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This research utilizes both single crystal and polycrystalline models to probe the fatigue crack propagation mechanism in pure silver via molecular dynamics (MD) simulations. A comprehensive validation approach at both micro and macro scales, incorporating transmission electron microscopy (TEM), electron backscatter diffraction (EBSD), and compact tension (CT) specimen fatigue testing, is developed to verify the reliability of simulation models and results. Simulation findings indicate that the initial crack orientation significantly influences crack propagation. As the crack advances within the crystal, two primary crack propagation mechanisms are discerned: (1) nano-voids appear at the crack tip, and the crack propagates by continuously aggregating with the nano-voids ahead; (2) the formation of Stair-rod dislocations and V-shape stacking faults due to dislocation reactions and slip band movements impedes crack propagation, accompanied by the dislocation reaction of Shockley partial dislocations ( 1 6 <112>) generating Hirth dislocations ( 1 6 <110>). The dislocation reaction is verified through the dislocation analysis of the crack tip area of the CT specimen after fatigue experiment by using TEM. In addition, the results of this study show that the angle between the direction of crack propagation and the grain boundary affects the fatigue crack propagation, e.g. when the angle is less than 60°, the crack rapidly propagates along the grain boundary. The orientation distribution function (ODF) results of EBSD can verify that the polycrystalline model containing 30 grains is a reliable model for the MD simulation of behavior of the crack tip of CT specimen. Lastly, the Paris law constants for pure silver are determined as m = 3.72 and lg C = − 10.77, providing a reference for the fatigue analysis and life prediction of silver components or silver soldering pots in engineering applications. [ABSTRACT FROM AUTHOR]

Triggering the lattice oxygen oxidation mechanism is crucial for improving oxygen evolution reaction (OER) performance, because it could bypass the scaling relation limitation associated with the conventional adsorbate evolution mechanism through the direct formation of oxygen–oxygen bond. High‐valence transition metal sites are favorable for activating the lattice oxygen, but the deep oxidation of pre‐catalysts suffers from a high thermodynamic barrier. Here, taking advantage of the Jahn–Teller (J–T) distortion induced structural instability, we incorporate high‐spin Mn3+ (t2g3eg1 ${{t}_{2g}^{3}{e}_{g}^{1}}$) dopant into Co4N. Mn dopants enable a surface structural transformation from Co4N to CoOOH, and finally to CoO2, as observed by various in situ spectroscopic investigations. Furthermore, the reconstructed surface on Mn‐doped Co4N triggers the lattice oxygen activation, as evidenced experimentally by pH‐dependent OER, tetramethylammonium cation adsorption and online electrochemical mass spectrometry measurements of 18O‐labelled catalysts. In general, this work not only offers the introducing J–T effect approach to regulate the structural transition, but also provides an understanding about the influence of the catalyst's electronic configuration on determining the reaction route, which may inspire the design of more efficient catalysts with activated lattice oxygen. [ABSTRACT FROM AUTHOR]

Triggering the lattice oxygen oxidation mechanism is crucial for improving oxygen evolution reaction (OER) performance, because it could bypass the scaling relation limitation associated with the conventional adsorbate evolution mechanism through the direct formation of oxygen–oxygen bond. High‐valence transition metal sites are favorable for activating the lattice oxygen, but the deep oxidation of pre‐catalysts suffers from a high thermodynamic barrier. Here, taking advantage of the Jahn–Teller (J–T) distortion induced structural instability, we incorporate high‐spin Mn3+ (t2g3eg1 ${{t}_{2g}^{3}{e}_{g}^{1}}$) dopant into Co4N. Mn dopants enable a surface structural transformation from Co4N to CoOOH, and finally to CoO2, as observed by various in situ spectroscopic investigations. Furthermore, the reconstructed surface on Mn‐doped Co4N triggers the lattice oxygen activation, as evidenced experimentally by pH‐dependent OER, tetramethylammonium cation adsorption and online electrochemical mass spectrometry measurements of 18O‐labelled catalysts. In general, this work not only offers the introducing J–T effect approach to regulate the structural transition, but also provides an understanding about the influence of the catalyst's electronic configuration on determining the reaction route, which may inspire the design of more efficient catalysts with activated lattice oxygen. [ABSTRACT FROM AUTHOR]

There are various indoor fingerprint localization techniques utilizing the similarity of received signal strength (RSS) to discriminate the similarity of positions. However, due to the varied states of different wireless access points (APs), each AP's contribution to RSS similarity varies, which affects the accuracy of localization. In our study, we analyzed several critical causes that affect APs' contribution, including APs' health states and APs' positions. Inspired by these insights, for a large-scale indoor space with ubiquitous APs, a threshold was set for all sample RSS to eliminate the abnormal APs dynamically, a correction quantity for each RSS was provided by the distance between the AP and the sample position to emphasize closer APs, and a priority weight was designed by RSS differences (RSSD) to further optimize the capability of fingerprint distances (FDs, the Euclidean distance of RSS) to discriminate physical distance (PDs, the Euclidean distance of positions). Integrating the above policies for the classical WKNN algorithm, a new indoor fingerprint localization technique is redefined, referred to as FDs' discrimination capability improvement WKNN (FDDC-WKNN). Our simulation results showed that the correlation and consistency between FDs and PDs are well improved, with the strong correlation increasing from 0 to 76% and the high consistency increasing from 26% to 99%, which confirms that the proposed policies can greatly enhance the discrimination capabilities of RSS similarity. We also found that abnormal APs can cause significant impact on FDs discrimination capability. Further, by implementing the FDDC-WKNN algorithm in experiments, we obtained the optimal K value in both the simulation scene and real library scene, under which the mean errors have been reduced from 2.2732 m to 1.2290 m and from 4.0489 m to 2.4320 m, respectively. In addition, compared to not using the FDDC-WKNN, the cumulative distribution function (CDF) of the localization errors curve converged faster and the error fluctuation was smaller, which demonstrates the FDDC-WKNN having stronger robustness and more stable localization performance. [ABSTRACT FROM AUTHOR]

The separation of CO activation and C─C coupling enables oxide–zeolite catalyzed tandem reaction toward direct conversion of syngas into light olefins to be a promising alternative for the traditional Fischer–Tropsch process with elevated selectivity. Utilizing controlled mass transfer to match the activation of reactants and the coupling of intermediates presents an appealing strategy to break the limitation on space‐time yield in this tandem process. In this work, ZnCrOx hollow multi‐shelled structures (HoMS) are fabricated to enhance the adsorption and enrichment ability of syngas, thereby strengthening the rate‐determining activation step of reactants and resulting in an accelerated generation of intermediates. When coupled with SAPO zeolite, quintuple‐shelled ZnCrOx HoMS‐based catalysts exhibit a record high C2= ‐C4= space‐time yield of 559 mg·gcat−1·h−1 with a selectivity of 90%. This work demonstrates the advantages of precise nanostructure sculpturing on the mass transfer behavior in the microenvironment and provides a new strategy for highly selective direct conversion of syngas to light olefins, based on efficient activation of reactants and sufficient feeding of intermediates through enrichment effects within HoMS. [ABSTRACT FROM AUTHOR]

Tuning the electrocatalytic selectivity and long‐term stability for industrially significant, yet reactively unfavorable products, remains a challenge in oxygen reduction. Herein, the Au/TiO2 catalysts with strong metal–support interactions (SMSI) are designed and synthesized through an in situ auto‐reduction of Au‐modified Ti‐MOF. Highly dispersed ultra‐low loading of Au NPs strongly capsulated in porous TiO2 substrate, together with conductive carbon derivated from MOFs, enables Au/TiO2 electrocatalysts to achieve excellent H2O2 electrosynthesis through the two‐electron oxygen reduction reaction (2e ORR). Au(1.0)/TiO2 (0.52 wt% Au loading) exhibited a high selectivity of 90%, a remarkable Faradaic efficiency of 98%, and 72.2 mg L−1 h−1 H2O2 production. Highly dispersed Au NPs promote active site exposure, while the conductive carbon and the porous superstructure enhance mass diffusion. Notably, the SMSI between Au NPs and TiO2 substrate leads to superb stability (over 168 h) of the electrocatalysts, as it ensures continuous electronic interactions. Experimental characterizations and density functional theory (DFT) simulations further revealed that the SMSI effect medicates the activation of the *OOH intermediate formation and the d‐band center, which are conductive to 2e ORR. Moreover, this strategy provides a potential way toward high‐performance electrocatalysts in flow system devices for continuously purifying sewage and chemical bleaching in extreme environments. [ABSTRACT FROM AUTHOR]

N‐doping is an effective technique for enhancing the exploitation of TiO2 under visible light, thanks to the level of doping introduced. It is also important to explore N‐doping in the metastable polymorph TiO2(B), which is renowned for its applications in energy materials. In order to investigate the impact of N‐doping on the optical properties of TiO2(B), a systematic comparison of the electronic structural and optical properties of pure and N‐doped TiO2(B) was conducted using density function theory (DFT) calculations. The results indicate that N‐doping is more thermodynamically favorable at the O site with four coordinated atoms. Upon N‐doping, impurity states emerged within the bandgap of TiO2(B), leading to a significant reduction in the energy gap. Consequently, N‐doping primarily enhances the absorbance of visible light, which is crucial for photocatalysis. Furthermore, the adsorption energy of H at the (0 0 1) surface of N‐doped TiO2(B) decreased by 2.75 eV, providing valuable insight for the design of TiO2(B) with exceptional photo‐ and electro‐catalytic performance. [ABSTRACT FROM AUTHOR]

Photocatalytic CO2 reduction holds great promise to solve energy shortage and global warming. Nb2O5 has demonstrated superiority in CO2 activation and selectivity regulation, but suffers from poor light absorption ability and fast carrier recombination. To tackle these problems, we designed and synthesized ultrathin Nb2O5 nanosheets which were decorated with tiny NiP nanoparticles as cocatalyst. In this way, light absorption range broadened, carrier migration distance reduced, charge transfer resistance decreased, and surface reaction kinetics promoted. Consequently, the as‐prepared NiP/Nb2O5 showed notably enhanced activity (148.7 μmol ⋅ g−1) and selectivity (82.1 %) towards CO, as well as remarkable stability. This work paves the way for cheap and earth abundant alternatives as cocatalysts and deepens the understanding of their functions in CO2 photoreduction. [ABSTRACT FROM AUTHOR]

This paper introduces a method for high-resolution lattice image reconstruction and dislocation analysis based on diffraction extinction. The approach primarily involves locating extinction spots in the Fourier transform spectrum (reciprocal space) and constructing corresponding diffraction wave functions. By the coherent combination of diffraction and transmission waves, the lattice image of the extinction planes is reconstructed. This lattice image is then used for dislocation localization, enabling the observation and analysis of crystal planes that exhibit electron diffraction extinction effects and atomic jump arrangements during high-resolution transmission electron microscopy (HRTEM) characterization. Furthermore, due to the method's effectiveness in localizing dislocations, it offers a unique advantage when analyzing high-resolution images with relatively poor quality. The feasibility of this method is theoretically demonstrated in this paper. Additionally, the method was successfully applied to observed edge dislocations, such as 1 / 6 [ 21 1 − ] , 1 / 6 [ 2 − 1 1 − ] , and 1 / 2 [ 0 1 − 1 ] , which are not easily observable in conventional HRTEM characterization processes, in electro-deposited Cu thin films. The Burgers vectors were determined. Moreover, this paper also attempted to observe screw dislocations that are challenging to observe in high-resolution transmission electron microscopy. By shifting a pair of diffraction extinction spots and superimposing the reconstructed images before and after the shift, screw dislocations with a Burgers vector of 1 / 2 [ 01 1 − ] were successfully observed in electro-deposited Cu thin films. [ABSTRACT FROM AUTHOR]

Recently, the development of new materials and devices has become the main research focus in the field of energy. Supercapacitors (SCs) have attracted significant attention due to their high power density, fast charge/discharge rate, and excellent cycling stability. With a lamellar structure, 2D transition metal dichalcogenides (2D TMDs) emerge as electrode materials for SCs. Although many 2D TMDs with excellent energy storage capability have been reported, further optimization of electrode materials and devices is still needed for competitive electrochemical performance. Previous reviews have focused on the performance of 2D TMDs as electrode materials in SCs, especially on their modification. Herein, the effects of element doping, morphology, structure and phase, composite, hybrid configuration, and electrolyte are emphatically discussed on the overall performance of 2D TMDs‐based SCs from the perspective of device optimization. Finally, the opportunities and challenges of 2D TMDs‐based SCs in the field are highlighted, and personal perspectives on methods and ideas for high‐performance energy storage devices are provided. [ABSTRACT FROM AUTHOR]

Forest fire risk prediction is essential for building a forest fire defense system. Ensemble learning methods can avoid the problem of difficult model selection for disaster susceptibility prediction and can significantly improve modeling accuracy. This study introduces a stacking ensemble learning model for predicting forest fire risks in Yunnan Province by integrating various data types, such as meteorological, topographic, vegetation, and human activity factors. A total of 70,274 fire points and an equal number of randomly selected nonfire points were used to develop the model, with 70% of the data allocated for training and the remaining 30% for testing. The stacking model combined four diverse machine learning methods: random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and multilayer perceptron (MLP). We evaluated the model's predictive performance using metrics like accuracy, area under the characteristic curve (AUC), and fire density (FD). The results demonstrated that the stacking fusion model exhibited remarkable accuracy with an AUC of 0.970 on the test set, significantly surpassing the performance of individual machine learning models, which had AUC values ranging from 0.935 to 0.953. Furthermore, the stacking fusion model effectively captured the maximum fire density in extremely high susceptibility areas, demonstrating enhanced generalization capabilities. [ABSTRACT FROM AUTHOR]

To reveal the effects of water vapor on the oxidation mechanism of Al–Zr-based materials, the Al2Zr alloy was oxidized in a wet atmosphere. Water vapor achieves the synchronous oxidation of Al and Zr to form amorphous (Al0.67Zr0.33)O1.66 oxide on the Al2Zr surface. The oxidation kinetics of the Al2Zr alloy is significantly retarded by the presence of water vapor. Compared with the oxygen molecules, water molecules are preferentially adsorbed on the surface, thereby providing fewer oxidizing species for wet oxidation than those for oxygen-involved oxidation. This work provides fundamental insights for surficial protection of structural alloys in humid environments. [ABSTRACT FROM AUTHOR]

Automated Breast Ultrasound is a highly advanced breast tumor detection modality that produces hundreds of 2D slices in each scan. However, this large number of slices poses a significant burden for physicians to review. This paper proposes a novel 2.5D tumor detection model, named "ABUSDet," to assist physicians in automatically reviewing ABUS images and predicting the locations of breast tumors in images. At the core of this approach, a sequence of data blocks partitioned from a pre-processed 3D volume are fed to a 2.5D tumor detection model, which outputs a sequence of 2D tumor candidates. An aggregation module then clusters the 2D tumor candidates to produce the ultimate 3D coordinates of the tumors. To further improve the accuracy of the model, a novel mechanism for training deep learning models, called "Deliberate Training," is proposed. The proposed model is trained and tested on a dataset of 87 patients with 235 ABUS volumes. It achieves sensitivities of 77.94%, 75.49%, and 65.19% at FPs/volume of 3, 2, and 1, respectively. Compared with the 2D and 3D object detection models, the proposed ABUSDet model achieves the highest sensitivity with relatively low false-positive rates. [ABSTRACT FROM AUTHOR]

Intelligent agriculture has become the development trend of agriculture in the future, and it has a wide range of research and application scenarios. Using machine learning to complete basic tasks for people has become a reality, and this ability is also used in machine vision. In order to save the time in the fruit picking process and reduce the cost of labor, the robot is used to achieve the automatic picking in the orchard environment. Cherry target detection algorithms based on deep learning are proposed to identify and pick cherries. However, most of the existing methods are aimed at relatively sparse fruits and cannot solve the detection problem of small and dense fruits. In this paper, we propose a cherry detection model based on YOLOv5s. First, the shallow feature information is enhanced by convolving the feature maps sampled by two times down in BackBone layer of the original network model to the input end of the second and third CSP modules. In addition, the depth of CSP module is adjusted and RFB module is added in feature extraction stage to enhance feature extraction capability. Finally, Soft- Non-Maximum Suppression (Soft-NMS) is used to minimize the target loss caused by occlusion. We test the performance of the model, and the results show that the improved YOLOv5s-cherry model has the best detection performance for small and dense cherry detection, which is conducive to intelligent picking. [ABSTRACT FROM AUTHOR]

Content-based image retrieval algorithm (CBIR) aims to find semantically matching or similar images with query images. It analyzes visual content in a large number of image databases. It is important to obtain discriminant image representation by feature extraction. With the continuous development of deep learning, the image feature representation method used in image retrieval has gradually changed. The original extraction method is based on manual features. Now it is based on deep features. From the perspective of different feature extraction methods, the recent image retrieval algorithms based on depth feature are reviewed and traced. The image retrieval algorithms based on depth feature are divided into two aspects: depth global feature and depth local feature. The deep convolution feature aggregation technique is emphasized in the deep local feature algorithm. The widely used image retrieval methods of deep global and local feature fusion are summarized. This paper discusses the practical application of deep feature image retrieval technology in remote sensing image retrieval, e-commerce product retrieval and medical image retrieval. And it compares the performance of these feature extraction algorithms in image retrieval accuracy. Finally, the future research trend of depth feature extraction in case image retrieval is forecasted. [ABSTRACT FROM AUTHOR]

A comprehensive investigation of metal–alloy induced crystallization (MAIC) of amorphous silicon (a-Si) is presented. The crystallization processes in three microstructurally principally different, representative types of metal(-alloy)/a-Si systems, Alx(Ge1−x)/a-Si, AgxAl1−x/a-Si, and AlxZn1−x/a-Si, have been monitored by in situ heating x-ray diffraction (XRD) from 25 °C up to 475 °C, until crystallization of a-Si was completed. The obtained experimental results have been systematically compared to predictions obtained by applications of thermodynamic models based on calculations of interface and crystallization energies for the determination of so-called critical thicknesses and initial crystallization temperatures. From the investigation of the MAIC processes in the metal–alloy/a-Si systems, it has been demonstrated that the crystallization temperature and the crystallization kinetics can be well tailored and optimized by controlling the composition and microstructure of the metal alloys. This research, on the one hand, exposes the fundamental, principal role of interface thermodynamics on the crystallization processes and, on the other hand, opens new possibilities for the growth of technologically important, pure, crystalline semiconductor thin films at very low temperatures, as compared to the crystallization temperature of isolated, bulk semiconductor materials. [ABSTRACT FROM AUTHOR]

Despite the expectation on transition‐metal phosphides as precious‐metal‐free electrocatalysts, the reported performance of these materials still necessitates further improvement. Ingenious regulations of both geometric and electronic structure have been proposed as an effective approach to boost their electrocatalytic properties. In this regard, the self‐supported V doped CoP nanowires on nickel foam are prepared to accommodate both optimized electronic structure and desired nanostructure, which enable large surface area, abundant active sites exposure, low charge transfer resistance, as well as favorable H* adsorption. As for the alkaline hydrogen evolution, it only requires a lower potential of 79 mV and 125 mV to drive 10 mA ⋅ cm−2 and 100 mA ⋅ cm−2 current with a Tafel slope of 47.41 mV ⋅ dec−1, which prevails over commercial Pt/C catalysts. The catalyst also exhibits excellent durability to retain activity unchanged for more than 16 h. Such a simple and convenient strategy by electronic tuning and structure design provides a new avenue toward the exploration of efficient electrocatalysts. [ABSTRACT FROM AUTHOR]

Development of efficient non-precious and abundant electrocatalysts for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is one of the key tasks in renewable energy technologies. Transition-metal selenides have been widely studied as promising candidates. Herein, a layer-structured CoSe2 was used as a precursor, followed by simple one-step dopamine coating. The as-prepared Co0.85Se@NC showed outstanding performance in both ORR and OER catalysis. The onset potential and half-wave potential of the ORR in 0.1 M KOH solution can reach 0.96 V and 0.85 V, respectively. The OER overpotential corresponding to 10 mA cm−2 in 1.0 M KOH solution is only 350 mV, which is much smaller than that of RuO2 (390 mV). Importantly, the catalyst showed good stability, demonstrating that the layered Co0.85Se@NC has great potential for advanced bifunctional electrocatalysis. [ABSTRACT FROM AUTHOR]

In this paper, nanoporous gold (NPG) thin films with superior catalytic performance were prepared on glassy carbon electrodes (GCE) by optimizing the process parameters and adopting an improved solid-phase reaction method. The morphology and structures of NPG films were comprehensively investigated and the structural defects on continuous NPG ligaments were observed. The NPG films demonstrated higher sensitivity and a lower detection limit during the amperometric sensing of aniline than NPGs made using conventional techniques. The results of multiple electrochemical tests demonstrated that the NPG/GCE electrodes possess high stability and good reproducibility. The prepared NPG film is a favorable material that can be superior in aniline electrochemical detection and can also be applied in other electrochemical sensing reactions. [ABSTRACT FROM AUTHOR]

BaTiO3/TiO2@polypyrrole (PPy) composites with hollow multishelled structure (HoMS) were constructed to enhance the electromagnetic wave absorbing properties of BaTiO3-based absorbing material. BaTiO3/TiO2 HoMSs were prepared by hydrothermal crystallization using TiO2 HoMSs as template. Then, FeCl3 was introduced to initiate the oxidative polymerization of pyrrole monomer, forming BaTiO3/TiO2@PPy HoMSs successfully. The electromagnetic wave absorbing properties of BaTiO3/TiO2 HoMSs and BaTiO3/TiO2@PPy HoMSs with different shell number were investigated using a vector network analyzer. The results indicate that BaTiO3/TiO2@PPy HoMSs exhibit improved microwave absorption compared with BaTiO3/TiO2 HoMSs. In particular, tripled-shelled BaTiO3/TiO2@PPy HoMS has the most excellent absorbing performance. The best reflection loss can reach up to −21.80 dB at 13.34 GHz with a corresponding absorber thickness of only 1.3 mm, and the qualified absorption bandwidth of tripled-shelled BaTiO3/TiO2@PPy HoMS is up to 4.2 GHz. This work paves a new way for the development of high-performance composite microwave absorbing materials. [ABSTRACT FROM AUTHOR]

Pathological diagnosis is considered to be declarative and authoritative. However, reading pathology slides is a challenging task. Different parts of the section are taken and read for different purposes and with different focuses, which further adds difficulty to the pathologist's diagnosis. In recent years, the deep neural network has made great progress in the direction of computer vision and the main approach to image segmentation is the use of convolutional neural networks, through which the spatial properties of the data are captured. Among a wide variety of different network structures, one of the more representative ones is UNET with encoder and decoder structures. The biggest advantage of traditional UNET is that it can still perform well with a small number of samples, but because the information in the feature map is lost in the downsampling process of UNET, and a large amount of spatially accurate detailed information is lost in the decoding part. This makes it difficult to complete accurate segmentation of cell images with dense numbers and high adhesion. For this reason, we propose a new network structure based on UNET, which can be used to segment cell images by aggregating the global contextual information between different channels and assigning different weights to the corresponding channels through the gated adaptive mechanism, we improve the performance of UNET in the cell segmentation task and consider the use of unsupervised segmentation methods for secondary segmentation of the predicted results of our model, and the final results obtained are tested to meet the needs of the readers. [ABSTRACT FROM AUTHOR]

A WGAN-GP-based ECG signal expansion and an SE-ResNet1D-based ECG classification method are proposed to address the problem of poor modeling results due to the imbalanced sample distribution of ECG data sets. The network architectures of WGAN-GP and SE-ResNet1D are designed according to the characteristics of ECG signals so that they can be better applied to the generation and classification of ECG signals. First, ECG data were generated using WGAN-GP on the MIT-BIH arrhythmia database to balance the dataset. Then, the experiments were performed using the AAMI category and inter-patient data partitioning principles, and classification experiments were performed using SE-ResNet1D on the imbalanced and balanced datasets, respectively, and compared with three networks, VGGNet, DenseNet and CNN+Bi-LSTM. The experimental results show that using WGAN-GP to balance the dataset can improve the accuracy and robustness of the model classification, and the proposed SE-ResNet1D outperforms the comparison model, with a precision of 95.80%, recall of 96.75% and an F1 measure of 96.27% on the balanced dataset. Our methods have the potential to be a useful diagnostic tool to assist cardiologists in the diagnosis of arrhythmias. [ABSTRACT FROM AUTHOR]

The coupling of TiO2 and SrTiO3 through elaborate bandgap engineering can provide synergies for highly efficient photocatalysts. To further improve the separation between photogenerated electrons and holes, a nano‐heterostructured combination of semicrystalline SrTiO3 (S‐SrTiO3) and anatase TiO2 nanoparticles is designed, and an optimized interface is achieved between uniformly grown S‐SrTiO3 and metal organic framework (MOF)‐derived anatase TiO2 through a controlled hydrothermal process. Besides tuning of the bandgap and broadening of the absorption spectral range, S‐SrTiO3 particles alleviate charge carrier recombination benefiting from the coupling of the semicrystalline SrTiO3 around the interface. Additionally, highly dispersed S‐SrTiO3 on TiO2 provides a good spatial distribution of active sites and the abundant carbon remained from MOF may reduce charge transport resistance. Moreover, the rapid transfer within the nano‐heterostructure promotes the separation of the photogenerated charge carriers. With the above predominant architecture, when used as a photocatalyst, the as‐synthesized S‐SrTiO3/TiO2 heterostructure exhibits exceptionally high photocatalytic performance of 13 005 µmol h–1 g–1 for H2 production, exceeding most oxide‐based photocatalysts reported. This study might provide mechanistic insights into a new perspective for the design and preparation of photocatalysts with novel structure and enhanced catalysis activity. [ABSTRACT FROM AUTHOR]

The kinetics of Fe subsurface dissolution and surface segregation upon annealing Fe/Pd(111) in vacuum/oxygen environment are simulated by the modified Darken model incorporation of oxygen absorption. The simulation results indicate that (1) Fe dissolution takes place only in the subsurface layer upon annealing Fe/Pd(111) in vacuum, and (2) Fe surface segregation takes place by consuming Fe atoms from the FePd3 phase formed in the subsurface layer due to Fe dissolution upon annealing Pd/FePd3/Pd(111) in oxygen environment. These results agree very well with the experimental observations published recently. Meanwhile, a new method for determining the local diffusion coefficient based on the experimental STM observation is proposed by modeling the Fe dissolution kinetics at different annealing temperatures. [ABSTRACT FROM AUTHOR]

Hollow multishelled structure (HoMS) is one of the most promising multifunctional structures. The high complexity of its structure makes the general and controllable synthesis of HoMS rather challenging. By integration of multidisciplinary knowledge, a great achievement in HoMSs has been obtained in the past decade. Especially, the developed sequential templating approach has significantly boomed the progress of HoMS in composition and structure diversity and application area. The implementation of the temporal-spatial ordering in HoMS makes it indispensable in solving the key scientific problems in energy conversion, catalysis and drug delivery areas. Further development in HoMSs with novel intricate structures will bring new understandings. In this review, we systematically introduce the development history of HoMSs, summarize the inspiration inherited from the previous research on hollow structures, and discuss the milestones in the development of HoMSs, with a focus on the sequential templating approach for HoMS fabrication, attractive temporal-spatial ordering property and dynamic smart behavior for advanced applications. We hope to reveal the inherent relationship between the precise synthesis of HoMS and its highly tunable compositional and structural characteristics, and point out its future direction to boost HoMS area further. [ABSTRACT FROM AUTHOR]

Aiming at the issue that the noise generated during image acquisition and transmission would degrade the ability of subsequent image processing, a generative adversarial network (GAN) based multi-channel image denoising algorithm was developed. The noisy color image could be separated into red-green-blue (RGB) three channels via the proposed approach, and then the denoising could be implemented in each channel on the basis of an end-to-end trainable GAN with the same architecture. The generator module of GAN was constructed based on the U-net derivative network and residual blocks such that the high-level feature information could be extracted effectively via referring to the low-level feature information to avoid the loss of the detail information. In the meantime, the discriminator module could be demonstrated on the basis of fully convolutional neural network such that the pixel-level classification could be achieved to improve the discrimination accuracy. Besides, in order to improve the denoising ability and retain the image detail as much as possible, the composite loss function could be depicted by the illustrated denoising network based on the following three loss measures, adversarial loss, visual perception loss, and mean square error (MSE). Finally, the resultant three-channel output information could be fused by exploiting the arithmetic mean method to obtain the final de-noised image. Compared with the state-of-the-art algorithms, experimental results show that the proposed algorithm can remove the image noise effectively and restore the original image details considerably. [ABSTRACT FROM AUTHOR]

The high-temperature oxidation of ZrAl2 upon exposure to pure O2 at 800–950 °C was studied in terms of the oxidation kinetics and the formation mechanism of the oxide layer. The alloy followed parabolic oxidation kinetics, and the activation energy of oxidation was 239 ± 14 kJ/mol. During the early stages of oxidation below 850 °C, a single-layer oxide formed due to the crystallization of the initially formed amorphous oxide layer. A multilayer oxide structure developed at higher temperatures, due to the slightly higher affinity of oxygen for Zr than for Al and the oxidation-induced compositional changes. [ABSTRACT FROM AUTHOR]

Background: Changes to human body composition reflect changes in health status to some extent. It has been recognized that these changes occur earlier than diseases. This means that a reasonable prediction of body composition helps to improve model users' health. To overcome the low accuracy and poor adaptability of existing human body composition prediction models and obtain higher efficiency, we proposed a novel method for predicting human body composition which uses a modified adaptive genetic algorithm (MAGA). Methods: Firstly, since there are many parameters for a human body composition model, and these parameters are associated, we designed a new parameter selection approach by combining the improved RReliefF method with the mRMR method. Following this, selected parameters were used to establish a model that fits body composition. Secondly, in order to accurately calculate the weight of parameters in this model, we proposed a solution which used a modified adaptive genetic algorithm, taking advantage of both roulette and optimum reservation strategies. This solution also has an improved selection operator. Thirdly, taking the percentage of body fat (PBF) as an example of body composition, we conducted experiments to compare performance between our algorithm and other algorithms. Results: Through our simulations, we demonstrated that the adaptability of the proposed model is 0.9921, the mean relative error is 0.05%, the mean square error is 1.3 and the correlation coefficient is 0.982. When compared with the indexes of other models, our model has the highest adaptability and the smallest error. Additionally, the suggested model, which has a training time of 28.58s and a running time of 2.84s, is faster than some models. Conclusion: The PBF prediction model established by MAGA has high accuracy, stronger generalization ability and higher efficiency, which could provide a new method for human composition prediction. [ABSTRACT FROM AUTHOR]

The crystal phase plays an important role in controlling the properties of a nanomaterial; however, it is a great challenge to obtain a nanomaterial with high purity of the metastable phase. For instance, the large‐scale synthesis of the metallic phase MoS2 (1T‐MoS2) is important for enhancing electrocatalytic reaction, but it can only be obtained under harsh conditions. Herein, a spatially confined template method is proposed to synthesize high phase‐purity MoS2 with a 1T content of 83 %. Moreover, both the confined space and the structure of template will affect the purity of 1T‐MoS2; in this case, this approach was extended to other similar spatially confined templates to obtain the high‐purity material. The obtained ultrathin nanosheets exhibit good electrocatalytic activity and excellent stability in the hydrogen evolution reaction. [ABSTRACT FROM AUTHOR]

The crystal phase plays an important role in controlling the properties of a nanomaterial; however, it is a great challenge to obtain a nanomaterial with high purity of the metastable phase. For instance, the large‐scale synthesis of the metallic phase MoS2 (1T‐MoS2) is important for enhancing electrocatalytic reaction, but it can only be obtained under harsh conditions. Herein, a spatially confined template method is proposed to synthesize high phase‐purity MoS2 with a 1T content of 83 %. Moreover, both the confined space and the structure of template will affect the purity of 1T‐MoS2; in this case, this approach was extended to other similar spatially confined templates to obtain the high‐purity material. The obtained ultrathin nanosheets exhibit good electrocatalytic activity and excellent stability in the hydrogen evolution reaction. [ABSTRACT FROM AUTHOR]

Precisely carving of multi‐shelled manganese–cobalt oxide hollow dodecahedra (Co/Mn‐HD) with shell number up to three is achieved by a controlled calcination of the Mn‐doped zeolitic imidazolate framework ZIF‐67 precursor (Co/Mn‐ZIF). The unique multi‐shelled and polycrystalline structure not only provides a very large electrochemically active surface area (EASA), but also enhances the structural stability of the material. The residual C and N in the final structures might aid stability and increase their conductivity. When used in alkaline rechargeable battery, the triple‐shelled Co/Mn‐HD exhibits high electrochemical performance, reversible capacity (331.94 mAh g−1 at 1 Ag−1), rate performance (88 % of the capacity can be retained with a 20‐fold increase in current density), and cycling stability (96 % retention over 2000 cycles). Me, my shell, and I: A controlled continuous two‐step calcination of the Mn‐doped zeolitic imidazolate framework ZIF‐67 precursor (Co/Mn‐ZIF) gives triple‐shelled manganese–cobalt oxide hollow dodecahedra (Co/Mn‐HD). Co/Mn‐HD has promising electrochemical performance for rechargeable alkaline batteries. [ABSTRACT FROM AUTHOR]

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Ti2AlNb‐based alloys are synthesized by spark plasma sintering from pre‐alloyed and ball‐milled Ti–22Al–25Nb powder, and the structure of the alloys is regulated by aging at 800 °C for 0.5, 1, 2, and 3 h. Comparison of phase composition, microstructure, and mechanical properties are made in this study. Aging in the B2 + O phase region refers to the reversible transformation of B2 ↔ O. Complete B2 + O Widmanstätten structure is obtained in the aged alloys synthesized from pre‐alloyed powder, and the ones from milled powder contain acicular O and B2 + O Widmanstätten structure. Ball milling eliminates the B2 + O colonies, facilitates the continuous transformation of O → B2, and induces acicular O in the alloys; however, the hardness of these alloys is decreased in contrast with that of the ones synthesized from pre‐alloyed powder. Owing to the precipitation strengthening based on a large amount of fine O‐phase precipitates, the 3 h aged alloy from pre‐alloyed powder exhibits comprehensive mechanical properties with Vickers hardness of 448 ± 9 HV, ultimate tensile strength of 730 MPa, and elongation of 0.43%. [ABSTRACT FROM AUTHOR]

TiAlNb-based alloys synthesized at 1223 K (950 °C) by spark plasma sintering were aged at 973 K, 1023 K, 1073 K, and 1123 K (700 °C, 750 °C, 800 °C, and 850 °C), respectively. Phase composition, microstructure, and microhardness of the aged alloys were investigated in this study. Equiaxed O grains and Widmanstätten B2/ β + O laths were formed in the aged alloys, and the microhardness was improved in contrast with the spark plasma-sintered alloy without aging. The microhardness relies largely on the O-phase content, as well as the length and width of the O laths. In particular, complete Widmanstätten B2/ β + O laths, with locally finely dispersed β precipitates, were obtained in the alloy aged at 1073 K (800 °C), and the alloy exhibited the best microhardness performance. Such fine structure is due to the temperature-dependent transformations O→O + B2/ β , O→O + B2/ β , and B2/ β →O. [ABSTRACT FROM AUTHOR]

Data segmentation plays a critical role in performing human activity recognition in the ambient assistant living systems. It is particularly important for complex activity recognition when the events occur in short bursts with attributes of multiple sub-tasks. Although substantial efforts have been made in segmenting the real-time sensor data stream such as static/dynamic window sizing approaches, little has been explored to exploit object semantic for discerning sensor data into multiple threads of activity of daily living. This paper proposes a semantic-based approach for segmenting sensor data series using ontologies to perform terminology box and assertion box reasoning, along with logical rules to infer whether the incoming sensor event is related to a given sequences of the activity. The proposed approach is illustrated using a use-case scenario which conducts semantic segmentation of a real-time sensor data stream to recognise an elderly persons complex activities. [ABSTRACT FROM AUTHOR]

We unambiguously discovered the existence of room-temperature ferromagnetic-like behavior (RTFM) in pure ZnO pellets, which are made from the nanoparticles showing only paramagnetism and diamagnetism. In contrast to previous reports, our systematic work shows that thermal annealing of ZnO at different temperatures can either enhance or reduce ferromagnetic-like ordering regardless of post-treatment in argon and oxygen. After post-annealing under different conditions, the treated pellets show significant and complicated variation in surface configurations, including for example different levels of surface dehydrogenation, carbon adsorption, grain size and Zn/O ratio. The quantitative analysis indicates that the RTFM of ZnO is affected mainly by surface oxygen vacancies and hydrogenation. The observed dependence of intrinsic RTFM on the energy position of the Zn 3d photoemission peak suggests the presence of unpaired electrons leading to vacancy-mediated ferromagnetism. On the other hand, we also found that the RTFM of ZnO can be easily modified by adsorbed species, which give rise to charge-transfer at the surface. Based on this result, we further identified that surface carbon contamination is a potential source for the reported controversies, related to poor reproducibility of experimental results in the area of so-called d0 ferromagnetism. [ABSTRACT FROM AUTHOR]

Hollow microspheres of two bismuth oxychlorides, BiOCl and BiOCl, were successfully synthesized using carbonaceous microsphere sacrificial templates. The phase evolution from BiOCl to BiOCl was easily realized by heating the former at 600 °C. With a uniform diameter of about 200 nm, an average shell thickness of 40 nm, and basic nanosheets of <20 nm, the hollow microspheres of both BiOCl and BiOCl showed high visible light photocatalytic activity towards the degradation of Rhodamine B (RhB). Besides the effective photosensitization process and efficient photointroduced carrier separation, the high photocatalytic activity was believed to result from their hollow-structure-dependent large visible light absorption. Moreover, as a chlorine-deficient analogue, the BiOCl hollow spheres possessed a narrower band gap, more dispersive band structure, and higher photocarrier conversion efficiency, which further helped them to exhibit better photocatalytic activity. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]