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The amorphous formation ability, thermal properties, crystallization behavior, magnetic properties, resistivity and bending ductility of Fe 84.5- x B 12 P 2 C 1 Cu 0.5 Co x (x = 0, 4, 8) alloys were systematically investigated. It is found that the substitution of Fe by Co promotes the transformation of the as-spun alloys from a completely amorphous structure to an amorphous/nanocrystalline dual-phase structure, which is related to the differences in the interactions between the involved atoms. The saturation magnetization of alloys increases with increasing Co content and can be increased to 1.93 T at x = 8 by heat treatment, but excessive substitution of Co for Fe deteriorates the coercivity and bending ductility due to the pre-existing α-Fe(Co) grains. The resistivity is positively correlated with the disorder of structure, and the as-spun alloy with x = 4 exhibits a high resistivity of 136.2 μΩ cm. As a result, the annealed Fe 80.5 B 12 P 2 C 1 Cu 0.5 Co 4 alloy with excellent soft magnetic properties (M s = 1.81 T, H c = 7.8 A/m) and good bending ductility in combination with high resistivity has potential for application in the field of electronic devices. • The crystallization tendency of alloy is enhanced by the substitution of Fe by Co. • The annealed Co4 alloy exhibits an ultrafine nanocrystalline structure. • Co4 alloy combines excellent soft magnetic properties with high resistivity. • Co0, Co4 Alloys exhibit good bending ductility even when annealing at T x1 -60 K. [ABSTRACT FROM AUTHOR]

Because most chickens are reared in intensive farms, where a range of feed additives are used routinely, concerns have been raised on the potential public health risk of chicken product consumption. This study was conducted to characterize the contents of trace metals in fresh chicken tissues (354 samples) on the food markets in Guangdong province of southern China, a major region of chicken production with heavy per capita chicken consumption, and to assess the public health risk from chronic dietary exposure to the trace metals through chicken consumption. With the exception of Cr, Ni, and Pb, the contents of trace metals were generally higher in the chicken giblets (livers, gizzards, hearts, and kidneys) compared to muscles (breasts and drumsticks). Chicken tissues from the urban markets generally contained higher levels of As, Cu, Mn, and Zn than those from the rural markets, while the contents of Pb were typically higher in the chicken muscles from the rural markets. Results of statistical analyses indicate that Cu, Zn, and As in the chicken tissues derived mainly from the feeds, which is consistent with the widespread use of Cu, Zn, and phenylarsenic compounds as feed supplements/additives in intensive poultry farming. No non-carcinogenic risk is found with the consumption of fresh chicken meat products on the food markets, while approximately 70% of the adult population in Guangzhou and 30% of those in Lianzhou have bladder and lung cancer risk above the serious or priority level (10 −4 ), which arises from the inorganic arsenic contained in the chicken tissues. These findings indicate that the occurrence of inorganic arsenic at elevated levels in chicken tissues on the food markets in Guangdong province poses a significant public health risk, thus the use of phenylarsenic feed additives in China's poultry farming should be significantly reduced and eventually phased out. [ABSTRACT FROM AUTHOR]

Graphene oxide supported l -proline (GO–Proline) bifunctional catalyst was prepared by covalent bonds via a succinate spacer. Fourier transform infrared spectrum (FTIR), Raman spectroscopy, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), high-resolution transmission electron microscopy (HRTEM), and X-ray photoelectron spectroscopy (XPS) were employed to characterize the structure and morphology. The characterizations demonstrated l -proline molecules could be readily introduced to the graphene oxide sheets with homogeneous distributions. Systematic studies demonstrated that it was an efficient, recoverable, and recyclable catalyst in the solvent free ketene forming reaction. Effect of different solvents on its catalytic properties was also investigated. [ABSTRACT FROM AUTHOR]

Animal wastes from concentrated animal feeding operations (CAFOs) can cause soil arsenic pollution due to the widespread use of organoarsenic feed additives. This study investigated the arsenic pollution of surface soils in a typical CAFO zone, in comparison with that of agricultural soils in the Pearl River Delta, China. The mean soil arsenic contents in the CAFO zone were elevated compared to those in the local background and agricultural soils of the Pearl River Delta region. Chemical speciation analysis showed that the soils in the CAFO zone were clearly contaminated by the organoarsenic feed additive, p -arsanilic acid (ASA). Transformation of ASA to inorganic arsenic (arsenite and arsenate) in the surface soils was also observed. Although the potential ecological risk posed by the arsenic in the surface soils was relatively low in the CAFO zone, continuous discharge of organoarsenic feed additives could cause accumulation of arsenic and thus deserves significant attention. [ABSTRACT FROM AUTHOR]

• A simple solvent engineering strategy was employed to control morphology of PbI 2 films effectively by water processing. • Platelet-like PbI 2 films can successfully control the residual amount of PbI 2 in perovskite film. • Platelet-like PbI 2 films can control the morphology of the perovskite film and improve the device efficiency [Display omitted] The performance of organic-inorganic perovskite solar cells depends largely on the quality of perovskite film. Currently, various methods are applied to prepare the perovskite film. Among them, the two-step method is counted as a promising candidate to obtain high-quality perovskite film. In this study, we attain a special platelet-like PbI 2 films by applying pure water to cover wet PbI 2 film and standing for a period of time. The unique morphology contributes to the entry of organic cations solution into the PbI 2 and promoting its reaction with PbI 2 , which reducing the residual amount of PbI 2 in the perovskite film. Compared to the traditional two-step method, water processing method can obtain a high-quality perovskite film with enlarged grain size, improved crystallization, and prolonged carrier lifetime. As a result, the efficiency of the prepared device based on the film has increased from 17.90% without water processing to 20.14% of water processing. Which demonstrates that this solvent engineering for PbI 2 film opens up a possibility to prepare high-quality perovskite in a two-step method and obtain highly efficient perovskite solar cells. [ABSTRACT FROM AUTHOR]

• A Pose-Invariant Convolutional Baseline is proposed. • Appearance-Enhanced Feature Learning Network is proposed. • The state-of-the-art results are reported in three Re-ID datasets. Person re-identification (Re-ID) has important practical application value in intelligent video analysis. Due to the illumination, occlusion, and pose variation, person Re-ID is still a challenging problem. Some recent Re-ID methods based on ResNet-50 have achieved high accuracy, but performance degradation is caused by pose variation. To address this issue, Pose-Invariant Convolutional Baseline (PICB) embed with the proposed Pooling Fusion Block (PFB) is put forward as a new baseline for person Re-ID task. On the basis of PICB, an end-to-end network named Appearance-Enhanced Feature Learning Network (AEFLN) is proposed to simultaneously learn diversity body features and discriminative part features. Specially, a novel (DBFL) strategy is presented to learn diversity body features, which could alleviate the potential local minima problem generated by optimizing model with randomly initialized parameters in PFB. In addition, uniform part-level feature extractors are applied to learn part features, which compensates for body features' lack of distinguishable local information. In testing phase, body features and part features are integrated to represent the enhanced appearance feature for each person image. Comprehensive experiments have demonstrated that our method can outperform the sate-of-the-art results on several public available datasets, including Market-1501, CUHK03 and DukeMTMC-reID. For instance, we achieve 74.8% (+11.1%) and 76.5% (+19.0%) in Rank-1 accuracy and mAP on CUHK03 dataset. [ABSTRACT FROM AUTHOR]

It is still a considerable challenge for spinel Li 4 Ti 5 O 12 to achieve high tap density while retaining excellent power capability. Herein, a compact and mesopore-oriented holey-graphene framework (HGF) caging nano-Li 4 Ti 5 O 12 particles (Li 4 Ti 5 O 12 /HGF) is synthesized by capillary shrink effect. In the capillary drying process, nano-Li 4 Ti 5 O 12 particles prevent the absolute aggregation of graphene sheets, remaining mesopore-oriented porosity for rapid Li+ diffusion. After precisely adjusting the porous structure, Li 4 Ti 5 O 12 /HGF composite successfully achieves a balance between tap density and porosity. Furthermore, the in-plane nanopores of holey-graphene sheets provide channels for Li+ diffusion, obviously weakening the Li+ diffusion resistances of compact composite. The resultant Li 4 Ti 5 O 12 /HGF composite combines a high tap density of 1.1 g cm−3 and a moderate mesopore-oriented porosity with BET specific area of 152 m2 g−1, delivering volumetric-specific capacities of 161, 142, 120, 103 mA h cm−3 at 0.035, 1.75, 7 and 14 A g−1, respectively. Even as current density reaches 17.5 A g−1, the as-prepared Li 4 Ti 5 O 12 /HGF composite still displays a capacity of 98 mA h cm−3, showing excellent ultrahigh-rate performance. After 1000 cycles at 7A g−1, the capacity of dense Li 4 Ti 5 O 12 /HGF composite remains 84%, demonstrating high cycle stability. Image 1 • A balance between high tap density and mesopore-oriented structure. • Decreasing Li+ diffusion resistance due to holey-graphene sheets. • Excellent power capability and high cycle stability. [ABSTRACT FROM AUTHOR]

Summary: The condition with recurrence of ameloblastoma in autogenous iliac bone grafts is very rare. This report presents such a case from a 55-year-old female. [Copyright &y& Elsevier]

During tumor development, the tumor itself must continuously generate new blood vessels to meet their growth needs while also allowing for tumor invasion and metastasis. One of the most common features of tumors is hypoxia, which drives the process of tumor angiogenesis by regulating the tumor microenvironment, thus adversely affecting the prognosis of patients. In addition, to overcome unsuitable environments for growth, such as hypoxia, nutrient deficiency, hyperacidity, and immunosuppression, the tumor microenvironment (TME) coordinates angiogenesis in several ways to restore the supply of oxygen and nutrients and to remove metabolic wastes. A growing body of research suggests that tumor angiogenesis and hypoxia interact through a complex interplay of crosstalk, which is inextricably linked to the TME. Here, we review the TME's positive contribution to angiogenesis from an angiogenesis-centric perspective while considering the objective impact of hypoxic phenotypes and the status and limitations of current angiogenic therapies. [Display omitted] • A close interactive link exists between tumor angiogenesis, hypoxia, and TME, collectively promoting tumorigenesis and progression. • Growth factors in the tumor microenvironment are secreted and regulated by various cell types, and a significant correlation exists between their expression levels and hypoxia. • The development of anti-angiogenic therapy is hampered by the lack of accurate biomarkers, the uncertain time window of medication, and the widespread problem of drug resistance. [ABSTRACT FROM AUTHOR]

Automatic image-based weather recognition has a great significance in the practical use of computer visual applications. The weather recognition approaches via multi-task learning obtain the description of weather conditions by jointly tackling weather-cue segmentation task and weather classification task. However, the existing approaches neglect the multiple scales of weather cues, which may decrease the ability to deal with both large and small weather cues in weather-cue segmentation. They also fail to assign appropriate weights, which the multi-task learning for weather recognition relies on, to the two tasks. To address these problems, we propose a novel end-to-end Convolutional Neural Network (CNN)-based Multi-task Weather Recognition Network with multi-scale weather cues (CMWRN). Specifically, in the weather-cue segmentation task, we propose to segment weather cues, e.g. blue sky and black clouds, by capturing multi-scale weather-cue features. Arbitrary-scale weather-cue regions in the outdoor images can be accurately and effectively classified via resampling the weather-cue features at multiple scales. In the weather classification task, a generalized pooling method is introduced to generate more discriminative weather representations. To further promote the weather classification, the multi-scale weather-cue features are exploited to provide weather clues for weather representations. Moreover, we develop an adaptive weighting scheme to automatically balance the weather classification task and weather-cue segmentation task for more effective training. Compared with the state-of-the-arts, experimental results on two public available benchmark datasets demonstrate the superior performance of our approach. • We capture multi-scale weather-cue features for multi-task weather recognition. • A generalized pooling is proposed to generate weather feature representations. • An adaptive weighting scheme is proposed for multi-task weather recognition. • The state-of-the-art results are reported on two weather recognition datasets. [ABSTRACT FROM AUTHOR]

Recently, the progress of electronic devices toward miniaturization has strongly promoted development of multifunctional materials possessing multiple desirable properties. In this study, we develop and fabricate 0.93Bi 0.5 Na 0.5 TiO 3 -0.07BaTiO 3 - x Er multifunctional ceramics which show simultaneously considerable electric-field-induced strain and bright green light emission properties. With the introduction of Er3+, the ceramics gradually transform from non-ergodic relaxor phase to ergodic relaxor phase which could reversibly transform to ferroelectric phase under the electric field. As a result, with improving Er3+ content, the shape of the polarization-electric field loops of the ceramics become pinched, and it is obvious that the negative strain disappears while the positive strain gradually increases and reaches a maximum value 0.46% at x = 1.2 mol%. Besides, After the ceramics are poled, the light emission peak are greatly enhanced attributed to the decreased crystal symmetry and increased domain size, and is the strongest at x = 1.2 mol%. These results indicate that 0.93Bi 0.5 Na 0.5 TiO 3 -0.07BaTiO 3 - x Er ceramics are good candidates for developing multifunctional optoelectronic devices. [ABSTRACT FROM AUTHOR]

With the explosive increase of remote sensing data, how to search for remote sensing data quickly and accurately in a vast dataset is an incredibly critical matter for research subjects. The deep hashing method has become the dominant method for remote sensing image retrieval because of its low-cost storage and high-speed retrieval. However, for the reason of the limitation of fixed convolutional kernels, deep hashing frameworks based on Convolutional Neural Networks (CNNs) fail to obtain the global semantic information well, which leads to the generation of suboptimal solutions. Furthermore, existing hashing methods commonly employ the random sampling strategy or hardest sample mining to build training batches, resulting in bad local minima. To remedy these problems, a novel Deep Global Semantic Structure-preserving Hashing framework via corrective triplet loss (DGSSH) is proposed for remote sensing image retrieval to learn a discriminative and stable embedding space, achieving intra-class confusion and inter-class diversity. Specifically speaking, the feature extraction module based on Swim Transformer architecture is developed to capture global semantic information and multiscale features from remote sensing images. Based on a distribution matching constraint, the corrective triplet loss for deep hashing schemes is designed to reduce the distribution shift caused by the random selection or hardest sample mining. Meanwhile, to reduce the time overhead of the model, the asymmetric learning strategy is employed to perform effective compact representation learning. Numerous experiments have been carried out on three publicly available benchmarks, which indicates that the proposed DGSSH framework could achieve optimal performance for remote sensing image retrieval applications. The source code of our DGSSH framework is hosted at https://github.com/QinLab-WFU/DGSSH.git. • The Swim Transformer architecture is developed to capture global semantic features. • The corrective triplet loss is proposed to reduce the distribution shift. • An asymmetric learning strategy is employed to improve training efficiency. • The state-of-the-art results are reported on three benchmark datasets. [ABSTRACT FROM AUTHOR]

The aspect ratio of nanorods (NR) is polydisperse in the real application which is often omitted in the electrical conductivity. In this work, by adopting a coarse-grained molecular dynamics simulation, the effect of the polydispersity index (PDI) of NRs on the conductive probability of polymer nanocomposites has been investigated in details under the quiescent state and under the shear field which aims to uncover their relationship. By analyzing the conductive network, it is found that the percolation threshold is inversely proportion to the PDI under the quiescent state. On one hand, one long NR can connect more other NRs than one short NR. In addition, more long NRs participate in building the conductive network with the PDI than short NRs, which thus enhances the conductive probability. Compared with in the quiescent state, the percolation threshold is enhanced under the shear field. By characterizing the orientation degree and the connection mode of both long NRs and short NRs, the shear field significantly changes the original conductive network which rationalizes the conductive probability. Interestingly the percolation threshold first increases and then decreases with the shear rate which reaches the maximum value at the intermediate shear rate. At the low shear rate, the initial orientation of NRs induces the breakage of the conductive network perpendicular to the shear direction which improves the percolation threshold. In addition, more short NRs participate in building the conductive network than long NRs with the further increase of the shear rate. Meanwhile more direct contact aggregation structure of NRs appears which induces the recovery of the conductive network. Image 1 [ABSTRACT FROM AUTHOR]

Overcoming the self-corrosion and surface passivation of aluminum anode, and the slow kinetics of cathodic electrochemical reactions are of great significance for the practical application of aluminum–air battery. In this study, we replaced the traditional aqueous electrolyte with AlCl 3 -urea ionic liquid electrolyte, and prepared Co–MnO 2 /C catalysts as cathode catalyst. Structures and electrocatalytic activity of the x % Co–MnO 2 /C (x is the mole percent of Co to Mn, x = 0, 10, 20, 30, 40 and 50) catalysts have been investigated systematically. After Co ions intercalation, the specific surface area of the catalyst increased and average pore diameter decreased. The unique interaction between Co ions and MnO 2 led to an increase in the catalytic activity of the catalyst in the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) compared with MnO 2 /C. In particular, 40% Co–MnO 2 /C showed the largest specific surface area (154.25 m2 g−1) and the smallest average pore diameter (6.47 nm). It showed the most positive half-wave potential (0.727 V vs. RHE) and the biggest limiting current density (4.744 mA cm−2) in ORR process, and also exhibited the lowest onset potential (1.593 V) and the biggest limit current density (15.177 mA cm−2) in OER process. Furthermore, aluminum–air battery assembled with 40% Co–MnO 2 /C demonstrated excellent reversible charge and discharge performance, which had an average discharge voltage of 1.5 V and an average charge voltage of 2 V during 30 cycles at a limited battery capacity of 375 mAh g−1. Our results reveal the possibility of designing a rechargeable aluminum-air battery working at ambient conditions based on the Co–MnO 2 /C air cathode catalyst for the first time. Our work opens up a new way to achieve the rechargeability of aluminum-air batteries, and our highly active electrocatalytic materials can be used in a wider range of electrochemical energy applications. Co–MnO 2 /C catalysts were prepared by intercalating Co ions between MnO 2 layers, the unique interaction between Co ions and MnO 2 led to an increase in the catalytic activity of the catalysts in ORR/OER process compared with MnO 2 /C, and the aluminum–air battery assembled with 40% Co–MnO 2 /C catalyst and AlCl 3 -urea ionic liquid electrolyte demonstrated excellent reversible charge and discharge performance. Image 1 • A novel Co–MnO 2 /C catalyst was successfully prepared by intercalating Co ions between MnO 2 layers. • The unique interaction between Co ions and MnO 2 led to an increase in the catalytic activity of the catalyst. • 40% Co–MnO 2 /C as air cathode catalyst exhibited the best ORR/OER catalytic activity. • A button-type rechargeable aluminum-air battery working at ambient conditions was designed for the first time. • As-prepared aluminum-air battery demonstrated excellent reversible charge and discharge performance. [ABSTRACT FROM AUTHOR]

The tumor microenvironment (TME), the "soil" on which tumor cells grow, has an important role in regulating the proliferation and metastasis of tumor cells as well as their response to treatment. Cancer-associated fibroblasts (CAFs), as the most abundant stromal cells of the TME, can not only directly alter the immunosuppressive effect of the TME through their own metabolism, but also influence the aggregation and function of immune cells by secreting a large number of cytokines and chemokines, reducing the body's immune surveillance of tumor cells and making them more prone to immune escape. Our study provides a comprehensive review of fibroblast chemotaxis, malignant transformation, metabolic characteristics, and interactions with immune cells. In addition, the current small molecule drugs targeting CAFs have been summarized, including both natural small molecules and targeted drugs for current clinical therapeutic applications. A complete review of the role of fibroblasts in TME from an immune perspective is presented, which has important implications in improving the efficiency of immunotherapy by targeting fibroblasts. [Display omitted] • Complex regulatory relationships between fibroblasts and immune cells during metabolism, chemotaxis, and malignant transformation. • Fibroblasts regulate immune cell activity in an environmentally dependent manner. • Natural small molecules targeting CAFs and targeted drugs for current clinical therapeutic applications. [ABSTRACT FROM AUTHOR]

Tumor-associated macrophages (TAMs) are the most critical effector cells of innate immunity and the most abundant tumor-infiltrating immune cells. They play a key role in the clearance of apoptotic bodies, regulation of inflammation, and tissue repair to maintain homeostasis in vivo. With the progression of triple-negative breast cancer（TNBC）, TAMs are "subverted" from tumor-promoting immune cells to tumor-promoting immune suppressor cells, which play a significant role in tumor development and are considered potential targets for cancer therapy. Here, we explored how macrophages, as the most important part of the TNBC ecosystem, are "subverted" to drive cancer evolution and the uniqueness of TAMs in TNBC progression and metastasis. Similarly, we discuss the rationale and available evidence for TAMs as potential targets for TNBC therapy. [Display omitted] • An exploration of how macrophages are gradually being "subverted" to drive cancer evolution. • The uniqueness of TAMs in TNBC progression and metastasis was elucidated. • The rationale and available evidence for TAMs as potential targets for TNBC treatment are detailed. • The co-dependence of TAMs on tumor evolution was explored from the perspective of co-evolution of TAMs and TNBC ecosystem. • It is helpful to optimize the current treatment plan of TNBC. [ABSTRACT FROM AUTHOR]