle management and conservation activities.As noted above, this Bulletin is also intended to act as a background and supporting document to the next edition of the fib Model Code for Concrete Structures, which is currently under development under the auspices of TG10.1 with the working title of ‘fib Model Code 2020’.Eduardo Júlio and Eduardo Cavaco

Herein, we report the development of a self-sensing and active corrosion protection coating which incorporates pH-sensitive multilayer chitosan/alginate-covered CaCO3 microcontainers containing 1,10-phenanthrolin-5-amine (APhen). The microcontainers can respond to pH variation to release APhen which serves not only as a corrosion indicator but also as an inhibitor. An epoxy coating doped with 5 wt% microcontainers exhibited improved corrosion performance and was capable of inhibiting corrosion spreading from the damaged area in a 3.5 wt% NaCl solution. The salt spray test showed that corrosion damage can be quickly detected by the appearance of a red color within 2 min.

Additional file 1: Table S1. Primers for Q-PCR analysis.

Scattering of light in complex media scrambles optical wavefronts and breaks the principles of conventional imaging methods. For decades, researchers have endeavored to conquer the problem by inventing approaches such as adaptive optics, iterative wavefront shaping, and transmission matrix measurement. That said, imaging through/into thick scattering media remains challenging to date. With the rapid development of computing power, deep learning has been introduced and shown potentials to reconstruct target information through complex media or from rough surfaces. But it also fails once coming to optically thick media where ballistic photons become negligible. Here, instead of treating deep learning only as an image extraction method, whose best-selling advantage is to avoid complicate physical models, we exploit it as a tool to explore the underlying physical principles. By adjusting the weights of ballistic and scattered photons through a random phasemask, it is found that although deep learning can extract images from both scattered and ballistic light, the mechanisms are different: scattering may function as an encryption key and decryption from scattered light is key sensitive, while extraction from ballistic light is stable. Based on this finding, it is hypothesized and experimentally confirmed that the foundation of the generalization capability of trained neural networks for different diffusers can trace back to the contribution of ballistic photons, even though their weights of photon counting in detection are not that significant. Moreover, the study may pave an avenue for using deep learning as a probe in exploring the unknown physical principles in various fields., Comment: 12 pages, 6 figures

Additional file 2: Table S2. Annotation information of 100 ESTs with expression levels 10-fold higher inadipose tissue than in non-adipose tissues.

Undoubtedly, SARS-CoV-2 has caused an outbreak of pneumonia that evolved into a worldwide pandemic. The confusion of early symptoms of the SARS-CoV-2 infection with other respiratory virus infections made it very difficult to block its spread, leading to the expansion of the outbreak and an unreasonable demand for medical resource allocation. The traditional immunochromatographic test strip (ICTS) can detect one analyte with one sample. Herein, this study presents a novel strategy for the simultaneous rapid detection of FluB/SARS-CoV-2, including quantum dot fluorescent microspheres (QDFM) ICTS and a supporting device. The ICTS could be applied to realize simultaneous detection of FluB and SARS-CoV-2 with one test in a short time. A device supporting FluB/SARS-CoV-2 QDFM ICTS was designed and had the characteristics of being safe, portable, low-cost, relatively stable, and easy to use, ensuring the device could replace the immunofluorescence analyzer in cases where there is no need for quantification. This device does not need to be operated by professional and technical personnel and has commercial application potential.

Digital holographic microscopy has significant advantages over traditional 3D measurements. In order to obtain a reconstructed image of superior quality, the zero-order-term spectrum and the −1 term spectrum must be eliminated during the digital reconstruction. At the same time, digital holographic microscopy has changed from the traditional manual selection of the +1 term spectrum to the automatic selection of the +1 term spectrum. In the process of spatial filtering of the +1 term spectrum, the filtering window is crucial, and the shape of the filtering window and the robustness of the filtering window to noise will ultimately affect the reconstruction results. In this paper, we propose an automatic spatial filtering method that combines wavelet transform and mathematical morphology to automatically extract the +1 term spectrum. Compared with conventional methods, the reconstruction results are more accurate and robust to noise, and the experimental results verify the feasibility of the proposed method.

The degradation effect of mold on the coating in a hot and humid environment is one of the important factors that cause layer failure. Combined with the wire beam electrode (WBE) and the traditional surface analysis technique, the local biodegradation of the coatings and the corrosion behaviors of metal substrates can be characterized accurately by a WBE. Herein, a WBE was used to study the degradation impact of Talaromyces funiculosus (T.funiculosus) isolated from a tropical rainforest environment on the corrosion of polyurethane (PU) coating. After immersion for 14 days, the local current density distribution of the WBE surface can reach ~10−3 A/cm2 in the fungal liquid mediums but maintains ~10−7 A/cm2 in sterile liquid mediums. The |Z|0.01Hz value of the high current densities area (#85 electrode) was 1.06 × 109 Ω cm2 in a fungal liquid medium after 14 days of immersion. After being attacked by T.funiculosus, the degradation of the PU was more severe, and there were wrinkles, cracks, blisters, and even micro-holes distributed randomly on the surface of electrodes. This resulted from the self-corrosion caused by the T.funiculosus degradation of the coating; the corrosion caused by the electric coupling effect of the coating was introduced. Energy dispersive spectroscopy (EDS) and Raman spectra results showed that the corrosion products were flakey and globular, which consisted of γ-FeOOH, γ-Fe2O3, and α-FeOOH.

Optical fiber sensors are used for partial discharge detection in many applications due their advantage of strong anti-electromagnetic interference capability. Multi-point distributed partial discharge detection and location are important for electrical equipment. In this paper, a distributed partial discharge location and detection scheme based on optical fiber Rayleigh backscattering light interference is experimentally demonstrated. At the same time, the location and extraction algorithm is used to demodulate the partial discharge signal; furthermore, the high-pass filter is used to reduce the system low-frequency noise and environment noise. It is clear that the proposed system can detect a partial discharge signal generated by metal needle sensitivity, and the detectable frequency range is 0–2.5 kHz. We carried out 10 locating tests for two sensing units, the experimental results show that the maximum location error is 1.0 m, and the maximum standard deviation is 0.3795. At same time, the signal-to-noise ratio (SNR) of sensing unit 1 and sensing unit 2 are greatly improved after demodulation, which are 39.7 and 38.8, respectively. This provides a new method for a multipoint-distributed optical fiber sensor used for detecting and locating a long-distance electrical equipment partial discharge signal.

Separation technology is central to industries as diverse as petroleum, pharmaceuticals, mining and life sciences. Metal-organic cages, a class of molecular containers formed via coordination-driven self-assembly, show great promise as separation agents. Precise control of the shape, size and functionalization of cage cavities enables them to selectively bind and distinguish a wide scope of physicochemically similar substances in solution. Extensive research has, thus, been performed involving separations of high-value targets using coordination cages, ranging from gases and liquids to compounds dissolved in solution. Enantiopure capsules also show great potential for the separation of chiral molecules. The use of crystalline cages as absorbents, or the incorporation of cages into polymer membranes, could increase the selectivity and efficiency of separation processes. This Review covers recent progress in using metal-organic cages to achieve separations, with discussion of the many methods of using them in this context. Challenges and potential future developments are also discussed.

Knowledge Graphs (KGs) have shown great success in recommendation. This is attributed to the rich attribute information contained in KG to improve item and user representations as side information. However, existing knowledge-aware methods leverage attribute information at a coarse-grained level both in item and user side. In this paper, we proposed a novel attentive knowledge graph attribute network(AKGAN) to learn item attributes and user interests via attribute information in KG. Technically, AKGAN adopts a heterogeneous graph neural network framework, which has a different design between the first layer and the latter layer. With one attribute placed in the corresponding range of element-wise positions, AKGAN employs a novel interest-aware attention network, which releases the limitation that the sum of attention weight is 1, to model the complexity and personality of user interests towards attributes. Experimental results on three benchmark datasets show the effectiveness and explainability of AKGAN., 11 pages, 4 figures

This study discovers a reversible order-disorder transition (ODT) in a 10-cation compositionally complex ceramic, (Nd0.15Pr0.15Dy0.8Ho0.8Er0.8Ti0.2Yb0.1Hf0.1Zr0.1Nb0.8)O7-delta, induced via annealing in oxidized vs. reduced environments at 1600C. Notably, the 10-cation oxide remains a homogenous single-phase high-entropy solid solution before and after the ODT in the pyrochlore vs. fluorite structure that can be quenched. In-situ neutron diffraction reveals the oxygen vacancy formation and atomic displacement during this ODT. The temperature dependence of thermal conductivity is altered by the ODT. This study reveals a new pathway to induce ODT via a redox transition to tailor the properties of compositionally complex fluorite-based oxides.

Ratiometric luminescence thermometry with trivalent lanthanide ions and their 4fn energy levels is an emerging technique for non-invasive remote temperature sensing with high spatial and temporal resolution. Conventional ratiometric luminescence thermometry often relies on thermal coupling between two closely lying energy levels governed by Boltzmann’s law. Despite its simplicity, Boltzmann thermometry with two excited levels allows precise temperature sensing, but only within a limited temperature range. While low temperatures slow down the nonradiative transitions required to generate a measurable population in the higher excitation level, temperatures that are too high favour equalized populations of the two excited levels, at the expense of low relative thermal sensitivity. In this work, we extend the concept of Boltzmann thermometry to more than two excited levels and provide quantitative guidelines that link the choice of energy gaps between multiple excited states to the performance in different temperature windows. By this approach, it is possible to retain the high relative sensitivity and precision of the temperature measurement over a wide temperature range within the same system. We demonstrate this concept using YAl3(BO3)4 (YAB):Pr3+, Gd3+ with an excited 6PJ crystal field and spin-orbit split levels of Gd3+ in the UV range to avoid a thermal black body background even at the highest temperatures. This phosphor is easily excitable with inexpensive and powerful blue LEDs at 450 nm. Zero-background luminescence thermometry is realized by using blue-to-UV energy transfer upconversion with the Pr3+−Gd3+ couple upon excitation in the visible range. This method allows us to cover a temperature window between 30 and 800 K.

The use of di(2-pyridyl)ketone in subcomponent self-assembly is introduced. When combined with a flexible triamine and zinc bis(trifluoromethanesulfonyl)imide, this ketone formed a new Zn4 L4 tetrahedron 1 bearing twelve uncoordinated pyridyl units around its metal-ion vertices. The acid stability of 1 was found to be greater than that of the analogous tetrahedron 2 built from 2-formylpyridine. Intriguingly, the peripheral presence of additional pyridine rings in 1 resulted in distinct guest binding behavior from that of 2, affecting guest scope as well as binding affinities. The different stabilities and guest affinities of capsules 1 and 2 enabled the design of systems whereby different cargoes could be moved between cages using acid and base as chemical stimuli.

In this study, we propose an optical hybrid encryption scheme based on compressive temporal ghost imaging. This scheme combines the asymmetric of the public key cryptography and the non-linear of ghost imaging. First, according to the principle of temporal ghost image encryption, the chaotic modulation pattern is used as the key to encrypt the plaintext information, and then the chaotic pattern is encrypted by the public key cryptography. Then, only the authorized receiver can decrypt the chaotic pattern with the private key. Finally, the plaintext can be decrypted with the compressive sensing algorithm. This scheme solves the problem of key distribution in traditional ghost imaging encryption scheme. At the same time, the application of public key cryptography reduces the cost of establishing private channels and enhances the security of the system. In addition, feasibility, security, and robustness of the scheme were verified by simulation. This scheme has the advantages of high quality, high safety, wide applicability and low cost, which can immediately be applied to encryption.

Array signal simulation of active sonar echo is an important basis for the verification of new target detection technologies and equipment training. Backscatter signal simulation is the main part of echo signal simulation of monostatic sonar target. Based on the improvement of the traditional highlight model of submarine target, this paper presents a method to simulate the backscatter signal of a submarine target based on the spatial distribution characteristics of target intensity at a different angle of the ship's side. Compared with the traditional method, the backscatter signals obtained by the proposed method can better reflect the broadening and amplitude fluctuation characteristics of the backscatter signals of the submarine target in the time domain. As for the spatial distribution of the target intensity, it can change with the spatial variation of the incident Angle of the signal, and get the spatial distribution diagram which is consistent with the variation law of the "butterfly figure" of the simulation target, so that the simulated backscatter signal of the target is more consistent with the spatial distribution characteristics of the target intensity of the given target, which can provide technical support for the simulation of the active sonar echo signal.

In this paper, soybean protein isolate (SPI) was used as template, hydroxyapatite was crystallized on protein chains of SPI by in-situ synthesis, then the obtained inorganic HA/biopolymer SPI composite (HA@SPI) was calcined at suitable temperature, which afforded a novel hydroxyapatite-based porous materials (HApM). The results indicated that the product showed a porous morphology structure and excellent absorption performance for Pb2+. HApM maximum removal of lead was attained (96.25%) at an initial pH value of 7.4, temperature of 25 °C and contact time of 30 min with an initial metal concentration of 60 mg/L. In order to identify composition, structure and functional groups involved in the uptake of Pb2+, Fourier transform infrared spectrometer (FTIR), thermogravimetric analysis (TG), X-ray diffraction (XRD) scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and Brunauer–Emmett–Teller (BET) analysis were carried out. Therefore, the hydroxyapatite-based porous materials (HApM) is a promising candidate for the treatment of liquid wastes containing toxic Pb2+ metal ion, heavy metal ion antidotes and other related fields.

In this paper, according to the phase object in the ghost imaging has a stealth effect, we proposed an optical encryption method based on compressive ghost imaging and public key cryptography. This method solves the key distribution problem of ghost imaging encryption, and reduces the additional cost of establishing security channels. The simulation results verify the feasibility, security and robustness of the proposed encryption scheme. This technique can be immediately applied to encryption and data storage with the advantages of high-safety, high-robustness and low-cost.

The use of carbon fiber-reinforced polymer (CFRP) in aviation, automobile, marine and offshore, etc. increases sharply. The metals such as aluminum alloy are still widely used in these industries. Then, the joining technology of CFRP-metal is one of the key problems urgently to be solved and developed in these industries, especially in aviation industries. Thus, this paper gives a review on the joining processes of carbon fiber-reinforced polymer and metal. The implementation processes and joining material types of adhesive bonding, bolt connection, riveting, welding, “z-pin” (pin inserts), and joining (such as self-pierce riveting, hot riveting, mechanical clinching, friction welding) by plastic deformation, were summarized.

As a novel computational imaging (CI) method, single pixel imaging (SPI) can obtain the spatial information of the target object with only a single-pixel detector, especially the SPI with Fourier basis has higher imaging efficiency and quality. However, Fourier single-pixel imaging (FSI) will still be affected in atmospheric turbulence, imaging will be unstable, and image quality will decrease. This paper first uses the phase screen method to simulate atmospheric turbulence, and then in the FSI process, the Fourier coefficients are processed to filter noise in the Fourier domain to reduce the impact of turbulence on imaging. Then we use the conditional generative adversarial network (CGAN) of deep learning methods to further improve the clarity and quality of the restored image.

Ghost imaging (GI) is a technology of nonlocal optical imaging, which is widely used in the field of information encryption. However, there are some inherent shortcomings in the encryption process, such as imperfect security and low imaging precision. To solve these problems, we propose a camouflaged encryption mechanism based on sparse decomposition of principal component orthogonal basis and ghost imaging (CSP-GI). Unlike the traditional encryption method, there are two-level keys and ciphertexts. The information of the secret image is hidden in the camouflaged image to improve the security of the system. The use of the sparse decomposition of principal component orthogonal basis expands the information content of encrypted transmission, improves the accuracy of reconstructed image, and reduces the reconstruction time. The simulation and experimental results show that the proposed method not only has good security and robustness but also reduces reconstruction time.

Additional file1. Additional data.

现如今，快节奏高效率的生活让人们逐渐体会到汽车在日常生活中带给人们的便利。因 此人们对汽车的需求从公共交通类的公交车和出租车逐渐趋向于私家车，并且现在很多家庭也 已不满足于一台私家车。据数据统计，在过去的 2020年里，我国汽车的产销量达 2658.63 万台， 位居世界前几。但同比2019 年 1986.58 万台的产销量呈下降趋势。而呈现下降趋势的一大部分 原因就是因为“有车无位”。根据以上背景，本文提出了用数据挖掘技术分析了我国城市交通现 状，主要内容包括：国内汽车购买及汽车停放现状分析；公共停车场与收费停车情况对比；未 来汽车总量与停车位需求量预算分析；解决方案。

Figure and Table

This paper introduces the design of intelligent Therapy Bracelet system based on Internet of things technology. The smart Therapy Bracelet system mainly realizes the functions of blood pressure detection, blood pressure value viewing, historical blood pressure value viewing, peripheral services, personal information, account setting, etc. Firstly, the research background and demand analysis of the intelligent Therapy Bracelet system are analyzed, and then the function modules of the system are designed. Finally, the hardware is selected and designed according to the required functions and performance requirements, and the system functions are realized. Through the test, the system runs well, can achieve the expected goal, and has good application value.

Scanning probe microscopy (SPM) has emerged as an indispensable technique to image, characterize, manipulate, and create new functional properties of materials at the nanoscale. Concurrently, the tantalizing nanoscale properties of ferroelectric materials have aroused immense interest both scientifically and technologically. Here SPM techniques are used to probe and exploit the nanoscale ferroelectric functionalities in various material systems, and each chapter in this dissertation is allocated to one specific material. Polarization retention failure compromises the performance and life expectancy of non-volatile nanoelectronic devices and thus needs to be addressed. In a designer-defect-engineered epitaxial BiFeO3 system, an ultralong polarization retention with no degradation over one year has been discovered. SPM based dynamic switching measurements reveal a significantly increased activation field that provides sufficient energy for efficient domain wall pinning. Atomic resolution scanning transmission electron microscopy indicates that nanoscale defect pockets pervade the entire film thickness acting as domain wall pinning centers. The findings provide guidelines for improving polarization retention in ferroelectrics using defect engineering. Domain walls, as one type of topological defect, have given rise to the recent development of prototype domain wall nanoelectronics elements. Here, the nanoscale electrical conduction behaviour of single crystal 0.7Pb(Mg1/3Nb2/3)-0.3PbTiO3 (PMN-PT) with a (001) orientation is investigated. Electrical conductivity at domain walls in these crystals is observed using conductive AFM (c-AFM). The AC-conductivity response at such walls is mapped and local preferential charge relaxation along domain walls is investigated by Kelvin probe force microscopy revealing slow dynamics in the minute's range. These findings provide new insight into domain wall properties at a.c. frequencies for domain wall based nanoelectronics. Van der Waals (vdW) thio- and seleno-phosphates have recently gained considerable attention for the use as ‘active’ dielectrics in two-dimensional or quasi-two-dimensional electronic devices. Bulk ionic conductivity in these materials has been identified as a key factor for the control of their electronic properties. However, direct evidence of specific ion species’ migration at the nanoscale, particularly under electric fields, and its impact on material properties has been elusive. Here, direct evidence of a phase-selective anisotropic Cu ion hopping mechanism is reported in copper indium thiophosphate (CuInP2S6) through detailed scanning probe microscopy measurements. A two-step Cu-hopping path including a first intralayer hopping (in-plane) and second interlayer hopping (out-of-plane) crossing the vdW gap is unveiled. Evidence of electrically controlled Cu ion migration is further verified by nanoscale energy-dispersive X-ray spectroscopy (EDS) mapping. These findings offer new insight into anisotropic ionic manipulation in layered vdW ferroelectric/dielectric materials for emergent vdW electronic device design. Overall, these studies suggest that SPM can provide detailed nanoscale insight into the functional properties of ferroelectric materials, and advance the development of prototype nanoelectronics components via the in-situ field control.